Journal of Experimental Botany

Raines, Christine

doi: 10.1093/jxb/erl041pmid: N/A

Two major areas in the field of plant research have been, and continue to be, development and metabolism. However, little attention has been paid to the potential role of primary metabolism in determining and/or modulating plant development. Recently, a number of papers have been published providing clear evidence of links between the modulation of plant development and leaf carbon metabolism. To highlight this, and to bring together researchers from both the development and metabolism research areas, a session on Leaf Metabolism and Development was held at the Society for Experimental Biology Annual Meeting in Barcelona, Spain, in July 2005. The four focus papers in this issue of the Journal of Experimental Botany were invited contributions from this session and will hopefully provide some insight into this emerging area. I would like to thank the Journal of Experimental Botany and the Society for Experimental Biology for financial support for this session. Thanks also to the editorial staff at the Journal of Experimental Botany; Mary Traynor, Jane Basterfield, Raquel Gonzalez Cuesta, and Pam Rogers. Published by Oxford University Press [2006] on behalf of the Society for Experimental Biology

Whittle, C-A;Johnston, MO

doi: 10.1093/jxb/erj155pmid: 16687435

Abstract Currently, the types of factors that impact the mutation rate is a controversial issue. The marked attention towards identifying the factors that impact the genomic mutation rate is justified because mutations are the source of genetic variation underlying evolution and because many mutations have deleterious effects and can cause diseases. Although data showing correlations between germ cell division number and mutation rates (from epidemiological studies and molecular evolutionary rate analyses) have suggested that most mutations in animals are replication errors, this notion is highly debated and inconsistencies in the correlations suggest that other, replication-independent factors, could play an important role. Likely candidates include environmental parameters and cell age, but these issues have proved to be difficult to study using animals and in vitro systems, and consequently, very few or no data currently exist. The specific features of plants that make them powerful model systems for revealing the influence of the environment (natural environmental factors) and cell age on the spontaneous genomic mutation rate are discussed here. Overall, the evidence suggests that plants could be key biological systems for advancing our knowledge about how and why heritable mutations arise. Cell age, environment, genomic mutation rate, model system, plants Introduction Given that the genomic mutation rate plays a critical role in many evolutionary processes, for example evolution of mating systems, sex, ploidy levels, Y chromosomes, and species extinctions (Charlesworth and Charlesworth, 1998; Kondrashov, 1998), and that many mutations cause diseases, it is of broad scientific interest to determine the factors that influence the rate of mutation. Currently, however, much remains unknown. Findings of correlations between the number of germ cell divisions (DNA replication) and mutation rates in humans and other organisms suggest that most germ line mutations are replication errors. Specifically, human epidemiological data and/or nucleotide substitution rates of selectively neutral DNA (which equals the mutation rate, Kimura, 1983; Miyata et al., 1987) have shown that more mutations occur in the male than in the female germ line for numerous animal taxa (e.g. humans, mice, chickens, and sheep) and in older rather than younger human males, patterns that each agree with the cell-division hypothesis (i.e. more DNA replications in males and in particular older males; Penrose, 1955; Risch et al., 1987; Becker et al., 1996; Moloney et al., 1996; Li, 1997; Green et al., 1999; Crow, 2000; Li et al., 2002; Makova and Li, 2002). Other data, however, have indicated that the mutation bias reported relative to gender and male age are not generally well correlated with the number of germ cell divisions and that other factors could explain these trends, such as methylation patterns, differential repair, metabolic rates, and preferential transmission of mutations to progeny from older males (Risch et al., 1987; Martin and Palumbi, 1993; Drost and Lee, 1995; Bromham et al., 1996; Hurst and Ellegren, 1998; Martin, 1999; Crow, 2000; Huttley et al., 2000; McVean, 2000; Sommer et al., 2001; Hebert et al., 2002; Hurst and Ellegren, 2002; Kumar and Subramanian, 2002; Li et al., 2002; Bartosch-Harlid et al., 2003). Regardless of whether one is, at present, more convinced by one argument or the other, it is apparent that most information about the factors that underlie spontaneous mutation rates has been limited to the detection of the presence or absence of correlations between the numbers of germ cell divisions and mutation rates. It is thus evident that further empirical data are needed regarding the relationship between replication-independent factors, such as environmental parameters and cell age, and the mutation rate. A first step in making progress on this issue is to consider why so few data currently exist. The challenges in assessing the impact of environmental parameters and cell age on genomic mutation rates using the relatively conventional in vitro and animal-based systems are described here and the innate advantages of plants for such research are highlighted. Plausible reasons for the lack of data Poor suitability of in vitro research To date, most quantitative mutagenesis research has largely been based on in vitro analysis of bacteria, yeast, and isolated animal cell lineages. Although such research has played a critical role in current understanding of the mechanisms of mutation, including the molecular pathways involved in DNA damage and repair (Wabl et al., 1987; Rudd et al., 1990; Boesen et al., 1994; Friedberg et al., 1995; Miller, 1996; Bridges, 1997; Drake et al., 1998; Yang et al., 2004), it is generally not likely to reflect the types of parameters that impact the spontaneous in vivo mutation rate, which is most relevant for evolutionary and disease-related issues. This is because (i) few, if any, organisms in nature are subjected to the near homogenous and narrow environmental/growth conditions provided in vitro; (ii) most species are dependent on organism- level factors, not existing as isolated cell lines (Bridges, 1997); (iii) in vitro mutation rates have proved to be poor indicators of in vivo rates, even within a single species and thus are not likely to be effective models systems for mutational processes inherent to other organisms (Drake, 1991; Bridges 1997); and (iv) in vitro cells, can turn over in a single hour or day (Cullum and Vicente, 1978; Kuick et al., 1992), and thus, do not reflect the fact that most cells in nature, including those of bacteria, yeast, animals, and plants, are non-dividing for most of their lifespan (Loewe et al., 2003) [The human oocyte, for example, spends its entire lifespan, often decades, in the resting stage (Drost and Lee, 1995; Crow, 2000) while the male germ cells also spend substantial periods in the resting stage, with about one cell division per month on average, representing marked resting periods (Crow, 2000)]. With regard to the study of cell ageing, there are the additional difficulties in detecting mutations in non-dividing in vitro cells, as this process requires artificially imposed impediments to cell division (making it difficult to isolate replication-independent effects on mutation), and cloning, which inherently entails high numbers of cell divisions (DNA replications; Bridges, 1997; Heddle, 1998). In summary, in vitro analysis is not likely to represent the impact of environmental parameters or cell age on the spontaneous genomic mutation rate and thus has limited implications for this issue. In vivo research of mutation rates is challenging in animals Similar to in vitro analysis, there are innate challenges to investigating the impact of environmental parameters and cell age on the mutation rate in vivo in animal model systems. In particular, each of the main approaches to examine genomic mutation rates in animals, namely molecular evolutionary rate analysis, epidemiology, and short-term experimentation (Drake et al., 1998) is poorly suited to detecting these types of cause–effect relationships (Table 1). In terms of the impact of environmental parameters on mutation rates, for example, molecular evolutionary rate analysis and epidemiology are each unlikely to be effective for this purpose given that most animals are highly mobile, and that specific growth conditions/agents are likely not to be consistent enough to have a detectable impact, particularly for parameters that have a moderate or mild impact. Experimental methods, including mutation accumulation and observation of visible mutants, are challenged by the difficulty in quantifying the rate of spontaneous mutations in vivo over the time-course of an experiment (given the mutation rate is so low; for example 0.16 and 0.49 total mutations/genome/cell division in mice and humans, respectively, Drake et al., 1998), especially when assessed relative to a gradient of external environmental conditions. Another contributing factor is that there are very few animal taxa appropriate for experimental manipulation (Table 1). Similar to environmental parameters, there are innate challenges for the study of cell age in animal systems. Specifically, mutation-rate estimates obtained from molecular evolutionary rate analysis, epidemiology, and/or experimental methods, can generally only provide rates per generation (i.e. mutation rates per cell division are determined by dividing these values by the number of germ cell divisions per generation), and thus, do not provide any insight regarding the impact of replication-independent events including cell ageing (Drake et al., 1998; Lewis, 1999). Furthermore, germ line development has been described in only a very few animal species, making it difficult to conduct interspecies comparisons of the mutation rates of taxa that have germ cells with longer versus shorter periods of rest (non-dividing). This difficulty is confounded by the fact that there is no obvious benchmark for making comparisons of the impact of cell age among species. The average germ cell age across the germ line, for example, is not likely to represent the effects of ageing as specific stages with a particularly long resting stage are likely to have a greater impact than the average (age-related DNA damage per unit time is proportionally higher as cell age progresses; Sommer et al., 2001). Short-term experimental approaches to the study of cell age are also challenged by the difficulty in measuring the mutation rate within a single resting cell (or a series of cells relative to time), and thus, such approaches have generally been limited to the examination of the onset of chemically induced mutations at different stages of male germ line development (as determined by its correlation to the time in the individuals development) or the study of the gametogenesis stage (Allen et al., 1995; Lewis, 1999; Russell, 2004). Altogether, the obstacles inherent to in vitro and in animal-based approaches likely explain the current absence of data regarding the impact of environmental parameters and cell age on the mutation rate. Other biological systems and approaches thus need to be explored. Table 1 Summary of challenges to assessing the impact of environmental parameters and cell age on the mutation rate using in vitro and animal-based research Scientific approach  Basis of challenge  Resulting limitation(s) for determining the cause(s) of mutations  Environmental factors      Molecular evolutionary rates  Mobility of animals  Mobility makes it unlikely that any parameter/agent that may alter the mutation rate (in the short term) will have a detectable impact on nucleotide substitution.  Epidemiology  Determining causation  Innate difficulty in determining the level of exposure to the parameter/agent of interest, identifying and distinguishing between confounding factors, and discerning the effects at mild or moderate dosages (Smith and Phillips, 1992; Smith, 2001).  Experimentation  Logistical  Few animal species are appropriate for in vivo research on effects of environmental stresses.    Low response  Many environmental parameters have a subtle, and thus undetectable, effect on the spontaneous mutation rate over a single or few generations.    Mutation rate estimation  General difficulty in measuring mutation rates in the short term as they are very low (Drake et al., 1998).  Cell age      Molecular evolutionary rates  Few species with germ lines characterized  Comparison of mutation between species with short versus long resting stages in the germ cells is not possible (Vogel and Natarajan, 1995).    No benchmark for age-based comparisons  The average germ cell age, for instance, is unlikely to be an effective standard for age-based comparisons across the germ lines among species because germ cells with particularly protracted resting periods are likely to have a far greater impact than the average (Sommer et al., 2001). No means to isolate impact of cell ageing from replication-dependent mutations within the male or female germ line in estimates of mutation rates per generation.  Epidemiology  Isolating impact of cell age  Epidemiology generally provides no information about what stages of germ line development spontaneous mutations arise, and thus it cannot be determined whether more/fewer mutations arise during stages with extended resting periods. Although the germ line stages in which mutations occur can sometimes be inferred from the pattern of mutations in F1 and F2 progeny, this is rarely achieved and is generally speculative (Lewis, 1999).  Experimentation  Isolating impact of cell age  In vivo experimental studies have primarily been limited to mice and are challenged by the inability to determine the stage of germ line development where mutations arise, and therefore, whether they occur in stages with extended resting periods (Lewis, 1999).  Scientific approach  Basis of challenge  Resulting limitation(s) for determining the cause(s) of mutations  Environmental factors      Molecular evolutionary rates  Mobility of animals  Mobility makes it unlikely that any parameter/agent that may alter the mutation rate (in the short term) will have a detectable impact on nucleotide substitution.  Epidemiology  Determining causation  Innate difficulty in determining the level of exposure to the parameter/agent of interest, identifying and distinguishing between confounding factors, and discerning the effects at mild or moderate dosages (Smith and Phillips, 1992; Smith, 2001).  Experimentation  Logistical  Few animal species are appropriate for in vivo research on effects of environmental stresses.    Low response  Many environmental parameters have a subtle, and thus undetectable, effect on the spontaneous mutation rate over a single or few generations.    Mutation rate estimation  General difficulty in measuring mutation rates in the short term as they are very low (Drake et al., 1998).  Cell age      Molecular evolutionary rates  Few species with germ lines characterized  Comparison of mutation between species with short versus long resting stages in the germ cells is not possible (Vogel and Natarajan, 1995).    No benchmark for age-based comparisons  The average germ cell age, for instance, is unlikely to be an effective standard for age-based comparisons across the germ lines among species because germ cells with particularly protracted resting periods are likely to have a far greater impact than the average (Sommer et al., 2001). No means to isolate impact of cell ageing from replication-dependent mutations within the male or female germ line in estimates of mutation rates per generation.  Epidemiology  Isolating impact of cell age  Epidemiology generally provides no information about what stages of germ line development spontaneous mutations arise, and thus it cannot be determined whether more/fewer mutations arise during stages with extended resting periods. Although the germ line stages in which mutations occur can sometimes be inferred from the pattern of mutations in F1 and F2 progeny, this is rarely achieved and is generally speculative (Lewis, 1999).  Experimentation  Isolating impact of cell age  In vivo experimental studies have primarily been limited to mice and are challenged by the inability to determine the stage of germ line development where mutations arise, and therefore, whether they occur in stages with extended resting periods (Lewis, 1999).  View Large Opportunities in plants Although plants differ markedly from animals, most apparently in their development (including the lack of separation of the germ line and soma in plants) and cellular structure, they have consistently served as key model systems for the discovery of fundamental genetic processes inherent to all eukaryotes. Plants, for example, were the first to reveal the laws of genetics, the existence of transposable elements, and the ability to clone multicellular organisms (from a single somatic cell). Moreover, plant research has greatly contributed to our understanding of many genetic processes such as gene silencing, chromosome structure, and gene function (Table 2). The effectiveness of plant model systems for this purpose is probably attributable to the many genetic-based commonalities among eukaryotes, including genome organization and structure (Heslop-Harrison, 2000; Mayr et al., 2003), mechanisms and types of DNA damage, DNA repair and mutation (e.g. dimer bypass; Friedberg et al., 1995; Britt, 1996, 1999), processes of DNA replication and repair (Britt, 1999) and molecular pathways involved in DNA damage-induced cell cycle regulation and arrest (Huntley and Murray, 1999; Stals and Inzé, 2001; Vazquez-Ramos and Sanchez, 2003), mitosis (Criqui and Genschik, 2002), and cell-to cell interaction (Becraft and Freeling, 1992). Given the proven effectiveness of plants as model systems for genetics research for eukaryotes, they are an obvious alternative to be considered for the further study of the role of environmental parameters and cell age on the genomic mutation rate. Table 2 (a) Examples of major discoveries in genetics originating from plants. (b) Examples of genetic principles and processes that has been advanced by research in plants (a) Discovery originating from plants  Species  Later reported in:  Laws of genetics  Peas (Pisum sativum), Mendel, 1865  All living organisms  Transposable elements  Maize(Zea mays), McClintock, 1951  Most organisms, e.g. DrosophilaPimpinelli et al., 1995, Kidwell and Lisch, 1997  Post-transcriptional gene-silencing  Petuna (Ruelia spp.), Napoli et al., 1990; Van der Krol et al., 1990  Taxa of the animal kingdom, such as C. elegans    Fire et al., 1998, Plasterk, 2002  Paramutation  Maize, Brink, 1956; Stam et al., 2002  Other eukaryotes, e.g. mice      Herman et al., 2003  Activity of catalytic viroids  Potato, Diener, 1971  Humans, underlies the Hepatitis D      Branch et al., 1993  Successful cloning of an individual from an somatically differentiated adult cell  Carrot (Daucus carota), Steward et al., 1958  Sheep and others    Campbell et al., 1996, Wilmut et al., 1997  Discovery originating from plants  Species  Later reported in:  Laws of genetics  Peas (Pisum sativum), Mendel, 1865  All living organisms  Transposable elements  Maize(Zea mays), McClintock, 1951  Most organisms, e.g. DrosophilaPimpinelli et al., 1995, Kidwell and Lisch, 1997  Post-transcriptional gene-silencing  Petuna (Ruelia spp.), Napoli et al., 1990; Van der Krol et al., 1990  Taxa of the animal kingdom, such as C. elegans    Fire et al., 1998, Plasterk, 2002  Paramutation  Maize, Brink, 1956; Stam et al., 2002  Other eukaryotes, e.g. mice      Herman et al., 2003  Activity of catalytic viroids  Potato, Diener, 1971  Humans, underlies the Hepatitis D      Branch et al., 1993  Successful cloning of an individual from an somatically differentiated adult cell  Carrot (Daucus carota), Steward et al., 1958  Sheep and others    Campbell et al., 1996, Wilmut et al., 1997  (b)    Genetic principles and molecular processes aided by plant research  Citation  Genome structure  Meinke et al., 1998  Genes involved in genome maintenance, DNA repair and mutagenesis  Hays, 2002  Mechanisms of genome duplication and polyploidy  Chen et al., 2004a, b  Structure and function of centromeres  Copenhaver, 2003  Molecular structures of proteins such as those inherent to hemoglobins  Kundu et al., 2003  Molecular mechanisms of virulence of human/animal pathogens  Prithiviraj et al., 2005  Gene silencing  Meyer, 2000  (b)    Genetic principles and molecular processes aided by plant research  Citation  Genome structure  Meinke et al., 1998  Genes involved in genome maintenance, DNA repair and mutagenesis  Hays, 2002  Mechanisms of genome duplication and polyploidy  Chen et al., 2004a, b  Structure and function of centromeres  Copenhaver, 2003  Molecular structures of proteins such as those inherent to hemoglobins  Kundu et al., 2003  Molecular mechanisms of virulence of human/animal pathogens  Prithiviraj et al., 2005  Gene silencing  Meyer, 2000  View Large Environmental parameters One of the most apparent benefits of plants for revealing the impact of environmental parameters on the genomic mutation rate is that they are sessile organisms, and thus, are forced to endure their localized growth conditions. Specifically, because plants cannot escape their localized conditions, their environmental conditions are more likely to be consistent over the long term. This would act to enhance the relationship between mutation rates and environmental parameters, and improve the ability to detect their impact using experimental approaches and molecular evolutionary rate analysis. In addition to their sessile nature, the detection of natural environmental mutagens is also facilitated by the presence of indeterminate growth in plants (Gill and Halverson, 1984; Klekowski, 1998). As a result of this growth pattern, plants, unlike most organisms, are able to transmit mutations that arise in the soma to successive generations. In turn, because the soma in plants is constantly subjected to localized growth conditions, including topical (e.g. irradiation, UV, humidity) and soil-based agents (e.g. nutrients, water, minerals) as well as biotic agents (e.g. pathogens; Lucht et al., 2002; Kovalchuk et al., 2003), and because these mutations can be inherited by offspring, the effects of environmental agents on the mutation rate may be more readily evident in these than in other organisms using both molecular evolutionary analysis and experimental approaches. Plants should therefore be especially suitable for studying effects of environmental factors on mutagenesis where these factors are localized and consistent, and thus, reveal important factors affecting mutation rates in eurkaryotes. Although the impact of certain environmental agents will have plant-specific effects due to their distinct growth pattern, this is likely to be relatively rare given the fundamental nature of mutation. Notably, such mutation rate differences between plants and animals (relative to the environment), even when detected, would act to assist in revealing how and why environmental parameters influence the mutation rate. Another highly valuable feature of plants for the study of environmental parameters is that, unlike animals, associations between environmental parameters and in vivo mutation rates can be readily detected using highly sensitive bioassay systems. Plants have consistently shown superior sensitivity (lower doses) and reliability (fewer false negatives) as environmental bioindictors than the comparable bacterial and mouse-based (in vivo and in vitro) systems (Heslop-Harrison, 1978; Zing and Zhang, 1990; de Serres, 1992; Grant, 1994, 1998, 1999; Rodrigues et al., 1997; Kovalchuk et al., 2001). For example, Tradescantia spp, have been used to detect ambient levels of natural conditions/agents such as irradiation, UV-B, temperature changes, and ozone (sensitivity is also demonstrated by the detection of extremely low doses of anthropogenic agents in the soil, water, and air; Grant, 1992, 1998; Ichikawa, 1992; Rodrigues et al., 1996, 1997; Wang and Wang, 1999; Klumpp et al., 2004). Mutations can be readily observed through the observation of changes in flower colour (stamens) throughout the soma (based on the expression recessive mutations at a gene for flower colour in heterozygous plants) and chromosomal aberrations (micronuclei in the meiotic pollen mother cells (Rodrigues et al., 1997; Grant, 1998; Wang and Wang, 1999). These plant systems serve as a quick and effective means to identify those environmental parameters (non-anthropogenic) that have the potential to alter the in situ genomic mutation rate. In addition to these bioassay systems, plant species of many genera including Allium, Arabidopsis, Crepis, Glycine, Hordeum, Nicotiana, Solanum, Rhizophora, and Pisum, can and have been widely utilized for the detection of environmental mutagens (e.g. ozone, alkylating agents) based on chlorophyll mutation assays, pollen abortions, recessive visible mutations at heterozygous loci, chromosomal aberrations in root tips, and/or analysis of genetic markers (Stadler, 1930; Rodrigues et al., 1996, 1997; Grant, 1998, 1999; Kovalchuk et al., 2000; Proffitt and Travis, 2005). Overall, these highly sensitive and established systems provide an effective means to identify naturally occurring environmental parameters/agents (through experiments relative to environmental gradients) that have the ability to alter the in vivo mutation rate that is not as readily available for other organisms. In this regard, they could be key players in the determination of which environmental parameters are likely to have an impact on mutation rates among eukaryotes and thus to provide direction for future studies. Moreover, the wide array of mutants available in plants, particularly in Arabidopsis thaliana, could play a key role in the identification of genes and molecular pathways associated with environmentally induced mutations (Rhee et al., 2003). It should be noted that, in addition to the identification of environmental parameters that could alter the in vivo genomic mutation rate, plants also offer the opportunity to reveal whether environmental fluctuation has an impact. Evidence indicates that this could be the case. A study of the impact of climatic conditions on the effectiveness of the Tradescantia bioassays, for example, incidentally revealed that high levels of temperature fluctuation have a greater impact on the in vivo mutation rate and the level of DNA damage (both with and without the anthropogenic mutagen) than specific high or low temperatures (Klumpp et al. 2004). In addition, plant systems could also reveal whether environmental parameters and/or fluctuations interact and influence the in vivo mutation rate. This has been suggested to be the case by the enhanced mutagenic activity of anthropogenic agents under low-humidity conditions in Tradescantia (Takahashi and Ichikawa, 1976; Klumpp et al., 2004). Unlike animals, where in vivo experimentation relative to environmental fluctuation is not appropriate and/or possible for most species, plants could reveal important patterns in the relationship between environment and mutation rates. Age-related factors In contrast to in vitro and animal-based research, where the study of cell age on spontaneous mutation rates is impeded by challenges in the quantification and manipulation of the duration of the resting stage of cells, plants provide a readily utilizable system for the investigation of age-related mutation. Specifically, embryo cells within plant seeds are non-dividing and are maintained in the G0/G1 stage of the cell cycle for extended time periods (Georgieva et al., 1994; Whittle et al., 2001; Vazquez-Ramos and Sanchez, 2003). The duration of the resting stage may thus be readily manipulated in seeds, allowing a means to assess the physiological and genetic impact of cell age on in vivo DNA damage and the onset of mutations. In this regard, plant seeds represent a naturally existing biological system where the impact of cell ageing on the rate of mutation can be readily studied. Although a substantial argument has been made for the notion that many mutations in animals are replication errors (Crow, 2000), the evidence available to date from seed embryos indicates that significant levels of mutations result from age-related, replication-independent, events. Analysis of evolutionary rates of selectively neutral DNA among plant taxa, for example, has shown that nucleotide substitution rates at silent sites are higher for taxa with persistent (long-term) than transient (short-term) seedbanks, suggesting that more heritable base substitution mutations occur per unit time during seed (cell) ageing than during the lifetime of the plant (wherein the meristematic regions are constantly undergoing replication; Whittle and Johnston, 2006). In addition, there is increased variation in AFLPs and other genetic markers in naturally aged rye (Secale cereale) seeds that are inherited by the progeny for at least three generations (Chwedorzewska et al., 2002a, b). Individuals produced from older seeds have also been shown to contain higher levels of chromosomal and/or gene mutations in Crepis (Gerassimova, 1935), Zea mays (Peto, 1933), and Triticum (Floris and Melletti, 1972) and to have a higher frequency of pollen abortions, an indicator of lethal mutations (in haploid cells) in Datura (i.e. pollen abortion increases from one to more than 8% over 10 years; Cartledge and Blakeslee, 1934). It is thus evident that cell age plays a prominent role in determining the mutation rate in plants. Although these trends could be plant-specific, it seems unlikely given the fundamental genetic-based similarities between plants and other multicellular eukaryotes, and the fact that most other organisms have extended resting periods in the majority of their cells, including animal germ lines. Given the relative ease of study of plant seeds, compared with in vivo animal and in vitro systems, they offer valuable opportunities for better understanding the basic mechanisms underlying age-related mutations. In addition to understanding quantitative relationships between cell age and mutation rate, seeds also offer a readily utilizable means to assess why age-related mutations arise. Data obtained to date from plant seeds suggest that the age-related mutations could be caused by DNA replication across strand breaks and chromosomal aberrations, which have been found to accumulate in embryonic cells over time (with older embryos having a greater proportion of cells with damage and higher levels of damage per cell; Cheah and Osborne, 1978), and/or from the impairment of the DNA replication or repair machinery. It has been shown that older seeds also have a lower RNA and protein content (suggesting substantial degradation; Begnami and Cortelazzo, 1996; Reuzeau and Cavalie, 1997), reduced ability to translate RNA (Reuzeau and Cavalie, 1997), lowered activity of enzymes (Basavarajappa et al., 1991) such as RNA poly (A) polymerase (Grilli et al., 1995; Reuzeau and Cavalie, 1997), each of which might negatively influence the level and/or activity of molecules involved in DNA replication and repair. In this regard, seeds provide an effective system to assess the changes in the DNA (DNA damage), cell physiology, and gene expression, that are associated with age-related mutations. Estimates of mutation rates may also be obtained using genome-wide approaches such as mutation accumulation (where changes in fitness are believed to be proportional the mutation rate, Drake et al., 1998). For example, one may develop mutation accumulation lines (as has already been achieved in A. thaliana; Schultz et al., 1999; Shaw et al., 2000), where the seeds are aged between generations, and subsequently estimate the genomic mutation rate per generation as well as the proportion of the mutation rate that can be attributed to ageing (either based on fitness assays or from direct measurement of mutations using molecular mutation detection techniques; Del Tito et al., 1998). Given that the impact of seed ageing may depend on moisture and temperature conditions (Sivritepe and Dourado, 1998) such studies will need to be conducted under various natural and experimental environmental conditions to ascertain any possible differential effects. It is notable that the effectiveness of seeds for mutation research has been well established by the fact that they have been utilized in extensive mutagenesis studies, including ionizing radiation, UV, and ethyl methanesulphonate (EMS), which has led to the identification of genes and the mechanisms involved in DNA repair in plants (Britt, 1996; Preuss and Britt, 2003). Conclusions Much currently remains unknown about how and why mutations arise. In particular, there is a notable gap in the available data regarding the role of environmental parameters and cell ageing on the onset of mutations. The reasons why plants could be a more productive biological system than bacterial, yeast, and animal systems to advance our current understanding of the role of these factors on the mutation rate have been highlighted here. Although aspects of such research will be plant specific, it is likely given the fundamental nature of mutation, that such investigations will, at a minimum, provide insight into the types of environmental parameters that need to be further evaluated in other eukaryotes, the potential impact of cell ageing on the mutation rate, and the basic cellular events correlated to environmental and age-related mutagenesis. Overall, given the relative experimental advantages of plants, including low cost, ready availability, no ethical concerns regarding treatment, and their often short generation times, plus their innate benefits for the study of environmental parameters and cell age, it is believed that they will be powerful model systems for making advances in current understanding of how and why mutations arise. The authors thank Dr SP Otto for reviewing the manuscript. This work was supported by an NSERC PDF to C-AW, an NSERC Discovery Grant to MOJ, and by an NSERC Discovery Grant to Dr SP Otto. 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Raines, CA;Paul, MJ

doi: 10.1093/jxb/erl011pmid: 16714302

Abstract Considerable effort has been expended on understanding the genetic networks that regulate leaf development and morphology, however, less attention has been given to the role of leaf carbon status in modulating the plant developmental programme. Unexpected changes in plant development have been observed in response to changes in leaf metabolism. The focus of this review will be to discuss how manipulation of leaf carbon metabolic pathways, such as the photosynthetic carbon reduction cycle and trehalose biosynthesis, has provided insights into links between metabolism and development. Carbon metabolism, leaf development, leaf morphology, phenotypic plasticity, regulation Introduction The primary role of the plant shoot is to produce leaves to capture light energy and to convert this to sugars in the process of photosynthesis. During seedling development leaves are produced from primordia generated by the shoot apical meristem. As the young seedling progresses from the juvenile vegetative phase, through the mature vegetative, to the reproductive stage, changes in leaf shape and size occur. These processes are under the control of an endogenous developmental programme and a number of the genes involved have now been identified (Poethig, 1990, 2003; Piazza et al., 2005). In addition to endogenous genetic mechanisms, shoot and leaf morphology is also modulated by environmental factors such as daylength and light availability (Björkman, 1981; Evans, 1996; Evans and Poorter, 2001; Adams and Langton, 2005; Kozuka et al., 2005). Changes in leaf and shoot morphology have been observed in transgenic plants with altered leaf metabolism suggesting that the plant developmental programme can be modulated by the metabolic status of the leaf. As yet the mechanism(s) that are involved in mediating these changes in growth and development in response to changes in metabolism have not been identified. However, some insight into the way in which leaf metabolism affects the plant developmental programme is now emerging. The main focus of this review will be to summarize the impact of transgenic changes in photosynthetic carbon fixation and trehalose metabolism, on leaf and shoot development and to discuss the mechanisms that may be responsible for this. Dramatic and unexpected leaf phenotypes have occurred in response to relatively minor changes in leaf metabolism other than photosynthesis and selected examples are presented to demonstrate the link between metabolic process in plants and development. Effect of manipulation of photosynthetic carbon fixation Optimizing photosynthetic carbon assimilation with the environment plays a crucial role in determining fitness and survival. Studies of biodiversity have shown that the relationship between photosynthetic capacity of leaves and investment of biomass in leaf area is conserved across species (Reich et al., 1997). This would suggest that plants have evolved mechanisms to ensure co-ordination of leaf development with metabolism. Given that photosynthesis in mature source leaves determines the availability of carbohydrate essential for plant growth, it is likely that products of primary metabolism may also play a role in mediating development. The first enzyme in the Calvin cycle to be studied using antisense technology was Rubisco. Antisense Rubisco plants with reductions in photosynthesis accumulated less carbohydrate, resulting in changes in the root-to-shoot ratios and specific leaf area (specific leaf area (SLA) defines leaf area per unit of leaf carbon mass (m2 kg−1) (Quick et al., 1991; Fichtner et al., 1993; Stitt and Schulze, 1994). Indeed, a near linear relationship between photosynthetic rate, starch levels, and SLA over a wide range of reductions in Rubisco activity was observed (Fichtner et al., 1993). Interestingly, the decrease in carbohydrate availability seen in the Rubsico antisense plants also caused a delay in the normal timing of developmental events. The leaves produced on the shoots of plants in the juvenile phase of development are smaller and simpler than those of the adult plant and the Rubisco antisense plants continued to produce this type of leaves until node 11, in contrast with the wild-type plants which had adult leaves by node 8 (Tsai et al., 1997). This suggested that these plants had an extended period in the juvenile vegetative phase. Increased leaf longevity was also observed, suggesting that senescence was delayed in the antisense Rubisco plants (Tsai et al., 1997; Miller et al., 2000). These results provided the first evidence that reductions in photosynthetic carbon assimilation, resulting in reduced availability of carbohydrate (source strength), not only had an impact on plant yield but also played a role in modulating the developmental programme of the shoot. The only confounding factor in these studies is that the antisense plants used only had 20% of the wild-type Rubisco activity and, as a consequence, large changes in nitrate and the nitrogen status of the leaves as Rubisco constitutes approximately 25% of leaf protein. This raises the possibility that the changes in development observed in the anitsense Rubisco plants were due not only to an altered carbon status but that changes in N status may also be having an impact (Masle et al., 1993; Fichtener et al., 1993). By contrast to Rubisco the enzyme sedoheptulose-1,7-bisphosphatase (SBPase: EC 3.1.3.37) accounts for less than 1% of leaf protein, therefore antisense down-regulation of this enzyme would not lead to large perturbations in nitrogen balance and hence direct effects of photosynthesis on leaf development could be examined. SBPase functions in the regenerative phase of the Calvin cycle where it catalyses the dephosphorylation of sedoheptulose-1,7-bisphosphate. Transgenic tobacco plants with small reductions in SBPase activity were found to have decreased rates of photosynthetic carbon fixation (Harrison et al., 1998, 2001; Olcer et al., 2001). Analyses of the SBPase antisense plants revealed that small changes in photosynthesis resulted in a reduction in starch accumulation in the source leaves and changes in leaf and shoot development (Lawson et al., 2006). As with the Rubisco antisense plants, a change in SLA was evident in the SBPase antisense plants, but no delay in the development of the juvenile phase of vegetative growth was seen. What was interesting about the impact of reduced SBPase activity was that growth showed a bimodal response to reductions in SBPase activity (Lawson et al., 2006). Antisense plants with small reductions in SBPase activity and, concomitantly, small decreases in the end of day levels of starch, were shorter and produced smaller, thicker leaves (reduced specific leaf area) when compared with wild-type plants. By contrast, plants with large reductions in SBPase activity had low levels of both starch and sucrose, and in these plants the specific leaf area was increased and the height of the plants was either similar to, or taller, with thinner stems when compared with wild-type plants. Similar changes in shoot morphology have been observed in some species in response to light levels in the growth environment (Björkman, 1981; Evans, 1996). In growth conditions where light is limiting, and the carbohydrate status of the leaf reduced, plants produce thinner, larger leaves and longer, thinner stems to maximize light capture. Recently, evidence has been provided indicating a role for photoassimilated sucrose in the regulation of leaf growth patterns in response to shade (Kozuka et al., 2005). It is possible that the reductions in source capacity in the SBPase antisense plants alter the metabolic signals that mimic the acclimatory responses to different light environments, but as yet no candidate molecules mediating this response have been identified. At the whole plant level increased SLA would attenuate the effects of decreased photosynthesis. This is likely to be beneficial to the plant as resources are invested in leaf area to increase light capture, rather than photosynthetic machinery. A correlation between an increase in specific leaf area and reduced photosynthetic rates was observed in the Calvin cycle antisense plants (Stitt and Schulze, 1994; Price et al., 1995; Banks et al., 1999; Raines 2003). The conservation of response in this diverse set of transgenic plants suggests a common signal coming either directly or indirectly from photosynthesis that can influence shoot development. Impact of transgenic manipulation of trehalose metabolism A striking impact on specific leaf area and its relationship to photosynthesis and carbohydrate metabolism has been observed in plants expressing E. coli genes encoding enzymes in the trehalose pathway. The trehalose pathway, once believed to be of curiosity interest in plants, is now known to be indispensable and probably universal playing a central role in regulating carbon use for growth (Eastmond et al., 2002; Schluepmann et al., 2003). It is thought that a key role is played by the signal metabolite trehalose 6-phosphate (T-6-P) (Schluepmann et al., 2003, 2004; Pellny et al., 2004; Lunn et al., 2006). Remarkably, elevated T-6-P in transgenic tobacco leads to a decrease in SLA and up to a 40% increase in photosynthetic carbon assimilation per unit leaf area, due mainly to increased Rubisco activity (Pellny et al., 2004). However, because SLA and leaf area per plant is lower, photosynthesis at the whole plant level does not differ from the wild type. In plants expressing transgenes encoding trehalose phosphate phosphatase or trehalose phosphate hydrolase to reduce T-6-P content, SLA was increased and, in this case, photosynthetic capacity per unit leaf area was lower but, at the whole plant level, greater leaf area compensated for the decrease in photosynthetic capacity. The changes in leaf development observed in plants with altered T-6-P levels may be a consequence of the altered allocation of carbon between starch and sucrose. The recent finding that high levels of T-6-P stimulate the post-translational activation of ADP glucose pyrophosphorylase, thereby increasing starch biosynthesis, provides a link between cytosolic metabolism and the chloroplast (Kolbe et al., 2005; Lunn et al., 2006). This work supports the central role of T-6-P in regulating carbon metabolism in plants and the possibility that T-6-P effects on leaf development can be explained through this route. T-6-P may link cytosolic metabolism with that of the chloroplast, but the full mechanistic basis for this has yet to be established. The mode of action of T-6-P and regulation of T-6-P metabolism are two important questions to be addressed to further our understanding of how this signalling network functions. A role for starch/sucrose ratios and T-6-P in regulating leaf development? The similarities in leaf phenotypes (altered SLA), together with changes in starch-to-sucrose ratios, found in the plants with reduced Calvin cycle activity and plants with altered T-6-P levels, raises the interesting possibility that a common mechanism was responsible for these changes. These results suggest that a balance between the utilization and storage of fixed carbon plays a role in the modulation of leaf development. The importance of sucrose-to-starch ratios for growth was demonstrated by analysis of tomato plants overexpressing sucrose phosphate synthase (SPS). This manipulation has the effect of directing the newly fixed carbon into sucrose, at the expense of starch accumulation. A small change in this balance in favour of sucrose accelerated floral development and increased fruit yield in tomato but, if an excess of newly fixed carbon was used to synthesize sucrose, then no increase in growth was evident (Sharkey et al., 2004). The mechanism underlying the increase in plant yield in the overexpressing SPS lines is not clear but it was not due to a stimulation in photosynthesis. The major effect was to partition a higher proportion of newly fixed carbon directly into sucrose, resulting in an increase in the sucrose-to-starch ratio. Three further studies have highlighted the potential importance of the regulation of carbon allocation to starch and sucrose biosynthesis. Changes in the starch-to-sucrose ratio were evident in the SBPase antisense plants and, in source leaves, starch levels were decreased in response to small reductions in SBPase activity. Interestingly, in these plants with small reductions in SBPase activity, sucrose accumulated in the young leaves, despite having lower levels of starch in the source leaves. To explain this result it was suggested that the plant was able to ‘sense’ the source limitation and, to compensate, the growth of the shoot was reduced, imposing a temporary sink limitation in the young leaves (Olcer et al., 2001; Lawson et al., 2006). A more recent study where daily starch accumulation was limited by altering the length of the photoperiod provides support for this hypothesis. Reductions in the levels of starch accumulation during the photoperiod resulted in a depletion of sugar levels at the end of the night but, surprisingly, when sugar became available at the start of the next photoperiod, it was not used and starch accumulated (Gibon et al., 2004). It is likely that this accumulation of carbohydrate occurs in response to reduced growth caused by a shortage of sugars for growth in the dark phase. The importance of carbon allocation over the diurnal cycle, was also shown using a range of transgenic plants with altered metabolism (Kehr et al., 1998). Taken together the studies described in this section highlight the potential importance of the availability of carbohydrate, for utilization in the dark, in the regulation of growth and development. The mechanism by which plants sense changes in the availability of carbohydrate and how this feeds through to effects on growth are not known. A number of recent studies have provided evidence showing that the majority of starch degradation at night occurs through the hydrolytic pathway, resulting in the formation of maltose and glucose in the cytosol (Fig. 1). This opens up the possibility that starch to sucrose conversion and the resulting altered starch:sucrose ratios can be sensed by tracking flux through the cytosolic hexokinase (Sharkey et al., 2004). This mechanism is likely to form part of a complex regulatory network, involving T-6-P, that maintains a balance between carbon storage and utilization. How such changes in carbon balance are then linked to changes in development is not known, but hexokinase may play a central role in this process by integrating the effects of light, hormones, and nutrient status (Rollond and Sheen, 2005) (Fig. 1). Fig. 1 View largeDownload slide The central role of metabolism in mediating the regulation of growth and development. During the day light absorbed is used to fix carbon in the Calvin cycle producing intermediates for both starch and sucrose biosynthesis (solid arrows). Starch produced during the photoperiod is broken down at night into glucose and maltose via the hydrolytic pathway to provide sucrose for growth at night (broken lines). Levels of sucrose in the cytosol are communicated to the chloroplast by T-6-P by an, as yet, unknown process and increased T-6-P activates AGPase increasing starch accumulation (dashed line). The mechanism by which T-6-P modulates AGPase activity is also not known but may be mediated by thioredoxin. It has been proposed that the glucose sensor, hexokinase, integrates light, hormone, and nutrient signalling to control plant development. Under conditions where starch levels are reduced, sucrose supply is restricted and growth is slowed to compensate. Conversely, when growth is restricted, sucrose accumulates and starch levels increase. Fig. 1 View largeDownload slide The central role of metabolism in mediating the regulation of growth and development. During the day light absorbed is used to fix carbon in the Calvin cycle producing intermediates for both starch and sucrose biosynthesis (solid arrows). Starch produced during the photoperiod is broken down at night into glucose and maltose via the hydrolytic pathway to provide sucrose for growth at night (broken lines). Levels of sucrose in the cytosol are communicated to the chloroplast by T-6-P by an, as yet, unknown process and increased T-6-P activates AGPase increasing starch accumulation (dashed line). The mechanism by which T-6-P modulates AGPase activity is also not known but may be mediated by thioredoxin. It has been proposed that the glucose sensor, hexokinase, integrates light, hormone, and nutrient signalling to control plant development. Under conditions where starch levels are reduced, sucrose supply is restricted and growth is slowed to compensate. Conversely, when growth is restricted, sucrose accumulates and starch levels increase. Changes in non-photosynthetic metabolism impact on leaf development In addition to the impact of changes in photosynthetic carbon fixation on development, evidence is accumulating to suggest that development in plants is also sensitive to changes in the flux of carbon in the chloroplast, between the chloroplast and the cytosol and also in the cytosol. A number of mutants have been produced in which the flux of carbon has been altered and this has led to dramatic and unexpected changes in leaf shoot morphology. Selected examples are discussed below to highlight some of the effects of metabolic perturbations on leaf development. The enzyme ketohexokinase (KHK) is not found in plants, but in E. coli it catalyses the conversion of fructose to fructose-1-phosphate. Ectopic expression of KHK in transgenic potato plants creates an alternative pathway of fructose metabolism and leads to severe abnormalities in leaf area and shape (Fig. 2A). The main metabolic effect of this manipulation is to increase the levels of triose phosphates and glyceraldehyde. KHK expression also resulted in a reduction in photosynthetic carbon fixation by as much as 50%, and flux of carbon to both starch and sucrose was also decreased. An increase in respiratory activity was evident and the activity of glucose-6-phosphate dehydrogenase, the first enzyme in the oxidative pentose phosphate pathway, was increased by 50%, suggesting an increased demand for NAD(P)H in these plants. (Geigenberger et al., 2004). A severe leaf phenotype, with characteristics similar to that observed in the KHK overexpressing potato plants, was observed in antisense tobacco plants with reduced levles of a small chloroplast protein, CP12 (Fig. 2B). This CP12 antisense phenotype was not expected as the proposed role for CP12 is in the regulation of two enzymes in the Calvin cycle phosphoribulokinase (PRKase) and NADP-glyceraldehyde-2-phosphate dehydrogenase (GAPDH). Given that neither the PRKase (Paul et al., 1995) or the GAPDH (Paul et al., 1995; Price et al., 1995) antisense plants exhibited such a phenotype, it seems likely that CP12 plays a wider role in chloroplast metabolism over an above regulating the activity of PRK and GAPDH (C Raines et al., unpublished observations). Interestingly, analysis of the CP12 antisense plants revealed an increase in the activity of glucose-6-phosphate dehydrogenase and a decrease in plastid malate dehydrogenase activity in the light. These data indicate that, as with the KHK overexpressing potato, the NADPH status of the CP12 plants was altered, suggesting that a change in redox state may be part of the underlying cause for the abnormal leaf phenotypes. An alternative explanation may be that changes in carbon fluxes are occurring, altering the availability of compounds such as homones essential for the control of leaf development. Fig. 2 View largeDownload slide Leaf phenotypes. (A) Potato plants over-expressing E. coli ketohexokinase. (B) Antisense tobacco plants with reduced levels of the chloroplast protein CP12. The shape of the leaf is dramatically modified in both of these plants with increased leaf thickness and prominent veins. Figure 2A was provided by Dr P Geigenberger and Dr A Fernie, MPI, Potsdam (see Geigenberger et al., 2004 for the full reference) and is reproduced by kind permission of Springer Science and Business Media. Fig. 2 View largeDownload slide Leaf phenotypes. (A) Potato plants over-expressing E. coli ketohexokinase. (B) Antisense tobacco plants with reduced levels of the chloroplast protein CP12. The shape of the leaf is dramatically modified in both of these plants with increased leaf thickness and prominent veins. Figure 2A was provided by Dr P Geigenberger and Dr A Fernie, MPI, Potsdam (see Geigenberger et al., 2004 for the full reference) and is reproduced by kind permission of Springer Science and Business Media. Large changes in carbon fluxes with a reallocation of photosynthate from sucrose biosynthesis into organic acids also occurred in plants with reductions in the levels of the plastidic 2-oxoglutarate/malate translocator DiT1. These plants had altered leaf morphology, irregular leaf margins, and reduced apical dominance (Schneidereit et al., 2006). Changes in leaf phenotype have also been observed in Arabidopsis plants with a mutation in the crumpled leaf gene, CRL, encoding a protein of the plastid outer envelope. No function has been found for the product of this gene but it is possible that it has a role in metabolism at the interface between the chloroplast and the cytosol (Asano et al., 2004). These two examples provide further evidence of the importance of regulating carbon fluxes in determining plant development. Systematic analysis of plants with leaf phenotypes such as those described here will provide invaluable information on the regulatory networks involved in co-ordinating metabolism and growth. Conclusions This review discusses evidence from the current literature that highlights the links between leaf metabolism and development. In a diverse set of Calvin cycle antisense plants similar changes in leaf development were noted, suggesting that there may be a common signal from photosynthesis that regulates this aspect of development. Part of this mechanism may involve T-6-P as a signal molecule to maintain a balance between the utilization and storage of carbohydrates. How these metabolites are sensed by the plant and how cell division and expansion are influenced by changes in metabolism are future challenges that need to be resolved to enable the maximum potential to be gained from transgenic manipulation of photosynthetic metabolism to increase yields. Manipulation of pathways of chloroplast metabolism, other than photosynthesis has yielded a number of mutants with altered leaf phenotypes, but the signalling pathways involved are at present unknown. Products from phenolic acid metabolism, sterol biosynthesis, and isoprenoid biosynthesis have been shown to have an impact on the regulation of leaf development (Streatfield et al., 1998; Tamagnone et al., 1998; Estevez et al., 2000; Carland et al., 2002). Understanding the factors regulating the flux of carbon between these pathways will be important if plants are to be fully exploited as biofactories for the production of commercially important compounds. CAR acknowledges support from BBSRC and the University of Essex Research Promotion Fund. Rothamsted Research receives grant-aided support from the Biotechnological and Biological Sciences Research Council of the United Kingdom. The authors would like to thank Drs Geigenberger and Fernie for Fig. 2A. 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Fleming, A

doi: 10.1093/jxb/erj178pmid: 16690623

Abstract Research over the last decade has led to tremendous advances in the characterization of the transcriptional networks involved in the initiation and maintenance of the shoot apical meristem (SAM), as well as the factors involved in the formation and development of leaves by this organ. However, one aspect of the SAM that has received rather limited attention is the fact that it is characterized by being heterotrophic, in contrast to the majority of cells and tissues immediately derived from it which rapidly undergo differentiation to form photosythetically active, autotrophic organs. This clear physiological and biochemical distinction of the SAM from the surrounding tissue raises interesting questions as to what controls the transition from heterotrophic to autotrophic growth, the nature and sequence of the metabolic events that must occur on this transition, as well as basic questions as to the potential interaction of development and metabolism in this small but essential organ of the plant. In this review, an overview is provided of present knowledge in this area, as well as some recent data that provide an insight into the potential intertwining of metabolic and developmental mechanisms during leaf initiation. Biochemistry, carbohydrate, cell wall, development, photosynthesis Introduction The shoot apical meristem (SAM) contains a group of pluripotent cells which undergo repeated rounds of division over an extended period of time to generate the daughter cells from which the main aerial bulk of the plant is produced. It has been the focus of extensive investigations and, with the advent of molecular genetic approaches, a detailed picture of the genetic and molecular interactions involved in the establishment, maintenance, and function of this specialized group of cells is beginning to emerge (reviewed in Veit, 2004). As a result, it is now common to view the SAM as an organ patterned by specific transcription factors whose combinatorial or exclusive expression dictates the fate of cells within it. In addition, it has become clear that precise yet complicated signalling processes occur both within the SAM and between the SAM and the surrounding tissue to reinforce or define the spatial boundaries of transcription factor activity. The nature of these signalling networks and how they feed-back and feed-forward to the transcriptional networks is a major focus of current research (Hay et al., 2004). However, at the same time, the SAM has some unique metabolic and physiological attributes which have yet to be directly addressed by molecular genetic approaches. If the functioning of the SAM is to be fully understand, the nature of these target processes and their relationship with the transcriptional and signalling networks controlling meristem function must be unravelled. Indeed, some of the metabolic characters may be an essential aspect of meristem function. In this article, the focus is on defining this problem, providing a summary of some recent data in this area and a framework for future lines of research. Metabolic events in the shoot apical meristem Viewing the SAM under fluorescent illumination (Fig. 1A) reveals a basic aspect of meristem biology. The cells of the SAM are heterotrophic, i.e. they do not contain chlorophyll. Analysis of meristem cells at the TEM level backs up this simple observation, showing that the cells contain proplastids with no or very limited lamella structure (Fig. 1B). Similarly, analysis of transcript patterns for genes whose products are required for photosynthesis (e.g. RBCS; Fig. 1C) reveals that these genes are not expressed within the SAM but are highly expressed in regions just outside the meristem. Use of promoter::reporter gene constructs in transgenic plants supports this observation (Fig. 1D, E), indicating that transcriptional activation of photosynthetic target genes occurs within a very few cell diameters of leaving the meristem domain. Fig. 1 Open in new tabDownload slide The shoot apical meristem shows distinct patterns of gene expression linked to metabolism. (A) Image of a tomato SAM viewed under epifluorescence. Chlorophyll (yellow fluorescence) is visible in the leaf primordia and stem tissue but is absent from the dome of the SAM (m). (B) Transmission electron micrograph of a cell in the tomato SAM. Proplastids (pp) are visible adjacent to the large nucleus (nu). (C) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for RBCS. Signal (silver grains) is visible in the leaf primordia and the stem tissue but is absent from the SAM (m) and the leaf vascular tissue (v). (D) Visualization of GUS activity in the shoot apex of a transgenic tobacco plant containing an RBCS promoter sequence linked to the GUS reporter gene. The section has been viewed with dark-field optics so that the GUS signal appears red. Signal is absent from the SAM (m). (E) Visualization of GUS activity using a fluorogenic substrate in the shoot apex of a transgenic tomato plant containing an RBCS promoter sequence linked to the GUS reporter gene. A high signal (yellow) is observed in the cells that have just left the Sam domain (m) to become incorporated into a new leaf primordium (p). (F) In situ hybridization of a longitudinal section of a tobacco shoot apex with an anti-sense probe for NTH15 encoding a tobacco STM-like KNOX protein. Signal (purple) is seen in the SAM, but is excluded from the site of presumptive leaf formation, as well as the leaf primordia themselves. (G) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for the large subunit 1 of AGPase. Signal (purple) is seen in a band of cells internal to the site of presumptive leaf formation. (H) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for SuSy. Elevated signal (purple) is seen in a group of cells adjacent to the site of presumptive leaf formation. Parts A, E are from Fleming et al. (1996),The Plant Journal10, 745–754, part C from Fleming et al. (1993),The Plant Journal5, 297–309, part D from Mandel et al. (1995),Plant Molecular Biology29, 995–1004, and parts G, H from Pien et al. (2001b)Proceedings of the National Academy of Sciences, USA98, 11812–11817. Fig. 1 Open in new tabDownload slide The shoot apical meristem shows distinct patterns of gene expression linked to metabolism. (A) Image of a tomato SAM viewed under epifluorescence. Chlorophyll (yellow fluorescence) is visible in the leaf primordia and stem tissue but is absent from the dome of the SAM (m). (B) Transmission electron micrograph of a cell in the tomato SAM. Proplastids (pp) are visible adjacent to the large nucleus (nu). (C) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for RBCS. Signal (silver grains) is visible in the leaf primordia and the stem tissue but is absent from the SAM (m) and the leaf vascular tissue (v). (D) Visualization of GUS activity in the shoot apex of a transgenic tobacco plant containing an RBCS promoter sequence linked to the GUS reporter gene. The section has been viewed with dark-field optics so that the GUS signal appears red. Signal is absent from the SAM (m). (E) Visualization of GUS activity using a fluorogenic substrate in the shoot apex of a transgenic tomato plant containing an RBCS promoter sequence linked to the GUS reporter gene. A high signal (yellow) is observed in the cells that have just left the Sam domain (m) to become incorporated into a new leaf primordium (p). (F) In situ hybridization of a longitudinal section of a tobacco shoot apex with an anti-sense probe for NTH15 encoding a tobacco STM-like KNOX protein. Signal (purple) is seen in the SAM, but is excluded from the site of presumptive leaf formation, as well as the leaf primordia themselves. (G) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for the large subunit 1 of AGPase. Signal (purple) is seen in a band of cells internal to the site of presumptive leaf formation. (H) In situ hybridization of a longitudinal section of a tomato shoot apex with an anti-sense probe for SuSy. Elevated signal (purple) is seen in a group of cells adjacent to the site of presumptive leaf formation. Parts A, E are from Fleming et al. (1996),The Plant Journal10, 745–754, part C from Fleming et al. (1993),The Plant Journal5, 297–309, part D from Mandel et al. (1995),Plant Molecular Biology29, 995–1004, and parts G, H from Pien et al. (2001b)Proceedings of the National Academy of Sciences, USA98, 11812–11817. The inability of the SAM to perform photosynthesis, coupled with the rapid acquisition of photosynthetic capacity as cells leave the SAM domain, raises two basic questions. Firstly, what controls this transition and, secondly, what is the significance of this lack of photosynthetic capacity for the SAM? Taking the question of the control of transition from non-photosynthetic to photosynthetic capacity, research over the last decade has led to the fundamental concept that the SAM is defined by a series of transcriptional networks whose spatial and temporal control defines SAM function (Veit, 2004). However, how easily the patterns of these transcriptional networks transpose onto the pattern of switching of photosynthetic capacity is questionable. The SAM consists of a population of cells which, during embryogenesis, become committed to the formation of a group of initials (or stem cells) which undergo repeated rounds of proliferation. The positioning of these stem cells within the SAM is regulated by a set of genes including WUSHEL, CLAVATA1, and CLAVATA3 which display spatially distinct patterns of expression (Brand et al., 2000; Schoof et al., 2000). However, none of these patterns easily links to those displayed in Fig. 1C, D or E by genes involved in the acquisition of photosynthetic capacity. The meristem domain itself is initially defined by expression of STM-like KNOX homeobox genes (Long et al., 1996). Repression of STM-like gene expression within the SAM is associated with the determination of a subset of meristem cells to form a leaf primordium (Jackson et al., 1994; Fig. 1F). However, this loss of STM-like gene expression (and concomitant gain of expression of ARP-like transcription factors, such as PHANTASTICA (Hay et al., 2004)) occurs significantly before the overt acquisition of photosynthetic capacity, suggesting that these transcription factors are not simply linked to this physiological and metabolic switch. Moreover, in a number of SAMs STM-like gene expression can extend into the sub-meristem region of the stem where, for example, chlorophyll accumulation is clearly occurring. These observations suggest that the switch from heterotrophic to autotrophic growth is not simply regulated by a KNOX gene-dependent mechanism. Other genes, such as AINTEGUMENTA, are expressed very early in the leaf primordium, but appear to be absent from the subtending stem tissue. Since the acquisition of photosynthetic capacity occurs in both leaf and stem tissues, it would seem unlikely that such genes are intimately involved in this switching process. With respect to genes belonging to the network of PHABULOSA, KANADI and YABBY factors (Kerstetter et al., 2001; McConnell et al., 2001; Eshed et al., 2004), altered expression leads to clear changes in leaf polarity and switching between adaxial and abaxial cell identity, but the differentiation of the cells formed appears normal, indicating that these networks control patterning rather than the specific differentiation events. It is, thus, at present very unclear how (or whether) the transcription factor networks so far identified as playing an essential role in initiation and maintenance of the SAM play a direct role in repressing the acquisition of the photosynthetic apparatus in meristem cells. It is, however, intriguing that a recent paper from the Weigel group has revealed that the exogenous supply of sucrose to plants mutated in a specific WUS-related gene (STIMPY/WOX9) can rescue a wild-type phenotype. In the absence of exogenous sucrose the mutant displays an impaired ability to maintain a functional SAM and is seedling lethal (Wu et al., 2005). The mutant seedlings are green, and thus presumably can photosynthesize and generate sucrose. Either the transport, metabolism or signalling of sucrose is impaired as a result of the loss of the transcription factor activity, and this loss in carbohydrate metabolism or signalling is instrumental in the meristem phenotype observed. Alternatively, the exogenous sucrose by-passes a pathway linked to the appropriate expression of the STIMPY/WOX9 transcription network. An input of sucrose on cell division is long established and maintenance of cell division is a clear characteristic of the SAM. It is therefore interesting to note that recent papers have implicated CK-responsiveness in SAM function (Leibfried et al., 2005). A linkage of cytokinin and sucrose on cell proliferation is well established from work on tissue cultures, and significant data indicate that at least some of the transcription factors involved in meristem function lead to altered hormone (CK and GA) levels (Jasinski et al., 2005). A network is thus appearing in which sugars, hormones, and transcription factors interact to regulate meristem function. A vast body of work shows that the acquisition of photosynthetic capacity can be repressed by darkness, leading to the formation of etiolated tissue. Thus, one possibility is that the lack of photosynthetic capacity in the SAM is a consequence of its position in the plant, i.e. that its enclosed nature prevents access of light, thus leading to an essentially etiolated tissue. However, simple exposure of SAMs to light does not trigger either accumulation of chlorophyll or the expression of light-regulated genes such as RBCS (Fleming et al., 1996). These data indicate that the specific pattern of metabolism in the SAM reflects an intrinsic developmental state of the tissue rather than an environmentally imposed limitation. So, if our knowledge of the transcriptional networks involved in switching non-photosynthetic meristem cells to photosynthetic non-meristem cells is very much incomplete, what of our understanding of the consequences of this metabolic status? What is the metabolic character of the SAM? What changes occur as a meristem cell undergoes differentiation to form a leaf or stem cell? If meristem cells possess a specific metabolism, does this in any way have an impact on their specific developmental function, i.e. is meristem-cell function dependent on a particular metabolic state? Is it possible to form a green SAM, or are these two attributes exclusive? Early work on the SAM indicated that specific enzyme activities (e.g. acid phosphatase, succinic dehydrogenase) showed specific patterns within the SAM, however, the functional significance of these patterns of enzyme activity remained open to speculation (Fosket and Miksche, 1966; Gifford and Corson, 1971). Following these initial studies, interest in the metabolic status of the SAM waned but was reinvigorated by the work of Kerk and Feldman studying the root apical meristem (RAM). They showed that the quiescent centre of the RAM (which forms part of the stem cell niche) contains very low levels of ascorbate and high activities of the enzyme ascorbate oxidase (AOO). Moreover, they could demonstrate that the gene encoding AOO was auxin-inducible. Since the available evidence indicates that auxin transport is channelled down the root towards the RAM, these authors proposed that the flux of auxin towards the QC induced AOO, leading to low levels of ascorbate and (in addition) metabolism of auxin by AOO. Since low levels of ascorbate had previously been correlated with blockage of the cell cycle, they proposed that the altered oxidative environment in the QC invoked by auxin was the mechanism by which cell proliferation was blocked (Kerk and Feldman, 1995; Jiang et al., 2003). Indeed, feeding roots with low levels of ascorbate did promote cell proliferation. Whether a similar situation exists in the SAM (where auxin flux plays a key role in leaf initiation) remains unknown. It is also worth noting that at least some animal stem cell populations are characterized by high activities of aldehyde dehydrogenase (ALDH) (Storms et al., 1999). Although is has been proposed that this activity functions in a defence-related mode to destroy cytotoxic compounds, it has also been suggested that ALDH plays a role in the metabolism of retinal, a vitamin A-derived growth factor implicated in various aspects of animal developmental biology. It is interesting that lines of investigation in both animals and plants suggest that stem cell niches are characterized by oxidizing enzyme activities which have been proposed to play a role in the metabolism of growth factors. Although many aspects of stem cell identity are distinct between plant and animals (Sablowski, 2004), some aspects (such as cell cycle regulation) appear highly conserved. Is a distinct metabolic status a unifying theme in stem cells? The advent of novel methods for metabolite analysis in very small tissue samples provides a way of testing some of these ideas, as will be discussed later in this article. Metabolic events during the earliest stages of leaf initiation As outlined above, despite significant advances in our understanding of the transcriptional networks controlling leaf devolopment, none of the genes so far characterized seem to play an obvious role in the differentiation of meristem to non-meristem (leaf) cell. Certainly, some of these transcriptional changes impinge on hormone (notably GA) metabolism (Sakamoto et al., 2001; Hay et al., 2002), however, how or to what degree the resulting changes in hormone action are related to the differentiation of, for example, leaf tissues is unclear. As also outlined above, the switch from meristem to non-meristem cell appears to be entwined with plastid differentiation and the acquisition of photosynthetic capacity, suggesting that a switch in carbohydrate metabolism, which must accompany this plastid differentiation, might be involved in this change of cell identity. Some data from this laboratory have provided intriguing data that altered carbohydrate metabolism is indeed linked with the earliest phase of commitment by meristem cells to form a leaf (Pien et al., 2001a). Using bisected tomato SAMs, the RNA profiles in meristem tissue just undergoing commitment to leaf formation was compared with meristem tissue that would not undergo this process for approximately another 48 h. Five clones were obtained that showed increased RNA expression (as revealed by in situ hybridization analysis) in tissue associated with leaf formation (the I1 position in the SAM). One of these genes encoded an ARP transcription factor, i.e. the expression pattern of a gene expected to be specifically expressed in I1 tissue (Hay et al., 2004). A second gene encoded a P450 enzyme implicated in the biosynthesis of brassinolide, a hormone implicated in various aspects of plant growth. More recent data also indicate that brassinolide synthesis plays a role during the early stages of leaf formation (Montoya et al., 2005). The fact that both GA and brassinolide metabolism may be specifically altered at the site of presumptive leaf formation, along with the data indicating that altered auxin flux at this site is a key step in leaf initiation (Reinhardt et al., 2003, reviewed in Fleming, 2005), demonstrates the importance of concerted hormone metabolism and flux at the site of presumptive leaf formation. However, the remaining three I1 markers encoded proteins involved in various aspects of carbohydrate metabolism (sucrose synthase (SuSy), ADP glucose pyrophosphorylase (AGPase) and a SNF1-like kinase). The potential roles of these gene products will be discussed below, but it is perhaps worth considering first why genes involved in carbohydrate metabolism might be identified by the screen performed here. The anatomy and function of the SAM present the plant with an intriguing set of problems. The SAM is among the most metabolically active regions of the plant, generating new cells to supply the rest of the plant. However, all carbon must be imported into the SAM from the vasculature which, moreover, terminates at a distance from the base of the SAM. It is, therefore, not unexpected that the SAM might have a distinct pattern of carbohydrate metabolism from the surrounding tissue which is derived from it. However, the nature of this metabolism and its control remains unclear. For example, the pattern of AGPase at sites internal to where leaf initiation occurs (Fig. 1G) suggests that starch accumulation is occurring, and TEM analysis of starch grain density supports this view (Pien et al., 2001a). However, why starch should accumulate at this site is open to speculation. One possibility is that a temporary storage of C ensures that during the initial stages of leaf formation a sufficient supply of C and energy is available to ensure that the process proceeds. The differential expression of an SNF1-like protein kinase suggests that the response of meristem cells to sugar signals might be distinct from that of the surrounding tissue. SNF1-like protein kinases are thought to be necessary for the transduction of signals regulating the response of a tissue to specific sugar signals (Halford et al., 2000). Moreover, activity of an SNF1-like kinase has been implicated in the control of AGPase activity, suggesting that the overlapping expression domains observed in the analysis in the SAM may have functional significance. Certainly, meristem cells respond to exogenous supplied sucrose by altered patterns of gene expression (Pien et al., 2001a), but the significance of this is at present unclear since meristem function does not appear to be affected. Finally, the local expression of SuSy at the presumptive site of leaf formation is intriguing since the activity of this enzyme has often been correlated with sink activity (i.e. regions of high sucrose utilization) (Zrenner et al., 1995; Koch, 2004). Furthermore, it has also been postulated that SuSy might function in regions where low oxygen or low adenylate energy charge preclude or limit alternative means of sucrose breakdown (e.g. via invertase) (Ricard et al., 1998). The situation in the SAM is unclear since invertases are certainly expressed in this tissue, however, the relative in vivo activity of the two metabolic pathways is unknown. A recurring problem with the data described above is that of interpreting metabolism on the basis of transcript data alone. Transcript patterns provide an indication of where a protein might accumulate, but do not indicate the in vivo activity of that protein or enzyme. Even if data on protein or enzyme activity are available, this does not necessarily translate to a particular flux through a metabolic pathway. In a first attempt to combat this problem, a project aimed at metabolic profiling of the SAM has recently been initiated. By comparison of metabolite and transcript data in a precisely defined tissue, it is hoped to be able to assess the significance of the observed transcript patterns at the level of metabolism. Metabolic profiling of the shoot apical meristem Metabolite profiling is a mass spectrometry-based technique whereby molecular components of a complex sample are volatilized and passed through a mass spectrometer and separated according to their charge/mass ratio. In the simplest scenario, each ionized molecule within a tissue will possess a distinct charge/mass ratio which allows its facile identification by comparison with known standards. In reality, the extremely complex nature of most tissues, coupled with differences in ease of volatilization, molecular breakdown pattern, and various other factors, makes identification of all compounds in one sample virtually impossible. Nevertheless, in most samples a number of common metabolites can be identified relatively easily and, moreover, in a semi-quantifiable fashion. In addition, the exquisite sensitivity of the methods now available means that it is feasible to analyse samples taken from extremely small samples, indeed down to the level of the single cell. A project has been initiated aimed at analysing the metabolite profiles of single tomato meristems, focusing on small metabolites closely associated with carbohydrate metabolism. By comparison with the transcript patterns described above, the relevance of the observed patterns of gene expression to actual metabolism within the meristem and young developing leaves is being investigated. In a first series of experiments, individual SAMs were dissected from tomato plants and analysed by TOF mass spectrometry. For comparison, young leaf primordia (P3-P4) were also analysed, as were SAMs which had been pretreated with 1 μM IAA. Previous data have indicated that local treatment with auxin is sufficient to induce leaf formation on tomato SAMs and reflects an endogenous function of auxin in determing the site of leaf initiation (Reinhardt et al., 2003). As a control, tomato fruit tissue was analysed since data for this organ were already available (Overy et al., 2005) and it represents a clearly differentiated tissue from both the SAM and leaf primordia. The preliminary results, shown in Fig. 2, indicate that, firstly, metabolite profiling of individual SAMs is feasible. Clean, reproducible traces were obtained using the minute amounts of starting material. Secondly, metabolite profiles from untreated SAMs were distinct from auxin-treated SAMs and from leaf primordia and fruit tissue, i.e. distinct tissues show distinct profiles and the SAM displays a distinct response to auxin, a known modulator of SAM activity. Fig. 2 Open in new tabDownload slide Metabolite profiling of the SAM. (A) Metabolite profile of an SAM. Single tomato SAMs were extracted in 70% methanol then, following centrifugation, samples were directly injected into a mass spectrometer (ESI-ToF) equipped with nano-spray injector and lock-spray for accurate mass determination at a flow rate of 10 μl min−1. Data were acquired for 30 s in both positive and negative ion modes. The trace reveals a typical sequence of peaks, with each peak relating to an individual mass/charge ratio. (B) Principle Component Analysis reveals differences in metabolic profiles between different tissues. A series of metabolic profiles were performed on individual SAMs, some of which were pretreated for 16 h with 10 μM IAA. Metabolic profiles were also performed on individual leaf primordia (stage P2–P4). Data for tomato fruit were taken from Overy et al. (2005). PCA reveals that profiles from different tissues tend to form distinct groups, indicating distinct metabolic composition. Open circles, SAM; closed circles, SAM pretreated with auxin; closed squares, leaf primordia; closed triangles, tomato fruit. Fig. 2 Open in new tabDownload slide Metabolite profiling of the SAM. (A) Metabolite profile of an SAM. Single tomato SAMs were extracted in 70% methanol then, following centrifugation, samples were directly injected into a mass spectrometer (ESI-ToF) equipped with nano-spray injector and lock-spray for accurate mass determination at a flow rate of 10 μl min−1. Data were acquired for 30 s in both positive and negative ion modes. The trace reveals a typical sequence of peaks, with each peak relating to an individual mass/charge ratio. (B) Principle Component Analysis reveals differences in metabolic profiles between different tissues. A series of metabolic profiles were performed on individual SAMs, some of which were pretreated for 16 h with 10 μM IAA. Metabolic profiles were also performed on individual leaf primordia (stage P2–P4). Data for tomato fruit were taken from Overy et al. (2005). PCA reveals that profiles from different tissues tend to form distinct groups, indicating distinct metabolic composition. Open circles, SAM; closed circles, SAM pretreated with auxin; closed squares, leaf primordia; closed triangles, tomato fruit. Analysis of the individual metabolites within the different samples is still in progress, but the initial data are already intriguing. Of the top 50 metabolites showing a significant relative difference in level between SAM and leaf primordia tissue, eight were provisionally identified as either dNTPs or dNDPs. In particular, in all cases there is an elevated ratio of dNDP to dNTP in the SAM relative to leaf tissue. Interestingly, one of the earliest reports on a gene specifically expressed in the SAM described the expression pattern of a dUTPase whose transcripts were elevated in the SAM (Pri-Hadesh et al., 1992). This analysis provides the first indication that the specific transcript pattern (described 14 years ago!) has relevance at the metabolite level. This, of course, raises the question of the functional significance of this metabolite pattern. Bearing in mind the specific transcript pattern for SuSy observed in the tomato SAM, it is worth noting that SuSy catalyses the production of fructose and UDGglc from sucrose and UDP. The accepted hypothesis is that, under most circumstances, SuSy catalyses the reaction in this direction although (based on delta G values) the reaction is readily reversible (Geigenberger and Stitt, 1993). Sucrose is thought to reach the SAM from the sub-adjacent phloem (i.e. is present is excess), but its catalysis requires an appropriate supply of UDP. Maintenance of a relatively high ratio dNDP/dNTP ratio might facilitate this. This still, of course, leaves open the question of why SuSy expression should be up-regulated at the site of presumptive leaf formation. SuSy is not the only option for sucrose breakdown in the SAM since data indicate that invertase genes are expressed at reasonable levels within this tissue, at least at the transcript level (Pien et al., 2001a). Various ideas have been proposed that under certain physiological conditions (e.g. hypoxia, low adenylate energy charge) utilization of SuSy might be preferable to invertase (Ricard et al., 1998; Koch, 2004). What the situation is in the SAM is unclear. SuSy has also been implicated in metabolite channelling, in particular with respect to a role of providing UDP-glucose precursors for cell wall biosynthesis (Amor et al., 1995). As described in the next section, altered cell wall characteristics are likely to play a key role in the initial events of leaf formation, thus localization of SuSy at the site of leaf initiation might have a role in channelling UDP-glucose towards cell wall biosynthesis. Molecular events in the cell wall during leaf initiation A substantial body of evidence supports the hypothesis that control of cell wall structure and architecture plays a key role in the initial events of leaf formation (Cosgrove, 2000). Plant cell walls act to restrain expansion, counteracting the turgor force generated within the cell. For controlled growth to occur, a temporary imbalance in these forces must occur. The majority of data indicate that plants control this process by regulation of cell wall extensibility, i.e. local loosening of the cell wall allows growth to occur in this region until a new biophysical equilibrium is established between tensile force in the cell wall and the internally generated turgor pressure. This growth via altered cell wall loosening would, if integrated over time, lead to a gradual thinning of the cell wall as its perimeter increased to contain the increased volume of the enclosed material. Such thinning of the cell wall would tend to weaken the cell wall, decreasing the resistance to expansion, thus leading to a potentially cataclysmic cycle of events leading to eventual tearing apart of the wall. The fact that this does not happen is due to two co-ordinated processes. Firstly, the evidence suggests that the alterations in cell wall architecture that occur during expansion growth occur in a highly controlled fashion. Secondly, observations on most growing tissues (with hypocotyls being an exception) indicate that cell wall thinning does not occur, implying that the process of cell wall synthesis and turnover is tightly coupled to the process of cell wall loosening. With respect to cell wall loosening, most attention has focused on a family of proteins termed expansins (Cosgrove, 2000; Lee et al., 2001). These proteins are localized in the cell wall, are found in very wide range of plants, and their expression pattern frequently correlates with tissue undergoing rapid expansion. In vitro assays show that purified expansins can promote cell wall elongation and, moreover, manipulation of expansin gene expression in transgenic plants leads to phenotypes consistent with the proposed function of these proteins as regulators of cell wall extensibility (Cho and Cosgrove, 2000; Pien et al., 2001b; Choi et al., 2003). However, the mechanism of expansin action is still somewhat shrouded in mystery. The data indicate that the optimal substrate for these proteins is a mixture of cellulose and xyloglucans (Whitney et al., 2000). Since the non-covalent interaction of these two macromolecules is thought to form a lattice-work providing resistance to extension, a site of action of a cell wall loosening protein at the interface of this lattice seems very reasonable. However, how expansin acts at this interface to loosen the lattice in a controlled fashion is unknown. It certainly appears that expansin does not possess any of the classical enzymatic activities associated with cell wall synthesis and metabolism. Immunocytochemistry data indicate that expansins accumulate at the middle lamella, but whether this reflects their site of action is unknown, i.e. it might indicate where expansins end up but does not necessarily show where they act in the cell wall matrix. If expansins were to be closely associated with controlling the architecture of newly synthesized cellulose and xyloglucans, a localization towards the inner side of the cell wall close to the plasmalemma-localized cellulose synthase complexes would seem more likely. It should also be pointed out that expansins are not the only potential player in controlling cell wall extensibility and evidence exists that other proteins, such as lipid transfer proteins, also influence cell wall architecture (Nieuwland et al., 2005). Furthermore, enzymatic functions that lead to the modification of cell wall macromolecules (such as XETs) and to the generation of hydroxyl radicals have also been proposed as endogenous regulators of cell wall function (Schopfer, 2001). A tight co-ordination and channelling of new wall material at the plasma membrane/cell wall interface, coupled with a mechanism for controlling how the cell wall constituents interact would seem eminently sensible. However, knowledge of the dynamics of cell wall architecture during synthesis of the cell wall and, indeed, the process by which new cell wall material is integrated into the existing matrix is so limited (Somerville et al., 2004) that any mechanisms put forward must be treated as speculative. Progress in this area is essential if the integration of catabolic events associated with growth and differentiation in the SAM is to be understood. Conclusions The SAM is an organ of fundamental importance in plant biology. It is clear that the SAM is metabolically distinct from the adjacent tissue derived from it. The mechanism controlling the switch of metabolism that must occur as cells leave the SAM domain is unclear. Whether the SAM displays a unique or special metabolic character is suggested by available data, but is essentially not documented. Whether such a metabolic character is intrinsic to the special function that the SAM performs is similarly untested. With so many unknowns, it is clear that the field is open for essential progress in this area. The advent of highly sensitive and powerful tools for the analysis of metabolism in extremely small samples means that at last it is possible at least to attempt to answer these fundamental questions. Coupled with the broad range of molecular genetic tools now available, correlations and indications revealed by such metabolic analyses can now be realistically put to the test. Although such work will obviously be technologically challenging, it is feasible, and if the goal of gaining a meaningful understanding of all plant gene function is to be accomplished, such challenges must be met. Thanks go to Heather Walker (Sheffield) for invaluable work performing the metabolite profiling, Joanna Wyrzykowska (ETH-Zurich) for assistance in preparing the auxin treated SAMs and Paul Quick (Sheffield) for help and advice on the interpretation of the metabolite profiling data. 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Aluru, Maneesha R.;Yu, Fei;Fu, Aigen;Rodermel, Steven

doi: 10.1093/jxb/erj008pmid: 16449381

Abstract Plant variegations are characterized by the presence of white sectors in normally green tissues and organs. Whereas the white sectors contain defective plastids that lack coloured pigments, the green sectors contain morphologically normal chloroplasts. Variegation mutants are defective in chloroplast developmental processes and arise due to mutations in nuclear or organellar genes. Despite their widespread occurrence in nature, only a few variegations have been studied at the molecular level. In this review, recent progress toward understanding two Arabidopsis variegations, immutans (im) and var2 is summarized. Both im and var2 are caused by nuclear recessive mutations and the responsible genes have been cloned and characterized. IMMUTANS functions as a chloroplast terminal oxidase that transfers electrons from the plastoquinol pool to oxygen. It appears to be a versatile electron sink, especially early in chloroplast development, when its function is crucial for carotenoid biosynthesis, and in excess light, when it serves as a ‘safety valve’. IM also probably functions in chlororespiration. VAR2 encodes a chloroplast FtsH metalloprotease (termed AtFtsH2). Along with other AtFtsH proteins (AtFtsH1, 5 and 8), it forms complexes in the thylakoid membrane that are probably involved in the process of PSII repair during photoinhibition. A model has been proposed to explain the mechanism of var2 variegation, which suggests that threshold levels of FtsH complexes are required for green sector formation. It is concluded that studies on im and var2 have provided novel insights into nuclear–chloroplast interactions and, especially, into mechanisms of photoprotection. Immutans, metalloprotease, photo-oxidation, photoprotection, terminal oxidase, thylakoid, var2 Introduction The endosymbiotic theory of evolution postulates that chloroplasts originated from endosymbiotic cyanobacteria and that, during the process of symbiogenesis, many symbiont genes were lost or transferred to the nucleus. Consistent with this theory, plastid genomes encode ∼ 80–100 proteins, while ∼ 2500–3500 nucleus-encoded proteins are predicted to be targeted to the chloroplast (Goldschmidt-Clermont, 1998; Abdallah et al., 2000; Peltier et al., 2002). Both anterograde (nucleus-to-chloroplast) and retrograde (plastid-to-nucleus) signals have evolved to facilitate the co-ordinate expression of nuclear and chloroplast genes. Anterograde mechanisms are elicited in response to exogenous or endogenous signals and regulate the expression of nuclear genes for plastid proteins. These include structural proteins in the plastid, as well as regulatory proteins that are necessary for the expression of plastid genes. The translational regulation of rbcL expression (for the Rubisco large subunit, LS) in the plastid by the abundance of nuclear-encoded (rbcS) small subunits (SS) is a classic example of how anterograde traffic co-ordinates the accumulation of gene products from nuclear and chloroplast genomes (Rodermel, 1999). Conversely, early observations that the transcription of nuclear genes for chloroplast proteins, such as Lhcb and rbcS, is down-regulated in tissues treated with the carotenoid biosynthesis inhibitor, norflurazon (a bleaching herbicide), and in mutants with defective chloroplasts gave rise to the notion of retrograde signalling. Retrograde signals are produced in response to the developmental and/or metabolic state of the plastid and regulate the expression of nuclear genes (reviewed in Rodermel, 2001b; Surpin et al., 2002). Thus, the development of a fully-functional chloroplast is dependent on nuclear-organelle interactions. Variegation mutants have played a prominent role in the history of genetics and led to the discovery of non-Mendelian inheritance (Tilney-Bassett, 1975). Variegated plants have green and white (or yellow) sectors in normally green organs of the plant. Whereas the green sectors contain normal-appearing chloroplasts, the white sectors have abnormal plastids that lack well-developed lamellar structures and are deficient in chlorophyll and carotenoid pigments (reviewed in Rodermel, 2001a). Sectoring in these mutants arises as a consequence of mutations in nuclear or plastid genes that disrupt a process that is required for normal chloroplast development; the lack of pigments is often a secondary consequence of the primary lesion. Unlike albino plants, variegation mutants are non-lethal and offer excellent opportunities to study nuclear-organelle interactions. However, only a few variegations have been studied at the molecular level. This laboratory has long been interested in variegation mutants of Arabidopsis as a means of understanding nuclear-organelle interactions. Relatively few variegations have been reported in Arabidopsis, despite the fact that a large number of colour mutants (usually uniformly pale-green, yellow, or all-white) are found in many types of mutagenesis screens. Initial studies focused on immutans, then branched out to a mutant that was thought might be an allele of immutans. This turned out to be an incorrect assumption and, rather, led to the identification of another variegation mutant, var2. This mutant has been studied further. In this manuscript, an overview is provided of what is known about immutans and var2. Both mutants have yielded novel insights into the mechanisms of nuclear–chloroplast interactions and chloroplast biogenesis. immutans The immutans (im) variegation mutant is one of the oldest Arabidopsis mutants. It was first described and partially characterized nearly 50 years ago by Rédei in the US and Röbbelen in Germany (reviewed in Rodermel, 2001a; Aluru and Rodermel, 2004). They isolated independent alleles of the gene. Green- and white-sectoring in im is caused by a nuclear recessive gene and the gene has a normal Mendelian mode of transmission (Fig. 1). Light intensity and quality modulate white sector formation, with increased light enhancing white sector formation. Progeny of im seeds display the same parental variegation pattern regardless of whether they are derived from branches of green or white sectors. This indicates that both types of sectors have a uniform genetic constitution and that variegation is not due to the action of a transposable element. It also suggests that a bi-directional switch occurs between the green and white phenotype whereby the plastid composition can be reversed, i.e. green plastids can be converted to white plastids and vice versa. Because of this phenotypic reversibility, and because of the mutant's inability to convert permanently from an all-green to an albino phenotype, Rédei called the mutant immutans (for ‘immutable’) (Rédei, 1975). Fig. 1 View largeDownload slide The spotty allele of immutans. Sectoring in immutans leaves is caused by a nuclear-recessive gene. Whereas cells in the green sectors contain normal-appearing chloroplasts, cells in the white sectors contain abnormal plastids that lack organized lameller structures. spotty is in the Columbia background (described in Wetzel et al., 1994). Fig. 1 View largeDownload slide The spotty allele of immutans. Sectoring in immutans leaves is caused by a nuclear-recessive gene. Whereas cells in the green sectors contain normal-appearing chloroplasts, cells in the white sectors contain abnormal plastids that lack organized lameller structures. spotty is in the Columbia background (described in Wetzel et al., 1994). immutans is impaired in carotenoid biosynthesis Whereas im green sectors contain a normal complement of chlorophylls and carotenoids, the white tissues accumulate phytoene, a non-coloured C40 carotenoid intermediate (Wetzel et al., 1994). This finding suggested that im is blocked at the phytoene desaturase (PDS) step of carotenoid biosynthesis. Coloured carotenoids (which are produced downstream of the PDS step) dissipate excess light energy absorbed by the light-harvesting complexes as heat, and a lack of coloured carotenoids results in photo-oxidation of the contents of the plastid under high light conditions (Demmig-Adams and Adams, 1996). Therefore, the accumulation of phytoene in im white tissues suggested that the mutant is incapable of producing enough carotenoids to avoid photo-oxidation; i.e. im is a classical carotenoid mutant. Consistent with this idea, green sector formation in im is enhanced by low-light conditions and high light intensity favours white sector formation. Map-based cloning and sequencing of IM revealed that the gene product bears similarity to mitochondrial alternative oxidase (AOX) (Carol et al., 1999; Wu et al., 1999). Alternative oxidases are inner membrane proteins that function as terminal oxidases in the alternative pathway of mitochondrial respiration by transferring electrons from ubiquinol to water using molecular oxygen as a terminal acceptor (Vanlerberghe and McIntosh, 1997). Prior to the cloning of IM, it was known that PDS activity requires several redox components, including plastoquinone and molecular oxygen (reviewed by Carol and Kuntz, 2001). Therefore the sequence similarity of IM to AOX suggested that IM is a component of the phytoene desaturation pathway and functions as a terminal oxidase by transferring electrons from the plastoquinol pool to molecular oxygen (Fig. 2). In accordance with this notion, recombinant IM protein has plastoquinol oxidase activity in vitro (Josse et al., 2000), and IM has been implicated in the transfer of electrons from PSII to molecular oxygen via the plastoquinol pool in a PSI-deficient Chlamydomonas mutant (Cournac et al., 2000). The in vitro and in vivo data thus support the idea that IM functions as a terminal oxidase, and further suggest that its role in plastid metabolism is more widespread than carotenoid biosynthesis. This will be more fully discussed later. Fig. 2 View largeDownload slide IM functions as a terminal oxidase in carotenogenesis. It is proposed that electrons from the desaturation reactions of carotenoid biosynthesis (mediated by phytoene desaturase, PDS, and zeta carotene desaturase, ZDS) are transferred to the plastoquinone pool, and that IM oxidizes this pool by transferring electrons from plastoquinol to molecular oxygen. Lack of IM, therefore, results in over-reduction of the plastoquinone pool and the subsequent accumulation of phytoene. (This figure is from Aluru and Rodermel, 2004 and is reproduced by kind permission of Blackwell Publishing.) Fig. 2 View largeDownload slide IM functions as a terminal oxidase in carotenogenesis. It is proposed that electrons from the desaturation reactions of carotenoid biosynthesis (mediated by phytoene desaturase, PDS, and zeta carotene desaturase, ZDS) are transferred to the plastoquinone pool, and that IM oxidizes this pool by transferring electrons from plastoquinol to molecular oxygen. Lack of IM, therefore, results in over-reduction of the plastoquinone pool and the subsequent accumulation of phytoene. (This figure is from Aluru and Rodermel, 2004 and is reproduced by kind permission of Blackwell Publishing.) The active site iron binding sites are essential for IM activity The resemblance of the AOX and IM sequences raises questions about the similarity of the two proteins regarding structure/function relationships. According to a recent structural model of AOX by Andersson and Nordlund (1999), the hydrophobic regions of AOX are not membrane-spanning (as originally thought), but interfacial as in other di-iron carboxylate (RNR R2) proteins. A similar model for IM has been proposed (Fig. 3) (Berthold et al., 2000; Rodermel, 2001a). According to this model, E136, E175, H178, E227, E296, and H299 serve as Fe-binding sites in the reaction centre of IM. To test this hypothesis, site-directed mutagenesis experiments were conducted in which the four E residues were mutated to A, D, or H and the two H residues were mutated to A, E, or N (A Fu and S Rodermel, unpublished data). In addition, H177, E224, and H298 were mutated to A as internal controls. The recombinant proteins were expressed in E. coli and IM activity was assayed according to Josse et al. (2000, 2003). In this assay, O2 consumption is measured in membranes isolated from E. coli that have been transformed with various mutant IM sequences. The addition to the membranes of NADH as an electron donor results in the formation of reduced quinone (by membrane-bound NADH dehydrogenase). Electrons are then transferred to molecular oxygen via IM or the cytochrome pathway. IM activity is inhibited by pyrogallol analogues, such as propyl gallate and octyl gallate, but is insensitive to cyanide. Thus, O2 consumption occurs by the cytochrome pathway in the absence of KCN, but by IM activity in the presence of KCN. KCN and n-propyl gallate (n-PG) together abolish O2 consumption. IM becomes engaged in this system only when the cytochrome pathway is blocked. Fig. 3 View largeDownload slide Structural model of IMMUTANS. IM is proposed to be an interfacial membrane protein with a di-iron centre in the active site. This figure is based on the model proposed for the mitochondrial alternative oxidase (AOX) (Berthold et al., 2000; Rodermel, 2001a). Fig. 3 View largeDownload slide Structural model of IMMUTANS. IM is proposed to be an interfacial membrane protein with a di-iron centre in the active site. This figure is based on the model proposed for the mitochondrial alternative oxidase (AOX) (Berthold et al., 2000; Rodermel, 2001a). It was found that amino acid changes in any of the six putative Fe-binding sites cause IM to lose its cyanide-resistant, propyl gallate-sensitive oxygen consumption activity (A Fu and S Rodermel, unpublished data). On the other hand, proteins with mutations in H177, E224, and H298, which are adjacent to the putative Fe-ligands, exhibit wild-type activity. These results confirm the importance of the six iron-binding sites for IM activity. These results were confirmed by in planta experiments in which the mutant IM sequences were transformed into a null allele of immutans: the six Fe ligand mutations were not able to revert the variegation phenotype to normal, whereas normal plants were obtained when im was transformed with the H177, E224, and H298 mutations. In contrast to AOX, IM has an additional 48 bp sequence (16 amino acids) located near its C-terminus. This sequence comprises all of exon 8 and is found in nearly all IM-like homologues. After expression in E. coli, the mutant protein (i.e. lacking exon 8) accumulates normally, but shows no in vitro activity (A Fu and S Rodermel, unpublished data). However, the mutant protein behaves differently in planta. Fortuitously, an allele of im that lacks exon-8 was discovered. This mutant produces normal levels of mRNA, but no IM protein accumulates. This appears to be due to turnover, inasmuch as in vitro-expressed IM that lacks the exon 8 sequence is less stable than wild-type IM following import into isolated chloroplasts. Taken together, these data suggest that exon 8 sequences are important for IM function, folding, and/or stability. IM plays a global role in plastid metabolism Previous data from light shift experiments indicated that IM is expressed early in cotyledon development (Röbbelen, 1968; Wetzel et al., 1994). During this ‘light-responsive’ phase, the phenotype of the cotyledons is irreversibly determined depending on the light environment. However, IM expression is not restricted to green tissues, as demonstrated by promoter/GUS fusion, northern, RT-PCR, and western blotting experiments. IM appears to be expressed ubiquitously in Arabidopsis tissues and organs throughout development. Consistent with these findings, the development of multiple plastid-types, including chloroplasts, amyloplasts (in roots), and etioplasts (in dark-grown seedlings) is impaired in im (Aluru et al., 2001). This raises the question of whether IM plays a global role in plastid metabolism, e.g. whether it is active in non-green tissues that do not accumulate appreciable levels of carotenoids. Carotenogenesis occurs in all plant tissues, and thus this is one possible function of IM in non-green tissues. As a notable example, carotenoids are the precursors of ABA, which is found in all tissues. Another function of IM that might not be restricted to leaves is chlororespiration (oxidation of PQ in the dark), where IM is probably the long sought-after terminal oxidase of this process. In chlororespiration, NADPH is oxidized by plastid membrane-bound NADPH dehydrogenase, generating plastoquinol; the plastoquinol is then oxidized by IM to generate water. Evidence for this role of IM has come from experiments in PSI-deficient Chlamydomonas and in tobacco that overexpress Arabidopsis IM (Cournac et al., 2000; Joet et al., 2002). In addition, IM, like the Ndh complex, is localized in the stromal lamellae where cyclic electron transfer reactions around PSI occur (Joet et al., 2002; Lennon et al., 2003). This has led to the suggestion that IM plays a role in regulating the cyclic flow of electrons around PSI. Another function of IM is as a ‘safety valve’ in photo-oxidative stress. IM protein levels increase under low light in double antisense tobacco plants lacking two hydrogen-peroxide detoxifying enzymes, catalase and ascorbate peroxidase (Rizhsky et al., 2002). IM is also induced under high light conditions in wild-type Arabidopsis and tobacco. These studies suggest that IM is involved in detoxifying excess electrons (i.e. is a ‘safety valve’). Experiments with ndh mutants have revealed that the Ndh complex plays a role in protection against photo-oxidative stress (Martin et al., 1996). Considered together, the data suggest a working hypothesis in which chlororespiratory processes are involved in photoprotection through the oxidation of stromal reductants. Altered rates of photosynthesis in im green leaf sectors Light microscopy has revealed that, except for leaves, the morphology of im organs and tissues is not altered (Aluru et al., 2001). As shown in Fig. 4, the green sectors of im are thicker than normal due to an increase in epidermal and mesophyll cell sizes, and an increase in air space volume. The white sectors have a normal thickness but the palisade cells do not expand normally. Alterations in leaf anatomy are not common in chloroplast development mutants, and such perturbations have been interpreted as due to an impairment in plastid-to-nucleus signalling pathways that impact cell and leaf differentiation. This has been observed, for example, in Arabidopsis cla1, cue1, and pac; in dcl of tomato; and in dag of Antirrhinum majus (Aluru et al., 2001; Rodermel, 2001a). Fig. 4 View largeDownload slide Leaf morphology of wild-type and im. Light microscopy was performed on sections of fully-expanded leaves from plants grown under continuous illumination. A magnification of ×25 applies to all panels. (A) Wild-type Arabidopsis, (B) green leaf sector of the spotty allele of im, (C) white leaf sector of spotty, (D) adjacent white and green leaf sectors of spotty. (This figure is from Aluru et al., 2001, copyright the American Society of Plant Biologists, and is reprinted with permission.) Fig. 4 View largeDownload slide Leaf morphology of wild-type and im. Light microscopy was performed on sections of fully-expanded leaves from plants grown under continuous illumination. A magnification of ×25 applies to all panels. (A) Wild-type Arabidopsis, (B) green leaf sector of the spotty allele of im, (C) white leaf sector of spotty, (D) adjacent white and green leaf sectors of spotty. (This figure is from Aluru et al., 2001, copyright the American Society of Plant Biologists, and is reprinted with permission.) In addition to anatomical changes, other physiological and biochemical changes have been observed in im leaves (Aluru et al., 2001). The green leaf sectors have higher than normal chlorophyll a/b ratios and increased light-dependent oxygen evolution rates under CO2-saturating conditions, when compared with the wild type. These changes/adaptations occur even in plants grown under normal light conditions. One hypothesis is that the increases in photosynthesis are a means of compensating for a lack of photosynthesis in the white sectors. For example, the green/white sectoring pattern is established early in leaf development, and it is therefore possible that im plants have a dramatic increase in sink demand since there is decreased total source area. To test this hypothesis, various aspects of photosynthesis and photosynthate partitioning in the spotty allele of immutans were measured. Figure 5 shows that im green leaf sectors have elevated rates of photosynthesis as monitored by 14CO2 uptake. These results confirm the earlier oxygen evolution data suggesting that the green sectors have elevated rates of photosynthesis (Aluru et al., 2001). The green sectors also have enhanced levels of starch and sucrose (on a chlorophyll basis) when compared with the wild-type, and they partition more newly-fixed carbon into soluble carbohydrate. Global transcription profiling and protein analyses revealed that expression of photosynthetic and carbon assimilation genes is unaltered in the green sectors, which suggests that the enhanced photosynthesis in theses sectors is not due to an up-regulation of gene expression (M Aluru and S Rodermel, unpublished data). Rather, the increases are probably due to enhanced activities and activation states of key regulatory enzymes, such as Rubisco and sucrose phosphate synthase (Fig. 6). Fig. 5 View largeDownload slide Carbon partitioning in wild-type and im. Plants were grown under continuous light (100 μmol m−2 s−1) for 3–4 weeks then labelled with 14CO2 for 10 min. After a chase in air for 10 min, the leaves were removed, ground in liquid nitrogen, and 80% ethanol-soluble and insoluble extracts were prepared. The insoluble fraction represents the flux of 14C into starch, while the soluble fraction represents flux into soluble sugars. The total incorporation is the sum of the values obtained for the soluble and insoluble fractions. im green sectors show a 2-fold increase in total 14C incorporation and partition; ∼60% into the insoluble fraction and 40% into the soluble fraction. By contrast, wild-type leaves allocate 75% of the carbon into the insoluble fraction and 25% into the soluble fraction. The spotty allele of im was used in these studies. Fig. 5 View largeDownload slide Carbon partitioning in wild-type and im. Plants were grown under continuous light (100 μmol m−2 s−1) for 3–4 weeks then labelled with 14CO2 for 10 min. After a chase in air for 10 min, the leaves were removed, ground in liquid nitrogen, and 80% ethanol-soluble and insoluble extracts were prepared. The insoluble fraction represents the flux of 14C into starch, while the soluble fraction represents flux into soluble sugars. The total incorporation is the sum of the values obtained for the soluble and insoluble fractions. im green sectors show a 2-fold increase in total 14C incorporation and partition; ∼60% into the insoluble fraction and 40% into the soluble fraction. By contrast, wild-type leaves allocate 75% of the carbon into the insoluble fraction and 25% into the soluble fraction. The spotty allele of im was used in these studies. Fig. 6 View largeDownload slide Enzyme activities of key regulatory proteins of the carbon assimilation pathway. Plants were grown under continuous illumination (100 μmol m−2 s−1). Enzyme activity assays were conducted on leaf samples from plants grown for 3–4 weeks. (A) Rubisco activity. Initial and total activities of Rubisco were measured in wild-type and im green leaf sectors. The activation state of Rubisco is the ratio of initial to total activity. The initial and total activities are elevated 1.5-fold and 1.25-fold, respectively, in the im green sectors. This results in a 25% higher Rubisco activation state (the ratio of initial to total activity). (B) Sucrose phosphate synthase activity. Vmax represents SPS activity under substrate-saturating conditions and Vsel represents activity under limiting conditions. The activation state is the ratio of Vsel to Vmax. im green sectors have both higher than normal maximal SPS activities (Vmax) and higher selective activities (Vsel). im white sectors have a higher Vmax but a lower activation state than the wild type. Fig. 6 View largeDownload slide Enzyme activities of key regulatory proteins of the carbon assimilation pathway. Plants were grown under continuous illumination (100 μmol m−2 s−1). Enzyme activity assays were conducted on leaf samples from plants grown for 3–4 weeks. (A) Rubisco activity. Initial and total activities of Rubisco were measured in wild-type and im green leaf sectors. The activation state of Rubisco is the ratio of initial to total activity. The initial and total activities are elevated 1.5-fold and 1.25-fold, respectively, in the im green sectors. This results in a 25% higher Rubisco activation state (the ratio of initial to total activity). (B) Sucrose phosphate synthase activity. Vmax represents SPS activity under substrate-saturating conditions and Vsel represents activity under limiting conditions. The activation state is the ratio of Vsel to Vmax. im green sectors have both higher than normal maximal SPS activities (Vmax) and higher selective activities (Vsel). im white sectors have a higher Vmax but a lower activation state than the wild type. In contrast to the green sectors, the white sectors of im accumulate low levels of sucrose, indicating there is a sucrose gradient between the green and white sectors (sink demand). Import of sucrose is vital to maintain metabolism in sink tissues. Plant invertases hydrolyse sucrose into glucose and fructose and are considered to contribute to sink strength by maintaining a gradient of sucrose from source to sink tissues (for reviews see Sturm, 1999; Tymowska-Lalanne and Kreis, 1998). In particular, cell wall invertases influence resource allocation between source–sink tissues and thereby control plant growth and development (Heyer et al., 2004). The white sectors of im have higher cell wall invertase activities than the green sectors (Fig. 7), which is consistent with the movement of sucrose from source to sink (M Aluru and S Rodermel, unpublished data). Although flux has not been measured directly from the im green to the im white tissues, these data are consistent with the idea that sink demand plays a role in enhancing sucrose production and partitioning in the green tissues. However, further experiments need to be performed to understand and clarify the exact mechanism(s). Fig. 7 View largeDownload slide Insoluble acid invertase activity. Activities were measured in wild-type, im green and im white sectors from plants grown under continuous illumination (100 μmol m−2 s−1). Wild-type leaves have higher cell wall acid invertase activities than mutant leaves, but activities are significantly higher in the im white versus green sectors. Fig. 7 View largeDownload slide Insoluble acid invertase activity. Activities were measured in wild-type, im green and im white sectors from plants grown under continuous illumination (100 μmol m−2 s−1). Wild-type leaves have higher cell wall acid invertase activities than mutant leaves, but activities are significantly higher in the im white versus green sectors. Mechanism of im variegation Arabidopsis im is a classic example of a variegation in which the cells of the plant have a uniform genetic constitution (i.e. mutant) but the mutant phenotype is expressed only in the white sectors: despite a lack of IM, im is variegated, not albino. How do the green sectors form? During the first critical days of seedling germination and photomorphogenesis, proplastids in the leaf meristem are converted into chloroplasts. This involves an elaboration of the thylakoid membrane, the synthesis and assembly of the photosynthetic apparatus, and an increase in chlorophyll and carotenoid biosynthesis (Mullet, 1988). Carotenoids act as photoprotective agents by quenching excess light energy absorbed by the light-harvesting complexes (Demmig-Adams and Adams, 1996). This study's working hypothesis is that IM plays a major role as an electron sink during the early events of thylakoid membrane formation when the membrane might become transiently over-reduced due to uneven production of the components of the electron transport chain. For instance, IM would be present to dissipate excess electrons in case PSII, but not PSI, were functional. Under high light conditions, a lack of IM would thus be expected to generate over-reduced membranes and toxic oxygen radicals. Without carotenoids, the developing plastid would become photo-oxidized. How can one explain the generation of a normal-appearing chloroplast in im? One possibility is that that there is a compensating IM function, for instance, a redox component downstream from the plastoquinone pool, such as the cyt b6/f complex, PSI, or even other terminal oxidases (Peltier and Cournac, 2002). Consistent with this idea is the high likelihood that there are intrinsic differences in the rates of the various reactions involved in light capture versus use. As Niyogi (1999) points out, photoprotection is a ‘balancing act’ comprised of many different activities. It is therefore speculated that im plastids can tolerate high light below a certain threshold of these activities, but that above this threshold, photodamage occurs. The crucial element of this model is that the threshold varies from plastid-to-plastid. For instance, some plastids have more or less of the compensating activity, or of some other photoprotective activity, with the net result being a heterogeneity of light damage from plastid-to-plastid. Regardless of precisely how chloroplasts form, it is assumed that variegation per se is a consequence of the sorting-out of white versus green plastids early in leaf development (Tilney-Bassett, 1978). At this stage of development, chloroplast divisions occur concomitantly with cell division and cell elongation (Mullet, 1988). Although the responsible mechanisms are obscure, it is thought that this process also involves the parcelling of different plastid types into different cells. This might be a random or directed process. Nevertheless, the net consequence of this sorting-out process is the formation of sectors, which represent clones of cells containing either all-green or all-white plastids. Once the process of plastid division has ceased (well before the attainment of full leaf expansion), plastid- and cell-type are fixed and cannot be reversed. Only nascent daughter plastids have the potential of changing their state, depending on the existing conditions that either promote or inhibit photodamage. var2 The Arabidopsis yellow variegated mutant was isolated by Rédei in the 1950s (GP Rédei, personal communication). It was initially thought this mutant might be an allele of im, but it was found, instead, that it is allelic to another Arabidopsis variegation mutant, var2 (Martínez-Zapater, 1993). Like im, var2 is caused by a nuclear recessive gene mutation and has green- and white-sectored leaves (Chen et al., 1999; Takechi et al., 2000). Also like im, cells in the green sectors of var2 have normal-appearing chloroplasts, while plastids in the cells of the white sectors are vacuolated, lack organized membrane structures, and contain a large number of plastoglobuli-like bodies. Yet, some cells in the white sectors of these mutants are heteroplastidic and contain plastids in various developmental stages, including plastids resembling normally developed chloroplasts (Chen et al., 1999). Such ‘plastid autonomous’ behaviour is also found in im (Wetzel et al., 1994). In contrast to im, the cotyledons of var2 are not variegated. Map-based procedures were used to clone VAR2 and it was found that it encodes a homologue of FtsH, an ATP dependent metalloprotease (Chen et al., 2000). A T-DNA tagged allele of VAR2 has also been reported (Takechi et al., 2000). VAR2 (also designated AtFtsH2) is predicted to contain two transmembrane-spanning domains in its N-terminus and a large C-terminus that contains functional domains for ATP- and metal- binding (described below). Consistent with a membrane localization, chloroplast import assays have demonstrated that VAR2 is targeted to thylakoid membranes with its large C-terminus facing the stroma (Chen et al., 2000). FtsH gene family The ftsH (filamentation temperature sensitive) gene was first identified in E. coli (Ogura et al., 1997). It encodes a plasma membrane-bound metalloprotease. FtsH is a member of the large and diverse AAA (ATPase associated with diverse cellular activities) protein family. All members of this family contain either one or two conserved 200–250 amino acid ATP-binding domains (termed the ‘AAA cassette’) that contain several well-conserved regions including Walker A, Walker B, and ‘second region of homology’ (SRH) (Beyer, 1997). FtsH proteins contain a single AAA cassette in their C-terminus. Also in the C-terminus is a conserved zinc-binding domain (HEXXH). It is thought that these functional regions impart chaperone and protease activity to the enzyme. All FtsH proteins appear to be localized to membranes. FtsH was first identified in higher plants when an E. coli FtsH antibody was used to detect a western blot signal corresponding to a protein of the expected size of E. coli FtsH in spinach chloroplasts. An FtsH-like cDNA was subsequently isolated in Arabidopsis (designated AtFtsH1) (Lindahl et al., 1996). FtsH genes have been found to be present as a multigene family in all prokaryotic and eukaryotic photosynthetic organisms examined. For example, for those species whose genomes have been sequenced, the cyanobacterium Synechocystis sp. PCC 6803 contains four FtsH genes (Kaneko et al., 1996); at least nine FtsH genes are present in the rice genome (Yu et al., 2005); and in Arabidopsis thaliana there are 12 FtsH genes (Sokolenko et al., 2002; Sakamoto et al., 2003; Yu et al., 2004). Of the 12 Arabidopsis genes, eight comprise four highly-conserved gene pairs (AtFtsH1/5, AtFtsH2/8, AtFtsH3/10, AtFtsH7/9) (Sakamoto et al., 2003; Yu et al., 2004), while AtFtsH4 and AtFtsH11 are also related to a much lesser degree. Nine of the 12 FtsH gene products are located in chloroplasts (AtFtsH1/2/6/7/8/9/11/12) and three are targeted to mitochondria (AtFtsH3/4/10) (Chen et al., 2000; Sakamoto et al., 2002, 2003; Yu et al., 2004). Phylogenetic comparisons of the structures and protein sequences of rice and Arabidopsis FtsH genes revealed that a ‘core’ complement of FtsH genes existed before the monocot/dicot divergence (Yu et al., 2005; Fig. 8). The subsequent evolution of these genes was characterized by extensive gene duplication, especially in Arabidopsis (Vision et al., 2000). Fig. 8 View largeDownload slide Phylogenetic analysis of FtsH proteins from Arabidopsis, rice, and Synechocystis sp PCC6803. AtFtsHX numbers represent Arabidopsis proteins and OsFtsHX numbers represent rice proteins. Full-length protein sequences were used to construct the phylogenetic tree. (This figure is from Yu et al., 2005, copyright the American Society of Plant Biologists, and is reprinted with permission.) Fig. 8 View largeDownload slide Phylogenetic analysis of FtsH proteins from Arabidopsis, rice, and Synechocystis sp PCC6803. AtFtsHX numbers represent Arabidopsis proteins and OsFtsHX numbers represent rice proteins. Full-length protein sequences were used to construct the phylogenetic tree. (This figure is from Yu et al., 2005, copyright the American Society of Plant Biologists, and is reprinted with permission.) FtsH function in plants In E. coli, FtsH has both chaperone and protease activities and is involved in the degradation of a variety of protein substrates (Suzuki et al., 1997). In higher plants, FtsH appears to be involved in the degradation of unassembled cytochrome b6f Rieske FeS proteins in thylakoid membranes (Ostersetzer and Adam, 1997), as well as in the N-gene-mediated hypersensitive reaction against tobacco mosaic virus infection in tobacco (Seo et al., 2000). FtsH proteins might also participate in membrane fusion and/or translocation events since the pepper Pftf (Plastid fusion and/or translocation factor) protein shares high similarity with FtsH (Hugueney et al., 1995). However, the best characterized function of FtsH is its involvement in photosystem II (PSII) photodamage and repair (Nixon et al., 2005). It is well-documented that the D1 reaction centre protein of PSII is the target of reactive oxygen species formed during photosynthesis, and that photodamaged D1 is turned-over and replaced by a newly-synthesized copy. Evidence that FtsH is involved in the D1 turnover process was first published by Lindahl et al. (2000), and it is now thought that turnover is a two-step process in plants: (i) the photodamaged D1 protein (∼32 kDa) is cleaved by DegP2, a serine protease, into a 23 kDa fragment and an ∼9 kDa fragment (Haußühl et al., 2001); and (ii) the 23 kDa fragment is degraded by AtFtsH1. However, it seems that the absence of DegP2 activity in Synechocystis does not lead to the inhibition of D1 turnover, suggesting that FtsH itself might be sufficient for the turnover process in this species (Nixon et al., 2005). In addition to AtFtsH1, AtFtsH2 and AtFtsH5 might be involved in D1 turnover inasmuch as var2 and var1, an Arabidopsis variegation that is due to a mutation in the nuclear gene for another chloroplast FtsH homologue, AtFtsH5 or VAR1 (Sakamoto et al., 2002), are more prone to PSII photoinhibition, and the D1 degradation process is impaired in var2 (Bailey et al., 2002). Interestingly, an insertional mutant of slr0228, one of the four FtsH genes in Synechocystis, exhibits impaired D1 turnover, suggesting that involvement of FtsH in D1 turnover is conserved in both prokaryotic and eukaryotic photosynthetic organisms (Silva et al., 2003). However, the same mutant also shows a significant reduction in the amount of photosystem I, something not seen in the higher plant AtFtsH mutants (Mann et al., 2000). This reduction might be a secondary effect of impaired D1 turnover, or it might suggest that, at least in Synechocystis, FtsH has a more general role in the maintenance of photosynthetic membranes. FtsH oligomeric complex formation in chloroplast thylakoid membrane In E. coli, FtsH forms homocomplexes (Akiyama et al., 1995) and heterocomplexes with HflK/C (Kihara et al., 1996). In plants, higher molecular weight complexes containing chloroplast FtsH have also been observed when thylakoid membranes are fractionated by gel filtration, or by sucrose gradient centrifugation and two-dimensional green gels (Sakamoto et al., 2003; Yu et al., 2004, 2005). Sakamoto et al. (2003) have also shown by co-IP that AtFtsH2 and 5 might directly interact with each other and that AtFtsH2 might form homocomplexes. However, the results of these studies are difficult to interpret because polyclonal antibodies were used that detect multiple isoforms. The stability of the AtFtsH2/8 pair and the AtFtsH5/1 pair are mutually-dependent because the levels of AtFtsH2 and AtFtsH5 are co-ordinately reduced in amount in var1 and var2 mutants (Yu et al., 2004). Using two-dimensional green gel analysis, it was possible to detect two AtFtsH-containing bands that migrate close to one another on second dimension gels (SDS-PAGE) containing Arabidopsis thylakoid membrane proteins. Four AtFtsH proteins could be identified in the two protein bands by mass spectrometry: an upper band that contains AtFtsH1 and 5 and a lower band that contains AtFtsH2 and 8. These two bands are co-ordinately decreased in amount in var2 and var1. Because these reductions occur post-translationally, the data are consistent with the idea that proteins in each band interact with one another and that excess subunits are turned over (Yu et al., 2004). Using an AtFtsH1-specific antibody and an AtFtsH2 polyclonal antibody (which detects AtFtsH2 and AtFtsH8), it was found by co-IP that AtFtsH1 interacts with AtFtsH2/8 (Yu et al., 2005). This suggests that interactions occur between the proteins in each of the two bands. A recent report using isoelectric focusing in the first dimension and SDS–PAGE in the second dimension identified the same four AtFtsH proteins from Arabidopsis thylakoid membranes as were identified on the two-imensional green gels (Sinvany-Villalobo et al., 2004). GFP-tagging has also shown that these four proteins are targeted to thylakoids (Sakamoto et al., 2003). Taken together, these data support the notion that there are at least four FtsH proteins located in chloroplast thylakoid membranes. Mechanism of var2 and var1 variegation One of the most intriguing features of var2 is its variegation phenotype. As with im, how can one explain the formation of green sectors in a uniform genetic background (i.e. var2/var2)? Similar to im, early explanations for this centred on the notion of compensating activities (Chen et al., 2000; Rodermel, 2001). These have now been refined and a model has been presented that is based on the finding that AtFtsH is a multigene family (Yu et al., 2004, 2005). This model is described below. A similar mechanism cannot be formulated for IM, which is a single gene in Arabidopsis. Model The closest homologue of AtFtsH2 is AtFtsH8 (∼90% amino acid identity) (Yu et al., 2004; Sinvany-Villalobo et al., 2004). To test whether AtFtsH8 is able to compensate for AtFtsH2, AtFtsH8 cDNA was overexpressed in var2 (Yu et al., 2004). It was found that the var2 variegation phenotype was abolished in the transgenic plants, and that normal-appearing plants were generated. This suggests that AtFtsH8 is able to replace the activity of AtFtsH2 in chloroplasts. As mentioned above, two-dimensional green gel analyses revealed that ‘upper’ and ‘lower’ AtFtsH-containing bands are co-ordinately reduced in amount in var2. Similar analyses of the overexpression plants showed that levels of both bands were restored back to wild-type levels. This suggests that AtFtsH8 is able to replace AtFtsH2 in thylakoid membrane AtFtsH complexes. Based on these observations, a model was proposed to explain the mechanism of var2 variegation (Yu et al., 2004; Fig. 9). In this model, two pairs of FtsH proteins, AtFtsH1 and 5 and AtFtsH2 and 8, form oligomeric complexes in the thylakoid membrane and a threshold level of complexes is required for normal chloroplast function and green sector formation. When complex levels fall below the threshold, chloroplast function will be impaired and white sectors form. It was also proposed that proteins within each pair are interchangeable and that the abundance of proteins in each pair is matched with that of the other pair, with excess subunits being turned over post-translationally. Thus, overexpression of AtFtsH8 in var2 will result in a ‘lower band’ containing normal AtFtsH protein levels, and this will serve to stabilize AtFtsH1 and 5 in the ‘upper band’. Fig. 9 View largeDownload slide Mechanism of var2 variegation (from Yu et al., 2004 and reproduced by kind permission of Blackwell Publishing). Fig. 9 View largeDownload slide Mechanism of var2 variegation (from Yu et al., 2004 and reproduced by kind permission of Blackwell Publishing). In further support of the model, the level of AtFtsH1 was manipulated in var1, which lacks AtFtsH5 (Yu et al., 2005). As with var2, the upper and lower AtFtsH-containing bands were co-ordinately reduced in amount in var1. In agreement with the model, the var1 variegation was rescued by AtFtsH1 overexpression, and AtFtsH2 and 8 protein levels were restored to wild-type levels. Recent overexpression and antisense experiments have revealed that AtFtsH1 and AtFtsH5 share redundant functions, like AtFtsH2 and AtFtsH8 (Yu et al., 2005). All four genes also have similar expression patterns as revealed by RT-PCR and promoter–GUS fusion gene studies: all four are predominantly expressed in green photosynthetic tissues (Yu et al., 2004, 2005). However, overexpression of AtFtsH2 failed to rescue the var1 variegation. This suggests that the two pairs of FtsH proteins might play distinct structural or functional roles. It has been reported that AtFtsH1, 2, 5, and 8 are expressed at different levels with AtFtsH2 being the most abundantly expressed, followed by AtFtsH5, AtFtsH1, and AtFtsH8 at both the transcript and protein levels (Sinvany-Villalobo et al., 2004). These quantitative differences in gene expression correlate well with the mutant phenotypes: var2 has the highest degree of variegation; var1 is only slightly variegated; and mutants of AtFtsH1 and AtFtsH8 resemble the wild type and do not display any variegation (Sakamoto et al., 2003; F Yu and S Rodermel, unpublished data). The rationale underlying these differences in expression is not clear. However, one possibility is that AtFtsH gene expression is optimized to achieve high protein concentrations in the chloroplast, similar to the proposed rationale for the proliferation of the rbcS (Rubisco small subunit) gene family (Rodermel, 1999). In the case of AtFtsH, this would allow complex formation to occur that is above the threshold required for normal chloroplast function. var2 suppressor screening To gain a better understanding of FtsH function and the mechanism of var2 variegation, a second-site suppressor screen was carried out to isolate mutants that modify the var2 variegation phenotype. One normal-appearing, non-variegated suppressor was identified and cloned by map-based methods (Park and Rodermel, 2004). The responsible gene was found to be ClpC2, which encodes a class 1 Hsp100 chaperone, containing two conserved ATP-binding domains. ClpC2 is located in the chloroplast stroma. Suppression of variegation is expressed in nuclear recessive plants (i.e. clpC2/clpC2). The single mutant plants do not have a visible phenotype, but they have vastly reduced levels of ClpC2 due to a splice site mutation in ClpC2. clpC2 and var2 act antagonistically, and thus it was suggested that whereas VAR2 promotes thylakoid membrane biogenesis, ClpC2 normally serves to suppress this process, perhaps by enhancing photo-oxidative stress while the photosynthetic apparatus is being assembled. Further characterization of this mutant and other suppressor lines will help us to understand the mechanisms of variegation and the regulation of chloroplast development. 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Carrari, Fernando;Fernie, Alisdair R.

doi: 10.1093/jxb/erj020pmid: 16449380

Abstract The development and maturation of tomato fruits has received considerable attention because of both the uniqueness of such processes to the biology of plants and the importance of these fruits as a component of the human diet. Molecular and genetic analysis of fruit development, and especially ripening of fleshy fruits, has resulted in significant gains in knowledge over recent years. A large amount of knowledge has been gathered on ethylene biosynthesis and response, cell wall metabolism, and environmental factors, such as light, that impact ripening. Considerably less attention has been paid directly to the general metabolic shifts that underpin these responses. Given the vast complexity of fruit metabolism, the focus chosen for this review is on primary metabolites and those secondary metabolites that are important with respect to fruit quality. Here, recent advances in dissecting tomato metabolic pathways are reviewed. Also discussed are recent examples in which the combined application of metabolic and transcriptional profiling, aimed at identifying candidate genes for modifying metabolite contents, was used. Development, fruit metabolism, ripening, Solanum, tomato Introduction Fruits are not only colourful and flavoursome components of human and animal diets, but they are also an important source of minerals, vitamins, fibres, and antioxidants in food and animal feed. For this reason a fuller comprehension of the biosynthetic pathways for the production of these nutrients is of applied as well as fundamental importance. Whilst plant model systems such as Arabidopsis may be a suitable starting point in the search for key regulatory mechanisms acting in fruit development and ripening (Liljegren et al., 2004), it must be borne in mind that the term ‘fruit’ encompasses an enormous diversity of different kinds of organs. Thus, although fundamental development processes might be shared among different plant species, this cannot be blithely assumed. Indeed there are dramatic developmental differences across species, even in those of the same family (Fernie and Willmitzer, 2001). This fact is one of the main reasons that considerable effort is being put into genomic and post-genomic study of plant species other than Arabidopsis (Goff et al., 2002; Carrari et al., 2004; Desbrosses et al., 2005; Mueller et al., 2005). One example of this is the use of tomato (Solanum lycopersicum), as a model system for plants bearing fleshy fruits. Several features of the tomato fruit make it a highly interesting system to study, all of them linked to the dramatic metabolic changes that occur during development. Tomato fruit follows a transition from partially photosynthetic to true heterotrophic metabolism during development by the parallel differentiation of chloroplasts into chromoplasts and the dominance of carotenoids and lycopene on ripening. This review will start by detailing briefly the recent advances in our understanding of the hormonal and genetic control of the ripening process that has been facilitated by the adoption of molecular genetic approaches (Vrebalov et al., 2002; Giovannoni, 2004), before focusing exclusively on metabolism. The rationale behind this is that whilst there are several excellent reviews in the field of genetic/hormonal control of ripening (Adams-Phillips et al., 2004; Giovannoni, 2001, 2004) and on the temporal regulation of specific areas of metabolism [for example, cell wall (Hadfield and Bennett, 1998; Rose et al., 2004b) or pigments (Hirschberg, 2001)], a broad synthesis of the metabolic changes that underlie ripening has not been attempted recently. Whilst the majority of this article will concentrate on central carbon metabolism, since this is the subject of the majority of the authors' own research, it is also intended to document progress in the understanding of metabolic regulation of the secondary metabolites of importance to fruit quality. These include vitamins, volatiles, flavonoids, and pigments in addition to the major plant hormones. The interrelationship of these compound types is presented in Fig. 1. Given the recent development of tools that allow comprehensive phenotyping of the cell (Alba et al., 2004; Fei et al., 2004; Fernie et al., 2004a; Rose et al., 2004a), it is now possible to access vast datasets at the level of transcript abundance (Alba et al., 2004; Fei et al., 2004), protein abundance (Rose et al., 2004a), metabolite accumulation (Roessner-Tunali et al., 2003; Fernie et al., 2004a), and metabolic flux analysis (Roessner-Tunali et al., 2004). In conclusion, recent applications of multi-level phenotyping (Urbanczyk-Wochniak et al., 2003; Hirai et al., 2004) will be described and the likely outcome of taking such an approach detailed to understand better the metabolic regulation underlying tomato fruit development. Fig. 1 View largeDownload slide Interrelationships of primary and secondary metabolism pathways leading to the biosynthesis of aroma volatiles, hormones, pigments, and vitamins. Fig. 1 View largeDownload slide Interrelationships of primary and secondary metabolism pathways leading to the biosynthesis of aroma volatiles, hormones, pigments, and vitamins. Genetic and hormonal control of fruit development As mentioned in the Introduction, the Arabidopsis model system has served as a starting point in the identification of genes influencing fruit development. In this vein, a gene family that has received considerable attention is that encoding MADS-box proteins (for a review, see Giovanonni, 2004). These floral homeotic genes are key determinants of carpel development. While many of these genes are highly represented in the large collection of the available expressed sequence tags for tomato (http://www.tigr.org/tdb/tgi/lgi and http://www.sgn.cornell.edu), only a few of them are specifically expressed at fruit development and at later stages, including ripening and senescence. An example of this is the rin locus, mutation at which affects all aspects of the tomato fruit ripening process. Molecular cloning of the rin locus revealed tandem MADS box genes separated by 2.6 kb of intervening genomic DNA but only one of them was necessary for ripening (Vrebalov et al., 2002). A phenotypically similar mutant in terms of responsiveness to ethylene was characterized and named nor (non-ripening) (Lincoln and Fisher, 1988). Further genetic analysis showed that these two mutations reside in two different unlinked loci (Giovannoni et al., 1995); however, despite the fact that nor encodes a transcription factor (Giovannoni et al., 2001), the exact molecular mechanism of its operation remains unknown. Other fruit-ripening mutants identified on the basis of their insensitivity to ethylene are Never ripe (Nr) (Lanahan et al., 1994), green ripe (Gr), and Never ripe 2 (Nr2) (Barry et al., 2005). Since the first demonstration that the Nr locus encodes an ethylene receptor (Wilkinson et al., 1995) a broad gene family of receptors has been cloned and their expression analysed in several species (for a review, see Adams-Phillips et al., 2004). However, the analysis of transgenic plants with reduced Nr levels showed that this gene is not necessary for the ripening programme to proceed (Hackett et al., 2000), suggesting that the other fruit-specific member of the receptor family can compensate for its deficiency (Tieman et al., 2000). A further mutant worthy of mention is colourless non-ripening (Cnr), which results in mature fruits with colourless pericarp tissue showing excessive loss of cell adhesion (Thompson et al., 1999). Subsequent studies using PCR and biochemical analyses demonstrated that the expression and activity of a wide range of cell wall-degrading enzymes was altered in cnr during development and ripening. Further micro-array experiments demonstrated that the Cnr mutation had a profound effect on many aspects of ripening-related gene expression. The programme of gene expression in Cnr resembles, to some degree, that found in dehiscence or abscission zones, prompting speculation that there is a link between events controlling cell separation in tomato, a fleshy fruit, and those involved in the formation of dehiscence zones in dry fruits (Erickson et al., 2004). Although the Gr and Nr2 spontaneous mutants were identified in the early 1980s (Kerr, 1981, 1982; Jarret et al., 1984), it was only recently that they were physiologically characterized (Barry et al., 2005). As in the case of the Nr mutant, the reduction in the rate of ripening exhibited by Gr and Nr2 also results from a decreased ethylene sensitivity of the fruits. However, as observed in Cnr, this phenotype was found to be extended to other unrelated ripening processes such as floral senescence, abscission, and root elongation. By genetic mapping these loci were found to be tightly linked on the long arm of chromosome 1. These results, when taken together with the similar dominant phenotypes of the mutants, suggest that they might be allelic; however, the molecular identities of Gr and Nr2 genes remain unknown. As with other aspects of tomato fruit biology, the quantitative trait loci (QTL) approach has contributed to the definition of important characteristics of the tomato fruit development process. The first cloned QTL affecting tomato fruit weight (fw2.2) was dissected using a very well-characterized population of tomato near isogenic lines (Alpert and Tanksley, 1996). The open reading frame contained in this locus was predicted to encode a protein homologue to a human RAS oncogene (Frary et al., 2000), specifically expressed at pre-anthesis in floral organs. A recent analysis of transgenic tomato plants carrying an artificial gene dosage series confirmed this gene to be a negative regulator of pericarp cell division (Liu et al., 2003). Climacteric fruits such as tomato are distinguished from non-climacteric by their increased respiration and ethylene biosynthesis rates during ripening. This is one of the main reasons that the majority of biochemical research has concentrated on this hormone. Initial molecular studies focused on the isolation of ethylene-regulated genes which include those encoding the ethylene biosynthesis enzymes (S-adenosylmethionine, SAM-synthase, 1-aminocyclopropane carboxylic acid, ACC-synthase, and ACC oxidase), and cell wall-disassembling enzymes such as endo-polygalacturonase and pectin methylesterase (PME) (reviewed by Redgwell and Fischer, 2002). It was later demonstrated, using the reverse genetic approach, that either lowering the amount of ethylene produced or delaying its production constituted a successful strategy to extend the shelf-life of fruits (Grierson, 1992). Moreover, the inhibition of ethylene biosynthesis in melon fruits by down-regulation of ACC oxidase has produced plants with improved flavour as the fruits could be left on the plants for longer before harvest (Ayub et al., 1996). Biochemical evidence suggests that ethylene production may well be influenced or regulated by interactions between its biosynthesis and other metabolic pathways. One such example is provided by the fact that S-adenosylmethionine is the substrate for both the polyamine pathway and nucleic acid methylation; the competition for substrate was demonstrated by the finding that the overexpression of a SAM hydrolase has been associated with inhibited ethylene production during ripening (Good et al., 1994). On the other hand, the methionine cycle directly links ethylene biosynthesis to the central pathways of primary metabolism. A cummulative body of genetic and biochemical evidence led Klee (2002) to propose a model for ethylene perception and metabolism. As the receptor also acts as a negative regulator of downstream responses, in the absence of ethylene, receptors actively suppress expression of ethylene responsive genes. Consistent with this model, a reduction in the overall level of receptor increases ethylene responsiveness of a tissue, while higher expression of receptor decreases ethylene sensitivity. This model is supported by the fact that loss-of-function receptor mutants also exhibit a similar responsiveness level as wild-type plants, since they have lost the active suppression of response to ethylene. Recently, several further ethylene-inducible genes have been identified in tomato, including mitochondrial translation elongation factors (Benichou et al., 2003) and CTR-1 (Leclercq et al., 2002; Adams-Philips et al., 2004). It seems likely, given the development of micro-array resources for tomato, that significant advances will be made in understanding signal transduction following ethylene perception. Examples of this have already been started by using the first tomato cDNA micro-array containing 12 000 unique elements encoding 8500 genes covering a range of metabolic and developmental processes (http://bti.cornell.edu/CGEP/CGEP.html) (Fei et al., 2004; Baxter et al., 2005b). In comparison with ethylene, very little is known about the role of other hormones in fruit development. The role of auxins has been extensively investigated in other fruits such as strawberry (Manning, 1994) and grape berries (Davies et al., 1997). In tomato, the fact that several expansins encoding genes are expressed during fruit development, and that they are regulated by auxins in other plant organs, led to the postulate that auxins are part of the hormonal signalling transduction network controlling cell expansion in tomato fruit (Catala et al., 2000). This hypothesis is further supported by the fact that the auxin concentration in tomato fruits peaks well before the onset of ripening [approximately at 10 d after anthesis (DAA)] coincident with a higher expression of fruit-specific expansin genes (Gillaspy et al., 1993). More recently, Balbi and Lomax (2003), by means of a thorough characterization of a set of the auxin-resistant mutants dgt, have proposed a cross-talk model of auxin responsiveness and ethylene biosynthesis at very early stages of fruit development. This finding opens a new route that merits further investigation to test whether this has implications in determining the final fruit size. Central carbon metabolism To analyse metabolism proper it seems sensible to begin with the major carbohydrates, since this class of compounds comprises the most abundant and widely distributed food components derived from plants. Carbohydrate contents vary greatly in fresh tomato fruits depending on two main factors: the environmental conditions during development and ripening; and the cultivar in question. Most modern tomato varieties are derived from the domestication of the Peruvian wild cherry types, brought to Mexico by pre-Hispanic civilizations and spread over Europe in the sixteenth century (Luckwill, 1943). Since this fruit was initially used as a dessert, selection was orientated to sweetness with sugars representing up to 60% of the total dry weight. Sucrose, glucose, and fructose are the major sugars found in tomato fruits with high hexose accumulation being characteristic of domesticated tomato (Solanum lycopersicum), whereas some wild tomato species (i.e. S. chmielewskii) accumulate mostly sucrose (Yelle et al., 1991). Together with quinic and citric acid, these compounds are the principal quality components for ‘ketchup’ tomatoes, determining the soluble solid content or Brix index. The variance in relative levels of sucrose and hexoses is most likely due to the relative activities of the enzymes responsible for the degradation of sucrose – invertase and sucrose synthase. However, any discussion on sucrose metabolism in the fruit should begin by detailing the route by which carbon enters the fruit. This is, however, currently somewhat contentious since, although it has previously been suggested that unloading of sucrose occurs symplastically in the tomato pericarp until 14 DAA, following which it is unloaded apoplastically (Ruan and Patrick, 1995), recent results suggest a role for apoplastic unloading at a much earlier time point. The genetic bases of the sucrose-accumulation trait of the wild species tomato has been highly studied by means of introgressing wild germplasms into domesticated cultivars (Yelle et al., 1991; Fridman et al., 2000, 2004), and a role for an apoplastic invertase in regulating sucrose metabolism in tomato fruits has long been postulated. It was, however, not until recently that Fridman et al. (2004) provided conclusive evidence of the importance of this enzyme, by demonstrating that variance in its kinetic properties was the mechanistic explanation underlying a moderate QTL for Brix identified in a population derived from the cross S. lycopersicum×S. pennellii (Eshed and Zamir, 1995; Fridman et al., 2000). Previous to this study, map-based cloning had been used to delimit this QTL to a 484 bp region of the apoplastic invertase gene Lin5 (Fridman et al., 2000). Although the expression pattern of this enzyme suggested that it was restricted to fruits and flowers (Fridman and Zamir, 2003), the exact reason for the Brix effect was unclear from these studies. Analysis of introgression lines from other wild species tomatoes, however, revealed a single nucleotide polymorphism that correlated with increased Brix (Fridman et al., 2004). Utilizing complementation assays in an invertase-deficient yeast strain it was possible to demonstrate that the wild allele had a far greater affinity for sucrose (Fridman et al., 2004), most probably due to the proximity of the single nucleotide polymorphism to the fructosyl binding site of the protein (Alberto et al., 2004). Other lines of evidence also support the role of this enzyme in regulating the sugar composition in tomato fruits and suggest that changes in composition contribute to alterations in fruit size. Utilizing the reverse genetic approach, Klann et al. (1996) reported that invertase antisense plants had increased sucrose and decreased hexose sugar concentrations in the fruits and 30% smaller fruits than those from control plants. Interestingly, a role for apoplastic invertase in the control of sink size has also been postulated previously in other species, the heterologous expression of yeast invertase in the potato tuber amyloplast resulting in dramatically increased yield, whereas the apoplastic invertase-deficient miniature1 mutant of maize exhibits a dramatically decreased seed size (Miller and Chourey, 1992; Sonnewald et al., 1997). A detailed biochemical characterization of vegetative and fruit tissues of the introgression line carrying the Lin5 wild allele (IL9-2-5) and harbouring the moderate Brix QTL, was recently reported by Baxter et al. (2005a). The finding in this work of an increased capacity of IL to take up sucrose from the phloem adds physiological support to the conclusions drawn by Fridman et al. (2004) concerning the key role played by the apoplastic invertase LIN5. Moreover, the fact that this line accumulates significantly more starch in both pericarp and columella tissues contributes new evidence on the importance of starch accumulation as a factor determining the soluble solids content of mature fruit (Dinar and Stevens, 1981; Schaffer and Petreikov, 1997). The other enzyme with a proposed central role in developing tomato fruits is sucrose synthase (SuSy). D'Aoust et al. (1999), assessed the specific role of this enzyme in growing tomato fruits by means of silencing a fruit-specific isoform and found that, unlike in other sink organs [i.e. maize endosperm (Chourey and Nelson, 1978) or potato tuber (Zrenner et al., 1995)], SuSy activity was not essential for starch synthesis. However, its inhibition leads to a reduced unloading capacity of sucrose in the initial stages of fruit development (7 DAA) but only a small effect from 23 DAA onwards when ripening starts to take place. The influence of SuSy in the carbon metabolism of the fruit during the earliest stages of development runs in parallel with the highest demand for hexose phosphates (Roessner-Tunali et al., 2003), the rapid accumulation of starch and the highest levels of ADP-glucose pyrophosphorylase activity (Beckles et al., 2001). Thus, the reduced fruit size observed in the SuSy antisense plants may be explained, at least in part, by a reduction in starch degradation during the early stages of the fruit development. Unfortunately, however, this explanation remains speculative since no data on the starch contents in these fruits are provided during this period (D'Aoust et al., 1999). It should also be noted that these results were not reproduced in an independent transformation carried out by a different research group (Chengappa et al., 1999), who found little evidence for such an important role for SuSy in fruit metabolism and development. Furthermore, by marked contrast to the invertases, the only isoforms of sucrose synthase to have been mapped on the tomato genome to date do not co-localize with important agronomic QTL such as fruit size and total soluble solid content (Causse et al., 2004). The use of introgression lines and other permanent genetic resources incorporating the diversity inherent in wild germplasm described here mirrors a broad and increasing interest in analysing the biological properties of natural genetic diversity (Maloof, 2003; Koornneef et al., 2004). In addition, it further highlights the enormous potential of exotic germplasm as a source for the improvement of agriculturally important traits (Zamir, 2001). Another recent example of this is provided by a comprehensive comparative analysis of the metabolite composition in leaves and fruits from six tomato species reported by Schauer et al. (2005). This study revealed that there is a tremendous variance in both leaves and fruits of the wild species analysed with respect to the sugar content, as well as dramatic changes in amino acid composition and secondary metabolite levels. However, somewhat surprisingly, the levels of the TCA cycle intermediates are invariant across the species. The reported changes in sugar levels are in close agreement with the above-mentioned results reporting high variability in invertase activities in fruits of wild species tomatoes (Yelle et al., 1991; Fridman et al., 2004), whilst those in other metabolites may be explained by adaptation to the various ecological niches that the wild species are found in. Given that these species can be readily crossed, this dataset provides an interesting inventory that may eventually prove useful in the selection of breeding material as an alternative to current transgenesis-based metabolic engineering strategies (Carrari et al., 2003a). In an ongoing project in our laboratories we are analysing the metabolite contents of the 76 introgression line population harbouring segments of the entire S. pennellii genome in the background of the elite processing cultivar M82 (Eshed and Zamir, 1995). Once complete, this will allow the identification of QTL for a wide range of metabolites, including those of nutritional and organoleptic importance. Such studies have been carried out previously, albeit on a smaller scale, and a handful of metabolite QTL including sugars and organic acids have been determined (Causse et al., 2002, 2004; Fulton et al., 2002; Lecomte et al., 2004). It is likely, given the tomato sequencing project (Mueller et al., 2005,a, b) and the current interest in the broad phenotyping of natural variance in crop species (European Plant Science Organisation, 2005), that such approaches will play a major role in the elucidation of key regulators of fruit metabolism. As a first experiment in this direction, an established metabolic profiling method (Roessner et al., 2001) was optimized for tomato tissues and then, utilizing this method in combination with different analytical technologies (including conventional spectrophotometric and liquid chromatography) and statistical tools, the metabolite composition in developing tomato fruits was catalogued and evaluated (Roessner-Tunali et al., 2003). Through the analysis of over 70 primary metabolites it was possible to differentiate three developmental stages of the fruits (green, orange, and red) and follow the influence of hexose phosphorylation through fruit development by analysing transgenic plants constitutively overexpressing an Arabidopsis hexokinase (AtHXK1). The changes observed in metabolite levels during ripening of the wild-type fruit were broadly similar to those previously reported for less extensive metabolic surveys (Boggio et al., 2000; Chen et al., 2001), with the major changes between green and red fruit contents summarized in Fig. 2. As illustrated, there is a large increase in the major hexoses, glucose and fructose, in the cell wall components, and in the aromatic amino acids and aspartate, lysine, methionine, and cysteine, and, as expected, in all the pigments other than chlorophyll. By contrast, almost all of the TCA intermediates decrease in the red fruits, as well as sucrose, hexose phosphates, and most of the sugar alcohols. Although the point-by-point analysis of the changes of specific metabolites over developmental time was highly interesting, two main conclusions emerged from this study: (i) that tomato fruits of different developmental stage can be distinguished from one another on the basis of their metabolic complement alone; and (ii) that the influence of hexose phosphorylation on primary metabolism diminishes markedly over developmental time. At the same time a similar dataset was produced on the same transgenic plants (Menu et al., 2004) from which similar conclusions can be drawn. Fig. 2 View largeDownload slide Schematic representation of the metabolic changes occurring in the transition from development to ripening processes in tomato fruits. Sugars, sugar-phosphates, sugar-alcohols, amino and organic acids, pigments, and cell wall components were determined in pericarps of tomato samples taken from 30 d until 60 d after anthesis (DAA). Names of metabolites in orange, green, and grey indicate increased, decreased, and no changes, respectively, in the levels of the corresponding metabolite at 60 DAA with respect to 30 DAA. Names in white letters indicate that the corresponding metabolite was not determined, and are included in the graph for explanatory reasons only. Fig. 2 View largeDownload slide Schematic representation of the metabolic changes occurring in the transition from development to ripening processes in tomato fruits. Sugars, sugar-phosphates, sugar-alcohols, amino and organic acids, pigments, and cell wall components were determined in pericarps of tomato samples taken from 30 d until 60 d after anthesis (DAA). Names of metabolites in orange, green, and grey indicate increased, decreased, and no changes, respectively, in the levels of the corresponding metabolite at 60 DAA with respect to 30 DAA. Names in white letters indicate that the corresponding metabolite was not determined, and are included in the graph for explanatory reasons only. Together with SuSy and HXK, fructokinase (FRK) forms the pool of hexose phosphates subsequently used as substrates for respiration and starch biosynthesis. Two different isoforms of this enzyme (FRK1 and 2) have been detected in tomato fruits exhibiting temporal and spatially distinct expression patterns (Kanayama et al., 1997, 1998). However, although both FRK1 and 2 enzymes have been shown to play a role in floral initiation and abortion, seed number, and stem and root growth in tomato plants (Odanaka et al., 2002), their role in fruit metabolism has received far less attention to date. The regulation of the hexose content itself has recently received considerable interest following the construction of a functional linkage map of the carbohydrate metabolic pathway of the tomato fruit (Levin et al., 2004). This map aided the discovery of two interacting chromosomal regions introgressed from S. habrochaites, leading to an almost 3-fold epistatic increase in the fructose to glucose ratio in the mature fruit (Levin et al., 2000); however, the mechanistic reasoning for this is yet to be elucidated. Earlier work provided a study of the sucrose to starch transition in the tomato fruit and suggested that the activities of sucrose synthase, fructokinase, and AGPase are likely to share control of the rate of starch accumulation (Schaffer and Petreikov, 1997). The recent application of the theory of metabolic control analysis to the same pathway in potato tubers suggested that only AGPase exhibited considerable control of starch synthesis (Geigenberger et al., 2005; Davies et al., 2005); however, it should be noted that these studies are not directly comparable. In another study focusing on starch metabolism in the fruit the contribution of fruit photosynthesis to the total photosynthate incorporated into the fruit was assessed via transgenesis. For this purpose, the expression of the plastidial fructose bisphosphatase was inhibited in a fruit-specific manner utilizing the antisense approach (Obiadalla-Ali et al., 2004b). The resultant transgenic lines exhibited surprisingly few changes in their carbohydrate metabolism but displayed considerably decreased fruit size. Intriguingly, the decrease in size was quantitatively similar to previous estimates of the contribution of the fruit to the production of the photosynthate, which it utilizes, made in earlier physiological studies (Guan and Janes, 1991a, b). Although clearly of central importance to the tomato fruit, relatively little is currently known concerning the regulation of glycolysis and the conversion of hexose phosphates into organic acids. Similarly, although organic acids are of fundamental importance at the cellular level for several biochemical pathways and at the whole organism level, their study has received much less attention than that of the sugars to date. Indeed the TCA cycle in plants is very poorly characterized in general and, although the structure of the pathway is well known, its regulation is not (Fernie et al., 2004b). In addition to the fundamental importance of understanding this pathway, its manipulation also has value from a metabolic engineering perspective with the organic acid to sugar ratio of particular pertinence, since it defines quality parameters at harvest time. Furthermore, especially in red fruits which contain little starch, glycolysis and respiration represent the dominant carbon fluxes in the fruit (Rontein et al., 2002; F Carrari and AR Fernie, unpublished results). Interestingly, the relative fluxes through the central metabolic pathways do not alter massively through the life cycle of suspension-cultured tomato cells, whilst those of anabolic pathways such as starch synthesis and the biosynthesis of amino acids and cell wall polysaccharides are low and variable (Rontein et al., 2002). The high-value metabolites derived from carbon skeletons provided by the central pathway encompass many more pathways than these, however, including fatty acids (Browse and Somerville, 1991), flavonoids (Dooner et al., 1991; Fatland et al., 2002), pigments (Mann et al., 2000), alkaloids (Hughes and Shanks, 2002), and isoprenoids (Lange et al., 2001), some of which are briefly discussed below. The exhaustive analysis of this pathway should, therefore, not only yield answers to very important fundamental biological questions but may also find useful application. Recently, a research project has been initiated focusing on organic acid metabolism in tomato. As part of this ongoing project to determine the role of the mitochondrial TCA cycle in plants, studies were first concentrated on the illuminated leaf. Comprehensive phenotyping of an aconitase mutant (Aco1) of Solanum pennellii (Carrari et al., 2003b), as well as S. lycopersicum plants in which the mitochondrial malate dehydrogenase (mMDH) was repressed via antisense and RNA interference techniques (Nunes-Nesi et al., 2005), uncovered large changes in both leaf metabolism and in plant performance. Biochemical analysis of the Aco1 mutant revealed that it exhibited a decreased flux through the TCA cycle, decreased levels of TCA cycle intermediates, and enhanced carbon assimilation. In addition, although it must be borne in mind that S. pennellii is a green-fruited species bearing very small fruits (Schauer et al., 2005), these plants were characterized by a dramatically increased fruit weight. Studies in Fernie's laboratory (Nunes-Nesi et al., 2005) on the mMDH antisense plants revealed that decreased activity of this enzyme in the elite cultivated species S. lycopersicum also resulted in enhanced photosynthetic activity and in an increment in fruit dry weight. Despite the fact that much research work is needed to understand the exact reasons for the increment in the fruit dry matter, manipulation of central organic acids is clearly a promising approach to enhance tomato fruit yield. Transcript and metabolite profiling of leaf material from these lines suggests that some of the increase in photosynthetic capacity is due to an elevated expression of genes associated with photosynthesis (Urbanczyk-Wochniak et al., unpublished data), perhaps as a consequence of the increased levels of ascorbate found in these plants (Kiddle et al., 2003). Cell wall metabolism The integrity of the fruit cells can be ascribed to wall-to-wall adhesion between cells and the strength of the primary wall. These traits have been described as critical factors influencing the perception of the fruit textures by the consumers (Pitt and Chen, 1983). Fleshy fruits such as tomatoes are predominantly composed of parenchyma cells enclosed by an unlignified layer of cellulose microfibrils suspended in a matrix of glycoproteins, water, and pectic and hemicellulose polysaccharides. The latter accounts for 90% of the cell wall (Redgwell and Fischer, 2002), with cell wall polysaccharides largely derived from sugars and sugar phosphates (Scheible and Pauly, 2004). Tomato fruit development is marked by significant changes in the cell wall components and a handful of polysaccharide-degrading enzymes has received much attention over the last 15 years. The activity of these enzymes is directly linked to the shelf-life of the fruits, one of the characteristics crucial to the tomato market. Endo-polygalacturonase has been the most studied among the enzymes involved in cell-wall metabolism. Polygalacturonase catalyses the hydrolysis of the linear α-1,4-D-galacturonan backbone of pectic polysaccharides and, alongside the mRNA level, its activity increases dramatically during tomato ripening (Della Penna et al., 1986). Rhamnogalacturonase and β-galactosidase (TBG) are enzymes which depolymerize branched pectins resistant to attack by endo-polygalacturonase. Rhamnogalacturonase and TBG have been purified and found to be highly active in tomato fruits (Gross et al., 1995). At least seven tomato TBG genes are expressed during fruit development (Smith and Gross, 2000); six are known to be expressed during ripening and the products of five of them are predicted to be targeted to the cell wall. Furthermore the functionality of three of these genes (TBG1, 3, and 4) has been assessed in tomato via transgenesis. Whilst reducing the expression of TBG1 did not result in changes in texture or cell wall composition (Carey et al., 2001), antisense suppression of the TBG3 gene led to an increase in wall galactosyl content, an increased proportion of insoluble solids, and slightly increased viscosity (de Silva and Verhoeyen, 1998), and suppression of TBG4 resulted in increased fruit cracking, reduced locular space, and a doubling in the thickness of the fruit cuticle (Moctezuma et al., 2003), in addition to a decrease in fruit softening (Smith et al., 2002). PME catalyses the de-esterification of pectin. In tomato, PME arises from the expression of three genes (Tucker and Zhang, 1996). When a fruit-specific PME (PME2) was down-regulated in tomato, the degree of softening during ripening was unaltered, but upon storage at room temperature for 7 weeks, the transgenic fruit lost tissue integrity while the wild-types held their cohesiveness. Thus, reduced pectin depolymerization had a negative effect on shelf-life (Tieman et al., 1992). Endo-β-1,4-glucanases (or cellulase, EGase) are a class of enzymes which degrade carboxymethylcellulose. Their activity is associated with softening in tomato and other fruits, suggesting a role in ripening. EGases are encoded by a seven-member gene family (Brummell et al., 1999) and antisense suppression of a fruit-specific member caused no change in the pattern of softening, but the abscission zones of the transgenic fruit were strengthened. In addition, xyloglucan endotransglycosylase which cleaves the xyloglucan molecules of the wall has been implicated in ripening-related changes to the fruit cell wall in tomato (Maclachlan and Brady, 1994). Whilst the above list of enzymes is relatively extensive, it actually only constitutes a few examples of the wall-modifying proteins, with numerous new classes remaining to be discovered. It is also rather cursory due both to space limitations and the plethora of high quality reviews that characterize this area of metabolism (Pilling and Hofte, 2003; Rose et al., 2004b; Scheible and Pauly, 2004). A further complexity arises when non-enzymatic mechanisms of cell wall changes are considered. One such example are the expansins—small proteins that catalyse cell-wall extension and for which at least 10 distinct genes have been identified in the tomato. A member of this family (LeExp2) is expressed in several growing tissues and has been demonstrated to be induced by physiological concentrations of auxins. Moreover, during fruit development it is co-expressed with xyloglucan- endotransglycosylase-, and EGase-encoding genes (Catala et al., 2000), suggesting cross-talk between hormone and cell wall metabolism. Surprisingly, another α-expansin gene from tomato (LeExp1) was found to be specifically and abundantly expressed in ripening fruit where cell expansion was supposed not to occur (Rose et al., 1997). Again, this protein has been shown to be ethylene-induced in tomato fruits and other species and differentially regulated in the rin (ripening inhibitor) and in the ethylene receptor Nr (Never ripe) mutants (Rose et al., 2000). As cell division and ripening are physiologically distinct, the role played by expansins during these processes remains obscure (Bertin, 2005). In addition to direct studies of cell wall metabolism the recent elucidation of an alternative pathway for ascorbate biosynthesis in strawberry that utilizes glucuronic acid, presumably derived from cell wall breakdown (Valpuesta and Botella, 2004), is of high interest. Although homologues for the genes encoding the necessary enzymes have not yet been identified in tomato, the presence of this pathway currently remains an open question. Recently, efforts have begun to establish proteomics technical platforms in order to characterize the differences in wall structure and composition that occur during tomato fruit development and ripening (see Rose et al., 2004a, b), and the adoption of systems biology approaches to study the cell wall have been championed (Somerville et al., 2004). It is thus likely that, in the coming years, our understanding both of the co-ordination of cell wall metabolism during fruit development and the consequences of temporal changes in wall metabolism on fruit metabolism, and morphology in general, will be furthered. Pigments and flavonoids Pigments of ripe fruits are not only attractive to consumers, but are also beneficial for health, including protection from cancers, and it is well documented that carotenoid deficiencies may cause blindness (Mayne, 1996). They are considered essential nutrients as they cannot be synthesized de novo in the human body. In plants, pigments and flavonoids are derived from acetyl-CoA metabolism through conversion to mevalonic acid, and from phenylalanine metabolism through the action of the PAL (phenylalanine ammonia-lyase) enzyme, respectively. Moreover, carotenoids with a beta-ring end group are required for the synthesis of vitamin A. Tomato fruits are the principal dietary source of carotenoids in many Western diets. Almost all the enzymes acting in the carotenoid biosynthesis pathway have been cloned, and their manipulation has been the subject of various metabolic engineering approaches aimed at enhancing pigment quantity and quality (reviewed in Hirschberg, 2001). A null mutation in the gene encoding a chromoplast-specific phytoene synthase (Psy1) is one of the reasons for the lack of pigmentation in the green-fruited species Solanum pennellii (Ronen et al., 2000). Up-regulation of Psy1 in tomato fruits resulted in redirection of GGPP to the gibberellin pathway yielding dwarf plants (Fray et al., 1995). However, overexpressing the psy gene of different species in rice caryopses has resulted in a highly successful biotechnological application—the considerable increment in the contents of pro-vitamin A in the cases of Golden Rice (Ye et al., 2000) and Golden Rice 2 (Paine et al., 2005). By contrast, the heterologous expression of a phytoene desaturase (Pds) from Erwinia uredovora in tomato resulted in a significant increment of the β-carotene levels at the expense of lycopene and the total level of carotenoids (Römer et al., 2000). Alterations in the pigment accumulation patterns have been observed in several spontaneously occurring tomato mutants, and two recent reports extolled the potential of these genetic tools for the manipulation of nutritional components. In the recessive mutant high pigment (hp), carotenoid levels are twice that in wild-type fruits (Yen et al., 1997); in addition, many other antioxidants are increased (Bino et al., 2005). Hp carries a mutation in a tomato UV-DAMAGED DNA-BINDING PROTEIN 1 (DDB1) homologue (Liu et al., 2004) whose Arabidopsis counterpart interacts with the product of hp2 locus DET1. These two mutants display a similar phenotype regarding fruit pigmentation, their products being members of the same light signal cascade (Schroeder et al., 2002). Understanding their key control points will render the possibility of manipulating nutritional characteristics of the fruits. Recent success stories include the elevation of both lycopene and β-carotene exhibited following the fruit-specific silencing of the endogenous photomorphogenesis regulatory gene DET1 (Davuluri et al., 2005). Similarly, an increase in both carotenoid and flavonoid content following the overexpression of the cryptochrome, CRY2 (Giliberto et al., 2005), and the production of high-flavonol tomatoes following heterologous expression of the maize transcription factor genes, LC and C1, have been reported (Bovy et al., 2002). Another, non-pigment-derived vitamin of high importance is folate. It has been calculated that more than one-third of the folate in an average diet is provided by fruits and vegetables (FDA; http://www.fda.gov/fdac/features/796_fol.html). Plants synthesize folate from pteridine, but levels of this molecule are very low in tomato fruits. A novel approach reported by Diaz de la Garza et al. (2004) achieved a significant increment in folate levels following the overexpression of a non-regulated synthetic gene based on mammalian GTP cyclohydrolase I (Basset et al., 2002). Much less attention has been placed on antioxidants with non-vitamin activity. However, recently, Giovinazzo et al. (2005) have produced tomato transgenic plants for a stilbene synthase from grape. The overexpression of this gene results in increased competition for substrates of the anthocyanin pathways, thus resulting in an increment in the levels of resveratrol, ascorbate, and glutathione. The above-mentioned examples constitute only a few of the recent findings utilizing transgenesis to engineer pigment and flavonoid levels in tomato fruits. Notwithstanding these successes, which are largely based on a relatively limited number of genetic manipulations, a recent report indicates that a diverse network of processes control pigment contents of tomato (Liu et al., 2003). Liu et al. (2003) utilized the S. pennelli×S. lycopersicum introgression lines described above to identify 19 QTLs for fruit colour, and analysed the co-localization of these QTLs with loci corresponding to carotenoid-related sequences. This candidate gene approach proved to be efficient for the identification of sequences that regulate fruit colour qualitatively, but not for the quantitative variation in colour or the regulation of pigment accumulation. As such, this report hints at further, as yet unidentified, factors that control the accumulation of pigments within the tomato fruit. The elucidation of these factors thus represents a significant challenge for understanding and influencing pigment content. Volatiles At the onset of ripening the vast array of volatile compounds produced by tomato fruits are responsible for their flavour and aroma characteristics. These compounds are sensed orally and nasally and are the final determinant of consumers' choice of food. Plants have been reported to emit >1000 low-molecular-weight organic compounds (Knudsen et al., 1993). As in other areas of plant biology, major progress has recently been made in understanding plant volatiles via the application of molecular and biochemical techniques (reviewed in Dudareva et al., 2004). From the 400 different volatile compounds that tomato fruits are estimated to contain, the principal contributors to the ripe tomato flavour are cis-3-hexanal, cis-3-hexanol, hexanal, 3-methylbutanal, 6-methyl-5-hepten-2-one, 1-pentan-3-one, trans-2-hexanal, methyl salicylate, 2-isobutylthiazole, and β-ionone (Buttery and Ling, 1993). Among this group, esters are the most commonly detected in tomato fruits and their biosynthesis is catalysed by the enzyme alcohol acetyltransferase. Moreover, the availability of ester precursors may also play a role in determining the nature of the volatiles to be formed. The major source of esters is derived from the metabolism of pyruvate through its conversion to acetyl CoA by the pyruvate dehydrogenase complex or via pyruvate decarboxylase to acetaldehyde and, subsequently, to ethanol by alcohol dehydrogenase. Thus, these three enzymes are good candidates for the manipulation of fruit flavour, with modification of the alcohol dehydrogenase levels being demonstrated to be a successful strategy to modify the contents of hexanol and cis-3-hexenol (Speirs et al., 1998; Prestage et al., 1999). In another recent example, the carotenoid cleavage dioxygenase 1 genes were demonstrated via transgenesis to contribute to the formation of the flavour volatiles β-ionine, psuedosonone, and geranylactone (Simkin et al., 2004). Another volatile compound which influences flavour quality of tomatoes is the acyclic monoterpene alcohol, linalool (Buttery et al., 1990). S-Linalool is the product of the reaction catalysed by linalool synthase (LIS) which uses geranyldiphosphate (GPP) as substrate, and the expression of a heterologous LIS gene from Clarkia breweri in tomato under a fruit-specific promoter yielded plants displaying considerably higher levels of S-linalool and 8-hydroxylinalool (Lewinsohn et al., 2001). However, although this constitutes a clear example of the possibility of increasing the tomato fruit aroma, it remains to be tested whether the resultant fruits are actually preferred by the consumers. A complementary approach, again utilizing broad genetic crosses, has been taken by Causse et al. (2002) who identified QTL for organoleptic properties of tomatoes. The lines identified as preferable by the consumer could now be comprehensively characterized with respect to volatile and non-volatile compounds alike. It is clear that not all volatile compounds will confer positive taste attributes to tomato. One such example that this is the case was provided by the identification of malodorous a wild species allele affecting tomato aroma that was selected against during domestication (Tadmor et al., 2002). However, it is perhaps not surprising that some of the chemicals emitted by plants taste bad to us, given that the plant produces many of them as protectants from pests. A combined metabolic, genomic, and biochemical analysis of glandular trichomes from the wild tomato species S. habrochaites recently identified a key enzyme in the biosynthesis of methylketones which serve this purpose (Fridman et al., 2005). To summarize this section, it seems fair to say that, in recent years, there have been dramatic improvements in the knowledge of tomato volatiles; however, there is still a great deal of work to be done before it can be claimed that the understanding of their biosynthesis is comprehensive. Conclusions and future perspectives The majority of the studies detailed above were carried out exclusively on pericarp tissue or at the whole-fruit level. Whilst this provides important information, it is worth noting that it is now well accepted that the metabolism in the fruit pericarp is different from that in the placenta, and this is even different from that in the columella (Obiadalla-Ali et al., 2004a; Baxter et al., 2005a). These differences are not only evidenced by the contrasting concentrations of the major sugars and starches (Obiadalla-Ali et al., 2004a) but also by the differences observed between the tissues in the activities of several enzymes involved in glycolysis, Calvin cycle, and sucrose degradation (Obiadalla-Ali et al., 2004a). The data presented in this study also revealed an up-regulation of glycolysis just prior to the onset of ripening that, together with the increment in the ethylene biosynthesis rates, is the main feature which distinguishes climacteric fruit, such as tomato, from non-climacteric fruits. To recapitulate, whilst great progress has been made in understanding the hormonal control of fruit development and, with respect to the control of a handful of metabolic pathways during this process, compilation of the datasets is only just beginning, allowing a broader systems-orientated view of metabolism of the developing fruit. The continued establishment of even more sophisticated tools to dissect metabolism and development at both spatial and temporal levels (Rontein et al., 2002; Kehr, 2003; Junker et al., 2003, 2004) means that it will also be crucial in the future to analyse tissues independently and across a broad developmental time frame in order to allow comprehensive understanding of networks occurring within given cell types. As a first step in this direction, a study has recently been initiated in which the levels of primary metabolites in the pericarp of wild-type fruit were profiled every 7 d from 7 DAA to 70 DAA and, additionally, transcript levels in identical tissue samples were profiled for the majority of these time points. Once they are fully evaluated, it is the intention to integrate the datasets prior to correlation analysis in the same way as was previously done for the developing potato tuber (Urbanczyk-Wochniak et al., 2003), and to do a pathway-based analysis as recently performed for diurnal changes in potato leaf metabolism (Urbanczyk-Wochniak et al., 2005). It is hoped that this approach will allow a fuller understanding of the genetic and metabolic networks that govern tomato fruit metabolism and mediate the dramatic metabolic changes that occur in the life cycle of this organ. The contribution of Ilse Balbo, Charles Baxter, Björn Junker, Andrea Leisse, James Lloyd, Anna Lytovchenko, Adriano Nunes-Nesi, Ute Roessner, Nicolas Schauer, Claudia Studart-Guimarães, Lee Sweetlove, Ewa Urbanczyk-Wochniak, Lothar Willmitzer, and Dani Zamir to primary research on this theme over the last few years is gratefully acknowledged. We are indebted to Josef Bergstein for the photographic work. FC and ARF express gratitude for support in the form of a Max-Planck partner laboratory grant from the Max-Planck Society. FC also acknowledges support from CONICET and EMBO and ARF support from the DFG and the BMBF in the form of German–Israeli Cooperation (DIP). 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Xu, Hua-Wei;Ji, Xiu-Mei;He, Zheng-Hui;Shi, Wei-Ping;Zhu, Guo-Hui;Niu, Jian-Kang;Li, Bao-Sheng;Peng, Xin-Xiang

doi: 10.1093/jxb/erj131pmid: 16595582

Abstract Cellular oxalate, widely distributed in many plants, is implicated to play important roles in various functions and is also known to affect food qualities adversely in fruits and vegetables. How oxalate is regulated in plants is currently not well understood. Glycolate oxidase (GLO) has long been considered as an important player in oxalate accumulation in plants. To gain further insight into the biochemical and molecular mechanisms, the possible roles of GLO in the process were studied. Drastically different levels of oxalate could be achieved by treating rice with various nitrogen forms (nitrate versus ammonium). While nitrate stimulated oxalate accumulation, ammonium reduced its level. Such treatments resulted in similar pattern changes for some other related organic acids, such as glycolate, oxaloacetate, and malate. By feeding plants with exogenous glycolate it was possible almost completely to restore the ammonium-decreased oxalate level. Under the two treatments few differences were observed for GLO mRNA levels, protein levels, and in vitro activities. Both Km for glycolate/glyoxylate and Ki for oxalate remained almost the same for GLO purified from either nitrate- or ammonium-fed leaves. A further in vivo study, with transgenic plants carrying an estradiol-inducible GLO antisense gene, showed that, while the estradiol-induced antisense expression remarkably reduced both GLO protein levels and activities, oxalate levels were not significantly altered in the estradiol-treated transgenic plants. Taken together, it is suggested that oxalate accumulation and regulation is independent of GLO in rice leaves. Glycolate oxidase, oxalate accumulation, rice Introduction Oxalate is widely distributed in the plant kingdom, and many plant species accumulate oxalate in a range of 3–15% (w/w) of their dry weight (Zindler-Frank, 1976; Libert and Franceschi, 1987; Nakata, 2003; Franceschi and Nakata, 2005). Studies have shown that oxalate may play various roles in plants including calcium regulation, ion balance (e.g. Na and K), plant protection, tissue support, and heavy metal detoxification (Libert and Franceschi, 1987; Franceschi and Nakata, 2005). Some plants, such as buckwheat, taro, and rice, exude and/or in vivo accumulate oxalate to detoxify aluminium and lead (Ma et al., 1997; Ma and Miyasaka, 1998; Yang et al., 2000). Oxalate may also be involved in the detoxification of other hazardous metals such as strontium (Franceschi and Schueren, 1986), cadmium (Choi et al., 2001), and copper (Mazen and Maghraby, 1997). Inoculation of tobacco leaves with an oxalate-deficient non-pathogenic mutant of Sclerotinia sclerotiorum induced measurable oxidant biosynthesis, but inoculation with an oxalate-secreting strain did not, indicating that oxalate was able to quench the oxidative burst in plants in responding to pathogen attack (Cessna et al., 2000). Despite the broadly suggested oxalate functional roles in plants, high oxalate content can also be a concern to human nutrition and health (Franceschi and Nakata, 2005). Excess levels of oxalate in any edible parts of plants significantly lower the nutritional quality, as oxalate decreases calcium bioavailability and may cause kidney stones (Libert and Franceschi, 1987; Horner and Wagner, 1995; Massey, 2003; Franceschi and Nakata, 2005). Therefore, elucidating oxalate metabolic and regulatory mechanisms becomes increasingly important in both scientific and applied aspects. Efforts have been made to elucidate the metabolic pathways of oxalate biosynthesis and to reduce the oxalate levels in some crop plants (Libert and Franceschi, 1987). Several pathways were hypothesized, including photorespiratory glycolate/glyoxylate oxidation, cleavage of ascorbate, hydrolysis of oxaloacetate (Horner and Wagner, 1995; Nakata, 2003; Franceschi and Nakata, 2005). Glycolate/glyoxylate oxidation has long been proposed as an important pathway for oxalate biosynthesis in plants (Libert and Franceschi, 1987; Fujii et al., 1993; Nakata, 2003; Franceschi and Nakata, 2005). This proposal was ultimately based on the enzymatic evidence, in which glycolate oxidase (GLO) was shown to be able to catalyse glyoxylate oxidation to oxalate, although its ability to convert glycolate to glyoxylate during photorespiration was well known (Richardson and Tolbert, 1961; Tolbert, 1981). So far this is the sole enzyme in plants convincingly justified to catalyse oxalate formation. However, there are several lines of evidence challenging this pathway. Raven et al. (1982) showed that 18O2 incorporation into glycolate did not extend to oxalate. Some C4 plants such as amaranth, with minor photorespiration, still accumulated high concentrations of oxalate (Libert and Franceschi, 1987; Franceschi, 1987; Li et al., 2000). Oxalate accumulates even in the dark or in callus where there is supposedly no photorespiration (Franceschi and Horner, 1979; Franceschi, 1987). The calcium oxalate crystal idioblasts even lack GLO and/or photorespiration (Kausch and Horner, 1985; Li and Franceschi, 1990; Franceschi and Nakata, 2005). More recent work points towards an ascorbate cleavage as a major pathway for oxalate production in some plant species (Horner et al., 2000; Keates et al., 2000; Kostman et al., 2001). Green and Fry (2005) found that this pathway could even operate extracellularly. Nevertheless, the biochemical data for this proposed pathway are lacking so far. Interestingly, Franceschi (1987) showed that glycolate/glyoxylate may have served as the intermediates in catabolism of ascorbate to oxalate. Oxaloacetase, commonly found in microbes, can cleave oxaloacetate into oxalate and acetate (Gadd, 1999). Although oxaloacetase was once reported to exist in crude preparations of beetroot and spinach (Chang and Beevers, 1968), its existence in plants remains to be confirmed. Overall, an oxalate biosynthetic pathway in plants remains controversial, but more researchers tend to the view that the predominant biosynthetic pathway of oxalate may vary from plant species to species. GLO has long been considered as a key component mediating oxalate biosynthesis in some plants (Millerd et al., 1963a, b; Piquemal et al., 1980; Chang and Huang, 1981; Franceschi, 1987; Li and Franceschi, 1990), yet its role in regulating oxalate accumulation is not defined. It has been observed that GLO activity and its kinetic property did not differ between oxalate-accumulating and oxalate non-accumulating plant species (Watanabe et al., 1995; Li et al., 2000) and that the Km of GLO for glyoxylate was determined to be much higher than the measured physiological glyoxylate concentration (Davies and Asker, 1983; Libert and Franceschi, 1987). In this study, the role of GLO in oxalate accumulation and regulation was investigated in rice plants. Biochemical and transgenic analyses have suggested that oxalate accumulation and regulation is independent of GLO in rice leaves, although the metabolites glycolate/glyoxylate still appear to be involved in the process. Materials and methods Plant materials Two varieties of rice (Oryza sativa L.) were used in the experiment: Xiangzhongxian 2 for the biochemical study and Shishoubaimao for antisense transformation. Growth conditions and treatments Pre-germinated seeds were grown in Kimura B complete nutrient solution (Yoshida et al., 1976) under greenhouse conditions [average temperature of 30/25 °C (day/night), relative humidity 60–80%, average photosynthetically active radiation 600–1000 μmol m−2 s−1 and photoperiod of 14 h day/10 h night]. Until the seedlings had four leaves they were treated with the two forms of nitrogen by replacing the nitrogen element in the complete solution with sole nitrate or sole ammonium (2.86 mM). The solution was renewed every 3 d. For the other treatments (i.e. feeding of glycolate, glyoxylate, ascorbate, oxaloacetate, isocitrate), the chemicals were added to the ammonium nutrient solution without altering the other elements. Analysis was made at regular time intervals after the treatments (0, 3, 6, 9, and 12 d or as specified elsewhere). Growth of the transgenic plants and the estradiol-induced treatment were conducted in a growth chamber. The condition was controlled as follows: temperature 30/25 °C (day/night), relative humidity ∼70%, photosynthetically active radiation about 600 μmol m−2 s−1 and photoperiod of 14 h day/10 h night. Determination of oxalate and other organic acids Extraction of organic acids: Aliquots of 0.2–0.5 g FW, depending on sample availability, were homogenized in 1–4 ml of 0.5 N HCl. The homogenate was heated at 80 °C for 10 min with intermittent shaking. To the homogenate was added distilled water up to a volume of 5–25 ml. About 2–3 ml of the solution was withdrawn and centrifuged at 12 000 g for 10 min. One millilitre of supernatant was passed through a filter (0.45 μm) before HPLC analysis. Analysis of oxalate, citrate, and malate: The analysis was made according to Libert (1981) with modifications (Yu et al., 2002). Hypsil C18 column (5 μM, 4.6 mm×250 mm) equipped Waters 550 (Waters, MA, USA) was used as the static phase and the mobile phase was a solution containing 0.5% KH2PO4 and 0.5 mM TBA (tetrabutylammonium hydrogen sulphate) buffered at pH 2.0 with orthophosphoric acid. Flow rate was 1 ml min−1 and detection wavelength was at 220 nm. Analysis of glycolate, glyoxylate, and oxaloacetate: The analysis was made according to Petrarulo et al. (1989, 1990) with modifications (Ji et al., 2005). Glyoxylate and oxaloacetate were first derivatized by phenylhydrazine to form phenylhydrazone, then the derivatives were separated and quantified by reversed-phase HPLC. Hypersil C18 column (5 μM, 4.6×250 mm), a mobile phase containing 5% methanol and 95% phosphate buffer (13 mM potassium biphosphate; 1 mM potassium phosphate dibasic pH 6.0) and detection at 324 nm were applied in the system. Glycolic acid was determined by oxidizing glycolate into glyoxylic acid with purified GLO, then followed by the same procedure as above for glyoxylate determination. For determination of ascorbic acid, 0.5 g of fresh leaves was homogenized in 3.5 ml 5% TCA solution and the homogenate was centrifuged at 20 000 g for 10 min. The supernatant was used for further analysis according to Okamura (1980). Purification of GLO Twenty grams of fresh leaves were homogenized in 80 ml of 100 mM phosphate buffer (pH 8.0) with a homogenizer. The homogenate was filtered through two layers of cheesecloth to remove fibrous materials. The filtrate was centrifuged at 15 000 g for 10 min and the precipitate was discarded. The pH of the supernatant was carefully adjusted to 5.5 with diluted HCl and then centrifuged at 15 000 g for 10 min. The supernatant was then fractionated between 20% and 40% of ammonium sulphate and the final precipitate was resuspended in 15 ml 5 mM TRIS-HCl (pH 7.5) and centrifuged again. The resultant supernatant was desalted through a Sephadex G-25 column (30 mm×200 mm) and the desalted solution was then loaded onto a DEAE-Sepharose Fast Flow column (20 mm×150 mm). The column was first flushed with 5 mM TRIS-HCl buffer (pH 7.5) and the enzyme was subsequently eluted with 100 mM TRIS-HCl buffer (pH 7.5). RNA, protein blot, and activity assay of GLO RNA blot: Total RNA was extracted from rice leaves according to Logemann et al. (1987). Northern hybridization was after Sambrook et al. (1989). Thirty micrograms of total RNA were size-fractionated on a formaldehyde agarose gel and transferred to Hybond-N+ nylon membrane (Amersham). The blot was hybridized with a random prime [α-32P]-labelled cDNA probe: the complete GLO cDNA (1.3 kb) synthesized on RT-PCR product template with the upstream primer 5′-GAGAGAACTAGTGCAGGGTTCACAAGGCAGGAGAAAA-3′ and the downstream primer 5′-GTGTCTCTCGAGCATGAACGACCCAGTTACGA-3′. Protein blot: Proteins were extracted by homogenizing 0.5 g of fresh leaves in 4 ml 20 mM phosphate buffer (pH 8.0). The homogenate was centrifuged at 15 000 g for 15 min. Equally loaded samples (15 μg protein) were fractionated on a 4–20% gradient SDS-PAGE, and then electroblotted onto a nitrocellulose membrane using a Mini Trans-Blot cell (Bio-Rad). GLO protein was detected using a rabbit polyclonal GLO antibody (1:1000). The antibody was prepared by expressing the complete GLO cDNA (inserted to a pET-23d vector; Novagen) in Escherichia coli (BL21) after Dumbroff and Gepstein (1993), and the expressed GLO protein induced by IPTG was purified on gradient SDS-PAGE (4–20%) and then injected into a rabbit. The serum was withdrawn as the antibody. Activity assay: GLO activity was assayed according to Hall et al. (1985) with some modifications. Samples (0.1–0.5 g) of fresh leaves were homogenized in 1–5 ml extraction buffer (100 mM phosphate, pH 8.0) at 4 °C. The homogenate was then centrifuged at 15 000 g for 15 min. The supernatant was used for the enzyme activity assay. A 1.5 ml sample of the reaction mixture contained 66 mM phosphate buffer (pH 8.0), 1 mM 4-amino-antipyrine, 5 units of horseradish peroxidase, 2 mM phenol, 0.1 mM FMN, 5 mM glycolate/glyoxylate, and 0.05 ml of enzyme extract. The enzyme was added last to start the reaction and distilled water substituted the substrate as the blank. H2O2 produced in the reaction mixture was determined spectrophotometrically at 520 nm and under 30 °C. Construction of transgenics and induced down-regulation of GLO expression The estradiol-inducible transformation vector pER 8 was kindly provided by Dr Nam-Hai Chua (Rockefeller University, New York) (Zuo et al., 2000). To generate the pER 8-GLO antisense construct, the complete cDNA of GLO was cloned by RT-PCR as described above, then inserted into pER8 between SpeI and XhoI restriction sites. First, PCR with specific primers and cutting with restriction enzymes showed that the target fragment had been correctly ligated. DNA sequencing further confirmed the correct orientation and cDNA identity [100% identical to that reported in the gene bank (AK098878)]. The pER8-GLO was transformed into rice by Agrobacterium-mediated infection (strain EHA105). The first two cycles of selection by hygromycin (50 mg l−1) was followed by HPT marker PCR amplification to select the positive transformants (since it is known that nos promoter governing the hygromycin resistance gene works less efficiently in monocotyledonous plants, more cycles of hygromycin selection were avoided). For further estradiol-inducibility tests, the seeds harvested from the positive T0 lines were germinated and grown in Kimura B complete nutrient solution. Until the T1 plants had three leaves they were treated with estradiol (5 μmol l−1) by adding it into the nutrient solution which was renewed every 3 d. GLO activity was determined 8 d after the treatment. The plants with markedly decreased GLO activity were selected as inducibility positive, and were transferred to normal soil conditions to grow until the seeds were harvested. The seeds harvested from the positive T1 lines (26-18, 26-19, 26-23), originated from T0 line no. 26, were germinated and grown in Kimura B complete nutrient solution. Until the seedlings of T2 heterozygous plants had four leaves they were treated with estradiol (5 μmol l−1) and, at the same time, the nitrogen element in the nutrient solution was replaced with sole nitrate. For the controls, wild-type plants were grown and treated in the same manner. After treatment for 6 or 12 d, the first and second leaves from the top were detached for determining oxalate content, GLO activity, and enzyme protein. Protein determination Protein content was determined according to Bradford (1976). Results Effects of nitrate/ammonium on the metabolism of organic acids Nitrogen nutrition is known to cause changes in oxalate accumulation in certain plants (Libert and Franceschi, 1987). To identify the potential regulators for oxalate metabolism, an attempt was made to utilize different nitrogen forms to achieve various levels of oxalate accumulation. Rice seedlings treated for different periods with either nitrate or ammonium were harvested and assayed for oxalate content. As previously reported, nitrogen forms dramatically affected oxalate accumulation in rice. As shown in Fig. 1, while nitrate treatment significantly stimulated the foliar oxalate accumulation, ammonium had a suppressive effect. Three days after treatment, the oxalate content had increased by nearly 100% in nitrate-treated leaves but had decreased by >65% in ammonium-treated ones. As a result of the opposite effects, oxalate level in nitrate-treated leaves was five times higher than that in ammonium-treated ones at 3 d after treatment. Oxalate levels remained low in ammonium-treated leaves thereafter. By contrast, oxalate levels in nitrate-treated leaves continued increasing. At 12 d after treatment, the oxalate level in nitrate-treated leaves was nine times higher than that in ammonium-treated ones (Fig. 1). Fig. 1 View largeDownload slide Oxalate content in rice leaves as affected by nitrate/ammonium. Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition as detailed in the Materials and methods. Fresh leaves were randomly sampled at different time intervals after the treatments. The values are means ±standard deviation of three replicates and representative of three independent experiments. Open triangles represent ammonium; filled triangles, nitrate. Fig. 1 View largeDownload slide Oxalate content in rice leaves as affected by nitrate/ammonium. Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition as detailed in the Materials and methods. Fresh leaves were randomly sampled at different time intervals after the treatments. The values are means ±standard deviation of three replicates and representative of three independent experiments. Open triangles represent ammonium; filled triangles, nitrate. Metabolism of organic acids is regarded as well co-ordinated (Ryan et al., 2001). In order to understand how oxalate accumulation is associated in the metabolic network, the rice seedlings treated with either nitrate or ammonium were measured for levels of glycolate, glyoxylate, ascorbate, oxaloacetate, citrate, and malate. As shown in Fig. 2, while some of the organic acids demonstrated a similar time-course, others showed delayed responses. Glycolate, oxaloacetate, and malate showed a similar time-course to that of oxalate (Fig. 2A–C versus Fig. 1), whereas ascorbate and citrate responded noticeably later than oxalate to the treatments (Fig. 2D, E versus Fig. 1). By contrast, glyoxylate accumulated in ammonium-fed leaves throughout the whole treatment course (Fig. 2F) and changes in oxalate and glyoxylate were in a negative parallel. Fig. 2 View largeDownload slide Content of some other organic acids in rice leaves as affected by nitrate/ammonium: (A) glycolate; (B) oxaloacetate; (C) malate; (D) ascorbate; (E) citrate; (F) glyoxylate. Other details are identical to those in Fig. 1. Fig. 2 View largeDownload slide Content of some other organic acids in rice leaves as affected by nitrate/ammonium: (A) glycolate; (B) oxaloacetate; (C) malate; (D) ascorbate; (E) citrate; (F) glyoxylate. Other details are identical to those in Fig. 1. Effects of oxalate precursors on ammonium-suppressed oxalate accumulation Glycolate, glyoxylate, ascorbate, oxaloacetate, and isocitrate have been suggested as the metabolic precursors for oxalate formation (Nakata, 2003). To find out how these precursors would affect oxalate accumulation they were fed exogenously to rice seedlings. As shown in Table 1 and Fig. 3, when glycolate was fed to the ammonium-treated rice plants it could reverse the decreased oxalate up to the level in the nitrate-fed leaves. Glyoxylate and oxaloacetate restored it to ∼50% of the nitrate-fed leaves. Ascorbate was less effective, with only about 30% of the nitrate-fed leaves. Isocitrate had no significant effect on the ammonium-suppressed oxalate level (Table 1). These results suggest that glycolate may be the predominant precursor and/or regulator for oxalate formation in rice leaves. Fig. 3 View largeDownload slide Effect of glycolate or glyoxylate on ammonium-decreased oxalate in rice leaves. Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition. Into the ammonium nutrient solution were added 5 mM glycolate (GLC) or glyoxylate (GLX). At different time intervals after treatment, fresh leaves were randomly sampled for oxalate analysis experiments. Crosses represent ammonium; filled squares, nitrate; filled triangles, ammonium+GLC; open circles, ammonium+GLX. Other details are identical to those in Fig. 1. Fig. 3 View largeDownload slide Effect of glycolate or glyoxylate on ammonium-decreased oxalate in rice leaves. Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition. Into the ammonium nutrient solution were added 5 mM glycolate (GLC) or glyoxylate (GLX). At different time intervals after treatment, fresh leaves were randomly sampled for oxalate analysis experiments. Crosses represent ammonium; filled squares, nitrate; filled triangles, ammonium+GLC; open circles, ammonium+GLX. Other details are identical to those in Fig. 1. Table 1 Effect of some possible precursors on oxalate content (mg g−1 FW) in rice leaves Treatments  Oxalate content (mg g−1 FW)     3 d  6 d  Nitrate  7.48±0.60  8.85±0.16  Ammonium  1.80±0.45  1.71±0.20  Ammonium+GLC  8.19±0.28  8.11±1.05  Ammonium+GLX  4.32±0.55  4.42±0.95  Ammonium+OAA  4.16±0.05  3.95±0.45  Ammonium+ASA  3.01±0.17  3.74±0.75  Ammonium+ICA  2.27±0.54  2.74±0.28  Treatments  Oxalate content (mg g−1 FW)     3 d  6 d  Nitrate  7.48±0.60  8.85±0.16  Ammonium  1.80±0.45  1.71±0.20  Ammonium+GLC  8.19±0.28  8.11±1.05  Ammonium+GLX  4.32±0.55  4.42±0.95  Ammonium+OAA  4.16±0.05  3.95±0.45  Ammonium+ASA  3.01±0.17  3.74±0.75  Ammonium+ICA  2.27±0.54  2.74±0.28  Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition. Into the ammonium nutrient solution were added 5 mM precursors. At different time intervals after treatment, fresh leaves were randomly sampled for oxalate analysis. GLX, glyoxylate; GLC, glycolate; OAA, oxaloacetate; ASA, ascorbate; ICA, isocitrate. The values are means ±standard deviation of three replicates and representative of three independent experiments. View Large GLO expression, activity, and catalytic kinetics as affected by nitrate/ammonium The experiments mentioned above showed that glyoxylate and oxalate levels were adversely correlated (Fig. 1 versus Fig. 2F); feeding plants with either glycolate or glyoxylate could significantly increase the ammonium-suppressed oxalate level (Table 1; Fig. 3). These results hint at a possible involvement of glycolate metabolism in oxalate accumulation and regulation in rice. GLO, the key enzyme of glycolate metabolism (Tolbert, 1981), has long been suggested as an important player in oxalate accumulation in various plant species (Franceschi, 1987; Franceschi and Nakata, 2005). To define the potential role of GLO during oxalate accumulation in rice, GLO expressions were examined in both nitrate- and ammonium-fed rice leaves. Total RNA was extracted from the treated leaves and used for northern blotting. As shown in Fig. 4A, the two nitrogen forms had little effect on GLO transcript levels at the time intervals tested. Total proteins were prepared from the treated samples and analysed by western blotting. GLO protein levels remained unchanged between the two treatments during the time course (Fig. 4B). GLO activities in the various treated samples were also determined using either glycolate (Fig. 4C) or glyoxylate (Fig. 4D) as the substrate. There was no significant difference for GLO catalytic activities between the two treatments. Taken together, it is suggested that nitrate/ammonium treatments had little effect on both GLO expressions and activities, although, in this case, a dramatic difference in oxalate accumulation occurred (Fig. 1). Fig. 4 View largeDownload slide GLO in rice leaves as affected by nitrate/ammonium at the levels of transcription (A), translation (B), and enzyme activity (C, D). (C, D) Glycolate-oxidizing and glyoxylate-oxidizing activities, respectively, of GLO. The values in (C) and (D) are means ±standard deviation of three replicates and representative of three independent experiments; the results shown in (A) and (B) are representative of two independent experiments. Other details are identical to those in Fig. 1. Fig. 4 View largeDownload slide GLO in rice leaves as affected by nitrate/ammonium at the levels of transcription (A), translation (B), and enzyme activity (C, D). (C, D) Glycolate-oxidizing and glyoxylate-oxidizing activities, respectively, of GLO. The values in (C) and (D) are means ±standard deviation of three replicates and representative of three independent experiments; the results shown in (A) and (B) are representative of two independent experiments. Other details are identical to those in Fig. 1. To obtain detailed kinetic data, GLO was purified from both nitrate-fed and ammonium-fed leaves. The purification efficiency was monitored by measuring the specific activity at various fractionation steps. The final GLO obtained carried a purification factor of 58-fold. Kinetic analysis revealed that the Km of GLO for glycolate and glyoxylate was about 0.4 mM and 4 mM, respectively. Little difference was observed for the Km of GLO between the treatments with the two forms of nitrogen (Table 2). Oxalate, the product of glyoxylate oxidation, was able competitively to inhibit the activity, with a Ki of 1.5 mM. The Ki values remained the same between the two treatments (Table 2). Table 2 The kinetic parameters of GLO from nitrate- and ammonium-fed rice leaves   GLO kinetic parameters (mM)     Nitrate leaves  Ammonium leaves  Km (for glycolate)  0.46  0.50  Km (for glyoxylate)  4.53  5.05  Ki (oxalate) (for glycolate)  2.16  2.09  Ki (oxalate) (for glyoxylate)  1.65  1.52    GLO kinetic parameters (mM)     Nitrate leaves  Ammonium leaves  Km (for glycolate)  0.46  0.50  Km (for glyoxylate)  4.53  5.05  Ki (oxalate) (for glycolate)  2.16  2.09  Ki (oxalate) (for glyoxylate)  1.65  1.52  Plants with four leaves, pre-grown in Kimura B complete nutrient solution, were transferred to sole nitrate or sole ammonium nutrition. Six days after treatment, at which the difference of leaf oxalate content between the two treatments was determined up to 7-fold, the leaves from either nitrate- or ammonium-fed plants were used to purify GLO for the kinetic analysis. View Large Antisense suppression of GLO and oxalate accumulation To verify the role of GLO in oxalate accumulation and regulation further, an estradiol-inducible system was used to express the GLO antisense gene. Transgenic GLO antisense rice plants were analysed for GLO proteins, activities, and oxalate levels (Fig. 5). Application of the inducer estradiol effectively suppressed GLO expression. Six days after estradiol treatment, both GLO enzymatic activities and protein levels in the antisense plants were significantly reduced, as compared with the wild-type controls (Fig. 5A, C). Twelve days after estradiol treatment, the enzymatic activities were minimal (>90% down-regulated) and GLO proteins became undetectable in the transgenic antisense plants (Fig. 5A, C). It can also be noted that there was a good correlation between the amount of GLO protein and GLO activity for these plants (Fig. 5A, C). Oxalate contents in the transgenic antisense plants remained almost the same throughout the estradiol treatment (Fig. 5B). These results further confirmed that oxalate accumulation is GLO-independent. Fig. 5 View largeDownload slide GLO activities, oxalate content and protein levels in the leaves of wild-type and transgenic plants. (A) GLO activities at 6 d and 12 d after treatment; (B) oxalate levels at 6 d and 12 d after treatment; (C) GLO protein levels at 6 d and 12 d after treatment. CK1, wild-type plants grown under sole nitrate nutrition as detailed in the Materials and methods; CK2, wild-type plants grown under nitrate nutrition plus 1.8 mM DMSO and 5 μM inducer estradiol (DMSO, necessarily used as a solvent for estradiol); T, the transgenic plants were grown under sole nitrate nutrition plus 1.8 mM DMSO and 5 μM estradiol. The heterozygous transgenic plants with GLO remarkably down-regulated were selected to determine oxalate content and shown up in this figure. Values are means ±standard deviation of 16 transgenic plants (T1 lines, 26-18, 26-19, 26-23) and representative of three independent experiments. Fig. 5 View largeDownload slide GLO activities, oxalate content and protein levels in the leaves of wild-type and transgenic plants. (A) GLO activities at 6 d and 12 d after treatment; (B) oxalate levels at 6 d and 12 d after treatment; (C) GLO protein levels at 6 d and 12 d after treatment. CK1, wild-type plants grown under sole nitrate nutrition as detailed in the Materials and methods; CK2, wild-type plants grown under nitrate nutrition plus 1.8 mM DMSO and 5 μM inducer estradiol (DMSO, necessarily used as a solvent for estradiol); T, the transgenic plants were grown under sole nitrate nutrition plus 1.8 mM DMSO and 5 μM estradiol. The heterozygous transgenic plants with GLO remarkably down-regulated were selected to determine oxalate content and shown up in this figure. Values are means ±standard deviation of 16 transgenic plants (T1 lines, 26-18, 26-19, 26-23) and representative of three independent experiments. Discussion Plants may accumulate oxalate in a range of 3–15% (w/w) of their dry weight (Zindler-Frank, 1976; Libert and Franceschi, 1987; Nakata, 2003). Rice, as a model monocotyledonous plant, generally contains 3–6% of oxalate depending on growth stages and culture conditions (Libert and Franceschi, 1987; Ji and Peng, 2005; Fig. 1), with 40–50% of the soluble form and without any noticeable crystals during the growth stage being investigated in the present study (data not shown). Various forms of evidence have supported the idea that oxalate does not originate from the same source in different plant species. Through a number of isotope-labelling experiments, it was considered to be a strong possibility that the photorespiratory glycolate pathway is responsible for oxalate synthesis in various plants (Millerd et al., 1963b; Chang and Beevers, 1968; Osmond and Avadhani, 1968; Seal and Sen, 1970; Piquemal et al., 1980; Fujii et al., 1993; Franceschi and Nakata, 2005), although C2/C3 cleavage of ascorbate was recently suggested as a major oxalate source in Lemna minor L. and Pistia stratiotes (Keates et al., 2000; Kostman et al., 2001). It was initially detected that nitrate/ammonium was able to alter markedly oxalate levels in rice leaves (Ji and Peng, 2005; Fig. 1; Table 1) and provided further evidence that such an alteration was due to the efficiently regulated oxalate metabolism within rice leaves rather than due to its different downwards transportation and exudation (Ji and Peng, 2005). The mechanistic basis underlying this regulation may bring to light the general mechanism of oxalate accumulation and regulation in rice and, perhaps, in other plants. Apart from oxalate, some other organic acids were also suppressed by ammonium treatment (Fig. 2). Sole ammonium source is known to cause toxicity to many plant species (Britto et al., 2001), so that one may consider that the ammonium-suppression of oxalate and some other organic acids could simply result from the toxicity-induced whole metabolism breakdown in plants. It should be noted, however, that rice is a typical ammonium-preferring plant, which usually does not suffer from ammonium toxicity (Magalhaes et al., 1995; Britto et al., 2001). By contrast, sole nitrate nutrition stimulated not only the accumulation of oxalate but also some other organic acids, such as glycolate, oxaloacetate, malate, ascorbate, and citrate (Fig. 2). This observation is consistent with a previous report that nitrate itself acted as a direct signal to induce organic acid accumulation (Scheible et al., 1997). It is yet to be defined how oxalate is metabolically associated with the other organic acids. Ascorbate and citrate accumulated noticeably later than oxalate during nitrate treatment (Fig. 2D, E versus Fig. 1). By contrast to glycolate, neither ascorbate nor isocitrate was able to greatly enhance the ammonium-decreased oxalate (Table 1). This result suggested that the level of either ascorbate or isocitrate may not have played the predominant role in mediating oxalate accumulation in rice plants. Interestingly, glyoxylate accumulated in ammonium-fed leaves and in a negative correlation with oxalate (Figs 1, 2F), suggesting that the downstream of glyoxylate metabolism including glyoxylate oxidation to oxalate could be interrupted under ammonium treatment. Considered together with the fact that glycolate/glyoxylate significantly restored the ammonium-suppressed oxalate level (Table 1; Fig. 3) it is possible that glycolate/glyoxylate is involved in oxalate accumulation in rice leaves. In this case, glycolate/glyoxylate may have acted as a metabolic precursor to activate and/or protect from the inhibition of an oxalate-forming enzyme. However, it is unclear why glycolate was even more effective than glyoxylate in the effect (Table 1; Fig. 3), since glyoxylate had been frequently shown to be a more direct and efficient precursor for oxalate formation in oxalate-accumulating plants (Millerd et al., 1963a, b; Chang and Beevers, 1968; Osmond and Avadhani, 1968; Seal and Sen, 1970; Fujii et al., 1993). The possible involvement of glycolate/glyoxylate in rice oxalate accumulation re-prompted interest as to the role of GLO in the process. So far, GLO is the only enzyme convincingly proved to be capable of catalysing oxalate synthesis in plants. GLO from various plant species was found to be able to catalyse not only glycolate oxidation to glyoxylate but also glyoxylate oxidation to oxalate (Richardson and Tolbert, 1961; Havir, 1983). Evidence was further presented that GLO mediated in vivo oxalate accumulation and regulation in plants (Millerd et al., 1963a, b; Piquemal et al., 1980; Chang and Huang, 1981; Franceschi, 1987). The present results, however, suggest that GLO may not be involved in oxalate accumulation and regulation in rice leaves based on the following evidence. There was no difference between the leaves with contrasting oxalate content regulated by nitrate/ammonium in terms of GLO expressions, activities, and kinetic properties (Fig. 4; Table 2). Both Km for glycolate/glyoxylate and Ki for oxalate remained the same for GLO purified from either nitrate- or ammonium-fed leaves. Further in vivo study with antisense transgenic plants showed that, while GLO was >90% down-regulated, foliar oxalate levels were not altered, (Fig. 5) and correlation analysis assured that oxalate content and GLO activities were not significantly correlated (data not shown). Previous reports have also indicated that GLO activity and kinetic property were not different between the oxalate-accumulating and oxalate-non-accumulating plant species (Watanabe et al., 1995; Li et al., 2000), and the Km of GLO for glyoxylate was determined to be much higher than the measured physiological glyoxylate concentration (Davies and Asker, 1983; Libert and Franceschi, 1987). Here, it was also shown that the Km of rice GLO for glyoxylate was ∼4 mM while glyoxylate concentration in cells could be much lower than this value (Heupel and Heldt, 1994; Fig. 2B). GLO-catalysed glyoxylate oxidation was competitively inhibited by the product oxalate, with a Ki about 1.5 mM, whereas cellular oxalate may be much higher than this value (Fig. 1; Table 2). The value could be even higher at the subcellular level if oxalate is truly produced in peroxisomes by GLO catalysis. As far as is known, the present results have provided the strongest evidence so far, arguing against GLO's role in oxalate accumulation and regulation in plants, although glycolate/glyoxylate's involvement in this process is still not excluded. How exactly oxalate accumulation is regulated in plants is currently not clear. It is proposed that there is a novel and undetermined enzyme(s) in rice responsible for oxalate synthesis from glycolate/glyoxylate. Millerd et al. (1963b) mentioned that an enzyme oxidizing glycolate/glyoxylate in Oxalis pes-caprae differed from the defined GLO since it catalysed glyoxylate turnover more efficiently than glycolate. While evidence for multiple enzymes with glycolate and glyoxylate oxidase activity was also demonstrated in tobacco leaves by Havir (1983), Nishimura et al. (1983) claimed existence of only one glycolate oxidase in spinach leaves. Glyoxylate dehydrogenase for oxalate production was detected in animals and microbes (Tokimatsu et al., 1998) but has not yet been identified in plants. A glycolate dehydrogenase, catalysing direct oxidation of glycolate to oxalate without forming glyoxylate as an intermediate, was only reported in animals (Fry and Richardson, 1979). Another glycolate dehydrogenase, recently described in Arabidopsis mitochondria, catalyses glycolate oxidation to glyoxylate (Bari et al., 2004), and, similarly, Goyal and Tolbert (1996) observed a glycolate-quinone oxidoreductase system, which is associated with the chloroplast photosynthetic electron transport chain catalyses the oxidation of glycolate to glyoxylate. Whether such glycolate dehydrogenases could also catalyse the oxidation of glyoxylate to oxalate in plants is unknown. Lactate dehydrogenase might also act on glyoxylate to produce oxalate in plants (Davies and Asker, 1983). Further biochemical, molecular, and genetic analysis will help to identify the potential novel enzyme(s) and finally define the metabolic mechanism of oxalate accumulation and regulation in plants. We thank Dr Li-Zhen Tao (Department of Biochemistry and Molecular Biology, University of Massachusetts) for critically reading the manuscript. This work was supported by The National Science Foundation of China (No. 30270799, 30470152). 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Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved. For Permissions, please e-mail: [email protected]

Rodrigues, Simone M.;Andrade, Maxuel O.;Gomes, Ana Paula Soares;DaMatta, Fabio M.;Baracat-Pereira, Maria C.;Fontes, Elizabeth P.B.

doi: 10.1093/jxb/erj132pmid: 16595581

Abstract Despite extensive studies in eukaryotic aldehyde dehydrogenases, functional information about the ALDH7 antiquitin-like proteins is lacking. A soybean antiquitin homologue gene, designated GmTP55, has been isolated which encodes a dehydrogenase motif-containing 55 kDa protein induced by dehydration and salt stress. GmTP55 is closely related to the stress-induced plant antiquitin-like proteins that belong to the ALDH7 family. Transgenic tobacco (Nicotiana tabacum) and Arabidopsis (Arabidopsis thaliana) plants constitutively expressing GmTP55 have been obtained in order to examine the physiological role of this enzyme under a variety of stress conditions. Ectopic expression of GmTP55 in both Arabidopsis and tobacco conferred tolerance to salinity during germination and to water deficit during plant growth. Under salt stress, the germination efficiency of both transgenic tobacco and Arabidopsis seeds was significantly higher than that of their control counterparts. Likewise, under progressive drought, the transgenic tobacco lines apparently kept the shoot turgidity to a normal level, which contrasted with the leaf wilt phenotype of control plants. The transgenic plants also exhibited an enhanced tolerance to H2O2- and paraquat-induced oxidative stress. Both GmTP55-expressing Arabidopsis and tobacco seeds germinated efficiently in medium supplemented with H2O2, whereas the germination of control seeds was drastically impaired. Similarly, transgenic tobacco leaf discs treated with paraquat displayed a significant reduction in the necrotic lesions as compared with control leaves. These transgenic lines also exhibited a lower concentration of lipid peroxidation-derived reactive aldehydes under oxidative stress. These results suggest that antiquitin may be involved in adaptive responses mediated by a physiologically relevant detoxification pathway in plants. Aldehyde dehydrogenase, antiquitin, detoxification pathway, environmental stresses, stress tolerance, turgor-responsive protein Introduction Environmental stress conditions, such as water deficit and salinity, have become major constraints for plant growth, crop productivity, and species distribution. Among other consequences, both drought and high salinity produce osmotic stress by decreasing the water chemical activity and affecting the cell turgor (Zhu, 2001). These environmental stressors also cause a rapid and excessive accumulation of reactive oxygen species (ROS) in plant cells (Bartels, 2001; Zhu, 2001). In addition to reacting directly to proteins, amino acids, and nucleic acids, ROS cause a lipid peroxidation chain reaction resulting in chemically reactive cleavage products, largely represented by aldehydes. ROS accumulation is counteracted by antioxidant systems that include low-molecular-mass molecule and enzyme scavengers (Allen, 1995; Mittler, 2002), whereas the potentially toxic nature of aldehydes is challenged by increased aldehyde dehydrogenase (ALDH) activity as one of the cellular defence strategies in the detoxification of these stress-generated chemically reactive compounds (Sunkar et al., 2003). While some ALDHs have been described as part of this antioxidant defence system, other drought and salt stress-induced ALDHs seem to play a direct role in cellular osmoregulation by catalysing the synthesis of osmoprotectants (Kirch et al., 2004). Aldehyde dehydrogenase is a superfamily of enzymes catalysing the conversion of various endogenous and exogenous aldehydes to the corresponding carboxylic acids using the coenzyme NAD+ or NADP+ (Yoshida et al., 1998). The eukaryotic ALDHs can be organized into 21 families based on sequence identity (Sophos and Vasiliou, 2003). In general, 40% sequence similarity or less places the enzymes in a different family category, whereas 60% sequence identity categorizes members of a subfamily (Kirch et al., 2004). In mammals, different ALDH representatives have been implicated in intermediate metabolism, such as vitamin A biosynthesis and amino acid metabolism, as well as in detoxification of stress-generated aldehydes and osmoprotection (Perozich et al., 1999). The plant ALDH genes are represented in 11 ALDH families: ALDH2, ALDH3, ALDH5, ALDH6, ALDH7, ALDH10, ALDH11, ALDH12, ALDH18, ALDH19, and ALDH21. The ALDH11, ALDH19, and ALDH21 families are unique to plants and, more recently, ALDH sequences encoding members of a novel family, ALDH22, have been identified in Arabidopsis, maize, and rice genomes (Kirch et al., 2004). Biological function has been assigned to members of the plant ALDH superfamily in development and/or stress adaptation. Among the stress-related ALDHs, the plant ALDH3 and ALDH5 families are involved in detoxification of aldehydes (Bouché et al., 2003; Sunkar et al., 2003), whereas the ALDH10, ALDH11, and ALDH12 families act primarily in cellular osmoregulation by catalysing the synthesis of osmoprotectant (Kirch et al., 2004). The ALDH10 family is represented by the dehydration and salt-inducible betaine aldehyde dehydrogenase (BADH), which catalyses the oxidation of betaine aldehyde to the compatible solute glycine betaine, as an adaptation to osmotic stress (Weretilnyk and Hanson, 1990; Kumar et al., 2004). In Arabidopsis, the ALDH11 family consists of a single gene that encodes a non-phosphorylating glyceraldehyde 3-phosphate dehydrogenase, GAPDH (GAPN), whereas the ALDH12 family is represented by a mitochondrial Δ1-pyrroline-5-carboxylate dehydrogenase (P5CDH) gene (Kirch et al., 2004). P5CDH is a key enzyme in the degradation of proline to glutamate and its transcript is up-regulated by exogenous proline and salinity (Deuschle et al., 2001). Among the stress-associated ALDHs, the members of the ALDH7 family, also designated antiquitin, have not been related to any biochemical pathway. The aldehyde-oxidizing activity of the enzyme has been assayed using acetaldehyde and aromatic benzaldehyde as substrates, but the specific physiological substrate for antiquitin remains to be identified (Tang et al., 2002; Chan et al., 2003; Fong et al., 2003). The physiological function of antiquitin is believed to be related to the regulation of turgor pressure or to a general stress response. The plant antiquitin homologue gene has been shown to be induced by water deprivation and exposure to high salinity in pea (Pisum sativum), in canola (Brassica napus), and in Arabidopsis (Guerrero et al., 1990; Stroeher et al., 1995; Kirch et al., 2005). In mammals, the antiquitin gene is highly expressed in organs in which the osmotic balance must be maintained for proper function, such as the cochlea and kidney (Skvorak et al., 1997). Despite the stress-induced pattern of antiquitin gene expression, the functional significance of the evolutionary conserved antiquitin family has yet to be elucidated. In this investigation, an antiquitin homologue cDNA was isolated from soybean (Glycine max) that was highly represented in a dehydrated-seed cDNA library. To elucidate the function of ALDH7 from soybean, the current study was conducted using transgenic tobacco as a model system, as it can easily be transformed by A. tumefaciens. It was also reasoned that the wide distribution of plant ALDH7 homologues in distantly related genera would argue strongly for the conservation of the ALDH7 function as well. To test this prediction further, Arabidopsis was also included as a model system for the functional analyses. Both tobacco and Arabidopsis transgenic lines producing the soybean enzyme displayed a lower concentration of reactive aldehydes and enhanced tolerance to drought, salinity, and ROS-producing chemical treatments. These results suggest that the antiquitin-like ALDH7 gene might be involved in the detoxification of reactive aldehyde species generated by oxidative stress-associated lipid peroxidation. Materials and methods Plant material and greenhouse experiments Soybean plants (Glycine max cv. Cristalina) were germinated in 5.0 l pots containing a mixture of soil, sand, and dung (3:1:1 by vol.) and grown under standardized greenhouse conditions. The water-stress condition was induced in 40-d-old plants by withholding watering for 9 d before harvesting of tissues (Cascardo et al., 2000). Salt stress was imposed by irrigating the plants with 0.66 M NaCl solution for 9 d. Leaves, roots, and stems were harvested from unstressed and stressed plants, immediately frozen in liquid nitrogen, and stored at −80 °C. Isolation of an antiquitin homologue cDNA (ALDH7) from soybean The antiquitin-like cDNA, also designated GmATQ or GmTP55 (GenBank accession number AY250704), was isolated through BLAST searches of a Glycine max EST database that was developed from a soybean seed cDNA library prepared in this laboratory. The computer program CLUSTALX was used for sequence alignment and the phylogenetic tree was produced using the Genebee program (http://www.genebee.msu.su/services/phtree_reduced.html). Construction of plasmids The GmTP55 (GmATQ) protein was expressed as an N-terminal His-tagged fusion protein. For this purpose, the 1300 bp BamHI fragment was released from GmTP55 cDNA (pUFV388) and inserted into pET-16b. The resulting clone, pUFV458, contains a GmTP55 truncated fragment, which encodes amino acids 97–517, fused in-frame to the His tag. For plant transformation, the full-length GmTP55 cDNA fragment was transferred as an EcoRI fragment from pUFV388 to pCAMBIA1301Z, generating pUFV408. Alternatively, a binary recombinant plasmid was obtained through the GATEWAY system (Invitrogen Life Technologies Inc.). Briefly, the GmTP55 full-length cDNA fragment was amplified by PCR with appropriate extensions and introduced by recombination into the entry vector pDONR201, sequenced, and then transferred to the binary vector pK7WG2, yielding pK7-GmATQ. The resulting clones, pUFV408 and pK7-GmATQ, harbour the GmTP55 cDNA under the control of the CaMV 35S promoter and the polyadenylation signal of the T-DNA nopaline synthase (nos) gene. Antibody production The recombinant plasmid, pUFV458, was transformed into E. coli strain BL21 (DE3) and the synthesis of the recombinant protein was induced by 0.5 mM isopropyl thio-β-D-galactoside for 4 h at 37 °C (IPTG). The His-tagged protein was purified by affinity chromatography using Ni-chelating Sepharose resin (Amersham Pharmacia Biotech.) according to manufacturer's instructions. The recombinant purified protein was used as an antigen to raise polyclonal antisera in rabbits, which were immunized through subcutaneous injections at 2-week intervals. Protein extraction and immunoblotting analysis Total protein was extracted from an acetone dry powder, using a protocol adapted from Görg et al. (1988). Briefly, plant tissues (roots, leaves, and stems) were crushed in liquid nitrogen, and 2 g of the powder was homogenized with 10% (w/v) TCA in acetone containing 0.07% (v/v) 2-mercaptoethanol. Total protein was precipitated for 40 min at −20 °C, recovered by centrifugation at 16 000 g for 15 min, and washed two or three times with acetone containing 0.07% (v/v) 2-mercaptoethanol. The pellet was dried under vacuum, and 100 mg of the acetone dry powder was homogenized in 1 ml of 50 mM TRIS-HCl (pH 7.5), 1% (w/v) SDS, and 25 mM EDTA. Cell debris was removed by centrifugation at 25 000 g for 20 min and protein concentration was determined as described by Hill and Straka (1988). Equivalent amounts of total protein (30 mg) were resolved by SDS-PAGE on a 10% polyacrylamide gel and transferred to nitrocellulose membranes by electroblotting. The membrane was blocked with 3% (w/v) bovine serum albumin in TBST [100 mm TRIS-HCl (pH 8), 150 mm NaCl, 0.05% (v/v) Tween 20]. GmTP55 (GmALDH7) was detected using a polyclonal antibody raised against the recombinant protein at a 1:1000 dilution, followed by a goat anti rabbit IgG conjugated to alkaline phosphatase (Sigma) at a 1:5000 dilution. The activity of alkaline phosphatase was assayed using 5-bromo-4-chloro-3-indolyl phosphate (Life Technologies do Brasil Ltda, São Paulo, Brazil) and p-nitroblue tetrazolium (Life Technologies). Plant transformation Leaf discs from in vitro-grown tobacco (Nicotiana tabacum L. cv. Havana) plants were co-cultivated for 15 min with Agrobacterium tumefaciens strain LBA4404 containing the binary plasmid pUFV408. Transformed shoots were selected on Murashige and Skoog medium (Murashige and Skoog, 1962) supplemented with 6-benzylaminopurine (400 μg ml−1), timentin (500 μg ml−1), and hygromycin (50 μg ml−1). Regenerated shoots were rooted on phytohormone-free medium containing hygromycin (50 μg ml−1), transferred into soil, and grown under standardized greenhouse conditions (T0 plants) to generate seeds. Four independently regenerated hygromycin-resistant plants harbouring the GmTP55 sense construct were grown for further analyses. Tobacco plants were also transformed with the binary vector pCAMBIA1301Z without any insert. These hygromycin-resistant plants for the pCAMBIA1301Z incorporated binary vector as well as wild-type plants were used as controls. Arabidopsis thaliana Col-0 was transformed with the binary construct pK7-GmATQ by Agrobacterium tumefaciens-mediated transformation using the floral dip method (Clough and Bent, 1998). Transformants (T1) were selected on MS agar plates containing 50 mg l−1 kanamycin. Analysis of transgenic plants The presence of hyg or nptII and GmTP55 transgenes was analysed by PCR from leaf tissue samples. PCR was carried out on 20 ng of genomic DNA isolated from 4-week-old greenhouse-grown tobacco transgenic plants, using 0.4 μM each of hyg primers or GmTP55 gene-specific primers and one unit of Taq polymerase in a final volume of 25 μl. For confirmation of Arabidopsis transgenic lines, PCR was conducted on 20 ng of genomic DNA isolated from seedlings, using 0.4 μM each of nptII primers or GmTP55 gene-specific primers and one unit of Taq polymerase in a final volume of 25 μl. The GmTP55-specific primers were 4076-AntiF501 (coordinates 539–559, upstream) and 4077-AntiR506 (positions 1042–1063, downstream). The primers specific for the nptII gene were 5′-TCGACGTTGTCACTGAAGCGCG-3′ (sense) and 5′-GCGGTCAGCCCATTCGCCGCC-3′ (antisense) and for the hygromycin gene were 5′-CGCTTCTGCGGGCGATTTGTGTACG-3′ (sense) and 5′-TCAGCTTCGATGTAGGAGGGCGTGG-3′ (antisense). Transgene copy number was determined by segregation analyses. For segregation analysis, tobacco seeds were germinated on Murashige and Skoog medium containing 50 μg ml−1 hygromycin. Homozygous T1 lines with respect to the T-DNA loci were selected by determining the frequency of their antibiotic-resistant T2 seeds after self-pollination. Analysis of transgene expression The detection of transgene expression was carried out by gene-specific RT-PCR. Leaves were harvested from 4-week-old tobacco transgenic plants that were grown under standardized greenhouse conditions and immediately frozen in liquid nitrogen. Total RNA was extracted from leaves by the TRIZol method (Invitrogen). First-strand cDNA was synthesized from 2–5 μg of total RNA using the SuperScript III Kit (Invitrogen Life Technologies, Inc.) according to the manufacturer's instructions. PCR assays were performed with GmTP55-specific primers as described (Cascardo et al., 2000). Control reactions were conducted with polyA+ RNA without reverse transcriptase. PCR was also carried out with actin gene-specific primers to assess the quantity and quality of the cDNA. Protein accumulation was monitored by immunoblotting of total protein extracted from leaves of 4-week-old tobacco transgenic plants that were grown under standardized greenhouse conditions. Stress treatments To induce salinity stress during germination, both tobacco and Arabidopsis seeds were surface-sterilized and sown on agar plates containing MS medium with different concentrations of NaCl (0, 100, 150, and 200 mM). Tobacco seedlings were grown with a day/night cycle of 14/10 h at 28 °C and an irradiance of 200 μmol m−2 s−1 and Arabidopsis seedlings were grown in a growth chamber with a day/night cycle of 16/8 h at 22 °C and an irradiance of 50 μmol m−2 s−1. For H2O2 treatment, both surface-sterilized tobacco and Arabidopsis seeds were placed on filter paper prewetted with deionized water containing different concentration of H2O2 (0, 10, 15, and 20 μM). The conditions of seed germination were as described above. For paraquat-induced oxidative stress, 15 mm leaf discs from 2-month-old transgenic and untransformed plants were incubated with a series of paraquat (methyl viologen, Sigma) concentrations (0, 1, 2, and 4 μM) and kept for 1 h in the dark, followed by incubation for 18 h with a light intensity of 200 μmol m−2 s−1 at 24 °C. The extent of the oxidative damage was assessed by determining the necrotic area of the disc leaf using the QUANT 1.0.1-R1 program. The water-stress treatment was induced in soil-grown tobacco plants, as described previously (Alvim et al., 2001). Briefly, transgenic T1 seeds were germinated in kanamycin-containing medium for 3 weeks before transplantation. Plants were grown in a mixture of soil, sand, and dung (3:1:1 by vol.) for 2 weeks in the greenhouse under natural conditions of light, relative humidity at 70%, and controlled temperature, 18 °C and 30 °C (night and day). After 30 d of growth with normal water supply, drought stress was imposed by withholding water for 2 weeks from half of the transgenic plants. The remaining transgenic plants received normal water supply continuously. In control experiments, the same conditions of water availability were applied in untransformed control plants at the same developmental stage as transgenic GmTP55 plants. All the experiments were conducted with five clones from the independently transformed lines. Assay of lipid peroxidation The malondialdehyde (MDA) content was determined by the reaction of thiobarbituric acid (TBA) as described by Cakmak and Horst (1991). Results Isolation of GmTP55, a soybean antiquitin homologue that belongs to the ALDH7 family A soybean antiquitin-related cDNA (GenBank accession number AY250704) was randomly isolated from a Glycine max seed cDNA library constructed in λZAPII. The full-length soybean antiquitin cDNA sequence encodes a protein with an estimated Mr of 55 562 and pI 5.27. The GmTP55 (Glycine max turgor-reponsive 55 kDa protein), also designated GmATQ (Glycine max antiquitin), is most closely related to the pea turgor-reponsive protein 26g, an antiquitin-related ALDH (82% sequence identity). Based on ALDH superfamily phylogeny, GmTP55 (ALDH-Gm) segregates more closely with clusters of the ALDH7 family, which contains antiquitin-like (ATQ) proteins found in plants, fish, and mammals (Fig. 1). It retains more than 70% sequence identity with other plant antiquitin-like proteins and shares remarkable conservation of primary structure with the human and mouse antiquitin (about 60% sequence identity). In addition, the soybean antiquitin-like protein possesses a conserved domain characteristic of members of the ALDH7 family that encompasses the aldehyde dehydrogenase glutamic acid active site 270LELSGNNA277 (PROSITE PS 00687; Perozich et al., 1999) and a transmembrane segment 158IVGVISAFNFPCAVLGWN ACIAL180 (Guerrero et al., 1990; Lee et al., 1994). Fig. 1 View largeDownload slide Phylogenetic tree based on family 7 (ALDH7) and family 10 (BADH) aldehyde dehydrogenase sequences. Amino sequences from ALDHs were aligned using ClustalX, and the dendrogram was generated using Genebee program. The sequences come from members of the ALDH7 family (antiquitin), such as ALDH7 of Brassica napus (ALDH-Bn, accession Q41247), Arabidopsis thaliana (ALDH-At Q95Y67), Malus domestica (ALDH-Md, Q9ZPB7), Pisum sativum (ALDH-Ps P25795), Glycine max (ALDH-Gm, AY250704), Oryza sativa (ALDH-Os, AF323586), Dictyostelium discoideum (ALDH-Dd, P83401), human (ALDH-Hs, antiquitin, P49419), Caenorhabditis elegans (ALDH-Ce, P46562); members from the betaine aldehyde dehydrogenase, ALDH10 family, such as BADH of Amaranthus hypochondriacus (BADH-Ah, O04895), Beta vulgaris (BADH-Bv, P28237), Spinacea oleracea (BADH-So, P17202), Arabidopsis thaliana (BADH-At, Q9S795), Avicennia marina (BADH-Am, Prf:2715330A), Hordeum vulgare (BADH-Hv, Q40024), Oryza sativa (BADH-Os, O24174), E.coli (BADH-Ec, P77674), and an Arabidopsis thaliana glucose-6-phosphate dehydrogenase (G6PD6-At, Q9FJI5), as an outgroup. Numbers at nodes indicate the percentage bootstrap scores (100 replications) and those shown below the frame indicate the percentage of sequence identity. The arrow indicates the position of the Glycine max ALDH7 protein. Fig. 1 View largeDownload slide Phylogenetic tree based on family 7 (ALDH7) and family 10 (BADH) aldehyde dehydrogenase sequences. Amino sequences from ALDHs were aligned using ClustalX, and the dendrogram was generated using Genebee program. The sequences come from members of the ALDH7 family (antiquitin), such as ALDH7 of Brassica napus (ALDH-Bn, accession Q41247), Arabidopsis thaliana (ALDH-At Q95Y67), Malus domestica (ALDH-Md, Q9ZPB7), Pisum sativum (ALDH-Ps P25795), Glycine max (ALDH-Gm, AY250704), Oryza sativa (ALDH-Os, AF323586), Dictyostelium discoideum (ALDH-Dd, P83401), human (ALDH-Hs, antiquitin, P49419), Caenorhabditis elegans (ALDH-Ce, P46562); members from the betaine aldehyde dehydrogenase, ALDH10 family, such as BADH of Amaranthus hypochondriacus (BADH-Ah, O04895), Beta vulgaris (BADH-Bv, P28237), Spinacea oleracea (BADH-So, P17202), Arabidopsis thaliana (BADH-At, Q9S795), Avicennia marina (BADH-Am, Prf:2715330A), Hordeum vulgare (BADH-Hv, Q40024), Oryza sativa (BADH-Os, O24174), E.coli (BADH-Ec, P77674), and an Arabidopsis thaliana glucose-6-phosphate dehydrogenase (G6PD6-At, Q9FJI5), as an outgroup. Numbers at nodes indicate the percentage bootstrap scores (100 replications) and those shown below the frame indicate the percentage of sequence identity. The arrow indicates the position of the Glycine max ALDH7 protein. GmTP55 is induced by salinity and water deficit The antiquitin-like protein GmTP55 has been expressed in E. coli as N-terminal His-tagged fusion protein and purified to raise antibodies. Immunoblottings of total protein from different tissues of soybean grown under normal conditions demonstrated that the GmTP55 protein accumulates predominantly in the stem (Fig. 2A, lane S) and it is barely detected in leaves (lane L). Several turgor-responsive ALDH7 genes have been shown to be induced by dehydration and high salinity (Guerrero et al., 1990; Stroeher et al., 1995; Kirch et al., 2005). Accordingly, GmTP55 accumulation is induced by water deficit (Fig. 2B) and salt stress (Fig. 2A) in all organs tested. Fig. 2 View largeDownload slide GmTP55 is induced by salinity and water deficit. (A) GmTP55 accumulation in response to NaCl. Equivalent amounts of total protein from stems (S), roots (R), and leaves (L) from soybean plants grown under normal conditions (0 mM) and from NaCl-treated soybean plants (600 mM) were fractionated by SDS-PAGE and immunoblotted using an anti-GmTP55 serum. (B) Induction of GmTP55 accumulation by drought. Immunoblotting of total protein extracted from soybean plants grown under water deficit for 9 d. Normal shows the GmTP55 levels in plants before withholding watering. Fig. 2 View largeDownload slide GmTP55 is induced by salinity and water deficit. (A) GmTP55 accumulation in response to NaCl. Equivalent amounts of total protein from stems (S), roots (R), and leaves (L) from soybean plants grown under normal conditions (0 mM) and from NaCl-treated soybean plants (600 mM) were fractionated by SDS-PAGE and immunoblotted using an anti-GmTP55 serum. (B) Induction of GmTP55 accumulation by drought. Immunoblotting of total protein extracted from soybean plants grown under water deficit for 9 d. Normal shows the GmTP55 levels in plants before withholding watering. Expression of GmTP55 in transgenic tobacco and Arabidopsis Tobacco was transformed via Agrobacterium tumefaciens with the GmTP55 gene, under the control of 35S cauliflower mosaic virus (CaMV) promoter and the nos polyadenylation signal. Several independent transgenic lines were established, transferred into soil, and grown in a greenhouse to generate seeds (T1 seeds). The integration and gene copy number of the construct in the transformed plants were further confirmed by PCR analysis with GmTP55-specific primers (Fig. 3A) and segregation analysis of the hyg gene in the T0 progenies (T1 plants). Four independent transgenic sense lines (TP55-S1, TP55-S2, TP55-S3, and TP55-S5) were selected for further analyses. Under normal, non-stressed conditions, GmTP55 mRNA was detected in their leaves (Fig. 3B, lanes S1, S2, S3, and S5) but not in the wild type (data not shown) and pCAMBIA1301Z-transformed control (lane pC) tobacco leaves. Apparently, the primers are capable of discriminating between homologous sequences present in the tobacco genome and GmTP55-specific sequences, as they also failed to amplify a homologous cDNA from drought untransformed tobacco leaves (data not shown). Under normal, non-stressed conditions, the GmTP55 protein levels were detected in the transgenic leaves (Fig. 3C, lanes S1, S2, S3 and S5) but not in the wild type (data not shown) and pCAMBIA-transformed control (pC) tobacco leaves. Fig. 3 View largeDownload slide Analysis of transgene expression in tobacco plants transformed with the GmTP55 cDNA. (A) Diagnostic of transgene incorporation. Total DNA was isolated from greenhouse-grown transgenic plants and provided the template in PCR reactions using GmTP55 gene-specific primers. S refers to the plants transformed with the GmTP55 cDNA. Different numbers following the S symbol indicate that the transgenic plants were originated from independent events of transformation. WT corresponds to the result of a PCR reaction performed with DNA from control plants and pC from pCAMBIA-transformed control plants. (B) Accumulation of GmTP55 transcripts in tobacco transgenic plants. RT-PCR assays were performed using cDNA prepared from polyA+ RNA of pCAMBIA-transformed control plants (pC), GmTP55-transformed plants (S), and the GmTP55 gene-specific primers. The positions of DNA standard markers are indicated on the left in kb. (C) Enhanced levels of GmTP55 (ALDH7) protein in tobacco transgenic plants. Equivalent amounts of total protein (30 mg per lane) extracted from the fully expanded third leaf of four independent transgenic 35S-TP55-S (sense) tobacco plants (lanes S1, S2, S3, and S5) and pCAMBIA-transformed control plants (pC) were fractionated by SDS-PAGE, transferred to nitrocellulose membrane, and probed with the anti-TP55 antibody. The arrow indicates the position of the GmTP55 protein. Fig. 3 View largeDownload slide Analysis of transgene expression in tobacco plants transformed with the GmTP55 cDNA. (A) Diagnostic of transgene incorporation. Total DNA was isolated from greenhouse-grown transgenic plants and provided the template in PCR reactions using GmTP55 gene-specific primers. S refers to the plants transformed with the GmTP55 cDNA. Different numbers following the S symbol indicate that the transgenic plants were originated from independent events of transformation. WT corresponds to the result of a PCR reaction performed with DNA from control plants and pC from pCAMBIA-transformed control plants. (B) Accumulation of GmTP55 transcripts in tobacco transgenic plants. RT-PCR assays were performed using cDNA prepared from polyA+ RNA of pCAMBIA-transformed control plants (pC), GmTP55-transformed plants (S), and the GmTP55 gene-specific primers. The positions of DNA standard markers are indicated on the left in kb. (C) Enhanced levels of GmTP55 (ALDH7) protein in tobacco transgenic plants. Equivalent amounts of total protein (30 mg per lane) extracted from the fully expanded third leaf of four independent transgenic 35S-TP55-S (sense) tobacco plants (lanes S1, S2, S3, and S5) and pCAMBIA-transformed control plants (pC) were fractionated by SDS-PAGE, transferred to nitrocellulose membrane, and probed with the anti-TP55 antibody. The arrow indicates the position of the GmTP55 protein. Segregation analysis suggested that the lines TP55-S2 and TP55-S3 plants appeared to have an integrated T-DNA locus on a single chromosome, since 75% of their T1 segregating seedlings were resistant to hygromycin (Table 1). In addition, these lines were phenotypically normal and, therefore, they were selected for further studies. The selected transgenic lines also exhibit similar developmental performance as the wild type and pCAMBIA-transformed control lines (Table 2). Table 1 Expression of hygromycin resistance and salt stress tolerance in the T1 generation of transgenic tobacco plants Plant lines tested  Hygromycin- resistant seedlings  Ratio  χ2  200 mM NaCl-tolerant seedlings  Ratio  χ2  TP55-S2  1377+/486−  3:1  1.23  316+/118−  3:1  1.10  TP55-S3  1244+/455−  3:1  2.87  208+/68−  3:1  0.02  Controla  0003+/997−  –  –  NDb  ND  ND  Plant lines tested  Hygromycin- resistant seedlings  Ratio  χ2  200 mM NaCl-tolerant seedlings  Ratio  χ2  TP55-S2  1377+/486−  3:1  1.23  316+/118−  3:1  1.10  TP55-S3  1244+/455−  3:1  2.87  208+/68−  3:1  0.02  Controla  0003+/997−  –  –  NDb  ND  ND  χ2 tests indicate good agreement with segregation ratio indicated. a Untransformed, wild-type plants. b Not determined. View Large Table 2 Growth measurements of transgenic lines Plant lines tested  Height (cm)  Floweringa  Aerial part (DW)b  Roots (DW)b  Wild type  98.7±5.8  62.3±3.2  51.03±21.50  7.37±2.1  TP55-S2  95.4±12.2  61.7±5.1  53.50±15.47  7.32±1.95  TP55-S3  87.2±14.1  58.2±2.3  47.20±7.37  6.83±0.84  Controlc  85.5±9.8  55.7±5.1  49.2±12.25  6.91±1.12  Plant lines tested  Height (cm)  Floweringa  Aerial part (DW)b  Roots (DW)b  Wild type  98.7±5.8  62.3±3.2  51.03±21.50  7.37±2.1  TP55-S2  95.4±12.2  61.7±5.1  53.50±15.47  7.32±1.95  TP55-S3  87.2±14.1  58.2±2.3  47.20±7.37  6.83±0.84  Controlc  85.5±9.8  55.7±5.1  49.2±12.25  6.91±1.12  Data are given as mean ±SD from three replicates. No significant differences at P ≤0.05 were observed. a Days in greenhouse. b Dry weight (g). c Plants transformed with the binary vector alone. View Large Salt tolerance during germination and early seedling development As a first step towards understanding the function of antiquitin, the effect of the GmTP55 gene expression on salt tolerance was evaluated. Tobacco transgenic T1 seeds expressing the soybean antiquitin gene as well as wild-type seeds were allowed to germinate in MS media (Murashige and Skoog, 1962) containing different concentrations of NaCl, as indicated in Fig. 4A. Under normal conditions (0 mM NaCl) both wild-type and T1 transgenic seeds germinated into seedlings with similar frequency and no phenotypic difference on seedling development was observed. Between wild-type and tobacco transgenic lines, differences of germination efficiency and seedling development became apparent at 100 mM NaCl and were statistically significant at 150 mM NaCl (Fig. 4B). While the germination efficiency of wild-type seeds was 30% reduced at 150 mM, TP55-S2 and TP55-S3 transgenic lines kept the germination frequency to normal levels. Both tobacco transgenic lines exhibited enhanced tolerance to salinity, although to different extents, as the TP55-S2 transgenic seeds exhibited a better performance at high salt concentrations. In fact, TP55-S2 transgenic seeds germinated with high efficiency (>90%) under 200 mM NaCl, whereas only 58% of TP55-S3 seeds germinated into seedlings under this condition. For the TP55-S2 and TP55-S3 independent transgenic lines analysed, the salt-tolerant germination phenotype at 200 mM NaCl was found to be linked to the hyg gene because it segregated with the same ratio as the hygromycin-resistant phenotype (Table 1). Since transformation of tobacco with the hyg gene alone did not confer tolerance to salinity during seed germination, it was concluded that the salt-tolerant germination phenotype was caused by ectopic expression of the antiquitin-like gene. In fact, PCR analysis of the segregating population with GmTP55-specific primers further confirmed the results (data not shown). Fig. 4 View largeDownload slide GmTP55 transgenic lines exhibit increased tolerance to salinity during germination and early seedling development. (A) Germination efficiency of transgenic tobacco seeds under salt stress. Transgenic (TP55-S2 and TP55-S3) and control (WT) seeds were germinated on MS agar plates containing the indicated concentrations of NaCl. The data are expressed as a percentage of 100 seeds germinated from each indicated line and the values are given as mean ±SD of five determinations from each independent transformant line. The asterisks indicate significant differences at P ±0.05. (B) Germination and seedling development of Arabidopsis transgenic seeds exposed to NaCl. Transgenic (ATQ8 and ATQ12) and control (WT) Arabidopsis seeds were germinated on MS agar plants containing the indicated concentrations of NaCl for 15 d. The data are expressed as a percentage of 200 seeds germinated from each indicated line and the values are given as mean ±SD of three independent experiments. The asterisks indicate significant differences at P ≤0.05. Fig. 4 View largeDownload slide GmTP55 transgenic lines exhibit increased tolerance to salinity during germination and early seedling development. (A) Germination efficiency of transgenic tobacco seeds under salt stress. Transgenic (TP55-S2 and TP55-S3) and control (WT) seeds were germinated on MS agar plates containing the indicated concentrations of NaCl. The data are expressed as a percentage of 100 seeds germinated from each indicated line and the values are given as mean ±SD of five determinations from each independent transformant line. The asterisks indicate significant differences at P ±0.05. (B) Germination and seedling development of Arabidopsis transgenic seeds exposed to NaCl. Transgenic (ATQ8 and ATQ12) and control (WT) Arabidopsis seeds were germinated on MS agar plants containing the indicated concentrations of NaCl for 15 d. The data are expressed as a percentage of 200 seeds germinated from each indicated line and the values are given as mean ±SD of three independent experiments. The asterisks indicate significant differences at P ≤0.05. Similar results were observed for the Arabidopsis transgenic seeds, ATQ8 and ATQ12, which displayed an enhanced tolerance to salinity during germination and seedling development (Fig. 4C). At 100 mM NaCl, the GMTP55-expressing seeds germinated with high efficiency (100% for ATQ8 transgenic line and >60% for ATQ12 transgenic line), whereas less than 10% of the control, untransformed seeds germinated into seedlings under similar conditions. Water stress tolerance of soil-grown transgenic plants Because GmTP55 (Fig. 2B) and its plant homologues have also been shown to be induced by water deficit (Guerrero et al., 1990; Stroeher et al., 1995; Kirch et al., 2005), the response of the tobacco transgenic lines to drought stress was examined next. For this experiment, young seedlings were transferred to a greenhouse where half of the plants received no irrigation and the remaining ones were irrigated throughout the period of the experiment. After 2 weeks under progressive dehydration, a drought stress-tolerant phenotype was clearly developed by the transgenic plants expressing the GmTP55 gene (Fig. 5). Whereas the untransformed, wild-type control leaves were completely wilted (relative water content 39.5±1.5%), the transgenic leaves apparently kept the turgidity to a higher level (relative water content of TP55-S2, 61.2±0.3% and TP55-S3, 52.2±0.9%). These results were not due to differences in the developmental performance of the transgenic lines, because, under irrigation, the overall development of wild-type and transgenic lines was phenotypically undistinguishable (bottom panel). The likely maintenance of turgidity in stressed sense plants (Fig. 5) might suggest that some degree of osmotic adjustment in these plants helped to some extent to prevent cellular dehydration. Fig. 5 View largeDownload slide GmTP55 overexpression confers drought stress tolerance to transgenic plants. Drought condition was induced in 6-week-old control (WT) and transformed seedlings grown in a greenhouse by withholding irrigation for 2 weeks. At the bottom, wild-type and transgenic plants received normal water supply continuously. Fig. 5 View largeDownload slide GmTP55 overexpression confers drought stress tolerance to transgenic plants. Drought condition was induced in 6-week-old control (WT) and transformed seedlings grown in a greenhouse by withholding irrigation for 2 weeks. At the bottom, wild-type and transgenic plants received normal water supply continuously. Performance of GmTP55-overexpressing plants under oxidative stresses Both water deficit and salinity often promote the formation of reactive oxygen species (ROS) that interact directly with different macromolecules. In particular, the destruction of the lipid membranes leads to the formation of lipid hydroperoxides and their toxic aldehyde degradation products. To determine whether the stress protective role of GmTP55 is associated with an aldehyde detoxification pathway, oxidative stress was induced by treating transgenic lines with H2O2 and paraquat. While 10 μM H2O2 did not affect the germination efficiency and seedling development of tobacco transgenic seeds, it promoted a 50% inhibition of wild-type, control seed germination (Fig. 6A). This significantly enhanced tolerance to H2O2 of transgenic seeds persisted with the progressive increase of H2O2 concentration (up to 20 μM). Likewise, Arabidopsis transgenic seeds germinated more efficiently in the presence of H2O2 than wild-type, untransformed seeds (Fig. 6B). Fig. 6 View largeDownload slide H2O2 tolerance of transgenic lines during germination. Seeds from tobacco transgenic (A) and Arabidopsis transgenic (B) lines as well as from their wild-type counterparts (control) were germinated under various concentrations of H2O2 (as indicated). Data are the mean ±SD of three independent experiments. The asterisks indicate significant differences at P ≤0.05. Fig. 6 View largeDownload slide H2O2 tolerance of transgenic lines during germination. Seeds from tobacco transgenic (A) and Arabidopsis transgenic (B) lines as well as from their wild-type counterparts (control) were germinated under various concentrations of H2O2 (as indicated). Data are the mean ±SD of three independent experiments. The asterisks indicate significant differences at P ≤0.05. The TP55-S2 and TP55-S3 tobacco transgenic lines were also included in a resistance test against paraquat, as an alternative oxidative stress-inducing agent. The visible injuries, resulted from oxidative damages, were recorded on leaf discs from transgenic and untransformed plants (Fig. 7) and the extent of leaf necrotic area was measured with the program Quant 1.0.1-R1 (Table 3). Leaf discs from both TP55-S2 and TP55-S3 transgenic tobacco were able to tolerate high concentrations of paraquat up to 4 μM and 2 μM, respectively, whereas control leaf discs were bleached in concentrations as low as 1 μM of paraquat (Fig. 7A). As indicated by the area of leaf bleaching, while 4 μM paraquat treatment caused almost total chlorophyll loss in untransformed leaves (98% necrotic area), the tobacco transgenic lines were more resistant to paraquat, as their necrotic areas were as low as 29.5% (TP55-S2) and 58.8% (TP55-S3) under the same conditions. Fig. 7 View largeDownload slide GmTP55 reduces paraquat-induced lipid peroxidation in transgenic lines. (A) Paraquat visual injury. Leaf discs of 1.5 cm of diameter from wild type (WT) and tobacco transgenic lines (TP55-S2 and TP55-S3) were incubated with the indicated concentrations of paraquat (MV) for 1 h dark period followed by 18 h under light. (B) Lipid peroxidation expressed as MDA contents of paraquat-treated leaf discs. Leaf discs from control (WT) and tobacco transgenic lines (TP55-S2 and TP55-S3) were treated with paraquat and the malondialdehyde (MDA) content was determined. Values are given as mean ±SD from three replicates. The asterisks indicate significant differences at P ≤0.05. Fig. 7 View largeDownload slide GmTP55 reduces paraquat-induced lipid peroxidation in transgenic lines. (A) Paraquat visual injury. Leaf discs of 1.5 cm of diameter from wild type (WT) and tobacco transgenic lines (TP55-S2 and TP55-S3) were incubated with the indicated concentrations of paraquat (MV) for 1 h dark period followed by 18 h under light. (B) Lipid peroxidation expressed as MDA contents of paraquat-treated leaf discs. Leaf discs from control (WT) and tobacco transgenic lines (TP55-S2 and TP55-S3) were treated with paraquat and the malondialdehyde (MDA) content was determined. Values are given as mean ±SD from three replicates. The asterisks indicate significant differences at P ≤0.05. Table 3 Leaf necrotic area measured by Quant 1.0.1-R1 software Plant lines tested  Paraquat concentration     0 μM  1 μM  2 μM  4 μM  Controla  0%  36.0±0.6%  61.8±0.8%  97.0±0.3%  TP55-S2  0%  13.6±0.2%  21.7±0.1%  29.5±0.7%  TP55-S3  0%  14.1±0.7%  46.2±0.6%  56.9±0.3%  Plant lines tested  Paraquat concentration     0 μM  1 μM  2 μM  4 μM  Controla  0%  36.0±0.6%  61.8±0.8%  97.0±0.3%  TP55-S2  0%  13.6±0.2%  21.7±0.1%  29.5±0.7%  TP55-S3  0%  14.1±0.7%  46.2±0.6%  56.9±0.3%  Values for leaf necrotic area are the mean ±standard deviation from three replicates. a Untransformed, wild-type plants. View Large Oxidative stress promotes increased levels of ROS and subsequent lipid peroxidation. The levels of lipid peroxidation were measured in paraquat-treated leaves on the basis of the accumulation of malondialdehyde (MDA), a major product of lipid peroxidation (Esterbauer et al., 1991). As shown in Fig. 7, significant differences in the levels of MDA were detected among the paraquat-treated lines. A significant reduced accumulation of lipid peroxidation-derived reactive aldehydes was observed in both TP55-S2 and TP55-S3 transgenic tobacco as compared to control, untransformed lines. These results indicate that antiquitin-like ALDH7 may be involved in the detoxification of aldehydes generated by lipid peroxidation after the formation of ROS. Discussion ALDHs make a large gene family in plants comprising at least 11 subfamilies whose members are involved in development and/or stress adaptation. Among the stress-related ALDHs, the plant ALDH3 and ALDH5 families are involved in detoxification of aldehydes, whereas the ALDH10 and ALDH11 families act primarily in cellular osmoregulation by catalysing the synthesis of osmoprotectants. Members of the ALDH7 family of aldehyde dehydrogenase superfamily have been identified in humans, fishes and plants, but functional studies are lacking. The characterization of an ALDH7 gene is described here and it is shown that it can provide a protective function for the plants under a wide range of stresses such as dehydration, salinity, and oxidative stress. Despite the fact that no biochemical pathway has been assigned to the ALDH7 proteins, it has been hypothesized that this family of ALDHs, that includes the human antiquitin, plays a direct role in the maintenance of osmotic homeostasis. This hypothesis has been raised based on three observations: (i) all the plant ALDH7 proteins already described have been shown to be induced by dehydration and salinity (Guerrero et al., 1990; Stroeher et al., 1995; Kirch et al., 2005), (ii) the expression of the human antiquitin predominated in organs that depend on a tight osmotic balance for proper function (Skvorak et al., 1997), and (iii) representatives of several ALDH families have been demonstrated to be involved in osmoregulation (Kirch et al., 2004). However, two lines of evidence that ALDH7 may function in aldehyde detoxification have been provided. First, the ectopic expression of GmTP55 in both Arabidopsis and tobacco resulted in cross-tolerance to multiple abiotic stresses that share the oxidative stress, as a common component. Oxidative stress is associated with increased levels of ROS that cause peroxidation of membrane lipids and consequent accumulation of toxic degradation products, largely represented by aldehydes. The GmTP55-mediated cross-tolerance mechanism may underscore a potential role of ALDH7 in detoxification of reactive aldehydes derived from lipid peroxidation. Second, the broad stress tolerance of the GmTP55-overexpressing transgenic lines was correlated with a decrease in lipid peroxidation, as detected by a significant decrease in the accumulation of MDA in transgenic lines. Similar results were obtained by overexpression of At-ALDH3 in Arabidopsis and MsALR from alfafa (Medicago sativa) in tobacco (Oberschall et al., 2000; Sunkar et al., 2003). The analyses of both Arabidopsis and tobacco transgenic lines indicate that overexpression of both the aldehyde dehydrogenase (At-ALDH3) and aldehyde reductase (MsALR) improves stress-tolerance most likely by scavenging toxic aldehydes and thus reducing lipid peroxidation. Although further studies will be necessary to discern the precise mechanism of GmTP55-mediated stress tolerance, its potential aldehyde detoxifying activity may provide a link for the apparent effectiveness of GmALDH7 protective properties against several abiotic stresses. Nevertheless, these data did not rule out the possibility that lipid peroxidation was reduced in transgenic leaves by activation of alternative osmolyte- producing pathways. Although several functions have been attributed to osmolytes, such as stabilization of cytoplasmic components, water retention, and ion sequestration, the underlying mechanism of osmolyte action and their physiological role under dehydration remain largely unknown (Hare et al., 1998). Different approaches to increase stress tolerance have been undertaken by manipulating and reprogramming the expression of endogenous stress-related genes. In general, strategies targeting transcription factor expression have been shown to be effective due to the consequent up-regulation of many downstream genes (Jaglo-Ottosen et al., 1998; Kasuga et al., 1999; Hsieh et al., 2002). However, enhanced stress tolerance has also been achieved by changing the expression of a single downstream gene (Zhu, 2001; Kumar et al., 2004). In this case, two distinct functional classes of genes have been demonstrated to be effective targets for engineering stress tolerance. The first class encompasses genes involved in mechanisms that prevent intracellular stress build-up. An example in this class includes the Na+/H+-antiporter gene whose overexpresssion in tomato and Arabidopsis promoted a significant increase in NaCl resistance (Apse et al., 1999). The second class acts functionally in the detoxification of toxic by-products and in cellular repair, such as the antioxidant system genes (Gupta et al., 1993; Badawi et al., 2004). The aldehyde dehydrogenase superfamily has been shown to encompass both classes of downstream genes, as the ALDH10 gene family is involved in the maintenance of osmotic homeostasis (Kirch et al., 2004), whereas genes from the ALDH3 family are clearly involved in aldehyde detoxification-mediated stress tolerance mechanisms in plants (Sunkar et al., 2003). However, the majority of these ALDH genes are involved in some aspects of intermediary metabolism in plants and, as a consequence, their overexpression, while it has been shown to be effective on enhancing stress tolerance, also adversely impacts plant growth under optimal growth conditions. Thus, the pleiotropic effects resulted from up-regulation of ALDH genes under optimal conditions may counteract advantages of transgene-mediated improvements in the physiological performance of the transgenic plants under stress conditions. In this context, these results on ALDH7 ectopic expression in transgenic plants incorporate relevant implications for agriculture as the ALDH7-overexpressing lines showed enhanced resistance to water deficit, salinity and oxidative stress, but did not exhibit growth-related phenotypes under normal conditions. In fact, the transgenic plants were phenotypically indistinguishable from the control plants under favourable growth conditions. Collectively, these results indicate that GmALDH7 may be an effective engineering target to improve environmental stress resistance in agriculturally important crops without affecting the overall field performance of transgenic crops under optimal conditions. This research was supported by the Brazilian Government Agency, CNPq Grants 50.6119/2004-1, 501189/2004-1, 500605/2004-1, and 470787/2004-0 (to EPBF). SMR was supported by a FAPEMIG graduate fellowship from the Minas Gerais State, Brazil. MOA and APSG were supported by a CNPq undergraduate scholarship from the Brazilian Government. The authors thank Dr Andréa Miyasaka and Dr Luiz Orlando de Oliveira for helpful discussions and Dr Alessandro J Waclawovsky for technical assistance. 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Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved. For Permissions, please e-mail: [email protected]

Gutierrez, Laurent;Conejero, Geneviève;Castelain, Mathieu;Guénin, Stéphanie;Verdeil, Jean-Luc;Thomasset, Brigitte;Van Wuytswinkel, Olivier

doi: 10.1093/jxb/erj138pmid: 16606634

Abstract A cDNA-AFLP approach on Linum usitatissimum (flax) was used to identify genes specifically expressed during the seed maturation process. Among the 20 000 cDNA-AFLP tags produced, 486 were selected for their seed-specific expression during maturation. When compared with the publicly available databases, half of them presented some significant similarity with known plant sequences. The results obtained confirmed the accuracy of the approach as numerous genes previously described as being expressed exclusively in plant seeds were identified in this screen. The focus was on sequences similar to plant regulators involved in the control of gene expression, either at the transcriptional, post-transcriptional, or post-translational levels. Using a real-time RT-PCR approach, seed-specific expression kinetics were confirmed for 13 of these regulators that were never characterized for being expressed during seed maturation. Among these, a flax gene of the non-LEC1-like HAP3 family and a flax MYB factor were shown to be expressed in specialized tissues of flax embryo using an in situ hybridization approach. By expression kinetic comparison between these flax genes and their Arabidopsis counterparts, it was found that the new HAP3 gene should be related to a ubiquitous seed maturation mechanism, while a new MYB factor appears to be related to a more seed-specific maturation mechanism. These results demonstrate the utility of the flax database in not only identifying new genes expressed during seed maturation but also in being able to highlight the distinction between conserved and non-conserved seed maturation mechanisms. cDNA-AFLP, flax, gene expression, maturation, seed Introduction Seed development is a critical process in the life cycle of higher plants, allowing the connection between two distinct sporophytic generations leading to the maintenance of the species. According to several plant models, this process can be divided into morphogenesis and maturation stages (Goldberg et al., 1994). During morphogenesis, the 2n zygote will divide following a stereotyped cell division set leading to the formation of the heart-stage embryo (Laux et al., 2004). Maturation begins from early torpedo stage, proceeds through a period of embryo growth and seed filling, and ends with a desiccation phase after which the embryo enters into a quiescent state, thereby permitting its storage and survival in various environmental conditions (Bewley and Black, 1994). The storage compounds found in most seeds consist of carbohydrates, oils, or specialized storage proteins. These reserves are of major importance because of their involvement in a successful early seedling growth but also because they represent the economic value of many crops. Whereas the main biosynthesis pathways involved in seed filling are well known, their regulation still remains widely uncharacterized. Indeed, while pathways for starch (James et al., 2003) or oil (Schmid and Ohlrogge, 1996) biosynthesis are well described, their accurate regulations are not understood (Hills, 2004). Linum usitatissimum (flax) is an interesting crop regarding the diversity of its storage products. Indeed, flax seeds accumulate oil particularly rich in linoleic and linolenic acid which is quite unusual among oleaginous plants (Morris, 2003). Moreover, 2S, 7S, and 11S types of storage proteins (Marcone et al., 1994, 1998) are expressed in flax seeds. This diversity is also quite unusual. Generally, seeds of other plant species accumulate preferentially only two of the three types of storage proteins. Finally, flax seeds are a source of fibre, mucilage carbohydrates (Cui, 2001), and remarkable secondary metabolites like phytoestrogen lignans (Axelson et al., 1982). All these components contribute to the interest shown in flax seed in the areas of nutrition and therapeutics, in which flax seed, for example, has been implicated in reducing metastasis formation (Dabrosin et al., 2002), cardiovascular risks (Bloedon and Szapary, 2004), and hypercholesterolemy (Lemay et al., 2002; Bhathena et al., 2003). As a consequence, flax appeared to be an extremely informative model for seed maturation study regarding the variety of biosynthesis pathways in its seeds, implying a higher diversity of genes involved in the seed maturation phase when compared with Arabidopsis. It must also be mentioned that the flax seed maturation phase extends for a longer time period when compared with Arabidopsis, allowing the harvest of seed batches at precise stages of maturation. Thus, this model also appeared to be attractive because of the possibility it gives to study the maturation process accurately at several successive development kinetic points. The last interesting point about the flax model is that flax is a dicot belonging to the Malpighiales order which is relatively far removed from the Brassicales order that contains the two major oilseed models, Arabidopsis and rapeseed (Savolainen and Chase, 2003). This phylogenetic distance should allow, by comparison with results obtained with the other plant models, identification of biological mechanisms involved in seed maturation which are (or are not) ubiquitous. The main objective of this work was to set up an original database of seed maturation-specific genes, using a new plant model in order to gain insight into the diversity of biological mechanisms involved during this stage. With this in mind, a cDNA-AFLP analysis of flax seed maturation stage was performed using kinetic points covering the whole seed maturation stage, from embryo growth phase to mature seed. cDNA-AFLP (Bachem et al., 1996) is a valid alternative for quantitative genome-wide expression analysis, especially for species, like flax, for which genomic resources are lacking (Breyne et al., 2003; Volkmuth et al., 2003). Moreover, rather than just being an alternative, cDNA-AFLP analysis was shown to be an accurate tool for transcriptome study, allowing stronger specificity and sensitivity than microarrays analysis (Reijans et al., 2003). About 20 000 independent flax ESTs were analysed, among which 486 showed a specific expression during seed maturation. About 50% of these ESTs shared significant similarities with sequences identified from the publicly available databases. When translated, some of them were similar to proteins which had already been shown to be specifically expressed in plant seeds, indicating the accuracy of the cDNA-AFLP approach and allowing identification of the different phases of flax seed maturation. This work focuses on regulator genes in order to illustrate one area of interest in the information to be found in the database described here. Among the sequences characterized, 30 of them show some similarity with plant regulators involved in the control of gene expression, either at the transcriptional, post-transcriptional, or post-translational levels. Using a real-time RT-PCR approach, seed-specific expression kinetics were confirmed for all 13 of these regulators that had never been characterized for expression during seed maturation. Among these, a flax gene of the non-LEC1-like HAP3 family and a flax MYB factor were shown to be expressed in flax embryo-specialized tissues using an in situ hybridization approach. Expression kinetic comparison between these flax genes and their Arabidopsis counterparts was performed and interest in this transversal analysis in the distinction between ubiquitous and non-ubiquitous seed maturation mechanisms is discussed. Materials and methods Plant material Linum usitatissimum plants (Barbara ecotype) were grown under a 16 h light period and day/night temperatures of 18/15 °C. Arabidopsis thaliana plants (Columbia ecotype) were grown under the same light period conditions and day/night temperatures of 22/20 °C. To harvest seeds (flax) or siliques (Arabidopsis) of defined age, individual flowers were tagged with coloured threads on the day of flower opening. Flax seeds, 10, 20, 30, 40, and 50 d after flowering (DAF), were dissected from the capsule, immediately frozen in liquid nitrogen, and stored at −80 °C. In the same way, Arabidopsis siliques were harvested and grouped into eight samples according to the number of days after flowering: 1–2, 3–4, 5–6, 7–8, 9–11, 12–14, 15–17, and 18–20. Flax seed used for in-situ hybridization experiments were dissected from capsules and immersed in fixation solution. Histology Lipids were stained using Nile red dye on fresh tissues and visualized on an LSM 510 Meta confocal microscope (Zeiss, Oberkochen, Germany), using an argon 488 nm laser. Proteins and polysaccharides were visualized on sections of flax embryos. Flax embryos were fixed overnight in freshly prepared 4% paraformaldehyde in phosphate buffer, then dehydrated in a graded ethanol series, and embedded in paraffin. Sections (8 μm thick) were double stained in periodic acid–Schiff (PAS) and naphthol blue-black (NBB). Polysaccharides were stained red with PAS (Martoja and Martoja, 1967) and soluble and insoluble proteins were specifically stained blue with NBB (Fisher, 1968). cDNA-amplified fragment length polymorphism Two sets of total RNA were prepared from two independent batches of flax seeds, of 6-month-old mature seeds, and of vegetative tissues including stem, leaves, and apical meristems. Tissues were ground in liquid nitrogen and, after a preliminary polyphenol and polysaccharide precipitation (Gehrig et al., 2000), RNA was extracted from the supernatant using a hot phenol purification protocol (modified after Verwoerd et al., 1989). For each condition, experiments were independently performed on the two RNA sets. Poly (A)+ RNA was isolated using Dynabeads® mRNA Purification Kit (Dynal A. S., Oslo, Norway). Synthesis of cDNA was performed with Superscript II™ Reverse Transcriptase, RNase H, DNA Polymerase I, and Escherichia coli Ligase (Invitrogen, Carlsbad, CA, USA). cDNA-amplified fragment length polymorphism (cDNA-AFLP) analysis was performed according to Bachem et al. (1996). Double-stranded cDNA was digested with the restriction enzymes TaqI and AseI. The adaptor primers 5′-GACGATGAGTCCTGAC-3′ and 3′-TACTCAGGACTGGC-5′ (TaqI) and 5′-CTCGTAGACTGCGTACC-3′ and 3′-CTGACGCATGGAT-5′ (AseI) were ligated to the restriction fragments, and a PCR preamplification step was performed using the adaptor primers without selective nucleotides. The selective PCR amplification step was performed using the primers 5′-GATGAGTCCTGACCGANN-3′ (TaqI) and 5′-GACTGCGTACCTAATNN-3′ (AseI) (N represents A, T, G, or C) and AmpliTaq® DNA Polymerase (Applied Biosystems, Foster City, CA, USA). For each condition, reactions were systematically performed with both cDNAs from the two independent RNA sets, and all the 256 AFLP combinations were done. Polymorphism was analysed as described by Bachem et al. (1996). The bands of interest, appearing in duplicate, were cut from the gel with a surgical blade, eluted, and reamplified with the same primer set used for the initial amplification. The reamplified cDNAs were subcloned using the pGEM®-T Easy Vector system (Promega, Madison, WI, USA) and sequenced (MWG Biotech AG, Ebersberg, Germany). Database searches were performed at the NCBI World Wide Web server using the Basic Local Alignment Search Tool (BLAST) network service (Altschul et al., 1997). Each transcript-derived fragment sequence was compared against all sequences in the non-redundant database using the BLASTX program. Default parameters were used for all analyses. The same BLASTX analysis was performed on the FLAGdb++ database (Samson et al., 2004), allowing an increased accuracy of the determination of the homology scores. Real-time reverse transcriptase-PCR analysis Total RNA was treated with amplification-grade DNase I (Invitrogen). First-strand cDNA was synthesized using Superscript II™ Reverse Transcriptase (Invitrogen). These cDNAs were used for PCR experiments using gene-specific primers designed with the LC Probe Design© software (Roche, Basel, Switzerland) from identified flax EST sequences or from available Arabidopsis sequences. All primers were optimized for being used with an annealing temperature of 60 °C during PCR. Forward and reverse primers were used for producing a single amplicon from flax genes LuC1 (5′-ATAAAGGCCGCCAAGTCACTAGC-3′ and 5′-TGCAACAATCAACCCAGGATTC-3′), LuC2 (5′-GAGGAGTTGTTCCTCGGCTA-3′ and 5′-AAGCTCTTCATTCACCTCTTGC-3′), Lu05113 (5′-ACCCTAGTGAGTTCCTTT-3′ and 5′-GGGAGGTTCACCAAGC-3′), Lu05142 (5′-CGTACTGATTAAATAGTTCCGATGTTAGGG-3′ and 5′-ATCGGTGGGTTGCATTCACCTTC-3′), Lu05146 (5′-CGTACTGATTAAATAGTTCCGATGTTAGGG-3′ and 5′-ATCACGTTGCGGTTAGCATGC-3′), Lu06141 (5′-AATTGCTGACGAGGCTGCCAC-3′ and 5′-TTACAGCCTAAACCAGAACTTGAAAGG-3′), Lu08041 (5′-CAGACTCTCCTTGACTGG-3′ and 5′-GTATGACCGGAAAAGTGG-3′), Lu09021 (5′-AGATTGACGGTGCAGT-3′ and 5′-TCAAGCCTTAGGGCACA-3′), Lu09022 (5′-AATGAACACTGTTGAAGGAG-3′ and 5′-CGAACTGGATGATCATCAT-3′), Lu09105 (5′-AATGAACACTGTTGAAGGAG-3′ and 5′-CGAGCTGGATGATCATCAT-3′), Lu10015 (5′-ACGCACAGAAGTATTTCTTG-3′ and 5′-GGAATTGGGAATGGGATCA-3′), Lu11064 (5′-ACAGGAGGTGTGAAGC-3′ and 5′-CGCCAGCCTTAACATTTAT-3′), Lu11142 (5′-ATGGCGACGATTTGCTGT-3′ and 5′-GGCCATCTTTTCTAGCAGCA-3′), Lu11146 (5′-ATGGCGATGATTTGCTGT-3′ and 5′-CATCGTTCATCCCATAGT-3′), and Lu12076 (5′-TCCAAACTACCGACGC-3′ and 5′-GGACCTCAAGTGTCCG-3′). Forward and reverse primers were used for producing amplicon from Arabidopsis genes At5g02840 (5′-TGACCTCAACCAATCCGGT-3′ and 5′-TTCCAGAAACTTGTCGTGTTC-3′), At2g37060 (5′-CAGTTTCGTCACCAGC-3′ and 5′-GTCTGTTCCCGGCATT-3′), LEC1 (5′-TGGTTCTGCACTTAGAGG-3′ and 5′-GGAAGACGAAGAGCCAC-3′), and L1L (5′-GACCGAGTATGGAGCC-3′ and 5′-AGCTTGCACCTACTAACAG-3′). Real-time PCR was performed on a Roche LightCycler® using the FastStart DNA MasterPLUS SYBR Green I kit (Roche) in a final volume of 20 μl according to the manufacturer's protocol. All reactions were prepared in duplicate and performed twice. For each sample and calibrator (vegetative control), the relative amount of a target gene and a reference gene allowing the normalization of small differences in template amounts, LUC1 for flax and eF1αA4 (Nesi et al., 2000) for Arabidopsis, were determined. Crossing-point values, which are the PCR cycle numbers at which the accumulated fluorescent signal in each reaction crosses a threshold above background, were obtained with the LightCycler® software 3.5 (Roche) using the second derivative maximum method. Crossing-point values are a function of the amplification efficiency of the respective PCR. These data were then exported into the RelQuant© software (Roche). This software provides efficiency-corrected, calibrator-normalized quantification results. Results are expressed as the target/reference ratio of the sample, divided by the target/reference ratio of the calibrator, and, therefore, are corrected for sample heterogeneities and detection-caused variances. The efficiency-corrected quantification performed by RelQuant© is based on relative standard curves describing the PCR efficiencies of each target and the reference gene. The relative standard curves are determined and are used for each analysis. For each gene of interest, the same melting point temperature and size were observed for PCR products obtained by real time RT-PCR using cDNAs or the corresponding plasmid-cloned sequence as the template, indicating a low probability of false priming. RNA in situ hybridization One antisense Lu11146, riboprobe 240 bases long, one antisense Lu10015 riboprobe, 176 bases long, and one antisense GUS riboprobe, 200 bases long, were labelled with biotin (Lig'nScribe, MAXIScript, and BrighStar Psoralen-Biotin kits; Ambion, Austin, TX, USA). A probe concentration of 2.5 μg ml−1 was used in an overnight hybridization of tissue sections 8 μm thick. Detection was performed with NBT-BCIP for 24 h (Vectastain ABC-AP kit; Vector Laboratories, Burlingame, CA, USA). Results and discussion Microscope observations of flax embryo development In order to visualize the evolution of its structure and to determine the time points at which to gather seeds used in the cDNA-AFLP study described here, observations on flax embryos harvested at different developmental stages were performed using a microscope. The torpedo stage appears in embryos 10 DAF (Fig. 1A) still surrounded by endosperm. The 20 DAF embryo (Fig. 1B) fills the seed sac and reaches its full size. Between 20 and 40 DAF, cotyledon thickness increases (Fig. 1C). At this stage, the green colour of the embryo softens and pigmentation appears in the peripheral layer of the inner integument (Fig. 1D) to give the characteristic brown colour of the desiccated seed at 50 DAF. Therefore, 10 DAF is the hinge step, when embryo morphogenesis is over and the embryo growth phase indicates the beginning of the seed maturation stage. Then, during flax embryogenesis, maturation seems to extend from 10 to 50 DAF. Fig. 1 View largeDownload slide Distribution of storage compounds in flax embryo. (A–C) Longitudinal sections of flax embryos at different developmental stages: 10 DAF (A), 20 DAF (B), and 40 DAF (C). (D) Enlargement of the area framed in (C). (E, F) Cotyledon storage cells of mature seed. (A–E) Light micrographs using bright-field. (F) Confocal micrograph. Localization of storage products using specific dyes: (A–E) for proteins (naphthol Blue Black: blue dye), for polysaccharides (Schiff: pink dye), and (F) for lipids (Nile Red: yellow fluorescence). cot, Cotyledon; cx, cortex; en, endosperm; in, inner integument; mi, micropyle; mu, mucilage; pc, procambium; pl, pigment layer; sam, shoot apical meristem; sl, storage lipid; sp, storage proteins; spo, storage polysaccharides; st, starch. Scale bars in D–F=20 μm. Fig. 1 View largeDownload slide Distribution of storage compounds in flax embryo. (A–C) Longitudinal sections of flax embryos at different developmental stages: 10 DAF (A), 20 DAF (B), and 40 DAF (C). (D) Enlargement of the area framed in (C). (E, F) Cotyledon storage cells of mature seed. (A–E) Light micrographs using bright-field. (F) Confocal micrograph. Localization of storage products using specific dyes: (A–E) for proteins (naphthol Blue Black: blue dye), for polysaccharides (Schiff: pink dye), and (F) for lipids (Nile Red: yellow fluorescence). cot, Cotyledon; cx, cortex; en, endosperm; in, inner integument; mi, micropyle; mu, mucilage; pc, procambium; pl, pigment layer; sam, shoot apical meristem; sl, storage lipid; sp, storage proteins; spo, storage polysaccharides; st, starch. Scale bars in D–F=20 μm. The diversity and cellular organization of flax seed storage products were revealed by using specific dyes on seed sections (Fig. 1). Mature seeds (Fig. 1E, F) accumulate all the three major classes of storage compounds: lipids, proteins, and polysaccharides. The complex evolution of polysaccharide stock (pink colour in Fig. 1A–C) during embryo maturation and how it is stored in the mature seed are of particular interest (Fig. 1E). At 10 DAF, polysaccharides are stored in two main forms: starch (few amyloplasts) in the endosperm; mucilage in the torpedo embryo. It must be noticed that the polysaccharide-specific pink dye is almost absent at 20 DAF, indicating that starch and mucilage storage forms are transitory (Fig. 1B). Moreover, this stage presents an important synthesis of storage proteins (blue colour). However, while showing an increased storage protein content, the 40 DAF embryo contains polysaccharides mainly as mucilage, starch being completely absent (Fig. 1C, D). Finally, in the mature embryo (Fig. 1E), stored polysaccharides are still present as mucilage but also in a hollow structure in the centre of the two or three storage protein bodies present in each embryo cell. The nature of these protein body polysaccharides is unknown. Such structures, as far as is known, have not been described before and potentially constitute an unidentified polysaccharide storage form. A cDNA-AFLP screen identified 486 flax ESTs specific to seed maturation cDNA-AFLP analysis was performed as described in the Materials and methods, using developing flax seeds 10, 20, 30, 40, and 50 DAF. Vegetative tissues (stem, leaves, apical meristems) and mature seeds were also included as controls. It must be mentioned that the 10 DAF samples contain a large amount of maternal tissues, including the endosperm. The cDNA expression profiles were determined by PCR-selective amplification using 256 different primer combinations, and ∼20 000 cDNA fragments were screened. For each condition, two cDNA-AFLP reactions were performed from two sets of independently prepared mRNAs samples. Comparison of fingerprints obtained from the five seed populations and the two controls allowed identification of transcript-derived fragments, called ESTs in the following text, from mRNAs that accumulated specifically during flax seed maturation (Fig. 2). Most ESTs showed similar levels of accumulation in each of the two independently repeated reactions. Fig. 2 View largeDownload slide cDNA-AFLP autoradiogram showing the accumulation patterns of ESTs from flax seed during seed development. Templates were derived from vegetative tissues (V), from seeds 10, 20, 30, 40, and 50 DAF and from mature seed (MS). For each condition, two independent cDNA-AFLP reactions were loaded side by side. Lanes are in groups of 14: each group was amplified using a different combination of primers with two selective nucleotides. Various expression patterns can be detected: constitutive expression (i), seed specific expression (ii), and vegetative expression (iii). Fig. 2 View largeDownload slide cDNA-AFLP autoradiogram showing the accumulation patterns of ESTs from flax seed during seed development. Templates were derived from vegetative tissues (V), from seeds 10, 20, 30, 40, and 50 DAF and from mature seed (MS). For each condition, two independent cDNA-AFLP reactions were loaded side by side. Lanes are in groups of 14: each group was amplified using a different combination of primers with two selective nucleotides. Various expression patterns can be detected: constitutive expression (i), seed specific expression (ii), and vegetative expression (iii). A total of 486 ESTs specific to seed maturation were extracted from the polyacrylamide gels, reamplified, and subcloned for sequencing. The sequence obtained for each tag was compared with the GenBank non-redundant public sequence database using the BLASTX program (Altschul et al., 1997). Among these, 256 (52.7%) showed close matches [BLASTX expectation values (E) of <10−3] to database entries with assigned identities (see supplementary data atwww.jxb.oupjournals.org). This result is in agreement with previous cDNA-AFLP studies in which around 50% of the ESTs identified had no or poor identity with sequences available so far (Durrant et al., 2000; Milioni et al., 2002; Kwon et al., 2004; Mao et al., 2004). These sequences are classified into 11 groups based on functional categories established for Arabidopsis (Arabidopsis Genome Initiative, 2000). Figure 3 gives the proportion of ESTs in each category. Fig. 3 View largeDownload slide Classification of 486 seed-specific flax ESTs. On the basis of BLASTX expectation (E) values of <10–3, 210 sequences were assigned to functional categories. Among these, 30 sequences (6.2%) share similarity with gene expression regulators. Fig. 3 View largeDownload slide Classification of 486 seed-specific flax ESTs. On the basis of BLASTX expectation (E) values of <10–3, 210 sequences were assigned to functional categories. Among these, 30 sequences (6.2%) share similarity with gene expression regulators. Marker genes cDNA-AFLP patterns identify the different phases of flax seed maturation Seed maturation goes through three successive phases: embryo growth phase, storage phase, and late maturation phase, including acquisition of desiccation tolerance and dormancy induction. Expression profiles of marker genes identified by cDNA-AFLP show the right staging of flax seed maturation. The homology scores for some of these sequences and their corresponding cDNA-AFLP patterns are given in Fig. 4. Fig. 4 View largeDownload slide cDNA-AFLP patterns of growth phase or maturation stage marker genes. Duration of each of the flax seed development stages was deduced from the pattern of expression of listed genes and is indicated at the bottom of the figure (see text for details). Fig. 4 View largeDownload slide cDNA-AFLP patterns of growth phase or maturation stage marker genes. Duration of each of the flax seed development stages was deduced from the pattern of expression of listed genes and is indicated at the bottom of the figure (see text for details). The flax EST Lu06073 similar (E=1e-14) to ABI3 (Giraudat et al., 1992) confirms that the five kinetic points used in the present cDNA-AFLP study are covering the entire flax seed maturation stage. Indeed, ABI3 is one of the major transcription factors controlling maturation in Arabidopsis seeds (Ooms et al., 1993; Parcy et al., 1994, 1997; Nambara et al., 1995), expressed from the end of the embryo growth phase and remaining at a high expression level during the entire maturation stage (Raz et al., 2001). In the microscope observations (Fig. 1), the flax seed maturation stage was identified as extending from 10 to 50 DAF. These observations are sustained by the cDNA-AFLP analysis since the Lu06073 expression pattern indicates that this gene is expressed at a low level in seed at 10 DAF, reaches its highest expression level from 20 to 50 DAF, and shows no expression in mature seeds. Flax ESTs sequences Lu16014, Lu07021, Lu12051, Lu11041, and Lu04051 are similar to APETALA2 (E=3e-47), NAM-like (E=2e-06), Cyc1B (E=7e-13), CYSTEINE PROTEINASE (E=5e-33), and HSP60 CHAPERONIN (E=2e-09), respectively, from Arabidopsis. As shown in Fig. 1A, the 10 DAF flax embryo is in the growth phase that marks out the beginning of maturation. This timing is confirmed by these five genes known for their involvement during this phase in embryo or in maternal tissues (Jofuku et al., 1994; Souer et al., 1996; Aida et al., 1997; Apuya et al., 2001; Maes et al., 2001; Raz et al., 2001; Takada et al., 2001; Wan et al., 2002; Vroemen et al., 2003; Dong et al., 2004; Weir et al., 2004) and for which expression is specifically found in 10 DAF flax seeds (Fig. 4). Many ESTs in the database share similarities with legumin 11S (23 ESTs), vicillin 7S (four ESTs), and albumin 2S (eight ESTs) confirming the presence of these three kinds of storage proteins in flax seed as previously shown (Marcone et al., 1994, 1998). Two additional ESTs similar to oleosins are found, as well as the Lu12074 EST similar to the FAD2 gene (E=1e-25). Oleosins and FAD2 are required for lipid synthesis and storage in seeds (Heppard et al., 1996). For each kind of storage protein and for oleosins, a representative cDNA-AFLP pattern is shown (Fig. 4). Expression kinetics of these genes shows that the storage phase of flax seed maturation lasts from 20 to 30 DAF. Flax ESTs sequences Lu13141 and Lu10071 are similar to LATE EMBRYOGENESIS ABUNDANT (LEA) (E=1e-31) and HSP70 (E=1e-28), respectively, from Arabidopsis (Fig. 4). These genes, expressed during the desiccation phase of seed maturation (DeRocher and Vierling, 1995; Sung et al., 2001; Wise and Tunnacliffe, 2004), allow identification of 30–50 DAF as the late maturation phase of flax seed. The three different phases of the flax seed maturation stage are presented in the lower part of Fig. 4. Identification of new gene expression regulators expressed during flax seed maturation and validation of their expression patterns by real-time RT-PCR Many of the 256 seed maturation-specific ESTs identified in the database (see supplementary data atwww.jxb.oupjournals.org) were never characterized as either playing a role in plant seed development or having a seed-specific expression. This amount of new expression data implies the existence of many mechanisms involved in seed maturation that still remain unknown. In order to validate information contained in the database described here and to highlight its interest, the focus was on ESTs similar to gene expression regulators. Among the 30 ESTs identified in this functional class, 13 share similarities with Arabidopsis regulators, known for their involvement in gene expression regulation at the transcriptional, post-transcriptional, or post-translational levels, and that had never been shown to be expressed in a plant seed. Different expression patterns are found among these 13 regulators, from the embryo growth phase to the late maturation phase. Seed-specific expression is validated for each of them using a real-time RT-PCR approach performed with a third set of independently prepared mRNA samples (Fig. 5A–C), showing a good correlation with the cDNA-AFLP pattern. To normalize each gene expression level between the different samples, amplification of a sequence from a reference constitutive gene was performed. The flax LuC1 and LuC2 EST sequences which showed a constitutive cDNA-AFLP pattern were used (Fig. 5D). LuC1 is similar to an Arabidopsis NADH:UBIQUINONE OXIDOREDUCTASE (E=1e-24) and LuC2 is similar to an Arabidopsis DSBA OXIDOREDUCTASE family cDNA (E=6e-23). A constant level of LuC1 expression was validated in real-time RT-PCR when normalized against the LuC2 expression level (Fig. 5D). It was concluded that LuC1 could be used as a reference constitutive gene in this study. Fig. 5 View largeDownload slide Comparison of expression patterns of regulator genes obtained by cDNA-AFLP and real-time RT-PCR. (A–C) For each gene, a graph showing its expression kinetically assessed by real-time RT-PCR is placed above its cDNA-AFLP pattern. The level of each gene expression was normalized with LuC1 and expressed with a value relative to the gene expression level in the vegetative control. The cDNA-AFLP patterns were confirmed for all these 13 genes. (A) Transcriptional regulators; (B) post-transcriptional regulators; (C) post-translational regulators; (D) constitutive cDNA-AFLP and real-time RT-PCR patterns of LuC1 and LuC2. Real-time RT-PCR data shown represent mean values obtained from four independent amplification reactions and the error bars indicate ±standard deviation. Fig. 5 View largeDownload slide Comparison of expression patterns of regulator genes obtained by cDNA-AFLP and real-time RT-PCR. (A–C) For each gene, a graph showing its expression kinetically assessed by real-time RT-PCR is placed above its cDNA-AFLP pattern. The level of each gene expression was normalized with LuC1 and expressed with a value relative to the gene expression level in the vegetative control. The cDNA-AFLP patterns were confirmed for all these 13 genes. (A) Transcriptional regulators; (B) post-transcriptional regulators; (C) post-translational regulators; (D) constitutive cDNA-AFLP and real-time RT-PCR patterns of LuC1 and LuC2. Real-time RT-PCR data shown represent mean values obtained from four independent amplification reactions and the error bars indicate ±standard deviation. Identification of new transcription factors expressed during flax seed maturation The flax EST sequence Lu12076 is similar to a MYB factor (E=3e-06) and shows strong expression only during the embryo growth phase (10 DAF) (Figs 4, 5A). When compared with the Arabidopsis MYB family, the Lu12076-translated sequence shares strong similarity with a subfamily of the R2R3 MYBs characterized by a C-terminal LNL(E/D)L motif. It must be mentioned that the similarity zone between the flax and the Arabidopsis sequences is located at the C-terminus and contains the LNLEL motif (data not shown). In Arabidopsis, this subfamily contains four members including AtMYB4 which was shown to be involved in plant UV protection by controlling the expression of sinapate ester sunscreens (Jin et al., 2000). The Lu12076 EST is detected very early in the flax seed maturation process and perhaps during the morphogenesis stage. Only one R2R3 MYB factor called TRANSPARENT TESTA 2 (AtMYB123) had been shown previously to be expressed during early embryo development, from zygote to early torpedo stage (Nesi et al., 2001). TT2 acts as a major factor for the determination of the BAN mRNA expression pattern, BAN being involved in tannin accumulation in seed (Debeaujon et al., 2003). However, TT2 seems to be part of a distinct MYB subfamily rather than the one containing AtMYB4. This result could indicate the existence of a new class of MYB factors involved in early plant seed maturation. Flax EST sequences Lu11142 and Lu1146 are similar to the same HAP3 subunit of the CCAAT-box binding transcription factor and show specific expression during the embryo growth phase and up to the end of the storage phase (10–30 DAF) (Fig. 5A). HAP3 is one of the three subunits of the CCAAT-box binding transcription factor (CBF) (for reviews, see Maity and de Crombrugghe, 1998; Mantovani, 1999). The HAP3 protein contains three regions, the A, B, and C domains, with the central B domain conserved throughout eukaryotes (Li et al., 1992; Xing et al., 1993; Sinha et al., 1996). Arabidopsis LEC1 shares significant sequence similarity with the HAP3 subunit of the CCAAT-box binding transcription factor (Lotan et al., 1998; Lee et al., 2003). LEC1 is one of the major genes required for normal development during both morphogenesis and maturation phases in plant embryos (reviewed by Harada, 2001). The 10 Arabidopsis HAP3 genes (AHAP3) can be divided into two classes: the LEC1-type and non-LEC1-type (Kwong et al., 2003). At present, only LEC1-type AHAP3 genes were shown to be involved in embryogenesis. The two flax ESTs, Lu11142 and Lu11146, are both similar to non-LEC1-type AHAP3 (E=9e-22 and E=6e-23, respectively), sharing much less similarity with LEC1-type AHAP3 (E∼1e-08, data not shown). This could indicate a role for the non-LEC1-type HAP3 factors in the plant embryo maturation process. The flax Lu10015 EST sequence is similar to another MYB factor (E=2e-09) and is strongly expressed during the storage phase, but more precisely close to the end of this phase (30 DAF) (Figs 4, 5A). The translated Lu10015 sequence is highly similar to a subfamily of MYB-like SHAQKYF DNA-binding domain protein consisting of five members in Arabidopsis (data not shown). This DNA-binding domain, restricted to plant proteins, is often associated with a response regulator domain (Rose et al., 1999). These factors are characterized, in part, by a well-conserved motif SH(AL)QKY(RF) at the C-terminal end of the DNA-binding domain. The translated Lu10015 EST contains this domain (data not shown). The flax Lu05113 EST sequence presents a clear similarity with the C-terminus of CONSTANS-LIKE1 (COL1) (E=2e-07) and is also strongly expressed during the storage phase, but more precisely close to the end of this phase (30 DAF) (Figs 4, 5A). COL1, which codes for an Arabidopsis zinc-finger transcription factor, was characterized as being a regulator of circadian rhythm, its expression being itself regulated by the circadian clock (Ledger et al., 2001). COL1 is part of the CONSTANS-like factor family which contains 16 members (Griffiths et al., 2003). The translated Lu05113 EST shows at its N-terminus a part of the CONSTANS factor-specific CCT domain while its C-terminus presents a high similarity with an extension only found in six of the Arabidopsis CONSTANS proteins [CO and COL(1–5); data not shown]. No gene of this family has ever been described as showing a seed-specific expression. Differences in Lu05113 expression levels are too low to claim this gene is seed specific, but the present result indicates that, at least in flax, a CONSTANS-like factor could also be involved in the maturation process. It can be proposed that seed-specific expression of CONSTANS-like genes in flax could be an adaptation to couple this process to the environment, especially to photoperiod. Indeed, flax seed development spans at least 8 weeks, showing why its comparison with a plant such as Arabidopsis, for which this process takes only 3 weeks, is of interest. Finally, the Lu09021 and Lu06141 flax ESTs are expressed during the late maturation phase (Figs 4, 5A). Lu09021 is similar to a single Arabidopsis ZINC-FINGER TRANSCRIPTION FACTOR (E=6e-15) and is expressed from 30 to 50 DAF but its transcript levels are drastically decreased in mature seed. Lu06141, similar to a HISTONE2B (H2B) (E=3e-15), remains strongly expressed from 30 DAF to mature seed. It was shown that H2B, once ubiquitinylated, plays an important role in the trans-histone methylation of histone H3, a modification with close ties to the regulation of gene expression (reviewed by Osley, 2004). Identification of new post-transcriptional regulators expressed during seed maturation The Lu11064 flax EST is similar to AGO1-like (E=6e-22) and is slightly more expressed during the growth phase and the first half of the storage phase (10–20 DAF) (Figs 4, 5B). The Arabidopsis ago1 mutant phenotype is mainly characterized by several developmental defects (Bohmert et al., 1998). AGO1 was described as an important factor involved in miRNA production as it participates to the formation of the RISC complex (Vaucheret et al., 2004). Concerning the role of AGO1 factors in plant development, data were mainly obtained on the leaf development model (Palatnik et al., 2003; Kidner and Martienssen, 2004). The present data suggest that production of miRNA through AGO1-like factors activity could also be involved in plant seed maturation. The Lu09022 and Lu09105 flax ESTs, both similar to an mRNA CLEAVAGE FACTOR subunit (E=1e-20 and E=1e-28, respectively), are strongly expressed at the end of the storage phase (30 DAF) and then remain expressed, but more weakly, till the end of the embryo development process (Figs 4, 5B). These proteins are part of the cleavage factor complex involved in the 3′ splicing and polyadenylation of mRNAs. A development-specific expression of such factors looks surprising at first. However, factors involved in the same process were shown to play a role in floral induction through the autonomous pathway by controlling the 3′ processing of specific transcripts (Simpson et al., 2003). Moreover, mRNA cleavage-associated factors were recently shown to be expressed in the Arabidopsis flower and to be essential for its embryo development (Xu et al., 2004). The embryo expression pattern characterized in this study for the Lu09105 and Lu09022 flax ESTs could indicate that a related mechanism is involved during the late phase of plant embryo development. Following the same trend, the Lu08041 flax EST is expressed during the late maturation phase, from 40 to 50 DAF, and its transcript levels are drastically decreased in mature seed (Figs 4, 5B). This EST is similar to a U5 SMALL NUCLEAR RIBONUCLEOPROTEIN HELICASE (U5sn RNP) (E=2e-63). U5 snRNP, in association with other small ribonucleoprotein particles and non-snRNP proteins, is one element of the spliceosome (for a review, see Will and Lührmann, 2001). Identification of new post-translational regulators expressed during seed maturation Flax EST Lu05142 and Lu05146, similar to FLAVIN-BINDING KELCH REPEAT, F-BOX (FKF1) (E=3e-29 and E=1e-25, respectively), are expressed from 40 DAF, but their mRNA levels increased until reaching a maximum in mature seed (Figs 4, 5C). F-box proteins are part of the SCF complex involved in the targeted ubiquitinylation process allowing degradation of specific proteins by the 26S proteasome (Vierstra, 2003). In the Arabidopsis genome, around 750 F-box coding genes were found, indicating the importance of post-translational regulations in plants. Involvement of an F-box-containing SCF complex in the auxin transduction pathway is now well demonstrated (Dharmasiri and Estelle, 2002) as well as their participation in the response to other phytohormones, in cell cycle control, as well as in photomorphogenesis and plant circadian clock functioning (Somers et al., 2004; Schwechheimer and Calderón Villalobos, 2004). Within the plant F-box family, a small subgroup comprising FKF1, ZTL, and LKP2 is characterized by several C-terminal Kelch repeats. The translated Lu05142 and Lu05146 paralogous ESTs present high similarities with this specific C-terminus Kelch repeat. FKF1, shown to modulate the Arabidopsis circadian clock, contains an F-box domain characteristic of proteins that direct ubiquitin-mediated degradation and a PAS domain similar to the flavin-binding region of some photoreceptors (Nelson et al., 2000). It must be noticed that Lu05142 and Lu05146 are detected at the late maturation phase but also in the mature desiccated seed. Moreover, it was shown recently that maintenance of an mRNA stock within the mature seed is more important for germination success than mRNA neosynthesis during this process (Rajjou et al., 2004). Thus, these two putative flax F-box proteins could be involved, if not in the seed development process, perhaps in seed germination. In this case, the hypothesis of a possible involvement of targeted protein degradation during the early seed germination process could be supposed. Considering the role played by FKF1, which shows the strongest similarities with Lu05142 and Lu05146, in modulating the Arabidopsis circadian clock by means of light (Nelson et al., 2000), such a hypothesis could be related to the control by light of the end of dormancy and early seedling initiation. Transcript localization of previously identified HAP3 and MYB factor by in situ hybridization on flax embryo With the aim of going further in discovering new mechanisms involved in seed maturation, focus was on the three identified flax putative transcription factors expressed during the storage phase (20–30 DAF): Lu10015, similar to a MYB factor, and Lu11142 and Lu11146, both similar to a HAP3 subunit of the CCAAT-box binding transcription factor. For this purpose, in situ hybridization experiments were done to locate their expression specificities at the tissue level. These experiments were performed using a labelled antisense RNA probe on 30 DAF flax embryo sections, on which hybridization was detected by a purple coloration of the cells (Fig. 6). Flax EST Lu11142 and Lu11146 tally with the same part of the HAP3 genes and, while their sequences show sufficient differences to show that they are derived from two different genes, they present strong nucleic acid similarities (∼92% similar nucleic acids, not shown). For this reason, only one Lu11146 probe was used, assuming it is likely to hybridize to both Lu11146 and 11142 mRNAs. In each experiment, a hybridization negative control was performed using a labelled GUS antisense RNA probe. Fig. 6 View largeDownload slide Localization of Lu10015 and Lu11146 transcripts by in situ hybridization on flax 30 DAF embryo sections. (S) Diagram of a flax embryo on which each embryo view is identified by a corresponding boxed area. The sections were probed with antisense-labelled Lu10015 RNA (A, B), Lu11146 RNA (C, D), and GUS RNA (A', C', D') used as a negative control. The Lu10015 transcripts were localized at the top end of cotyledons (A) and a strong signal appeared in some lines of cortex cells (arrows in B). The Lu11146 transcripts were localized in the procambium, only at the embryo axis level, in root cap (C) and in the three upper layers of the apical meristem (D). No significant signal was detected with the GUS probe (A', C', D'). Scale bars=150 μm in (A) and (A'), 50 μm in (B), (C'), (D), and (D'), and 500 μm in (C). cot, Cotyledon; cx, cortex; daf, procambium; rc, root cap; sam, shoot apical meristem. Fig. 6 View largeDownload slide Localization of Lu10015 and Lu11146 transcripts by in situ hybridization on flax 30 DAF embryo sections. (S) Diagram of a flax embryo on which each embryo view is identified by a corresponding boxed area. The sections were probed with antisense-labelled Lu10015 RNA (A, B), Lu11146 RNA (C, D), and GUS RNA (A', C', D') used as a negative control. The Lu10015 transcripts were localized at the top end of cotyledons (A) and a strong signal appeared in some lines of cortex cells (arrows in B). The Lu11146 transcripts were localized in the procambium, only at the embryo axis level, in root cap (C) and in the three upper layers of the apical meristem (D). No significant signal was detected with the GUS probe (A', C', D'). Scale bars=150 μm in (A) and (A'), 50 μm in (B), (C'), (D), and (D'), and 500 μm in (C). cot, Cotyledon; cx, cortex; daf, procambium; rc, root cap; sam, shoot apical meristem. Lu10015 transcripts are localized in cotyledons (Fig. 6A), with a strongest hybridization signal at their top end. A hybridization signal also appears in the cortex but is confined in some cell lines, some others presenting no signal (Fig. 6B). As far as is known, such MYB factor transcript localization is original and has never been described in a plant embryo during seed maturation. This result confirms that a MYB factor is involved in a still unknown gene expression regulation mechanism acting during seed maturation. Lu11146 transcripts are localized in the procambium of the embryo axis level, in the root cap (Fig. 6C), and in the three upper layers of the shoot apical meristem (Fig. 6D). This tissue-specific expression is radically different from the one of the LEC1-type AHAP3 (LEC1 and L1L), shown to be mainly expressed in the outer cell layers of the whole embryo (Lotan et al., 1998; Kwong et al., 2003). The accuracy of their proven tissue specificity confirms that these Lu11146 HAP3 transcripts are not of the LEC1-type. Thus, it appears that some non-LEC1-type HAP3s are involved in a previously unknown gene expression regulation mechanism during seed maturation. Gene expression of HAP3 and MYB factor Arabidopsis counterparts during silique development Results concerning MYB factor and HAP3 genes assess the existence of previously unknown mechanisms acting during seed maturation. Are these mechanisms conserved within plant species or are they restricted to some species like flax? The use of flax as a model is of interest to answer such questions. Indeed, by comparison of the present results with those obtained on another plant model phylogenetically far removed, like Arabidopsis (see Introduction), it might be possible to distinguish ubiquitous from non-ubiquitous seed maturation mechanisms. Kinetic expression during silique development was measured by real-time RT-PCR for Arabidopsis genes At2g37060, a non-LEC1-type AHAP3 showing the most sequence similarity with Lu11142 and Lu11146 (E=9e-22 and E=6e-23, respectively), for the nine other AHAP3 including LEC1 and L1L, and for At5g02840 and At3g09600, two MYB factors showing the most sequence similarity with Lu10015 (E=1e-21 each). As expected regarding previous studies (Lotan et al., 1998; Kwong et al., 2003), LEC1 and L1L show a strong expression during silique development (Fig. 7). Among all other non-LEC1-type AHAP3s, only At2g37060 is specifically expressed in siliques. Its expression kinetic is wave-shaped, showing a first over-expression peak around 5–6 DAF and a second highest peak around 15–17 DAF (Fig. 7). This result indicates that, contrary to LEC1 and L1L, At2g37060 is expressed in siliques not only during the morphogenesis stage but also during the late maturation stage of the seed. This expression specificity, in correlation with previous flax results, sustains the hypothesis that non-LEC1-HAP3-type genes could be involved in a seed maturation mechanism of gene expression regulation that should be ubiquitous and that is different from those related to LEC1 or L1L. Fig. 7 View largeDownload slide Expression patterns of LEC1, L1L, At2g37060, and At5g02840 during Arabidopsis silique development by real-time RT-PCR. As expected, LEC1 and L1L are strongly expressed in the silique. The AHAP3 At2g37060 gene showed a specific wave kinetic expression during silique development, while the At5g02840 MYB factor gene showed no expression specificity. The level of each gene expression was normalized using as constitutive reference the amount of eF1a transcripts. Data shown represent mean values obtained from four independent amplification reactions and the error bars indicate ±standard deviation. V, Vegetative control; FB, floral bud; 01–02 to 18–20 DAF, days after flowering of Arabidopsis siliques. Fig. 7 View largeDownload slide Expression patterns of LEC1, L1L, At2g37060, and At5g02840 during Arabidopsis silique development by real-time RT-PCR. As expected, LEC1 and L1L are strongly expressed in the silique. The AHAP3 At2g37060 gene showed a specific wave kinetic expression during silique development, while the At5g02840 MYB factor gene showed no expression specificity. The level of each gene expression was normalized using as constitutive reference the amount of eF1a transcripts. Data shown represent mean values obtained from four independent amplification reactions and the error bars indicate ±standard deviation. V, Vegetative control; FB, floral bud; 01–02 to 18–20 DAF, days after flowering of Arabidopsis siliques. On the contrary, MYB factor Lu10015 appears to be related to a non-ubiquitous gene expression regulation mechanism. Indeed, neither At5g02840 (Fig. 7) nor At3g09600 (not shown) show specific expression during silique development. Concluding remarks With the intention of improving the knowledge of seed maturation mechanisms, several studies were carried out, using a genome-wide expression analysis approach on seed (Girke et al., 2000; White et al., 2000; Lee et al., 2002; Ruuska et al., 2002; Suh et al., 2003; Dong et al., 2004; Sreenivasulu et al., 2004). These studies were performed on a small group of monocot and dicot plant models, using a macro- or microarray analysis approach, which considerably improved the amount of data obtained because they provide a wide vision of transcriptome variations during this essential step in a plant's lifespan. However, despite its ability to characterize, for example, functional metabolic pathways, such approaches are not always the ones most adopted to identify new genes on the basis of their expression specificities. This observation is especially relevant when considering gene expression regulators which are often expressed at low levels and belong to multigenic families in which specific expression of one gene is difficult to distinguish from the others. As an example, these approaches did not allow the identification of new seed-specific regulators. WRINKLED1, the only transcription factor characterized so far (in Arabidopsis) to be specifically involved in regulating the synthesis of some storage products in the embryo (Focks and Benning, 1998; Cernac and Benning, 2004) was identified through a classic mutant approach. WRINKLED1 is clearly a prominent factor regulating central lipid and carbohydrate metabolism during seed maturation (Ruuska et al., 2002), but is possibly not the only one. The aim of this present study was to identify new genes specifically expressed during the seed maturation phase. In order to make up for specific limitations of previous studies, use was made of (i) a new plant model that offers several advantages for studying seed maturation; (ii) kinetic points covering the whole seed maturation stage, from embryo growth phase to mature seed; and (iii) the cDNA-AFLP technique as a tool for gene expression analysis. This approach led to development of a database containing ESTs from 256 genes, among which most had not previously been characterized for such expression. With the purpose of validating information contained in the present database and to highlight its interest, this study focused on gene expression regulators. The first interest in this database was to identify new genes expressed during seed maturation and, then, to underline the existence of seed maturation mechanisms still unknown. While such regulators are usually characterized with difficulty by transcript profiling tools because of their multigenic family membership (e.g. in Arabidopsis ∼250 MYB factors genes and ∼750 F-box genes) or their low expression levels, 13 regulators were identified that had never been characterized before for their expression either in seed maturation or in early seedling development. Moreover, some of them are related to mechanisms never described during seed maturation: circadian clock regulation and post-transcriptional and post-translational regulations. These results show the originality of the information found on seed maturation. These new regulators might be involved in still unknown seed maturation mechanisms as was assessed for HAP3 and MYB factor genes, regarding the original localization of their transcripts. The second interest in this database was the development of a flax gene database, a plant relatively phylogenetically far removed from Arabidopsis. Indeed, for each gene of interest, a transversal analysis performed between flax and Arabidopsis allows genes involved in ubiquitous seed maturation mechanisms to be distinguished, as the new non-LEC1-type HAP3 identified in this work, and genes involved in more specific seed maturation mechanisms, as the flax Lu10015 putative MYB factor identified in this work. New genes involved in ubiquitous seed maturation mechanisms, conserved within these species, were identified thanks to the strong sensitivity and specificity of the cDNA-AFLP analysis. New genes involved in more specific seed maturation mechanisms, restricted to a limited number of species, were identified due to the unusual flax model used, allowing insight to be gained into the diversity of biological mechanisms involved during seed maturation. Therefore, this database could constitute a very informative tool for studying new seed maturation mechanisms. This work was supported by Alternatech and the Conseil Régional de Picardie, Amiens. Many thanks to Sonia Rippa, Carol Darcq, Morgan David, Fanny Henrion, and Romain Hecquet for EST cloning assistance, to Stéphanie Troufflard for supplying flax plants, to François Guerineau and Jérôme Pelloux for helpful discussions and for reviewing the manuscript, and to Philippe Grappin for providing the protocol of the cDNA-AFLP method. 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Torres, Carolina A.;Andrews, Preston K.;Davies, Neal M.

doi: 10.1093/jxb/erj136pmid: 16698820

Abstract Photo-oxidative stress was imposed under natural solar radiation on exposed and shaded sections of detached fruit of immature green tomato (Lycopersicon esculentum Miller=Solanum lycopersicum L.) mutants (anthocyanin absent, β-carotene, Delta, and high pigment-1) and their nearly isogenic parents (‘Ailsa Craig’ and ‘Rutgers’). After 5 h exposure to high solar irradiance, either with or without ultraviolet (UV) radiation, surface colour changes, pigment composition, photosynthetic efficiency, antioxidant metabolites and enzyme activities, and selected flavonoids and antioxidant proteins in exocarp tissue were evaluated. The imposed photo-oxidative stress reproduced the symptoms observed on attached fruit. Both high temperature and solar irradiance caused fruit surface discoloration with faster degradation of chlorophyll (Chl) than carotenoids (Car), leading to an increase in the Car/Chl ratio. Surface bleaching was mostly caused by visible light, whereas elevated temperatures were mostly responsible for the inactivation of photosynthesis, measured as decreased Fv/Fm. Ascorbate, glutathione, and total soluble protein concentrations decreased in the exocarp as the duration of exposure increased. Specific activities of superoxide dismutase, ascorbate peroxidase, dehydroascorbate reductase, monodehydroascorbate reductase (MDHAR), glutathione reductase (GR), and catalase increased with exposure, suggesting that these proteins were conserved during the imposed stress. GR protein expression remained stable during the imposed stress, whereas, MDHAR protein expression increased. Quercetin and kaempferol concentrations increased rapidly upon exposure, but not to UV radiation, suggesting rapid photo-protection in response to visible light; however, naringenin synthesis was not induced. The apparent increased tolerance of hp-1 fruit is discussed. Acclimation, antioxidant, fruit, oxidative stress, photo-oxidation, photosynthesis, sunscald, UV Introduction In fruit, photo-oxidative damage is typically due to photodynamic injury of heated tissue that occurs under conditions of intense sunlight and elevated temperatures (Barber and Sharpe, 1971). This form of photo-oxidative damage, commonly called ‘sunscald’, can be severe enough to cause economic losses in tomatoes (Moore and Rogers, 1943; Ramsey et al., 1952; Retig and Kedar, 1967; Rabinowitch et al., 1974) and apples (Brooks and Fisher, 1926; Moore and Rogers, 1943; Andrews and Johnson, 1996; Yuri et al., 1996), and other fruit crops. In tomato (Lycopersicon esculentum Miller=Solanum lycopersicum L.) fruit, photo-oxidative damage occurs mainly in the green epidermal and hypodermal tissues, although ‘mature-green’ and ‘breaker’ fruit are the most susceptible (Retig and Kedar, 1967). Photo-oxidative stress in fruit is linked with fruit maturation, because oxidative processes have been implicated in the ripening process (Blackman and Parija, 1928; Brennan and Frenkel, 1977; Jiménez et al., 2002; Andrews et al., 2004). Although both high irradiance and elevated temperatures are necessary to cause ‘sunscald’ symptoms, there has been little research addressing the importance of these environmental factors individually, as well as the role of ultraviolet (UV) radiation on photo-oxidative injury of fruit. Photo-oxidative damage is caused by reactive oxygen species (ROS), the flux of which are greatly increased under photo-oxidative stress (Foyer et al., 1994). ROS, produced normally and continuously by cells, are tightly controlled by complex and dynamic antioxidant systems. Plant antioxidant defences are comprised of both enzymes and non-enzymatic metabolites that are localized in specific tissues (e.g. epidermis/hypodermis) and cellular compartments (e.g. chloroplasts), which function in a complex series of overlapping oxidation–reduction pathways. Isoenzymes of superoxide dismutase (SOD; EC 1.15.1.1) catalyse the dismutation of the superoxide anion (O2·−), producing hydrogen peroxide (H2O2), which is reduced to water by either catalases (CAT; EC 1.11.1.6) (Willekens et al., 1997) or ascorbate peroxidases (APX; EC 1.11.1.11). APXs utilize reduced ascorbic acid (AsA) as an electron donor (Groden and Beck, 1979; Anderson et al., 1983). Monodehydroascorbate (MDHA), an oxidized form of AsA, is reduced to AsA via reduced ferredoxin (Miyake and Asada, 1994) or by the ascorbate–glutathione cycle (Foyer and Halliwell, 1976) via monodehydroascorbate reductase (MDHAR; EC 1.6.5.4). Dehydroascorbate (DHA), another oxidized form of AsA is converted back to AsA by dehydroascorbate reductases (DHAR; EC 1.8.5.1), which utilize glutathione (GSH) as reductant (Foyer et al., 1994). GSH is regenerated by glutathione reducatse (GR; EC 1.6.4.2) from its oxidized form, glutathione disulphide (GSSG). Among fruit crops, tomatoes serve as model species for understanding fruit physiology, biochemistry, and genetics. In the present study, tomato fruit was used to study physiological and biochemical components involved in photo-oxidative damage. To accomplish this, a system utilizing detached fruit and natural solar radiation to accelerate injury was implemented. Tomato mutants were also selected with attenuated/enhanced pigments and/or antioxidant metabolites to evaluate the importance of certain antioxidant components on fruit acclimation. Materials and methods Tomato mutants Seven tomato (L. esculentum Mill.) genotypes were used in this study. In the first, anthocyanin absent (aa) (LA 3617), with a mutation in chromosome 2, anthocyanin is completely absent in all plant parts (CM Rick Tomato Genetics Resources Center; University of California, Davis, CA, USA). The second mutant, β-carotene (B) (LA 3179), with a mutation at loci 6 and 106 (Stevens and Rick, 1986), has high β-carotene and low lycopene concentrations in bright orange mature fruit (Tomes et al., 1956, 1958; Harris and Spurr, 1969; Ronen et al., 2000). The B gene (B/B alleles) is allelic in a locus encoding a fruit and flower-specific lycopene β-cyclase that shifts the carotenoid pathway from lycopene to β-carotene synthesis (Ronen et al., 2000). The third mutant, Delta (Del) (LA 2996A), has inhibited lycopene and increased δ-carotene (Williams et al., 1967) in reddish-orange mature fruit. The fourth mutant, high pigment (hp-1), represented by two genotypes (LA 2838A, hpA, and LA 3004, hpR), has a recessive non-allelic mutation at locus 12 that was first identified in 1917. Chlorophyll, carotenoids (lycopene and β-carotene), and ascorbic acid (AsA) contents of fruit are intensified (Thompson, 1955, 1961; Baker and Tomes, 1964; Clayberg et al., 1970; Jarret et al., 1984; Stevens and Rick, 1986; Torres, 2001; Andrews et al., 2004), as well as anthocyanins (Wettstein-Knowles, 1968a, b; Kerckhoffs et al., 1997). The mutation is located on a negative regulator(s) of phytochrome signal translation, which causes amplified photo-responsiveness and pleitropic effects (Kerr, 1965; Jarret et al., 1984; Kerckhoffs et al., 1997; Peters et al., 1998). All mutants are nearly isogenic in the cultivar ‘Alisa Craig’ (AC), except LA 3004, which is nearly isogenic in ‘Rutgers’ (R). Seeds from the previously described tomato mutants and their parents were obtained from the CM Rick Tomato Genetics Resource Center (University of California, Davis, CA, USA). Field site The research site was located in Lewiston, Idaho (46°23′ N; 116°59′ W) at an elevation of 430 m above sea level. The site was level and had a uniform soil of Nez Perce silty, clay-loam texture (fine, montmorillonitic, mesic Xeric Argialbolls). This region is classified as desert steppe with summer (June–September) mean maximum temperatures of 30 °C on generally cloudless days, as most precipitation occurs only in the winter months. Seedlings of the tomato genotypes were germinated in cell packs in a greenhouse and grown until they had several true leaves, at which time they were transplanted in a replicated, randomized complete block design in the field, consisting of four blocks with six plants per plot. Plants were spaced 1.2 m apart in the rows, with rows 2.4 m apart. All plants were irrigated with buried drip tape, 1 h d−1 during the first 30 d after planting, and 2 h d−1 from 30 d after planting until the end of the growing season. The output of each emitter was 1.9 l h−1. Plants were fertilized 2 weeks after transplanting with calcium nitrate (30 g per plant). Experimental set-up Determination of susceptibility to photo-oxidative damage was evaluated by exposing detached, immature green fruit from all genotypes to treatments of natural sunlight, either with (+UV) or without UV exposure (−UV, by the use of 0.635 cm thick safety glass plate filter), for 0, 2.5, and 5 h exposure. In order to investigate the independent effects of solar radiation and high temperature on photo-oxidative injury, half of each fruit from the treatments previously described was covered with reflective tape allowing air movement on the fruit surface beneath. Each treatment was represented by a group of four similar-sized fruits, harvested from non-sunlit exposed locations within the plant canopies just before setting up the experiment, for a total of 168 fruit tested per date. Harvested fruits were placed on top of a white board with the calyx-end up. The set of treatments described previously were replicated on five separate dates in 2003: 17, 22, and 29 July and 13 and 26 August. On all dates, experiments were conducted between 11.30 h and 17.00 h Pacific Daylight Savings time. Each date was considered a block. Field measurements Chlorophyll fluorescence was measured using a portable chlorophyll fluorometer (OS-500, Opti-Science, Tyngsboro, MA). The fluorescence parameters calculated to evaluate intrinsic photosystem II (PSII) efficiency during photo-oxidative stress was (Fm–F0)/Fm or Fv/Fm, where F0 and Fm are the minimal and maximal fluorescence yield of a dark-adapted measurement. By convention, Fv is variable fluorescence, Fm–F0. Dark-adapted fruit measurements were taken after 30 min of darkening the tissue. For this purpose, an additional fruit was provided from each treatment and measured three times on each experimental date. Surface colour changes were measured using a colourimeter (Minolta CR-300, Ramsey, NJ, USA). Data were expressed in CIELAB units where L* indicates lightness/darkness, and a* blue-green/red-purple and b* yellow-blue hue components. The a* and b* coordinates were used to determine hue angle (tan−1 (b*/a*), 0°–360°) or colour, and chroma [C, (a*2+b*2)1/2] or colour saturation or intensity (McGuire, 1992). Measurements were taken in triplicate per fruit on the treated fruit surface on all experimental dates. Biochemical assays Sampling: The exocarp (up to 2 mm thick) was removed separately with a scalpel from the two sections, exposed and covered with reflective tape, from fruit submitted to the treatments. Only light-green tissue was sampled (no dark green or ‘green shoulder’ tissue) from immature green fruit to maintain sampling homogeneity. Samples were immediately frozen in liquid N2, transported on dry ice, and stored at −80 °C for later analysis. Before biochemical measurements, samples were finely ground in liquid N2 with a mortar and pestle, and weighed for each of the different assays. Pigments: Chlorophyll (Chl a and Chl b) and total carotenoids (Car) were extracted from 50–150 mg of frozen exocarp tissue in 1 ml of 100% acetone at −20 °C for 24 h. Extracts were then centrifuged at 5000 g for 10 min at 4 °C. Absorbances were read at 470, 645, and 662 nm on a UV-visible spectrophotometer (Hewlett-Packard Company, Model 8453, Wilmington, DE, USA). Concentrations of Chl a, Chl b, and total Car (including xanthophylls) were determined by the following equations (Lichtenthaler and Wellburn, 1983):  Chl a=(11.75×A662)−(2.35×A645)  Chl b=(18.61×A645)−(5.03×A662)  Car=[(1000×A470)−(2.27×Chl a)−(81.4×Chl b)]/227 Antioxidant metabolites: Approximately 0.2 g of exocarp tissue per sample was extracted by grinding in liquid N2, acid-washed sand, and 1.5 ml of 1 M HClO4. Following centrifugation (13 000 g for 10 min at 4 °C), supernatants were partitioned into two, 400 μl aliquots for ascorbic acid (AsA) and glutathione (GSH) determinations. To these extracts, 200 or 100 μl of 0.1 M HEPES/KOH buffer (pH 7.0) was added for AsA and GSH determinations, respectively. Aliquots of 6 M K2CO3 were incorporated gradually to adjust pH to 4.0–5.0 for AsA determination or 6.0–7.0 for GSH determination, and to precipitate perchlorate. Samples were centrifuged, as before, and the pellets were discarded. Reduced AsA and oxidized DHA were assayed spectrophotometrically via a kinetic reaction at 265 nm by adding 4 units ascorbate oxidase (from Cucurbita sp, Sigma-Aldrich, USA) to a reaction mixture containing 0.1 M Na2HPO4 buffer (pH 5.6) and sample extract (Andrews et al., 2004). For DHA determination, 100 μl extract was incubated for 5 min on ice with 50 mM dithiothreitol (DTT) in 0.1 M Na2HPO4 buffer (pH 7.5). Reduced glutathione (GSH) and its oxidized form (GSSG) were measured spectrophotometrically by the modified methods of Griffiths (1980) via a kinetic reaction at 412 nm by adding 1.0 unit glutathione reductase (from Bakers yeast, Sigma-Aldrich, USA) to a reaction mixture containing 0.1 M Na2HPO4 buffer (pH 7.5), 6 mM EDTA, 6 mM 5–5′-dithio-bis(2-nitrobenzoic acid) (DTNB), 10 mM NADPH, and 10 μl sample extract. Antioxidant enzymes: Enzymes were extracted by grinding ∼0.2 g frozen exocarp in liquid N2, acid-washed sand, 50 mM MES/KOH buffer (pH 6.0), 40 mM KCl, 2 mM CaCl2, and 1 mM L-AsA. After centrifugation (13 000 g for 10 min at 4 °C), supernatants were used immediately for enzyme activity assays, except SOD, for which an aliquot of supernatant was stored at −80 °C for later assay. Bradford's (1976) method was used to determine soluble protein content of samples. All enzyme activity assays were conducted at 20 °C in 0.5 ml reaction volume. SOD activity was assayed as described by McCord and Fridovich (1969) with some modifications in a reaction mixture of 50 mM HEPES buffer (pH 7.8), 0.5 mM EDTA, 0.5 mM nitroblue tetrazolium, 4 mM xanthine, 50 μl extract, and 0.04 units xanthine oxidase. After 10 min, absorbance was measured at 560 nm. SOD activity was determined by a standard curve using horseradish SOD (Sigma-Aldrich, St Louis, MO, USA). APX activity was assayed by a modified procedure of Nakano and Asada (1987) in a reaction mixture of 50 mM KH2PO4 buffer (pH 7.0), 250 μM L-AsA, and 10 μl extract, with 5 mM H2O2 added to initiate the reaction. Change in absorbance was monitored at 290 nm and activity was calculated from the reaction rate using an extinction coefficient of 2.8 mM−1. MDHAR activity was measured in a reaction mixture of 100 mM HEPES buffer (pH 7.6), 2.5 mM L-AsA, 250 μM NADH, and 10 μl extract, with 0.4 units of ascorbate oxidase added to start the reaction. DHAR activity was determined in a reaction mixture of 50 mM HEPES buffer (pH 7.0), 0.1 mM EDTA, 2.5 mM GSH, and 10 μl extract, with 0.2 mM DHA added to initiate the reaction. Change in absorbance was monitored for 3 min at 340 or 265 nm and activity was calculated from this reaction rate using extinction coefficients of 3.3 mM−1 or 7.0 mM−1 for MDHAR and DHAR, respectively (Miyake and Asada, 1992). GR was measured in a mixture of 50 mM HEPES buffer (pH 8.0), 0.5 mM EDTA, 250 μM NADPH, and 10 μl extract, with non-enzymatic NADPH oxidation measured in each reaction mixture before 500 μM GSSG was added to start the reaction (Foyer and Halliwell, 1976). Change in absorbance was monitored for 3 min at 340 nm and enzyme activity was calculated by subtracting the rate of the non-enzymatic reaction from the rate of the GR-specific activity using an extinction coefficient of 6.22 mM−1. CAT was measured spectrophotometrically using the method of Chance and Maehly (1955) in a reaction mixture containing 50 mM KH2PO4 buffer (pH 7.0), 15 mM H2O2, and 100 μl extract to initiate the reaction. Activity was expressed as the change in absorbance at 240 nm as 50 mM H2O2 was degraded. Catalase activity was calculated using an extinction coefficient of 39.4 mM−1 (Aebi, 1983). SDS-polyacrylamide gel electrophoresis (PAGE) and immunoblotting Sample proteins were separated by 12% (w/v) SDS-PAGE (Laemmli, 1970). Samples were equalized by protein content (20 μg per lane), homogenized in loading buffer consisting of 50 mM TRIS–HCl (pH 7.3), 2% (w/v) SDS, 10% (v/v) glycerol, 10% (v/v) 2-mercaptoethanol, and 0.01% (w/v) phenol red, boiled for 2 min, and then centrifuged at 7000 g for 5 min at 25 °C before loading. Separated proteins were then transferred to polyvinylidene difluoride (PVDF) membranes (Bio-Rad Laboratories, Hercules, CA, USA) using an electrophoretic transfer cell (Model Mini-Trans-Blot, Bio-Rad Laboratories, Hercules, CA, USA) at 100 V for 1 h, and probed with polyclonal antibodies, rabbit anti-Zea mays leaf MDHAR (Ushimaru et al., 1997) diluted 1:1000 and rabbit anti-spinach leaf GR (Tanaka et al., 1994) diluted 1:4000. Horseradish peroxidase-conjugated goat anti-rabbit IgG (Bio-Rad Laboratories, Hercules, CA, USA) was used as secondary antibody diluted 1:2000 with blocking buffer containing 20 mM TRIS–HCl (pH 7.2), 150 mM NaCl, and 0.5% (v/v) Tween-20. Western blots were visualized by chemiluminescence using the ECL Western blotting detection system (Amersham Pharmacia Biotech, Piscataway, NJ, USA). Flavonoids: Flavonoids were extracted from frozen tissue with methanol and hexane, reconstituted in the mobile phase, and enzymatically hydrolysed with Helix pomatia Type-HP-2 β-glucuronidase to measure total quercetin, kaempferol, and naringenin enantiomers (Torres et al., 2005; Yañez and Davies, 2005). Daidzein and 7-ethoxycoumarin were added as internal standards for naringenin, and quercetin and kaempferol, respectively. Extracts with standards were injected into a Shimadzu HPLC system (Kyoto, Japan), consisting of a LC-10AT VP pump, a SIL-10AF auto injector, a SPD-M10A VP spectrophotometric diode array detector, and a SCL-10A system controller. Integration and collection of data was carried out using the Shimadzu EZ Start 7.1.1. SP1 software (Kyoto, Japan). Naringenin enantiomers were separated by a Chiralcel OD-RH column (150 mm×4.5 mm I.D., 5 μm particle size; Chiral Technologies Inc., Exton, PA, USA) using an isocratic mobile phase of acetonitrile:water:phosphoric acid (30:70:0.04 by vol.) at a flow rate of 0.4 ml min−1 at 25 °C, with detection at 292 nm. Quercetin and kaempferol were also separated isocratically by a Chiralcel AD-RH column (150 mm×4.5 mm ID, 5 μm particle size; Chiral Technologies Inc., Exton, PA, USA), using a mobile phase of acetonitrile:water:phosphoric acid (42:58:0.01 by vol.) at a flow rate of 0.6 ml min−1, with detection at 370 nm. Statistical analysis The experimental design was analysed as a split-split block with three factors as main effects: (i) genotype (A), (ii) duration of exposure (B), and (iii) presence or absence of UV radiation (C). The interactions of these three factors are indicated in the tables as (A)×(B), (A)×(C), (B)×(C), and (A)×(B)×(C). Covered and exposed sections of fruit were analysed separately. Analysis of variance and mean separation were only performed after data met the assumption of normality, which in some cases was achieved by transforming the data using the ladder of powers (x=yp). When statistical differences were found, Tukey HSD test (P <0.05) was used for mean separation. Orthogonal polynomials were used to evaluate trend contrasts with a Bonferroni adjustment. These analyses were performed using the statistical package SAS Institute Inc. (Cary, NC, USA). Flavonoid contents were quantified based on standard curves constructed using peak area ratio (PAR) against the concentration of the standards. PAR was obtained by dividing peak area of the compound and peak area of the internal standard. Least squares linear regression was used for this purpose. Results Environmental conditions The photosynthetic photon flux density (400–700 nm) and UV radiation (295–385 nm) were measured in ambient sunlight and under the glass filter on each sampling date with quantum sensors (Li-190SA, Li-Cor, Lincoln, NE, USA) and a total UV radiometer (TUVR, The Eppley Laboratory, Newport, RI, USA), respectively. The glass filter (−UV) reduced UV radiation by ∼95%, as well as PPFD by ∼20% (Torres, 2005). The surface temperatures of exposed fruit, measured with copper-constantan thermocouples connected to a datalogger (Model CR10X, Campbell Scientific, Logan, UT, USA), averaged 12 °C higher than air temperature (Torres, 2005). Surface temperatures of the exposed portion of fruit and the section shaded by reflective tape showed a similar diurnal pattern, but temperatures of the exposed surface of fruit not under the glass filter were ∼3–4 °C higher than the exposed fruit surface under the glass (Torres, 2005). Surface colour and pigments As duration of natural sunlight exposure increased, the fruit surface became less green and more yellow, measured as a decrease in hue angle (Table 1). This discoloration mainly occurred during the first 2.5 h of exposure. Fruit colour also became less saturated or intense (i.e. duller) as time passed, indicated by a decrease in C values (Table 1). When genotypes were compared, both hp-1 (hpA and hpR) mutants had the same hue or green colour as the parents and other mutants, but their colour was significantly intensified (higher C) and darker (smaller L*) than the parents (Table 1). This was observed after either 2.5 or 5.0 h of exposure (P=0.002). No significant differences were detected in any colour parameter between fruit fully exposed to sunlight (+UV) or under the glass filter (−UV). When the effect of temperature without direct sunlight was analysed by comparing covered and exposed sections of fruit, the exposed section had lower hue and C values, indicating greater discoloration and less colour intensity, respectively, after 2.5 h (data not shown) and 5 h of exposure (Table 2). There was also a slight lightening (larger L*), representing chlorophyll bleaching, in surface colour of the exposed section compared with the covered section of fruit at 2.5 h (data not shown) and 5 h of exposure (Table 2). Although non-significant, L* showed an inverse linear trend as duration of exposure increased (Table 1), suggesting chlorophyll bleaching. Table 1 Surface colour parameters for lightness (L*), chroma (C), and hue angle from exocarp of immature green fruit of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (UV) radiation (C) on sections of exposed fruit Factors  L*  C  Hue (°)  Genotypes (A)            ‘Ailsa Craig’  65.2 aba  32.4 ac  110.7      aa  67.3 a  29.6 ab  110.4      B  67.3 a  29.0 ab  109.8      Del  65.7 a  31.7 ac  110.0      hpA  58.6 c  37.1 d  111.7      ‘Rutgers’  66.3 a  26.9 b  110.9      hpR  61.9 bc  35.7 cd  110.7  P-value  <0.0001  <0.0001  0.481  Duration (h) (B)            0  65.2  33.8  114.3      2.5  64.8  31.4  109.4      5.0  63.9  30.1  108.0  P-value, linear  0.140  0.000  <0.0001  P-value, non-linear  0.954  0.466  0.003  (A)×(B) P-value  0.719  0.984  0.874  UV radiation (C)            +UV  64.5  31.4  110.4      −UV  64.7  32.1  110.8  P-value  0.508  0.109  0.105  (A)×(C) P-value  0.259  0.920  0.370  (B)×(C) P-value  0.512  0.175  0.237  (A)×(B)×(C) P-value  0.489  0.715  0.760  Factors  L*  C  Hue (°)  Genotypes (A)            ‘Ailsa Craig’  65.2 aba  32.4 ac  110.7      aa  67.3 a  29.6 ab  110.4      B  67.3 a  29.0 ab  109.8      Del  65.7 a  31.7 ac  110.0      hpA  58.6 c  37.1 d  111.7      ‘Rutgers’  66.3 a  26.9 b  110.9      hpR  61.9 bc  35.7 cd  110.7  P-value  <0.0001  <0.0001  0.481  Duration (h) (B)            0  65.2  33.8  114.3      2.5  64.8  31.4  109.4      5.0  63.9  30.1  108.0  P-value, linear  0.140  0.000  <0.0001  P-value, non-linear  0.954  0.466  0.003  (A)×(B) P-value  0.719  0.984  0.874  UV radiation (C)            +UV  64.5  31.4  110.4      −UV  64.7  32.1  110.8  P-value  0.508  0.109  0.105  (A)×(C) P-value  0.259  0.920  0.370  (B)×(C) P-value  0.512  0.175  0.237  (A)×(B)×(C) P-value  0.489  0.715  0.760  P-values indicated for comparisons within columns. Trend contrasts P-values represent a Bonferroni adjustment. a Different letters within columns indicate statistical differences. Protected LSD (P <0.05). View Large Table 2 Surface colour parameters (lightness, L*; chroma, C; and hue angle), pigment concentrations (chlorophyll; Chl a, Chl b, total Chl; carotenoids, Car), chlorophyll fluorescence (Fv/Fm), and flavonoids (kaempferol, K; quercetin, Q; Q/K ratio) from sunlight-exposed and covered sections of immature green fruit after 5 h of exposure Variable  Exposed  Covered  P-value  Colour parameters            L*  63.9  63.3  0.073      C  30.1  34.1  <0.0001      Hue (°)  108.1  111.2  <0.0001  Pigments            Chl a (μg g−1 FW)  24.4  35.7  <0.0001      Chl b (μg g−1 FW)  3.4  6.8  <0.0001      Total Chl (μg g−1 FW)  27.7  42.5  <0.0001      Car (μg g−1 FW)  8.9  11.8  0.006      Chl a/Chl b ratio  9.2  6.1  <0.0001      Car/Chl ratio  0.38  0.31  0.001  Chl fluorescence            Fv/Fm  0.19  0.31  0.001  Flavonoids            K (μg g−1 FW)  236.5  201.7  0.115      Q (μg g−1 FW)  3051.2  1268.2  0.032      Q/K ratio  12.3  5.9  0.024  Variable  Exposed  Covered  P-value  Colour parameters            L*  63.9  63.3  0.073      C  30.1  34.1  <0.0001      Hue (°)  108.1  111.2  <0.0001  Pigments            Chl a (μg g−1 FW)  24.4  35.7  <0.0001      Chl b (μg g−1 FW)  3.4  6.8  <0.0001      Total Chl (μg g−1 FW)  27.7  42.5  <0.0001      Car (μg g−1 FW)  8.9  11.8  0.006      Chl a/Chl b ratio  9.2  6.1  <0.0001      Car/Chl ratio  0.38  0.31  0.001  Chl fluorescence            Fv/Fm  0.19  0.31  0.001  Flavonoids            K (μg g−1 FW)  236.5  201.7  0.115      Q (μg g−1 FW)  3051.2  1268.2  0.032      Q/K ratio  12.3  5.9  0.024  P-value indicated for comparison within rows. View Large Changes in pigment concentrations in fruit exocarp confirmed colour measurements and observed visible symptoms. As duration of exposure increased, Chl concentrations decreased (Table 3). Chl b was degraded faster than Chl a, represented by an increase in Chl a/Chl b ratio with exposure (Table 3). Total Car decreased, but only after 5 h of exposure (Table 3). The Car/Chl ratio increased with exposure (Table 3) concomitant with the change in fruit colour from green to yellow (i.e. decreasing hue angle) (Table 1). Table 3 Chlorophyll (Chl) a, Chl b, total Chl, and total carotenoid (Car) concentrations from exocarp of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (UV) radiation (C) on sections of exposed immature green fruit Factors  Chl a (μg g−1 FW)  Chl b (μg g−1 FW)  Total Chl (μg g−1 FW)  Total Car (μg g−1 FW)  Chl a/Chl b ratio  Car/Chl ratio  Genotypes (A)                  ‘Ailsa Craig’  17.3 aa  2.60 a  19.9 a  6.30 a  10.0  0.34 ab      aa  16.6 a  2.55 a  19.2 a  6.08 a  11.5  0.34 abc      B  15.4 a  1.64 a  17.0 a  5.75 a  10.2  0.38 a      Del  17.6 a  2.50 a  20.1 a  6.71 a  8.9  0.36 a      hpA  100.7 c  19.16 c  119.9 c  30.08 c  5.4  0.26 c      ‘Rutgers’  10.8 a  1.77 a  12.6 a  3.82 a  10.3  0.32 ab      hpR  57.8 b  7.77 b  65.6 b  17.15 b  8.5  0.29 bc  P-value  <0.0001  <0.0001  <0.0001  <0.0001  0.1482  0.001  Duration (B)                  0 h  39.1  7.57  46.6  11.1  5.5  0.25      2.5 h  36.4  5.00  41.4  12.5  12.9  0.35      5 h  24.4  3.37  27.7  8.9  9.2  0.38  P-value, linear  <.0001  <.0001  <.0001  0.001  0.005  <.0001  P-value, non-linear  0.360  0.290  0.710  0.001  <.0001  0.005  (A)×(B) P-value  0.238  0.519  0.175  0.252  0.587  0.139  UV radiation (C)                  +UV  29.5  3.94  33.5  10.4  10.3  0.41      −UV  30.9  4.41  35.3  10.8  11.6  0.35  P-value  0.544  0.022  0.091  0.086  0.943  0.074  (A)×(C) P-value  0.455  0.408  0.426  0.167  0.525  0.069  (B)×(C) P-value  0.277  0.055  0.018  0.021  0.036  0.779  (A)×(B)×(C) P-value  0.332  0.201  0.061  0.170  0.422  0.058  Factors  Chl a (μg g−1 FW)  Chl b (μg g−1 FW)  Total Chl (μg g−1 FW)  Total Car (μg g−1 FW)  Chl a/Chl b ratio  Car/Chl ratio  Genotypes (A)                  ‘Ailsa Craig’  17.3 aa  2.60 a  19.9 a  6.30 a  10.0  0.34 ab      aa  16.6 a  2.55 a  19.2 a  6.08 a  11.5  0.34 abc      B  15.4 a  1.64 a  17.0 a  5.75 a  10.2  0.38 a      Del  17.6 a  2.50 a  20.1 a  6.71 a  8.9  0.36 a      hpA  100.7 c  19.16 c  119.9 c  30.08 c  5.4  0.26 c      ‘Rutgers’  10.8 a  1.77 a  12.6 a  3.82 a  10.3  0.32 ab      hpR  57.8 b  7.77 b  65.6 b  17.15 b  8.5  0.29 bc  P-value  <0.0001  <0.0001  <0.0001  <0.0001  0.1482  0.001  Duration (B)                  0 h  39.1  7.57  46.6  11.1  5.5  0.25      2.5 h  36.4  5.00  41.4  12.5  12.9  0.35      5 h  24.4  3.37  27.7  8.9  9.2  0.38  P-value, linear  <.0001  <.0001  <.0001  0.001  0.005  <.0001  P-value, non-linear  0.360  0.290  0.710  0.001  <.0001  0.005  (A)×(B) P-value  0.238  0.519  0.175  0.252  0.587  0.139  UV radiation (C)                  +UV  29.5  3.94  33.5  10.4  10.3  0.41      −UV  30.9  4.41  35.3  10.8  11.6  0.35  P-value  0.544  0.022  0.091  0.086  0.943  0.074  (A)×(C) P-value  0.455  0.408  0.426  0.167  0.525  0.069  (B)×(C) P-value  0.277  0.055  0.018  0.021  0.036  0.779  (A)×(B)×(C) P-value  0.332  0.201  0.061  0.170  0.422  0.058  P values indicated for comparisons within columns. Trend contrasts P-values represent a Bonferroni adjustment. a Different letters within columns indicate statistical differences. Protected LSD (P <0.05). View Large The glass filter, which attenuated UV radiation, did not significantly affect pigment composition of fruit exocarp with the exception of Chl b, which increased slightly under −UV radiation (Table 3). For total Chl and Car concentrations of exposed fruit, there was a significant interaction between duration of exposure and UV radiation (Table 3). There were significant reductions in both Chl and Car concentrations in UV-exposed (+UV) exocarp after 5 h of exposure (data not shown). Fruit exocarp from both hp-1 mutants (hpA, hpR) had 3–5-fold higher Chl and Car levels compared with the other genotypes (Table 3). HpA was the only genotype whose Car/Chl ratio was lower than its parent (Table 3). The covered section of exocarp had higher Chl (a and b) and Car concentrations, but lower Chl a/Chl b and Car/Chl ratios, than the exposed section after both 2.5 h (data not shown) and 5 h of exposure (Table 2). The reduction in Chl b concentration occurred faster than that of Chl a, which was reflected by the higher Chl a/Chl b ratio of exposed fruit sections. After 5 h of exposure to natural sunlight, 37% of Chl a was lost compared to 55% of Chl b (Table 3). Chl b concentrations in exocarp from the exposed section of fruit varied with genotype (Fig. 1). Fig. 1 View largeDownload slide Effect of genotype and exposure (covered or exposed) on chlorophyll (Chl) b concentration in exocarp from immature green fruit after 5 h of exposure to sunlight. An asterisk indicates statistically different covered versus exposed within genotypes (Tukey HSD, P <0.05). Fig. 1 View largeDownload slide Effect of genotype and exposure (covered or exposed) on chlorophyll (Chl) b concentration in exocarp from immature green fruit after 5 h of exposure to sunlight. An asterisk indicates statistically different covered versus exposed within genotypes (Tukey HSD, P <0.05). Photosynthetic efficiency The ratio of Fv/Fm of dark-adapted fruit did not vary among genotypes, but did with duration of exposure (Table 4). Fv/Fm, or intrinsic PSII efficiency, decreased substantially from 0.71 to 0.18 during the first 2.5 h of exposure to sunlight, but did not change between 2.5 h and 5 h. The absence of UV radiation had no clear effect on the apparent functionality of the fruit's photochemical apparatus. After 2.5 h of exposure, fruit under the glass filter (−UV) had a lower Fv/Fm ratio than fruit exposed to +UV, but this was reversed after 5 h of exposure (data not shown). The covered section of fruit had significantly higher Fv/Fm than the sun-exposed section both at 2.5 h (data not shown) and 5 h of exposure (Table 2). A significant interaction of genotype and exposure (covered or exposed) indicated that only for B and Del did the sun-exposed section of the fruit not have reduced Fv/Fm compared to the covered section of the same fruit (Fig. 2). Fig. 2 View largeDownload slide Effect of genotype and exposure (covered or exposed) on Fv/Fm ratio in exocarp from immature green fruit after 2.5 h of exposure to sunlight. An asterisk indicates statistically different between covered and exposed within genotypes (Tukey HSD, P <0.05). Fig. 2 View largeDownload slide Effect of genotype and exposure (covered or exposed) on Fv/Fm ratio in exocarp from immature green fruit after 2.5 h of exposure to sunlight. An asterisk indicates statistically different between covered and exposed within genotypes (Tukey HSD, P <0.05). Table 4 Fv/Fm ratio of immature green fruit surface of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (UV) radiation (C) on sections of exposed fruit Factors  Fv/Fm  Genotypes (A)        ‘Ailsa Craig’  0.34      aa  0.40      B  0.36      Del  0.38      hpA  0.34      ‘Rutgers’  0.37      hpR  0.38  P-value  0.282  Duration (B)        0 h  0.71      2.5 h  0.18      5 h  0.19  P-value, linear  <0.0001  P-value, non-linear  <0.0001  (A)×(B) P-value  0.389  UV radiation (C)        +UV  0.37      −UV  0.37  P-value  0.896  (A)×(C) P-value  0.206  (B)×(C) P-value  0.012  (A)×(B)×(C) P-value  0.210  Factors  Fv/Fm  Genotypes (A)        ‘Ailsa Craig’  0.34      aa  0.40      B  0.36      Del  0.38      hpA  0.34      ‘Rutgers’  0.37      hpR  0.38  P-value  0.282  Duration (B)        0 h  0.71      2.5 h  0.18      5 h  0.19  P-value, linear  <0.0001  P-value, non-linear  <0.0001  (A)×(B) P-value  0.389  UV radiation (C)        +UV  0.37      −UV  0.37  P-value  0.896  (A)×(C) P-value  0.206  (B)×(C) P-value  0.012  (A)×(B)×(C) P-value  0.210  P-values indicated for comparisons within columns. Trend contrasts P-values represent a Bonferroni adjustment. View Large Antioxidant metabolites Reduced AsA, as well as the redox ratio [AsA/(AsA+DHA)], decreased significantly in the exocarp of immature green fruit as duration of exposure increased (Table 5). The rate at which AsA decreased was greater than the rate at which DHA decreased, which is evident by the increase in the DHA/AsA ratio as the duration of exposure increased (Table 5). In fact, after 2.5 h there was a proportional increase in DHA concentration (6%) with a reduction in AsA (6%), suggesting an inability of the ascorbate pool to respond quickly to the imposed photo-oxidative stress (Table 5). By contrast, after 5 h of exposure to solar irradiance not only had AsA declined by 30%, but DHA had decreased by 20% as well, suggesting a partial degradation of the entire ascorbate pool (Table 5). AsA and total ascorbate (AsA+DHA) concentrations and the ratios of AsA/(AsA+DHA) and DHA/AsA decreased linearly with increasing duration of exposure, while the decline in DHA and total ascorbate concentrations were non-linear (Table 5). Table 5 Reduced ascorbic acid (AsA), dehydroascorbic acid (DHA), and total AsA+DHA concentrations, and the redox [AsA/(AsA+DHA)] and DHA/AsA ratios in exocarp of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (+UV or −UV) radiation (C) on exposed sections of immature green fruit Factors  AsA (μmol g−1 FW)  DHA (μmol g−1 FW)  AsA+DHA (μmol g−1 FW)  Redox ratio (AsA/AsA+DHA)  DHA/AsA ratio  Genotypes (A)                ‘Ailsa Craig’  1.59 ba  2.55 ab  4.14 b  0.36  1.99      aa  1.80 b  3.06 a  4.86 bc  0.36  1.92      B  1.86 bc  2.90 a  4.76 bc  0.37  1.79      Del  1.64 b  2.85 a  4.49 bc  0.33  2.09      hpA  3.04 d  4.91 c  7.96 d  0.37  1.78      ‘Rutgers’  1.18 a  1.55 b  2.73 a  0.38  1.54      hpR  2.42 c  3.22 a  5.64 c  0.42  1.71  P-value  <0.0001  <0.0001  <0.0001  0.612  0.643  Duration (B)                0 h  2.20  3.09  5.29  0.41  1.58      2.5 h  2.07  3.29  5.36  0.36  1.82      5 h  1.53  2.64  4.17  0.33  2.14  P-value, linear  <0.0001  0.066  0.001  0.004  <.0001  P-value, non-linear  0.140  0.029  0.030  0.451  0.568  (A)×(B) P-value  0.545  0.082  0.764  0.643  0.380  UV radiation (C)                +UV  1.95  2.96  4.91  0.37  1.81      −UV  1.92  3.05  4.98  0.37  1.86  P-value  0.811  0.687  0.755  0.849  0.355  (A)×(C) P-value  0.903  0.956  0.755  0.934  0.789  (B)×(C) P-value  0.583  0.228  0.481  0.119  0.055  (A)×(B)×(C) P-value  0.990  0.881  0.979  0.953  0.481  Factors  AsA (μmol g−1 FW)  DHA (μmol g−1 FW)  AsA+DHA (μmol g−1 FW)  Redox ratio (AsA/AsA+DHA)  DHA/AsA ratio  Genotypes (A)                ‘Ailsa Craig’  1.59 ba  2.55 ab  4.14 b  0.36  1.99      aa  1.80 b  3.06 a  4.86 bc  0.36  1.92      B  1.86 bc  2.90 a  4.76 bc  0.37  1.79      Del  1.64 b  2.85 a  4.49 bc  0.33  2.09      hpA  3.04 d  4.91 c  7.96 d  0.37  1.78      ‘Rutgers’  1.18 a  1.55 b  2.73 a  0.38  1.54      hpR  2.42 c  3.22 a  5.64 c  0.42  1.71  P-value  <0.0001  <0.0001  <0.0001  0.612  0.643  Duration (B)                0 h  2.20  3.09  5.29  0.41  1.58      2.5 h  2.07  3.29  5.36  0.36  1.82      5 h  1.53  2.64  4.17  0.33  2.14  P-value, linear  <0.0001  0.066  0.001  0.004  <.0001  P-value, non-linear  0.140  0.029  0.030  0.451  0.568  (A)×(B) P-value  0.545  0.082  0.764  0.643  0.380  UV radiation (C)                +UV  1.95  2.96  4.91  0.37  1.81      −UV  1.92  3.05  4.98  0.37  1.86  P-value  0.811  0.687  0.755  0.849  0.355  (A)×(C) P-value  0.903  0.956  0.755  0.934  0.789  (B)×(C) P-value  0.583  0.228  0.481  0.119  0.055  (A)×(B)×(C) P-value  0.990  0.881  0.979  0.953  0.481  Trend contrasts P-values represent a Bonferroni adjustment. a Different letters within columns indicate statistical differences. Tukey (P <0.05). View Large The glass filter, which removed 95% of UV radiation, had no effect on ascorbate levels in the exocarp of immature green fruit (Table 5). Fruit of both hp-1 mutants (hpA and hpR), but especially hpA, contained significantly higher concentrations of both AsA and DHA than the other genotypes, but their redox and DHA/AsA ratios did not differ (Table 5). When exposed and covered sections of fruit were compared, exocarp from the sunlight-exposed section had less total ascorbate than exocarp from the covered section after 5 h of exposure (Table 6). Although differences in AsA and DHA concentrations between exposed and covered sections of the fruit were non-significant, both declined sufficiently to result in a significant decrease in total ascorbate from the imposed photo-oxidative stress. Table 6 Reduced ascorbic acid (AsA), dehydroascorbic acid (DHA), total AsA+DHA, reduced glutathione (GSH), glutathione disulphide (GSSG), and total GSH+GSSG concentrations, redox ratios [AsA/(AsA+DHA) and GSH/(GSH+GSSG)] and DHA/AsA and GSSG/GSH ratios in exocarp from exposed and covered sections of immature green fruit after 5 h of exposure Variable  Exposed  Covered  P-value  AsA (μmol g−1 FW)  1.52  1.89  0.057  DHA (μmol g−1 FW)  2.60  3.08  0.072  AsA+DHA (μmol g−1 FW)  4.12  4.98  0.026  Redox ratio(AsA/AsA+DHA)  0.34  0.37  0.298  DHA/AsA ratio  2.27  2.08  0.616  GSH (μmol g−1 FW)  0.138  0.154  0.091  GSSG (μmol g−1 FW)  0.004  0.006  0.214  GSH+GSSG (μmol g−1 FW)  0.142  0.160  0.135  Redox ratio (GSH/GSH+GSSG)  0.930  0.990  0.106  GSSG/GSH ratio  0.089  0.069  0.639  Variable  Exposed  Covered  P-value  AsA (μmol g−1 FW)  1.52  1.89  0.057  DHA (μmol g−1 FW)  2.60  3.08  0.072  AsA+DHA (μmol g−1 FW)  4.12  4.98  0.026  Redox ratio(AsA/AsA+DHA)  0.34  0.37  0.298  DHA/AsA ratio  2.27  2.08  0.616  GSH (μmol g−1 FW)  0.138  0.154  0.091  GSSG (μmol g−1 FW)  0.004  0.006  0.214  GSH+GSSG (μmol g−1 FW)  0.142  0.160  0.135  Redox ratio (GSH/GSH+GSSG)  0.930  0.990  0.106  GSSG/GSH ratio  0.089  0.069  0.639  P-value indicated for comparison within rows. View Large Both GSH and total glutathione (GSH+GSSG) concentrations decreased linearly in fruit exocarp as duration of exposure increased (Table 7). Neither the redox ratio [(GSH/(GSH+GSSG)] nor the GSSG/GSH ratio changed with duration of exposure (Table 7). Just as for ascorbate, UV radiation did not significantly affect glutathione levels in fruit exocarp (Table 7). There were also no significant differences in glutathione concentrations or ratios among genotypes (Table 7), or between sections of fruit that were covered or exposed to solar irradiance (Table 6). Table 7 Reduced (GSH), oxidized (GSSG), and total glutathione (GSH+GSSG) concentrations, and the redox [GSH/(GSH+GSSG)] and GSSG/GSH ratios in exocarp of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (+UV and −UV) radiation (C) on exposed sections of immature green fruit Factors  GSH (nmol g−1 FW)  GSSG (nmol g−1 FW)  GSH+GSSG (nmol g−1 FW)  Redox ratio (GSH/GSH+GSSG)  GSSG/GSH ratio  Genotypes (A)                ‘Ailsa Craig’  179  4.9  184  1.00  0.029      aa  181  4.4  185  0.99  0.026      B  194  2.2  196  0.99  0.019      Del  197  6.0  203  0.94  0.168      hpA  201  6.2  206  0.98  0.058      ‘Rutgers’  208  5.1  213  0.94  0.806      hpR  185  5.0  190  0.96  0.113  P-value  0.431  0.527  0.412  0.596  0.186  Duration (B)                0 h  234  5.1  239  0.98  0.025      2.5 h  207  5.0  212  0.98  0.025      5 h  138  4.2  142  0.94  0.088  P-value, linear  <0.0001  0.840  <0.0001  0.782  0.082  P-value, non-linear  0.140  0.920  0.142  0.654  0.420  (A)×(B) P-value  0.429  0.614  0.723  0.975  0.483  UV radiation (C)                +UV  184  5.0  188  0.97  0.269      −UV  200  5.1  205  0.97  0.070  P-value  0.245  0.354  0.234  0.925  0.139  (A)×(C) P-value  0.499  0.859  0.512  0.678  0.730  (B)×(C) P-value  0.601  0.707  0.585  0.837  0.429  (A)×(B)×(C) P-value  0.772  0.936  0.732  0.654  0.855  Factors  GSH (nmol g−1 FW)  GSSG (nmol g−1 FW)  GSH+GSSG (nmol g−1 FW)  Redox ratio (GSH/GSH+GSSG)  GSSG/GSH ratio  Genotypes (A)                ‘Ailsa Craig’  179  4.9  184  1.00  0.029      aa  181  4.4  185  0.99  0.026      B  194  2.2  196  0.99  0.019      Del  197  6.0  203  0.94  0.168      hpA  201  6.2  206  0.98  0.058      ‘Rutgers’  208  5.1  213  0.94  0.806      hpR  185  5.0  190  0.96  0.113  P-value  0.431  0.527  0.412  0.596  0.186  Duration (B)                0 h  234  5.1  239  0.98  0.025      2.5 h  207  5.0  212  0.98  0.025      5 h  138  4.2  142  0.94  0.088  P-value, linear  <0.0001  0.840  <0.0001  0.782  0.082  P-value, non-linear  0.140  0.920  0.142  0.654  0.420  (A)×(B) P-value  0.429  0.614  0.723  0.975  0.483  UV radiation (C)                +UV  184  5.0  188  0.97  0.269      −UV  200  5.1  205  0.97  0.070  P-value  0.245  0.354  0.234  0.925  0.139  (A)×(C) P-value  0.499  0.859  0.512  0.678  0.730  (B)×(C) P-value  0.601  0.707  0.585  0.837  0.429  (A)×(B)×(C) P-value  0.772  0.936  0.732  0.654  0.855  Trend contrasts P-values represent a Bonferroni adjustment. View Large Antioxidant enzymes When enzyme activities were expressed on a fresh weight (FW) basis, different trends were observed as duration of exposure increased (Table 8). SOD activity increased in the exocarp of immature green fruit, while APX, GR, and CAT decreased. DHAR activity also decreased (P=0.056) as duration of exposure increased (Table 8). Only GR and CAT activities were affected by exposure to UV radiation, with CAT activity more than doubling but GR activity decreasing (Table 8). Exocarp from hpA fruit had the highest APX and GR activities among genotypes (Table 8). APX, GR, and CAT activities expressed on a FW basis were higher in the exocarp of the covered section compared with the section exposed to solar irradiance (Table 9), however, when expressed on a protein basis all enzyme activities except GR and CAT were higher in the exposed section (Table 9). Table 8 Antioxidant enzyme (SOD, APX, DHAR, MDHAR, GR, CAT) activities expressed on a fresh weight (FW) basis from exocarp of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (+UV and −UV) radiation (C) on sections of exposed immature green fruit Factors  SOD (units min−1 g−1 FW)  APX (μmol AsA min−1 g−1 FW)  DHAR (nmol AsA min−1 g−1 FW)  MDHAR (μmol NADH min−1 g−1 FW)  GR (μmol NADPH min−1 g−1 FW)  CAT (AU min−1 g−1 FW)  Genotypes (A)                  ‘Ailsa Craig’  178  12.7 aba  1493  5.8  1.60 b  0.94      aa  173  12.5 ab  1853  8.7  1.37 ab  0.77      B  183  12.1 ab  2070  9.7  1.41 ab  0.94      Del  170  11.5 ab  1424  7.9  1.37 ab  1.12      hpA  164  18.0 c  2071  6.1  2.10 c  0.58      ‘Rutgers’  169  11.0 ab  1806  5.1  1.04 a  1.03      hpR  184  11.8 b  2373  6.2  1.67 bc  1.29  P-value  0.683  0.005  0.089  0.096  0.020  0.370  Duration (B)                  0 h  168  13.7  2110  6.7  2.80  1.53      2.5 h  183  13.9  1804  6.5  1.13  0.65      5 h  172.0  10.9  1724  8.2  0.61  0.66  P-value, linear  1.120  0.003  0.056  0.209  <0.0001  <0.0001  P-value, non-linear  0.017  0.082  0.950  0.300  0.001  0.006  (A)×(B) P-value  0.308  0.518  0.683  0.078  0.583  0.695  UV radiation (C)                  +UV  176.3  12.1  1740  7.5  0.78  0.932      −UV  179.8  12.4  1683  7.4  1.00  0.409  P-value  0.635  0.471  0.436  0.117  0.047  0.026  (A)×(C) P-value  0.114  0.319  0.729  0.743  0.470  0.085  (B)×(C) P-value  0.876  0.478  0.656  0.293  0.588  0.888  (A)×(B)×(C) P-value  0.365  0.332  0.587  0.880  0.861  0.598  Factors  SOD (units min−1 g−1 FW)  APX (μmol AsA min−1 g−1 FW)  DHAR (nmol AsA min−1 g−1 FW)  MDHAR (μmol NADH min−1 g−1 FW)  GR (μmol NADPH min−1 g−1 FW)  CAT (AU min−1 g−1 FW)  Genotypes (A)                  ‘Ailsa Craig’  178  12.7 aba  1493  5.8  1.60 b  0.94      aa  173  12.5 ab  1853  8.7  1.37 ab  0.77      B  183  12.1 ab  2070  9.7  1.41 ab  0.94      Del  170  11.5 ab  1424  7.9  1.37 ab  1.12      hpA  164  18.0 c  2071  6.1  2.10 c  0.58      ‘Rutgers’  169  11.0 ab  1806  5.1  1.04 a  1.03      hpR  184  11.8 b  2373  6.2  1.67 bc  1.29  P-value  0.683  0.005  0.089  0.096  0.020  0.370  Duration (B)                  0 h  168  13.7  2110  6.7  2.80  1.53      2.5 h  183  13.9  1804  6.5  1.13  0.65      5 h  172.0  10.9  1724  8.2  0.61  0.66  P-value, linear  1.120  0.003  0.056  0.209  <0.0001  <0.0001  P-value, non-linear  0.017  0.082  0.950  0.300  0.001  0.006  (A)×(B) P-value  0.308  0.518  0.683  0.078  0.583  0.695  UV radiation (C)                  +UV  176.3  12.1  1740  7.5  0.78  0.932      −UV  179.8  12.4  1683  7.4  1.00  0.409  P-value  0.635  0.471  0.436  0.117  0.047  0.026  (A)×(C) P-value  0.114  0.319  0.729  0.743  0.470  0.085  (B)×(C) P-value  0.876  0.478  0.656  0.293  0.588  0.888  (A)×(B)×(C) P-value  0.365  0.332  0.587  0.880  0.861  0.598  Trend contrasts P-values represent a Bonferroni adjustment. a Different letters within columns indicate statistical differences. Tukey HSD (P <0.05). View Large Table 9 Antioxidant enzyme (SOD, APX, DHAR, MDHAR, GR, CAT) activities expressed on fresh weight (FW) and protein bases, and total protein in exocarp from exposed and covered sections of immature green fruit after 5 h of exposure Variable  Exposed  Covered  P-value  SOD (units min−1g−1 FW)  173  162  0.444  APX (μmol AsA min−1 g−1 FW)  10.8  12.9  0.000  DHAR (nmol AsA min−1 g−1 FW)  1707  1572  0.287  MDHAR (μmol NADH min−1 g−1 FW)  8.3  6.3  0.097  GR (μmol NADPH min−1 g−1 FW)  0.63  1.36  <0.0001  CAT (AU min−1 g−1 FW)  0.66  1.11  0.031  Protein (mg g−1 FW)  1.8  2.7  0.003  SOD (units min−1g−1 protein)  711  186  0.001  APX (μmol AsA min−1g−1 protein)  30.3  10.6  0.002  DHAR (nmol AsA min−1 g−1 protein)  1459  897  0.001  MDHAR (μmol NADH min−1 g−1 protein)  3199  553  0.002  GR (μmol NADPH min−1 g−1 protein)  97.3  65.7  0.236  CAT (AU min−1 g−1 protein)  2.37  0.20  0.445  Variable  Exposed  Covered  P-value  SOD (units min−1g−1 FW)  173  162  0.444  APX (μmol AsA min−1 g−1 FW)  10.8  12.9  0.000  DHAR (nmol AsA min−1 g−1 FW)  1707  1572  0.287  MDHAR (μmol NADH min−1 g−1 FW)  8.3  6.3  0.097  GR (μmol NADPH min−1 g−1 FW)  0.63  1.36  <0.0001  CAT (AU min−1 g−1 FW)  0.66  1.11  0.031  Protein (mg g−1 FW)  1.8  2.7  0.003  SOD (units min−1g−1 protein)  711  186  0.001  APX (μmol AsA min−1g−1 protein)  30.3  10.6  0.002  DHAR (nmol AsA min−1 g−1 protein)  1459  897  0.001  MDHAR (μmol NADH min−1 g−1 protein)  3199  553  0.002  GR (μmol NADPH min−1 g−1 protein)  97.3  65.7  0.236  CAT (AU min−1 g−1 protein)  2.37  0.20  0.445  P-value indicated for comparison within rows. View Large Exocarp of immature fruit of both hp-1 mutants had the highest protein concentrations compared with their parents and the other mutants, except the aa mutant (Table 10). Protein concentrations decreased linearly as duration of exposure increased (Table 10). After 5 h of exposure to solar irradiance there was only half of the initial protein concentration in the exocarp (Table 10). The protein concentration was also lower in the exocarp from sections of fruit exposed to sunlight compared with sections of fruit that were covered (Table 9). UV radiation apparently contributed to this decline in protein concentration, because fruit that were not exposed to UV radiation had 20% higher protein concentrations than fruit that were exposed (Table 10). Table 10 Total protein and antioxidant enzymes (SOD, APX, DHAR, MDHAR, GR, CAT) activities expressed on a protein basis in exocarp of different tomato genotypes (A), duration of exposure to natural sunlight (B), and presence or absence of ultraviolet (+UV and −UV) radiation (C) on sections of exposed immature green fruit Factors  Protein (mg g−1 FW)  SOD (units min−1 g−1 protein)  APX (μmol AsA min−1 g−1 protein)  DHAR (nmol AsA min−1 g−1 protein)  MDHAR (nmol NADH min−1 g−1 protein)  GR (nmol NADPH min−1 g−1 protein)  CAT (AU min−1 g−1 protein)  Genotypes (A)                    ‘Ailsa Craig’  3.01 aa  104  6.41 ab  872  462  50.8  0.13 a      aa  3.10 abc  90.3  5.08 ab  809  533  45.3  0.06 a      B  2.36 a  115  6.22 a  1099  466  58.4  0.12 a      Del  1.91 a  1646  10.30 a  1328  4188  191.3  4.72 c      hpA  3.73 c  359  5.13 ab  689  1759  65.9  0.03 a      ‘Rutgers’  2.45 a  348  9.33 a  1323  1087  66.9  0.87 b      hpR  3.24 bc  1045  4.11 b  888  271  50.9  0.20 a  P-value  <0.0001  0.139  0.014  0.303  0.120  0.406  0.049  Duration (B)                    0 h  3.74  56.9  4.02  623  202  84.1  0.11      2.5 h  2.89  87.2  6.06  941  333  44.4  0.08      5 h  1.91  1064  29.6  1438  3113  94.5  2.34  P-value, linear  <0.0001  <0.0001  <0.0001  0.001  <0.0001  0.002  0.284  P-value, non-linear  0.950  0.126  0.322  0.948  0.070  0.220  <0.0001  (A)×(B) P-value  0.138  0.304  0.389  0.247  0.453  0.355  0.253  UV radiation (C)                    +UV  2.18  676  19.4  1289  2616  92.4  1.30      −UV  2.62  473  8.4  1014  967  48.5  1.26  P-value  0.022  0.292  0.009  0.474  0.026  0.426  0.368  (A)×(C) P-value  0.415  0.525  0.271  0.527  0.839  0.115  0.183  (B)×(C) P-value  0.926  0.092  0.130  0.217  0.067  0.075  0.604  (A)×(B)×(C) P-value  0.055  0.426  0.372  0.242  0.263  0.617  0.414  Factors  Protein (mg g−1 FW)  SOD (units min−1 g−1 protein)  APX (μmol AsA min−1 g−1 protein)  DHAR (nmol AsA min−1 g−1 protein)  MDHAR (nmol NADH min−1 g−1 protein)  GR (nmol NADPH min−1 g−1 protein)  CAT (AU min−1 g−1 protein)  Genotypes (A)                    ‘Ailsa Craig’  3.01 aa  104  6.41 ab  872  462  50.8  0.13 a      aa  3.10 abc  90.3  5.08 ab  809  533  45.3  0.06 a      B  2.36 a  115  6.22 a  1099  466  58.4  0.12 a      Del  1.91 a  1646  10.30 a  1328  4188  191.3  4.72 c      hpA  3.73 c  359  5.13 ab  689  1759  65.9  0.03 a      ‘Rutgers’  2.45 a  348  9.33 a  1323  1087  66.9  0.87 b      hpR  3.24 bc  1045  4.11 b  888  271  50.9  0.20 a  P-value  <0.0001  0.139  0.014  0.303  0.120  0.406  0.049  Duration (B)                    0 h  3.74  56.9  4.02  623  202  84.1  0.11      2.5 h  2.89  87.2  6.06  941  333  44.4  0.08      5 h  1.91  1064  29.6  1438  3113  94.5  2.34  P-value, linear  <0.0001  <0.0001  <0.0001  0.001  <0.0001  0.002  0.284  P-value, non-linear  0.950  0.126  0.322  0.948  0.070  0.220  <0.0001  (A)×(B) P-value  0.138  0.304  0.389  0.247  0.453  0.355  0.253  UV radiation (C)                    +UV  2.18  676  19.4  1289  2616  92.4  1.30      −UV  2.62  473  8.4  1014  967  48.5  1.26  P-value  0.022  0.292  0.009  0.474  0.026  0.426  0.368  (A)×(C) P-value  0.415  0.525  0.271  0.527  0.839  0.115  0.183  (B)×(C) P-value  0.926  0.092  0.130  0.217  0.067  0.075  0.604  (A)×(B)×(C) P-value  0.055  0.426  0.372  0.242  0.263  0.617  0.414  Trend contrasts P-values represent a Bonferroni adjustment. a Different letters within columns indicate statistical differences. Tukey HSD (P <0.05). View Large Exocarp of hpR had the lowest APX activity per unit protein, but it was not significantly different from AC, hpA, and aa (Table 10). By contrast, Del had much higher CAT specific activity than the other genotypes (Table 10). Although non-significant, SOD, MDHAR, and GR activities of Del exocarp appeared to be higher, this partially may be due to its lower total protein concentration. All enzyme activities increased per unit protein with duration of exposure, but this was partly due to reduced protein concentration (Table 10). These increases in enzyme activities with duration of exposure followed linear trends, except for CAT activity. Only APX and MDHAR specific activities were significantly higher in exocarp from the section of fruit exposed to UV radiation compared with the unexposed section (Table 10). For all enzymes, except CAT, specific activities were significantly higher in exocarp from the sunlight-exposed section of fruit than from the covered section (Table 9). SDS-PAGE immunoblotting confirmed that the expression of MDHAR protein in the exocarp of immature green fruit increased from 0 h and 2.5 h to 5 h of sun exposure, while GR protein expression remained stable (Fig. 3). Fig. 3 View largeDownload slide SDS-PAGE and immunoblots of MDHAR and GR from immature green hp-A tomato exocarp (20 μg protein lane−1) from photo-oxidative stress treatments indicated by duration of exposure (0, 2, or 5 h), presence or absence of UV radiation (+UV or −UV), and covered (C) or exposed (E) fruit sections. MDHAR (47 kDa) cross-reacted with anti-Zea mays MDHAR and GR (58 kDa) cross-reacted with anti-spinach GR. Fig. 3 View largeDownload slide SDS-PAGE and immunoblots of MDHAR and GR from immature green hp-A tomato exocarp (20 μg protein lane−1) from photo-oxidative stress treatments indicated by duration of exposure (0, 2, or 5 h), presence or absence of UV radiation (+UV or −UV), and covered (C) or exposed (E) fruit sections. MDHAR (47 kDa) cross-reacted with anti-Zea mays MDHAR and GR (58 kDa) cross-reacted with anti-spinach GR. Flavonoids Specific flavonoids were only studied in the most apparently tolerant genotype to photo-oxidative stress, hpA, and its parent ‘Ailsa Craig’ (AC). Kaempferol and quercetin concentrations were significantly higher in hpA fruit exocarp than AC (Table 11). No differences were found in quercetin or kaempferol concentrations, or Q/K ratio, as duration of exposure increased (data not shown). The Q/K ratio is not numerically the same as the ratio of the mean concentrations of these flavonoids in the table, because the ratio is calculated from the measured quercetin and kaempferol concentrations of individual samples. Similarly, UV radiation did not result in significant differences in flavonoid concentrations or ratios, despite the apparent higher concentrations in −UV exocarp (data not shown). Table 11 Total kaempferol (K), quercetin (Q), R-naringenin, S-naringenin, and total naringenin concentrations and Q/K and R-naringenin/S-naringenin (R-/S-) ratios from exocarp of immature green fruit from ‘Ailsa Craig’ and hpA on sections of exposed fruit Factors  Kaempferol (μg g−1 FW)  Quercetin (μg g−1 FW)  Q/K  R-naringenin (μg g−1 FW)  S-naringenin (μg g−1 FW)  Total naringenin (μg g−1 FW)  R-/S- ratio  Genotypes                    ‘Ailsa Craig’  185.7  831.9  5.2  53.4  59.8  113.2  0.91      hpA  277.7  4280.2  14.9  75.0  140.1  215.1  0.56  P-value  0.042  0.033  0.059  0.056  0.010  0.010  0.001  Factors  Kaempferol (μg g−1 FW)  Quercetin (μg g−1 FW)  Q/K  R-naringenin (μg g−1 FW)  S-naringenin (μg g−1 FW)  Total naringenin (μg g−1 FW)  R-/S- ratio  Genotypes                    ‘Ailsa Craig’  185.7  831.9  5.2  53.4  59.8  113.2  0.91      hpA  277.7  4280.2  14.9  75.0  140.1  215.1  0.56  P-value  0.042  0.033  0.059  0.056  0.010  0.010  0.001  P-values indicated for comparisons within columns. Trend contrasts P-values represent a Bonferroni adjustment. View Large Only quercetin concentration and Q/K ratio were higher in the exocarp of the sunlight-exposed section compared with the covered section after 5 h of exposure (Table 2). The concentrations of both the R- and S-naringenin enantiomers were significantly higher in the exocarp of the hpA mutant than in AC (Table 11). HpA exocarp had a larger proportion of S-naringenin than AC, represented by a lower R-/S- ratio (Table 11). Except for the lower R-/S- ratio in exocarp exposed to UV radiation, naringenin concentrations did not vary with duration of exposure or UV radiation (data not shown). Discussion Surface bleaching and discoloration are common symptoms of photo-oxidative damage of tomato fruit (Ramsey et al., 1952; Tomes et al., 1956; Retig and Kedar, 1967; Rabinowitch et al., 1974). In this study, it was found that the method of inducing photo-oxidative damage on detached and susceptible immature-green tomato fruit under natural conditions was effective in accelerating the development of typical sunscald symptoms that are seen visually on attached fruit exposed to full sunlight. Both high temperatures and solar irradiance caused fruit surface discoloration (Table 2), but it was solar irradiance that was most responsible for the typical bleaching symptoms in the immature green exocarp of these tomato genotypes, which increased with duration of exposure to solar irradiance (Table 1). Fruit discoloration from green towards a yellow colour, caused by high temperature either with or without direct sunlight, was related to a decrease of Chl relative to Car concentrations (Table 2). This apparent greater photo-stability by carotenoids has been previously reported in apple fruit by Merzlyak and Solovchenko (2002). Furthermore, Merzlyak et al. (2002) reported that sunscald-tolerant apple cultivars (e.g. ‘Zhigulevskoye’) build up large amounts of carotenoids in their sunlight-exposed fruit peel as a response to higher irradiance. They hypothesized that Car serve as photo-protectants in these cultivars. These authors also indicated that this increase in carotenoids does not occur in sunscald-susceptible cultivars (e.g. ‘Granny Smith’), where both carotenoids and chlorophyll decline in sunlight-exposed fruit peel. Car and Chl also declined in the exocarp of immature green tomato fruit in our study. Interestingly, chlorophyll degradation and an increase in Car/Chl ratio are also part of ripening and senescence processes in many fleshy fruits, including tomatoes (Torres, 2001; Andrews et al., 2004). Andrews et al. (2004) reported that as tomatoes ripened the Chl a/Chl b ratio in exocarp declined linearly, which is opposite to this study's results with immature green fruit during the development of photo-oxidative damage (Table 3). Similarly, an increase in Chl a/Chl b ratio was reported when shaded leaves were transferred to full sunlight (Burritt and Mackenzie, 2003). This response might be interesting to explore further in other fruit, such as apples, as a non-destructive method to determine the occurrence of mild photo-oxidative damage or sunscald. Hp-1 (hpA and hpR) fruit exocarp had significantly higher Chl and Car contents than the other genotypes (Table 3), as has been previously reported for both exocarp and mesocarp tissues (Thompson, 1955, 1961; Baker and Tomes, 1964; Clayberg et al., 1970; Jarret et al., 1984; Stevens and Rick, 1986; Torres, 2001; Andrews et al., 2004). This characteristic of hp-1 fruit was directly related to differences in surface colour parameters. Hue angle, the parameter that represents colour, was similar in all genotypes, including the two hp-1 mutants (Table 1). However, the green coloration of the hp-1 mutants was more saturated (lower C) and of a darker (lower L*) green colour than the other genotypes (Table 1). Thus, the hp-1 mutants, especially hpA, appeared most visually tolerant to the imposed photo-oxidative stress, in agreement with previous findings (Torres, 2001). The lower values of L* and C probably resulted from the higher Chl and Car concentrations in hp-1 exocarp (Table 3). This apparent tolerance, however, was not detectable by the method of measuring surface colour that was employed, since there was no significant interaction between genotypes and duration of exposure for L*, C, or hue angle during the 5 h of photo-oxidative stress (Table 1). Fruit exocarp of the hp-1 mutants did not show any tolerance to photoinhibition, measured as Fv/Fm (Table 4). This suggests that their visually higher tolerance to photo-oxidative stress may not be due to protection of the reaction centres by their additional carotenoids, but to other antioxidant components, such as ascorbate and some ascorbate–glutathione cycle enzymes, which are enhanced in these mutants (Jarret et al., 1984; Torres, 2001; Andrews et al., 2004). High temperatures without direct sunlight, represented by the covered section of the fruit were responsible for 53% of the decrease in photosynthetic efficiency, measured as a reduction in the Fv/Fm ratio, in the first 2.5 h of exposure. The presence of sunlight accounted for the remaining 22% decrease of an overall 75% decrease in Fv/Fm. It has been reported that the leaves of certain desert plants have different temperature thresholds for chlorophyll fluorescence depending on their environmental adaptation. Above these temperature thresholds, chlorophyll fluorescence increases dramatically in these species. This temperature threshold ranged between 42–47 °C in high-temperature-adapted species (Seemann et al., 1984). Ludlow and Björkman (1984) also described a similar phenomenon in Macroptilium atropurpureum ‘Siratro’ leaves at temperatures over 42 °C under high irradiance, which they called ‘high-temperature-induced photoinhibition’. In our study, thermoinhibition was detected after 2.5 h of exposure when fruit surface temperatures averaged 46 °C. It is also possible that this high-temperature effect occurred prior to 2.5 h of exposure at lower surface temperatures, especially since Smillie et al. (1999) showed that PSII efficiency decreased more rapidly in fruit than in leaves with increasing PPFD. Thermoinhibition, as well as photoinhibition, could cause increases in cellular ROS flux and possible up-regulation of antioxidant systems to cope with the increased ROS. The results suggest that antioxidant metabolites and enzymes could have been exerting some degree of protection from photo-oxidative damage under these experimental conditions. This is supported by the increased activities of antioxidant enzymes as duration of exposure increased (Table 10). If the photo-oxidative stress conditions had persisted, however, the antioxidant systems may have been overcome at some point, leading to permanent photo-oxidative injury, especially in non-aclimated fruit tissue. In agreement with Adegoroye and Jollife (1987) and Prohens et al. (2004), AsA levels decreased in fruit exocarp as duration of exposure increased (Table 5). Similar to these results, a decline in ascorbate content as a response to imposed oxidative stress in leaves has been reported in other studies (Wise and Naylor, 1987; Sairam et al., 1998). On the other hand, plant acclimation and/or plant tolerance to oxidative/photo-oxidative stress have resulted in higher ascorbate contents in both leaves and fruits (Gatzek et al., 2002; Logan et al., 1998; Ma and Cheng, 2003). Although fruit ripening has been associated with oxidative stress, trends vary in AsA levels in different and even among similar species (Andrews et al., 2004; Jiménez et al., 2002; Lentheric et al., 1999; Torres, 2001). Unlike the effects of UV-B radiation on leaves (Hideg et al., 1997), no effect on the ascorbate pool by the presence or absence of natural UV radiation was seen (Table 5). The results also suggest that both intense visible sunlight and elevated temperatures were equally responsible for the decline in reduced AsA and DHA (Table 6). Similar to the findings of Foyer et al. (1989) for leaves, there were no differences in the redox state of ascorbate between covered and sunlight-exposed fruit (Table 6). As found in this study and also reported by Andrews et al. (2004), the ascorbate pool was elevated in the exocarp of the hp-1 mutant (Table 5). Since ascorbate decreased across genotypes as photo-oxidative stress progressed, the higher ascorbate concentration in the exocarp of hp-1 might confer this mutant with greater tolerance to photo-oxidative stress than the other genotypes. Although glutathione has been used as an oxidative stress indicator in plants (Grill et al., 2001), there is conflicting evidence about glutathione responses under oxidative stress conditions. While some studies have found an increase in glutathione synthesis in response to oxidative stress (Kumar and Knowles, 1996;, Sgherri and Navari, 1995), others have found no increase in GSH by environmental stresses (Tausz et al., 2004). No increase was found in either GSH or GSSG as photo-oxidative stress progressed (Table 7). This suggests that response mechanisms against oxidative stress are more complex, involving other cellular antioxidant systems besides glutathione. As suggested by Tausz et al. (2004), it is also possible that the fruits had only reached an initial state of acclimation to photo-oxidative stress. This may in fact be the case, since the fruits were harvested from shaded positions within the plant canopy. If the stress was more sustained, there would be a period of dynamic change in the glutathione pool, and possibly the ascorbate pool as well, giving cells the potential to increase their levels of antioxidant metabolites sufficiently to reach either a protective steady-state, or fail and die. This response would explain the findings of increased GSH levels in plants submitted to long-term environmental stresses (Polle and Rennenberg, 1992) These data suggest that increasing GR activity (Table 10) was able to maintain the glutathione redox state [GSH/(GSH+GSSG)] at over 0.94 during exposure of the fruit to photo-oxidative stress (Table 7), thereby reducing GSSG to GSH via a NADPH-dependent reaction (Carlberg and Mannervik, 1985). Despite the decline in total protein during exposure to solar radiation, the activities of all antioxidant enzymes on a protein basis dramatically increased as photo-oxidative stress progressed (Table 10). These results signify that the activities of these enzymes were conserved, perhaps because they were not targeted by proteinases under the environmental conditions imposed in our study. Furthermore, the amount of MDHAR and GR as a fraction of total protein increased or remained the same, respectively, as photo-oxidative stress progressed (Fig. 3), indicating that these enzymes were conserved under the stress conditions used here. This may represent an acclimation response to photo-oxidative stress. Indeed, MDHAR mRNA was found to increase in response to oxidative stresses generated by ozone, hydrogen peroxide, and methyl-viologen (Yoon et al., 2004). Similarly, increases in mRNA have been observed for other antioxidant enzymes, such as APX (Park et al., 2004) and DHAR (Urano et al., 2000), during oxidative stress. UV radiation (+UV) increased APX and MDHAR activities on a protein basis (Table 10), and CAT activity on a FW basis (Table 8). Similarly, enhanced peroxidase (including APX) activities in Arabidopsis thaliana leaves exposed to UV-B irradiation were reported by Rao et al. (1996). In leaves, UV irradiation mainly stimulated the production of O2·−, instead of 1O2, whereas mostly 1O2 production was stimulated when leaves were exposed to strong visible light (Hideg et al., 2002). Drought and chilling stress, as well as other stresses, have been associated with oxidative stress, but for both drought and chilling stress different responses by antioxidant components have been reported (Gechev et al., 2003). In our study, all antioxidant enzyme activities, except CAT, were higher on a protein basis as duration of exposure increased in the exocarp of both the sunlight-exposed and covered sections of tomato fruit (Table 9). This indicates that high temperatures, even without the stress imposed by visible light, produced a similar response in these enzymes to an increase in ROS flux. The hp-1 mutants, particularly hpA, as well as having more elevated ascorbate pools in exocarp tissue than the other genotypes (Table 5), also had higher APX and GR activities (Table 8). The increased APX activity of hp-1 might be a consequence of greater AsA availability, while the increased GR activity might be due to a higher demand for a reduction of oxidized glutathione (GSSH) in order to recycle DHA to AsA. There were no detectable changes in concentrations of quercetin, kaempferol, or naringenin enantiomers in fruit exocarp as the duration of exposure increased (data not shown), yet kaempferol and especially quercetin accumulated rapidly when fruits were exposed to sunlight (Table 2). These results suggest that kaempferol and quercetin synthesis might be triggered as a photoprotective mechanism by a sudden increase in light levels as suggested by Close and McArthur (2002) for leaves and Merzlyak et al. (2002) in apple fruit peel. However, once the synthesis of these flavonoids is induced, their concentrations under the same light conditions might stay constant or increase at a much slower rate. Interestingly, the concentration of naringenin did not respond to either the presence or absence of sunlight (data not shown). The presence or absence of natural UV radiation did not have an effect on flavonoid accumulation (data not shown), as has been shown for leaves (Ryan et al., 2002). This suggests that the accumulation of flavonoids as a photoprotective mechanism might be rapidly engaged by a sudden increase of visible light, but not UV radiation. It is also possible that UV-B induction of flavonoids (Ryan et al., 2002; Solovchenko and Schmitz-Eiberger, 2003) is a slower process under natural sunlight. It is important to mention that phenolics are able not only to absorb UV-B radiation in vitro, but also visible light (Jordan, 1996), minimizing photo-damage suffered by the photosynthetic apparatus under high light. The rapid accumulation of quercetin in exposed sections of fruit exocarp resulted in a significantly higher Q/K ratio after 5 h of exposure (Table 2). Curiously, although quercetin and kaempferol did not increase in the +UV treatment, the Q/K ratio did, from 7.9 for −UV to 10.6 for +UV (P=0.07). An increase in Q/K ratio might be a photoprotective mechanism that occurs with higher levels of UV-B radiation (Ryan et al., 2002). This supposition is based on the fact that quercetin (an ortho-dihydroxylated flavonoid) showed higher antioxidant capacity in vitro than its mono-hydroxylated flavonoid equivalent, kaempferol (Montesinos et al., 1995), and so quercetin synthesis is favoured over kaempferol in light-stress conditions. However, an increasing Q/K ratio could be merely due to a faster rate of degradation of kaempferol than quercetin. Previous reports on hp-1 mutants have indicated the enhancement of anthocyanin levels in several plant parts (Wettstein-Knowles, 1968a; Jarret et al., 1984). In this study, each of the flavonoids analysed was greatly enhanced in hpA fruit exocarp compared with its parent, AC (Table 11). This is another pleitropic effect of the mutation on the HP genes, which are believed to be negative regulators of phytochrome signal translation (Kerr, 1965; Kerckhoffs et al., 1997; Peters et al., 1998; Mustilli et al., 1999). In conclusion, in this study, the progression of photo-oxidative stress was followed in detached fruit under natural solar irradiance. Using this system, factors that were involved in the development of visual symptoms of sunscald and damage to the photosynthetic apparatus during photo-oxidative stress episodes were elucidated. These results suggest that antioxidant metabolites and enzymes may have been exerting some degree of protection to photo-oxidative damage. If the photo-oxidative stress conditions had persisted longer, however, the antioxidant systems may have been overcome, leading to permanent photo-oxidative injury. It was also determined that, as well as in leaves, flavonoids are rapidly induced in fruit exocarp exposed to solar irradiance as a physiological acclimatory response. It did not appear, however, that the natural UV radiation levels at the experimental site were responsible for either the increased flavonoids in the exocarp or sunscald development in any of the genotypes studied. Finally, the results suggest that during the photo-oxidative stress there was an increase in ROS flux due to decreased intrinsic PSII efficiency in the chlorophyll-containing exocarp of these immature tomato fruit. Although antioxidant metabolite pools initially decreased in response to photo-oxidative stress, the specific activities of antioxidant enzymes increased in order to maintain the ascorbate and glutathione pools in their reduced forms to eliminate ROS. 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