Plant Physiology

Minorsky, Peter V.

doi: 10.1104/pp.104.900255pmid: N/A

Photosynthesis Regulation of Root Ion Transporters The uptake rates of many ions are dependent on light conditions and fluctuate diurnally or are stimulated by an increase in light intensity. This control over root uptake systems has often been attributed to the regulatory action of sugars produced by photosynthesis and transported downward to the roots. These carbon (C) status-induced changes in root ion uptake are generally correlated with similar changes in the expression of genes encoding root ion transporters. Thus, it seems that the sugar regulation of ion transporter gene expression in the roots is a widespread mechanism, allowing the coordination of the transport of various ions with photosynthesis and the C status of the plant. Previously, it was shown in Arabidopsis (Arabidopsis thaliana) that the induction of the NRT2.1 NO3− transporter gene by sugars was dependent on C metabolism downstream of hexokinase (HXK) in glycolysis. To gain further insights into this signaling pathway and to explore more systematically the mechanisms coordinating root nutrient uptake with photosynthesis, Lejay et al. (pp. 2036–2053) studied the regulation of 19 light-/sugar-induced ion transporter genes. Various combinations of sugar, sugar analogs, light, and CO2 treatments provided evidence that these genes are not regulated by a common mechanism, and unraveled at least four different signaling pathways involved: regulation by light per se, by HXK-dependent sugar sensing, and by sugar sensing upstream or downstream HXK, respectively. Another major finding was that an inhibitor of phosphogluconate dehydrogenase almost completely prevented induction of NRT2.1 and NRT1.1 by sucrose, indicating that that the metabolism of glucose-6-P by the oxidative pentose phosphate pathway is required for generating the sugar signal. Out of the 19 genes investigated, most of those belonging to the NO3−, NH4+, and SO42− transporter families were regulated in a manner similar to NRT2.1 and NRT1.1. These data suggest that a yet-unidentified oxidative pentose phosphate pathway-dependent sugar sensing pathway governs the regulation of root nitrogen and sulfur acquisition by the C status of the plant, presumably coordinating the availability of these three elements for amino acid synthesis. Glycine Decarboxylase Subunit Gene from a C3-C4 Intermediate Species Net photosynthetic CO2 assimilation in C3 plants is reduced by photorespiration. The mitochondrial multienzyme complex glycine decarboxylase (GDC) plays a key role in photorespiration. GDC is composed of four subunits (P, H, L, and T) with the P-subunit (GLDP) serving as the actual decarboxylating unit. GDC is present in all photosynthetic cells of C3 plant leaves, but strictly confined to the bundle-sheath cells of C4 species. Conceivably, the specific expression of GLDP in the bundle-sheath cells may have constituted a biochemical starting point for the evolution of C4 photosynthesis. Plant species possessing a C3-C4 intermediate type of photosynthesis are of special interest for studying the evolution of C4-characteristic traits. As in C4 plants, functional GDC occurs only in the bundle-sheath cells of the leaves of C3-C4 intermediate plants. The genus Flaveria of the Asteraceae is a well-established experimental system for investigating the evolution of C4 characteristic traits. This genus includes both C3 and C4 species, but also a large number of C3-C4 intermediate species. To understand the molecular mechanisms responsible for restricting GLDP expression to bundle-sheath cells, Engelmann et al. (pp. 1773–1785) performed a functional analysis of a GLDP promoter from the C4 species Flaveria trinervia (Fig. 1 Figure 1. Open in new tabDownload slide F. trinervia. The genus Flaveria has C3, C4, and C3-C4 intermediate species. Photo courtesy of Pedro Tenorio Lezama. Figure 1. Open in new tabDownload slide F. trinervia. The genus Flaveria has C3, C4, and C3-C4 intermediate species. Photo courtesy of Pedro Tenorio Lezama. ). The activity of this GLDP promoter was analyzed by means of reporter gene in transgenic Flaveria bidentis (C4) and Arabidopsis (C3). Similar expression patterns were observed in both species, indicating that a mechanism for bundle-sheath-specific expression is also present in C3 species. Arabidopsis was subsequently used as a heterologous system for testing a series of promoter deletions to identify C4-characteristic regulatory elements within the GLDP promoter. These analyses resulted in the identification of two notable regions within the GLDP promoter, one conferring repression of gene expression in mesophyll cells and one functioning as a general transcriptional enhancer. Herbivore-Induced Callose Deposition The brown planthopper (Nilaparvata lugens; BPH) is an insect that feeds on the leaf sheath of rice (Oryza sativa) plants, ingesting nutrients from the phloem. BPHs frequently cause widespread destruction of rice crops and heavy losses of yield. Feeding by numerous BPHs on a single plant results in the susceptible plants yellowing, browning, and drying. In this issue, Hao et al. (pp. 1810–1820) help shed light on an important mechanism involved in rice resistance to BPHs: callose deposition. They used a susceptible rice plant variety (TN1) as a control, and first studied the feeding behavior of the BPH on rice plants carrying the BPH-resistance genes Bph14 and Bph15. They report that feeding was often interrupted on resistant plants. Tests with [14C]sucrose showed that insects ingested much less phloem sap from the resistant than the susceptible plants. To investigate the mechanisms that prevent BPHs from continuously ingesting phloem sap from resistant rice plants, the leaf sheaths of BPH-infested and BPH-free resistant and susceptible plants were examined histologically and by real-time PCR. BPH feeding induced callose deposition in the sieve tubes at the point where the stylet was inserted and up-regulated callose synthase genes in all plants. The compact callose remained intact in the resistant plants, but genes encoding β-1,3-glucanases were activated in susceptible plants, causing unplugging of the sieve tube occlusions. Protein Complexes and Starch Synthesis in Grains Starch is produced inside plastids and represents a major storage product of many of the seeds and storage organs produced for human consumption and industrial applications. The starch granule is a complex structure with a hierarchical order, allowing efficient packing of large amounts of glucose into a water-insoluble form. Starch granules are composed of two distinct types of glucose polymer: amylose and amylopectin. Amylose comprises largely unbranched α-(1→4)-linked glucan chains and does not appear to participate in the formation of the ordered part of the matrix. Amylopectin is a branched glucan polymer typically comprising between 65% and 85% of the starch granule mass, and is produced by the formation of α-(1→6)-branch linkages between adjoining linear [α-(1→4)-linked] glucan chains. Short- and intermediate-sized glucan chains that form double helices and pack together in organized arrays are the basis of the semicrystalline nature of much of the matrix of the starch granule. Thus, granule formation is driven by both the semicrystalline properties of amylopectin, as determined by the length of the linear chains of amylopectin and the clustering and frequency of α-(1→6)-branch linkages. Two contributions in this issue, a study of maize (Zea mays) by Hennen-Bierwagen et al. (pp. 1892–1908) and a study of wheat (Triticum aestivum) by Tetlow et al. (pp. 1878–1891) shed light on the interactions between starch synthases (SSs) and starch branching enzymes (SBEs) in amyloplasts. Mutations affecting specific starch biosynthetic enzymes commonly have pleiotropic effects on other enzymes in the same metabolic pathway. Although such genetic evidence indicates functional relationships between components of the starch biosynthetic system including SSs and SBEs, the molecular explanation for these functional interactions is not known. One possibility is that specific SSs and SBEs associate physically with each other in multisubunit complexes. These two articles describe the isolation and characterization of protein complexes comprising SSs and SBEs and SBE dimers from amyloplast extracts. The data indicate that formations of SS/SBE protein complexes do occur and that these protein interactions may depend upon phosphorylation and hydrophobic effects. Protein Diffusion in Grana Thylakoids Thylakoid membranes of higher plants have an intricate structure and are laterally segregated into distinct regions known as the grana and the stroma lamellae. PSII and its associated light-harvesting complex II are concentrated in the grana, while PSI and the ATPase are excluded from the grana and located instead in the stroma lamellae or at the grana margins. Thylakoid membranes in vivo, however, are not static structures. It has long been known that some protein complexes can diffuse between the grana and the stroma lamellae, and that this movement is important for various processes, including membrane biogenesis, regulation of light harvesting, and turnover and repair of the photosynthetic complexes. Grana thylakoids are among the most crowded membranes in nature: 70% to 80% of the membrane area is occupied by proteins. How can efficient protein diffusion take place in this densely packed membrane? In this issue, Kirchhoff et al. (pp. 1571–1578) report on their use of fluorescence recovery after photobleaching to probe the mobility of chlorophyll-protein complexes in isolated grana membranes from spinach (Spinacia oleracea). The authors were able to use the native fluorescence from the photosynthetic pigments to visualize protein movement, obviating the need for artificial fluorescent tags. They show that about 75% of fluorophores are immobile within a measuring period of 9 min, and suggest that this immobility is due to a protein network covering a whole grana disc. However, the remaining fraction is surprisingly mobile, which suggests that it is associated with mobile proteins that exchange between the grana and stroma lamellae within a few seconds. This contrasts sharply with computer simulations suggesting an escape time of about 1 h. Manipulation of the protein-lipid ratio and the ionic strength of the buffer reveals the roles of macromolecular crowding and protein-protein interactions in restricting the mobility of grana proteins. Mimicking the Natural Mechanical Impedance of Soil In nature, plant roots must undergo morphological changes as they navigate past obstacles in the soil. Root cap cells are the apparent sensors of touch in roots, but much remains to be learned about the signaling systems involved. One of the major barriers to understanding root growth through soil is mimicking natural soil conditions in experimental assays. In an effort to understand the effect of continuous mechanical impedance on the root morphology of Arabidopsis, Okamoto et al. (pp. 1651–1662) have developed a new growing system that provides continuous mechanical stimulation to root tips. In this growing system, Arabidopsis seedlings are grown on dialysis membrane-covered agar plates, and placed vertically (plates on edge) or horizontally (plates lying flat). The presence of the dialysis membrane prevents the root from penetrating inside the agar. Using well-characterized Arabidopsis mutants and gene expression analyses, the authors used this new technique to examine the role of ethylene in regulating the growth and development of roots. Their results suggest that it is enhanced responsiveness to ethylene rather than enhanced ethylene synthesis that plays a primary role in changing root morphology in response to mechanical impedance. www.plantphysiol.org/cgi/doi/10.1104/pp.104.900255 © 2008 American Society of Plant Biologists This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Grennan, Aleel K.

doi: 10.1104/pp.104.900254pmid: 18390488

Plants are continually exposed to potential pathogens and herbivores and have evolved defenses to counter such opportunistic invasions, including both physical (i.e. waxy cuticles, cell walls) and biochemical (i.e. defense compounds) barriers (for review, see Grennan, 2006). A key component to mounting an effective response, which may involve a change in gene expression, is an efficient signaling pathway. The identification and characterization of some members of the jasmonate and ethylene (ETH) signaling pathways is the focus of this month's High Impact and the topic of an article by McGrath et al. (2005), “Repressor- and activator-type ethylene response factors functioning in jasmonate signaling and disease resistance identified via a genome-wide screen of Arabidopsis transcription factor gene expression,” which as of February 2008 had received 38 citations (Thompson Scientific). THE BACKGROUND Plants are in constant interaction with other organisms. These interactions can be benign, beneficial, or detrimental for a plant. Plants need to not only distinguish between these interactions but also must have the ability to respond in a timely manner to an opportunistic invasion. This may include the synthesis of defense-related compounds, requiring a change in gene expression. Several defense signaling pathways have been demonstrated to be regulated by low-M r signal molecules, such as salicylic acid (SA), abscisic acid, jasmonic acid (JA), and ETH. Major aspects of these pathways have been genetically defined, revealing a linkage between the signaling pathways. Jasmonates mediate responses to insect and arthropod herbivores, some necrotrophic fungal pathogens, and nonpathogenic fungi as well as being involved in root growth (for review, see Farmer et al., 2003). ETH can act synergistically or antagonistically with JA in the regulation of both stress and developmental responses. The connection between these two signaling pathways has been demonstrated genetically to be the transcription factor (TF) ETHYLENE RESPONSE FACTOR1 (ERF1; Lorenzo et al., 2003). ERF TFs are a subfamily of the APETELA2 (AP2) TF family and contain a single DNA-binding domain. The target sequence for ERF TFs is the GCC box that is found in several promoters of pathogenesis-related genes as well as ETH- and JA-inducible genes (for review, see Gutterson and Reuber, 2004). SA also induces certain members of the ERF family. Isolation of these TFs would aid in the understanding of this important plant defense pathway. WHAT WAS SHOWN McGrath et al. (2005) were interested in identifying TFs involved in jasmonate signaling and plant defense. To achieve this, 1,534 TFs from Arabidopsis (Arabidopsis thaliana) were screened using real-time quantitative PCR for a change in transcript level following inoculation with the incompatible necrotrophic pathogen Alternaria brassicicola or exposure to the signaling compound methyl jasmonate (MeJA). This approach identified 134 TFs exhibiting a significant change in transcript levels following treatment, 20 of which were induced by both treatments. Included among these, 20 genes were members of the AP2/ERF family. Functional analysis of two of these gene products, AtERF4 and AtERF2, revealed an antagonistic relationship where AtERF4 acts as a negative regulator of JA-responsive defense gene expression and resistance to the necrotrophic fungal pathogen Fusarium oxysporum while AtERF2 is a positive regulator. The role of these two gene products was determined in Arabidopsis plants either overexpressing the TFs or with a T-DNA insertion in the gene. In the case of AtERF2, its role as a positive regulator of MeJA response was confirmed, as had previously been suggested in plants overexpressing AtERF2 (Brown et al., 2003). Additionally, a reduction in disease symptoms relative to wild type after inoculation with F. oxysporum was observed, supporting a role for AtERF2 as a positive regulator of disease resistance. AtERF4 involvement in defense gene regulation was examined in Arabidopsis plants overexpressing AtERF4 as well as T-DNA insertion lines. In the overexpressing plants, the induction of two genes (PDF1.2 and CHIB) known to be regulated by the JA pathway was lower than wild-type plants when treated with MeJA, while a increase in basal transcript levels was observed in the T-DNA lines that did not express AtERF4. Overexpressing plants, when challenged with F. oxysporum, exhibited greater disease symptoms than the wild type. Together, these results strongly suggested the role of AtERF4 as a negative regulator of both JA-dependent response and resistance to necrotrophic pathogens. A question that still remains open concerns the coordination of the expression and regulation of these two opposing regulators during plant defense. However, the coordinated activation of negative and positive regulators could be a strategy that plants use to mount a defense response that is detrimental to an invading pathogen while avoiding potentially self-inflicted damage (Kazan, 2006). THE IMPACT The transcript profile of canola (Brassica napus) exposed to the fungal pathogen Sclerotinia sclerotiorum also demonstrated an up-regulation of genes orthologous to AtERF2 and AtERF4 (Yang et al., 2007). This finding lends further support to the involvement of ERFs in expression of defense-related genes, as demonstrated by the work by McGrath et al (2005), and other jasmonate-responsive TFs, as shown in earlier studies (Anderson et al., 2004). A pathogen-induced ERF gene from wheat (Triticum aestivum), TaERF3, was isolated, and although it was found to contain the highly conserved DNA-binding domains, it had low sequence similarity to other known ERF proteins (Zhang et al., 2007), suggesting that it is a new member of the ERF family. TaERF3-GFP fusion constructs demonstrate targeting of the protein to the nucleus. Changes in TaERF3 transcript profile were investigated in pathogen-exposed resistant and susceptible lines of wheat using real-time quantitative PCR. Induction of the gene was found in all lines, but the induction profiles between the resistant and susceptible lines were different. TaERF3 expression was also induced after treatment with SA, JA, or ETH, but earlier than pathogen exposure. Similarly, transgenic expression of another ERF-type TF, HvRAF, from barley (Hordeum vulgare) in Arabidopsis provided increased resistance against the bacterial pathogen Ralstonia solanacearum (Jung et al., 2007). Together, these suggest the involvement of ERFs in defense signaling pathways in diverse plant species. CONCLUSION The identification and functional characterization of additional members of the plant defense signaling pathway are important in the understanding of how plants respond to biotic stresses. As more is learned about the different defense signaling pathways, the complexity and interconnectedness between them becomes more apparent. www.plantphysiol.org/cgi/doi/10.1104/pp.104.900254. LITERATURE CITED Anderson JP, Badruzsaufari E, Schenk PM, Manners JM, Desmond OJ, Ehlert C, Maclean DJ, Ebert PR, Kazan K ( 2004 ) Antagonistic interaction between abscisic acid and jasmonate-ethylene signaling pathways modulates defense gene expression and disease resistance in Arabidopsis. Plant Cell 16 : 3460 – 3479 Crossref Search ADS PubMed Brown RL, Kazan K, McGrath KC, Maclean DJ, Manners JM ( 2003 ) A role for the GCC-box in jasmonate-mediated activation of the PDF1.2 gene of Arabidopsis. Plant Physiol 132 : 1020 – 1032 Crossref Search ADS PubMed Farmer EE, Alméras E, Krishnamurthy V ( 2003 ) Jasmonates and related oxylipins in plant responses to pathogenesis and herbivory. Curr Opin Plant Biol 6 : 372 – 378 Crossref Search ADS PubMed Grennan AK ( 2006 ) Plant response to bacterial pathogens. Overlap between innate and gene-for-gene defense response. Plant Physiol 142 : 809 – 811 Crossref Search ADS PubMed Gutterson N, Reuber TL ( 2004 ) Regulation of disease resistance pathways by AP2/ERF transcription factors. Curr Opin Plant Biol 7 : 465 – 471 Crossref Search ADS PubMed Jung J, Won SY, Suh SC, Kim H, Wing R, Jeong Y, Hwang I, Kim M ( 2007 ) The barley ERF-type transcription factor HvRAF confers enhanced pathogen resistance and salt tolerance in Arabidopsis. Planta 225 : 575 – 588 Crossref Search ADS PubMed Kazan K ( 2006 ) Negative regulation of defense and stress genes by EAR-motif-containing repressors. Trends Plant Sci 11 : 109 – 112 Crossref Search ADS PubMed Lorenzo O, Piqueras R, Sanchez-Serrano JJ, Solano R ( 2003 ) ETHYLENE RESPONSE FACTOR1 integrates signals from ethylene and jasmonate pathways in plant defense. Plant Cell 15 : 165 – 178 Crossref Search ADS PubMed McGrath KC, Dombrecht B, Manners JM, Schenk PM, Edgar CI, Maclean DJ, Scheible W, Udvardi MK, Kazan K ( 2005 ) Repressor- and activator-type ethylene response factors functioning in jasmonate signaling and disease resistance identified via a genome-wide screen of Arabidopsis transcription factor gene expression. Plant Physiol 139 : 949 – 959 Crossref Search ADS PubMed Yang B, Srivastava S, Deyholos MK, Kav NNV ( 2007 ) Transcriptional profiling of canola (Brassica napus L.) responses to the fungal pathogen Sclerotinia sclerotiorum. Plant Sci 173 : 156 – 171 Crossref Search ADS Zhang Z, Yao W, Dong N, Liang H, Liu H, Huang R ( 2007 ) A novel ERF transcription activator in wheat and its induction kinetics after pathogen and hormone treatments. J Exp Bot 58 : 2993 – 3003 Crossref Search ADS PubMed © 2008 American Society of Plant Biologists This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Kazan, Kemal; Manners, John M.

doi: 10.1104/pp.107.115717pmid: 18390489

OXYLIPINS AS SIGNALING MOLECULES IN DIVERSE LIFE FORMS Oxylipins are biologically active signaling molecules derived from oxygenated polyunsaturated fatty acids and are found ubiquitously in most living organisms. In mammals, the eicosanoids, which include prostaglandins, are one of the best-studied groups of biologically important oxylipins. In addition to their essential roles in numerous other physiological functions, eicosanoids function as signaling molecules in vertebrate and invertebrate animals and in eukaryotic microbes (Stanley, 2006). The discovery of prostaglandins and related biologically active substances was recognized by the award of a Nobel Prize in Physiology or Medicine in 1982. Shortly after this, the pioneering work published in Plant Physiology by Vick and Zimmerman (1984) provided one of the first insights into the biosynthesis of jasmonate (JA), an oxylipin signaling molecule in plants. Indeed, of the various oxylipins synthesized enzymatically through the oxylipin (also known as octadecanoid) pathway, the plant hormones JAs (e.g. jasmonic acid and its methyl ester, MeJA) are often considered to be the structural and, in some cases, functional analogues of prostaglandins in animals. JAs are potent regulators of genes involved in cell growth and biotic and abiotic stress responses. Over the last decade or so, the JA signaling pathway has been studied extensively in dicot plant species, such as Arabidopsis (Arabidopsis thaliana), tomato (Solanum lycopersicum), and tobacco (Nicotiana tabacum), and to a somewhat limited extent in monocot plants, such as barley (Hordeum vulgare) and rice (Oryza sativa). Although much remains to be learnt, both forward and reverse genetic studies, particularly in Arabidopsis, have greatly expanded our understanding of the potential roles of JAs in plants. The biosynthesis of JAs has recently been reviewed (Wasternack, 2007), and a general overview is shown in Figure 1 Figure 1. Open in new tabDownload slide An integrated view of JA biosynthesis and signaling, including signaling interactions between JA and SA and JA and auxin (IAA) in Arabidopsis. Biotic and abiotic stresses, such as pathogen and insect attack and wounding, generate signals/elicitors that activate a phosphorylation cascade that regulates JA biosynthesis and signaling. Briefly, JAs are derived from α-linolenic acid liberated from membrane phospholipids by the action of phospholipase A. α-Linolenic acid is first converted to 13-hydroperoxy linolenic acid (13-HPOT) and then to 12-OPDA in the chloroplasts in a series of reactions catalyzed by 13-lipoxygenase, allene oxide synthase, and allene oxide cyclase, respectively. 12-OPDA is then transported to peroxisomes either passively or actively by the ABC (ATP-binding cassette) transporter COMATOSA (CMS). 12-OPDA is subsequently reduced by 12-OXOPHYTODIENOATE REDUCTASE3 to 3-oxo-2-(2′-pentenyl)-cyclopentane-1-octanoic acid, which then undergoes three cycles of β-oxidation in the peroxisomes to produce jasmonic acid. Jasmonic acid is further modified in the cytosol to produce various jasmonic acid derivatives. For instance, jasmonic acid is converted to volatile oxylipin MeJA by a JA methyl transferase or conjugated into several amino acids by an amino acid synthetase encoded by the JAR1 gene. JAZ proteins act as negative regulators of the transcriptional regulator JIN1/MYC2, and their JA- and SCFCOI1-dependent degradation liberates JIN1/MYC2 from repression. JIN1/MYC2, by possibly binding to the conserved G-box element found in the promoters, coordinates a transcriptional cascade that involves other transcriptional activators and repressors from AP2/ERF, WRKY, and MYBs to modulate distinct JA-dependent functions. JA may also be transported to distal tissue that has not been directly challenged to activate systemic gene expression. The cross talk between JA and SA and JA and auxin signaling occurs at multiple points. As explained in the text, NPR1, MPK4, WRKY70, SCFCOI1, and JIN1/MYC2 are some of the major players involved in these interactions. Similarly, the JA-auxin cross talk is modulated by CSN, SGT1b, AXR1, and ARFs. Please note that for SA and auxin signaling, only those components known to interact with JA signaling are shown. See text for further details and abbreviations. Figure 1. Open in new tabDownload slide An integrated view of JA biosynthesis and signaling, including signaling interactions between JA and SA and JA and auxin (IAA) in Arabidopsis. Biotic and abiotic stresses, such as pathogen and insect attack and wounding, generate signals/elicitors that activate a phosphorylation cascade that regulates JA biosynthesis and signaling. Briefly, JAs are derived from α-linolenic acid liberated from membrane phospholipids by the action of phospholipase A. α-Linolenic acid is first converted to 13-hydroperoxy linolenic acid (13-HPOT) and then to 12-OPDA in the chloroplasts in a series of reactions catalyzed by 13-lipoxygenase, allene oxide synthase, and allene oxide cyclase, respectively. 12-OPDA is then transported to peroxisomes either passively or actively by the ABC (ATP-binding cassette) transporter COMATOSA (CMS). 12-OPDA is subsequently reduced by 12-OXOPHYTODIENOATE REDUCTASE3 to 3-oxo-2-(2′-pentenyl)-cyclopentane-1-octanoic acid, which then undergoes three cycles of β-oxidation in the peroxisomes to produce jasmonic acid. Jasmonic acid is further modified in the cytosol to produce various jasmonic acid derivatives. For instance, jasmonic acid is converted to volatile oxylipin MeJA by a JA methyl transferase or conjugated into several amino acids by an amino acid synthetase encoded by the JAR1 gene. JAZ proteins act as negative regulators of the transcriptional regulator JIN1/MYC2, and their JA- and SCFCOI1-dependent degradation liberates JIN1/MYC2 from repression. JIN1/MYC2, by possibly binding to the conserved G-box element found in the promoters, coordinates a transcriptional cascade that involves other transcriptional activators and repressors from AP2/ERF, WRKY, and MYBs to modulate distinct JA-dependent functions. JA may also be transported to distal tissue that has not been directly challenged to activate systemic gene expression. The cross talk between JA and SA and JA and auxin signaling occurs at multiple points. As explained in the text, NPR1, MPK4, WRKY70, SCFCOI1, and JIN1/MYC2 are some of the major players involved in these interactions. Similarly, the JA-auxin cross talk is modulated by CSN, SGT1b, AXR1, and ARFs. Please note that for SA and auxin signaling, only those components known to interact with JA signaling are shown. See text for further details and abbreviations. . Following synthesis, JAs are perceived by as yet unknown receptor proteins, and this presumably activates a signal transduction pathway that culminates in the transcriptional activation or repression of a large number of JA-responsive genes. JAs inhibit root elongation, and this property has been extensively exploited for the identification of JA signaling mutants. One of the first JA signaling mutants identified was the Arabidopsis coronatine insensitive1 (coi1) mutant. Root elongation of coi1 mutant seedlings showed reduced sensitivity to JAs but also to coronatine (COR), a functional JA homolog and toxin produced by the bacterial pathogen Pseudomonas syringae (Feys et al., 1994). The coi1 mutant displays defects in many, if not all, JA-dependent functions, such as fertility, secondary metabolite biosynthesis, pest and pathogen resistance, and wound responses. The COI1 locus encodes an F-box protein, and because F-box proteins are integral parts of multi-protein complexes involved in protein ubiquitination, it was speculated that COI1 is required for removal of repressors of the JA signaling pathway (Xie et al., 1998). However, until very recently, the nature of the COI1-targeted repressors has remained elusive. Similarly, two other JA signaling loci, JAR1 (JASMONATE RESISTANT1) and JIN1 (JASMONATE INSENSITIVE1), were identified from analyses of the Arabidopsis jar1 and jin1 mutants, which also show reduced sensitivity to exogenous JAs. JAR1 encodes a JA amino acid synthetase involved in conjugating jasmonic acid to Ile (Staswick and Tiryaki, 2004). JIN1 (also known as MYC2) encodes a basic helix-loop-helix-type transcription factor involved in the transcriptional regulation of JA-responsive gene expression (Lorenzo et al., 2004). Despite extensive characterizations of individual mutants, the exact nature of the functional relationships among these three major players (i.e. COI1, JAR1, and JIN1/MYC2) of JA signaling has long been enigmatic. Importantly, the recent cloning of the JAI3 (JASMONATE INSENSITIVE3) locus (Chini et al., 2007) has filled a significant gap in our overall understanding of the JA signaling pathway by mechanistically linking the functions of COI1, JAR1, and JIN1, as well as revealing the nature of the long-sought repressors of JA signaling. Our aim in this Update article is to briefly review these recent findings that have added fresh insights into our understanding of how JA signals are transmitted within the cell. Our particular focus will be on the roles of a recently discovered class of repressors whose destruction through a COI1-mediated ubiquitination pathway is required for the transcriptional activation of the JA-dependent gene expression. In addition, the emerging roles of the transcriptional regulator JIN1/MYC2 that acts immediately downstream from these repressors in coordinating a transcriptional cascade will be briefly reviewed. Finally, positive and negative feedback loops regulating JA biosynthesis and signaling and some recent examples of interactions between JA and other hormonal signaling pathways will be considered. Readers particularly interested in JA biosynthesis should refer to other recent reviews on this topic (Browse, 2005; Wasternack, 2007). ACTIVATION OF JA SIGNALING BY REPRESSOR REMOVAL Many plant processes are controlled by repressors of downstream transcriptional networks, and the degradation of these repressors under external stimuli and by plant hormones provides a rapid regulatory trigger system. The involvement of protein degradation pathways in JA signaling became apparent after the identification of the COI1 gene encoding an F-box protein with Leu repeats (Xie et al., 1998). Indeed, COI1 or SCFCOI1 is an integral part of a highly conserved multi-protein complex called the SCF E3 ubiquitin ligase complex. The SCF complex is found in all eukaryotes and consists of a Skp1 (S-phase kinase-associated protein)-related protein, a cullin, a RING-box protein, and an F-box protein. The SCF complex is involved in marking proteins with ubiquitin tags to facilitate their degradation by the 26S proteasome (for review, see Stone and Callis, 2007). The F-box protein component (e.g. SCFCOI1) is known to be responsible for the specificity of the SCF complexes to particular targets. However, as stated above, repressor proteins potentially targeted by SCFCOI1 have been unknown. Recently, three laboratories have simultaneously converged on a family of genes that fulfils this role. The cloning of mutated genes in JA-insensitive mutants has so far provided vital information about the signaling events involved in this pathway. In contrast to the recessive coi1, jar1, and jin1 mutations, the relatively less-studied jai3 mutation confers a dominant JA insensitivity phenotype (Chini et al., 2007). To identify the molecular nature of this mutation, Chini et al. (2007) have sequenced the chromosomal region around the genetically mapped location of jai3 for possible mutations. This exercise identified a point mutation in a gene of unknown function. This mutation is predicted to cause the aberrant splicing of this gene, presumably leading to the production of a protein truncated at the C terminus. As expected, transgenic expression of the jai3 mutant protein in wild-type plants, but not the wild-type JAI3, produces the jai3 mutant phenotype, confirming that the jai3 mutation was indeed responsible for the dominant JA insensitivity phenotype. The JAI3 protein contains a ZIM (zinc finger protein expressed in inflorescence meristem) domain (Shikata et al., 2003). Because JAI3 was both an early JA-responsive gene and required for JA sensitivity, it was renamed as JASMONATE ZIM DOMAIN3 (JAZ3; Chini et al., 2007). Thines et al. (2007), on the other hand, have used a reverse genetic approach to identify the possible functions of the early JA-inducible genes in Arabidopsis stamens. An earlier study had found that, as early as 30 min after JA treatment, several genes encoding individual members of the JAZ protein family showed strong induction in the stamens of the JA-deficient 12-oxophytodienoate reductase3 mutant (Mandaokar et al., 2006). Thines et al. (2007) studied the functions of these genes by overexpressing and knocking out the expression of individual JAZ genes. Disappointingly, none of the lines studied displayed any discernible JA-dependent phenotype, possibly due to functional redundancy. However, when a truncated version of JAZ1 called JAZ1Δ3 was transgenically expressed in Arabidopsis, a coi1-like phenotype characterized by male sterility, JA insensitivity, and increased resistance to infection by the bacterial pathogen P. syringae pv. tomato was observed. JAZ1Δ3 transgenic lines also show increased susceptibility to the herbivorous insect Spodoptera exigua (Chung et al., 2008). These transgene-conferred phenotypes were suggestive of a role for JAZ1 in JA signaling. The additional work by both Chini et al. (2007) and Thines et al. (2007) has led to the conclusion that JAZ1 and JAI3/JAZ3 are indeed the long-sought repressors of the JA signaling pathway, and their SCFCOI1-dependent ubiquitination is required for the activation of JA-responsive gene expression. Indeed, the JA-dependent degradation of JAZs could be inhibited by a specific inhibitor of the 26S proteasome activity or in the coi1 mutant background. Furthermore, results from yeast two-hybrid studies showed that SCFCOI1 interacts with the JAI3/JAZ3 C-terminal region, the same domain that is truncated in the jai3 mutant. Another interesting finding was that the interaction between SCFCOI1 and JAZ1 or JAI3/JAZ3 was promoted by JA-Ile in a highly specific manner but not by jasmonic acid, MeJA, COR, or the JA precursor 12-oxo-phytodionic acid (12-OPDA; Chini et al., 2007; Thines et al., 2007). This finding has obvious implications about the identity of the biologically active signal in this signaling pathway (see below). How does JA- and SCFCOI1-dependent degradation of JAZ repressors transcriptionally regulate the JA signaling pathway? JAZ proteins do not contain any DNA-binding domain. This is an indication that they may interact with other proteins to regulate gene expression (see also Vanholme et al., 2007 for additional discussion). Interestingly, both JAZ1 and JAI3/JAZ3 each interact with JIN1/MYC2, a transcriptional regulator in JA signaling (see also below), in yeast two-hybrid assays (Chini et al., 2007). This finding suggests that, in the absence of a JA signal, JAZ1 and JAI3/JAZ3 repress JIN1/MYC2. This repression most likely occurs in the nucleus, as both JAZ repressors and JIN1/MYC2 are found in the nucleus during normal growth and development (Lorenzo et al., 2004; Chini et al., 2007; Thines et al., 2007). Upon sensing of the JA signals, JAZ repressors are recruited to the SCF E3 complex for ubiquitination and subsequent degradation by the proteasome. The removal of these repressors then paves the way for JIN1/MYC2 to regulate JA-dependent gene expression (Fig. 1). Another member of the JAZ family, JASMONATE ASSOCIATED1 (JAS1), also appears to be involved in JA signaling (Yan et al., 2007). This gene was first identified by a microarray screen for JA-regulated transcripts. The JAS1.3 locus is an alternatively transcribed gene, producing two different isoforms in Arabidopsis. The overexpression and RNAi-mediated silencing of the shorter isoform of JAS1, designated as JAS1.3/JAZ10.3, made the plants less and more sensitive to growth repression by MeJA. In contrast, the overexpression of the longer isoform of this gene did not produce any JA-dependent growth phenotype. JAS1.3/JAZ10.3 overexpressing plants also showed reduced growth inhibition after wounding (Yan et al., 2007), another JA-dependent phenotype. The molecular mechanism(s) of JAS1.3/JAZ10.3-mediated growth phenotype is currently far from clear. However, these findings collectively suggest that the different members of the JAZ protein family have essential roles in multiple JA-dependent functions. MULTIPLICITY OF JA SIGNALS AND RECEPTORS The finding that JA-Ile, a jasmonic acid-Ile conjugate, but not jasmonic acid itself, MeJA, COR, or the JA precursor 12-OPDA promotes the interaction between SCFCOI1-JAZ complexes in yeast two-hybrid assays (Thines et al., 2007) raises new questions regarding the exact nature of the JA signal(s) perceived by putative JA receptors. This finding might imply that jasmonic acid may not be the signal directly responsible for the activation of the JA signaling pathway, but possibly it undergoes further modifications to be converted to a biologically active signal. In contrast to this, in other hormone signaling pathways (e.g. auxin), conjugation of amino acids to plant hormones is often used as a versatile mechanism for rapid reduction of the hormone levels and, consequently, down-regulation of the signaling pathway (Woodward and Bartel, 2005). When required, hormone-amino acid conjugates are rapidly hydrolyzed to release the active hormone and this activates the signaling pathway. As mentioned above, the product of the JAR1 locus conjugates Ile to jasmonic acid. However, the jar1 mutant does not display all the defects observed in the coi1 mutant, suggesting that JA-Ile may not be the only signal responsible for the activation of the JA signaling pathway. Interestingly, although JA-Ile produced by JAR1 promotes the interaction between JAZ and SCFCOI1, a recent report found that wound-induced expression JAZ and SCFCOI1-dependent genes in the jar1 mutant was similar to that in wild-type plants (Chung et al., 2008). This and other relatively subtle JA defects observed in the jar1 mutant could be due to the fact that wound-induced JA-Ile levels in this mutant are still relatively high (approximately 10%–25% of wild-type levels; Chung et al., 2008). This indicates that JAR1 is perhaps not the only enzyme conjugating JA to Ile in Arabidopsis. In addition to Ile, the JAR family of related GH3 enzymes has the potential to conjugate JA to other amino acids such as Trp, Val, and Leu as recently found in tobacco (Wang et al., 2008). In addition, both JA-Ile and 12-OPDA induce distinct but overlapping patterns of gene expression as jasmonic acid and MeJA (Taki et al., 2005; Wang et al., 2008). The 12-OPDA-induced gene expression also appears to be independent from SCFCOI1 in Arabidopsis (Taki et al., 2005). JA is converted to MeJA by a JA methyl transferase (Fig. 1), while at least in tobacco, exogenously applied MeJA is hydrolyzed by a MeJA esterase to produce jasmonic acid (Wu et al., 2008). Silencing the expression of the NaMJE gene encoding this MeJA-cleaving esterase in transgenic tobacco inhibits MeJA- but not jasmonic acid-induced insect resistance (Wu et al., 2008). It is not known whether the conversion of MeJA to jasmonic acid plays any role in transducing airborne signals emitted by the nearby plants through JA signaling. However, it is likely that there might be multiple JA-derived signals affecting the stability of different SCFCOI1-JAZ complexes. The presence of different JA-derived signals could be used as a means to regulate endogenous hormone levels but also help to rapidly respond to different endogenous and exogenous cues. TRANSCRIPTIONAL COORDINATION OF JA SIGNALING As mentioned above, JAI3/JAZ3 most likely suppresses the transcription factor JIN1/MYC2, which, acting early on in the signaling pathway, can either positively or negatively modulate diverse JA-dependent functions. In particular, the JA-dependent expression of pathogen and insect defense genes is differentially regulated by JIN1/MYC2. In the jin1/myc2 mutant, JA-dependent induction of wound and insect response genes was significantly attenuated, and, as a result, jin1/myc2 mutant plants showed increased susceptibility to an insect pest (Dombrecht et al., 2007). In contrast, the JA-dependent induction of pathogen defense genes was heightened in the jin1/myc2 mutant, which showed increased resistance to bacterial and fungal pathogens (Anderson et al., 2004; Lorenzo et al., 2004). Accumulating evidence indicates that plants are able to coordinate their responses depending on the type of attack so that the metabolic cost of plant defense can be minimized. Indeed, although both herbivory and pathogen attack activate JA signaling, the defense genes that are activated are functionally specialized against insect pests or pathogens, respectively (De Vos et al., 2005). JIN1/MYC2 and similar other molecular switches might perhaps be required to fine-tune plant defense against different biological threats. Recent research has also showed that, in addition to pathogen and insect defense, JIN1/MYC2 differentially regulates other JA-dependent functions in Arabidopsis. For instance, in addition to insect resistance, JIN1/MYC2 positively regulates JA-mediated oxidative stress tolerance and flavonoid metabolism. In contrast, JA-dependent pathogen defense and the biosynthesis of secondary metabolites (e.g. biosynthesis of indole glucosinolates) are negatively regulated by JIN1/MYC2 (Dombrecht et al., 2007; Fig. 2 Figure 2. Open in new tabDownload slide JIN1/MYC2 differentially regulates different JA-dependent phenotypes. Arrows and blunt arrows indicate positive and negative regulation, respectively. See text for details. Figure 2. Open in new tabDownload slide JIN1/MYC2 differentially regulates different JA-dependent phenotypes. Arrows and blunt arrows indicate positive and negative regulation, respectively. See text for details. ). It was proposed that these regulatory controls are mediated by JIN1/MYC2 by coordinating a transcriptional cascade involving a number of other transcription factors (AP2/ERFs, MYBs, zinc fingers, and WRKYs), each with demonstrated roles in regulating downstream gene expression (Dombrecht et al., 2007). JIN1/MYC2 does not have any obvious roles in fertility, although this trait is regulated by SCFCOI1. Fertility might be controlled by other SCFCOI1-regulated transcription factors. Recent analysis of the T-DNA insertion mutants of the two JA-responsive MYB transcription factor genes, MYB21 and MYB24, indicated their involvement in fertility (Mandaokar et al., 2006), although whether these MYB transcription factors interact with SCFCOI1 and/or JAZ repressors is currently unknown. NEGATIVE AND POSITIVE REGULATORY FEEDBACK LOOPS IN JA SIGNALING The relatively broad effects of hormone signaling pathways on multiple plant physiological processes demand that signaling pathways are tightly and coordinately regulated, preferably at multiple points. So far, both negative and positive feedback regulatory loops that regulate JA biosynthesis and signaling have been identified. First, JA biosynthesis genes are activated by JAs, suggesting that JAs positively regulate their own biosynthesis through a positive feedback loop. The recent identification of the Arabidopsis FATTY ACID OXYGENATION UPREGULATED2 gene that encodes a Ca2+-permeant nonselective cation channel suggested that cation fluxes are an important part of this positive feedback loop (Bonaventure et al., 2007). JA also rapidly activates the transcription of genes encoding JAZ repressors (Chini et al., 2007) while facilitating, as stated above, their destruction at the protein level. This destruction and subsequent resynthesis of JAZ repressors during JA signaling would reset the signaling pathway, avoiding a run-away response. Another level of control in JA signaling is exerted at the JIN1/MYC2 level. JIN1/MYC2 controls transcriptional activation of the JAZ-encoding genes (Chini et al., 2007). MYC2 expression itself is both positively and negatively regulated by JAs. The negative regulation of JIN1/MYC2 during JA signaling is proposed to occur through the mitogen-activated protein kinase pathways regulated by MKK3 and MPK6 (Takahashi et al., 2007). In addition, JIN1/MYC2 can negatively regulate its own expression, possibly by binding to the conserved G-box found in its own promoter (Dombrecht et al., 2007). Additional control points in JA signaling probably exist. In particular, complex cross communication between JA and other hormonal signaling pathways might help fine-tune JA biosynthesis and signaling (see below). The roles of protein phosphorylation/dephosphorylation pathways in negative and positive regulation of JA biosynthesis and signaling are just emerging. Importantly, protein phosphorylation often precedes the ubiquitination process, which, as discussed above, is critical for the activation of the JA signaling pathway. Although whether Arabidopsis JAZ repressors are phosphorylated before being ubiquitinated is not known, a recent report indicated that PPS3, the potato homolog of JAI3/JAZ3, is phosphorylated by StMPK1, which shows close sequence similarity to Arabidopsis MPK6 (Katou et al., 2005). In addition to phosphorylation, protein dephosphorylation pathways modulate JA levels. For instance, in response to wounding, the PP2C-type phosphatase AP2C1 negatively regulates mitogen-activated protein kinase signaling pathways as deduced from the analysis of the Arabidopsis ap2c1 mutant, which contains increased levels of wound-induced JAs and displays enhanced resistance to a phytophagous mite (Schweighofer et al., 2007). JA SIGNALING AND HORMONAL CROSS TALK It is becoming evident that plant hormone signaling pathways extensively interact during plant growth and development as well as during adaptation to biotic and abiotic stresses. This hormonal cross talk is indeed intriguingly complex and often dose-, species-, tissue-, and inducer-specific. The JA signaling pathway is no exception to this. Over the years, many components that are shared between JA and various other plant hormone signaling pathways have been identified. Cross talk is mostly inferred from the observation that genetic ablation of the individual shared components (or nodes) compromises both pathways or if one hormone brings about physiological changes mainly by promoting the synthesis or action of another hormone. JA-SALICYLIC ACID INTERACTIONS The mutually antagonistic interactions between salicylic acid (SA) and JA pathways first became evident from the analysis of SA- and JA-marker gene expression in SA and JA signaling mutants in Arabidopsis. Indeed, mutations that disrupt JA signaling (e.g. coi1) lead to the enhanced basal and inducible expression of the SA marker gene PR1, while mutations that disrupt SA signaling (e.g. npr1) lead to the concomitant increases in the basal or induced levels of the JA marker gene PDF1.2. Interestingly, exogenous SA promotes the JA-dependent induction of the defense gene PDF1.2 when applied at low concentrations. However, at higher SA concentrations, the induction of PDF1.2 by JA is reduced, leading to the proposal that the interaction between these two pathways might be dose dependent (Mur et al., 2006). Plants treated with SA or inoculated with virulent strains of P. syringae pv. tomato show compromised resistance to Alternaria brassicicola, a necrotrophic pathogen sensitive to JA-dependent defenses, possibly due to suppression of JA-dependent defenses known to be effective against necrotrophic pathogens (Spoel et al., 2007). Interestingly, however, inoculations with an avirulent strain of P. syringae that trigger hypersensitive response do not compromise A. brassicicola resistance, suggesting that cross talk between SA and JA signaling is also specific to pathogen strain (Spoel et al., 2007). The antagonistic interaction between SA and JA signaling is at least partly mediated by NONINDUCIBLE PR1 (NPR1), a master regulator of SA signaling, but also responds to oxidative events (Spoel et al., 2003, 2007). Interestingly, the SA-JA antagonism and the involvement of NPR1 is reminiscent to the inhibition of prostaglandin biosynthesis by aspirin, which acts by trans-acetylation of cylooxygenases and by inhibiting the transcription from cyclooxygenase-encoding genes involved in prostaglandin synthesis through the function of transcriptional repressor IKβ, an NPR1 homolog in animals. In tobacco, the role of NPR1 in regulating JA-SA cross talk also appears to be different from that in Arabidopsis. In insect-attacked tobacco, NPR1 down-regulates SA biosynthesis, and this leads to the up-regulation of JA biosynthesis and signaling that is required for defense against insect attack (Rayapuram and Baldwin, 2007). Therefore, the mechanism of antagonistic interaction between SA and JA pathways seems to vary between different species. Acting downstream from NPR1, WRKY70 is a versatile transcription factor with roles in multiple signaling pathways and physiological processes. WRKY70 regulates the antagonistic interactions between SA and JA pathways (Fig. 1). Overexpression of WRKY70 leads to the constitutive expression of the SA-responsive PR genes and increased resistance to SA-sensitive pathogens but reduces resistance to JA-sensitive pathogens. In contrast, suppression of WRKY70 leads to increased expression from JA-responsive genes and increased resistance to a pathogen sensitive to JA-dependent defenses (Li et al., 2004a). WRKY70 is also implicated in suppressing SA levels when SA levels are particularly high (Wang et al., 2006). Another WRKY transcription factor that negatively regulates JA signaling in an NPR1-dependent manner is WRKY62 (Mao et al., 2007; Fig. 1). The hierarchical relationship between WRKY70 and WRKY62 is unknown. The Arabidopsis mpk4 mutant exhibits constitutively active SA-dependent defense responses (e.g. increased SA levels, constitutive expression of PR1, and increased resistance to P. syringae) in the absence of pathogen attack. In contrast, the JA-dependent induction of the PDF1.2 gene was abolished in the mpk4 mutant (Petersen et al., 2000). Therefore, MPK4 is proposed to be a positive regulator of JA-dependent responses while a negative regulator of SA biosynthesis and signaling. As expected, overexpression of MKS1, a MPK4 substrate, also regulates SA signaling through interaction with WRKY transcription factors. However, no effect of MKS1 overexpression on JA signaling was found (Andreasson et al., 2005). Therefore, it is unknown whether MPK4 phosphorylates any JA signaling component during its positive regulation of JA signaling or if the reduced JA-dependent responses found in the mpk4 mutant is simply due to antagonistic effects of the enhanced SA biosynthesis and signaling. SA-JA interaction in Arabidopsis is also regulated by an SA-inducible glutaredoxin, GRX480, which interacts with the TGA-type transcription factors involved in the regulation of SA-inducible PR genes and suppresses the JA-responsive expression of PDF1.2 (Ndamukong et al., 2007). More recently, the involvement of ESR/ESP (epithiospecifying senescence regulator) and WRKY53 (Miao and Zentgraf, 2007) in SA-JA interaction has also been reported (Fig. 1). In addition to COI1, the transcriptional regulator JIN1/MYC2 also has a role in antagonizing SA signaling in plants during infection by P. syringae. Increased PR1 expression and resistance is found in P. syringae-infected jin1/myc2 plants that show increased resistance to this pathogen (Laurie-Berry et al., 2006). It is not clear, however, whether JIN1/MYC2 directly represses PR1 or whether the increased PR1 expression observed in the jin1/myc2 mutant is due to indirect effects of the compromised JA signaling on SA signaling and subsequent responses. JA-ETHYLENE INTERACTIONS The interaction between JA and ethylene signaling is rather complex, and both synergistic and antagonistic interactions have been reported, depending on the stress conditions examined. Adding to this complexity, the role of ethylene in biotrophic pathogen-plant interactions could be different than that in necrotrophic pathogen-plant interactions (Broekaert et al., 2006). JA and ethylene synergistically induce a subset of defense genes following pathogen inoculation in Arabidopsis. For instance, induction of PDF1.2 by A. brassicicola requires both JA and ethylene signaling pathways (Penninckx et al., 1998). The cellulose synthase gene CeSA3/CEV1 controls a point of convergence between these two pathways as a negative regulator of both pathways, as deduced from the analysis of the cev1 mutant that displays constitutively active JA and ethylene responses (Ellis et al., 2002). The ETHYLENE RESPONSE FACTOR1 transcription factor also functions at the crossroad of JA and ethylene signaling as a positive regulator of both pathways (Lorenzo et al., 2003). In contrast to these synergistic interactions, JA and ethylene signaling pathways act in a mutually antagonistic fashion in modulating ozone-induced cell death. Most, if not all, JA signaling and biosynthetic mutants show increased ozone sensitivity. In contrast to the effect of JA signaling, the ethylene signaling pathway promotes ozone-induced spread of lesion development (for review, see Overmyer et al., 2003). JA, LIGHT, AND AUXIN INTERACTIONS As discussed above, protein degradation pathways play essential roles not only in JA but also in light and auxin signaling. Not surprisingly, therefore, most cross talk among these pathways revolves around the SCF E3 ubiquitin ligase and the COP9 signalosome (CSN) complexes. For instance, mutations in CULLIN1/AUXIN RESISTANT6 (AXR6) component of the SCF ubiquitin ligase and CSN complexes compromise auxin, JA, and light responses. The axr6 mutant shows reduced sensitivity to JA and auxin (Feng et al., 2003; Ren et al., 2005) and hypersensitivity to far-red light (Quint et al., 2005). A direct interaction between CSN and SCFCOI1 has been shown. CSN reduction-of-function plants show a JA-insensitive root elongation phenotype and reduced expression from JA-responsive genes (Feng et al., 2003). AXR1, which encodes a subunit of the RUB1-activating enzyme that regulates the protein degradation activity of SCF complexes, regulates both SCFTIR1 and SCFCOI1 involved in auxin and JA signaling, respectively (Schwechheimer et al., 2002). The axr1 mutant shows reduced sensitivity to both JA and auxin (Tiryaki and Staswick, 2002). SUPPRESSOR OF THE G2 ALLELE OF skp1-4b is required for both SCFTIR-mediated auxin and SCFCOI1-mediated JA responses (Gray et al., 2003). Auxin and JA pathways are also interlinked at the level of ARFs. At least two ARFs, ARF6 and ARF8, are required for JA biosynthesis and flower fertility (Fig. 1). In addition to defective auxin responses, the arf6/arf8 double mutant shows JA deficiency, aberrant flower development, and reduced expression of several JA biosynthesis genes in flowers (Nagpal et al., 2005). JA activates expression from auxin biosynthesis genes (Dombrecht et al., 2007), while auxin activates expression of JA biosynthesis genes (Tiryaki and Staswick, 2002). These examples clearly illustrate that auxin and JA signaling are intimately interlinked. The Arabidopsis phytochrome mutants hy1 and hy2 show a JA overproduction phenotype and constitutive activation of the JA-inducible and SCFCOI1-dependent defense genes (Zhai et al., 2007). Importantly, JIN1/MYC2 acts as a negative regulator of blue light-mediated photomorphogenic growth and blue and far-red light-regulated gene expression in Arabidopsis (Yadav et al., 2005). JA-ABSCISIC ACID INTERACTIONS Both antagonistic and synergistic interactions occur between abscisic acid (ABA) and JA signaling in Arabidopsis. Both ABA and MeJA induce stomatal closure, most likely by triggering the production of reactive oxygen species (ROS) in stomatal guard cells (Munemasa et al., 2007). The coi1 mutation disrupts only MeJA-mediated ROS production without influencing ABA-mediated ROS production, suggesting that COI1 acts upstream from the convergence of ABA and MeJA signaling pathways. JIN1/MYC2, a negative regulator of JA-dependent pathogen defense gene expression, positively regulates ABA-dependent drought responses (Anderson et al., 2004). A recent study has shown that endogenous ABA had positive and negative regulatory effects on JA-responsive insect and pathogen defense genes, respectively. In the ABA-deficient mutant aba2-1, the insect-responsive expression of VSP2 was reduced while that of PDF1.2 was increased. Consistent with this, the Spodeptera littoralis larvae had a higher weight gain on the aba2-1 mutant than on wild-type plants (Bodenhausen and Reymond, 2007). Nevertheless, JA and ABA activate a large subset of genes also activated by the pathogenic oomycete Pythium irregulare. This effect of ABA is proposed to be due to the effect of this root-infecting pathogen to impose water stress in plants by clogging the vasculature (Adie et al., 2007). ABA also appears to induce JA biosynthesis in Arabidopsis, and increased JA levels found in ABA-treated plants were proposed to be a reason behind the reduced SA defense gene expression by ABA (Adie et al., 2007). CONCLUSIONS AND FUTURE PROSPECTS As exemplified throughout this article, the genetic and genomic resources available in Arabidopsis have been a driving force behind the recent discoveries made regarding how JA signals are transmitted. Some of the JA signaling components that have been identified in Arabidopsis have also been functionally analyzed in a few other dicot species, such as tobacco (Paschold et al., 2007; Rayapuram and Baldwin, 2007; Wang et al., 2008) and tomato (Boter et al., 2004; Li et al., 2004b; Thines et al., 2007), where they have been shown to be largely conserved. However, currently there is very little evidence regarding the actual roles of the Arabidopsis JA signaling genes in monocots. In crop plants that are not particularly amenable to functional studies (e.g. due to genetic redundancy and/or technical difficulties associated with genetic transformation), functional homology to Arabidopsis JA signaling genes was established based on the successful restoration of the wild-type phenotype when the cloned crop gene of interest was introduced into the well-characterized Arabidopsis mutant (e.g. coi1) defective for the same JA signaling component (Wang et al., 2005). The recent discovery of JAZ repressors in Arabidopsis and tomato has not only revealed new mechanical insights into JA signaling but also reinforced the notion that signal-mediated degradation of repressors is a common theme used in plant hormone signaling. The JAZ family contains at least 12 members in Arabidopsis (Vanholme et al., 2007). So far, the involvement of at least three (JAZ1, JAI3/JAZ3, and JAS1.3/JAZ10.3) with JA signaling has been demonstrated. Many members of this gene family also show JA, wound, and herbivore inducibility (Vanholme et al., 2007; Chung et al., 2008), although currently their roles in JA signaling are not clear. It is also possible that JAZ repressors may have additional roles in JA signaling. Publicly available expression data show that a number of JAZ genes, including JAI3/JAZ3, are strongly repressed by SA, indicating their possible involvement in SA-JA cross talk. The discovery of JAZ repressors has also led to the proposal that the complexes between SCFCOI1 and different JAZ proteins might be the sites of reception of different JA signals (Parry and Estelle, 2006; Chini et al., 2007; Farmer, 2007). Although this seems to be a plausible proposal, particularly in light of SCFTIR being an auxin receptor, the biochemical evidence for SCFCOI1 or SCFCOI-JAZ complexes being JA receptors is still missing. One of the criteria for a hormone receptor is reversible and high affinity binding to hormone or its derivatives. At the time of writing this article, no such ligand-receptor relationships between SCFCOI1-JAZ complexes and any JA signal have been demonstrated. Given the redundancy of receptors for other plant hormones, it would not be surprising that multiple JA receptors exist in plants. Indeed, not all JA responses are SCFCOI1 dependent (Devoto et al., 2005), suggesting that SCFCOI1 either is not a JA receptor or is functionally redundant. Although at least six SCFCOI1 homologs are found in the Arabidopsis genome, their possible function(s) in JA or other physiological processes has not yet been characterized. An intriguing question is whether the commonalities identified between JAs and prostaglandins can be extended into their perceptions. After synthesis, prostaglandins are transported out of cells and bind to plasma membrane-located, G-protein-coupled receptors (Hata and Breyer, 2004). In Arabidopsis, about 25 putative membrane-located, G-protein-coupled receptors have so far been identified (Grill and Christmann, 2007). The ligands for most, if not all, of these putative receptors are unknown. It is becoming evident that signaling cascades regulated by protein phosphorylation/dephosphorylation have roles in regulating JA signaling, although JA signaling components phosphorylated/dephosphorylated by these pathways are mostly unknown. Despite observations of extensive interactions between JA and other hormonal signaling pathways, our knowledge on the molecular mechanisms involved in these interactions is also still rudimentary. Nevertheless, this complex interaction among signaling networks is a testament to the plant's ability to integrate diverse signals from multiple sources so expediently that a finely tuned output can be produced and thereby provide adaptation to its environment. We expect that the elucidation of the intricate interactions between JA and other signaling pathways will continue to be a fertile area for future research. ACKNOWLEDGMENTS Owing to space limitations, not all relevant work on this topic could be cited. We thank Bruno Dombrecht, Louise Thatcher, and Brendan Kidd for useful discussions, Louise Thatcher and Brendan Kidd for critical manuscript reading, and two anonymous reviewers for useful comments. LITERATURE CITED Adie BA, Perez-Perez J, Perez-Perez MM, Godoy M, Sanchez-Serrano JJ, Schmelz EA, Solano R ( 2007 ) ABA is an essential signal for plant resistance to pathogens affecting JA biosynthesis and the activation of defenses in Arabidopsis. Plant Cell 19 : 1665 – 1681 Crossref Search ADS PubMed Anderson JP, Badruzsaufari E, Schenk PM, Manners JM, Desmond OJ, Ehlert C, Maclean DJ, Ebert PR, Kazan K ( 2004 ) Antagonistic interaction between abscisic acid and JA-ethylene signaling pathways modulates defense gene expression and disease resistance in Arabidopsis. Plant Cell 16 : 3460 – 3479 Crossref Search ADS PubMed Andreasson E, Jenkins T, Brodersen P, Thorgrimsen S, Petersen NH, Zhu S, Qiu JL, Micheelsen P, Rocher A, Petersen M, et al ( 2005 ) The MAP kinase substrate MKS1 is a regulator of plant defense responses. EMBO J 24 : 2579 – 2589 Crossref Search ADS PubMed Bodenhausen N, Reymond P ( 2007 ) Signaling pathways controlling induced resistance to insect herbivores in Arabidopsis. Mol Plant Microbe Interact 20 : 1406 – 1420 Crossref Search ADS PubMed Bonaventure G, Gfeller A, Proebsting WM, Hortensteiner S, Chetelat A, Martinoia E, Farmer EE ( 2007 ) A gain-of-function allele of TPC1 activates oxylipin biogenesis after leaf wounding in Arabidopsis. Plant J 49 : 889 – 898 Crossref Search ADS PubMed Boter M, Ruiz-Rivero O, Abdeen A, Prat S ( 2004 ) Conserved MYC transcription factors play a key role in jasmonate signaling both in tomato and Arabidopsis. Genes Dev 18 : 1577 – 1591 Crossref Search ADS PubMed Broekaert WF, Delauré SL, De Bolle MF, Cammue BP ( 2006 ) The role of ethylene in host-pathogen interactions. Annu Rev Phytopathol 44 : 393 – 416 Crossref Search ADS PubMed Browse J ( 2005 ) Jasmonate: an oxylipin signal with many roles in plants. Vitam Horm 72 : 431 – 456 Crossref Search ADS PubMed Chini A, Fonseca S, Fernandez G, Adie B, Chico JM, Lorenzo O, Garcia-Casado G, Lopez-Vidriero I, Lozano FM, Ponce MR, et al ( 2007 ) The JAZ family of repressors is the missing link in jasmonate signaling. Nature 448 : 666 – 671 Crossref Search ADS PubMed Chung HS, Koo AJK, Gao X, Jayanty S, Thines B, Jones AD, Howe GA ( 2008 ) Regulation and function of Arabidopsis JASMONATE ZIM-domain genes in response to wounding and herbivory. Plant Physiol 146 : 952 – 964 Crossref Search ADS PubMed De Vos M, Van Oosten VR, Van Poecke RM, Van Pelt JA, Pozo MJ, Mueller MJ, Buchala AJ, Metraux JP, Van Loon LC, Dicke M, et al ( 2005 ) Signal signature and transcriptome changes of Arabidopsis during pathogen and insect attack. Mol Plant Microbe Interact 18 : 923 – 937 Crossref Search ADS PubMed Devoto A, Ellis C, Magusin A, Chang HS, Chilcott C, Zhu T, Turner JG ( 2005 ) Expression profiling reveals COI1 to be a key regulator of genes involved in wound- and methyl JA-induced secondary metabolism, defence, and hormone interactions. Plant Mol Biol 58 : 497 – 513 Crossref Search ADS PubMed Dombrecht B, Xue GP, Sprague SJ, Kirkegaard JA, Ross JJ, Reid JB, Fitt GP, Sewelam N, Schenk PM, Manners JM, et al ( 2007 ) MYC2 differentially modulates diverse jasmonate-dependent functions in Arabidopsis. Plant Cell 19 : 2225 – 2245 Crossref Search ADS PubMed Ellis C, Karafyllidis I, Wasternack C, Turner JG ( 2002 ) The Arabidopsis mutant cev1 links cell wall signaling to jasmonate and ethylene responses. Plant Cell 14 : 1557 – 1566 Crossref Search ADS PubMed Farmer EE ( 2007 ) Jasmonate perception machines. Nature 448 : 659 – 660 Crossref Search ADS PubMed Feng S, Ma L, Wang X, Xie D, Dinesh-Kumar SP, Wei N, Deng XW ( 2003 ) The COP9 signalosome interacts physically with SCF COI1 and modulates jasmonate responses. Plant Cell 15 : 1083 – 1094 Crossref Search ADS PubMed Feys B, Benedetti CE, Penfold CN, Turner JG ( 1994 ) Arabidopsis mutants selected for resistance to the phytotoxin coronatine are male sterile, insensitive to methyl JA, and resistant to a bacterial pathogen. Plant Cell 6 : 751 – 759 Crossref Search ADS PubMed Gray WM, Muskett PR, Chuang HW, Parker JE ( 2003 ) Arabidopsis SGT1b is required for SCF(TIR1)-mediated auxin response. Plant Cell 15 : 1310 – 1319 Crossref Search ADS PubMed Grill E, Christmann A ( 2007 ) Botany. A plant receptor with a big family. Science 315 : 1676 – 1677 Crossref Search ADS PubMed Hata AN, Breyer RM ( 2004 ) Pharmacology and signaling of prostaglandin receptors: multiple roles in inflammation and immune modulation. Pharmacol Ther 103 : 147 – 166 Crossref Search ADS PubMed Katou S, Yoshioka H, Kawakita K, Rowland O, Jones JD, Mori H, Doke N ( 2005 ) Involvement of PPS3 phosphorylated by elicitor-responsive mitogen-activated protein kinases in the regulation of plant cell death. Plant Physiol 139 : 1914 – 1926 Crossref Search ADS PubMed Laurie-Berry N, Joardar V, Street IH, Kunkel BN ( 2006 ) The Arabidopsis thaliana JASMONATE INSENSITIVE 1 gene is required for suppression of salicylic acid-dependent defenses during infection by Pseudomonas syringae. Mol Plant Microbe Interact 19 : 789 – 800 Crossref Search ADS PubMed Li J, Brader G, Palva ET ( 2004 a) The WRKY70 transcription factor: a node of convergence for jasmonate-mediated and salicylate-mediated signals in plant defense. Plant Cell 16 : 319 – 331 Crossref Search ADS PubMed Li L, Zhao Y, McCaig BC, Wingerd BA, Wang J, Whalon ME, Pichersky E, Howe GA ( 2004 b) The tomato homolog of CORONATINE-INSENSITIVE1 is required for the maternal control of seed maturation, jasmonate-signaled defense responses, and glandular trichome development. Plant Cell 16 : 126 – 143 Crossref Search ADS PubMed Lorenzo O, Chico JM, Sánchez-Serrano JJ, Solano R ( 2004 ) JASMONATE-INSENSITIVE1 encodes a MYC transcription factor essential to discriminate between different jasmonate-regulated defense responses in Arabidopsis. Plant Cell 16 : 1938 – 1950 Crossref Search ADS PubMed Lorenzo O, Piqueras R, Sanchez-Serrano JJ, Solano R ( 2003 ) ETHYLENE RESPONSE FACTOR1 integrates signals from ethylene and jasmonate pathways in plant defense. Plant Cell 15 : 165 – 178 Crossref Search ADS PubMed Mandaokar A, Thines B, Shin B, Lange BM, Choi G, Koo YJ, Yoo YJ, Choi YD, Choi G, Browse J ( 2006 ) Transcriptional regulators of stamen development in Arabidopsis identified by transcriptional profiling. Plant J 46 : 984 – 1008 Crossref Search ADS PubMed Mao P, Duan M, Wei C, Li Y ( 2007 ) WRKY62 transcription factor acts downstream of cytosolic NPR1 and negatively regulates jasmonate-responsive gene expression. Plant Cell Physiol 48 : 833 – 842 Crossref Search ADS PubMed Miao Y, Zentgraf U ( 2007 ) The antagonist function of Arabidopsis WRKY53 and ESR/ESP in leaf senescence is modulated by the jasmonic and salicylic acid equilibrium. Plant Cell 19 : 819 – 830 Crossref Search ADS PubMed Munemasa S, Oda K, Watanabe-Sugimoto M, Nakamura Y, Shimoishi Y, Murata Y ( 2007 ) The coronatine-insensitive 1 mutation reveals the hormonal signaling interaction between abscisic acid and methyl jasmonate in Arabidopsis guard cells. Specific impairment of ion channel activation and second messenger production. Plant Physiol 143 : 1398 – 1407 Crossref Search ADS PubMed Mur LA, Kenton P, Atzorn R, Miersch O, Wasternack C ( 2006 ) The outcomes of concentration-specific interactions between salicylate and jasmonate signaling include synergy, antagonism, and oxidative stress leading to cell death. Plant Physiol 140 : 249 – 262 Crossref Search ADS PubMed Nagpal P, Ellis CM, Weber H, Ploense SE, Barkawi LS, Guilfoyle TJ, Hagen G, Alonso JM, Cohen JD, Farmer EE, et al ( 2005 ) Auxin response factors ARF6 and ARF8 promote jasmonic acid production and flower maturation. Development 132 : 4107 – 4118 Crossref Search ADS PubMed Ndamukong I, Abdallat AA, Thurow C, Fode B, Zander M, Weigel R, Gatz C ( 2007 ) SA-inducible Arabidopsis glutaredoxin interacts with TGA factors and suppresses jasmonate-responsive PDF1.2 transcription. Plant J 50 : 128 – 139 Crossref Search ADS PubMed Overmyer K, Brosché M, Kangasjärvi J ( 2003 ) Reactive oxygen species and hormonal control of cell death. Trends Plant Sci 8 : 335 – 342 Crossref Search ADS PubMed Quint M, Ito H, Zhang W, Gray WM ( 2005 ) Characterization of a novel temperature-sensitive allele of the CUL1/AXR6 subunit of SCF ubiquitin-ligases. Plant J 43 : 371 – 383 Crossref Search ADS PubMed Parry G, Estelle M ( 2006 ) Auxin receptors: a new role for F-box proteins. Curr Opin Cell Biol 18 : 152 – 156 Crossref Search ADS PubMed Paschold A, Halitschke R, Baldwin IT ( 2007 ) Co(i)-ordinating defenses: NaCOI1 mediates herbivore- induced resistance in Nicotiana attenuata and reveals the role of herbivore movement in avoiding defenses. Plant J 51 : 79 – 91 Crossref Search ADS PubMed Penninckx IA, Thomma BP, Buchala A, Métraux JP, Broekaert WF ( 1998 ) Concomitant activation of jasmonate and ethylene response pathways is required for induction of a plant defensin gene in Arabidopsis. Plant Cell 10 : 2103 – 2113 Crossref Search ADS PubMed Petersen M, Brodersen P, Naested H, Andreasson E, Lindhart U, Johansen B, Nielsen HB, Lacy M, Austin MJ, Parker JE, et al ( 2000 ) Arabidopsis map kinase 4 negatively regulates systemic acquired resistance. Cell 103 : 1111 – 1120 Crossref Search ADS PubMed Rayapuram C, Baldwin IT ( 2007 ) Increased SA in NPR1-silenced plants antagonizes jasmonate and jasmonate-dependent direct and indirect defenses in herbivore-attacked Nicotiana attenuata in nature. Plant J 52 : 700 – 715 Crossref Search ADS PubMed Ren C, Pan J, Peng W, Genschik P, Hobbie L, Hellmann H, Estelle M, Gao B, Peng J, Sun C, et al ( 2005 ) Point mutations in Arabidopsis Cullin1 reveal its essential role in jasmonate response. Plant J 42 : 514 – 524 Crossref Search ADS PubMed Schwechheimer C, Serino G, Deng XW ( 2002 ) Multiple ubiquitin ligase-mediated processes require COP9 signalosome and AXR1 function. Plant Cell 14 : 2553 – 2563 Crossref Search ADS PubMed Schweighofer A, Kazanaviciute V, Scheikl E, Teige M, Doczi R, Hirt H, Schwanninger M, Kant M, Schuurink R, Mauch F, et al ( 2007 ) The PP2C-type phosphatase AP2C1, which negatively regulates MPK4 and MPK6, modulates innate immunity, jasmonic acid, and ethylene levels in Arabidopsis. Plant Cell 19 : 2213 – 2224 Crossref Search ADS PubMed Shikata M, Takemura M, Yokota A, Kohchi T ( 2003 ) Arabidopsis ZIM, a plant-specific GATA factor, can function as a transcriptional activator. Biosci Biotechnol Biochem 67 : 2495 – 2497 Crossref Search ADS PubMed Spoel SH, Johnson JS, Dong X ( 2007 ) Regulation of tradeoffs between plant defenses against pathogens with different lifestyles. Proc Natl Acad Sci USA 104 : 18842 – 18847 Crossref Search ADS PubMed Spoel SH, Koornneef A, Claessens SM, Korzelius JP, Van Pelt JA, Mueller MJ, Buchala AJ, Metraux JP, Brown R, Kazan K, et al ( 2003 ) NPR1 modulates cross-talk between salicylate- and jasmonate-dependent defense pathways through a novel function in the cytosol. Plant Cell 15 : 760 – 770 Crossref Search ADS PubMed Stanley D ( 2006 ) Prostaglandins and other eicosanoids in insects: biological significance. Annu Rev Entomol 51 : 25 – 44 Crossref Search ADS PubMed Staswick PE, Tiryaki I ( 2004 ) The oxylipin signal jasmonic acid is activated by an enzyme that conjugates it to isoleucine in Arabidopsis. Plant Cell 16 : 2117 – 2127 Crossref Search ADS PubMed Stone SL, Callis J ( 2007 ) Ubiquitin ligases mediate growth and development by promoting protein death. Curr Opin Plant Biol 10 : 624 – 632 Crossref Search ADS PubMed Takahashi F, Yoshida R, Ichimura K, Mizoguchi T, Seo S, Yonezawa M, Maruyama K, Yamaguchi-Shinozaki K, Shinozaki K ( 2007 ) The mitogen-activated protein kinase cascade MKK3-MPK6 is an important part of the jasmonate signal transduction pathway in Arabidopsis. Plant Cell 19 : 805 – 818 Crossref Search ADS PubMed Taki N, Sasaki-Sekimoto Y, Obayashi T, Kikuta A, Kobayashi K, Ainai T, Yagi K, Sakurai N, Suzuki H, Masuda T, et al ( 2005 ) 12-Oxo-phytodienoic acid triggers expression of a distinct set of genes and plays a role in wound-induced gene expression in Arabidopsis. Plant Physiol 139 : 1268 – 1283 Crossref Search ADS PubMed Thines B, Katsir L, Melotto M, Niu Y, Mandaokar A, Liu G, Nomura K, He SY, Howe GA, Browse J ( 2007 ) JAZ repressor proteins are targets of the SCF(COI1) complex during jasmonate signaling. Nature 448 : 661 – 665 Crossref Search ADS PubMed Tiryaki I, Staswick PE ( 2002 ) An Arabidopsis mutant defective in jasmonate response is allelic to the auxin-signaling mutant axr1. Plant Physiol 130 : 887 – 894 Crossref Search ADS PubMed Vanholme B, Grunewald W, Bateman A, Kohchi T, Gheysen G ( 2007 ) The tify family previously known as ZIM. Trends Plant Sci 12 : 239 – 244 Crossref Search ADS PubMed Vick BA, Zimmerman DC ( 1984 ) Biosynthesis of jasmonic acid by several plant species. Plant Physiol 75 : 458 – 461 Crossref Search ADS PubMed Wang D, Amornsiripanitch N, Dong X ( 2006 ) A genomic approach to identify regulatory nodes in the transcriptional network of systemic acquired resistance in plants. PLoS Pathog 2 : e123 Crossref Search ADS PubMed Wang L, Allmann S, Wu J, Baldwin IT ( 2008 ) Comparisons of LIPOXYGENASE3- and JASMONATE-RESISTANT4/6-silenced plants reveal that jasmonic acid and jasmonic acid-amino acid conjugates play different roles in herbivore resistance of Nicotiana attenuata. Plant Physiol 146 : 904 – 915 Crossref Search ADS PubMed Wang Z, Dai L, Jiang Z, Peng W, Zhang L, Wang G, Xie D ( 2005 ) GmCOI1, a soybean F-box protein gene, shows ability to mediate jasmonate-regulated plant defense and fertility in Arabidopsis. Mol Plant Microbe Interact 18 : 1285 – 1295 Crossref Search ADS PubMed Wasternack C ( 2007 ) Jasmonates: an update on biosynthesis, signal transduction and action in plant stress response, growth and development. Ann Bot (Lond) 100 : 681 – 697 Crossref Search ADS Woodward AW, Bartel B ( 2005 ) Auxin: regulation, action, and interaction. Ann Bot (Lond) 95 : 707 – 735 Crossref Search ADS Wu J, Wang L, Baldwin IT ( 2008 ) Methyl jasmonate-elicited herbivore resistance: Does MeJA function as a signal without being hydrolyzed to JA? Planta (in press) Xie DX, Feys BF, James S, Nieto-Rostro M, Turner JG ( 1998 ) COI1: an Arabidopsis gene required for jasmonate-regulated defense and fertility. Science 280 : 1091 – 1094 Crossref Search ADS PubMed Yadav V, Mallappa C, Gangappa SN, Bhatia S, Chattopadhyay S ( 2005 ) A basic helix-loop-helix transcription factor in Arabidopsis, MYC2, acts as a repressor of blue light-mediated photomorphogenic growth. Plant Cell 17 : 1953 – 1966 Crossref Search ADS PubMed Yan Y, Stolz S, Chételat A, Reymond P, Pagni M, Dubugnon L, Farmer EE ( 2007 ) A downstream mediator in the growth repression limb of the jasmonate pathway. Plant Cell 19 : 2470 – 2483 Crossref Search ADS PubMed Zhai Q, Li CB, Zheng W, Wu X, Zhao J, Zhou G, Jiang H, Sun J, Lou Y, Li C ( 2007 ) Phytochrome chromophore deficiency leads to overproduction of jasmonic acid and elevated expression of jasmonate-responsive genes in Arabidopsis. Plant Cell Physiol 48 : 1061 – 1071 Crossref Search ADS PubMed Author notes * Corresponding author; e-mail [email protected]. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Kemal Kazan ([email protected]). www.plantphysiol.org/cgi/doi/10.1104/pp.107.115717 © 2008 American Society of Plant Biologists This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Covshoff, Sarah; Majeran, Wojciech; Liu, Peng; Kolkman, Judith M.; van Wijk, Klaas J.; Brutnell, Thomas P.

doi: 10.1104/pp.107.113423pmid: 18258693

Abstract During maize (Zea mays) C4 differentiation, mesophyll (M) and bundle sheath (BS) cells accumulate distinct sets of photosynthetic enzymes, with very low photosystem II (PSII) content in BS chloroplasts. Consequently, there is little linear electron transport in the BS and ATP is generated by cyclic electron flow. In contrast, M thylakoids are very similar to those of C3 plants and produce the ATP and NADPH that drive metabolic activities. Regulation of this differentiation process is poorly understood, but involves expression and coordination of nuclear and plastid genomes. Here, we identify a recessive allele of the maize high chlorophyll fluorescence (Hcf136) homolog that in Arabidopsis (Arabidopsis thaliana) functions as a PSII stability or assembly factor located in the thylakoid lumen. Proteome analysis of the thylakoids and electron microscopy reveal that Zmhcf136 lacks PSII complexes and grana thylakoids in M chloroplasts, consistent with the previously defined Arabidopsis function. Interestingly, hcf136 is also defective in processing the full-length psbB-psbT-psbH-petB-petD polycistron specifically in M chloroplasts. To determine whether the loss of PSII in M cells affects C4 differentiation, we performed cell-type-specific transcript analysis of hcf136 and wild-type seedlings. The results indicate that M and BS cells respond uniquely to the loss of PSII, with little overlap in gene expression changes between data sets. These results are discussed in the context of signals that may drive differential gene expression in C4 photosynthesis. In maize (Zea mays), photosynthetic activities are partitioned between two morphologically and biochemically distinct cell types, mesophyll (M) and bundle sheath (BS; Edwards and Walker, 1983). M and BS cells are organized as concentric files around the vasculature in a classical Kranz anatomy. Functionally, these two cell types cooperate in photosynthesis, carbon fixation (Edwards et al., 2001a; Majeran et al., 2005), nitrogen metabolism (Rathnam and Edwards, 1975, 1976; Harel et al., 1977; Becker et al., 1993), and sulfur assimilation (Burgener et al., 1998). Notably, M plastids contain grana thylakoids, perform linear electron transport, and photoreduce NADP+ (Andersen et al., 1972). In contrast, BS chloroplasts are agranal (Andersen et al., 1972; Kirchanski, 1975; Miller et al., 1977), PSII depleted (Schuster et al., 1985), and perform most of the reactions of the Calvin cycle (Chollet, 1973; Kagawa and Hatch, 1974). Partitioning of photosynthetic activities between M and BS cell types is mediated by cell-specific localization of multiple transcripts (Furumoto et al., 2000; Sawers et al., 2007) and proteins (Majeran et al., 2005). However, little is known about the transcriptional program regulating C4 differentiation. Previous studies have suggested that a small number of regulatory changes are sufficient to establish the C4 syndrome (Ku et al., 1996). To date, localization of a limited number of transcripts has been shown to be mediated by cis-regulatory elements (Langdale et al., 1991; Schaffner and Sheen, 1991, 1992; Sheen, 1991; Stockhaus et al., 1997). However, the discovery of a master switch that will explain the thousands of genes with cell-specific patterns of expression (Sawers et al., 2007) is unlikely (Edwards et al., 2001b). Rather, the accumulation of many of these transcripts may be mediated by changes that have resulted in novel cellular environments in the C4 leaf that continue to control gene expression through preexisting networks. Factors could include differential sugar concentrations, protein complexes, and gradients of small metabolites that influence M and BS cell identity. Another factor that may influence the differentiation process is redox poise. In the leaf blade, M cells contain both PSII and PSI activities and perform linear photosynthetic electron transport (PET). In contrast, BS cells lack detectable levels of functional PSII and are believed to be restricted to cyclic electron transport (Gregory et al., 1979; Ghirardi and Melis, 1983; Romanowska et al., 2006). As a result, proper functioning of M and BS cells is dependent on the intercellular transfer of photosynthetically derived reducing equivalents from M to BS cells. Specifically, NADPH generated during linear PET in M cells is exported to BS cells for Calvin cycle activity (Edwards and Walker, 1983). Thus, these differences in photochemistry lead to distinct redox profiles in M and BS cells. The characterization of mutants that are selectively disrupted in either M or BS cell photosynthetic differentiation may prove useful in understanding the networks that drive this process. For instance, bundle sheath defective2 (bsd2) seedlings do not accumulate Rubisco (Roth et al., 1996; Brutnell et al., 1999) and lack a functional Calvin cycle (Smith et al., 1998). Consequently, the linear PET chain is likely to be more reduced in mutant M cells than in wild type because it is lacking an electron sink. Conversely, M cell-defective mutants that lack PSII are unable to generate electron flow and likely result in overly oxidized linear PET chains. Additionally, both of these mutant classes will fail to accumulate soluble sugars due to the absence of photosynthesis. Thus, mutations that disrupt the cellular environments of M and BS cells may provide useful tools for probing the differentiation process. Several maize mutants have been reported with defects in PSII function, including high chlorophyll fluorescence3 (hcf3), hcf19G, and hcf19YG (Leto and Miles, 1980). However, the molecular lesions associated with these PSII-defective mutants have yet to be determined. In this study, we identify an Activator (Ac)-induced maize mutant that lacks PSII activity. Cloning and characterization of this gene indicates that it is a homolog of HCF136, which is necessary for PSII assembly or stability (Meurer et al., 1998; Plucken et al., 2002). In wild-type plants, ZmHcf136 transcript accumulation is predominantly confined to M cells, and proteomic analysis of hcf136 total leaf tissue shows that monomeric and dimeric PSII complexes do not accumulate. Interestingly, the plastid-encoded psbB-psbT-psbH-petB-petD polycistron is misprocessed in the mutant specifically in M cells. Microarray analysis reveals that M and BS cell transcript pools are altered by the hcf136 mutation. The loss of PSII leads to a disruption in spatial regulation of typically BS-enriched genes and an increase in the cellular specificity of typically M-enriched genes. Additionally, data from the protein and transcript profiles do not always correspond, suggesting that posttranscriptional/translational controls are also involved in C4 differentiation. RESULTS Ac-Tagged Zmhcf136 Is Seedling Lethal The Zmhcf136 mutant was first identified in sand bench screens of an Ac-mutagenized population as a recessive hcf seedling-lethal mutant (see “Materials and Methods”). DNA-blot analysis identified a 2.5-kb EcoRI fragment containing an Ac insertion that cosegregated with the mutant phenotype. Inverse PCR with primers designed to Ac (Kolkman et al., 2005) was used to amplify 265-bp of DNA flanking the Ac insertion. Initial BLAST searches revealed that this fragment has significant similarity to the Arabidopsis (Arabidopsis thaliana) gene HCF136, suggesting the Ac inserted into an exon of a maize Hcf136 homolog. The hcf136 mutant displays somatic instability consistent with an active transposable element insertion. In Arabidopsis, HCF136 is a lumenal protein that is specifically required for the assembly or stability of PSII (Meurer et al., 1998; Plucken et al., 2002). In maize, PSII accumulation is preferentially localized to mature M chloroplasts (Edwards and Walker, 1983; Schuster et al., 1985; Majeran et al., 2005). To identify full-length maize coding sequences for Hcf136, the 265 bp flanking the Ac was used to search available genomic and EST databases and a nearly full-length pseudomolecule of Hcf136 transcript was assembled. To confirm the cloning of Hcf136 and recover noncoding sequences associated with the Hcf136 gene, we exploited the somatic instability of an active Ac allele to selectively amplify sequences flanking the Ac insertion in ZmHcf136. By utilizing a genome-walking technique known as Ac casting (Singh et al., 2003), we were able to recover additional sequence upstream and downstream of the original Ac insertion site. PCR reactions performed using gene-specific and Ac end primers resulted in the amplification of 2,530 bp of genomic sequence flanking the Ac insertion, including 278 bp upstream of the start of translation (see “Materials and Methods”). Exon-intron boundaries were defined using reverse-transcription (RT)-PCR as described in “Materials and Methods” and a schematic of the gene is shown in Figure 1A Figure 1. Open in new tabDownload slide Sequence analysis of the ZmHcf136 homolog. A, The Ac element, shown as an arrowhead, is inserted in the sixth exon of ZmHcf136. Exons are represented by gray boxes and introns by solid lines. B, Protein alignment of HCF136 homologs from maize, sorghum, rice, Arabidopsis, G. theta, and Synechocystis sp. PCC 6803. Residues identical in at least three sequences are shaded black. Predicted mature end of ZmHCF136 is indicated by the black arrowhead. Figure 1. Open in new tabDownload slide Sequence analysis of the ZmHcf136 homolog. A, The Ac element, shown as an arrowhead, is inserted in the sixth exon of ZmHcf136. Exons are represented by gray boxes and introns by solid lines. B, Protein alignment of HCF136 homologs from maize, sorghum, rice, Arabidopsis, G. theta, and Synechocystis sp. PCC 6803. Residues identical in at least three sequences are shaded black. Predicted mature end of ZmHCF136 is indicated by the black arrowhead. . The Ac element is oriented in the 3′ to 5′ direction relative to the start of transcription of Hcf136 and is inserted in the sixth exon between bp 1,151 and 1,152 of the coding sequence. Rather than leading to a truncated protein, this orientation is predicted to produce a fusion hcf136-Ac transcript that is likely unstable and degraded. A ZmHcf136-specific probe was used to map the locus to the short arm of chromosome 1 (Bin 1.01) using the intermated B73 × Mo17 recombinant inbred mapping population (Lee et al., 2002). HCF136 Proteins Are Highly Conserved As shown in Figure 1B, HCF136 homologs are highly similar across monocots, dicots, algae, and cyanobacterial species. TargetP predicts that ZmHCF136 is chloroplast localized with a 25-amino-acid transit peptide (Emanuelsson et al., 2000). When the predicted N-terminal transit peptide is excluded from sequence comparisons, AtHCF136 and ZmHCF136 share 87% identity or 96% similarity across their entire length. Studies in Arabidopsis have suggested that HCF136 interacts directly with the PSII reaction core proteins D2 and Cyt b 559 at the lumenal side of the thylakoid membrane (Plucken et al., 2002). Sorghum (Sorghum bicolor) and maize HCF136 proteins are 96% identical, including the transit peptide. HCF136 from both the alga Guillardia theta and the cyanobacterium Synechocystis sp. PCC 6803 are 43% identical to maize. This high degree of sequence similarity between divergent species suggests a conserved and ancestral function for the HCF136 protein. Loss of HCF136 Affects PSII Function and Grana Formation Using in vivo fluorescence induction curves, we examined the functional status of PSII in hcf136 leaves (see “Materials and Methods”). Mutant seedlings displayed hcf, but no variable fluorescence, consistent with the absence of PSII activity (hcf136 F v/F m = 0; wild type = 0.8). Light microscopy of cross sections of wild-type and mutant leaf tissue revealed smaller chloroplasts in both M and BS cells of hcf136 (Supplemental Fig. S1B). Plastid ultrastructure was examined in greater detail using transmission electron microscopy (Fig. 2 Figure 2. Open in new tabDownload slide Plastid ultrastructure in second leaf tip of 10-d-old hcf136 mutant and wild-type siblings. A to D, Transmission electron micrographs from seedlings grown under 80 μmol s−1 m−2 light in 16-h days at 50% humidity. A to D, M plastids of wild type (A) and hcf136 mutants (B); bundle sheath plastids of wild type (C) and hcf136 mutants (D). Figure 2. Open in new tabDownload slide Plastid ultrastructure in second leaf tip of 10-d-old hcf136 mutant and wild-type siblings. A to D, Transmission electron micrographs from seedlings grown under 80 μmol s−1 m−2 light in 16-h days at 50% humidity. A to D, M plastids of wild type (A) and hcf136 mutants (B); bundle sheath plastids of wild type (C) and hcf136 mutants (D). ). In the hcf136 mutant, grana are absent or display aberrant ultrastructure in M plastids (Fig. 2B). In contrast, plastid ultrastructure in hcf136 BS cells appears normal (Fig. 2D). These results are consistent with the prediction that the primary defect in Zmhcf136 is a disruption in PSII assembly and accumulation. ZmHcf136 Transcripts Accumulate Preferentially in M Cells To determine whether ZmHcf136 transcript accumulation is M cell specific, RNA-blot analysis of several cell types and tissues was performed using an Hcf136-specific probe (Fig. 3 Figure 3. Open in new tabDownload slide RNA-blot analysis of Hcf136 transcript accumulation. Approximately 5 μg of total RNA was fractionated on 1.5% agarose gels and transferred to nitrocellulose membrane. Separate filters were hybridized to radiolabeled fragments of Hcf136 (A) and Pepc and Rbcs (B). Ethidium bromide-stained 18S rRNA (Etbr) is shown as a loading control. Figure 3. Open in new tabDownload slide RNA-blot analysis of Hcf136 transcript accumulation. Approximately 5 μg of total RNA was fractionated on 1.5% agarose gels and transferred to nitrocellulose membrane. Separate filters were hybridized to radiolabeled fragments of Hcf136 (A) and Pepc and Rbcs (B). Ethidium bromide-stained 18S rRNA (Etbr) is shown as a loading control. ). RNA was isolated from light-grown wild-type M cell protoplasts, BS strands, total leaf tissue, total hcf136 mutant leaf tissue, and total leaf tissue from wild-type dark-grown plants. To control for changes in gene expression due to M cell protoplast isolation, RNA was also extracted from total wild-type light-grown tissue that was stress-treated by a mock protoplast digestion (see “Materials and Methods”). The RNA samples were hybridized with probes derived from the cell-specific markers Pepc and Rbcs, which accumulate preferentially in M and BS cell types, respectively (Sheen and Bogorad, 1987; Langdale et al., 1988b). As shown in Figure 3B, there is little cross-contamination in our cell preparations, and Hcf136 transcripts clearly accumulate to higher levels in M relative to BS cells (Fig. 3A). Additionally, Hcf136 transcript accumulates in the dark, but is more abundant in light-grown tissues. The psbB-psbH-psbT-petB-petD Polycistron Is Misprocessed in M Cells When analyzing the mutant for changes in PSII transcript regulation, we unexpectedly observed a defect in the processing/stability of the psbB-psbH-psbT-petB-petD polycistron (Fig. 4A Figure 4. Open in new tabDownload slide psbB-psbT-psbH-petB-petD processing in hcf136. A, Schematic shows polycistronic organization to scale with probe locations marked above the gene by a thick black bar. Genes that are encoded on the plus strand are labeled above their corresponding box, and the minus strand gene is labeled below. Exons and introns of petB and petD are also labeled below their corresponding gene. Numbered lines represent bands in the blots shown in B and C. B, RNA from total leaf tissue of WT and hcf136 was hybridized to fragments of psbB, psbH/N, and petD. C, RNA from separated M and BS cells from wild type and hcf136 was hybridized to psbH/N. Processed fragments shown in A and B are marked by numbered arrows and an unidentified band is marked by an asterisk. Figure 4. Open in new tabDownload slide psbB-psbT-psbH-petB-petD processing in hcf136. A, Schematic shows polycistronic organization to scale with probe locations marked above the gene by a thick black bar. Genes that are encoded on the plus strand are labeled above their corresponding box, and the minus strand gene is labeled below. Exons and introns of petB and petD are also labeled below their corresponding gene. Numbered lines represent bands in the blots shown in B and C. B, RNA from total leaf tissue of WT and hcf136 was hybridized to fragments of psbB, psbH/N, and petD. C, RNA from separated M and BS cells from wild type and hcf136 was hybridized to psbH/N. Processed fragments shown in A and B are marked by numbered arrows and an unidentified band is marked by an asterisk. ). Components of PSII (psbB, psbH, psbN, and psbT) and Cyt b 6 f (petB and petD) are encoded by this polycistron, which is processed into many overlapping RNAs that are capable of directing protein synthesis (Barkan, 1988). As seen in Figure 4B, band 3 accumulates to much lower levels in the mutant leaf RNA, indicating a processing defect of the petB intron in hcf136. In addition, a fourth band (shown by asterisk) aberrantly accumulates in mutant M leaf tissue (Fig. 4C). In contrast, the polycistron is processed similarly in mutant and wild-type BS cells. No processing defects were detected in hcf136 mutants for other polycistronic transcripts examined, including those encoding the core of PSII (psbC and psbD), and other members of the group II intron family (atpF/H and psaAB; Rock et al., 1987; Cushman et al., 1988; Kuck, 1989; Kim and Hollingsworth, 1993). These data are shown in Supplemental Figure S2. Because a processing defect was only detected in the psbB-psbH-psbT-petB-petD polycistron, these findings suggest that a disruption in HCF136 function specifically affects psbB-psbH-psbT-petB-petD processing in M cells. Zmhcf136 Lacks HCF136 and PSII Proteins To examine the accumulation and localization of ZmHCF136, the profiles of wild-type and hcf136 stroma-enriched and thylakoid peripheral and lumenal proteins were compared by two-dimensional (2D) gel electrophoresis with immobilized pH gradient (IPG) strips in the first dimension and SDS-PAGE in the second dimension. A single spot was identified in Sypro Ruby-stained 2D gels as a spot that is present in plastid protein extracts of wild-type plants, but absent in hcf136 mutants (Supplemental Fig. S3). This spot was excised, trypsin digested, and analyzed by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) and identified as HCF136, confirming the identity of the Ac-tagged gene (TC296744; http://ppdb.tc.cornell.edu; Supplemental Table S1. To identify plastid-localized proteins that differentially accumulate in the hcf136 mutant, thylakoid membranes were isolated, subfractionated into membrane and soluble components, and separated by one-dimensional (1D) SDS-PAGE (Fig. 5 Figure 5. Open in new tabDownload slide Electrophoretic pattern of wild-type (WT in the image) and hcf136 proteins obtained by SDS-PAGE (tricine 12%) and stained with Sypro Ruby fluorescent dye. Total thylakoid membrane vesicles were isolated on Percoll cushions and then treated with a Dounce homogenizer followed by differential ultracentrifugation to collect membrane and soluble fractions. Bands displaying strong differential accumulation were excised and proteins digested and analyzed by MALDI-TOF MS PMF. Identified proteins are: (1) FtsH1 (TC292243); (2) CP47 (NP_043049.1); (3) OEC33-like (TC279249); (4) PSII-D2 (NP_043009.1); (5) LHCII-1 (TC286614); (6) PPDK (TC286559); (7) cpHsp70 (TC293193), and (8) RBCS (TC286731). These proteins are labeled with numbered arrows. Protein markers in kilodaltons are indicated on the right. Figure 5. Open in new tabDownload slide Electrophoretic pattern of wild-type (WT in the image) and hcf136 proteins obtained by SDS-PAGE (tricine 12%) and stained with Sypro Ruby fluorescent dye. Total thylakoid membrane vesicles were isolated on Percoll cushions and then treated with a Dounce homogenizer followed by differential ultracentrifugation to collect membrane and soluble fractions. Bands displaying strong differential accumulation were excised and proteins digested and analyzed by MALDI-TOF MS PMF. Identified proteins are: (1) FtsH1 (TC292243); (2) CP47 (NP_043049.1); (3) OEC33-like (TC279249); (4) PSII-D2 (NP_043009.1); (5) LHCII-1 (TC286614); (6) PPDK (TC286559); (7) cpHsp70 (TC293193), and (8) RBCS (TC286731). These proteins are labeled with numbered arrows. Protein markers in kilodaltons are indicated on the right. ). Strong differential accumulation was observed for a number of bands in the membrane fractions, but not in the soluble fraction. Eight major bands showing differential accumulation were identified by peptide mass finger printing (PMF) using a matrix-assisted laser-desorption ionization-time-of-flight (MALDI-TOF) mass spectrometer (Supplemental Table S2) as FtsH1 (band 1, TC292243), CP47 (band 2, NP_043049.1), OEC33-like (band 3, TC279249), PSII-D2 (band 4, NP_043009.1), light-harvesting complex (LHCII-1; band 5, TC286614), pyruvate, orthophosphate dikinase (PPDK; band 6, TC286559), cpHSP70 (band 7, TC293193), and small subunit of Rubisco (RBCS; band 8, TC286731). These identifications likely represent the most abundant protein in the band. In hcf136, FtsH1 metalloprotease accumulation is reduced, and the CP47, OEC33-like, and D2 subunits of PSII are absent or dramatically reduced. A slight reduction in the accumulation of the major LHCII-1 band is observed likely due to the absence of accumulation of its interacting PSII complex. PPDK, cpHSP70, and RBCS proteins have increased accumulation in the hcf136 membrane fraction, but no differential accumulation in the soluble fraction, suggesting that these proteins interact more strongly with thylakoid membranes in plastids that lack PSII or grana. It is unlikely that a treatment effect from thylakoid preparation accounts for this result because other abundant chloroplast-soluble components are not found in the membrane fraction. To improve resolution of the thylakoid proteome analysis and to determine the assembly state of the major photosynthetic complexes in wild type and hcf136, thylakoids were solubilized with the nonionic detergent n-dodecyl β-d-maltoside and analyzed by Blue Native (BN) gel electrophoresis followed by SDS-PAGE (2D BN SDS-PAGE; Fig. 6 Figure 6. Open in new tabDownload slide BN gel electrophoresis of thylakoid membranes from wild type and hcf136 mutants. Equivalent amounts of wild type and hcf136 thylakoid membranes (700 μg of protein) were solubilized with n-dodecyl β-d-maltoside and separated on native gels in the first dimension. Gel strips were reduced and alkylated in a solubilization buffer and separated by second dimension SDS-PAGE (tricine 12%). Proteins were identified by in-gel digestion, followed by MALDI-TOF MS PMF. Protein complexes were identified as: (I) PSI and PSII “supercomplexes”; (II) PSI and PSII dimers; (III) partially assembled PSI; (IV) PSII, ATP-synthase, and Cyt b 6 f; (V) partially assembled PSII; and (VI and VII) LHCII. The hcf136 mutant has additional complexes: (Vb–VIb) LHCI-4 and (VIIb) low molecular weight form of the LHCII-1 complex. In the wild-type gel, black boxes indicate the different forms of PSII present in wild type but absent in hcf136. In the hcf136 gel, black boxes indicate changes in LHCI accumulation and in the assembly state of LHCII. Spot identities are as follows (see also Supplemental Table S3); (1) LHCI-3 (TC286618); (2) PsaD-2 PSI subunit II (TC293201, TC293200); (3) PsaD-2 PSI subunit II (TC293201, TC293200); (4) PsaF PSI subunit III (TC299208, TC299217, TC299206); (5) PsaE-2 PSI subunit IV (TC279867); (6) unknown; (7) unknown; (8) CF1β (atpB, TC279356) and CF1α (atpA, TC303520); (9) CP47 (psbB, TC283413); (10) CF1γ (AtpC, TC287102); (11) D1 (psbA, TC290677); (12) Cyt b 6 f Rieske iron-sulfur (TC286511); (13) unknown; (14) LHCII-1 (TC299123); (15) LHCII-1 (TC286602); (16) LHCII-1 (TC299123); (17) LHCII-3 (TC286603); (18) LHCI-4 (TC279557). Protein marker positions in kilodaltons are indicated between the two gel images. [See online article for color version of this figure.] Figure 6. Open in new tabDownload slide BN gel electrophoresis of thylakoid membranes from wild type and hcf136 mutants. Equivalent amounts of wild type and hcf136 thylakoid membranes (700 μg of protein) were solubilized with n-dodecyl β-d-maltoside and separated on native gels in the first dimension. Gel strips were reduced and alkylated in a solubilization buffer and separated by second dimension SDS-PAGE (tricine 12%). Proteins were identified by in-gel digestion, followed by MALDI-TOF MS PMF. Protein complexes were identified as: (I) PSI and PSII “supercomplexes”; (II) PSI and PSII dimers; (III) partially assembled PSI; (IV) PSII, ATP-synthase, and Cyt b 6 f; (V) partially assembled PSII; and (VI and VII) LHCII. The hcf136 mutant has additional complexes: (Vb–VIb) LHCI-4 and (VIIb) low molecular weight form of the LHCII-1 complex. In the wild-type gel, black boxes indicate the different forms of PSII present in wild type but absent in hcf136. In the hcf136 gel, black boxes indicate changes in LHCI accumulation and in the assembly state of LHCII. Spot identities are as follows (see also Supplemental Table S3); (1) LHCI-3 (TC286618); (2) PsaD-2 PSI subunit II (TC293201, TC293200); (3) PsaD-2 PSI subunit II (TC293201, TC293200); (4) PsaF PSI subunit III (TC299208, TC299217, TC299206); (5) PsaE-2 PSI subunit IV (TC279867); (6) unknown; (7) unknown; (8) CF1β (atpB, TC279356) and CF1α (atpA, TC303520); (9) CP47 (psbB, TC283413); (10) CF1γ (AtpC, TC287102); (11) D1 (psbA, TC290677); (12) Cyt b 6 f Rieske iron-sulfur (TC286511); (13) unknown; (14) LHCII-1 (TC299123); (15) LHCII-1 (TC286602); (16) LHCII-1 (TC299123); (17) LHCII-3 (TC286603); (18) LHCI-4 (TC279557). Protein marker positions in kilodaltons are indicated between the two gel images. [See online article for color version of this figure.] ). Major photosynthetic complexes in wild-type and mutant tissues were identified by PMF analysis (Supplemental Table S3). In hcf136, PSII reaction center and core subunits are absent from thylakoid membranes, but there is no dramatic effect on the accumulation of PSI. The hcf136 mutant also has a different oligomeric assembly state of the major LHCII, which is present in a monomeric form rather than the trimeric form typical of wild-type thylakoids (Dekker and Boekema, 2005). This may be a consequence of the loss of its interaction partner, PSII core complex. Alternatively, the absence of membrane stacking may lead to increased accessibility to detergent and destabilization of LHC oligomers during membrane preparation. Other protein complexes, including ATP synthase and Cyt b 6 f, accumulate to similar levels in both wild-type and mutant plastids. Changes in Protein Accumulation Do Not Correlate with RNA Levels To determine the extent of transcriptional control on the observed changes in protein accumulation, the relative abundance of several transcripts was measured by quantitative real-time PCR (qPCR) in M and BS cell preparations (see “Materials and Methods”). Relative transcript levels were assayed using primer pairs specific to the following nuclear-encoded genes (Supplemental Table S4): Rbcs (TC286731), Ppdk (TC286559), FtsH1 (TC292243), cpHsp70 (TC293193), PsbO OEC33 (TC279249), Lhcb1 (TC286614), Lhca3 (TC286618), PsaD (TC293201, TC293200), PsaE (TC279867), PsaF (TC299208, TC299217, TC299206), and AtpC (TC287102). The plastid-encoded genes psbB (NP_043049), psbD (NP_043009), and psbE (TC279867) were also assayed (see Supplemental Table S2). A comparison of transcript levels in M and BS cells of hcf136 and wild type is shown in Figure 7 Figure 7. Open in new tabDownload slide Transcript abundance in M and BS cells of the hcf136 mutant relative to wild type. Fold-change values greater than one correspond to greater transcript abundance in hcf136 tissues relative to wild type. Means of three biological replicates and two technical replicates of qPCR are shown with se estimates. A list of primer sequences is given in Supplemental Table S4. Figure 7. Open in new tabDownload slide Transcript abundance in M and BS cells of the hcf136 mutant relative to wild type. Fold-change values greater than one correspond to greater transcript abundance in hcf136 tissues relative to wild type. Means of three biological replicates and two technical replicates of qPCR are shown with se estimates. A list of primer sequences is given in Supplemental Table S4. . A value >1 indicates transcripts were more abundant in the mutant than in the wild type, and a value <1 indicates transcript abundance was greater in the wild type. These data show that the observed disruption in plastid protein accumulation does not correspond to a general reduction in corresponding transcript accumulation. Examination of the qPCR data shown in Figure 7 indicated that, in general, transcripts accumulated to higher levels in mutant M cells and lower levels in BS. This finding suggests that disrupting PSII activity can enhance the differential expression of M-enriched transcripts (e.g. psbB; Kubicki et al., 1994), whereas decreasing the differential expression of BS-enriched transcripts (e.g. rbcS; Sheen and Bogorad, 1986; Langdale et al., 1988a). Loss of PSII Leads to Changes in C4 Spatial Regulation To further explore the disruption of PSII activity on gene expression, transcript profiles from separated M and BS cells were examined using two-label microarray analysis (see “Materials and Methods”). To avoid confounding treatment effects associated with direct comparisons of M and BS transcriptomes (Sawers et al., 2007), comparisons were only made using the same cell type across the hcf136 and wild-type sibling genotypes. After normalization and filtering, 7,377 and 8,463 features were considered for further analysis from the M and BS experiments, respectively (Supplemental Tables S5 and S6). These two data sets share 5,670 common features as summarized in Figure 8A Figure 8. Open in new tabDownload slide Venn diagrams demonstrating unique expression profiles of hcf136 M and BS cells. A, Total features detectable in M and BS cells. B, Features differentially expressed in hcf136 at a 5% FDR. C, Features differentially expressed in hcf136 at a 1% FDR. Figure 8. Open in new tabDownload slide Venn diagrams demonstrating unique expression profiles of hcf136 M and BS cells. A, Total features detectable in M and BS cells. B, Features differentially expressed in hcf136 at a 5% FDR. C, Features differentially expressed in hcf136 at a 1% FDR. . Using a false discovery rate (FDR) of 5%, we identified 2,568 differentially expressed features between hcf136 and wild type in the M cell data set. When a more stringent 1% FDR cutoff is applied, 1,078 features are differentially expressed of which 162 have at least a 2-fold change in expression and 773 are more abundant in the mutant relative to wild type. In the BS experiment, 1,669 features are differentially expressed between hcf136 and wild type at a 5% FDR and 586 at a 1% FDR. In the 1% FDR BS data set, 195 features change by at least 2-fold relative to wild type and 306 are more abundant in the mutant relative to wild type. When the differentially expressed genes are compared at a 5% FDR between M and BS data sets, 573 features are identified that are common to both cell types (Fig. 8B). This overlap is reduced to 147 features when significance is controlled at a 1% FDR (Fig. 8C). Because only 14% or 9% (high and low FDR, respectively) of differentially expressed features are shared, these data suggest there is a cell-specific transcriptional response to the loss of PSII. A comparison of these data to a previous study (Sawers et al., 2007) shows that BS:M ratios of 129 features that preferentially accumulate in M cells and 167 that preferentially accumulate in BS cells are altered in the hcf136 mutant relative to wild type (Supplemental Table S7). For example, Phosphoenolpyruvate carboxykinase (MZ00013532), which has a wild-type BS:M ratio of 2.82 and a predicted hcf136 ratio of 1.39, is less differentially expressed in the mutant. Conversely, Carbonic anhydrase (MZ00042197), which has a BS:M ratio of 0.24 in wild type and a predicted ratio of 0.18 in hcf136, is more differentially expressed in the hcf136 mutant. Of the 129 M-enriched transcripts, 57% are more differentially expressed in the mutant relative to wild type (e.g. M:BS mutant > M:BS wild type). Conversely, of the 167 BS-enriched transcripts, only 29% are more differentially expressed in the hcf136 mutant. These results suggest that when PSII function is disrupted, the directionality of transcriptional responses in M and BS cells differs. To verify the altered transcriptional profiles determined by microarray analysis, RNA blots were performed (Fig. 9 Figure 9. Open in new tabDownload slide RNA-blot analysis of differentially expressed genes. A to C, RNA blots of separated M and BS cells of hcf136 and wild-type siblings were sequentially hybridized with radiolabeled gene fragments shown. Each blot was first probed with a cell-specific marker to ensure isolation purity (Me, Pepc, Rbcs). The nuclear (N)- and chloroplast (C)-encoded genes include PsbS (N), matK (C), psaAB (C), rbcL (C), Lhcb (N), and psbH (C). Ethidium-bromide stained (Etbr in the image) 18S RNA is shown as a loading control. Figure 9. Open in new tabDownload slide RNA-blot analysis of differentially expressed genes. A to C, RNA blots of separated M and BS cells of hcf136 and wild-type siblings were sequentially hybridized with radiolabeled gene fragments shown. Each blot was first probed with a cell-specific marker to ensure isolation purity (Me, Pepc, Rbcs). The nuclear (N)- and chloroplast (C)-encoded genes include PsbS (N), matK (C), psaAB (C), rbcL (C), Lhcb (N), and psbH (C). Ethidium-bromide stained (Etbr in the image) 18S RNA is shown as a loading control. ). Probes were designed to a number of plastid- and nuclear-encoded genes with highly abundant transcripts involved in photosynthesis that are differentially expressed between hcf136 and wild type at a 5% FDR in at least one cell type. From the M cell data, chloroplast-encoded psaAB, rbcL, psbH, matK and nuclear-encoded Lhcb were chosen for verification. From the BS data, chloroplast-encoded rbcL and matK and nuclear-encoded PsbS, Lhcb, and Rbcs were chosen for confirmation. As shown in Figure 9, RNA-blot analysis confirmed the differential accumulation of these genes between wild-type and mutant plants. The expression change of PsbS in BS cells was at the limit of detection (Fig. 9), but these data were confirmed using qPCR (Supplemental Fig. S4). Collectively, these data validate a subset of the microarray results indicating differential responses of M and BS cells to a loss of HCF136 function. DISCUSSION HCF136 Function in Maize Using the transposable element Ac as a molecular tag, the ZmHcf136 gene was cloned and characterized. The pale green, seedling-lethal Zmhcf136 mutant displays reduced thylakoid stacking in M plastids, an absence of PSII complexes, and no detectable PSII reaction center functionality (F v/F m = 0). These data are consistent with the previously assigned function of HCF136 as a PSII reaction center assembly or stability factor (Meurer et al., 1998; Plucken et al., 2002). In maize, PSII activity is largely restricted to the M cells, resulting in a cell-specific defect in mutant leaf tissues. Loss of PSII Protein Accumulation in hcf136 Although PSII reaction center and core proteins fail to accumulate to detectable levels in hcf136, the corresponding transcripts of both nuclear and chloroplast genes accumulate to near wild-type levels. This lack of correlation between proteome and transcriptome profiles is likely a consequence of protein degradation of unassembled PSII reaction center and core proteins in the chloroplast. In contrast, nuclear-encoded protein components of PSI (PsaD, E, F) and ATP synthase (CF1γ–AtpC) accumulate to similar levels in mutant and wild-type tissues, but the corresponding transcript profiles are altered in the hcf136 mutant. Transcripts for PSI and ATP synthase-associated proteins tend to accumulate to higher levels in mutant M cells and lower levels in mutant BS cells relative to wild type. Thus, the nuclear-plastid transcriptional networks in these two cell types respond selectively to a loss of PSII function. Altered Transcript Patterns in hcf136 The microarray data revealed that, whereas many features are detectable in both M and BS cells of hcf136 (5670), only 573 features are differentially expressed between wild type and mutant at a 5% FDR and 147 at a 1% FDR. These data suggest that M and BS cells are responding differently to a perturbation in HCF136 function. Striking examples of these differences in regulation can be observed in transcripts encoded by the plastid genome (5% FDR). For instance, different sets of genes encoding PSII components are misregulated in hcf136 M and BS plastids. In mutant M cells, psbH, J, M, and N are differentially expressed relative to wild type, whereas in BS cells, psbD, E, J, and K show altered accumulation profiles. Also, three components of the ATP synthase (atpA, B, E) and four components of the NADH dehydrogenase (ndhE, F, G, I) are differentially expressed in M cells, but not in the BS. Additionally, significant changes in psaB, petA, petD, rpoA, rpoB, and infA expression are only detected in M cell comparisons. In contrast, transcripts for psaJ, rpoC2, atpI, and ndhJ are differentially expressed solely in the BS. Another striking trend in the M cell expression data is that nearly twice as many features are differentially expressed in M cells (2,568) relative to the BS (1,669) at a 5% FDR. This trend is most evident for plastid-encoded transcripts, where 57 genes are differentially expressed between wild-type and mutant in M chloroplasts and only 18 genes are differentially expressed in BS plastids. For example, of 21 rpl and rps genes detected in both cell types, all 21 are differentially expressed in the M cells, but only two of those 21 are differentially expressed in BS strands. In general, transcripts encoded by the plastid genome are more abundant in the mutant relative to wild type when differentially expressed. Specifically, only psbH, psaB, ndhJ, atpI, rps14, and rbcL are less abundant in hcf136 than in wild type. Consequently, these data suggest that pools of plastid mRNA, particularly in the M, are responding in concert and are either more stable or more highly expressed in the mutant. It is possible that the smaller global response in the BS may reflect its naturally PSII-depleted state. A comparison of M and BS cell data sets shows that a greater percentage of differentially expressed features change by more than 2-fold in BS relative to M cells at a 1% FDR (33% versus 15%). This indicates that BS features are capable of a strong transcriptional response to the loss of PSII. For example, putative maize homologs of Phosphatidylcholine acyltransferase (MZ00018920), Peroxidase (MZ00015594), U2 snRNP auxiliary factor (MZ00006052), H2B histone (MZ00013518), and BTH-induced ERF transcriptional factor1 (MZ00017004) are increased in accumulation by more than 2-fold only in the BS. Similarly, Phosphenolpyruvate carboxykinase (MZ00013533) and a putative Inositol 1,3,4-trisphosphate 5/6-kinase (MZ00029181) decrease by more than 2-fold in hcf136 BS cells. In addition, some features are differentially expressed in both cell types, but the magnitude of the response is greater in the BS. For example, Thylakoid formation1 (MZ00043318) increases 2.6-fold in the BS and only 1.9-fold in M cells. Similarly, Cytochrome c (MZ00013468) increases 2.3-fold in BS and 1.5-fold in M hcf136 cells. Thus, M and BS cells are capable of independently regulating gene expression in response to a disruption of PSII. We identified 296 features that were previously shown to differentially accumulate in BS and M cells (Sawers et al., 2007) and were misregulated in the hcf136 mutant. As described above, the general trend is for less differential expression of BS-enriched features (118/167) and more differential expression of M-enriched features (73/129) in hcf136 relative to wild type. Eighty-five of 118 BS-enriched features are less differentially expressed in hcf136 due to an increase in expression in M cells. For example, cytochrome c oxidase subunit2 (MZ00034818) accumulates to similar levels in mutant BS cells as in wild type, but is more abundant in M cells of hcf136. This bias toward greater differential accumulation in hcf136 M cells coincides with the observation that 72% of M cell features show increased expression in the hcf136 mutant. The Role of Cellular Environment in C4 Differentiation Current models propose that the evolution of C4 biology from the basal C3 state requires the recruitment of cis- and trans-acting regulatory elements to alter gene expression (Sage, 2004). However, a recent transcript-profiling experiment indicates that nearly 18% of the leaf transcriptome is differentially expressed between M and BS cells (Sawers et al., 2007). Given the vast numbers of regulatory elements necessary to establish this magnitude of differential expression, we suggest that recruiting thousands of cis- and trans-acting elements to mediate transcriptional change is not a parsimonious explanation for how such a large percentage of the genome is spatially controlled. Rather, key regulatory changes may have resulted in novel M and BS cellular environments and in response extant C3 networks may have been recruited during evolution of C4 photosynthesis (Sheen, 1999; Hibberd and Quick, 2002), accounting for the majority of observed transcriptional changes. Factors that may drive M and BS gene expression include differential protein complex formation (e.g. OEC and PSII in M cell plastids), plastid redox status, and sugar and energy metabolite concentrations. An example of misexpression due to a change in cellular environment may be the aberrant processing of the psbB-psbH-psbT-petB-petD polycistron detailed in Figure 4. This defect is likely due to a change in the environment of M cell plastids that is associated with the loss of PSII (e.g. pH change, redox poise, thylakoid membrane structure). Although we have not ruled out a direct role for HCF136 in RNA metabolism, the psbB polycistron is aberrantly processed in several nonallelic hcf mutants, including hcf2, hcf38, and hcf43 (Barkan et al., 1986). The less differentially expressed M- and BS-enriched features may also constitute a class of genes that are responding to a loss of C4 cellular environments in the mutant. For instance, genes with BS:M expression ratios that are closer to 1 in hcf136 relative to wild type (e.g. Pyruvate, orthophosphate dikinase [MZ00007665] and Phosphoenolpyruvate carboxykinase [MZ00013532]) may represent a reversion to a more basal C3 state (Langdale et al., 1988b). Together, these findings suggest that a general disruption of photosynthetic electron transport leads to altered processing of the psbB polycistron (Barkan et al., 1986) and deregulation of some spatially restricted transcripts. Many nuclear genes respond to plastid-derived signals that are integrated through a common pathway in the chloroplast (Koussevitzky et al., 2007). In Arabidopsis, genome uncoupled (gun) mutants have been used to dissect plastid to nucleus retrograde signals. Susek et al. (1993) found that Lhcb and Rbcs expression is unchanged or elevated when gun mutants are treated with the herbicide Norflurazon. Using microarray analysis, Strand et al. (2003) identified 322 genes that are misregulated following Norflurazon treatments, 152 of which do not respond appropriately in at least one gun mutant. Recent studies of plastid-nuclear signaling in Arabidopsis have defined GUN1 as a central integrator of tetrapyrrole metabolism, redox, and plastid gene expression state within the plastid. These multiple inputs are somehow transduced into a signal that is transmitted to transcriptional regulators, including ABI4, to regulate nuclear gene expression (Koussevitzky et al., 2007). It is possible that a disruption of PSII is similarly sensed by a plastid factor and this information is relayed to the nucleus. The slight, but significant, increase in the expression of many nuclear-encoded M-enriched transcripts in hcf136 may be the consequence of the perturbation of PSII activity and loss (or reduction) of a plastid-derived signal that typically negatively regulates gene expression. Furthermore, the reduction in abundance of several transcripts in BS cells may be a secondary response to a loss of reducing equivalents or sugar metabolites rather than a direct response to the absence of PSII function. In summary, the hcf136 mutant has provided an opportunity to examine the effects of altered M and BS cellular environments on C4 differentiation. The loss of PSII impacts M and BS protein composition, PET, redox poise, energy, and sugar metabolite gradients. As a result, there is a general increase in RNA transcript accumulation in the M cell, and M- and BS-enriched genes become more and less differentially expressed, respectively. Additionally, altering the BS cellular environment results in decreased transcript accumulation for a number of features and this may reflect a shift to a more basal C3 state in this cell type. MATERIALS AND METHODS Identification of ZmHcf136 The maize (Zea mays) homolog of Arabidopsis (Arabidopsis thaliana) Hcf136 was identified as part of a regional mutagenesis screen using Ac/Dissociation transposition in the W22 inbred line of maize. The mutant family JK03-77.24 was created by selecting transposition events from bti00228∷Ac and subsequent screening of self-pollinated populations (Kolkman et al., 2005). DNA-blot analysis was performed using an Ac-specific fragment (Ac900; Kolkman et al., 2005) to identify an EcoRI RFLP that cosegregated with the mutant phenotype. This fragment was cloned using inverse PCR as previously described (Kolkman et al., 2005). BLAST sequence comparisons in available databases revealed similarity to HCF136 protein homologs. A ZmHcf136-specific DNA fragment was mapped using RFLP analysis (Lee et al., 2002) with forward primer, JK03-77.24@FlAc900 (5′-CCGCCAATCTCTACTCCGTCAAGT) and reverse primer, Hcf136 3′-untranslated region (UTR) Common (5′-GGTTTTCAAGTTCCTAAGCAAGCAG). ZmHcf136 Sequence Assembly Ac casting was used to obtain genomic DNA sequence for the full ZmHcf136 gene (Singh et al., 2003). Nested PCR was performed using gene-specific primers in combination with Ac internal primers. The gene-specific primers were 5′ Ac Casting 1 (5′-AGTCGATGGGCAGGAAGAT), 5′ Ac Casting 2 (5′-GCCGTCTTTCGTCTCCAGTA), 5′ Ac Casting 3 (5′-TCTGCTCCCCAGTAGCTTTT), 5′ Ac Casting 4 (5′-ACCGCTAATGCCACTTGAAA), and GC-HCF136 Common Exon (5′-AAAGTCCACCGTCCGCTCTC). Downstream primers were 3′ Ac Casting 1 (5′-GATGCATGTGCTGCTTGC), 3′ Ac Casting 2 (5′-GCGTGTTGCTTCGGTATCTT), and GC-HCF136 3′-UTR Common (5′-CTGCTTGCTTAGGAACTTGAAAACC). PCR products were gel purified using QiaEXII (QIAGEN), cloned into pGEM (Promega), or TOPO vectors (Invitrogen). Plasmids were purified using the QIAprep Spin Miniprep kit (QIAGEN) according to manufacturer's recommendations. The DNA was sequenced as previously described (Singh et al., 2003). Plant Growth Conditions Plants were grown in 16-h days and constant 28°C under low-light conditions of 80 μmol m−2 s−1 for fluorescence, electron microscopy, and protein analyses and 40 μmol m−2 s−1 for all other experiments. Etiolated seedlings were grown in darkness at 28°C until their light-grown siblings were at the third leaf-emerging stage. Mutants were identified from segregating families, and near-isogenic comparisons made with phenotypically wild-type siblings. Fluorescence Measurements In vivo fluorescence induction curves for F v/F m were obtained at room temperature from the second leaf tip of seedlings at the third leaf-emerging stage of development using an actinic light source and bright saturating pulse as previously described (Maxwell and Johnson, 2000). The leaf area assayed was dark adapted for at least 15 min prior to illumination. F v/F m measurements were obtained with a modulated fluorescence apparatus (model no. FMS2; Hansatech Instruments). Electron Microscopy Electron microscopy was performed on wild-type and mutant plants at the third leaf-emerging stage of development. Tips of the second leaves of 10-d-old wild-type and mutant seedlings were harvested in the morning to deplete overnight starch reserves. Samples were fixed for 0.5 h at room temperature and 1.5 h at 4°C in 2.5% glutaraldehyde in 0.1 m sodium cacodylate, pH 6.8. The samples were rinsed at 4°C in 0.1 m sodium cacodylate buffer, pH 6.8, fixed in 1% osmium tetroxide, and rinsed in 0.1 m sodium cacodylate buffer, pH 6.8. Samples were dehydrated in a graded ethanol series, and then infiltrated with Spurr's resin. Sections were cut on a Reichert OmU2 Ultramicrotome and contrasted with uranyl acetate and lead citrate. The sections were viewed on a Tecnai 12 Biotwin transmission electron microscope (FEI Corporation). Digital images were acquired using a Gatan Multiscan Camera (model 791). Cell Preparation M protoplasts, BS strands, and the control stressed total tissue were prepared from second leaf blades as previously described (Markelz et al., 2003). RNA Isolation and Blot Analysis Total RNA was isolated and analyzed by RNA blot as previously described (Sheehan et al., 2004). Leaf tissue from light-grown plants was harvested when the third leaf was emerging. Dark-grown seedling tissue was harvested above the mesocotyl on the same day. Cell-specific markers were assayed to monitor the integrity of the M and BS preparations (Pepc, Rbcs, Me). Approximately 5 μg of total RNA were loaded for the initial analysis of Hcf136 transcript accumulation (Fig. 3). All other gel blots were prepared using 10 μg of total RNA. DNA probes used in RNA-blot analysis include Hcf136, Pepc, Rbcs, Me, Lhcb-m7, rbcL, PsbS, matK, psaAB, psbH, petD, psbB, psbD, petB, psbA, psbC, and atpF/H. The Hcf136 probe was a 648-bp fragment amplified from the 3′-end of the gene using the forward primer Hcf136 Common Exon (5′-GAGAGCGGACGGTGGACTTT) and reverse primer Hcf136 3′-UTR Common (5′-GGTTTTCAAGTTCCTAAGCAAGCAG). The rbcL probe was amplified from genomic maize DNA using the primers 5′-GCAGTAGCTGCGGAATCTTCTACT and 5′-GGTGAATGTGAAGAAGTAGGCCGT. PsbS was amplified using 5′-TCTCCATCATCGGCGAGATCATCA and 5′-TACAAGCAGACAACCCAACG. Other fragments were as previously described (Roth et al., 1996) or were generated using gene-specific primers to published maize plastid sequences. DNA probes were generated by PCR using GoTaq Green Master Mix (Promega), gel purified with QiaEXII (QIAGEN), and radiolabeled according to Sheehan et al. (2004). Protein Characterization of Zmhcf136 Plants were grown as described above and tissue harvested for 2D IPG SDS-PAGE when the third leaf was emerging and for 2D BN SDS-PAGE and 1D SDS-PAGE when the fifth leaf was emerging. Proteins were extracted from whole seedlings for 2D IPG SDS-PAGE and from apical regions about 4 cm from the tips of third and fourth leaves for other PAGE experiments. The total leaf microsomal fraction was isolated in grinding buffer (350 mm sorbitol, 50 mm HEPES-KOH, pH 8, 2 mm EDTA, 5 mm ascorbic acid, 5 mm l-Cys) in a blender at half speed, followed by Miracloth filtration and low-speed centrifugation (1,000g). The thylakoid membrane fraction was purified from the microsomal pellet on discontinuous Percoll gradients as previously described (Friso et al., 2004). Thylakoid membrane vesicles were treated with a Dounce homogenizer followed by differential ultracentrifugation (100,000g) to collect membrane and soluble fractions. Protein concentrations were determined with the bicinchoninic acid assay (Smith et al., 1985). For 1D SDS-PAGE separation, proteins were equilibrated with SDS (0.2%), Na2CO3 (100 mm), dithiothreitol (100 mm), and Suc (10%) and separated on 12% Tricine gels (Schägger and von Jagow, 1987). Gels were stained with fluorescent Sypro Ruby (Molecular Probes). 2D IPG SDS-PAGE protein separation was performed on the thylakoid soluble fraction using 150 μg of protein per IPG strip as previously described (Majeran et al., 2005). For 2D BN SDS-PAGE, equivalent amounts of wild type and hcf136 thylakoid membranes (700 μg of protein) were solubilized with n-dodecyl β-d-maltoside and separated in the native first dimension according to Schägger et al. (1994). Gel strips issued from the native dimension were reduced and alkylated in a solubilization buffer according to Majeran et al. (2005) and separated by second dimension SDS-Tricine 12% gels (Schägger and von Jagow, 1987). Gels were stained with Coomassie Brilliant Blue R-250 (USB Corporation). For protein identification, Coomassie Brilliant Blue or Sypro Ruby stained spots were picked manually. Spots were automatically washed and digested with modified trypsin (Promega) as previously described (Shevchenko et al., 1996), and peptides were extracted using a ProGest robot (Genomic Solutions), dried, and resuspended in 5% formic acid. Protein identification was performed by PMF using MALDI-TOF MS in reflectron mode (Perseptive Biosystems Voyager DE-STR Workstation) and online liquid chromatography-ESI-MS/MS (Micromass Q-TOF) according to Majeran et al. (2005). The MS or MS/MS spectra were searched against the maize EST assembly from The Institute for Genomic Research (www.tigr.org; ZmGI, version 1.6) supplemented with maize chloroplast genome sequences obtained from National Center for Biotechnology Information (NCBI; www.ncbi.nlm.nih.gov) using an in-house installation of Mascot (www.matrixscience.com). Microarray Total RNA was isolated from the second leaf of plants as described above. Six biological replicates were used to compare wild-type and mutant transcript profiles in separate M and BS experiments. To maximize biological replication, different seedling pools were used for each of the 12 hybridizations. Microarray experiments and analyses were performed according to Sawers et al. (2007) using the Maize Array Consortium oligonucleotide platform (www.maizearray.org). Feature intensity values were log-transformed and corrected for local background signal, and a LOWESS procedure (Dudoit et al., 2002) was used to normalize between channels. Features with either low or saturating signal intensity were discarded from further analysis. High expression filtering was less stringent to avoid elimination of previously characterized, high abundance, C4 cell-specific transcripts. After filtering, features that were not assigned an MZ number by the Maize Array Consortium were discarded from further analysis. The moderated t test (Smyth, 2004) using the R package limma was applied to identify differentially expressed features. The P values for each test (feature) were converted to q values for FDR analysis as described by Storey et al. (2004). SYBR Green qPCR Three biological replicates were used for qPCR, with two internal technical replicates for each reaction. Total RNA (8 μg) was treated with 3 units of DNase I amplification grade enzyme (Invitrogen) at 37°C for 30 min to remove contaminating DNA in the presence of 80 units of RNaseOUT (Invitrogen). Enzymes and salts were removed from the RNA with TRIzol reagent (Invitrogen). One microgram of purified RNA was incubated at 70°C for 10 min with 50-ng random hexamers and the reaction cooled on ice. Additional reagents were added to a final concentration of 5 mm MgCl2, 0.01 m dithiothreitol, 0.5 mm dNTP, 40 units of RNaseOUT, and 200 units of SuperScript III reverse transcriptase (Invitrogen). Water was substituted for enzyme in the negative control. cDNA synthesis was performed by incubation at 25°C for 10 min, 50°C for 50 min, 80°C for 5 min, and a 4°C soak. Upon completion, the RNA template was destroyed with 2 units Escherichia coli RNase H, and cDNA was diluted with 60 μL of water. For qPCR reactions, the template was further diluted with three parts water, and the SYBR Green JumpStart Taq ReadyMix without MgCl2 kit (Sigma) was used with final concentrations of 2.3 mm MgCl2 and 24 ng/μL forward and reverse primers. Primer sequences are available in Supplemental Table S4. An internal reference dye was used to measure data quality. Samples were run at 95°C for 2 min, cycled 47 times between 95°C for 15 s and 60°C for 1 min, followed by a dissociation stage of 95°C for 15 s, 60°C for 15 s, and 95°C 15 s on an ABI Prism 7900HT sequence detection system (Applied Biosystems). Data were analyzed using ABI Prism SDS 2.1 software. Results were normalized using 18S rRNA reactions as a control. Sequence data for the maize homolog of Hcf136 can be found in the GenBank library under accession number EF587243. The data discussed in this publication have been deposited in the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) and are accessible through GEO Series accession number GSE9698. For Figure 1B, HCF136 homologs were aligned using the following accessions: Z. mays (ABQ53629), Oryza sativa (BAD62115.1), Arabidopsis (O82660), G. theta (NP_113453.1), and Synechocystis sp. PCC 6803 (NP_440411). S. bicolor protein information was assembled from CN132236, CN142773, CN142842, CN145337, CN150433, CN150507, and CN148500. Supplemental Data The following materials are available in the online version of this article. Supplemental Figure S1. Light micrographs of 1-μm-thick cross sections from the leaf blade tips of 10-d-old wild type (A) and hcf136 mutants (B) at 400× magnification. Supplemental Figure S2. RNA-blot analysis of polycistronic transcripts. Supplemental Figure S3. A comparison of 2D electrophoresis (2-DE) gels from wild type and hcf136 mutant tissues. Supplemental Figure S4. qPCR of relative transcript levels of PsbS between wild type and hcf136 within M and BS cell types. Supplemental Table S1. Identification of the HCF136 protein in wild-type samples by ESI-MS/MS. Supplemental Table S2. Identification of differentially accumulating proteins by MALDI-TOF MS PMF in the hcf136 mutant relative to wild type. Supplemental Table S3. Identification of differentially accumulating proteins by MALDI-TOF MS PMF in the hcf136 mutant relative to wild type. Supplemental Table S4. Primer sequences for SYBR Green qPCR. Supplemental Table S5. Comparison of transcript profiles between hcf136 and wild-type M cells. Supplemental Table S6. Comparison of transcript profiles between hcf136 and wild-type BS cells. Supplemental Table S7. Comparison of cell-specific expression profiles between hcf136 and wild type. ACKNOWLEDGMENTS We gratefully thank Dr. Thomas Owens, Dr. Robert Turgeon, Dr. Tesfamichael Kebrom, Ms. Phyllis Farmer, and Dr. Qi Sun for technical advice and helpful discussions, Shannon Caldwell and Anita Aluisio at the Cornell Integrated Microscopy Center (Veterinary Medical Center, Cornell University) for the electron micrographs, and Dr. Katia Wostrikoff for helpful discussions. LITERATURE CITED Andersen KS, Bain JM, Bishop DG, Smillie RM ( 1972 ) Photosystem II activity in agranal bundle sheath chloroplasts from Zea mays. Plant Physiol 49 : 461 – 466 Crossref Search ADS PubMed Barkan A ( 1988 ) Proteins encoded by a complex chloroplast transcription unit are each translated from both monocistronic and polycistronic mRNAs. EMBO J 7 : 2637 – 2644 Crossref Search ADS PubMed Barkan A, Miles D, Taylor WC ( 1986 ) Chloroplast gene expression in nuclear, photosynthetic mutants of maize. EMBO J 5 : 1421 – 1427 Crossref Search ADS PubMed Becker TW, Perro-Rechenmann C, Suzuki A, Hirel B ( 1993 ) Subcellular and immunocytochemical localization of the enzymes involved in ammonia assimilation in mesophyll and bundle-sheath cells of maize leaves. Planta 191 : 129 – 136 Brutnell TP, Sawers RJ, Mant A, Langdale JA ( 1999 ) BUNDLE SHEATH DEFECTIVE2, a novel protein required for post-translational regulation of the rbcL gene of maize. Plant Cell 11 : 849 – 864 Crossref Search ADS PubMed Burgener M, Suter M, Jones S, Brunold C ( 1998 ) Cyst(e)ine is the transport metabolite of assimilated sulfur from bundle-sheath to mesophyll cells in maize leaves. Plant Physiol 116 : 1315 – 1322 Crossref Search ADS PubMed Chollet R ( 1973 ) Photosynthetic carbon metabolism in isolated maize bundle sheath strands. Plant Physiol 51 : 787 – 792 Crossref Search ADS PubMed Cushman JC, Hallick RB, Price CA ( 1988 ) The two genes for the P700 chlorophyll a apoproteins on the Euglena gracilis chloroplast genome contain multiple introns. Curr Genet 13 : 159 – 171 Crossref Search ADS PubMed Dekker JP, Boekema EJ ( 2005 ) Supramolecular organization of thylakoid membrane proteins in green plants. Biochim Biophys Acta 1706 : 12 – 39 Crossref Search ADS PubMed Dudoit S, Yang YH, Callow MJ, Speed TP ( 2002 ) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Statist Sinica 12 : 111 – 139 Edwards GE, Franceschi VR, Ku MS, Voznesenskaya EV, Pyankov VI, Andreo CS ( 2001 a) Compartmentation of photosynthesis in cells and tissues of C4 plants. J Exp Bot 52 : 577 – 590 PubMed Edwards GE, Furbank RT, Hatch MD, Osmond CB ( 2001 b) What does it take to be C4? Lessons from the evolution of C4 photosynthesis. Plant Physiol 125 : 46 – 49 Crossref Search ADS PubMed Edwards GE, Walker D ( 1983 ) C3, C4: Mechanisms, Cellular and Environmental Regulation of Photosynthesis. University of California Press, Berkeley, CA Emanuelsson O, Nielsen H, Brunak S, von Heijne G ( 2000 ) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 300 : 1005 – 1016 Crossref Search ADS PubMed Friso G, Giacomelli L, Ytterberg AJ, Peltier JB, Rudella A, Sun Q, Wijk KJ ( 2004 ) In-depth analysis of the thylakoid membrane proteome of Arabidopsis thaliana chloroplasts: new proteins, new functions, and a plastid proteome database. Plant Cell 16 : 478 – 499 Crossref Search ADS PubMed Furumoto T, Hata S, Izui K ( 2000 ) Isolation and characterization of cDNAs for differentially accumulated transcripts between mesophyll cells and bundle sheath strands of maize leaves. Plant Cell Physiol 41 : 1200 – 1209 Crossref Search ADS PubMed Ghirardi ML, Melis A ( 1983 ) Localization of photosynthetic electron transport components in mesophyll and bundle sheath chloroplasts of Zea mays. Arch Biochem Biophys 224 : 19 – 28 Crossref Search ADS PubMed Gregory RP, Droppa M, Horvath G, Evans EH ( 1979 ) A comparison based on delayed light emission and fluorescence induction of intact chloroplasts isolated from mesophyll protoplasts and bundle-sheath cells of maize. Biochem J 180 : 253 – 256 Crossref Search ADS PubMed Harel E, Lea PJ, Miflin BJ ( 1977 ) The localization of enzymes of nitrogen assimilation in maize leaves and their activities during greening. Planta 134 : 195 – 200 Crossref Search ADS PubMed Hibberd JM, Quick WP ( 2002 ) Characteristics of C4 photosynthesis in stems and petioles of C3 flowering plants. Nature 415 : 451 – 454 Crossref Search ADS PubMed Kagawa T, Hatch MD ( 1974 ) C4-acids as the source of carbon dioxide for Calvin cycle photosynthesis by bundle sheath cells of the C4-pathway species Atriplex spongiosa. Biochem Biophys Res Commun 59 : 1326 – 1332 Crossref Search ADS PubMed Kim JK, Hollingsworth MJ ( 1993 ) Splicing of group II introns in spinach chloroplasts (in vivo): analysis of lariat formation. Curr Genet 23 : 175 – 180 Crossref Search ADS PubMed Kirchanski SJ ( 1975 ) The ultrastructural development of the dimorphic plastids of Zea mays L. Am J Bot 62 : 695 – 705 Crossref Search ADS Kolkman JM, Conrad LJ, Farmer PR, Hardeman K, Ahern KR, Lewis PE, Sawers RJ, Lebejko S, Chomet P, Brutnell TP ( 2005 ) Distribution of Activator (Ac) throughout the maize genome for use in regional mutagenesis. Genetics 169 : 981 – 995 Crossref Search ADS PubMed Koussevitzky S, Nott A, Mockler TC, Hong F, Sachetto-Martins G, Surpin M, Lim J, Mittler R, Chory J ( 2007 ) Signals from chloroplasts converge to regulate nuclear gene expression. Science 316 : 715 – 719 Crossref Search ADS PubMed Ku MS, Kano-Murakami Y, Matsuoka M ( 1996 ) Evolution and expression of C4 photosynthesis genes. Plant Physiol 111 : 949 – 957 Crossref Search ADS PubMed Kubicki A, Steinmuller K, Westhoff P ( 1994 ) Differential transcription of plastome-encoded genes in the mesophyll and bundle-sheath chloroplasts of the monocotyledonous NADP-malic enzyme-type C4 plants maize and sorghum. Plant Mol Biol 25 : 669 – 679 Crossref Search ADS PubMed Kuck U ( 1989 ) The intron of a plastid gene from a green alga contains an open reading frame for a reverse transcriptase-like enzyme. Mol Gen Genet 218 : 257 – 265 Crossref Search ADS PubMed Langdale JA, Rothermel BA, Nelson T ( 1988 a) Cellular pattern of photosynthetic gene expression in developing maize leaves. Genes Dev 2 : 106 – 115 Crossref Search ADS PubMed Langdale JA, Taylor WC, Nelson T ( 1991 ) Cell-specific accumulation of maize phosphoenolpyruvate carboxylase is correlated with demethylation at a specific site greater than 3 kb upstream of the gene. Mol Gen Genet 225 : 49 – 55 Crossref Search ADS PubMed Langdale JA, Zelitch I, Miller E, Nelson T ( 1988 b) Cell position and light influence C4 versus C3 patterns of photosynthetic gene expression in maize. EMBO J 7 : 3643 – 3651 Crossref Search ADS PubMed Lee M, Sharopova N, Beavis WD, Grant D, Katt M, Blair D, Hallauer A ( 2002 ) Expanding the genetic map of maize with the intermated B73 x Mo17 (IBM) population. Plant Mol Biol 48 : 453 – 461 Crossref Search ADS PubMed Leto KJ, Miles D ( 1980 ) Characterization of three photosystem II mutants in Zea mays L. lacking a 32,000 Dalton lamellar polypeptide. Plant Physiol 66 : 18 – 24 Crossref Search ADS PubMed Majeran W, Cai Y, Sun Q, van Wijk KJ ( 2005 ) Functional differentiation of bundle sheath and mesophyll maize chloroplasts determined by comparative proteomics. Plant Cell 17 : 3111 – 3140 Crossref Search ADS PubMed Markelz NH, Costich DE, Brutnell TP ( 2003 ) Photomorphogenic responses in maize seedling development. Plant Physiol 133 : 1578 – 1591 Crossref Search ADS PubMed Maxwell K, Johnson GN ( 2000 ) Chlorophyll fluorescence—a practical guide. J Exp Bot 51 : 659 – 668 Crossref Search ADS PubMed Meurer J, Plucken H, Kowallik KV, Westhoff P ( 1998 ) A nuclear-encoded protein of prokaryotic origin is essential for the stability of photosystem II in Arabidopsis thaliana. EMBO J 17 : 5286 – 5297 Crossref Search ADS PubMed Miller KR, Miller GJ, McIntyre KR ( 1977 ) Organization of the photosynthetic membrane in maize mesophyll and bundle sheath chloroplasts. Biochim Biophys Acta 459 : 145 – 156 Crossref Search ADS PubMed Plucken H, Muller B, Grohmann D, Westhoff P, Eichacker LA ( 2002 ) The HCF136 protein is essential for assembly of the photosystem II reaction center in Arabidopsis thaliana. FEBS Lett 532 : 85 – 90 Crossref Search ADS PubMed Rathnam CK, Edwards GE ( 1975 ) Intracellular localization of certain photosynthetic enzymes in bundle sheath cells of plants possessing the C4 pathway of photosynthesis. Arch Biochem Biophys 171 : 214 – 225 Crossref Search ADS PubMed Rathnam CK, Edwards GE ( 1976 ) Distribution of nitrate-assimilating enzymes between mesophyll protoplasts and bundle sheath cells in leaves of three groups of C4 plants. Plant Physiol 57 : 881 – 885 Crossref Search ADS PubMed Rock CD, Barkan A, Taylor WC ( 1987 ) The maize plastid psbB-psbF-petB-petD gene cluster: spliced and unspliced petB and petD RNAs encode alternative products. Curr Genet 12 : 69 – 77 Crossref Search ADS PubMed Romanowska E, Drozak A, Pokorska B, Shiell BJ, Michalski WP ( 2006 ) Organization and activity of photosystems in the mesophyll and bundle sheath chloroplasts of maize. J Plant Physiol 163 : 607 – 618 Crossref Search ADS PubMed Roth R, Hall LN, Brutnell TP, Langdale JA ( 1996 ) bundle sheath defective2, a mutation that disrupts the coordinated development of bundle sheath and mesophyll cells in the maize leaf. Plant Cell 8 : 915 – 927 Crossref Search ADS PubMed Sage RF ( 2004 ) The evolution of C4 photosynthesis. New Phytol 161 : 341 – 370 Crossref Search ADS Sawers RJ, Liu P, Anufrikova K, Hwang JT, Brutnell TP ( 2007 ) A multi-treatment experimental system to examine photosynthetic differentiation in the maize leaf. BMC Genomics 8 : 12 Crossref Search ADS PubMed Schaffner AR, Sheen J ( 1991 ) Maize rbcS promoter activity depends on sequence elements not found in dicot rbcS promoters. Plant Cell 3 : 997 – 1012 PubMed Schaffner AR, Sheen J ( 1992 ) Maize C4 photosynthesis involves differential regulation of phosphoenolpyruvate carboxylase genes. Plant J 2 : 221 – 232 PubMed Schägger H, Cramer WA, von Jagow G ( 1994 ) Analysis of molecular masses and oligomeric states of protein complexes by blue native electrophoresis and isolation of membrane protein complexes by two-dimensional native electrophoresis. Anal Biochem 217 : 220 – 230 Crossref Search ADS PubMed Schägger H, von Jagow G ( 1987 ) Tricine-sodium dodecyl sulfate-polyacrylamide gel electrophoresis for the separation of proteins in the range from 1 to 100 kDa. Anal Biochem 166 : 368 – 379 Crossref Search ADS PubMed Schuster G, Ohad I, Martineau B, Taylor WC ( 1985 ) Differentiation and development of bundle sheath and mesophyll thylakoids in maize. Thylakoid polypeptide composition, phosphorylation, and organization of photosystem II. J Biol Chem 260 : 11866 – 11873 Crossref Search ADS PubMed Sheehan MJ, Farmer PR, Brutnell TP ( 2004 ) Structure and expression of maize phytochrome family homologs. Genetics 167 : 1395 – 1405 Crossref Search ADS PubMed Sheen J ( 1991 ) Molecular mechanisms underlying the differential expression of maize pyruvate, orthophosphate dikinase genes. Plant Cell 3 : 225 – 245 PubMed Sheen J ( 1999 ) C4 gene expression. Annu Rev Plant Physiol Plant Mol Biol 50 : 187 – 217 Crossref Search ADS PubMed Sheen J, Bogorad L ( 1986 ) Expression of the ribulose-1,5-bisphosphate carboxylase large subunit gene and three small subunit genes in two cell types of maize leaves. EMBO J 5 : 3417 – 3422 Crossref Search ADS PubMed Sheen JY, Bogorad L ( 1987 ) Differential expression of C4 pathway genes in mesophyll and bundle sheath cells of greening maize leaves. J Biol Chem 262 : 11726 – 11730 Crossref Search ADS PubMed Shevchenko A, Wilm M, Vorm O, Mann M ( 1996 ) Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal Chem 68 : 850 – 858 Crossref Search ADS PubMed Singh M, Lewis PE, Hardeman K, Bai L, Rose JK, Mazourek M, Chomet P, Brutnell TP ( 2003 ) Activator mutagenesis of the pink scutellum1/viviparous7 locus of maize. Plant Cell 15 : 874 – 884 Crossref Search ADS PubMed Smith LH, Langdale JA, Chollet R ( 1998 ) A functional Calvin cycle is not indispensable for the light activation of C4 phosphoenolpyruvate carboxylase kinase and its target enzyme in the maize mutant bundle sheath defective2-mutable1. Plant Physiol 118 : 191 – 197 Crossref Search ADS PubMed Smith PK, Krohn RI, Hermanson GT, Mallia AK, Gartner FH, Provenzano MD, Fujimoto EK, Goeke NM, Olson BJ, Klenk DC ( 1985 ) Measurement of protein using bicinchoninic acid. Anal Biochem 150 : 76 – 85 Crossref Search ADS PubMed Smyth GK ( 2004 ) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3 : Article 3 Stockhaus J, Schlue U, Koczor M, Chitty JA, Taylor WC, Westhoff P ( 1997 ) The promoter of the gene encoding the C4 form of phosphoenolpyruvate carboxylase directs mesophyll-specific expression in transgenic C4 Flaveria spp. Plant Cell 9 : 479 – 489 Crossref Search ADS PubMed Storey JD, Taylor JE, Siegmund D ( 2004 ) Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach. J R Stat Soc Ser B 66 : 187 – 205 Crossref Search ADS Strand A, Asami T, Alonso J, Ecker JR, Chory J ( 2003 ) Chloroplast to nucleus communication triggered by accumulation of Mg-protoporphyrinIX. Nature 421 : 79 – 83 Crossref Search ADS PubMed Susek RE, Ausubel FM, Chory J ( 1993 ) Signal transduction mutants of Arabidopsis uncouple nuclear CAB and RBCS gene expression from chloroplast development. Cell 74 : 787 – 799 Crossref Search ADS PubMed Author notes 1 This work was supported by the National Science Foundation (grant no. DBI–0211935 to T.P.B. and K.J.v.W.) and the Natural Sciences and Engineering Research Council of Canada (to S.C.). 2 Present address: Department of Plant Pathology, Cornell University, Ithaca, NY 14853. * Corresponding author; e-mail [email protected]. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Thomas P. Brutnell ([email protected]). [C] Some figures in this article are displayed in color online but in black and white in the print edition. [W] The online version of this article contains Web-only data. [OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.107.113423 © 2008 American Society of Plant Biologists © The Author(s) 2008. Published by Oxford University Press on behalf of American Society of Plant Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Lu, Yan; Savage, Linda J.; Ajjawi, Imad; Imre, Kathleen M.; Yoder, David W.; Benning, Christoph; DellaPenna, Dean; Ohlrogge, John B.; Osteryoung, Katherine W.; Weber, Andreas P.; Wilkerson, Curtis G.; Last, Robert L.

Cao, Mingshu; Koulman, Albert; Johnson, Linda J.; Lane, Geoffrey A.; Rasmussen, Susanne

doi: 10.1104/pp.107.112458pmid: 18287492

Abstract Direct-infusion mass spectrometry (MS) was applied to study the metabolic effects of the symbiosis between the endophytic fungus Neotyphodium lolii and its host perennial ryegrass (Lolium perenne) in three different tissues (immature leaf, blade, and sheath). Unbiased direct-infusion MS using a linear ion trap mass spectrometer allowed metabolic effects to be determined free of any preconceptions and in a high-throughput fashion. Not only the full MS1 mass spectra (range 150–1,000 mass-to-charge ratio) were obtained but also MS2 and MS3 product ion spectra were collected on the most intense MS1 ions as described previously (Koulman et al., 2007b). We developed a novel computational methodology to take advantage of the MS2 product ion spectra collected. Several heterogeneous MS1 bins (different MS2 spectra from the same nominal MS1) were identified with this method. Exploratory data analysis approaches were also developed to investigate how the metabolome differs in perennial ryegrass infected with N. lolii in comparison to uninfected perennial ryegrass. As well as some known fungal metabolites like peramine and mannitol, several novel metabolites involved in the symbiosis, including putative cyclic oligopeptides, were identified. Correlation network analysis revealed a group of structurally related oligosaccharides, which differed significantly in concentration in perennial ryegrass sheaths due to endophyte infection. This study demonstrates the potential of the combination of unbiased metabolite profiling using ion trap MS and advanced data-mining strategies for discovering unexpected perturbations of the metabolome, and generating new scientific questions for more detailed investigations in the future. With the advent of metabolomics, methods for the simultaneous analysis of a large number of small molecules (metabolites) have been developed and improved, providing more details about the metabolism of complex biological systems (Sumner et al., 2003; Dettmer et al., 2007). Metabolite fingerprinting methods provide relatively unbiased and high-throughput information on complex biological systems and have been used for yeast (Saccharomyces cerevisiae) strain classification (Allen et al., 2003) and annotation of gene functions (Raamsdonk et al., 2001). Comprehensive and unbiased metabolite analysis is also an indispensable tool for systems biology together with transcriptomics and proteomics (see commentary by Sauer et al., 2007). Direct-infusion (without prior chromatographic separation) electrospray ionization (ESI) mass spectrometry (MS) was introduced as a tool for the identification of novel fungal metabolites in culture (Smedsgaard and Frisvad, 1996) and is now widely applied in metabolomics (for a recent review, see Dettmer et al., 2007). High resolution MS instrumentation such as time-of-flight MS (Dunn et al., 2005) or Fourier transform ion cyclotron resonance MS (FT-ICR-MS; Aharoni et al., 2002) is often preferred for the specificity provided by resolution of isobaric ions and highly accurate estimates of mass-to-charge (m/z) ratios. We recently applied direct-infusion ESI MS using an ion trap MS (DIMSn) to determine metabolic differences between endophyte-infected and endophyte-free perennial ryegrass (Lolium perenne) seed samples (Koulman et al., 2007b). This study established that DIMSn is a powerful tool for determining metabolic profiles, even though ion trap MS is a low resolution MS technology. Its advantage lies in the capacity of the ion trap to rapidly collect fragmentation data on large numbers of ions (more than 200) selected from the MS1 spectrum using automated data-dependent scanning, thereby facilitating structural classification and identification of metabolites of interest. Direct-infusion ESI MS/MS with an ion trap has been used to discover unknown drug metabolites (e.g. Tozuka et al., 2003), but its potential for metabolome investigations warrants further exploration and development. Here, we have employed DIMSn technology to detect and investigate a wide range of metabolites involved in an association between perennial ryegrass and its endophytic fungus, Neotyphodium lolii. Symbiotic associations between fungal endophytes and grasses are widespread and have been estimated to occur in 20% to 30% of all grass species (Leuchtmann, 1992), and are therefore of wide interest to studies on plant-fungal interactions. The two most widely studied associations are the perennial ryegrass-N. lolii symbiosis in Australasia and tall fescue (Lolium arundinaceum)-Neotyphodium coenophialum in North America (Christensen et al., 1993). These two associations are of particular interest to agricultural pastoral systems because the fungal endophytes have been implicated in the toxicity of grazing livestock including ryegrass staggers and fescue foot, but also found to confer a range of agronomic benefits to their grass hosts, mainly through toxicity and feeding deterrent activities toward invertebrate herbivores. These antiherbivore activities have been associated with specific alkaloids produced by the fungi within the plant (Bush et al., 1997; Lane et al., 2000; Malinowski and Belesky, 2000; Schardl et al., 2004). The major known alkaloids produced by N. lolii in perennial ryegrass are peramine, lolitrem B, and ergovaline. Peramine, a pyrrolopyrazine alkaloid, protects the grass host from herbivorous insects such as the Argentine stem weevil (Listronotus bonariensis; Rowan and Gaynor, 1986; Fletcher and Easton, 1997) and has been shown to be exuded in the guttation fluid of endophyte-infected perennial ryegrass (Koulman et al., 2007a). The indole-diterpene lolitrem B acts as a neurotoxin and causes ryegrass staggers in grazing livestock (Gallagher et al., 1984). The peptide alkaloid ergovaline has been associated with heat stress and poor liveweight gains in livestock grazing endophyte-infected perennial ryegrass (Easton et al., 1986; Fletcher and Easton, 1997) and with fescue foot, a severe mammalian disorder that can lead to considerable productivity losses in livestock raised on endophyte-infected tall fescue (Lyons et al., 1986; Strickland et al., 1996). Considerable research efforts have been focused on the biosynthesis, accumulation, and ecological consequences of these fungal alkaloids (for review, see Schardl, 2001; Clay and Schardl, 2002; Schardl et al., 2004). Much less is known about the impacts of fungal endophytes on general host plant performance and metabolism, and recent publications indicate that the effects of fungal endophytes on plant metabolism might be of importance to the understanding of ecosystem-wide impacts of the grass-endophyte symbiosis (Hunt et al., 2005; Cheplick, 2007; Krauss et al., 2007; Rasmussen et al., 2007, 2008). In this article, we present exploratory data analysis approaches to investigate how metabolites analyzed by DIMSn differ between endophyte-infected and uninfected ryegrass plants in three tissue samples corresponding to three developmental stages (immature leaf, blade, and sheath) of the symbiosis of perennial ryegrass and N. lolii. We have also taken advantage of the MS/MS spectral information to aid metabolite identification and determine the homogeneity of the spectra, and hence uniformity of the metabolite species across the samples. Available software for automating the processing of liquid chromatography (LC)-MS data including commercial software such as MassFrontier (http://www.highchem.com/) and freeware and open source software such as MetAlign (http://www.metalign.nl), XCMS (Smith et al., 2006), and MZmine (Katajamaa and Orešič, 2005) is not applicable to infusion profiles of the type generated in our experiments, as these programs are designed to search for peaks in both the time and mass domain. Thus, computational tools for harnessing the raw data from DIMSn experiments have been developed in this study and will be made available upon request. RESULTS The approach to DIMSn data analysis in this article is as follows: (1) statistical analysis of MS1 data, with the range of 150 to1,000 m/z, to select nominal m/z bins that differ significantly in intensity between the groups of four samples from infected and uninfected plants within each of three tissue types (immature leaf, blade, and sheath); (2) analysis of the MS2 spectra deriving from the same parent MS1 m/z bin across all the samples using purpose-built computational tools to determine their similarity and aid identification of components in the fragmentation data; and (3) correlation network analysis of all MS1 bins to identify metabolite relationships not revealed by feature selection based on the statistical ranking. MS1 Data Analysis and the Selection of Differentiated MS1 m/z Bins The MS1 spectrum of each sample was obtained from the raw data as described in “Materials and Methods” (“Data Analysis”). To handle the low resolution infusion data we were able to adopt simple processing procedures (compare with Enot et al., 2006) compared to those required for handling high resolution LC-MS data (Hansen and Smedsgaard, 2004), where alignment in the time and mass domains can be challenging. The MS1 spectra were collated in nominal m/z bins in keeping with the 1 m/z resolution of the machine (called MS1 bins thereafter). After background subtraction, the median value of the ion abundance in each bin was determined. Each MS1 bin is thus likely to include ion signals from more than one metabolite. On the other hand, each metabolite is likely to contribute to signals for more than one MS1 bin due to the occurrence of isotopologue ions, hydrogen transfers in the source, and the formation of salt adduct ions. Both aspects must be taken into account for the interpretation of a nominal MS1 bin. Our experiment was designed to analyze how the metabolome of the symbiosis changes upon endophyte infection in different tissues, i.e. immature leaf, blade, and sheath (see Supplemental Table S1 for sample description). Our first data exploration based on principal component analysis revealed that the main variations (73.45% of the total variation) were explained by metabolic differences between tissues. The infected (E+) and uninfected (E−) samples were not resolved in the PC1-PC2 score plot (Supplemental Fig. S1). We therefore used an empirical Bayes moderated t test (Smyth, 2004) to investigate which metabolites were differentially expressed between E+ and E− in immature leaf, blade, and sheath tissue, respectively. This approach was devised to identify differentially expressed genes across specified conditions in designed microarray experiments, and it provides more stable inference when the sample size is small (Smyth, 2004). Significant differential MS1 bins were selected based on an adjusted P value <0.05 using Benjamin and Hochberg's false discovery rate to control false positives. Ten MS1 bins were identified based on this criterion, of which seven (m/z 230, 248, 205, 231, 335, 189, and 554) were significantly different between E+ and E− in sheath, four in immature (m/z 209, 297, 223, and 230), but none in blade tissue. The distributions of the ion abundance of MS1 bins of m/z 205, 248, 335, and 554 in different treatment groups are shown in Figure 1 Figure 1. Open in new tabDownload slide The distribution of MS1 ion abundance in different treatment groups. MS1 bins m/z 205, 248, 335, and 554 differ significantly (false discovery rate adjusted P value <0.05) between E+ and E− in sheath tissue. The barplot is based on the median and median absolute deviation values of the replicates (n = 4, median ± median absolute deviation). Labels of E+ and E− refer to presence and absence of endophyte, and I, B, and S refer to plant tissue immature leaf, blade, and sheath, respectively. See all sample names in Supplemental Table S1. Figure 1. Open in new tabDownload slide The distribution of MS1 ion abundance in different treatment groups. MS1 bins m/z 205, 248, 335, and 554 differ significantly (false discovery rate adjusted P value <0.05) between E+ and E− in sheath tissue. The barplot is based on the median and median absolute deviation values of the replicates (n = 4, median ± median absolute deviation). Labels of E+ and E− refer to presence and absence of endophyte, and I, B, and S refer to plant tissue immature leaf, blade, and sheath, respectively. See all sample names in Supplemental Table S1. . See Supplemental Figure S2 for the distribution of the other significant MS1 bins (m/z 230, 231, 189, 209, 223, and 297) and Table I Table I. A summary of MS1 bins discussed in this study MS1 Bin . Isotopologue . Ion Adduct . Putative Metabolitea . Ion Fragmentation . Tissueb . m/z 189 Unknown (no MS2) Sheath 205 [182Na]+ Mannitolp,f Supplemental Figure S3 Sheath 209 Unknown (heterogeneous bin) Figure 3 Immature 223 Unknown (no MS2) Immature 230 Unknown (no MS2) Sheath/immature 231 Unknown (no MS2) Sheath 248 Peraminef Supplemental Figure S7 Sheath 297 296 5-Hydroxyferulyl sinapinep Immature 335 333, 334 Perlolinep Sheath 543 544, 545, 546 [504K]+ Trihexosidep Sheath 554 555 [1,107H2]++ Cyclic peptidef Supplemental Figure S4, a and b Sheath 705 706 [666K]+ Tetrahexosidep Supplemental Figure S5a Sheath 867 868, 869, 870 [828K]+ Pentahexosidep Supplemental Figure S5a Sheath 779 781 [666K2Cl]+ Tetrahexosidep [K2Cl]+ cluster None 941 943 [828K2Cl]+ Pentahexosidep [K2Cl]+ cluster None MS1 Bin . Isotopologue . Ion Adduct . Putative Metabolitea . Ion Fragmentation . Tissueb . m/z 189 Unknown (no MS2) Sheath 205 [182Na]+ Mannitolp,f Supplemental Figure S3 Sheath 209 Unknown (heterogeneous bin) Figure 3 Immature 223 Unknown (no MS2) Immature 230 Unknown (no MS2) Sheath/immature 231 Unknown (no MS2) Sheath 248 Peraminef Supplemental Figure S7 Sheath 297 296 5-Hydroxyferulyl sinapinep Immature 335 333, 334 Perlolinep Sheath 543 544, 545, 546 [504K]+ Trihexosidep Sheath 554 555 [1,107H2]++ Cyclic peptidef Supplemental Figure S4, a and b Sheath 705 706 [666K]+ Tetrahexosidep Supplemental Figure S5a Sheath 867 868, 869, 870 [828K]+ Pentahexosidep Supplemental Figure S5a Sheath 779 781 [666K2Cl]+ Tetrahexosidep [K2Cl]+ cluster None 941 943 [828K2Cl]+ Pentahexosidep [K2Cl]+ cluster None a Superscript labels p and f indicate plant and fungal origin, respectively. b Tissue in which the bins show a statistically significant difference between E+ and E− material. MS1 bins m/z 209, 223, 297, and 335 are significantly higher in E− samples and all other MS1 bins are higher in E+ samples. Open in new tab Table I. A summary of MS1 bins discussed in this study MS1 Bin . Isotopologue . Ion Adduct . Putative Metabolitea . Ion Fragmentation . Tissueb . m/z 189 Unknown (no MS2) Sheath 205 [182Na]+ Mannitolp,f Supplemental Figure S3 Sheath 209 Unknown (heterogeneous bin) Figure 3 Immature 223 Unknown (no MS2) Immature 230 Unknown (no MS2) Sheath/immature 231 Unknown (no MS2) Sheath 248 Peraminef Supplemental Figure S7 Sheath 297 296 5-Hydroxyferulyl sinapinep Immature 335 333, 334 Perlolinep Sheath 543 544, 545, 546 [504K]+ Trihexosidep Sheath 554 555 [1,107H2]++ Cyclic peptidef Supplemental Figure S4, a and b Sheath 705 706 [666K]+ Tetrahexosidep Supplemental Figure S5a Sheath 867 868, 869, 870 [828K]+ Pentahexosidep Supplemental Figure S5a Sheath 779 781 [666K2Cl]+ Tetrahexosidep [K2Cl]+ cluster None 941 943 [828K2Cl]+ Pentahexosidep [K2Cl]+ cluster None MS1 Bin . Isotopologue . Ion Adduct . Putative Metabolitea . Ion Fragmentation . Tissueb . m/z 189 Unknown (no MS2) Sheath 205 [182Na]+ Mannitolp,f Supplemental Figure S3 Sheath 209 Unknown (heterogeneous bin) Figure 3 Immature 223 Unknown (no MS2) Immature 230 Unknown (no MS2) Sheath/immature 231 Unknown (no MS2) Sheath 248 Peraminef Supplemental Figure S7 Sheath 297 296 5-Hydroxyferulyl sinapinep Immature 335 333, 334 Perlolinep Sheath 543 544, 545, 546 [504K]+ Trihexosidep Sheath 554 555 [1,107H2]++ Cyclic peptidef Supplemental Figure S4, a and b Sheath 705 706 [666K]+ Tetrahexosidep Supplemental Figure S5a Sheath 867 868, 869, 870 [828K]+ Pentahexosidep Supplemental Figure S5a Sheath 779 781 [666K2Cl]+ Tetrahexosidep [K2Cl]+ cluster None 941 943 [828K2Cl]+ Pentahexosidep [K2Cl]+ cluster None a Superscript labels p and f indicate plant and fungal origin, respectively. b Tissue in which the bins show a statistically significant difference between E+ and E− material. MS1 bins m/z 209, 223, 297, and 335 are significantly higher in E− samples and all other MS1 bins are higher in E+ samples. Open in new tab for a summary of all the MS1 bins identified as being significantly different between infected and uninfected perennial ryegrass tissues. Based on the nominal mass of an MS1 bin only, it is impossible to determine the chemical identity of a selected ion in a single experiment. For the MS1 bins of m/z 230, 231, and 189, no MS2 data were generated and no putative identification can be suggested. We have shown previously that DIMSn with our instrumentation allows MS2 product ion spectra for selected MS1 features to be checked manually to identify unique MS1 ion species by their fragmentation pathway (Koulman et al., 2007b). Here, we developed a computational method to utilize the fragmentation data from all the samples where MS2 data are available and circumvent manual comparison of individual spectra from different samples. MS2 Data Analysis and the Identification of Selected MS1 Ions As noted above, MS1 bins of different m/z could arise from the same metabolite due to isotopic ions, hydrogen transfers, or salt adducts. To identify a metabolite we need to first identify the relevant monoisotopic (12C, 1H, 14N, 16O) MS1 bin. This can be partially addressed using correlation analysis (Enot et al., 2006) as bins deriving from the same metabolite should be highly correlated, and in the mass range we are investigating, the monoisotopic MS1 bin will be of highest intensity. Thus, to assist in the identification of ions in the significant MS1 bins, we have considered concurrently correlated MS1 bins of adjacent mass (possible isotopologues) as well as MS1 bins corresponding to salt (e.g. K+ and Na+) adducts. We have also compared their MS2 product ion spectra as an aid to identifying isotopologues, adducts, and binning anomalies. Analysis of the MS2 data can also assist in addressing the alternative scenario, namely, that any one MS1 bin (a nominal unit m/z) is also likely to contain signals for a number of different metabolites not resolved by instrument resolution (and also binning artefacts). If the MS1 bin of a nominal m/z contains ions from different metabolites in different samples, or from the same metabolites but in different concentrations, then the MS2 product ion spectra are likely to differ between samples. Thus we have developed a method for automated comparison of MS2 data across a sample set to investigate ion homogeneity within selected MS1 bins. The method is based on the modified Manhattan distance as a measurement of the similarity of MS2 spectra from ions in a given parent MS1 bin. The procedure is described in detail in “Materials and Methods.” In brief, MS2 data for a parent MS1 bin of interest were pairwise compared between samples. Only the 20 most intense fragment ions in each MS2 spectrum were used for the comparison. The sum of the absolute values of the difference in normalized intensities was used as a distance score. From a set of pairwise differences, a distance matrix was obtained for statistical classification (hierarchical clustering or multidimensional scaling [MDS], etc.) to assess the homogeneity of each MS1 bin. For most MS1 bins, no distinct groups were seen, indicating that the MS2 spectra were consistent, and thus these MS1 bins are homogeneous and likely to be dominated by a single ion species. However, there were a number of MS1 bins for which different MS2 spectral patterns were observed for different samples. The differences between MS2 spectra in samples can be visualized with clustering analysis methods such as hierarchical clustering or MDS. MDS preserves the distance metric, and the cluster structures are revealed in different directions in the manner of principal component analysis (Lattin et al., 2003). The m/z 209 MS1 bin, which showed significant differences in ion abundance between E+/E− in the immature tissues (see the plot in Supplemental Fig. S2), also exhibited different MS2 patterns in E+ and E− samples (Fig. 2 Figure 2. Open in new tabDownload slide The clustering of MS2 spectra derived from the parent MS1 bins m/z 209 and m/z 555 by MDS based on modified Manhattan distances, suggesting there are different MS2 spectral patterns in E+ and E− groups. Figure 2. Open in new tabDownload slide The clustering of MS2 spectra derived from the parent MS1 bins m/z 209 and m/z 555 by MDS based on modified Manhattan distances, suggesting there are different MS2 spectral patterns in E+ and E− groups. , premz 209, where premz means precursor m/z in MS2 plots). Inspection of individual MS2 spectra from the MS1 bin m/z 209 (Fig. 3 Figure 3. Open in new tabDownload slide Plots of MS2 spectra derived from the parent MS1 bin m/z 209 in E− immature tissue (spectra A and B) and E+ blade tissue (spectra C and D) showing different relative intensities of product ions indicative of different metabolite compositions within this bin in the two classes of samples. MS2 data were not obtained for other samples. Figure 3. Open in new tabDownload slide Plots of MS2 spectra derived from the parent MS1 bin m/z 209 in E− immature tissue (spectra A and B) and E+ blade tissue (spectra C and D) showing different relative intensities of product ions indicative of different metabolite compositions within this bin in the two classes of samples. MS2 data were not obtained for other samples. ) suggests there are at least two metabolites within the m/z 209 MS1 bin present in different concentrations in the E+ and E− samples (e.g. fragment ions m/z 191 and 192; in comparison with m/z 149, 177, and 181). The MS2 spectra for another significant MS1 bin m/z 554 and the MS1 bin of adjacent mass m/z 555 (see the following discussion) also showed different patterns between E+ and E− samples (Fig. 2, premz 555). See Supplemental Figure S4 for the detailed MS2 spectra of m/z 555. Many distance metrics have been proposed to measure the similarity of spectra such as the dot product (Stein and Scott, 1994) and correlation-based distance metrics such as 1-correlation coefficient or 1-cosine (Tabb et al., 2003). We observed that fragment masses in MS2 spectra often showed mismatches between samples, and major fragment masses needed to be treated individually. The top 20 ions in each MS2 spectrum were retained and compared in this study, but this number could be extended or decreased to any arbitrary number. However, McLafferty et al. (1999) reported that 18 peaks were 97% as effective as 150 peaks for searching and comparing electron impact mass spectra. In standard practice of chemical analysis, only a few major MS2 product ions are used for confirmation of the identity of the parent MS1 species (Allwood et al., 2006; Koulman et al., 2007b). The predominant component of the m/z 248 MS1 bin in the endophyte-infected samples is peramine, which is a known fungal alkaloid. Peramine has a guanidinium moiety that undergoes distinctive neutral losses of 17 and 42. Its MS2 product ion spectrum is in accordance with previous findings (Koulman et al., 2007a); see also Supplemental Figure S7 in which m/z 248 is used as an example for MS2 data handling. The MS2 fragmentation pattern of the m/z 205 MS1 bin showed a clear water loss. Weakly basic metabolites such as alcohols are prone to form sodium adducts rather than [MH]+ ions (Jemal et al., 1997). We propose the actual nominal mass of the metabolite to be 182 (i.e. m/z 205 is [MNa]+). A logical candidate is mannitol or a related sugar alcohol. To test this hypothesis, we infused a water solution of mannitol into the mass spectrometer and observed a sodiated ion of m/z 205 with a highly similar MS2 spectrum to that of the m/z 205 MS1 bin in the endophyte-infected samples (Supplemental Fig. S3). However, as there are several naturally occurring hexitols (10 possible stereoisomers) with similar MS2 product ion spectra (based on data from triple quadrupole MS; see www.hmdb.ca and www.massbank.jp), the MS2 spectrum may be derived from a combination of several unresolved sugar alcohols in the m/z 205 MS1 bin. No direct fragmentation data are available for the m/z 335 MS1 bin that was detected at higher abundance in endophyte-free tissue (Fig. 1, m/z 335). However, consideration of MS1 bins of adjacent masses suggested the ions of m/z 335 are mainly isotopologues of the ryegrass alkaloid perloline. The m/z 335 MS1 bin is highly correlated with the MS1 bins of m/z 333 (r = 0.86, r is the Pearson's correlation coefficient, thereafter) and 334 (r = 0.93). The major ion detected at m/z 333 in positive ESI MS is assigned as the anhydrocation perloline (C20H17N2O3 +), with predicted isotopologue ions at m/z 334 (13C1 and 15N1) and m/z 335 (13C1, 15N1, 13C2, 15N2, and 18O1). The expected relative intensities of m/z 333, 334, and 335 are 1:0.24:0.03. The MS1 bins of m/z 333, 334, and 335 were observed to have a mean relative intensity of 1:0.37:0.07. The measured ratios show higher abundances for the higher mass ions than the theoretical prediction, which suggests ions from additional compounds have also been detected in the m/z 335 MS1 bin. Thus, although modeling isotopic distribution has been attempted for high resolution MS data (Böcker et al., 2006), for low resolution infusion MS data this may be confounded by interfering components isobaric with isotopologue peaks. The m/z 554 MS1 bin is correlated with the m/z 555 MS1 bin with r = 0.72. MS2 product ion spectra of m/z 554 were available only from four E+ samples and were very similar to the MS2 product ion spectra of m/z 555 in E+ samples (m/z 555 represents a different compound in E− samples as noted above; see Fig. 2; Supplemental Fig. S4). For both MS1 bins, the MS2 spectra in E+ samples show a series of product ions with a higher m/z than the parent ion (Supplemental Fig. S4), suggesting this is a doubly charged ion. Manual examination of these ions showed that the parent ion occurred at m/z 554.5 and its monoisotopologue at m/z 555.1. Due to the limited precision of the mass spectrometer, the measured m/z varied between 554.22 and 554.55 and therefore caused binning problems with bins of unit m/z. The doubly charged state was confirmed by the occurrence of high mass product ions in the MS2 and MS3 data. There was a significant product ion of m/z 904.3 and several other high mass ions in the MS2 spectrum from m/z 554.5 and in the MS3 spectrum from its major MS2 product of m/z 516.7 (Supplemental Fig. S4, a and b). The exact structure of the compound remains to be elucidated, but the complex pattern of product ions suggests that it is a cyclic oligomer of amino acids. Differentially expressed ions in E+ versus E− immature leaves were observed in MS1 bins of m/z 209, 297, 223, and 230 (230 is also different in E+/E− sheaths). MS2 spectra for the m/z 297 MS1 bin were observed in only two samples. The dominant product ions were of m/z 104,105, 237, and 238. This occurrence of pairs of fragment ions in the MS2 spectrum suggested that the m/z 297 MS1 bin comprised isotopologues of ions in the m/z 296 bin, and the m/z 297 MS1 bin was highly correlated with the m/z 296 MS1 bin with r = 0.82. The m/z 296 MS1 bin abundance is higher in endophyte-free samples and its MS2 spectrum showed a dominant m/z 104 ion as well as a clear m/z 59 loss. The MS3 spectrum of the m/z 104 ion showed a major fragment of m/z 60. These fragmentations are all highly indicative of a choline group (http://metlin.scripps.edu). This appears to be a novel compound, as no plant or fungal compounds with a corresponding mass and a choline group have been reported. One possibility is a 5-hydroxyferulyl analog of sinapine. We also remain uncertain about the chemical identity of the major metabolites detected in the m/z 209 and 223 MS1 bins, although MS2 product ion spectra (data not shown) were obtained in this study. Correlation Network Analysis of MS1 Bins Feature selection based on statistical ranking or machine learning algorithms is an important step in high-throughput data analysis. However, no golden rules exist for choosing a cutoff of P values or ranking scores and alternative approaches other than statistical ranking may be of use. Correlations among variables are sometimes considered as redundancy and often one feature (variable) is selected from a correlative group for further analysis (Zou and Hastie, 2005). However, correlations between MS1 bins deriving from different metabolites may provide insights into the functional dependency of these metabolites. With the aid of network analysis tools (Carey et al., 2005), correlation (or relevance) networks (Butte et al., 2000) among all the measured MS1 bins in all the samples were investigated. The correlation networks constructed in this way should reveal when a group of MS1 bins exhibit the same pattern of relative concentration (ion abundance) across samples. Based on the criterion of r > 0.9, many isolated correlation units were found to be composed of MS1 bins of adjacent mass, which are likely to be due to natural isotopologues. A large highly connected subgraph (clique) in the network was identified with 12 nodes (Fig. 4 Figure 4. Open in new tabDownload slide A group of highly correlated MS1 ions identified by correlation network analysis. The ions with the same gray scale are the same metabolites with different m/z due to the presence of natural isotopologues or salt adducts. Figure 4. Open in new tabDownload slide A group of highly correlated MS1 ions identified by correlation network analysis. The ions with the same gray scale are the same metabolites with different m/z due to the presence of natural isotopologues or salt adducts. ). In this subgraph component, some correlations between these MS1 bins are due to naturally occurring isotopes. The m/z 543, 544, 545, and 546 MS1 bins belong to one group, the m/z 705 and 706 MS1 bins to another, and m/z 867, 868, 869, and 870 MS1 bins to a third group. That these subgroupings (highlighted by different gray scale in Fig. 4) are due to isotopologues was also supported by MS2 spectral information, as within each group the MS2 spectra for the higher mass MS1 bins were similar to that from the lowest mass (monoisotopic) MS1 bin but with additional isotopologous fragments. The core correlation is between the three most intense MS1 bins of the lowest mass in each group, corresponding to the monoisotopic ions (m/z: 543, 705, and 867; see Table I). These three MS1 bins differ by a mass of 162, and this corresponds to the mass of a hexose (180) − H2O. The MS2 and MS3 data showed consecutive losses of 162 from the high mass ions (Supplemental Fig. S5a). Ions of these m/z ratios have been reported by Enot et al. (2006) for potassiated fructan oligomers detected in DIMS of genetically modified potatoes (Solanum tuberosum; [504K]+, [666K]+, and [828K]+; potassiated trihexose, tetrahexose, and pentahexose, respectively). Perennial ryegrass is known to produce a range of fructan oligomers from degree of polymerization (DP) 3 to >8 (Pavis et al., 2001), and the identification of these MS1 bins as deriving from fructan oligomers was supported by comparison of MS2 and MS3 spectra with those obtained by infusion and MS/MS analysis of aqueous KCl solutions of 1-kestose, 1,1-tetrakestose, and 1,1,1-pentakestose (Supplemental Fig. S5b). We considered the possibility that the two other MS1 bins m/z 779 and 941 in the correlation network might derive from glycerol adducts of the oligosaccharides, as they differed in mass from the m/z 705 and 867 species by 74 units. Glycosylglycerides have recently been reported by Yamamoto et al. (2006) as synthetic products of kojibiose phosphorylase from Thermoanaerobacter brocki. However, the MS2 spectrum of the m/z 779 and 941 species in the plant extracts showed in each case only a neutral loss of 74, while synthetic glucosyl-, maltosyl-, and maltotriosylglycerol showed neutral losses of 92 and 162 on MS/MS analysis. Further, m/z 779 and 941 ions were also observed in the DIMSn profiles of 1,1-tetrakestose and 1,1,1-pentakestose, respectively, in aqueous KCl (above), and were accompanied by ions of lower intensity of m/z 781 and 943, respectively, in the DIMSn profiles of both the standard solutions and plant extracts. These higher mass ions fragmented with a sole neutral loss of 76. In each case the product ion underwent subsequent MS fragmentation as for the potassiated oligosaccharide. As neutral losses of 74 and 76 correspond to the two chlorine isotopologues of KCl, we conclude the m/z 779 and 941 species are KCl cluster adducts of the potassiated oligosaccharides of the m/z 705 and 867. Similar adduct ions were present for the potassiated trihexose, although they were not detected as part of the correlation network. The levels of the oligohexoses were low in the blades and high in immature tissue and present at intermediate levels in sheath tissue (Fig. 5 Figure 5. Open in new tabDownload slide A plot of raw ion abundance of five correlated MS1 bins (represented by m/z 543, 705, 867, 779, and 941) showing that these metabolites accumulate to higher levels in immature leaves, lower levels in blade, and intermediate levels in sheath tissue. Figure 5. Open in new tabDownload slide A plot of raw ion abundance of five correlated MS1 bins (represented by m/z 543, 705, 867, 779, and 941) showing that these metabolites accumulate to higher levels in immature leaves, lower levels in blade, and intermediate levels in sheath tissue. ). When considering the endophyte effect, concentrations of the oligosaccharides were significantly higher in the endophyte-infected sheaths by a simple t test, with P values of 0.0082, 0.0048, and 0.0075 for the m/z 543, 705, and 867 MS1 bins, respectively. However, there were no significant (P values >0.05) endophyte infection effects in immature leaf and blade. DISCUSSION Metabolite Identification and Measurement The identification of metabolites from raw signals detected by mass spectrometers is a challenging task in metabolomics that still demands considerable effort (Schauer and Fernie, 2006). Two types of MS technologies are in general use for high-throughput metabolomics analyses. One type is high-accuracy MS using ICR-MS or time-of-flight MS (Dettmer et al., 2007). Highly accurate m/z measurements narrow down the search space by providing a short list of chemical formulae (elemental compositions), although without additional isotope abundance data this list may remain extensive (Kind and Fiehn, 2006). The other type exploited in metabolomics is tandem MS (MS/MS or MSn) using an ion trap that can provide fragmentation data on the initial MS1 ions, although in practice this capacity is often foregone (Enot et al., 2006). As demonstrated here, these fragmentation data are useful for the elucidation and classification of chemical structures. Technologies combining these two features, e.g. ion trap with FT-ICR-MS, are also available to provide high mass resolution MS1 profiles and information on fragmentation patterns. However, applying this combination to obtain high resolution data on both MS1 and MS2 ions for large numbers of samples is impractical due to the slow scan speeds required by the FT-ICR-MS. All of these technologies generate complex data sets and there are many steps in translating raw signals into chemical entities. With access to the raw data now readily available in standard formats such as mzXML (Pedrioli et al., 2004), novel or improved algorithms can be employed in many steps of data analysis, such as data preprocessing (including baseline detection and removal, peak detection, peak, or retention time alignment, etc.) and inference of the identity of components (e.g. Listgarten and Emili, 2005; for a recent review of LC-MS data processing for metabolomics and currently available software, see Katajamaa and Orešič, 2007). We recently applied direct-infusion ESI MS using DIMSn to determine metabolic differences between endophyte-infected and endophyte-free ryegrass seed samples (Koulman et al., 2007b). In this study, we have extended this approach by developing tools to analyze the raw MS data from DIMSn and to compare MS2 spectra derived from the same parent MS1 bin from different samples. This has enabled us to handle the collected data appropriately. Rather than seeking alignment in the time domain as addressed by programs such as XCMS and MZmine, our software bins the data into unit m/z bins and finds the median intensity in each m/z bin over the course of the infusion. The challenges of mass alignment and binning of data collected at high mass resolution (e.g. Hansen and Smedsgaard, 2004) are also much less for data collected at unit m/z resolution. Developing methods for automating the handling of MS2 data has enabled us to determine if the assignment of MS1 signal variations to treatment effects on a specific metabolite is justified, as it has allowed us to distinguish whether these MS1 signals were derived from the same metabolite(s) in all the samples or whether there were different metabolites in different samples detected within the same MS1 bin. For chemical identification, an MS2 product ion spectrum derived from an isotopically and chemically homogenous MS1 bin is desirable. An MS2 spectrum derived from an MS1 bin comprising a mixture of isotopologue ions will show an anomalous pattern, as noted above for the m/z 297 MS1 bin. Thus prior to investigating the MS2 data, it is useful to screen candidate MS1 bins for the existence of highly correlated MS1 bins of adjacent mass and higher intensity that are likely candidates for the monoisotopic species. Correlation analysis can also reveal the presence of ESI adducts such as the [K2Cl]+ cluster adducts reported here. The development of software to automate the discovery of isotopologues and adducts is an area of current active research (Tautenhahn et al., 2007). While facilities for comparison of MSn data (ion trees) and construction of libraries are available in commercial software (e.g. MassFrontier), further refinement and extension of the tool developed here to automate the construction of MSn libraries to facilitate metabolite identification would be a valuable tool for the analysis of DIMSn data. Metabolites have diverse physical and chemical properties and a wide range of concentrations in a biological system, so any single analytical technique cannot detect all the metabolites of biological relevance. Using DIMSn, we have identified or classified a number of metabolites known to be present in endophyte-infected grass samples such as peramine and a sugar alcohol putatively annotated as mannitol (but we cannot exclude other sugar alcohols). Other well-known metabolites, e.g. the alkaloids lolitrem B and ergovaline, although of high biological significance were not detected in this experiment. Indolediterpenes like lolitrem B are lipophilic and not sufficiently extracted by the extraction solvents used in this study. Ergopeptides (like ergovaline) are usually present at very low concentrations in the symbiotum and their MS signals are within the noise range of DIMSn data. Therefore, the analysis of these classes of metabolites requires the deployment of dedicated approaches (Lehner et al., 2005; Spiering et al., 2005). In this study we only used positive ionization and only one type of extraction procedure. We believe that alternative extraction procedures and ionization methods would deliver additional information on other classes of metabolites. Quantitation in infusion ESI MS is subject to signal suppression or enhancement in the source (see Dettmer et al., 2007), and ionization from an infused mixture is likely to be selective and dependent on the ability of a molecule to capture a charge in the source. Thus the detection of species such as the peramine and perloline cations and the doubly charged putative peptide ion is not unexpected, and other species less prone to forming cations are likely to have been underrepresented in the profile. Developments in nanoscale ESI may provide improved performance in this regard. The experiments described here were carried out with a standard capillary and flow rates of 5 μL/min. Nanospray technology utilizing very low flow rates (<20 nL/min) can reduce and perhaps eliminate analyte suppression (Schmidt et al., 2003) and may provide a less biased profile. An implementation in a microchip-mounted microfluidic device has shown promise for drug metabolite discovery (Trunzer et al., 2007) and may provide advantages for metabolomics. The other factor confounding quantitation in ion trap DIMSn is the presence of multiple components within each 1 m/z bin. Thus, while the endophyte effect on the m/z 248 MS1 bin can be attributed to peramine, the differences in intensity between tissue types (Fig. 1) appear to derive from the unknown plant components also detected in this bin. Concentrations of peramine in these samples estimated by HPLC with photo diode array detection (L. Johnson, unpublished data) were similar in the three tissue types as reported by Spiering et al. (2005). Although we have clearly demonstrated the usefulness of fragmentation data for the classification and structural elucidation of metabolites, the method is of limited use for characterizing metabolites that do not show a fragmentation (e.g. m/z 230, 189). For such metabolites the MS1 data provide a lead to further investigation using other methods. Indeed for all putative novel metabolites, additional data such as accurate mass MS, and targeted isolation and structure elucidation by, for example, NMR spectroscopy is necessary for their complete chemical characterization. Biological Implications of Identified Metabolites Several metabolites identified in this study have interesting implications for the metabolic regulation of the perennial ryegrass-endophyte symbiotum. As discussed in detail above, the hexitol (m/z 205) present in endophyte-infected plants only is probably mannitol. Mannitol appears to be a very common polyol in fungi (Lewis and Smith, 1967) and has been reported to accumulate in endophyte-infected tall fescue (Richardson et al., 1992) and perennial ryegrass plants (Harwood, 1954; Johnson et al., 2006; Rasmussen et al., 2008). Although mannitol has been implicated as an osmoprotectant in the resurrection plant Myrothamnus flabellifolia (Bianchi et al., 1993) and in transgenic Arabidopsis (Arabidopsis thaliana) expressing a celery (Apium graveolens) Man-6-P reductase (Sickler et al., 2007) as well as in Nicotiana tabacum expressing a mannitol-1-P dehydrogenase (Karakas et al., 1997), a study in tall fescue indicates that mannitol levels in endophyte-infected plants are not increased under drought stress (Richardson et al., 1992). A recent review (Solomon et al., 2007) also questions this role for mannitol as well as other claimed functions like fungal carbohydrate storage (Voegele et al., 2005) or NADPH regeneration (Hult and Gatenbeck, 1978; Hult et al., 1980). Solomon et al. (2007) conclude that the role and requirements for mannitol seem to differ depending on the species of fungus. In Aspergillus niger, mannitol is involved in conidial oxidative and high temperature stress protection (Ruijter et al., 2003), and in the wheat (Triticum aestivum) pathogen Stagonospora nodorum it is required for asexual sporulation (Solomon et al., 2006). Clearly, more studies are needed to understand the function of mannitol in endophyte-infected grasses. Peramine (m/z 248) has been shown to be the likely agent to confer improved insect resistance to endophyte-infected plants affecting Argentine stem weevil and a range of other insects (Rowan and Gaynor, 1986; Latch, 1993; Rowan, 1993; Rowan and Latch, 1994). Recently, it was shown that peramine is produced by an endophyte-specific two-module nonribosomal peptide synthetase (perA) and that an Epichloë festucae mutant deleted for perA lacks detectable levels of peramine (Tanaka et al., 2005). It was also shown that plant material containing this mutant endophyte was as susceptible to Argentine stem weevil feeding as endophyte-free plants, demonstrating unambiguously that peramine confers resistance to this insect. Peramine is also the most abundant alkaloid produced by this endophyte in infected plants; its concentration is usually an order of magnitude higher than for the other endophyte-specific alkaloids (Spiering et al., 2005) and it is detectable in plant fluids from cut leaf and in guttation fluid (Koulman et al., 2007a). Perloline (m/z 333), a diazaphenanthrene alkaloid, is produced by the grass plant and has been isolated from both ryegrass and tall fescue plants (Grimmett and Waters, 1943; Jeffreys, 1964; Bush and Jeffreys, 1975). Our results suggest that perloline concentrations are reduced in endophyte-infected mature blades and sheaths; the mechanism for this effect remains to be elucidated. Not much is known about the biosynthesis or function of perloline, although it has been implicated in effects on fall armyworm (Spodoptera frugiperda JE Smith) performance (Salminen et al., 2005) and to stimulate prolactin secretion in rats (Strickland et al., 1992). Earlier reports on the function of perloline, such as causing ryegrass staggers, are questionable due to the possible presence of endophytes in the studied material unknown at the time (Fairbourn, 1962; Aasen et al., 1969). The putative oligopeptide (m/z 554.5) identified in this study accumulates exclusively in endophyte-infected tissues and is therefore most probably an endophyte-produced metabolite. Recently, a novel cyclic peptide, epichlicin, inhibiting spore germination of Cladosporidium phlei, a pathogenic fungus of timothy grass (Phleum pratense), was isolated from timothy grass infected with Epichloë typhina (Seto et al., 2007), a relative of N. lolii investigated in this study. Oligopeptides have been isolated from fungal endophytes previously, e.g. leucinostatin A, a phytotoxic, anticancer, and antifungal peptide (Arai et al., 1973), and from Acremonium sp., a fungus infecting Taxus baccata (Strobel et al., 1997). This mycotoxin causes necrotic symptoms in nonhost plants, presumably because these plants, unlike T. baccata, are not able to transform it into the less toxic leucinostatin A-β-di-O-glucoside (Strobel and Hess, 1997; Tan and Zou, 2001). The antimicrobial cyclic echinocandin peptides have been isolated from endophytic Cryptosporiopsis sp. and Pezicula sp. in Pinus sylvestris and Fagus sylvatica (Noble et al., 1991) and the antifungal cyclopeptide cryptocandin from the endophytic Cryptosporiopsis compared with quercina of redwood (Strobel et al., 1999). We are currently isolating the oligopeptide identified in this study from endophyte-infected perennial ryegrass to elucidate its structure and to test its potential antimicrobial activity. Correlation Network Analysis and Its Biological Implications Correlation analysis of metabolites has been used previously to explore the functional dependency of metabolites, and it was shown that this type of analysis allowed, for example, the reconstruction of the metabolic pathway leading to the biosynthesis of glucosinolates in Arabidopsis (Keurentjes et al., 2006). It has been proposed that the construction of correlation networks based on metabolic fingerprinting might help to uncover underlying enzymatic reaction networks (Steuer et al., 2003), although other origins of correlations between metabolites within a physiological state have also been discussed (Camacho et al., 2005). However, in this study comparing different plant tissues and endophyte infection status, physiological differences are likely to be the dominant factor. In this study we have identified three MS1 bins representing monoisotopic ions of different metabolites that correlate significantly in our sample set. Mass fragmentation indicates that these metabolites are potassiated tri-, tetra-, and pentahexosides and their identification as fructans of DP 3, 4, and 5 was supported by the comparison with DIMSn of solutions of standards in aqueous KCl. Many cool-season C3 grasses accumulate fructans (Suc derived Fru polymers) as storage carbohydrates in their vegetative tissue, especially in mature sheaths (Pollock and Cairns, 1991). The genera Lolium and Festuca accumulate appreciable amounts of low DP fructans belonging to the inulin series, inulin neoseries, and levan neoseries, which differ in the position of Glc (terminal or internal) and the linkage type of Fru residues (β2,1 or β2,6; Pollock, 1982; Pavis et al., 2001). It was also shown that the proportion of low DP fructans (DP < 6) was more prominent in bases of elongating leaves than in leaf sheaths, and that mature leaf blades accumulate predominantly 6G-kestotriose and 1- and 6G-kestotetraose. The limited MSn data obtained here do not provide direct information on linkage and branching type of these Fru-containing polymers, but differences in the relative intensity of product ions in the MS2 and MS3 spectra between extracts and standards (Supplemental Fig. S5, a and b) may reflect the mixed isomer composition of the plant fructans. Recent developments in the elucidation of carbohydrate structures by MSn without chemical derivatization (e.g. Fang and Bendiak, 2007) suggest more extensive MSn analysis may provide additional structural information. As was shown previously (Rasmussen et al., 2007, 2008), endophyte infection resulted in higher levels of some of the sugars, which might indicate that the increased sink strength in the infected tissue results in a higher turnover of high DP fructans with a concomitant increase in low DP oligosaccharides. Although the exact mechanism for this pattern of accumulation remains to be elucidated, it has been documented (for review, see Chalmers et al., 2005) that the base of youngest leaves and the sheath of the more mature leaves represent the organs where fructosyltransferase activities, fructan accumulation, and remobilization in perennial ryegrass is most active, and where several fructan metabolism genes are expressed. CONCLUSION Our results extend our current knowledge on the metabolites involved in the symbiosis of the fungus N. lolii and its host perennial ryegrass. Using unbiased metabolite profiling (DIMSn) and advanced data-mining strategies, we have been able to uncover a number of unexpected perturbations of the metabolome upon endophyte infection. Based on the MS1 spectra we have found several metabolites that were significantly different between endophyte-infected and endophyte-free samples. New methods for automated processing of MS2 data have proved useful in detecting whether ions in a unit m/z MS1 bin represent a single major component across a sample set, or a heterogeneous mixture. With the aid of the MS2 product ion spectra we could readily identify some MS1 ions on the top of the list such as the known metabolites peramine and mannitol. The analysis has also revealed some new metabolites that are present in endophyte-infected plants, such as putative cyclic oligopeptides, and plant compounds present at reduced levels in infected plants such as a novel putative choline derivative. The identification of unknown MS1 bins as being statistically significantly different in uninfected compared to infected tissues also provides justification for their further characterization using more targeted approaches. Linear correlation network analysis revealed the effect of the endophyte on a range of oligosaccharides, giving us new clues on how the endophyte utilizes plant carbohydrates. The methodology has proved to be a powerful tool for discovering leads to novel chemistry associated with the symbiosis, and these demand further chemical and biological investigation. MATERIALS AND METHODS Experimental Design and Sampling Clonal perennial ryegrass plants (Lolium perenne ‘Nui’), either infected with the fungal endophyte Neotyphodium lolii (strain Lp19) or endophyte free, were used in this study. Endophyte-free perennial ryegrass was obtained as described by Tanaka et al. (2005). A 2 × 3 factorial design was applied with endophyte-infected (E+) and endophyte-free (E−) plants, and three tissue types, namely, immature leaf, blade, and sheath. Four individual tillers, either all E+ or all E− perennial ryegrass, were planted in pots, to give four replicate pots of E+ and E− material. The three tissue types were dissected from each of the plants in each pot and pooled for analysis (see also Supplemental Table S1 for sample description). Thus, 24 ryegrass samples in total were examined in this study. These plants were grown in a controlled environment chamber with 14-h daylength (653 μmol m−2 s−1 of light intensity), a temperature of 20°C day/10°C night, and supplied with a modified Hoagland nutrient solution. The tissue samples were harvested and immediately frozen in liquid nitrogen, and stored at −80°C for subsequent analysis. Direct-Infusion MS Plant tissue samples were ground using pestle and mortar in liquid nitrogen and stored at −80°C. Fifty milligrams of ground samples were extracted with 1.5 mL of MeOH. The extract was partitioned between water and dichloromethane. The aqueous phase was lyophilized and redissolved in 1.5 mL of MeOH. The infusion solvent (MeOH) was pumped at 20 μL min−1 flow to a T junction just in front of the ESI source where 5 μL min−1 MeOH with 2% formic acid was added. A 100-μL aliquot of each sample was injected using an autosampler. After 10 min a MeOH blank was injected and run at 200 μL min−1 flow rate for 3 min. A linear ion trap mass spectrometer (Thermo LTQ) coupled to a Thermo Finnigan Surveyor HPLC system was used. Thermo Finnigan Xcalibur software (version 1.4) was used for data acquisition. The mass spectrometer was set for ESI in positive mode. Samples were infused through a polyimide-coated glass capillary (0.1 mm i.d., 0.19 mm o.d.) at a flow rate of 5 μL/min. The spray voltage was 5.0 kV and the capillary temperature 275°C. The ion optics were tuned using paxilline. The flow rates of sheath gas, auxiliary gas, and sweep gas were set (in arbitrary units/min) to 20, 5, and 12, respectively. For the first 0.9 min after injection only MS1 spectra were recorded; for the period from 0.9 to 10 min the mass spectrometer was set up in data-dependent mode to collect one MS1 spectrum, followed by the isolation (2 m/z) and fragmentation (35% CE; relative collision energy) of the most intense ion from the MS1 spectrum, followed by the isolation (2 m/z) and fragmentation (35% CE) of the most intense ion from the MS2 spectrum. A new MS1 spectrum was then recorded, followed by the repetitive isolation (2 m/z) and fragmentation (35% CE) of the most intense ions from that MS1 spectrum and the most intense MS2 product ion. When an MS1 ion with a specific mass had been isolated and fragmented for the second time, it was placed on an exclusion list for the duration of the run. In total up to approximately 200 MS2 spectra were recorded in an average run. Samples of glucosyl-, maltosyl-, and maltotriosylglycerol (provided by H. Nakano, Osaka Municipal Technical Research Institute, Osaka) and samples of standard 1-kestose, 1,1-tetrakestose, and 1,1,1-pentakestose (Megazyme International Ireland Ltd.; 4 μg mL−1) in aqueous KCl (50 mm) were infused and analyzed under the similar conditions. Data Analysis The raw data (Xcalibur raw file, in centroid mode) were converted into mzXML data format (Pedrioli et al., 2004) using software ReAdw available from http://sashimi.sourceforge.net/software_glossolalia.html. mzXML is a standard data format for tandem mass spectrometric data and relatively easy to manipulate. MS1 Data Analysis All the MS1 scans were retrieved from mzXML and the original data could also be checked manually using the Thermo proprietary software Xcalibur. Given the 1 m/z resolution of the machine, we binned the data to unit nominal m/z. Thus in each sample, for a given ion, for example, m/z 248, all the measured m/z values (e.g. 247.98, 248.12, 248.35) were rounded to an integer value of 248 (equivalent to binning with 1 m/z width), and the median (rather than the average) of the abundance of corresponding ions within a sample was taken as a robust statistical estimate to reduce potential rounding (or binning) artefacts. The resulting bins are described here as MS1 bins. For each MS1 bin, the first 300 scans (see Supplemental Fig. S6) were removed because they were background signals from solvent (noise). For each MS1 bin, the median value of these first 300 scans was then used as a baseline value, and subtracted from the ion abundance values for subsequent scans. Any negative values (below the background noise) and weak signals (less than the 10% quantile) were removed. The median value of the ion abundance of all the remaining scans in each sample was used as the representative MS1 bin abundance for that sample. The ion abundance values for MS1 bins over the range m/z 150 to 1,000 were determined for each sample to generate an MS1 data matrix of 24 × 851 for statistical analysis. The abundance of each MS1 bin was normalized against the median of the observations in all the samples, using log2 [x(i)/median (x)], where vector x comprises the abundance measurements of each MS1 bin, and x(i) is the abundance of each individual treatment with i from 1 to 24. Empirical Bayes moderated t statistics (Smyth, 2004) were applied to identify MS1 ions that were differentially expressed between E+ and E− across the three developmental stages (immature leaf, blade, and sheath). The algorithms are implemented and available as R package Limma (Smyth, 2004). MS1 data have been provided as Supplemental Data Set S1. MS2 Data Analysis All the MS2 data were retrieved by querying the mzXML data. MS2 spectra derived from an MS1 bin in one sample (e.g. 248.35, 248.39; see Supplemental Fig. S7) were merged by rounding to nominal m/z MS2 bins and assigning the median abundance value for each bin. For each sample, only the top 20 most abundant ions (MS2 bins) derived from an MS1 bin were retained for comparisons in this report. For a given parent MS1 bin, all derived MS2 spectra in each sample, if available, were pairwise compared based on a customized distance metric. The measurement of similarity of MS2 spectra is complicated not only by variation in ion abundance, but also by the occurrence of different fragment ions in spectra from the same MS1 bin in different samples and by carry over from adjacent MS1 bins of high intensity (as for isotopologues) as the isolation width of the ion trap was set to a range of 2 m/z for efficient capture and fragmentation of ions. The procedure for the distance metric of two MS2 spectra is as follows: (1) normalize each spectrum to its maximum abundance value and sort each spectrum based on its intensity, up to 20 most intense fragment ions are retained; (2) if the number of MS2 bins is still different, low intensity ions in the longer spectrum are truncated; (3) for the matched nominal ions (MS2 bins of same nominal m/z) occurring in both spectra, the Manhattan distance \(d{=}{\sum_{\mathrm{i}}^{\mathrm{k}}}{\vert}x_{\mathrm{i}}{-}y_{\mathrm{i}}{\vert}\) is calculated, where the two spectra are denoted as x = (x, …, x m) and y = (y, …, y n), and k is the number of shared MS2 bins [with m, n ≤ 20; k < min(m, n)]. For any unmatched MS2 bins, the normalized intensity is added to the distance. Step 3 provides a simplified way for m/z alignment. A similar idea was also employed by Zhang et al. (2005). The calculated pairwise distances for all samples were used for clustering analysis. All the software functions for handling and analysis of MS1and MS2 data, and correlation network analysis were written in R2.5 (R Development Core Team, 2007) based on a number of R packages. Supplemental Data The following materials are available in the online version of this article. Supplemental Figure S1. PCA analysis of normalized MS1 data. Supplemental Figure S2. Abundance of MS1 bins in treatment groups. Supplemental Figure S3. MS2 spectra of parent MS1 m/z 205 [182Na]+ and mannitol standard. Supplemental Figure S4. MS2 and MS3 spectra of parent m/z 555. Supplemental Figure S5. MS2 and MS3 spectra of potassium adducts of oligosaccharide and oligokestose standards. Supplemental Figure S6. Intensity plot of the nominal ion m/z 248 across all scans. Supplemental Figure S7. Spectral processing of MS2 using nominal MS1 ion m/z 248. Supplemental Table S1. Designation and description of experimental material. Supplemental Data Set S1. MS1 data matrix. ACKNOWLEDGMENTS We acknowledge Karl Fraser for the operation and maintenance of the mass spectrometer and the DIMSn analysis of fructan standards; Mike Christensen and Catherine Tootil for the maintenance of plant materials; and Hirofumi Nakano at Osaka Municipal Technical Research Institute, Osaka, for providing synthetic glucosyl-, maltosyl-, and maltotriosylglycerol. We appreciate Drs. Brian Tapper and Silas Villas-Boas for reviewing the manuscript and providing useful aspects for discussion. LITERATURE CITED Aasen AJ, Culvenor CCJ, Finnie EP, Kellock AW, Smith LW ( 1969 ) Alkaloids as a possible cause of ryegrass staggers in grazing livestock. Aust J Agric Res 20 : 71 – 86 Crossref Search ADS Aharoni A, de Vos R, Verhoeven H, Maliepaard C, Kruppa G, Bino R, Goodenowe D ( 2002 ) Non-targeted metabolic profiling using fourier transform ion cyclotron mass spectrometry (FTMS). OMICS 6 : 217 – 234 Crossref Search ADS PubMed Allen J, Davey HM, Broadhurst D, Heald JK, Rowland JJ, Oliver SG, Kell DB ( 2003 ) High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nat Biotechnol 21 : 692 – 696 Crossref Search ADS PubMed Allwood JW, Ellis DI, Heald JK, Goodacre R, Mur LAJ ( 2006 ) Metabolomic approaches reveal that phosphatidic and phosphatidyl glycerol phospholipids are major discriminatory non-polar metabolites in responses by Brachypodium distachyon to challenge by Magnaporthe grisea. Plant J 46 : 351 – 368 Crossref Search ADS PubMed Arai T, Mikami Y, Fukushima K, Utsumi T, Yazawa K ( 1973 ) A new antibiotic, leucinostatin, derived from Penicillium lilacinum. J Antibiot (Tokyo) 26 : 157 – 161 Crossref Search ADS PubMed Bianchi G, Gamba A, Limiroli R, Pozzi N, Elster R, Salamini F, Bartels D ( 1993 ) The unusual sugar composition in leaves of the resurrection plant Myrothamnus flabellifolia. Physiol Plant 87 : 223 – 226 Crossref Search ADS Böcker S, Letzel MC, Lipták Z, Pervukhin A ( 2006 ) Decomposing metabolomic isotope patterns. In P Bücher, BME Moret, eds, Proceedings of the Workshop on Algorithms in Bioinformatics, Vol 4175. Springer, Berlin, pp 12–23 Bush LP, Jeffreys JAD ( 1975 ) Isolation and separation of tall fescue and ryegrass alkaloids. J Chromatogr A 111 : 165 – 170 Crossref Search ADS Bush LP, Wilkinson HH, Schardl CL ( 1997 ) Bioprotective alkaloids of grass-fungal endophyte symbioses. Plant Physiol 114 : 1 – 7 Crossref Search ADS PubMed Butte AJ, Tamayo P, Slonim D, Golub TR, Kohane IS ( 2000 ) Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. Proc Natl Acad Sci USA 97 : 12182 – 12186 Crossref Search ADS PubMed Camacho D, de la Fuente A, Mendes P ( 2005 ) The origin of correlations in metabolomics data. Metabolomics 1 : 53 – 63 Crossref Search ADS Carey VJ, Gentry J, Whalen E, Gentleman R ( 2005 ) Network structures and algorithms in Bioconductor. Bioinformatics 21 : 135 – 136 Crossref Search ADS PubMed Chalmers J, Lidgett A, Cummings N, Cao Y, Forster J, Spangenberg G ( 2005 ) Molecular genetics of fructan metabolism in perennial ryegrass. Plant Biotechnol J 3 : 459 – 474 Crossref Search ADS PubMed Cheplick GP ( 2007 ) Costs of fungal endophyte infection in Lolium perenne genotypes from Eurasia and North Africa under extreme resource limitation. Environ Exp Bot 60 : 202 – 210 Crossref Search ADS Christensen MJ, Leuchtmann A, Rowan DD, Tapper BA ( 1993 ) Taxonomy of Acremonium endophytes of tall fescue (Festuca arundinacea), meadow fescue (Festuca pratensis) and perennial ryegrass (Lolium perenne). Mycol Res 97 : 1083 – 1092 Crossref Search ADS Clay K, Schardl C ( 2002 ) Evolutionary origins and ecological consequences of endophyte symbiosis with grasses. Am Nat 160 : S99 –S127 Crossref Search ADS PubMed Dettmer K, Aronov PA, Hammock BD ( 2007 ) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26 : 51 – 78 Crossref Search ADS PubMed Dunn WB, Overy S, Quick WP ( 2005 ) Evaluation of automated electrospray-TOF mass spectrometry for metabolic fingerprinting of the plant metabolome. Metabolomics 1 : 137 – 148 Crossref Search ADS Easton HS, Lane GA, Tapper BA, Keogh RG, Cooper BM, Blackwell M, Anderson MR, Fletcher L ( 1986 ) Ryegrass endophyte-related heat stress in cattle. In Proceedings of the New Zealand Grassland Association, Vol 57. New Zealand Grassland Association, Dunedin, New Zealand, pp 37–41 Enot DP, Beckmann M, Overy D, Draper J ( 2006 ) Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals. Proc Natl Acad Sci USA 103 : 14865 – 14870 Crossref Search ADS PubMed Fairbourn ML ( 1962 ) Alkaloid affects in vitro dry matter digestibility of Festuca and Bromus species. J Range Manage 35 : 503 – 504 Fang TT, Bendiak B ( 2007 ) The stereochemical dependence of unimolecular dissociation of monosaccharide-glycolaldehyde anions in the gas phase: a basis for assignment of the stereochemistry and anomeric configuration of monosaccharides in oligosaccharides by mass spectrometry via a key discriminatory product ion of disaccharide fragmentation, m/z 221. J Am Chem Soc 129 : 9721 – 9736 Crossref Search ADS PubMed Fletcher LR, Easton HS ( 1997 ) The evaluation of use of endophytes for pasture improvement. In CW Bacon, NS Hill, eds, Neotyphodium/Grass Interactions. Plenum Press, New York, pp 209–228 Gallagher RT, Hawkes AD, Steyn PS, Vleggaar R ( 1984 ) Tremorgenic neurotoxins from perennial ryegrass causing ryegrass staggers disorder of livestock: structure elucidation of Lolitrem B. J Chem Soc Chem Commun 9 : 614 – 616 Grimmett RE, Waters DF ( 1943 ) A fluorescent alkaloid in ryegrass (Lolium perenne L.). II. Extraction from fresh ryegrass and separation from other bases. NZ J Sci Tech 24 : 151B Hansen ME, Smedsgaard J ( 2004 ) A new matching algorithm for high resolution mass spectra. J Am Soc Mass Spectrom 15 : 1173 – 1180 Crossref Search ADS PubMed Harwood VD ( 1954 ) Analytical studies on the carbohydrates of grasses and clovers. VII. The isolation of D-mannitol from perennial ryegrass (Lolium perenne L.). J Sci Food Agric 5 : 453 – 455 Crossref Search ADS Hult K, Gatenbeck S ( 1978 ) Production of NADPH in the mannitol cycle and its relation to polyketide formation in Alternaria alternata. Eur J Biochem 88 : 607 – 612 Crossref Search ADS PubMed Hult K, Veide A, Gatenbeck S ( 1980 ) The distribution of the NADPH regenerating mannitol cycle among fungal species. Arch Microbiol 128 : 253 – 255 Crossref Search ADS PubMed Hunt MG, Rasmussen S, Newton PCD, Parsons AJ, Newman JA ( 2005 ) Near-term impacts of elevated CO2, nitrogen and fungal endophyte-infection on Lolium perenne L. growth, chemical composition and alkaloid production. Plant Cell Environ 28 : 1345 – 1354 Crossref Search ADS Jeffreys JAD ( 1964 ) 859. The alkaloids of perennial rye-grass (Lolium perenne L.). Part I. Perloline. J Chem Soc 4504 – 4512 Jemal M, Almond RB, Teitz DS ( 1997 ) Quantitative bioanalysis utilizing high-performance liquid chromatography/electrospray mass spectrometry via selected-ion monitoring of the sodium ion adduct [M + Na]+. Rapid Commun Mass Spectrom 11 : 1083 – 1088 Crossref Search ADS PubMed Johnson RD, Bassett S, Cao M, Christensen MJ, Gaborit C, Johnson LJ, Koulman A, Rasmussen S, Voisey C, Bryan G ( 2006 ) A multidisciplinary approach to dissect the molecular basis of the Neotyphodium lolii/ryegrass symbiosis. In CF Mercer, ed, Advances in Pasture Plant Breeding, Grassland Research and Practice Series No. 12. New Zealand Grassland Association, Dunedin, New Zealand, pp 107–114 Karakas B, Ozias-Akins P, Stushnoff C, Suefferheld M, Rieger M ( 1997 ) Salinity and drought tolerance of mannitol-accumulating transgenic tobacco. Plant Cell Environ 20 : 609 – 616 Crossref Search ADS Katajamaa M, Orešič M ( 2005 ) Processing methods for differential analysis of LC/MS profile data. BMC Bioinformatics 6 : 179 Crossref Search ADS PubMed Katajamaa M, Orešič M ( 2007 ) Data processing for mass spectrometry-based metabolomics. J Chromatogr A 1158 : 318 – 328 Crossref Search ADS PubMed Keurentjes JJB, Fu J, de Vos CHR, Lommen A, Hall RD, Bino RJ, van der Plas LHW, Jansen RC, Vreugdenhil D, Koornneef M ( 2006 ) The genetics of plant metabolism. Nat Genet 38 : 842 – 849 Crossref Search ADS PubMed Kind T, Fiehn O ( 2006 ) Metabolomic database annotations via query of elemental compositions: mass accuracy is insufficient even at less than 1 ppm. BMC Bioinformatics 7 : 234 Crossref Search ADS PubMed Koulman A, Lane GA, Christensen MJ, Fraser K, Tapper BA ( 2007 a) Peramine and other fungal alkaloids are exuded in the guttation fluid of endophyte-infected grasses. Phytochemistry 68 : 355 – 360 Crossref Search ADS PubMed Koulman A, Tapper BA, Fraser K, Cao M, Lane GA, Rasmussen S ( 2007 b) High-throughput direct-infusion ion trap mass spectrometry: a new method for metabolomics. Rapid Commun Mass Spectrom 21 : 421 – 428 Crossref Search ADS PubMed Krauss J, Harri SA, Bush L, Husi R, Bigler L, Power SA, Müller CB ( 2007 ) Effects of fertilizer, fungal endophytes and plant cultivar on the performance of insect herbivores and their natural enemies. Funct Ecol 21 : 107 – 116 Lane GA, Christensen MJ, Miles CO ( 2000 ) Coevolution of fungal endophytes with grasses: the significance of secondary metabolites. In CW Bacon, JF White, eds, Microbial Endophytes. Marcel Dekker, New York, pp 341–388 Latch GCM ( 1993 ) Physiological interactions of endophytic fungi and their hosts: biotic stress tolerance imparted to grasses by endophytes. Agric Ecosyst Environ 44 : 143 – 156 Crossref Search ADS Lattin J, Carroll JD, Green PE ( 2003 ) Analyzing Multivariate Data. Duxbury Applied Series, Thomson Learning, Pacific Grove, CA Lehner AF, Craig M, Fannin N, Bush L, Tobin T ( 2005 ) Electrospray[+] tandem quadrupole mass spectrometry in the elucidation of ergot alkaloids chromatographed by HPLC: screening of grass or forage samples for novel toxic compounds. J Mass Spectrom 40 : 1484 – 1502 Crossref Search ADS PubMed Leuchtmann A ( 1992 ) Systematics, distribution, and host specificity of grass endophytes. Nat Toxins 1 : 150 – 162 PubMed Lewis DH, Smith DC ( 1967 ) Sugar alcohols (polyols) in fungi and green plants. I. Distribution, physiology and metabolism. New Phytol 66 : 143 – 184 Crossref Search ADS Listgarten J, Emili A ( 2005 ) Statistical and computational methods for comparative proteomics profiling using liquid chromatography-tandem mass spectrometry. Mol Cell Proteomics 4 : 419 – 434 Crossref Search ADS PubMed Lyons PC, Plattner RD, Bacon CW ( 1986 ) Occurrence of peptide and clavine ergot alkaloids in tall fescue grass. Science 232 : 487 – 489 Crossref Search ADS PubMed Malinowski DP, Belesky DP ( 2000 ) Adaptations of endophyte-infected cool-season grasses to environmental stresses: mechanisms of drought and mineral stress tolerance. Crop Sci 40 : 923 – 940 Crossref Search ADS McLafferty FW, Staufferb DA, Lohb SY, Wesdemiotis C ( 1999 ) Unknown identification using reference mass spectra: quality evaluation of databases. J Am Soc Mass Spectrom 10 : 1229 – 1240 Crossref Search ADS PubMed Noble HM, Langley D, Sidebottom PJ, Lane SJ, Fisher PJ ( 1991 ) An echinocandin from an endophytic Cryptosporiopsis sp. and Pezicula sp. in Pinus sylvestris and Fagus sylvatica. Mycol Res 95 : 1439 – 1440 Crossref Search ADS Pavis N, Chatterton NJ, Harrison PA, Baumgartner S, Praznik W, Boucaud J, Prud'homme MP ( 2001 ) Structure of fructans in roots and leaf tissues of Lolium perenne. New Phytol 150 : 83 – 95 Crossref Search ADS Pedrioli PGA, Eng JK, Hubley R, Vogelzang M, Deutsch EW, Raught B, Pratt B, Nilsson E, Angeletti R, Apweiler R, et al ( 2004 ) A common open representation of mass spectrometry data and its application in a proteomics research environment. Nat Biotechnol 22 : 1459 – 1466 Crossref Search ADS PubMed Pollock CJ ( 1982 ) Oligosaccharide intermediates of fructan synthesis in Lolium temulentum. Phytochemistry 21 : 2461 – 2465 Crossref Search ADS Pollock CJ, Cairns AJ ( 1991 ) Fructan metabolism in grasses and cereals. Annu Rev Plant Physiol Plant Mol Biol 42 : 77 – 101 Crossref Search ADS Raamsdonk LM, Teusink B, Broadhurst D, Zhang N, Hayes A, Walsh MC, Berden JA, Brindle KM, Kell DB, Rowland JJ, et al ( 2001 ) A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat Biotechnol 19 : 45 – 50 Crossref Search ADS PubMed Rasmussen S, Parsons AJ, Bassett S, Christensen MJ, Hume DE, Johnson LJ, Johnson RD, Simpson WR, Stacke C, Voisey CR, et al ( 2007 ) High nitrogen supply and carbohydrate content reduce fungal endophyte and alkaloid concentration in Lolium perenne. New Phytol 173 : 787 – 797 Crossref Search ADS PubMed Rasmussen S, Parsons AJ, Fraser K, Xue H, Newman JA ( 2008 ) Metabolic profiles of Lolium perenne are differentially affected by nitrogen supply, carbohydrate content, and fungal endophyte infection. Plant Physiol 146 : 1 – 14 Crossref Search ADS Richardson MD, Chapman GW, Hoveland CS, Bacon CW ( 1992 ) Sugar alcohols in endophyte-infected tall fescue under drought. Crop Sci 32 : 1060 – 1061 Crossref Search ADS Rowan DD ( 1993 ) Lolitrems, peramine and paxilline: mycotoxins of the ryegrass/endophyte interaction. Agric Ecosyst Environ 44 : 103 – 122 Crossref Search ADS Rowan DD, Gaynor DL ( 1986 ) Isolation of feeding deterrents against Argentine stem weevil from ryegrass infected with the endophyte Acremonium loliae. J Chem Ecol 12 : 647 – 658 Crossref Search ADS PubMed Rowan DD, Latch GCM ( 1994 ) Utilization of endophyte-infected perennial ryegrasses for increased insect resistance. In CW Bacon, JF White, eds, Biotechnology of Endophytic Fungi in Grasses. CRC Press, Boca Raton, FL, pp 169–183 Ruijter GJG, Bax M, Patel H, Flitter SJ, van de Vondervoort PJI, de Vries RP, van Kuyk PA, Visser J ( 2003 ) Mannitol is required for stress tolerance in Aspergillus niger conidiospores. Eukaryot Cell 2 : 690 – 698 Crossref Search ADS PubMed Salminen SO, Richmond DS, Grewal SK, Grewal PS ( 2005 ) Influence of temperature on alkaloid levels and fall armyworm performance in endophytic tall fescue and perennial ryegrass. Entomol Exp Appl 115 : 417 – 426 Crossref Search ADS Sauer U, Heinemann M, Zamboni N ( 2007 ) Getting closer to the whole picture. Science 316 : 550 – 551 Crossref Search ADS PubMed Schardl CL ( 2001 ) Epichloë festucae and related mutualistic symbionts of grasses. Fungal Genet Biol 33 : 69 – 82 Crossref Search ADS PubMed Schardl CL, Leuchtmann A, Spiering MJ ( 2004 ) Symbioses of grasses with seedborne fungal endophytes. Annu Rev Plant Biol 55 : 315 – 340 Crossref Search ADS PubMed Schauer N, Fernie AR ( 2006 ) Plant metabolomics: towards biological function and mechanism. Trends Plant Sci 11 : 508 – 516 Crossref Search ADS PubMed Schmidt A, Karas M, Dülcks T ( 2003 ) Effect of different solution flow rates on analyte ion signals in nano-ESI MS, or: when does ESI turn into nano-ESI? J Am Soc Mass Spectrom 14 : 492 – 500 Crossref Search ADS PubMed Seto Y, Takahashi K, Matsuurai H, Kogami Y, Yada H, Yoshihara T, Nabeta K ( 2007 ) Novel cyclic peptide, epichlicin, from the endophytic fungus, Epichloë typhina. Biosci Biotechnol Biochem 71 : 1470 – 1475 Crossref Search ADS PubMed Sickler CM, Edwards GE, Kiirats O, Gao Z, Löscher W ( 2007 ) Response of mannitol-producing Arabidopsis thaliana to abiotic stress. Funct Plant Biol 34 : 382 – 391 Crossref Search ADS PubMed Smedsgaard J, Frisvad JC ( 1996 ) Using direct electrospray mass spectrometry in taxonomy and secondary metabolite profiling of crude fungal extracts. J Microbiol Methods 25 : 5 – 17 Crossref Search ADS Smith CA, Want EJ, O'Maille G, Abagyan R, Siuzdak G ( 2006 ) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching and identification. Anal Chem 78 : 779 – 787 Crossref Search ADS PubMed Smyth GK ( 2004 ) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 1: Article 3 Solomon PS, Waters ODC, Jörgens CI, Lowe RGT, Rechberger J, Trengove RD, Oliver RP ( 2006 ) Mannitol is required for asexual sporulation in the wheat pathogen Stagonospora nodorum (glume blotch). Biochem J 399 : 231 – 239 Crossref Search ADS PubMed Solomon PS, Waters ODC, Oliver RP ( 2007 ) Decoding the mannitol enigma in filamentous fungi. Trends Microbiol 15 : 257 – 262 Crossref Search ADS PubMed Spiering MJ, Lane GA, Christensen MJ, Schmid J ( 2005 ) Distribution of the fungal endophyte Neotyphodium lolii is not a major determinant of the distribution of fungal alkaloids in Lolium perenne plants. Phytochemistry 66 : 195 – 202 Crossref Search ADS PubMed Stein SE, Scott DR ( 1994 ) Optimization and testing of mass spectral library search algorithms for compound identification. J Am Soc Mass Spectrom 5 : 859 – 866 Crossref Search ADS PubMed Steuer R, Kurths J, Fiehn O, Weckwerth W ( 2003 ) Observing and interpreting correlations in metabolomic networks. Bioinformatics 19 : 1019 – 1026 Crossref Search ADS PubMed Strickland JR, Bailey EM, Abney LK, Oliver JW ( 1996 ) Assessment of the mitogenic potential of the alkaloids produced by endophyte (Acremonium coenophialum)-infected tall fescue (Festuca arundinacea) on bovine vascular smooth muscle in vitro. J Anim Sci 74 : 1664 – 1671 Crossref Search ADS PubMed Strickland JR, Cross DL, Jenkins TC, Petroski RJ, Powell RG ( 1992 ) The effect of alkaloids and seed extracts of endophyte-infected tall fescue on prolactin secretion in an in vitro rat pituitary perfusion system. J Anim Sci 70 : 2779 – 2786 Crossref Search ADS PubMed Strobel GA, Hess WM ( 1997 ) Glucosylation of the peptide leucinostatin A, produced by an endophytic fungus of European yew, may protect the host from leucinostatin toxicity. Chem Biol 4 : 529 – 536 Crossref Search ADS PubMed Strobel GA, Miller RV, Martinez-Miller C, Condron MM, Teplow DB, Hess WM ( 1999 ) Cryptocandin, a potent antimycotic from the endophytic fungus Cryptosporiopsis cf. quercina. Microbiology 145 : 1919 – 1926 Crossref Search ADS PubMed Strobel GA, Torczynski R, Bollon A ( 1997 ) Acremonium sp.—a leucinostatin A producing endophyte of European yew (Taxus baccata). Plant Sci 128 : 97 – 108 Crossref Search ADS Sumner L, Mendes P, Dixon R ( 2003 ) Plant metabolomics: large-scale phytochemistry in the functional genomics era. Phytochemistry 62 : 807 – 836 Tabb DL, MacCoss MJ, Wu CC, Anderson SD, Yates III Jr ( 2003 ) Similarity among tandem mass spectra from proteomic experiments: detection, significance, and utility. Anal Chem 75 : 2470 – 2477 Crossref Search ADS PubMed Tan RX, Zou WX ( 2001 ) Endophytes: a rich source of functional metabolites. Nat Prod Rep 18 : 448 – 459 Crossref Search ADS PubMed Tanaka A, Tapper BA, Popay A, Parker EJ, Scott B ( 2005 ) A symbiosis expressed non-ribosomal peptide synthetase from a mutualistic fungal endophyte of perennial ryegrass confers protection to the symbiotum from insect herbivory. Mol Microbiol 57 : 1036 – 1050 Crossref Search ADS PubMed Tautenhahn R, Böttcher C, Neumann S ( 2007 ) Annotation of LC/ESI-MS mass signals. In S Hochreiter, R Wagner, eds, Lecture Notes in Computer Science, Vol 4414. Springer, Berlin, pp 371–380 Tozuka Z, Kaneko H, Shiraga T, Mitani Y, Beppu M, Terashita S, Kawamura A, Kagayama A ( 2003 ) Strategy for structural elucidation of drugs and drug metabolites using (MS)n fragmentation in an electrospray ion trap. J Mass Spectrom 38 : 793 – 808 Crossref Search ADS PubMed Trunzer M, Graf D, Kiffe M ( 2007 ) Comparison of a two-dimensional liquid chromatography/mass spectrometry approach with a chip-based nanoelectrospray device for structural elucidation of metabolites in a human ADME study using a quadrupole time-of-flight mass spectrometer. Rapid Commun Mass Spectrom 21 : 937 – 944 Crossref Search ADS PubMed Voegele RT, Hahn M, Lohaus G, Link T, Heiser I, Mendgen K ( 2005 ) Possible roles for mannitol and mannitol dehydrogenase in the biotrophic plant pathogen Uromyces fabae. Plant Physiol 137 : 190 – 198 Crossref Search ADS PubMed Yamamoto T, Watanabe H, Nishimoto T, Aga H, Kubota M, Chaen H, Fukuda S ( 2006 ) Acceptor recognition of kojibiose phosphorylase from Thermoaerobacter brockii: syntheses of glycosyl glycerol and myo-inositol. J Biosci Bioeng 101 : 427 – 433 Crossref Search ADS PubMed Zhang X, Asara JM, Adamec J, Ouzzani M, Elmagarmid AK ( 2005 ) Data pre-processing in liquid chromatography-mass spectrometry based proteomics. Bioinformatics 21 : 4054 – 4059 Crossref Search ADS PubMed Zou H, Hastie T ( 2005 ) Regularization and variable selection via the elastic net. J R Statist Soc B 67 : 301 – 320 Crossref Search ADS Author notes 1 This work was supported by a grant from the New Zealand Foundation for Research Science and Technology (contracts C10X0203 and AGRX0204) and conducted at AgResearch Grasslands, Palmerston North, New Zealand. 2 These authors contributed equally to the article. * Corresponding author; e-mail [email protected]. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Susanne Rasmussen ([email protected]). [W] The online version of this article contains Web-only data. [OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.107.112458 © 2008 American Society of Plant Biologists © The Author(s) 2008. Published by Oxford University Press on behalf of American Society of Plant Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Naponelli, Valeria; Noiriel, Alexandre; Ziemak, Michael J.; Beverley, Stephen M.; Lye, Lon-Fye; Plume, Andrew M.; Botella, José Ramon; Loizeau, Karen; Ravanel, Stéphane; Rébeillé, Fabrice; de Crécy-Lagard, Valérie; Hanson, Andrew D.

Griesser, Markus; Hoffmann, Thomas; Bellido, Mari Luz; Rosati, Carlo; Fink, Barbara; Kurtzer, Robert; Aharoni, Asaph; Muñoz-Blanco, Juan; Schwab, Wilfried

doi: 10.1104/pp.107.114280pmid: 18258692

Abstract Strawberry (Fragaria × ananassa) fruit contains several anthocyanins that give the ripe fruits their attractive red color. The enzyme that catalyzes the formation of the first stable intermediate in the anthocyanin pathway is anthocyanidin-3-O-glucosyltransferase. A putative glycosyltransferase sequence (FaGT1) was cloned from a strawberry fruit cDNA library and the recombinant FaGT1 transferred UDP-glucose to anthocyanidins and, to a lesser extent, flavonols, generating the respective 3-O-glucosides. Quantitative polymerase chain reaction revealed that transcripts of FaGT1 were almost undetectable in green fruits, but gene expression increased dramatically in both turning and ripe red fruit, corresponding closely to the accumulation of anthocyanins during fruit ripening. The expression of FaGT1 is fruit associated and negatively regulated by auxin. To elucidate the in planta function of FaGT1, Agrobacterium tumefaciens cells harboring an intron-hairpin construct of a partial FaGT1 sequence were injected into midsized ripening fruits. In about one-third of the injected fruits, this led to significant down-regulation of FaGT1 transcript levels that corresponded to reduced concentrations of anthocyanin pigments in ripe strawberry fruits. In contrast, significant levels of epiafzelechin—formed by anthocyanidin reductase (ANR) from pelargonidin—were identified in FaGT1-silenced fruits, indicating competition of FaGT1 and FaANR for the common anthocyanidin substrate. Thus, FaGT1 represents an important branching-point enzyme because it is channeling the flavonoid pathway to anthocyanins. These results demonstrate a method to redirect the anthocyanin biosynthesis into flavan-3-ol production to increase the levels of bioactive natural products or modify pigments in plant tissues. Strawberry (Fragaria × ananassa) is one of the most popular fruit crops worldwide and has emerged as a model for nonclimacteric fruit ripening (Giovannoni, 2001). The strawberry fruit is an aggregate composed of a swollen receptacle and the numerous achenes that are the true fruit (Hancock, 1999). In addition to its flavor, much of the popularity of strawberry fruit is due to the attractive, deep red color caused by anthocyanin pigments. Fruit ripening is triggered by a decline in the levels of auxins released by the achenes in early developmental stages (Perkins-Veazie, 1995). The major pigments of the strawberry cultivar ‘Elsanta’ are pelargonidin 3-O-glucoside (92%), followed by cyanidin 3-O-glucoside (4%) and minor amounts of other pelargonidin derivatives (Fig. 1 Figure 1. Open in new tabDownload slide Anthocyanidins and flavonols are substrates of FaGT1 in vitro. Strawberries contain only pelargonidin- and cyanidin-derived pigments, mostly 3-O-glucosides (Bakker et al., 1994). Glycosides of quercetin and kaempferol are the main flavonols in strawberry fruit (Ryan, 1971; Häkkinen et al., 1999). Figure 1. Open in new tabDownload slide Anthocyanidins and flavonols are substrates of FaGT1 in vitro. Strawberries contain only pelargonidin- and cyanidin-derived pigments, mostly 3-O-glucosides (Bakker et al., 1994). Glycosides of quercetin and kaempferol are the main flavonols in strawberry fruit (Ryan, 1971; Häkkinen et al., 1999). ; Bakker et al., 1994). More recently, metabolite analyses revealed that pelargonidin- and cyanidin-3-O-glucoside-malonate as well as anthocyanin-flavanol conjugates such as (epi)afzelechin-pelargonidin 3-O-glucoside also occur in strawberries (Fossen et al., 2004; Yoshida and Tamura, 2005). Interestingly, the achenes and the receptacle differ significantly in their anthocyanin composition (Aaby et al., 2005; Yoshida and Tamura, 2005). Achenes have higher concentrations of malonylated pigments and contain almost equal amounts of cyanidin- and pelargonidin-derived anthocyanins. Quercetin and kaempferol are the major flavonols in strawberry fruits and occur as 3-O-glucosides and 3-O-glucuronides (Ryan, 1971; Häkkinen et al., 1999). It has been reported that anthocyanins are undetectable in green and white fruits and that their levels increase rapidly in turning and red stages (Given et al., 1988; Cheng and Breen, 1991). In contrast, the concentrations of polyphenols and non-tannin flavonoids reach their maximum in green fruits and decrease afterward (Cheng and Breen, 1991; Wang and Lin, 2000). Whereas the chemical composition of the anthocyanins has been studied in detail, genetic and biochemical information about the last steps in anthocyanin biosynthesis in strawberry fruit is still limited (Almeida et al., 2007). The first stable product of the anthocyanin pathway is formed when a glycosyltransferase attaches a sugar molecule to the hydroxyl group at position 3 on the anthocyanidin aglycone. It has been reported that anthocyanin concentration and flavonoid-3-O-glucosyltransferase activity increase in parallel during fruit ripening (Given et al., 1988). Cheng et al. (1994) isolated a glucosyltransferase from strawberry fruit that preferentially glucosylates biochanin A and several flavonols, but does not accept any anthocyanidins. Recently, an anthocyanidin glucosyltransferase gene has been isolated from strawberry fruits and the recombinant protein preliminarily characterized (Almeida et al., 2007). From grape (Vitis vinifera), another commercially important fruit crop, a UDP-Glc:flavonoid 3-O-glycosyltransferase (VvGT1) has been cloned that preferentially accepts anthocyanidins in vitro, whereas flavonols are less favored (Ford et al., 1998). Comparing glycosylation activities of recombinant VvGT1 and total enzyme extracts from different tissues, the authors concluded that VvGT1 is mainly responsible for the glucosylation of anthocyanidins, whereas additional glycosyltransferases would account for the formation of flavonol glycosides. This is in agreement with earlier findings that VvGT1 mRNA, unlike transcripts of other flavonoid pathway genes, can only be detected in the skin of red grape varieties and that gene expression of VvGT1 is induced after véraison (Boss et al., 1996a, 1996b). Recently, the three-dimensional structure of VvGT1 has been reported, which enabled the identification of key amino acids involved in substrate binding and catalytic activity (Offen et al., 2006). Anthocyanidin 3-O-glucosyltransferases have been isolated from flowers of many ornamental plants in which anthocyanins are the major determinants of flower color, including Gentiana triflora, Petunia hybrida, and Iris hollandica (Tanaka et al., 1996; Yamazaki et al., 2002; Yoshihara et al., 2005). The genome of the model plant Arabidopsis (Arabidopsis thaliana) contains over 100 putative glycosyltransferase sequences, and most of the respective proteins have been expressed heterologously (Li et al., 2001; Ross et al., 2001). Of 91 glycosyltransferases tested, 29 have been reported to accept the flavonol quercetin (Lim et al., 2004). However, there is only one report on an enzyme from Arabidopsis that glycosylates anthocyanidins (Tohge et al., 2005). Here, we report the cloning and biochemical characterization of a glucosyltransferase involved in anthocyanin biosynthesis in strawberry fruit. We provide data on the ripening-related and auxin-controlled expression of this gene. Whereas other techniques have been used to verify the function of glycosyltransferases in planta, this article reports on the RNA interference (RNAi)-mediated down-regulation of an anthocyanidin-3-O-glycosyltransferase gene in a commercially important fruit crop, thus confirming its function in planta. RESULTS Phylogenetic Analysis FaGT1 and three other putative glycosyltransferase genes (FaGT2–FaGT4) were identified among a set of 1,100 strawberry ESTs (Aharoni and O'Connell, 2002) and the full-length sequences were successfully cloned (Lunkenbein et al., 2006a). Further screening of other strawberry cDNA libraries and subsequent application of RACE led to the identification of three additional strawberry glycosyltransferase genes (FaGT5–FaGT7). Phylogenetic analysis (Fig. 2 Figure 2. Open in new tabDownload slide Phylogenetic analysis of selected plant secondary product glycosyltransferases and putative strawberry glycosyltransferases (boxed). The neighbor-joining tree was calculated with the Treecon software package (van de Peer and de Wachter, 1994). Distance calculation was performed with Poisson correction and insertions/deletions were not taken into account. The tree was rooted using a sterol glycosyltransferase from Avena sativa (AsSGT) as an outgroup. Branch lengths indicate the number of substitutions per site. Bootstrap analysis was performed with 100 replicates and only values above 50% are shown. GenBank accession numbers and sources for the respective protein sequences are AtUGT78D2 (NP_197207; Arabidopsis), AtUGT78D1 (NP_564357; Arabidopsis), VvGT1 (AAB81682; grape), FaGT1 (AAU09442; strawberry), DicGT1 (BAD52003; D. caryophyllus), PhF3GalT (AAD55985; P. hybrida), VmUFGT1 (BAA36972; V. mungo), GtF3GT (BAA12737; G. triflora), DicGT3 (BAD52005; D. caryophyllus), FaGT4 (AAU09445; strawberry), FaGT5 (ABB92747; strawberry), FaGT2 (AAU09443; strawberry), FaGT7 (ABB92749; strawberry), FaGT6 (ABB92748; strawberry), FaGT3 (AAU09444; strawberry), and AsSGT (CAB06081; A. sativa). Figure 2. Open in new tabDownload slide Phylogenetic analysis of selected plant secondary product glycosyltransferases and putative strawberry glycosyltransferases (boxed). The neighbor-joining tree was calculated with the Treecon software package (van de Peer and de Wachter, 1994). Distance calculation was performed with Poisson correction and insertions/deletions were not taken into account. The tree was rooted using a sterol glycosyltransferase from Avena sativa (AsSGT) as an outgroup. Branch lengths indicate the number of substitutions per site. Bootstrap analysis was performed with 100 replicates and only values above 50% are shown. GenBank accession numbers and sources for the respective protein sequences are AtUGT78D2 (NP_197207; Arabidopsis), AtUGT78D1 (NP_564357; Arabidopsis), VvGT1 (AAB81682; grape), FaGT1 (AAU09442; strawberry), DicGT1 (BAD52003; D. caryophyllus), PhF3GalT (AAD55985; P. hybrida), VmUFGT1 (BAA36972; V. mungo), GtF3GT (BAA12737; G. triflora), DicGT3 (BAD52005; D. caryophyllus), FaGT4 (AAU09445; strawberry), FaGT5 (ABB92747; strawberry), FaGT2 (AAU09443; strawberry), FaGT7 (ABB92749; strawberry), FaGT6 (ABB92748; strawberry), FaGT3 (AAU09444; strawberry), and AsSGT (CAB06081; A. sativa). ) revealed the relationship between FaGT1 and other strawberry as well as biochemically characterized plant glycosyltransferases. FaGT1 was most similar to the UDP-Glc:flavonoid 3-O-glycosyltransferase (VvGT1) from grape, which preferentially catalyzes the transfer of UDP-Glc to anthocyanidins (Ford et al., 1998). Similarities to glycosyltransferases from Dianthus caryophyllus (DicGT1, DicGT3; Ogata et al., 2004), P. hybrida (PhF3GalT; Miller et al., 1999), Vigna mungo (VmUFGT1; Mato et al., 1998), and G. triflora (GtF3GT; Tanaka et al., 1996) were also found, all of which transfer either UDP-Glc or UDP-Gal to anthocyanidins or flavonols. FaGT1 also shows close homology to UGT78D2 and UGT78D1 from Arabidopsis and can be allocated to group F of Arabidopsis glycosyltransferases. All genes from this group contain intron 2, which is the most widespread intron among the Arabidopsis glycosyltransferases (Li et al., 2001). A 166-bp intron inserted after position 493 of the FaGT1 open reading frame is consistent with the Arabidopsis intron. UGT78D2 has been expressed heterologously and has shown activity with anthocyanidins and flavonols using UDP-Glc as the sugar donor (Tohge et al., 2005). Whereas UGT78D1 was first reported to catalyze the transfer of UDP-Rha to position 3 of kaempferol and quercetin (Jones et al., 2003), it was later shown that UGT78D1 also accepts UDP-Glc (Lim et al., 2004). UGT78D2 has been identified as UDP-Glc:flavonoid 3-O-glucosyltransferase (Lee et al., 2005). Biochemical Characterization The full-length open reading frame of FaGT1 was cloned into the expression vector pET-29a(+) for heterologous protein expression in Escherichia coli. FaGT1 encodes a protein of 50.5 kD consisting of 466 amino acids. The recombinant protein was partially affinity purified on a Ni2+-charged resin that binds the protein's C-terminal His-tag. The presence of target protein was confirmed by SDS-PAGE and western blots using anti-His antibodies (data not shown). Initial activity tests were performed with UDP-Glc and various anthocyanidins and flavonols. Assays were analyzed by liquid chromatography (LC)-electrospray ionization (ESI)-mass spectrometry (MSn) for the formation of glycosylated products. FaGT1 activity could be readily detected with all tested anthocyanidins and flavonols, except for 3-hydroxyflavone and morin (3,5,7,2′,4′-pentahydroxyflavone; Fig. 3 Figure 3. Open in new tabDownload slide Flavonoid substrate preference of recombinant FaGT1. Enzymatic activity was measured in a liquid scintillation counter with a range of anthocyanidins (black bars) and flavonols (white bars) along with the radioactive donor substrate [6-3H]UDP-Glc. Figure 3. Open in new tabDownload slide Flavonoid substrate preference of recombinant FaGT1. Enzymatic activity was measured in a liquid scintillation counter with a range of anthocyanidins (black bars) and flavonols (white bars) along with the radioactive donor substrate [6-3H]UDP-Glc. ). Subsequently, the substrate screening was extended to other flavonoid subgroups, such as flavan-3-ols (catechin, epicatechin), flavanones (naringenin), dihydroflavonols (taxifolin), flavones (5-hydroxyflavone, 7-hydroxyflavone, chrysin, apigenin), flavonol glucosides (quercetin 3-O-glucoside, kaempferol 3-O-glucoside), and anthocyanins (pelargonidin 3-O-glucoside). However, no activity was detected with any of these substrates. The same applied for betanidin, 4-hydroxy-2,5-dimethyl-3(2H)-furanone, benzoic acid, cinnamic acid, and several hydroxycoumarins. These results strongly suggest that FaGT1 acts exclusively on anthocyanidins and flavonols in vitro. No product was formed when UDP-Gal and UDP-GlcUA were used as sugar donors with pelargonidin or quercetin as acceptor molecules. FaGT1 displayed a broad pH optimum in Tris-HCl buffer with maximal activity occurring between pH 7.0 and pH 8.0. After storage at 4°C for 1 week, the enzyme still showed 70% of its initial activity. The temperature optimum was located at 30°C and product formation was linear for 60 min under these conditions. Under optimal conditions, the maximal enzyme activity was with the substrates pelargonidin and cyanidin, both of which are endogenous strawberry anthocyanidins (Fig. 3; Bakker et al., 1994). Peonidin was also among the preferred substrates, whereas flavonols were poor substrates. It is noteworthy that anthocyanidins lacking substitution at position 5′ (pelargonidin, cyanidin, and peonidin) were better substrates than those with a hydroxyl or methoxy group at this position. The substitution of a hydroxyl group by a methoxy group seems to further reduce product formation (Fig. 3). Kinetic constants were determined for UDP-Glc and pelargonidin because it is the most common strawberry anthocyanidin. The K m for pelargonidin was 30 μ m and V max was 21 nkat/mg, whereas UDP-Glc had a K m of 1.1 mm and a V max of 73 nkat/mg. Identification of Reaction Products FaGT1 formed only a single monoglucoside from each substrate (Fig. 4, A–C Figure 4. Open in new tabDownload slide Identification of reaction products. Pelargonidin was incubated with recombinant FaGT1 and UDP-Glc followed by LC-ESI-MSn (A–D) and HPLC-DAD (E) analyses. Both the chromatogram at 520 nm (A) and the ion traces show that pelargonidin (m/z 271; B) is converted into a single glucosylated product (m/z 433; C). The MS2 spectrum (D) shows that this product readily loses a Glc moiety upon fragmentation. HPLC-DAD (E) revealed identical UV/Vis spectra for both reaction product and authentic pelargonidin 3-O-glucoside (reference). Figure 4. Open in new tabDownload slide Identification of reaction products. Pelargonidin was incubated with recombinant FaGT1 and UDP-Glc followed by LC-ESI-MSn (A–D) and HPLC-DAD (E) analyses. Both the chromatogram at 520 nm (A) and the ion traces show that pelargonidin (m/z 271; B) is converted into a single glucosylated product (m/z 433; C). The MS2 spectrum (D) shows that this product readily loses a Glc moiety upon fragmentation. HPLC-DAD (E) revealed identical UV/Vis spectra for both reaction product and authentic pelargonidin 3-O-glucoside (reference). ). Authentic reference compounds were used to identify the product derived from pelargonidin and the flavonols quercetin and kaempferol. The products and the reference compounds were analyzed by HPLC-diode array detector (DAD) and LC-ESI-MSn. Anthocyanins exhibit characteristic UV/Vis spectra and the recorded spectrum of the FaGT1 reaction product was identical to that of authentic pelargonidin 3-O-glucoside (Fig. 4E). In LC-ESI-MSn analyses, both the retention times and mass spectra of pelargonidin 3-O-glucoside, quercetin 3-O-glucoside, and kaempferol 3-O-glucoside corresponded closely to those of the respective assay products. Furthermore, the formation of glycosylated products could be confirmed in product ion experiments because the mass spectra of all FaGT1 reaction products were characterized by the loss of one Glc moiety to yield the respective aglycons (Fig. 4D). Together, the findings confirm that FaGT1 forms anthocyanidin and flavonol 3-O-glucosides in vitro. Spatial and Developmental Expression The spatial and temporal expression pattern of FaGT1 was studied with quantitative PCR (qPCR). RNA was extracted from vegetative tissue (flowers, roots, runners, leaves, and crowns) as well as from receptacles and achenes of small-sized green (G1), full-sized green (G3), white (W), and red (R) fruits. Following reverse transcription (RT), the respective mRNA levels were quantified using sequence-specific primers. The generated amplicon was sequenced and melting point determination, as well as gel electrophoresis, was applied to every sample to ensure the specificity of the qPCR analyses. FaGT1 clearly showed ripening-related expression in both achenes and receptacles, with the highest transcript levels being detected in fully ripe red receptacles (Fig. 5A Figure 5. Open in new tabDownload slide FaGT1 expression is ripening induced and auxin repressed. A, Ripening-related gene expression of FaGT1 in receptacle tissue (white bars) and achenes (black bars). RNA was extracted from pooled fruits at small-size green (G1), full-size green (G3), white (W), and red (R) stages. Transcript levels were analyzed by qRT-PCR as described in “Materials and Methods.” Gene expression is calibrated against expression in receptacle tissue from full-size green fruit (G3). B, Hormonal control of FaGT1 expression. Achenes were carefully removed at the midsize green stage (G2) and the fruits were harvested after 5 d. One set of de-achened green fruits was then treated with a lanolin paste containing the synthetic auxin NAA. FaGT1 expression was analyzed by qRT-PCR as described in “Materials and Methods” and normalized against the expression in untreated strawberries with attached achenes. Figure 5. Open in new tabDownload slide FaGT1 expression is ripening induced and auxin repressed. A, Ripening-related gene expression of FaGT1 in receptacle tissue (white bars) and achenes (black bars). RNA was extracted from pooled fruits at small-size green (G1), full-size green (G3), white (W), and red (R) stages. Transcript levels were analyzed by qRT-PCR as described in “Materials and Methods.” Gene expression is calibrated against expression in receptacle tissue from full-size green fruit (G3). B, Hormonal control of FaGT1 expression. Achenes were carefully removed at the midsize green stage (G2) and the fruits were harvested after 5 d. One set of de-achened green fruits was then treated with a lanolin paste containing the synthetic auxin NAA. FaGT1 expression was analyzed by qRT-PCR as described in “Materials and Methods” and normalized against the expression in untreated strawberries with attached achenes. ). The expression in receptacles was more than an order of magnitude higher than in achenes. FaGT1 transcripts could also be detected in runners, leaves, flowers, and crowns, but only at very low levels similar to the level in green receptacles (data not shown). These results clearly indicate that the expression of FaGT1 is fruit associated and highly ripening related. Hormonal Control of FaGT1 and Developmental Expression To investigate whether FaGT1 is under the control of auxin, midsized green fruits were carefully de-achened and gene expression was studied after 5 d. Additionally, de-achened fruits were treated with a lanolin paste containing naphthalene acetic acid (NAA), a synthetic auxin. The expression of FaGT1 increased substantially after 5 d in de-achened fruits and could be largely reversed by the auxin treatment (Fig. 5B). These results show that the expression of FaGT1 is ripening related and negatively regulated by auxin. Metabolite Studies in Ripening Strawberry Fruit To study the content of individual flavonoids during strawberry fruit ripening, small-sized green (G1), midsized green (G2), white (W), turning (T), and ripe red (R) fruits were extracted with methanol and analyzed by LC-ESI-MSn (Fig. 6 Figure 6. Open in new tabDownload slide Relative metabolite levels at different ripening stages. The levels of flavonol glucosides (kaempferol 3-O-glucoside, quercetin 3-O-glucoside; A), minor anthocyanins [cyanidin 3-O-glucoside, cyanidin 3-O-glucoside-malonate, (epi)afzelechin-pelargonidin 3-O-glucoside; B], and major anthocyanins (pelargonidin 3-O-glucoside, pelargonidin 3-O-glucoside-malonate; C) were determined in flowers (F), small-size green (G1), midsize green (G2), white (W), turning (T), and ripe red (R) fruits. Samples were extracted with methanol and quantified as mg-equ 4-methylumbelliferyl β-d-glucuronide (MUG) per g fresh weight by LC-ESI-MSn. Figure 6. Open in new tabDownload slide Relative metabolite levels at different ripening stages. The levels of flavonol glucosides (kaempferol 3-O-glucoside, quercetin 3-O-glucoside; A), minor anthocyanins [cyanidin 3-O-glucoside, cyanidin 3-O-glucoside-malonate, (epi)afzelechin-pelargonidin 3-O-glucoside; B], and major anthocyanins (pelargonidin 3-O-glucoside, pelargonidin 3-O-glucoside-malonate; C) were determined in flowers (F), small-size green (G1), midsize green (G2), white (W), turning (T), and ripe red (R) fruits. Samples were extracted with methanol and quantified as mg-equ 4-methylumbelliferyl β-d-glucuronide (MUG) per g fresh weight by LC-ESI-MSn. ). Only small amounts of pelargonidin and cyanidin 3-O-glucoside and pelargonidin 3-O-glucoside-malonate were detected in fruits of the early developmental stages. These compounds showed the highest concentration in ripe red fruits. Unlike its potential precursors, cyanidin 3-O-glucoside-malonate displays two concentration maxima during strawberry fruit ripening. High levels of both kaempferol 3-O-glucoside and quercetin 3-O-glucoside were found in small green fruits and their levels decreased in further developmental stages. However, both flavonol glucosides exhibit a second maximum at late-ripening stages. Transient Gene Silencing in Ripening Strawberry Fruit To elucidate the function of FaGT1 in planta, the expression of FaGT1 was down-regulated in strawberry fruit by RNAi using Agrobacterium tumefaciens cells harboring an intron-hairpin construct consisting of two inverted repeats of the FaGT1 sequence (Hoffmann et al., 2006). About one-third (21 of 65) of the fruits injected with pBI-FaGT1i were phenotypically different from fruits injected with the control construct pBI-Intron. Their color was generally less intense and of a different hue compared to the bright red fruits of the controls (Fig. 7, A and B Figure 7. Open in new tabDownload slide Down-regulation of FaGT1 in fruits injected with Agrobacterium cells harboring a FaGT1 intron-hairpin construct (pBI-FaGT1i). A and B, Phenotype of control fruits and fruits infiltrated with pBI-FaGT1i. Control fruits (A) infiltrated with Agrobacterium containing the control construct (pBI-Intron) are deeply red colored, whereas FaGT1-silenced fruits (B) show a less intense red pigmentation with a different hue. Photographs were taken 14 d after injection. C, qRT-PCR analysis of FaGT1 expression in strawberry fruits. cDNA was generated from total RNA isolated from single fruits infiltrated with Agrobacterium containing either the silencing pBI-FaGT1i (white bars) or the control pBI-Intron vector (gray bars). qRT-PCR was performed using FaGT1 and FaActin gene-specific primers, the latter used as internal control for normalization. Figure 7. Open in new tabDownload slide Down-regulation of FaGT1 in fruits injected with Agrobacterium cells harboring a FaGT1 intron-hairpin construct (pBI-FaGT1i). A and B, Phenotype of control fruits and fruits infiltrated with pBI-FaGT1i. Control fruits (A) infiltrated with Agrobacterium containing the control construct (pBI-Intron) are deeply red colored, whereas FaGT1-silenced fruits (B) show a less intense red pigmentation with a different hue. Photographs were taken 14 d after injection. C, qRT-PCR analysis of FaGT1 expression in strawberry fruits. cDNA was generated from total RNA isolated from single fruits infiltrated with Agrobacterium containing either the silencing pBI-FaGT1i (white bars) or the control pBI-Intron vector (gray bars). qRT-PCR was performed using FaGT1 and FaActin gene-specific primers, the latter used as internal control for normalization. ). In all fruits that showed a phenotypic change, a significant down-regulation of FaGT1 expression was determined by quantitative PCR in comparison to the transcript levels in control fruits (Fig. 7C). The effect of FaGT1 silencing on the metabolite concentrations was analyzed by LC-ESI-MSn. At first, levels of potential metabolites downstream of anthocyanidins and flavonols and the concentrations of phenylpropanoid Glc esters were determined. Due to biological variation and heterogeneous silencing effects, the variance of each compound within a sample group was relatively high. Therefore, statistical methods were applied to identify metabolites with significantly altered concentrations. Because the levels of the individual compounds were not normally distributed, we used the Wilcoxon-Mann-Whitney U test (Hart, 2001; Hoffmann et al., 2006). Only the levels of pelargonidin 3-O-glucoside malonate and pelargonidin 3-O-glucoside decreased significantly (P < 0.05) in fruits injected with pBI-FaGT1i, whereas changes in the levels of other anthocyanin derivatives, flavonol glucosides, and phenylpropanoid Glc esters were not significant, except for cinnamoyl Glc, whose level was higher in the controls (Fig. 8, A and B Figure 8. Open in new tabDownload slide Effect of FaGT1 gene silencing on the metabolite level. Fourteen days after pollination, strawberry fruits were infiltrated with Agrobacterium containing pBI-FaGT1i or control pBI-Intron vector. Levels of metabolites were determined by LC-ESI-MSn 14 d after infiltration in FaGT1-silenced (pBI-FaGT1i; n = 21) and control (pBI-Intron; n = 14) fruits. Identities of the compounds were confirmed with references and literature data. Box-whisker plots (A) show the median (horizontal line) and the first and third quartiles, whereas the whiskers extend to the data extremes. The Wilcoxon-Mann-Whitney U test (B) was used for the nonparametric analysis of between-group comparisons of data from FaGT1-silenced and control fruits. Metabolites showing statistically significantly reduced levels (P < 0.05) in the pBI-FaGT1i-infiltrated fruits are boxed. Figure 8. Open in new tabDownload slide Effect of FaGT1 gene silencing on the metabolite level. Fourteen days after pollination, strawberry fruits were infiltrated with Agrobacterium containing pBI-FaGT1i or control pBI-Intron vector. Levels of metabolites were determined by LC-ESI-MSn 14 d after infiltration in FaGT1-silenced (pBI-FaGT1i; n = 21) and control (pBI-Intron; n = 14) fruits. Identities of the compounds were confirmed with references and literature data. Box-whisker plots (A) show the median (horizontal line) and the first and third quartiles, whereas the whiskers extend to the data extremes. The Wilcoxon-Mann-Whitney U test (B) was used for the nonparametric analysis of between-group comparisons of data from FaGT1-silenced and control fruits. Metabolites showing statistically significantly reduced levels (P < 0.05) in the pBI-FaGT1i-infiltrated fruits are boxed. ). To explore also unexpected effects, we applied the software packages MZmine and XCMS for differential analyses of the LC-ESI-MSn data (Katajamaa et al., 2006; Smith et al., 2006). Both computer programs performed untargeted metabolite profiling and uncovered that the levels of epiafzelechin, catechin, and an unknown compound with a pseudomolecular ion m/z 495 were also significantly different in fruits injected with pBI-FaGT1i when compared with control fruits (Supplemental Figs. S1 and S2). The Wilcoxon-Mann-Whitney U test confirmed the findings (Fig. 8, A and B). These results show that pelargonidin is a substrate of FaGT1 in planta, whereas quercetin and kaempferol are probably glucosylated by different enzymes in strawberry fruit. The effect of FaGT1 down-regulation on the levels of upstream metabolites is much stronger than that on downstream natural products. DISCUSSION Biochemical Characterization FaGT1 exhibited a rather broad substrate preference, accepting all tested anthocyanidins and flavonols in vitro (Fig. 3). However, aglycones, belonging to chemically similar subgroups, such as flavones, flavanones, and dihydroflavonols, were not converted. VvGT1, the enzyme from grape that shows greatest similarity to FaGT1, exhibited a comparable substrate spectrum and was also unable to convert morin at a reasonable rate (Ford et al., 1998). This might be due to morin's unusual hydroxyl group at position 2′, which may cause a sterical hindrance for the deprotonation of hydroxyl group 3 by His-20 of VvGT1 (Offen et al., 2006). In accordance with published results, FaGT1 showed highest activity with pelargonidin and cyanidin, the endogenous substrates in strawberries (Almeida et al., 2007). FaGT1 activity decreased along with the substitution pattern (H > OH > OCH3) at the 5′ position of the anthocyanidin molecule. Replacement of a B-ring hydroxyl group with one methoxy group (e.g. cyanidin to peonidin) decreased the reactivity slightly, but dimethoxylated malvidin was the poorest substrate. These substitutions seem to hinder the efficient binding of hydroxyl group 3 near the His-22 residue of FaGT1. It is worth noting that there are no anthocyanins with a 5′ substitution in strawberries (Bakker et al., 1994). Contrary to its broad substrate tolerance for the flavonoid aglycones, FaGT1 only accepted UDP-Glc as a sugar donor. In contrast to FaGT1, the VvGT1 from grape showed weak activity with pelargonidin (Ford et al., 1998), which is not an endogenous substrate in grape (Mazza and Miniati, 1993). However, the obtained K m values for anthocyanidins and UDP-Glc are within the same order of magnitude for both enzymes. The attachment of the sugar was highly regiospecific because FaGT1 formed only anthocyanidin and flavonol 3-O-glucosides. This is consistent with the fact that 3,7-dihydroxyflavone, but not chrysin (5,7-hydroxyflavone), could serve as substrate for FaGT1. In accordance, plant secondary product glycosyltransferases have been reported to exhibit strict regioselectivity toward the position of the attached sugar (Vogt and Jones, 2000). Gene Expression Studies Key enzymes of the flavonoid pathway exhibit two maxima in enzymatic activity during strawberry fruit development (Halbwirth et al., 2006). This includes flavonoid 3-O-glycosyltransferase activity when measured with quercetin as the substrate, and Phe ammonia lyase (PAL) activity (Cheng and Breen, 1991). At the transcript level, it has been reported that the dihydroflavonol 4-reductase (DFR), putative chalcone synthase (CHS), and flavonoid 3-hydoxylase (F3H) genes show two peaks in gene expression at early and late developmental stages (Manning, 1998; Moyano et al., 1998), whereas glycosyltransferase genes highly homologous to FaGT1 were only expressed at late developmental stages (Manning, 1998; Almeida et al., 2007). In this article, we have confirmed the fruit-associated and ripening-related expression of FaGT1. The substantial increases in FaGT1 transcript levels in turning and ripe red fruit agree with our findings (Fig. 6, B and C) and earlier reports that both anthocyanin concentration and flavonoid 3-O-glycosyltransferase activity with malvidin increase during fruit development (Given et al., 1988). In contrast, the levels of polyphenols, non-tannin flavonoids, and cyanidin 3-O-glucoside-malonate are at a maximum shortly after flower opening, peaking again in the late ripening stages (Fig. 6, A and B; Cheng and Breen, 1991; Wang and Lin, 2000). Thus, it can be concluded that at least two different enzymes are involved in the glucosylation of anthocyanidins and flavonols in strawberry: a transferase, which forms the glucosides found at the early ripening stages, and FaGT1, which catalyzes the Glc transfer in ripe strawberry fruits. In grape berries, most anthocyanin pathway genes are expressed up to 4 weeks after anthesis and after véraison mainly in the skin, whereas VvGT1 transcripts are only detected in the skin of red grapes after véraison (Boss et al., 1996a, 1996b). Thus, VvGT1 seems to be regulated differently than other anthocyanin pathway genes and appears to be the major control point in anthocyanin biosynthesis. Interestingly, the expression of VvGT1 can be delayed by application of a synthetic auxin (Davies et al., 1997). Therefore, FaGT1 and VvGT1 share negative regulation by auxin, which plays an important role in nonclimacteric fruit ripening. Function of FaGT1 in Planta To demonstrate the role of FaGT1 in planta, we used a recently developed transient gene-silencing approach based on RNAi to down-regulate FaGT1 expression in strawberry fruit (Hoffmann et al., 2006). A large number of glycosyltransferases involved in plant secondary metabolism have already been cloned and heterologously expressed (Bowles et al., 2005). However, only in a few cases have their biological products been analyzed in planta (Chong et al., 2002; Jones et al., 2003; Morita et al., 2005; Sepúlveda-Jiménez et al., 2005). In about one-third of the fruits, the injection of pBI-FaGT1i caused a different phenotype with less intense color (Fig. 7A). In contrast, all fruits injected with A. tumefaciens carrying the pBI-FaCHSi construct showed reduced levels of anthocyanins and FaCHS transcripts (Hoffmann et al., 2006). The reason for the lower efficiency of FaGT1 down-regulation remains unknown, but we suspect that it depends on the part of the gene-specific sequence chosen for the cloning of the construct. The average FaGT1 transcript levels in pBI-FaGT1i fruits were about 15% of the levels in fruits injected with a control construct (Fig. 7C). When stable strawberry antisense lines of CHS were analyzed, only fruits with <25% of the original transcript level showed a detectable change in pigmentation (Lunkenbein et al., 2006b). Although the content of pelargonidin 3-O-glucoside in these fruits was reduced to 7.5% of control levels, the fruits were still colored orange and pink. A principal problem in silencing glycosyltransferases in plants is the occurrence of enzymes with redundant functions. In our study, the presence of other glycosyltransferases active on anthocyanidins and not silenced by pBI-FaGT1i can account for the partial phenotype observed. The large number of glycosyltransferase sequences in the genomes of Arabidopsis (Li et al., 2001), Oryza sativa (Ko et al., 2006), and Medicago truncatula (Achnine et al., 2005), and the presence of at least seven glycosyltransferase genes (Fig. 2) in strawberry, suggest that strawberries should also contain a large multigene family of glycosyltransferases. This consideration is further supported by the fact that the octoploid background of the cultivated strawberry genotype used in this study leads to a theoretical 4-fold increase of genes. One of these enzymes could be compensating for down-regulated FaGT1. In a similar case in Arabidopsis, the ugt78d2 mutant, lacking UGT78D2 function closely related to FaGT1 activity, still accumulated small amounts of anthocyanins (21% of the wild type), leading the authors to suggest the activity of other 3-O-glucosyltransferases (Tohge et al., 2005). Thus, the simultaneous silencing of several glycosyltransferase genes is likely to be necessary to obtain a clear white phenotype. Down-regulation of FaGT1 is accompanied by significantly (P < 0.05) reduced levels of the strawberry pigments pelargonidin 3-O-glucoside malonate and pelargonidin 3-O-glucoside, but the concentrations of other anthocyanins did not change significantly (Fig. 8, A and B). A second glucosyltransferase (e.g. the one that glucosylates cyanidin at early developmental stages and provides the precursor for the malonated derivative) could compensate for FaGT1 silencing in the case of cyanidin 3-O-glucoside (Fig. 6B). The strongly reduced concentrations of pelargonidin 3-O-glucoside-malonate in pBI-FaGT1i fruits are consistent with the idea that the first modification of the anthocyanidin structure is the attachment of a Glc molecule followed by esterification with malonic acid, and shows that pelargonidin is a substrate of FaGT1 in the late ripening stages in vivo. Weak enzymatic activity of the malonyl transferase at low pelargonidin 3-O-glucoside levels would lead to strongly reduced amounts of the malonylated derivative, whereas the level of pelargonidin 3-O-glucoside remains almost constant. This scenario would explain—at least for the pelargonidin derivatives—why the level of the 3-O-glucoside-malonate is stronger affected than the level of the glucoside. Surprisingly, the level of cinnamoyl Glc was also significantly reduced in fruits injected with pBI-FaGT1i, even though FaGT1 showed no activity toward cinnamic acid in vitro. Because we observed a similar effect when FaCHS was transiently silenced, we reason that manipulation of the flavonoid pathway modulates PAL activity through transcriptional and posttranscriptional mechanisms as has been shown by antisense expression of an alfalfa (Medicago sativa) cinnamic acid 4-hydroxylase (Supplemental Fig. S3; Blount et al., 2000; Hoffmann et al., 2006). The modulation of PAL activity by the metabolites of the phenylpropanoid pathway has already been reported and could cause the reduced level of the cinnamic acid derivative (Shirsat and Nair, 1986). Based on in vitro substrate preference and additional biochemical data, it has been proposed that VvGT1 is primarily responsible for the glucosylation of anthocyanidins in vivo (Ford et al., 1998). In contrast, in the homozygous Arabidopsis ugt78d2 mutant, the total level of anthocyanins (consisting exclusively of cyanidin glucoside derivatives) and the levels of four flavonol 3-O-glycosides were reduced (Tohge et al., 2005). Thus, because recombinant UGT78D2 glucosylates anthocyanidins (cyanidin, pelargonidin, and delphindin) and flavonols (kaempferol, quercetin, and myricetin) in vitro, it was concluded that the native enzyme catalyzes the glucosylation of both cyanidin and flavonols at the 3 position as UDP-Glc:flavonoid 3-O-glucosyltransferase in planta. Our data provide experimental evidence that FaGT1 is involved only in the formation of anthocyanins in planta, whereas flavonols can be excluded as in vivo substrates. This conclusion is based on the significantly reduced levels of pelargonidin 3-O-glucoside malonate and pelargonidin 3-O-glucoside and the strongly increased concentrations of flavan-3-ols (epiafzelechin, catechin, and epicatechin) in fruits in which FaGT1 transcript level had been genetically down-regulated. Because epiafzelechin is produced from pelargonidin by the action of anthocyanidin reductase (ANR), increased amounts of the ANR product can only be explained by enhanced availability of the pelargonidin substrate because average FaANR transcript levels were unaffected in pBI-FaGT1i fruits (Fig. 9 Figure 9. Open in new tabDownload slide Biosynthetic pathway leading to anthocyanins and flavan-3-ols. FHT, Flavanone 3-hydroxylase; ANS, anthocyanidin synthase. Because of the strict specificity of Fragaria LAR for leucocyanidin, afzelechin is not found in strawberry fruit (Almeida et al., 2007). Figure 9. Open in new tabDownload slide Biosynthetic pathway leading to anthocyanins and flavan-3-ols. FHT, Flavanone 3-hydroxylase; ANS, anthocyanidin synthase. Because of the strict specificity of Fragaria LAR for leucocyanidin, afzelechin is not found in strawberry fruit (Almeida et al., 2007). ; Supplemental Fig. S4). Thus, the increased level of epiafzelechin confirms the efficient and specific down-regulation of FaGT1 activity and provides further evidence for pelargonidin as in planta substrate of FaGT1. The successful redirection of the flavonoid biosynthesis also suggests that the reciprocal regulation of ANR and FaGT1 is important in directing the metabolic flux to either anthocyanins or flavan-3-ols (Lee et al., 2005). But FaGT1 silencing also provides enhanced levels of cyanidin and its precursor leucocyanidin, which are converted by FaANR and leucoanthocyanidin 4-reductase (LAR) to epicatechin and catechin, respectively (Fig. 9). The amounts of both flavan-3-ols increased as a consequence of FaGT1 down-regulation (Fig. 8). Because LAR from Fragaria shows strict substrate specificity toward leucocyanidin, the lack of afzelechin in strawberry is conceivable (Almeida et al., 2007). The unknown metabolite with a pseudomolecular ion of m/z 495 might be an anthocyanin derivative (downstream metabolite) according to its mass spectral data (data not shown) and reduced level in pBI-FaGT1i fruits. In addition to the findings in Arabidopsis, this article reports on gene silencing of an anthocyanidin 3-O-glucosyltransferase from a commercial fruit crop. We could clearly demonstrate that FaGT1 acts on anthocyanidins (pelargonidin and cyanidin), whereas other glycosyltransferases should be responsible for the glucosylation of flavonols (kaempferol and quercetin) in the receptacle. The redirection of the metabolic flux toward flavan-3-ols through down-regulation of FaGT1 offers a new method to increase the levels of these bioactive metabolites in fruit crops. The findings emphasize the necessity of in planta experiments for the elucidation of biological functions and enable novel insights into the flux control of the flavonoid pathway. MATERIALS AND METHODS Chemicals Except when otherwise stated, all chemicals, solvents, and reference compounds were obtained from Sigma, Aldrich, Fluka, Riedel de Haën, Merck, or Roth. Anthocyanidins were purchased from Polyphenols Laboratories. Radiolabeled [6-3H]UDP-Glc (1 mCi/mL, 60 Ci/mmol) was obtained from American Radiolabeled Compounds. Cloning of FaGT1 Genomic Sequence DNA used as a template for PCR amplification was isolated from strawberry (Fragaria × ananassa ‘Elsanta’) leaves using a commercial kit (Qiagen). Products obtained with primers located at the 5′- and the 3′-end of the full-length sequences were cloned into the pGEM-T vector (Promega) and sequenced by a commercial sequencing service (MWG Biotech). Construction of FaGT1 Expression Plasmid The cDNA library construction and sequence analysis of the ESTs have been described (Aharoni and O'Connell, 2002). The FaGT1 full-length open reading frame was subcloned in the pGEM-T vector (Promega). For the FaGT1 construct, 5′-TGAATTCATGGCACCAGTATCAAACC-3′ was used as the forward primer and 5′-TCTCGAGATTGGTTGTAGTCATTTCC-3′ as the reverse primer, introducing EcoRI and XhoI restriction sites that were used for subsequent cloning into the pET-29a(+) expression vector (Novagen). The insert was cloned in frame with a coding region for a C-terminal His-tag. The identity of the cloned gene was confirmed by sequencing the complete insert (MWG Biotech). Heterologous Protein Expression Escherichia coli BL21 (DE3) pLysS cells (Novagen) were transformed with the pET-29a(+) expression vector containing the FaGT1 open reading frame. Cultures were grown overnight at 37°C in Luria-Bertani medium containing 25 μg/mL kanamycin and 34 μg/mL chloramphenicol. The next day, the cultures were diluted to an OD600 of 0.06 with Luria-Bertani medium containing the appropriate antibiotics in a final volume of 800 mL. This culture was grown at 37°C to an OD600 of 0.4 to 0.6, cooled to 16°C, and 1 mm isopropylthio-β-galactoside was added to induce protein expression. After overnight incubation at 16°C to 18°C, cells were harvested by centrifugation and stored at −20°C. Cell Lysis and Protein Purification His-tagged protein was affinity purified using the His Bind Quick 900 cartridges (Novagen) as recommended by the manufacturer. Briefly, cells were resuspended in binding buffer and sonicated three times on ice. Viscosity was reduced through incubation with benzonase nuclease (Novagen) and the protein raw extract was applied to the cartridges. Recombinant protein was eluted with a buffer containing 1 m imidazol and kept on ice. Protein concentration was determined (Bradford, 1976) and the presence of recombinant protein was confirmed by SDS-PAGE and western blot using anti-His antibodies (Novagen). The amount of FaGT1 present in the partially purified eluate was quantified using the Alpha Imager 2200 documentation and analysis system and Alpha Ease software (Alpha Innotech). Aliquots of purified protein were stored at −20°C. Enzyme Assays Enzyme activity was assayed in a buffer containing 100 mm Tris-HCl (pH 7.0), 10% glycerol, and 10 mm β-mercaptoethanol. Standard assays contained 5 mm UDP-Glc, 200 μ m substrate, and protein raw extract with approximately 0.25 μg of recombinant protein in a total volume of 250 μL. Enzyme assays were incubated for 30 min at 30°C and stopped by the addition of 200 μL of 5% HCl (anthocyanidin substrates) or 50 μL of acetic acid (all other substrates). As a control, BL21 (DE3) pLysS cells were transformed with an empty pET29-a(+) vector and the resulting protein extract was assayed under the same conditions. As an additional control, assays were conducted with heat-inactivated enzyme solution (5 min at 95°C). Initial enzyme activity was monitored by detecting the reaction products with LC-ESI-MSn. The identity of the FaGT1 glycosylation product was also confirmed by HPLC-DAD. Enzyme Kinetics The biochemical characterization was carried out with radioactively labeled UDP-Glc allowing for detection of the reaction product by liquid scintillation counting. Assay conditions were essentially the same, except only 0.1 μg of affinity-purified recombinant protein was used in a total volume of 200 μL. The UDP-Glc was a mixture of 1 μL of 0.016 mm [6-3H]UDP-Glc (1 mCi/mL) and 99 μL of unlabeled 101 mm UDP-Glc. Assays were incubated at 30°C for 30 min and extracted with 1 mL of water-saturated n-butanol. The radioactivity of the products was determined by liquid scintillation counting (LKB Rackbeta 1219) after the addition of 4 mL of Ultima Gold XR LSC cocktail (Perkin-Elmer). The kinetic constants were calculated with SigmaPlot 8.0 software (Systat Software) assuming single-site saturation binding. HPLC-DAD The instrument used was a LaChrom HPLC (Merck-Hitachi) equipped with a DAD. HPLC separation was performed with a Phenomenex Luna C-8 column (150 mm long × 4.6 mm i.d., particle size 3 μm) applying a gradient that went from 100% A (0.05% formic acid in water) to 100% B (acetonitrile) in 30 min at a flow rate of 1 mL/min. Spectra and chromatograms were acquired with the Chromatography Data Station software (Merck-Hitachi). LC-ESI-MSn A Bruker Daltonics esquire 3000plus ion trap mass spectrometer (Bruker Daltonics) connected to an Agilent 1100 HPLC system (Agilent Technologies) equipped with a quaternary pump and a variable wavelength detector was utilized for all experiments. Components were separated with a Phenomenex Luna C-18 column (150 mm long × 2.0 mm i.d., particle size 5 μm) that was held at 25°C. Enzyme assays were analyzed using a linear gradient that went from 100% A (0.1% formic acid in water) to 100% B (acetonitrile) in 30 min with a flow rate of 0.2 mL/min. For metabolite analyses in strawberry fruit extracts, the gradient went from 100% A to 40% B in 40 min, then to 100% B in 5 min. The detection wavelength was either 520 (anthocyanidins) or 280 nm (other substrates and metabolite analyses). The ESI voltage of the capillary was set to −4,000 V and the end plate to −500 V. Nitrogen was used as dry gas at a temperature of 300°C and a flow rate of 10 L/min. The full-scan mass spectra were measured in a scan range from 50 to 800 m/z with a scan resolution of 13,000 m/z/s until the ICC target reached 20,000 or 200 ms, whichever was achieved first. Tandem MS was carried out using helium as the collision gas (3.56 × 10−6 mbar) with 1-V collision voltage. Spectra were acquired in the positive and negative ionization mode. Data analysis was performed using the DataAnalysis 3.1 software (Bruker Daltonics). Auxin Treatment The hormone treatment was performed as described previously (Medina-Escobar et al., 1997). Briefly, achenes from midsized green fruits were removed carefully with a scalpel blade. One set of fruits was treated with a lanolin paste containing 1 mm NAA in 1% (v/v) dimethyl sulfoxide. The other set of de-achened fruits was treated with the same paste without the synthetic auxin NAA. Fruits were harvested after 5 d and immediately frozen in liquid nitrogen. Developmental Analyses of FaGT1 Expression Total RNA was isolated from pools of six to seven strawberry fruits from each ripening stage as described (Asif et al., 2000). RNA was treated with DNase I (Amersham Bioscience) to remove any DNA contamination prior to cDNA synthesis. RT was carried out using 1 μg of total RNA and the iScript cDNA synthesis kit (Bio-Rad) as recommended by the manufacturer. qRT-PCR analysis was performed using the iCycler system (Bio-Rad) as described previously (Benítez-Burraco et al., 2003; Raab et al., 2006). FaGT1-specific primers were designed (5′-TGCGGTTGGAACTCGTGCGGTTGGAACTCGGTGCTTGCCTGTTGTGCGAGTTGTTTTGTGCTT-3′ and 5′-GCCTGTTGTGCGAGTTGTTTT-3′) and tested with cDNA from different ripening stages. The obtained amplification products were cloned and subsequently sequenced. The qRT-PCR data for FaGT1 were normalized against the expression levels of an interspacer 26S-18S RNA housekeeping gene (5′-ACCGTTGATTCGCACAATTGGTCATACTGCGGGTCGGCAATCGGACGTCG-3′ and 5′-TACTGCGGGTCGGCAATCGGACG-3′). PCR reactions contained 2 mm MgCl2, 0.2 mm dNTPs, 0.2 μ m of the respective primers, 2.5 μL SYBR-Green I (diluted 1:15,000), 2 μL cDNA, and 0.5 units Taq polymerase (Biotools) in a total volume of 25 μL. The thermal cycling conditions were as follows: 2 min at 94°C, followed by 40 cycles of 95°C for 15 s, 55°C for 30 s, and 72°C for 30 s. Melting-point analysis and agarose gel electrophoresis were performed on every reaction to ensure that only the desired amplicon had been generated. Each reaction was performed at least in triplicate and relative expression levels were calculated by calibrating the results with receptacle expression levels from full-sized green fruits (G3) or untreated controls with attached achenes (Livak and Schmittgen, 2001). Construction of pBI-FaGT1i A blunt-end PCR product containing the full-length sequence of FaGT1 was generated using a high-fidelity polymerase (Finnzymes) and the same primers used to subclone the expression vector. This amplicon was then digested with SpeI yielding a fragment of approximately 500 bp, which was used for ligation into the binary vector pBI121 that contained XbaI/NheI and SpeI/SacI (Ecl136II) restriction sites separated by an intron from strawberry (Hoffmann et al., 2006). To do this, the vector was cut with XbaI and a high-fidelity polymerase was used to create a blunt end. After cutting the vector with NheI, the 500-bp fragment was ligated in the sense direction. Second, the vector was digested with SpeI and Ecl136II and the 500-bp fragment was inserted in the antisense direction, yielding the intron-hairpin construct pBI-FaGT1i. Transfection of Strawberries by Agroinfiltration Strawberry cultivar ‘Elsanta’ plants were grown under standard conditions at 25°C and a 16-h photoperiod. Transfection was carried out as described previously (Hoffmann et al., 2006). Briefly, Agrobacterium tumefaciens strain AGL0 cells containing the pBI-FaGT1i construct were grown at 28°C until the OD600 reached approximately 0.8. Cells were harvested and resuspended in modified MacConkey agar medium and injected evenly in fruits still attached to the plant about 14 d after pollination. Ripe fruits with dark achenes were harvested approximately 14 d after injection and stored at −80°C. Control experiments were carried out by injecting strawberry fruits with A. tumefaciens AGL0 cells harboring a pBI-Intron control construct (Hoffmann et al., 2006). RNA Extraction and Expression Analyses Used for Transfected Fruits Agroinfiltrated fruits were individually freeze dried in a lyophilizer (Christ ALPHA 1–4) and ground to a fine powder. Fifty milligrams of the powder from each fruit was used for RNA extraction, followed by DNase I treatment and RT, as described before. Five nanograms of cDNA was used for qRT-PCR experiments, carried out with FaGT1, FaANR, and FaActin gene-specific primers (Almeida et al., 2007) using an ABI 7900 thermocycler (Applied Biosystems) and Platinum SYBR-Green kit (Invitrogen) according to the manufacturer's instructions. The FaActin gene, having constant expression levels, was used to normalize raw data and calculate relative FaGT1 and FaANR transcript levels. Metabolite Analysis Fifty milligrams of freeze-dried strawberry powder was extracted with 250 μL of methanol containing 0.2 mg/mL 4-methylumbelliferyl β-d-glucuronide as an internal standard. Methanol was removed in a rotary vacuum concentrator (Christ RVC 2–18) and the extract was redissolved in 35 μL of water for analysis by LC-ESI-MSn. For metabolite analyses during fruit development, 500-mg samples were extracted with 500 μL of methanol, 0.05 mg of internal standard was added, centrifuged (5,000g, 10 min), and analyzed by LC-ESI-MSn. Metabolite quantification was performed using QuantAnalysis 1.5 software (Bruker Daltonics) normalizing all results against the internal standard. Each analysis was performed in triplicate. Levels of metabolites determined in the RNAi experiment were displayed as box and whisker plots using the software SigmaPlot 8.0 (Systat Software). Statistical significance levels were calculated with the Wilcoxon-Mann-Whitney U Test (Hart, 2001) using the software package R (www.r-project.org). Sequence data from this article can be found in the GenBank/EMBL data libraries under accession number AAU09442 (FaGT1). Supplemental Data The following materials are available in the online version of this article. Supplemental Figure S1. Comparative HPLC-ESI-MS analysis of the metabolites visualized by MZmine. Supplemental Figure S2. Extracted ion trace m/z 273 visualized by XCMS. Supplemental Figure S3. Effect on the cinnamoyl glucose level by transient silencing of FaCHS. Supplemental Figure S4. Quantitative PCR analysis of FaANR expression in strawberry fruits. ACKNOWLEDGMENTS We thank Christian Landmann for helpful discussions and Heather Coiner for correcting the manuscript. LITERATURE CITED Aaby K, Skrede G, Wrolstad RE ( 2005 ) Phenolic composition and antioxidant activities in flesh and achenes of strawberries (Fragaria ananassa). J Agric Food Chem 53 : 4032 – 4040 Crossref Search ADS PubMed Achnine L, Huhman DV, Farag MA, Sumner LW, Blount JW, Dixon RA ( 2005 ) Genomics-based selection and functional characterization of triterpene glycosyltransferases from the model legume Medicago truncatula. Plant J 41 : 875 – 887 Crossref Search ADS PubMed Aharoni A, O'Connell AP ( 2002 ) Gene expression analysis of strawberry achene and receptacle maturation using DNA microarrays. J Exp Bot 53 : 2073 – 2087 Crossref Search ADS PubMed Almeida JRM, D'Amico E, Preuss A, Carbone F, de Vos RCH, Deiml B, Mourgues F, Perrotta G, Fischer TC, Bovy AG, et al ( 2007 ) Characterization of major enzymes and genes involved in flavonoid and proanthocyanidin biosynthesis during fruit development in strawberry (Fragaria × ananassa). Arch Biochem Biophys 465 : 61 – 71 Crossref Search ADS PubMed Asif MH, Dhawan P, Nath P ( 2000 ) A simple procedure for the isolation of high quality RNA from ripening banana fruit. Plant Mol Biol Rep 18 : 109 – 115 Crossref Search ADS Bakker J, Bridle P, Bellworthy SJ ( 1994 ) Strawberry juice colour: a study of the quantitative and qualitative pigment composition of juices from 39 genotypes. J Sci Food Agric 64 : 31 – 37 Crossref Search ADS Benítez-Burraco A, Blanco-Portales R, Redondo-Nevado J, Bellido ML, Moyano E, Caballero JL, Munoz-Blanco J ( 2003 ) Cloning and characterization of two ripening related strawberry (Fragaria x ananassa cv. Chandler) pectate lyase genes. J Exp Bot 54 : 633 – 645 Crossref Search ADS PubMed Blount JW, Korth KL, Masoud SA, Rasmussen S, Lamb C, Dixon RA ( 2000 ) Altering expression of cinnamic acid 4-hydroxylase in transgenic plants provides evidence for a feedback loop at the entry point into the phenylpropanoid pathway. Plant Physiol 122 : 107 – 116 Crossref Search ADS PubMed Boss PK, Davies C, Robinson SP ( 1996 a) Analysis of the expression of anthocyanin pathway genes in developing Vitis vinifera L. cv Shiraz grape berries and the implications for pathway regulation. Plant Physiol 111 : 1059 – 1066 Crossref Search ADS PubMed Boss PK, Davies C, Robinson SP ( 1996 b) Expression of anthocyanin biosynthesis pathway genes in red and white grapes. Plant Mol Biol 32 : 565 – 569 Crossref Search ADS PubMed Bowles D, Isayenkova J, Lim EK, Poppenberger B ( 2005 ) Glycosyltransferases: managers of small molecules. Curr Opin Plant Biol 8 : 254 – 263 Crossref Search ADS PubMed Bradford MM ( 1976 ) A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72 : 248 – 254 Crossref Search ADS PubMed Cheng GW, Breen PJ ( 1991 ) Activity of phenylalanine ammonia-lyase (PAL) and concentration of anthocyanins and phenolics in developing strawberry fruit. J Am Soc Hortic Sci 116 : 865 – 869 Crossref Search ADS Cheng GW, Malencik DA, Breen PJ ( 1994 ) UDP-glucose:flavonoid O-glucosyltransferase from strawberry fruit. Phytochemistry 35 : 1435 – 1439 Crossref Search ADS Chong J, Baltz R, Schmitt C, Beffa R, Fritig B, Saindrenan P ( 2002 ) Down-regulation of a pathogen-responsive tobacco UDP-Glc:phenylpropanoid glucosyltransferase reduces scopoletin glucoside accumulation, enhances oxidative stress, and weakens virus resistance. Plant Cell 14 : 1093 – 1107 Crossref Search ADS PubMed Davies C, Boss PK, Robinson SP ( 1997 ) Treatment of grape berries, a nonclimacteric fruit with a synthetic auxin, retards ripening and alters the expression of developmentally regulated genes. Plant Physiol 115 : 1155 – 1161 Crossref Search ADS PubMed Ford CM, Boss PK, Høj PB ( 1998 ) Cloning and characterization of Vitis vinifera UDP-glucose:flavonoid 3-O-glucosyltransferase, a homologue of the enzyme encoded by the maize Bronze-1 locus that may primarily serve to glucosylate anthocyanidins in vivo. J Biol Chem 273 : 9224 – 9233 Crossref Search ADS PubMed Fossen T, Rayyan S, Andersen ØM ( 2004 ) Dimeric anthocyanins from strawberry (Fragaria ananassa) consisting of pelargonidin 3-glucoside covalently linked to four flavan-3-ols. Phytochemistry 65 : 1421 – 1428 Crossref Search ADS PubMed Giovannoni J ( 2001 ) Molecular biology of fruit maturation and ripening. Annu Rev Plant Physiol Plant Mol Biol 52 : 725 – 749 Crossref Search ADS PubMed Given NK, Venis MA, Grierson D ( 1988 ) Phenylalanine ammonia-lyase activity and anthocyanin synthesis in ripening strawberry fruit. J Plant Physiol 133 : 25 – 30 Crossref Search ADS Häkkinen SH, Kärenlampi SO, Heinonen M, Mykkänen HM, Törrönen AR ( 1999 ) Content of the flavonols quercetin, myricetin, and kaempferol in 25 edible berries. J Agric Food Chem 47 : 2274 – 2279 Crossref Search ADS PubMed Halbwirth H, Puhl I, Haas U, Jezik K, Treutter D, Stich K ( 2006 ) Two-phase flavonoid formation in developing strawberry (Fragaria x ananassa) fruit. J Agric Food Chem 54 : 1479 – 1485 Crossref Search ADS PubMed Hancock JF ( 1999 ) Strawberries. CABI Publishing, New York Hart A ( 2001 ) Mann-Whitney test is not just a test of medians: differences in spread can be important. BMJ 323 : 391 – 393 Crossref Search ADS PubMed Hoffmann T, Kalinowski G, Schwab W ( 2006 ) RNAi-induced silencing of gene expression in strawberry fruit (Fragaria x ananassa) by agroinfiltration: a rapid assay for gene function analysis. Plant J 48 : 818 – 826 Crossref Search ADS PubMed Jones P, Messner B, Nakajima J-I, Schäffner AR, Saito K ( 2003 ) UGT73C6 and UGT78D1, glycosyltransferases involved in flavonol glycoside biosynthesis in Arabidopsis thaliana. J Biol Chem 278 : 43910 – 43918 Crossref Search ADS PubMed Katajamaa M, Miettinen J, Orešič M ( 2006 ) MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics 22 : 634 – 636 Crossref Search ADS PubMed Ko JH, Kim BG, Hur HG, Lim Y, Ahn JH ( 2006 ) Molecular cloning, expression and characterization of a glycosyltransferase from rice. Plant Cell Rep 25 : 741 – 746 Crossref Search ADS PubMed Lee Y, Yoon HR, Paik YS, Liu JR, Chung WI, Choi G ( 2005 ) Reciprocal regulation of Arabidopsis UGT78D2 and BANYULS is critical for regulation of the metabolic flux of anthocyanidins to condensed tannins in developing seed coats. J Plant Biol 48 : 356 – 370 Crossref Search ADS Li Y, Baldauf S, Lim EK, Bowles DJ ( 2001 ) Phylogenetic analysis of the UDP-glucosyltransferase multigene family of Arabidopsis thaliana. J Biol Chem 276 : 4338 – 4343 Crossref Search ADS PubMed Lim EK, Ashford DA, Hou B, Jackson RG, Bowles DJ ( 2004 ) Arabidopsis glycosyltransferases as biocatalysts in fermentation for regioselective synthesis of diverse quercetin glucosides. Biotechnol Bioeng 87 : 623 – 631 Crossref Search ADS PubMed Livak KJ, Schmittgen TD ( 2001 ) Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25 : 402 – 408 Crossref Search ADS PubMed Lunkenbein S, Bellido ML, Aharoni A, Salentijn EMJ, Kaldenhoff R, Coiner HA, Munoz-Blanco J, Schwab W ( 2006 a) Cinnamate metabolism in ripening fruit. Characterization of a UDP-glucose:cinnamate glucosyltransferase from strawberry. Plant Physiol 140 : 1047 – 1058 Crossref Search ADS PubMed Lunkenbein S, Coiner H, de Vos RCH, Schaart JG, Boone MJ, Krens FA, Schwab W, Salentijn EMJ ( 2006 b) Molecular characterization of a stable antisense chalcone synthase phenotype in strawberry (Fragaria x ananassa). J Agric Food Chem 54 : 2145 – 2153 Crossref Search ADS PubMed Manning K ( 1998 ) Isolation of a set of ripening-related genes from strawberry: their identification and possible relationship to fruit quality traits. Planta 205 : 622 – 631 Crossref Search ADS PubMed Mato M, Ozeki Y, Itoh Y, Higeta D, Yoshitama K, Teramoto S, Aida R, Ishikura N, Shibata M ( 1998 ) Isolation and characterization of a cDNA clone of UDP-galactose:flavonoid 3-O-galactosyltransferase (UF3GaT) expressed in Vigna mungo seedlings. Plant Cell Physiol 39 : 1145 – 1155 Crossref Search ADS PubMed Mazza G, Miniati E ( 1993 ) Anthocyanins in Fruits, Vegetables, and Grains. CRC Press, Boca Raton, FL Medina-Escobar N, Cárdenas J, Moyano E, Caballero JL, Munoz-Blanco J ( 1997 ) Cloning, molecular characterization and expression pattern of a strawberry ripening-specific cDNA with sequence homology to pectate lyase from higher plants. Plant Mol Biol 34 : 867 – 877 Crossref Search ADS PubMed Miller KD, Guyon V, Evans JNS, Shuttleworth WA, Taylor LP ( 1999 ) Purification, cloning, and heterologous expression of a catalytically efficient flavonol 3-O-galactosyltransferase expressed in the male gametophyte of Petunia hybrida. J Biol Chem 274 : 34011 – 34019 Crossref Search ADS PubMed Morita Y, Hoshino A, Kikuchi Y, Okuhara H, Ono E, Tanaka Y, Fukui Y, Saito N, Nitasaka E, Noguchi H, et al ( 2005 ) Japanese morning glory dusky mutants displaying reddish-brown or purplish-gray flowers are deficient in a novel glycosylation enzyme for anthocyanin biosynthesis, UDP-glucose:anthocyanidin 3-O-glucoside-2″-O-glucosyltransferase, due to 4-bp insertions in the gene. Plant J 42 : 353 – 363 Crossref Search ADS PubMed Moyano E, Portero-Robles I, Medina-Escobar N, Valpuesta V, Munoz-Blanco J, Caballero JL ( 1998 ) A fruit specific putative dihydroflavonol 4-reductase gene is differentially expressed in strawberry during the ripening process. Plant Physiol 117 : 711 – 716 Crossref Search ADS PubMed Offen W, Martinez-Fleites C, Yang M, Kiat-Lim E, Davis BG, Tarling CA, Ford CM, Bowles DJ, Davies GJ ( 2006 ) Structure of a flavonoid glucosyltransferase reveals the basis for plant natural product modification. EMBO J 25 : 1396 – 1405 Crossref Search ADS PubMed Ogata J, Itoh Y, Ispida M, Yoshida H, Ozeki Y ( 2004 ) Cloning and heterologous expression cDNAs encoding flavonoid glucosyltransferases from Dianthus caryophyllus. Plant Biotechnol J 21 : 367 – 375 Crossref Search ADS Perkins-Veazie P ( 1995 ) Growth and ripening of strawberry fruit. Hortic Rev (Am Soc Hortic Sci) 17 : 267 – 297 Raab T, López-Ráez JA, Klein D, Caballero JL, Moyano E, Schwab W, Munoz-Blanco J ( 2006 ) FaQR, required for the biosynthesis of the strawberry flavor compound 4-hydroxy-2,5-dimethyl-3(2H)-furanone, encodes an enone oxidoreductase. Plant Cell 18 : 1023 – 1037 Crossref Search ADS PubMed Ross J, Li Y, Lim EK, Bowles DJ ( 2001 ) Higher plant glycosyltransferases. Genome Biol 2 : 3004.1 – 3004 .6 Ryan JJ ( 1971 ) Flavonol glycosides of the cultivated strawberry. J Food Sci 36 : 867 – 870 Crossref Search ADS Sepúlveda-Jiménez G, Rueda-Benítez P, Porta H, Rocha-Sosa M ( 2005 ) A red beet (Beta vulgaris) UDP-glucosyltransferase gene induced by wounding, bacterial infiltration and oxidative stress. J Exp Bot 56 : 605 – 611 Crossref Search ADS PubMed Shirsat SG, Nair PM ( 1986 ) The mode of inhibition of the biosynthesis of phenylalanine ammonia lyase by its product cinnamic acid in aging potato parenchyma tissue. J Biosci 10 : 393 – 402 Crossref Search ADS Smith CA, Want EJ, Tong GC, Abagyan R, Siuzdak G ( 2006 ) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78 : 779 – 787 Crossref Search ADS PubMed Tanaka Y, Yonekura K, Fukuchi-Mizutani M, Fukui Y, Fujiwara H, Ashikari T, Kusumi T ( 1996 ) Molecular and biochemical characterization of three anthocyanin synthetic enzymes from Gentiana triflora. Plant Cell Physiol 37 : 711 – 716 Crossref Search ADS PubMed Tohge T, Nishiyama Y, Hirai MY, Yano M, Nakajima JI, Awazuhara M, Inoue E, Takahashi H, Goodenowe DB, Kitayama M, et al ( 2005 ) Functional genomics by integrated analysis of metabolome and transcriptome of Arabidopsis plants over-expressing a MYB transcription factor. Plant J 42 : 218 – 235 Crossref Search ADS PubMed van de Peer Y, de Wachter Y ( 1994 ) TREECON for Windows: a software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment. Comput Appl Biosci 10 : 569 – 570 PubMed Vogt T, Jones P ( 2000 ) Glycosyltransferases in plant natural product synthesis: characterization of a supergene family. Trends Plant Sci 5 : 380 – 386 Crossref Search ADS PubMed Wang SY, Lin HS ( 2000 ) Antioxidant activity in fruits and leaves of blackberry, raspberry, and strawberry varies with cultivar and developmental stage. J Agric Food Chem 48 : 140 – 146 Crossref Search ADS PubMed Yamazaki M, Yamagishi E, Gong Z, Fukuchi-Mizutani M, Fukui Y, Tanaka Y, Kusumi T, Yamaguchi M, Saito K ( 2002 ) Two flavonoid glucosyltransferases from Petunia hybrida: molecular cloning, biochemical properties and developmentally regulated expression. Plant Mol Biol 48 : 401 – 411 Crossref Search ADS PubMed Yoshida Y, Tamura H ( 2005 ) Variation in concentration and composition of anthocyanins among strawberry cultivars. J Jpn Soc Hort Sci 74 : 36 – 41 Crossref Search ADS Yoshihara N, Imayama T, Fukuchi-Mizutani M, Okuhara H, Tanaka Y, Ino I, Yabuya T ( 2005 ) cDNA cloning and characterization of UDP-glucose:anthocyanidin 3-O-glucosyltransferase in Iris hollandica. Plant Sci 169 : 496 – 501 Crossref Search ADS Author notes 1 This work was supported by Degussa AG. 2 Present address: Department of Pharmacology, Vanderbilt University, Nashville, TN 37232. 3 Present address: Department of Plant Sciences, Weizmann Institute of Science, 76100 Rehovot, Israel. * Corresponding author; e-mail [email protected]. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Wilfried Schwab ([email protected]). [W] The online version of this article contains Web-only data. [OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.107.114280 © 2008 American Society of Plant Biologists © The Author(s) 2008. Published by Oxford University Press on behalf of American Society of Plant Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Tronconi, Marcos A.; Fahnenstich, Holger; Gerrard Weehler, Mariel C.; Andreo, Carlos S.; Flügge, Ulf-Ingo; Drincovich, María F.; Maurino, Verónica G.

doi: 10.1104/pp.107.114975pmid: 18223148

Abstract Although the nonphotosynthetic NAD-malic enzyme (NAD-ME) was assumed to play a central role in the metabolite flux through the tricarboxylic acid cycle, the knowledge on this enzyme is still limited. Here, we report on the identification and characterization of two genes encoding mitochondrial NAD-MEs from Arabidopsis (Arabidopsis thaliana), AtNAD-ME1 and AtNAD-ME2. The encoded proteins can be grouped into the two clades found in the plant NAD-ME phylogenetic tree. AtNAD-ME1 belongs to the clade that includes known α-subunits with molecular masses of approximately 65 kD, while AtNAD-ME2 clusters with the known β-subunits with molecular masses of approximately 58 kD. The separated recombinant proteins showed NAD-ME activity, presented comparable kinetic properties, and are dimers in their active conformation. Native electrophoresis coupled to denaturing electrophoresis revealed that in vivo AtNAD-ME forms a dimer of nonidentical subunits in Arabidopsis. Further support for this conclusion was obtained by reconstitution of the active heterodimer in vitro. The characterization of loss-of-function mutants for both AtNAD-MEs indicated that both proteins also exhibit enzymatic activity in vivo. Neither the single nor the double mutants showed a growth or developmental phenotype, suggesting that NAD-ME activity is not essential for normal autotrophic development. Nevertheless, metabolic profiling of plants completely lacking NAD-ME activity revealed differential patterns of modifications in light and dark periods and indicates a major role for NAD-MEs during nocturnal metabolism. The enzymatic oxidation of l-malate to pyruvate and CO2 is catalyzed by two classes of malic enzymes (MEs) with the general requirement for divalent cations: NADP-dependent ME (NADP-ME; EC 1.1.1.40) and NAD-dependent ME (NAD-ME; EC 1.1.1.39 or 1.1.1.38, depending on the ability to decarboxylate oxaloacetate [OAA]). In plants, NADP-ME isoforms function in chloroplasts and the cytosol (Drincovich et al., 2001; Gerrard Wheeler et al., 2005), while NAD-ME isoforms are found in mitochondria (Winning et al., 1994). Photosynthetic NADP-ME isoforms are involved in metabolism in chloroplasts (C4 plants) or the cytosol (Crassulacean acid metabolism [CAM] plants; Drincovich et al., 2001), while plastidic nonphotosynthetic isoforms have been suggested to play a role in plant defense responses and lipid biosynthesis (Smith et al., 1992; Eastmond et al., 1997; Casati et al., 1999; Maurino et al., 2001). Several biological roles were proposed for the cytosolic NADP-ME isoforms, including participation in plant defense responses, lignin biosynthesis, and control of cytosolic pH (Martinoia and Rentsch, 1994). In some C4 and CAM plants, NAD-MEs provide CO2 for the Calvin cycle during photosynthetic metabolism (Hatch and Kagawa, 1974; Artus and Edwards, 1985). In some C4 plant species, NAD-ME is present at an activity of around 50 times that found in C3 plants and functions in bundle sheath mitochondria (Hatch and Carnal, 1992). Apart from the photosynthetic role, NAD-ME is also involved in malate respiration, a universal role that takes place in the mitochondria (Grover et al., 1981). Two sources of respiratory substrates are furnished to plant mitochondria: pyruvate and malate. Depending on the metabolic demands, it is possible that dark CO2 fixation diverts much phosphoenolpyruvate from pyruvate to malate formation, with malate entering the mitochondria and fulfilling two roles, replenishment of the tricarboxylic acid (TCA) cycle pool and furnishing part of the carbon used for mitochondrial respiration (Day and Hanson, 1977). In mitochondria, malate can be metabolized by malate dehydrogenase (MDH) or NAD-ME. In the latter case, malate is decarboxylated to pyruvate and this, in turn, is converted to acetyl-CoA, which by condensation with oxalacetate forms citrate, allowing repeated cycling of carbon skeletons through the TCA cycle. By providing a means of generating acetyl-CoA and thus ATP and carbon skeletons, NAD-ME was assumed to play a central role in the management of flux through the TCA cycle (Grover et al., 1981). It was postulated that the pH is an important modulator of this branch point: at pH 6.5, malate would be mainly oxidized by the NAD-ME, while at pH 7.5, where NAD-ME is inactive, malate is oxidized by the mitochondrial MDH (Palmer et al., 1982; Agius et al., 2001). Nonplant NAD-MEs are typically homotetrameric proteins (Caldes et al., 1978; Allen and Harris, 1981; Nagel and Sauer, 1982; Moreadith and Lehninger, 1984; Davisson and Schulz, 1985) and belong to the EC 1.1.1.38 subtype. On the other hand, plant NAD-ME, although very few have been characterized, belong to the EC 1.1.1.39 subtype, as they are not able to decarboxylate oxalacetate (Grover et al., 1981; Wedding and Black, 1983). One intriguing property of plant NAD-ME is that they are composed of two dissimilar subunits (α and β) at a 1:1 molar radio, at least in some species, e.g. Crassula argentea (CAM plant; Willeford and Wedding, 1987), potato (Solanum tuberosum; C3 plant; Grover and Wedding, 1982; Willeford and Wedding, 1987), Urochloa panicoides (C4-PEPCK plant; Burnell, 1987), and Amaranthus hypochondriacus (C4-NAD-ME plant; Long et al., 1994). Although the α- and β-subunits contain all the motifs required for a functional NAD-ME (Winning et al., 1994; Long et al., 1994), no activity was associated with the separated subunits, but activity could be found in a reconstituted system in potato and C. argentea (Willeford and Wedding, 1987). The β-subunit was suggested to play a regulatory role (Long et al., 1994). The cDNAs encoding for both subunits were isolated from potato and amaranth (Long et al., 1994; Winning et al., 1994). These subunits share 65% sequence identity at the amino acid level and are immunologicaly different, as antisera raised against the α-subunit did not cross react with the β-subunit (Long et al., 1994). The enzyme is active as a dimer, tetramer, and octamer, with the tetramer being the most active form (Grover and Wedding, 1982). On the other hand, the enzyme isolated from Eleusine coracana, Panicum dichotomiflorum, and Amaranthus tricolor (all C4-NAD-ME plants) was postulated to form an octamer of identical subunits (Oshugi and Murata, 1980; Murata et al., 1989). The genome of Arabidopsis (Arabidopsis thaliana) possesses two genes encoding putative NAD-MEs. Due to the assumed central role of NAD-ME in plant mitochondria, the aim of this work was to characterize the AtNAD-ME gene family at the biochemical and functional levels. Based on the biochemical characterization of recombinant proteins and metabolite profiles of loss-of-function mutants, novel properties for plant NAD-MEs are described. RESULTS Cloning and Sequence Analysis of AtNAD-ME1 and AtNAD-ME2 Two putative AtNAD-ME genes are present in the Arabidopsis genome, AtNAD-ME1 (At2g13560) and AtNAD-ME2 (At4g00570). The full-length cDNAs encoding AtNAD-ME1 and AtNAD-ME2 were cloned by reverse transcription (RT)-PCR and sequenced. The deduced proteins have molecular masses of 69.6 and 66.6 kD, respectively, share 63% identity at the amino acid level and are both predicted to contain a mitochondrial targeting peptide by four different prediction programs (ARAMEMNON, http://aramemnon.botanik.uni-koeln.de/). A phylogenetic analysis based on an alignment of the available plant NAD-ME full-length protein sequences indicated that NAD-MEs are divided into two clades: (1) the α-NAD-MEs, which include proteins of approximately 62 kD; and (2) the β-NAD-MEs, which include proteins of approximately 58 kD. AtNAD-ME1 and AtNAD-ME2 belong to the α- and β-NAD-ME clades, respectively (Fig. 1 Figure 1. Open in new tabDownload slide Phylogenetic tree of plant NAD-MEs. Mature proteins were aligned using the ClustalW (1.81) multiple alignment program (Thompson et al., 1994), and the alignment obtained was modified by visual inspection to exclude the sites containing gaps. The phylogenetic tree was constructed by the neighbor-joining method using the Phylip software package (Felsenstein, 1989). Statistical significance of each branch of the tree was evaluated by bootstrap analysis by 100 iterations of bootstrap samplings and reconstruction of trees by the neighbor-joining method. The topology obtained by this method is shown along with statistical significance of each branch. The following sequences are included: α-subunits from A. hypochondriacus (U01162; photosynthetic NAD-ME), Arabidopsis (At2g13560), potato (Z23023), and Oryza sativa (NM_001066235), and β-subunits from Arabidopsis (At4g00570), O. sativa (NM_001071533), and potato (Z23002). Figure 1. Open in new tabDownload slide Phylogenetic tree of plant NAD-MEs. Mature proteins were aligned using the ClustalW (1.81) multiple alignment program (Thompson et al., 1994), and the alignment obtained was modified by visual inspection to exclude the sites containing gaps. The phylogenetic tree was constructed by the neighbor-joining method using the Phylip software package (Felsenstein, 1989). Statistical significance of each branch of the tree was evaluated by bootstrap analysis by 100 iterations of bootstrap samplings and reconstruction of trees by the neighbor-joining method. The topology obtained by this method is shown along with statistical significance of each branch. The following sequences are included: α-subunits from A. hypochondriacus (U01162; photosynthetic NAD-ME), Arabidopsis (At2g13560), potato (Z23023), and Oryza sativa (NM_001066235), and β-subunits from Arabidopsis (At4g00570), O. sativa (NM_001071533), and potato (Z23002). ). Specific Expression of AtNAD-ME Genes To study the tissue-specific expression of AtNAD-ME genes, quantitative real-time (qRT)-PCR experiments were performed. Transcripts for both AtNAD-ME1 and AtNAD-ME2 were detected in all the organs tested. In all cases, the transcript levels of AtNAD-ME1 were higher than that of AtNAD-ME2 (Fig. 2A Figure 2. Open in new tabDownload slide Expression analysis of AtNAD-ME in different tissues. A, Expression of AtNAD-ME1 transcript relative to AtNAD-ME2 mRNA levels for each organ analyzed by qRT-PCR. B, Relative expression of AtNAD-ME1 and AtNAD-ME2 in different organs with respect to leaf analyzed by qRT-PCR. The y axis refers to the fold-difference of a particular AtNAD-ME transcript level relative to its amount found in leaf. The asterisks indicate that the expression values obtained were statistically significantly different from the ones obtained for leaf as determined by the Student's t test (P < 0.05). C, Analysis of AtNAD-ME∷GUS expression. a to j, AtNAD-ME1∷GUS; k to s, AtNAD-ME2∷GUS. a to d and k to m, Seedlings at 3, 5, and 12 DAI. e and n, Three-week-old rosette. f and o, Longitudinal section through the stem. g and p, Root system of a 3-week-old plant. h and q, Close-ups of the roots. i and r, Inflorescence with flowers at different stages. j and s, Siliques. Figure 2. Open in new tabDownload slide Expression analysis of AtNAD-ME in different tissues. A, Expression of AtNAD-ME1 transcript relative to AtNAD-ME2 mRNA levels for each organ analyzed by qRT-PCR. B, Relative expression of AtNAD-ME1 and AtNAD-ME2 in different organs with respect to leaf analyzed by qRT-PCR. The y axis refers to the fold-difference of a particular AtNAD-ME transcript level relative to its amount found in leaf. The asterisks indicate that the expression values obtained were statistically significantly different from the ones obtained for leaf as determined by the Student's t test (P < 0.05). C, Analysis of AtNAD-ME∷GUS expression. a to j, AtNAD-ME1∷GUS; k to s, AtNAD-ME2∷GUS. a to d and k to m, Seedlings at 3, 5, and 12 DAI. e and n, Three-week-old rosette. f and o, Longitudinal section through the stem. g and p, Root system of a 3-week-old plant. h and q, Close-ups of the roots. i and r, Inflorescence with flowers at different stages. j and s, Siliques. ). The comparison of the abundance of each transcript relative to the expression in leaves indicated that both genes have the same relative level of expression in all mature organs (Fig. 2B). The expression was similar in leaves and stems (100%), while the expression in flowers and roots accounted for 60% and 4% of the level in leaves, respectively (Fig. 2B). To investigate more precisely the organ- and tissue-specific expression of both AtNAD-ME genes, transgenic Arabidopsis plants expressing the GUS reporter gene driven by the AtNAD-ME promoters were generated and analyzed throughout development. About eight transgenic AtNAD-ME∷GUS lines were analyzed in detail, most of them showing a similar tissue-specific pattern of AtNAD-ME1 and AtNAD-ME2 expression. The pattern of GUS activity was very similar for the AtNAD-ME1∷GUS and AtNAD-ME2∷GUS plants (Fig. 2C). In both cases, GUS expression could be observed 2 d after imbibition (DAI) in the cotyledons, hypocotyls, and root tip (data not shown). At 3 DAI, the roots were completely stained (Fig. 2C, a and k) and in the case of AtNAD-ME1-promoter∷GUS plants, the root tip was highly stained (Fig. 2C, a). A high expression was observed in trichomes and trichome basal cells, especially in AtNAD-ME1∷GUS plants (Fig. 2C, b and l). At 5 DAI, both root tips were highly stained, and expression in all seedling tissues was maintained (Fig. 2C, c and ll). At 12 DAI, GUS expression was very low in the new leaves but became higher with maturation (Fig. 2C, d, e, m, and n). At all developmental stages, the expression in leaves was observed in the mesophyll and the cells that surround the vascular bundles (bundle sheet cells; Supplemental Fig. S1). Stems (Fig. 2C, f and o) and roots (Fig. 2C, g, h, p, and q) presented high expression in all tissues in both AtNAD-ME∷GUS plants. It is interesting to note that longitudinal sections of stems revealed a high level of activity of both promoters around the vascular system (Fig. 2C, f and o). In the reproductive organs of both lines, GUS expression was detected in the apical part of the gynoecium, stigmatic papillae, the filaments, and sepals (Fig. 2C, i and r). In developing siliques, expression was high in the apical part and the abscission zone (Fig. 2C, i, j, r, and s). It is worth mentioning that the GUS expression driven by the AtNAD-ME1-promoter was always stronger than by AtNAD-ME2-promoter in all lines tested. It should also be noted that the observations described above are consistent with AtGenExpress data from the Genevestigator microarray database (Zimmermann et al., 2004; http://www.genevestigator.ethz.ch/). Biochemical and Structural Properties of Recombinant AtNAD-MEs To assess whether the two predicted AtNAD-MEs are enzymatically active proteins, AtNAD-ME1 and AtNAD-ME2 cDNAs were cloned and expressed as recombinant proteins. The prediction of the length of the mitochondrial targeting sequences was performed by sequence comparison with potato NAD-ME and the assistance of prediction programs (ARAMEMNON, http://aramemnon.botanik.uni-koeln.de/). After eliminating mitochondrial targeting sequences of 38 and 31 amino acid residues for AtNAD-ME1 and AtNAD-ME2, respectively, the mature proteins were expressed in Escherichia coli. Following induction of the expression by isopropyl-β-thiogalactopyranoside or lactose, proteins with the expected molecular masses of 80 and 76 kD (AtNAD-ME1 and AtNAD-ME2, respectively) were purified by affinity chromatography (Fig. 3A Figure 3. Open in new tabDownload slide Recombinant Arabidopsis NAD-ME isoforms analyzed by gel electrophoresis. A, Coomassie-stained SDS-PAGE of recombinant NAD-ME isoforms. Five micrograms of purified recombinant AtNAD-ME1 and AtNAD-ME2 before (1) and after (2) enterokinase digestion was loaded in each case. The estimated molecular mass of the purified proteins is indicated on the right. B, Native-PAGE stained for NAD-ME activity. Approximately 20 milliunits of AtNAD-ME1 and AtNAD-ME2 were loaded, as well as a mixture of equal amounts of both proteins. A mitochondrial leaf crude extract (L, 20 milliunits) was also loaded in the gel. C, Western blot of native-PAGE using antibodies against A. hypochondriacus α-NAD-ME. Approximately 5 μg of NAD-ME1 and AtNAD-ME2 were loaded, as well as a mixture of equal amounts of both proteins. A mitochondrial leaf crude extract (L, 30 μg) was also loaded in the gel. Molecular mass markers (M) were run in parallel and stained with Coomassie Blue. Figure 3. Open in new tabDownload slide Recombinant Arabidopsis NAD-ME isoforms analyzed by gel electrophoresis. A, Coomassie-stained SDS-PAGE of recombinant NAD-ME isoforms. Five micrograms of purified recombinant AtNAD-ME1 and AtNAD-ME2 before (1) and after (2) enterokinase digestion was loaded in each case. The estimated molecular mass of the purified proteins is indicated on the right. B, Native-PAGE stained for NAD-ME activity. Approximately 20 milliunits of AtNAD-ME1 and AtNAD-ME2 were loaded, as well as a mixture of equal amounts of both proteins. A mitochondrial leaf crude extract (L, 20 milliunits) was also loaded in the gel. C, Western blot of native-PAGE using antibodies against A. hypochondriacus α-NAD-ME. Approximately 5 μg of NAD-ME1 and AtNAD-ME2 were loaded, as well as a mixture of equal amounts of both proteins. A mitochondrial leaf crude extract (L, 30 μg) was also loaded in the gel. Molecular mass markers (M) were run in parallel and stained with Coomassie Blue. ). After enterokinase digestion to remove the His tag used for purification, products of 63 and 58 kD were obtained for AtNAD-ME1 and AtNAD-ME2, respectively (Fig. 3A). Both recombinant proteins were recognized by the anti-A. hypochondriacus α-NAD-ME antibody, although AtNAD-ME1 displayed a higher reactivity (Figs. 3C and 4A). Antibodies raised against AtNAD-ME1 and AtNAD-ME2 reacted with the respective proteins but did not show cross reactivities (Fig. 4A Figure 4. Open in new tabDownload slide SDS- and native-PAGE of mitochondrial extracts analyzed for activity or by western blot. A, SDS-PAGE of leaf mitochondrial extracts (L, 50 μg of total protein) analyzed by western blot using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2), or, alternatively, against A. hypochondriacus α-NAD-ME (a-AhαME). As control, recombinant AtNAD-ME1 (3 μg, ME1) and AtNAD-ME2 (3 μg, ME2) were loaded. B, Native-PAGE of Arabidopsis mitochondrial extracts stained for NAD-ME activity. Approximately 20 milliunits of NAD-ME from mitochondrial crude extracts from leaf (L), stem (S), root (R), and flower (F) was loaded in each lane. Molecular mass markers were run in parallel and stained with Coomassie Blue. C, The active band from leaf mitochondrial crude extracts (excised band from B–L) was excised and analyzed by SDS-PAGE followed by western-blot analysis using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As controls, recombinant purified AtNAD-ME1 and AtNAD-ME2 (3 μg, ME1 and ME2) were loaded. D, Western-blot analysis of native-PAGE of mitochondrial crude extracts (30 μg) from leaf (L), stem (S), root (R), and flower (F) using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As control, recombinant purified AtNAD-ME1 and AtNAD-ME2 (3 μg, ME1 and ME2) were loaded. The molecular masses of the marker proteins run in parallel are indicated. Figure 4. Open in new tabDownload slide SDS- and native-PAGE of mitochondrial extracts analyzed for activity or by western blot. A, SDS-PAGE of leaf mitochondrial extracts (L, 50 μg of total protein) analyzed by western blot using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2), or, alternatively, against A. hypochondriacus α-NAD-ME (a-AhαME). As control, recombinant AtNAD-ME1 (3 μg, ME1) and AtNAD-ME2 (3 μg, ME2) were loaded. B, Native-PAGE of Arabidopsis mitochondrial extracts stained for NAD-ME activity. Approximately 20 milliunits of NAD-ME from mitochondrial crude extracts from leaf (L), stem (S), root (R), and flower (F) was loaded in each lane. Molecular mass markers were run in parallel and stained with Coomassie Blue. C, The active band from leaf mitochondrial crude extracts (excised band from B–L) was excised and analyzed by SDS-PAGE followed by western-blot analysis using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As controls, recombinant purified AtNAD-ME1 and AtNAD-ME2 (3 μg, ME1 and ME2) were loaded. D, Western-blot analysis of native-PAGE of mitochondrial crude extracts (30 μg) from leaf (L), stem (S), root (R), and flower (F) using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As control, recombinant purified AtNAD-ME1 and AtNAD-ME2 (3 μg, ME1 and ME2) were loaded. The molecular masses of the marker proteins run in parallel are indicated. ). These results indicate antigenic differences between both AtNAD-ME proteins. Interestingly, recombinant purified AtNAD-ME1 and AtNAD-ME2 showed both enzymatic activities and could thus be characterized with respect to their kinetic properties (Table I Table I. Kinetic properties of recombinant Arabidopsis NAD-ME isoforms The indicated values, obtained by nonlinear regression, are the average of at least three different measurements ± se. Parameter . NAD-ME1 . NAD-ME2 . pH optimum 6.4 6.6 k cat (s−1) 31.1 ± 1.7 44.1 ± 1.2 K m NAD (mm) 0.50 ± 0.2a 0.50 ± 0.1 k cat/K m NAD 60.2 88.2 K m malate (mm) 3.0 ± 0.7b 3.0 ± 0.2 k cat/K m malate 10.3 14.7 Parameter . NAD-ME1 . NAD-ME2 . pH optimum 6.4 6.6 k cat (s−1) 31.1 ± 1.7 44.1 ± 1.2 K m NAD (mm) 0.50 ± 0.2a 0.50 ± 0.1 k cat/K m NAD 60.2 88.2 K m malate (mm) 3.0 ± 0.7b 3.0 ± 0.2 k cat/K m malate 10.3 14.7 a S0.5 (Hill coefficient = n H = 1.3). b S0.5 (n H = 1.9). Open in new tab Table I. Kinetic properties of recombinant Arabidopsis NAD-ME isoforms The indicated values, obtained by nonlinear regression, are the average of at least three different measurements ± se. Parameter . NAD-ME1 . NAD-ME2 . pH optimum 6.4 6.6 k cat (s−1) 31.1 ± 1.7 44.1 ± 1.2 K m NAD (mm) 0.50 ± 0.2a 0.50 ± 0.1 k cat/K m NAD 60.2 88.2 K m malate (mm) 3.0 ± 0.7b 3.0 ± 0.2 k cat/K m malate 10.3 14.7 Parameter . NAD-ME1 . NAD-ME2 . pH optimum 6.4 6.6 k cat (s−1) 31.1 ± 1.7 44.1 ± 1.2 K m NAD (mm) 0.50 ± 0.2a 0.50 ± 0.1 k cat/K m NAD 60.2 88.2 K m malate (mm) 3.0 ± 0.7b 3.0 ± 0.2 k cat/K m malate 10.3 14.7 a S0.5 (Hill coefficient = n H = 1.3). b S0.5 (n H = 1.9). Open in new tab ). Both isoforms displayed similar k cat values, with AtNAD-ME2 having a 1.3-fold higher k cat value than AtNAD-ME1 (Table I). Comparing the apparent K m values for NAD and malate, AtNAD-ME1 and AtNAD-ME2 exhibited very similar affinities toward both compounds, while AtNAD-ME2 presented the highest catalytic efficiency (k cat/K m; Table I). It is worth mentioning that the kinetic behavior obtained for AtNAD-ME1 with respect to both NAD and malate was nonhyperbolic, presenting some kind of sigmoidicity and thus probable cooperative binding of the ligand in both cases (Table I). The pH optimum for both isoforms was very similar, at about pH 6.5 (Table I). Neither AtNAD-ME1 nor AtNAD-ME2 was able to decarboxylate OAA, even when using high protein concentrations for the assay (data not shown). Thus, both AtNAD-MEs clearly belong to the EC 1.1.1.39 subtype. Native electrophoresis of the purified recombinant AtNAD-MEs was analyzed by activity staining and western blot (Fig. 3, B and C). An active band compatible with a dimeric oligomeric state for the recombinant AtNAD-ME2 was detected by activity staining assays (Fig. 3B). This active band also reacted with the anti-A. hypochondriacus α-NAD-ME-antibody (Fig. 3C). Interestingly, the recombinant AtNAD-ME1 could not be detected by activity staining (even loading up to 40 milliunits of the purified enzyme), although a band with a higher mobility than that of AtNAD-ME2 was obtained by western blot using the anti-A. hypochondriacus α-NAD-ME- antibody (Fig. 3C). As the purified AtNAD-ME1 exhibited enzymatic activity in solution, it is possible that the protein lost its activity during electrophoresis. Size-exclusion chromatography was used to estimate the native molecular masses for both recombinant AtNAD-MEs. The calculated molecular masses for the purified AtNAD-ME1 and AtNAD-ME2 proteins were 120.0 ± 6 and 117.5 ± 6.5 kD, respectively. Thus, although AtNAD-ME1 and AtNAD-ME presented different mobilities by native electrophoresis, probably due to differences in the charge, both proteins obviously assembled as dimers in solution. AtNAD-ME1 and AtNAD-ME2 Form Both Homo- and Heterooligomers in Vitro and in Vivo NAD-ME activity was measured in different organs of mature Arabidopsis plants. Crude extracts from roots showed the highest activity expressed on the basis of total protein concentration (0.038 ± 0.03 units/mg), while leaves, stems, and flowers displayed between 58% and 65% of the activity measured in roots (Fig. 5C Figure 5. Open in new tabDownload slide Identification of nad-me insertion lines. A, AtNAD-ME gene structure showing the locations of the T-DNA insertions in the knockout mutants. The orientation of the T-DNA insertion is indicated as left border (LB). B, Semiquantitative RT-PCR showing the absence of the corresponding AtNAD-ME transcript in the single (nad-me1 and nad-me2) and double (1 × 2) T-DNA knockout lines. PCR products of 750 (NAD-ME1) and 928 (NAD-ME2) bp were amplified using 35 cycles. As loading control, a 521-bp Actin2 cDNA fragment was amplified by 29 cycles. C, NAD-ME activity (units/mg) in different organs of Arabidopsis wild type and the T-DNA insertion lines. The bars indicate the sd of the measurements from three different crude extract preparations. The activity measurement was performed three independent times with each crude extract preparation, with <5% sd within each preparation. Figure 5. Open in new tabDownload slide Identification of nad-me insertion lines. A, AtNAD-ME gene structure showing the locations of the T-DNA insertions in the knockout mutants. The orientation of the T-DNA insertion is indicated as left border (LB). B, Semiquantitative RT-PCR showing the absence of the corresponding AtNAD-ME transcript in the single (nad-me1 and nad-me2) and double (1 × 2) T-DNA knockout lines. PCR products of 750 (NAD-ME1) and 928 (NAD-ME2) bp were amplified using 35 cycles. As loading control, a 521-bp Actin2 cDNA fragment was amplified by 29 cycles. C, NAD-ME activity (units/mg) in different organs of Arabidopsis wild type and the T-DNA insertion lines. The bars indicate the sd of the measurements from three different crude extract preparations. The activity measurement was performed three independent times with each crude extract preparation, with <5% sd within each preparation. ). When extracts of isolated mitochondria from each organ were analyzed by SDS-PAGE followed by western-blot analysis, two well-separated bands could be detected using the anti-A. hypochondriacus α-NAD-ME-antibody (Fig. 4A). On the other hand, while the antibodies raised against AtNAD-ME1 recognize the 63-kD band, the ones raised against AtNAD-ME2 recognized the 58-kD band (Fig. 4A). The molecular masses of the immunoreactive bands in crude extracts correlated well with those of the recombinant purified AtNAD-ME1 and AtNAD-ME2 proteins (Fig. 4A). Interestingly, native PAGE of mitochondrial extracts from different Arabidopsis organs stained for NAD-ME activity showed a unique band of approximately 120 kD (Fig. 4B). To analyze the composition of this activity-containing band, gel slices including the band with activity from the leaf mitochondrial extract were excised from the native PAGE and subjected to SDS-PAGE coupled to western blot using specific antibodies against AtNAD-ME1 or AtNAD-ME2. As shown in Figure 4C, reactive bands corresponding to AtNAD-ME1 (63 kD) and AtNAD-ME2 (58 kD) could be detected. Considering the molecular masses of the separated AtNAD-MEs, these results clearly indicate that the active native band of approximately 120 kD is composed of AtNAD-ME1 and AtNAD-ME2, most probably in a 1:1 ratio. On the other hand, native PAGE of mitochondrial extracts from different Arabidopsis organs analyzed by western blot showed a band of approximately 120 kD using both specific antibodies directed against AtNAD-ME1 or AtNAD-ME2, while the recombinant proteins differ in electrophoretic mobilities and show specific reactions against their own antibodies (Fig. 4D). Moreover, a second immunoreactive band with the same mobility as the recombinant protein was detected in the mitochondrial extracts (Fig. 4D), indicating the possible existence of homodimers in vivo. The interaction of AtNAD-ME1 and AtNAD-ME2 observed in mitochondrial extracts was further tested in vitro using recombinant AtNAD-ME. Purified recombinant AtNAD-ME1 and AtNAD-ME2 were mixed in an equimolar ratio and subsequently analyzed by native PAGE. As shown in Figure 3, B and C, the mixture has active and immunoreactive bands as the isolated recombinant proteins, and, additionally, it has a band with similar mobility to that observed in the mitochondrial extracts. Taken together, these results revealed that the separated AtNAD-ME1 and AtNAD-ME2 assemble as active dimers and associate to form a heterodimer in vitro and in vivo. Isolation and Characterization of T-DNA Insertion Mutants of AtNAD-ME1 and AtNAD-ME2 Arabidopsis insertion mutants that contained T-DNA elements inserted in the AtNAD-ME1 and AtNAD-ME2 genes were isolated from the Sail-lines (Fig. 5A). Homozygous lines for each mutant were confirmed by PCR and designated nad-me1.1 (Sail-374-A02) and nad-me2.1 (Sail-291-C05), respectively. The sites of the insertions were analyzed by sequencing the PCR products obtained after amplifying both ends of the T-DNA insertion and the flanking genomic DNA. The knockout line nad-me1.1 had an insertion in exon 4 (at position +833 bp), and in line nad-me2.1 the insertion was localized in exon 5 (at position +1,030 bp). The mutant lines showed no expression of the corresponding genes as analyzed by RT-PCR (Fig. 5B), and the absence of the corresponding protein was confirmed by western blot using specific antibodies (data not shown). A second allelic mutant for each gene (Sail-374-A02, nad-me1.2 and Salk-131720, nad-me2.2) was also isolated and characterized in parallel, but the lines were not included in this work. As growth and development of all the single mutants analyzed did not show visual differences with respect to the wild type, homozygous double mutants were generated between nad-me.1.1 and nad-me2.1 by crossing. The absence of transcripts and proteins for both AtNAD-MEs in the double mutants was confirmed by RT-PCR and western blot (Fig. 5B; data not shown). Figure 5C shows residual NAD-ME activities measured in different organs from nad-me1.1 and nad-me2.1. The results indicated that in vivo, both AtNAD-ME1 and AtNAD-ME2 exhibit enzymatic activity and that AtNAD-ME2 possesses the highest specific activity, results that correlate well with those obtained for the recombinant proteins. The double mutant did not show any NAD-ME activity, indicating that AtNAD-ME1 and AtNAD-ME2 are solely responsible for the NAD-ME activities measured in crude extracts. Native PAGE conducted with mitochondria extracted from both single mutants showed an immunoreactive band corresponding to the remaining functional AtNAD-ME protein, while in the double knockout extracts, no immunoreactive band was detected (data not shown). It is worth mentioning that transcript levels of the remaining intact AtNAD-ME gene in the organs of each single mutant did not show significant difference relative to the expression observed in the wild-type organs when analyzed by qRT-PCR (data not shown). The germination, development, vegetative growth, and flowering time of the double knockouts were very similar to that of the wild type and the single knockout mutants when grown either at moderate (100 μmol m−2 s−1) or high (500 μmol m−2 s−1) light intensities. The data obtained indicated that there are no statistical differences in rosette diameter or dry weight between the wild type and homozygous mutants grown in both conditions (Table II Table II. Growth and photosynthetic parameters of the T-DNA insertional lines and the wild type grown for 5 weeks in long days at a photon flux density of 100 μmol m−2 s−1 DW, Dry weight; RD, rosette diameter; ETR measured at 800 μmol m−2 s−1. Values are means ± sd of determinations made on eight plants. . Wild Type . nad1.1 . nad2.1 . nad1.1 × 2.1 . DW (mg) 6.75 ± 0.08 6.76 ± 0.05 6.76 ± 0.07 6.78 ± 0.03 RD (cm) 6.86 ± 0.64 7.09 ± 0.73 7.09 ± 0.76 6.97 ± 0.46 ETR (μmol m−2 s−1) 80.9 ± 3.3 76.1 ± 8.8 83.4 ± 1.9 81.2 ± 3.0 Maximum quantum efficiency of PSII 0.713 ± 0.008 0.713 ± 0.003 0.726 ± 0.005 0.720 ± 0.002 . Wild Type . nad1.1 . nad2.1 . nad1.1 × 2.1 . DW (mg) 6.75 ± 0.08 6.76 ± 0.05 6.76 ± 0.07 6.78 ± 0.03 RD (cm) 6.86 ± 0.64 7.09 ± 0.73 7.09 ± 0.76 6.97 ± 0.46 ETR (μmol m−2 s−1) 80.9 ± 3.3 76.1 ± 8.8 83.4 ± 1.9 81.2 ± 3.0 Maximum quantum efficiency of PSII 0.713 ± 0.008 0.713 ± 0.003 0.726 ± 0.005 0.720 ± 0.002 Open in new tab Table II. Growth and photosynthetic parameters of the T-DNA insertional lines and the wild type grown for 5 weeks in long days at a photon flux density of 100 μmol m−2 s−1 DW, Dry weight; RD, rosette diameter; ETR measured at 800 μmol m−2 s−1. Values are means ± sd of determinations made on eight plants. . Wild Type . nad1.1 . nad2.1 . nad1.1 × 2.1 . DW (mg) 6.75 ± 0.08 6.76 ± 0.05 6.76 ± 0.07 6.78 ± 0.03 RD (cm) 6.86 ± 0.64 7.09 ± 0.73 7.09 ± 0.76 6.97 ± 0.46 ETR (μmol m−2 s−1) 80.9 ± 3.3 76.1 ± 8.8 83.4 ± 1.9 81.2 ± 3.0 Maximum quantum efficiency of PSII 0.713 ± 0.008 0.713 ± 0.003 0.726 ± 0.005 0.720 ± 0.002 . Wild Type . nad1.1 . nad2.1 . nad1.1 × 2.1 . DW (mg) 6.75 ± 0.08 6.76 ± 0.05 6.76 ± 0.07 6.78 ± 0.03 RD (cm) 6.86 ± 0.64 7.09 ± 0.73 7.09 ± 0.76 6.97 ± 0.46 ETR (μmol m−2 s−1) 80.9 ± 3.3 76.1 ± 8.8 83.4 ± 1.9 81.2 ± 3.0 Maximum quantum efficiency of PSII 0.713 ± 0.008 0.713 ± 0.003 0.726 ± 0.005 0.720 ± 0.002 Open in new tab ; data not shown). Moreover, the photosynthetic parameters maximum quantum efficiency of PSII and electron transport rate (ETR; Table II) and the qP and qN values (data not shown) indicated no differences between the knockout mutants and the wild type. AtNAD-ME Is More Active during the Night Period, and Mutant Lines Completely Lacking NAD-ME Activity Display Altered Steady-State Levels of Sugars and Amino Acids To gain further information about the extent of physiological disturbances generated by the lack of total NAD-ME activity, metabolite profiling analyses using gas chromatography-mass spectrometry (GC-MS; Fahnenstich et al., 2007) were performed using whole rosettes of mature plants harvested at the end of the light and the dark period. This study revealed distinct alterations in the metabolic status of the double loss-of-function mutant depending on the light/dark period. While both the double knockout mutant and the wild type showed the same accumulation of starch by the end of both periods (data not shown), the contents of a range of other metabolites were altered in the mutant compared to the wild type (Table III Table III. Metabolite content determined by GC-MS of plants lacking NAD-ME activity Values are mean ± se of four different biological replicas, each consisting of four determinations made on eight plants. The values are relative to the respective wild type (each metabolite = 1; the corresponding complete data set of metabolites is available in Supplemental Table S1). Those values that are significantly different from the respective wild type as determined by the Student's t test (P < 0.05) are in bold type. . nad1 × 2 . . . End of the Day . End of the Night . Ala 0.98 ± 0.21 1.34 ± 0.13 Asn 0.88 ± 0.16 2.52 ± 0.35 Asp 0.87 ± 0.09 1.29 ± 0.10 γ-Aminobutyrate 1.00 ± 0.09 1.91 ± 0.22 Glu 0.92 ± 0.07 1.40 ± 0.12 Gln 0.89 ± 0.15 3.51 ± 0.40 Gly 0.87 ± 0.11 1.78 ± 0.23 His 1.13 ± 0.26 1.63 ± 0.18 Ile 0.87 ± 0.11 1.15 ± 0.15 Leu 0.81 ± 0.11 1.15 ± 0.16 Lys 1.26 ± 0.18 1.89 ± 0.29 Met 1.26 ± 0.08 1.32 ± 0.10 Phe 0.86 ± 0.08 1.25 ± 0.11 Pro 0.81 ± 0.12 1.63 ± 0.40 Ser 0.92 ± 0.09 1.96 ± 0.20 Thr 1.13 ± 0.07 1.47 ± 0.14 Val 1.07 ± 0.09 1.23 ± 0.15 Citrate 0.60 ± 0.13 0.72 ± 0.07 2-Oxoglutarate 0.75 ± 0.06 1.30 ± 0.05 Succinate 0.82 ± 0.06 1.43 ± 0.15 Fumarate 0.84 ± 0.11 0.57 ± 0.08 Malate 0.84 ± 0.12 1.13 ± 0.07 OAA 1.18 ± 0.13 0.87 ± 0.14 Pyruvate 0.76 ± 0.11 0.91 ± 0.13 Ara 1.08 ± 0.07 0.92 ± 0.08 Ascorbate 1.43 ± 0.25 1.03 ± 0.30 Fru 1.43 ± 0.18 1.06 ± 0.22 Gal 1.77 ± 0.19 0.71 ± 0.10 Glc 1.57 ± 0.12 1.12 ± 0.17 Man 1.33 ± 0.17 0.73 ± 0.11 Rib 0.83 ± 0.16 1.64 ± 0.24 Suc 1.42 ± 0.13 0.98 ± 0.06 3-PGA 1.14 ± 0.20 1.11 ± 0.10 DHAP 0.76 ± 0.12 1.41 ± 0.20 Lactate 1.01 ± 0.17 1.47 ± 0.27 Glycerate 0.98 ± 0.09 1.14 ± 0.15 Glycerol 1.26 ± 0.08 1.39 ± 0.22 Glycolate 1.56 ± 0.39 1.09 ± 0.43 Glyoxylate 1.22 ± 0.14 1.07 ± 0.11 . nad1 × 2 . . . End of the Day . End of the Night . Ala 0.98 ± 0.21 1.34 ± 0.13 Asn 0.88 ± 0.16 2.52 ± 0.35 Asp 0.87 ± 0.09 1.29 ± 0.10 γ-Aminobutyrate 1.00 ± 0.09 1.91 ± 0.22 Glu 0.92 ± 0.07 1.40 ± 0.12 Gln 0.89 ± 0.15 3.51 ± 0.40 Gly 0.87 ± 0.11 1.78 ± 0.23 His 1.13 ± 0.26 1.63 ± 0.18 Ile 0.87 ± 0.11 1.15 ± 0.15 Leu 0.81 ± 0.11 1.15 ± 0.16 Lys 1.26 ± 0.18 1.89 ± 0.29 Met 1.26 ± 0.08 1.32 ± 0.10 Phe 0.86 ± 0.08 1.25 ± 0.11 Pro 0.81 ± 0.12 1.63 ± 0.40 Ser 0.92 ± 0.09 1.96 ± 0.20 Thr 1.13 ± 0.07 1.47 ± 0.14 Val 1.07 ± 0.09 1.23 ± 0.15 Citrate 0.60 ± 0.13 0.72 ± 0.07 2-Oxoglutarate 0.75 ± 0.06 1.30 ± 0.05 Succinate 0.82 ± 0.06 1.43 ± 0.15 Fumarate 0.84 ± 0.11 0.57 ± 0.08 Malate 0.84 ± 0.12 1.13 ± 0.07 OAA 1.18 ± 0.13 0.87 ± 0.14 Pyruvate 0.76 ± 0.11 0.91 ± 0.13 Ara 1.08 ± 0.07 0.92 ± 0.08 Ascorbate 1.43 ± 0.25 1.03 ± 0.30 Fru 1.43 ± 0.18 1.06 ± 0.22 Gal 1.77 ± 0.19 0.71 ± 0.10 Glc 1.57 ± 0.12 1.12 ± 0.17 Man 1.33 ± 0.17 0.73 ± 0.11 Rib 0.83 ± 0.16 1.64 ± 0.24 Suc 1.42 ± 0.13 0.98 ± 0.06 3-PGA 1.14 ± 0.20 1.11 ± 0.10 DHAP 0.76 ± 0.12 1.41 ± 0.20 Lactate 1.01 ± 0.17 1.47 ± 0.27 Glycerate 0.98 ± 0.09 1.14 ± 0.15 Glycerol 1.26 ± 0.08 1.39 ± 0.22 Glycolate 1.56 ± 0.39 1.09 ± 0.43 Glyoxylate 1.22 ± 0.14 1.07 ± 0.11 Open in new tab Table III. Metabolite content determined by GC-MS of plants lacking NAD-ME activity Values are mean ± se of four different biological replicas, each consisting of four determinations made on eight plants. The values are relative to the respective wild type (each metabolite = 1; the corresponding complete data set of metabolites is available in Supplemental Table S1). Those values that are significantly different from the respective wild type as determined by the Student's t test (P < 0.05) are in bold type. . nad1 × 2 . . . End of the Day . End of the Night . Ala 0.98 ± 0.21 1.34 ± 0.13 Asn 0.88 ± 0.16 2.52 ± 0.35 Asp 0.87 ± 0.09 1.29 ± 0.10 γ-Aminobutyrate 1.00 ± 0.09 1.91 ± 0.22 Glu 0.92 ± 0.07 1.40 ± 0.12 Gln 0.89 ± 0.15 3.51 ± 0.40 Gly 0.87 ± 0.11 1.78 ± 0.23 His 1.13 ± 0.26 1.63 ± 0.18 Ile 0.87 ± 0.11 1.15 ± 0.15 Leu 0.81 ± 0.11 1.15 ± 0.16 Lys 1.26 ± 0.18 1.89 ± 0.29 Met 1.26 ± 0.08 1.32 ± 0.10 Phe 0.86 ± 0.08 1.25 ± 0.11 Pro 0.81 ± 0.12 1.63 ± 0.40 Ser 0.92 ± 0.09 1.96 ± 0.20 Thr 1.13 ± 0.07 1.47 ± 0.14 Val 1.07 ± 0.09 1.23 ± 0.15 Citrate 0.60 ± 0.13 0.72 ± 0.07 2-Oxoglutarate 0.75 ± 0.06 1.30 ± 0.05 Succinate 0.82 ± 0.06 1.43 ± 0.15 Fumarate 0.84 ± 0.11 0.57 ± 0.08 Malate 0.84 ± 0.12 1.13 ± 0.07 OAA 1.18 ± 0.13 0.87 ± 0.14 Pyruvate 0.76 ± 0.11 0.91 ± 0.13 Ara 1.08 ± 0.07 0.92 ± 0.08 Ascorbate 1.43 ± 0.25 1.03 ± 0.30 Fru 1.43 ± 0.18 1.06 ± 0.22 Gal 1.77 ± 0.19 0.71 ± 0.10 Glc 1.57 ± 0.12 1.12 ± 0.17 Man 1.33 ± 0.17 0.73 ± 0.11 Rib 0.83 ± 0.16 1.64 ± 0.24 Suc 1.42 ± 0.13 0.98 ± 0.06 3-PGA 1.14 ± 0.20 1.11 ± 0.10 DHAP 0.76 ± 0.12 1.41 ± 0.20 Lactate 1.01 ± 0.17 1.47 ± 0.27 Glycerate 0.98 ± 0.09 1.14 ± 0.15 Glycerol 1.26 ± 0.08 1.39 ± 0.22 Glycolate 1.56 ± 0.39 1.09 ± 0.43 Glyoxylate 1.22 ± 0.14 1.07 ± 0.11 . nad1 × 2 . . . End of the Day . End of the Night . Ala 0.98 ± 0.21 1.34 ± 0.13 Asn 0.88 ± 0.16 2.52 ± 0.35 Asp 0.87 ± 0.09 1.29 ± 0.10 γ-Aminobutyrate 1.00 ± 0.09 1.91 ± 0.22 Glu 0.92 ± 0.07 1.40 ± 0.12 Gln 0.89 ± 0.15 3.51 ± 0.40 Gly 0.87 ± 0.11 1.78 ± 0.23 His 1.13 ± 0.26 1.63 ± 0.18 Ile 0.87 ± 0.11 1.15 ± 0.15 Leu 0.81 ± 0.11 1.15 ± 0.16 Lys 1.26 ± 0.18 1.89 ± 0.29 Met 1.26 ± 0.08 1.32 ± 0.10 Phe 0.86 ± 0.08 1.25 ± 0.11 Pro 0.81 ± 0.12 1.63 ± 0.40 Ser 0.92 ± 0.09 1.96 ± 0.20 Thr 1.13 ± 0.07 1.47 ± 0.14 Val 1.07 ± 0.09 1.23 ± 0.15 Citrate 0.60 ± 0.13 0.72 ± 0.07 2-Oxoglutarate 0.75 ± 0.06 1.30 ± 0.05 Succinate 0.82 ± 0.06 1.43 ± 0.15 Fumarate 0.84 ± 0.11 0.57 ± 0.08 Malate 0.84 ± 0.12 1.13 ± 0.07 OAA 1.18 ± 0.13 0.87 ± 0.14 Pyruvate 0.76 ± 0.11 0.91 ± 0.13 Ara 1.08 ± 0.07 0.92 ± 0.08 Ascorbate 1.43 ± 0.25 1.03 ± 0.30 Fru 1.43 ± 0.18 1.06 ± 0.22 Gal 1.77 ± 0.19 0.71 ± 0.10 Glc 1.57 ± 0.12 1.12 ± 0.17 Man 1.33 ± 0.17 0.73 ± 0.11 Rib 0.83 ± 0.16 1.64 ± 0.24 Suc 1.42 ± 0.13 0.98 ± 0.06 3-PGA 1.14 ± 0.20 1.11 ± 0.10 DHAP 0.76 ± 0.12 1.41 ± 0.20 Lactate 1.01 ± 0.17 1.47 ± 0.27 Glycerate 0.98 ± 0.09 1.14 ± 0.15 Glycerol 1.26 ± 0.08 1.39 ± 0.22 Glycolate 1.56 ± 0.39 1.09 ± 0.43 Glyoxylate 1.22 ± 0.14 1.07 ± 0.11 Open in new tab ; the complete data set of metabolites is available in Supplemental Table S1). At the end of the light period, the double knockout mutant showed an accumulation of mono- and disaccharides, such as Fru, Gal, Glc, and Suc (Table III). The levels of intermediates of the TCA cycle and of amino acids were comparable to those of the wild type, except citrate was decreased (Table III). In contrast, at the end of the night period, the carbohydrate levels were invariable with respect to the wild type, while many amino acids, principally those derived from 2-oxoglutarate and OAA, accumulated in the double knockout mutant (Table III). Moreover, the contents of the TCA metabolites were also altered. In the double knockout mutant, the levels of 2-oxoglutarate and succinate were higher, while that of citrate and fumarate were lower, and those of malate, pyruvate, and OAA were invariable compared to the wild type. Due to the differences found in the metabolic profile in the double loss-of-function mutant, the total NAD-ME activity, NAD-ME protein amount and the expression levels of both genes were analyzed at the end of the light and night periods in the wild type. Leaf crude extracts contained about 20% higher NAD-ME specific activities at the end of the night period than at the end of the day period (Fig. 6A Figure 6. Open in new tabDownload slide Diurnal changes in NAD-ME activity and expression level in wild-type leaves. A, Total NAD-ME activity at the end of the day and night periods. The bars indicate the sd of the measurements from three different crude extracts preparations. The activity measurement was performed three independent times with each crude extract preparation. The asterisk indicates that the NAD-ME activity determined at the end of the night period was statistically significantly higher than the one at the end of the light period as determined by the Student's t test (P < 0.05). B, SDS-PAGE of leaf crude extracts (50 μg of total protein) prepared at the end of the light and night periods and analyzed by western blot using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As control of the amount of protein loaded, antibodies against A. viridis PEPc (a-AvPEPc) were also used for detection. The estimated molecular mass of the immunoreactive bands is indicated on the left. C, Expression of AtNAD-ME1 and AtNAD-ME2 transcripts by the end of the night period relative to the expression by the end of the day period analyzed by qRT-PCR. The bars indicate the sd of measurements from three different biological replicates. For both genes, the relative expression values obtained at the end of the night period were statistically significantly higher than the ones at the end of the light period as determined by the Student's t test (P < 0.05). Figure 6. Open in new tabDownload slide Diurnal changes in NAD-ME activity and expression level in wild-type leaves. A, Total NAD-ME activity at the end of the day and night periods. The bars indicate the sd of the measurements from three different crude extracts preparations. The activity measurement was performed three independent times with each crude extract preparation. The asterisk indicates that the NAD-ME activity determined at the end of the night period was statistically significantly higher than the one at the end of the light period as determined by the Student's t test (P < 0.05). B, SDS-PAGE of leaf crude extracts (50 μg of total protein) prepared at the end of the light and night periods and analyzed by western blot using antibodies against AtNAD-ME1 (a-AtME1) or AtNAD-ME2 (a-AtME2). As control of the amount of protein loaded, antibodies against A. viridis PEPc (a-AvPEPc) were also used for detection. The estimated molecular mass of the immunoreactive bands is indicated on the left. C, Expression of AtNAD-ME1 and AtNAD-ME2 transcripts by the end of the night period relative to the expression by the end of the day period analyzed by qRT-PCR. The bars indicate the sd of measurements from three different biological replicates. For both genes, the relative expression values obtained at the end of the night period were statistically significantly higher than the ones at the end of the light period as determined by the Student's t test (P < 0.05). ). In line with this result, western-blot analysis of these extracts showed that both AtNAD-ME1 and AtNAD-ME2 were more abundant during the night period (Fig. 6B). Quantification of the amount of immunoreactive protein of three biological replicates indicated that AtNAD-ME1 and AtNAD-ME2 were enhanced approximately 3- and 2.5-fold in the night period with respect to the day period, respectively. Moreover, the expression of both genes, evaluated by qRT-PCR, was also enhanced by the end of the night (Fig. 6C). Taken together, Arabidopsis leaf extracts presented higher NAD-ME activity during the night period as a result of protein accumulation due to enhanced gene expression. DISCUSSION Arabidopsis Possesses a Heterodimeric NAD-ME, and Both Subunits Exhibit Enzymatic Activities in Vitro and in Vivo AtNAD-ME1 and AtNAD-ME2 show homologies to the α- and β-subunits of other plant NAD-MEs and are localized to mitochondria, as previously revealed by a mitochondrial proteomic study (Haezlewood et al., 2004). A multiple alignment showed that these two proteins possess the conserved motifs present in all members of the NAD(P)-ME family (Winning et al., 1994; Drincovich et al., 2001). In line with this, recombinant individual AtNAD-ME1 and AtNAD-ME2 subunits displayed NAD-ME activities. This is in contrast to a previous study of potato and C. argentea NAD-MEs that showed that the individual subunits do not possess NAD-ME activities (Willeford and Wedding, 1987). This discrepancy can be reconciled when considering that a urea-based procedure was used to separate these subunits, most probably causing denaturation of the proteins. A heteromeric composition of plant NAD-MEs has been reported for some species (Grover and Wedding, 1982; Burnell, 1987; Willeford and Wedding, 1987; Long et al., 1994). In Arabidopsis, several lines of evidence indicate that AtNAD-ME1 and AtNAD-ME2 are subunits of a heteromeric enzyme. A recombinant protein mixture of both AtNAD-MEs revealed an additional band with NAD-ME activity and similar mobility to that exhibited by the active and inmunoreactive bands observed in mitochondrial extracts (Fig. 3, B and C). Moreover, the active band found in the extracts contained two dissimilar and immunoreactive proteins that corresponded to the recombinant monomers (Fig. 4C). In addition, our results clearly show that AtNAD-ME1 and AtNAD-ME2 are functional enzymes in vivo, as the single insertion mutants exhibited residual NAD-ME activities, whereas NAD-ME activities were completely absent in the double knockout. In the active conformational state, the separated AtNAD-ME1 and AtNAD-ME2 assemble as dimers in vitro and in vivo. These observations lead to the suggestion that in vivo, AtNAD-ME1 and AtNAD-ME2 can form not only a heterodimer but also a homodimer. The kinetic analyses performed showed that AtNAD-ME2 displayed a slightly higher specific activity in comparison to AtNAD-ME1 (Table I). Nevertheless, the pH optimum and the affinity for NAD and malate were almost identical for both proteins, and this data is in agreement with previous reports on plant NAD-ME (Artus and Edwards, 1985). Although AtNAD-ME2 displays hyperbolic kinetics with respect to both substrates, AtNAD-ME1 presents sigmoidicity, which indicates differences in the substrate binding and/or cooperation between the subunits in AtNAD-ME1 (Table I). AtNAD-ME isoforms exhibit low affinity to the cofactor and higher specific activity at low pH values (below pH 7.0). Moreover, plant NAD-MEs display the weakest affinity for NAD and the lowest sensitivity to NADH inhibition of all NAD-linked dehydrogenases described in plant mitochondria (Pascal et al., 1990). Finally, in accordance to the universal role in plant mitochondria, the AtNAD-ME1 and AtNAD-ME2 genes have very similar levels of expression in all mature organs. It is worth mentioning that the level of expression of the AtNAD-ME1 transcript was higher than that of AtNAD-ME2 in all the organs analyzed; nevertheless, this does not necessarily imply a higher level of AtNAD-ME1 protein. Enhanced NADP-ME Activity during the Night Period and Distinctly Modified Leaf Metabolic Profiles during the Day and Night Periods of Mutants Lacking NAD-ME Activity Indicate a Major Participation of NAD-ME in Nocturnal Metabolism As NAD-ME was assumed to play a central role in the management of flux through the TCA cycle by providing a means of generating acetyl-CoA, and thus, ATP and carbon skeletons (Grover et al., 1981), we aimed to evaluate the relevance of NAD-ME in plant metabolism. For this purpose, T-DNA insertion mutants for each AtNAD-ME gene were isolated and double mutants were produced and characterized. Neither the single nor double loss-of function mutants showed differences in growth or lack of fitness when grown at moderate or high light intensities. Also, leaf photosynthesis was invariant compared to the wild-type, indicating that NAD-ME activity is not essential for normal autotrophic growth in a C3 plant. Jenner et al. (2001) showed that a reduction in NAD-ME activity in potato by antisense repression had no significant effects on plant morphology, tuber fresh weight, or number of tubers. Moreover, no effects on mitochondrial function associated with any changes in the levels of malate or citrate were found. The authors attributed this negligible impact of reduced NAD-ME activities on metabolism to compensation by activation of the residual NAD-ME activity or compensation via other metabolic processes. The Arabidopsis double knockout mutants showed no residual NAD-ME and thus, the small changes in metabolism found at the end of the light period can only be attributed to compensation through other metabolic processes that can supply pyruvate to the mitochondria. Neither malate nor pyruvate, the substrate and product of the NAD-ME reaction, was altered in the plants completely lacking the NAD-ME activity. As NAD-ME is not the sole source of pyruvate in mitochondria, it is not unexpected that the lack of NAD-ME activity resulted in no considerable effects on diurnal plant metabolism. In accordance with this, two genes encoding mMDH in Arabidopsis (At1g53240 and At3g47520) are induced by light (Price et al., 2004; Thum et al., 2004; Rasmusson and Escobar, 2007). Moreover, our results showed that NAD-ME expression is lower during the day than during the night period. In this way, it is possible that during the light period, the activity of NAD-ME is less important to fuel respiration. On the contrary, at the end of night, the levels of amino acids derived from OAA and 2-oxoglutarate were increased in the mutants completely lacking NAD-ME activity, particularly Asn and Gln. At the same time, these plants showed enhanced levels of the TCA cycle intermediates 2-oxoglutarate and succinate compared to the wild type. Interestingly, the levels of amino acids derived from pyruvate, e.g. Ala, Val, and Ile, were invariable in the mutant. In Arabidopsis, the malate level increases during the day, and this organic acid is accumulated in the vacuole until metabolic demands are sensed (Gout et al., 1993; Fahnenstich et al., 2007). During night, vacuolar malate is utilized in the mitochondria to furnish part of the TCA cycle and to replenish the TCA cycle pool. This function can be fulfilled through the concerted action of MDH and NAD-ME. During the night period, the activity of MDH is lower than during the light period (Price et al., 2004; Thum et al., 2004; Rasmusson and Escobar, 2007) but on the contrary, the activity of the NAD-ME was found to be higher during the night period (Fig. 6). Moreover, the nad-me loss-of-function mutant showed specifically accumulation of amino acids derived from intermediates of the TCA cycle. Taken together, it could be concluded that in plants lacking NAD-ME activity, the excess of mitochondrial malate occurring in the night period is diverted to the synthesis of amino acids from intermediates of the TCA cycle. Thus, the described differential patterns of modifications of the metabolic profile reveal a major participation of NAD-ME during the night period. In this way, we propose a role for the NAD-ME in the coordination of the carbon and nitrogen metabolisms in Arabidopsis. When carbon in the form of malate cannot be converted into pyruvate through the activity of NAD-ME and thus cannot completely flow through the TCA cycle, the flux from TCA intermediates toward the synthesis of amino acids is increased (Fig. 7 Figure 7. Open in new tabDownload slide Scheme representing the flux of metabolites in Arabidopsis lacking NAD-ME activities. The direction of the arrows indicates accumulation or depletion of the respective metabolite. During the night period, mitochondrial pyruvate derives from glycolysis and from vacuolar malate reserves through the action of NAD-ME in leaves. Figure 7. Open in new tabDownload slide Scheme representing the flux of metabolites in Arabidopsis lacking NAD-ME activities. The direction of the arrows indicates accumulation or depletion of the respective metabolite. During the night period, mitochondrial pyruvate derives from glycolysis and from vacuolar malate reserves through the action of NAD-ME in leaves. ). It was a matter of debate whether or not mitochondrial NAD-ME could compensate for limited capacity for pyruvate transport across the mitochondrial membrane by providing the TCA cycle with pyruvate under conditions of high-energy demands (Day and Hanson, 1977; Brailsford et al., 1986; Hill et al., 1994). It would thus be interesting to challenge the nad-me double knockout mutant to different conditions in order to prove this hypothesis. On the other hand, high activities of NAD-ME and NADP-ME were reported in cells around the vascular bundles in tobacco (Hibberd and Quick, 2002), where they were proposed to participate in the decarboxylation of malate derived from the respiratory activity of heterotrophic tissues. In C4 plants, MEs in vascular bundles decarboxylate malate derived from the C4 pathway. We show here that both AtNAD-ME genes are strongly expressed in bundle sheath cells of stems and petioles. Similarly, high GUS activity driven by the promoters of AtNADP-ME1, AtNADP-ME2, and AtNADP-ME4 was described for cells surrounding the vasculature of stems in Arabidopsis (Gerrard Wheeler et al., 2005). These results suggest a possible universal and specific function for these decarboxylases in the bundle sheath cells of C3 plants that still awaits elucidation. MATERIALS AND METHODS Isolation of T-DNA Insertion Lines and Plant Growth Conditions The T-DNA insertion lines Sail-374-A02 (nad-me1.1) and Sail-291-C05 (nad-me2.1) were obtained from the Nottingham Arabidopsis Stock Center (http://www.arabidopsis.info/). The genotype of the lines was determined using genomic DNA of individual plants as template for PCR amplifications of the wild-type and nad-me alleles. The primers used to amplify the wild-type alleles were as follows: NAD-ME1wtF (5′-ACGATGACGGAGAGAATCGT-3′) and NAD-ME1wtR (5′-ATGTTCAATGATGATGTCCAG-3′), and NAD-ME2wtF (5′-GACCTGTGTACAGCAATGTGATCG-3′) and NAD-ME2wtR (5′-GGTCTTGTCACCACGGAGAGGACA-3′). To amplify the nad-me alleles, the primers NAD-ME1wtF and NAD-ME2wtF were combined separately in a PCR with the primer SailLB (5′-TAGCATCTGAATTTCATAACCAATCTCGATACAC-3′). The location of the inserts was verified by amplifying and sequencing the T-DNA flanking genomic DNA. Seeds of Arabidopsis (Arabidopsis thaliana) ecotype Columbia-0 and the transformant lines were placed on soil and kept in darkness for 4 d at 4°C to synchronize germination. After 2 weeks, the seedlings were transferred to pots (one per pot) containing three parts of soil (Gebr. Patzer KG) and one part of vermiculite (Basalt Feuerfest). Plants were grown under a 16-/8-h photoperiod at 100 or, alternatively, at 500 μmol m−2 s−1 and 21°C/18°C (day/night) temperatures and 65% relative humidity in a controlled growth cabinet. Alternatively, Arabidopsis seeds were sterilized and sown in Murashige and Skoog agar plates containing 1% Suc. Cloning of Full-Length AtNAD-ME1 and AtNAD-ME2 Arabidopsis full-length cDNAs encoding NAD-ME1 and NAD-ME2 were amplified by RT-PCR using RNA extracted from leaves and the TRizol reagent (Gibco-BRL). Amplification was conducted using SuperScript II reverse transcriptase (Invitrogen) and specific primers. In the case of AtNAD-ME1, the oligonucleotide pair NAD-ME1GWF (5′-CACCATGGGAATAGCCAATAAGCTCCGGCT-3) and NAD-ME1GWF (5′-GAGTACCCGACTTTGGTCTACAAGGATGAC-3′) was used. AtNAD-ME2 was amplified with the primer pair NAD-ME2GWF (5′-CACCATGTGGAAGAACATTGCTGGGTTGTC-3′) and NAD-ME2GWR (5′-CCTGTTTACAGCCCTCTCGTTCACGAGAAA-3′). The PCR products were cloned into pENTR/D-TOPO (Invitrogen) and completely sequenced. Heterologous Expression of the Mature AtNAD-MEs and Purification of the Recombinant Proteins To amplify the cDNA fragments corresponding to the mature AtNAD-MEs, a PCR reaction was conducted using as template the full-length cDNAs cloned as described above and the following primer pairs: NAD-ME1F (5′-GGATCCCCCACCATCGTTCATAAA-3′) and NAD-ME1R (5′-GTCTACAAGGATGACTAAGTCGAC-3′), and NAD-ME2F (5′-GGATCCTGCATCGTCCACAAGCGT-3′) and NAD-ME2R (5′-ACGCTTGTGGACGATGCAGGATCC-3′). The primers were designed to introduce unique BamHI and SalI sites at the 5′ and 3′ ends, respectively, to facilitate the subcloning into the pET32 expression vector. In each pET32 vector containing the inserts of AtNAD-ME1 and AtNAD-ME2 (pET-NAD-ME1 and pET-NAD-ME2), the NAD-MEs are fused in-frame to a His tag to facilitate purification of the expressed fusion protein by a nickel-containing His-Bind column (Novagen). The induction and purification of the fusion proteins were performed as previously described for the Arabidopsis NADP-ME isoforms (Gerrard Wheeler et al., 2005). The fusion proteins were then concentrated on Centricon YM-30 (Amicon) using buffer MMG (50 mm MES-NaOH, pH 6.5, 5 mm MnCl2, and 10% [v/v] glycerol). Purified fusion NAD-ME proteins were then incubated with 0.05 to 0.075 units of enterokinase (EK-Max; Invitrogen) per milligram of protein at 16°C for 2 h to remove the N terminus coded for by the expression vector. The proteins were further purified using a Sephadex G-50 column equilibrated with buffer A (50 mm MES-NaOH, pH 6,5, 5 mm MnCl2, 5 mm dithiothreitol, and 20% [v/v] glycerol). Purified AtNAD-ME1 and AtNAD-ME2 were stored at −80°C in buffer A (with 50% glycerol) for further studies. Gel Filtration Chromatography Molecular masses of recombinant native AtNAD-ME1 and AtNAD-ME2 were evaluated by gel filtration chromatography on a FPLC system using a Superdex 200 10/300 GL column (Amersham Biosciences). The column was equilibrated with 25 mm Tris-HCl, pH 7.5, or with 50 mm MES-NaOH, pH 6.5, and calibrated using molecular mass standards. The sample and the standards were applied separately in a final volume of 50 μL at a constant flow rate of 0.5 mL/min. Preparation of Antibodies against AtNAD-ME1 and AtNAD-ME2 Polyclonal antibodies against recombinant AtNAD-ME1 and AtNAD-ME2 were obtained by immunization of rabbits with 200 μg of the purified proteins in four subcutaneous injections of 50 μg at 15-d intervals. The antibodies against the recombinant AtNAD-MEs were further purified from the crude antiserum (Plaxton, 1989), concentrated, and used (1:200 dilution) for western-blot analysis. Protein Crude Extract Preparations Different Arabidopsis organs (leaf, stem, flowers, and roots) of 6-week-old wild-type and T-DNA insertion lines were ground in N2, and the resulting powder was suspended in buffer B (50 mm MES-NaOH pH 6.5, 5 mm MnCl2, 1 mm EDTA, 10 mm 2-mercaptoethanol, 0.05% Triton X-100, 20% glycerol, and 1 mm phenylmethylsulfonyl fluoride). The homogenates were clarified by centrifugation. The supernatants were desalted using a Sephadex G-50 column equilibrated with buffer A and separated for activity measurements or subjected to electrophoresis. Isolation of Mitochondria from Different Tissues Mitochondria from leaves, stems, roots, and flowers were prepared by a modification of the method previously described by Keech et al. (2005). The tissue (approximately 2–5 g) was homogenized in a mortar with grinding buffer and the homogenate was filtered through two layers of muslin and centrifuged at 2,500g for 5 min. The supernatant was subjected to a second round of centrifugation at 12,000g for 15 min. The pellet containing the mitochondria was washed and resuspended with buffer C (50 mm HEPES, pH 6.5, 5 mm MnCl2, 1 mm EDTA, 10 mm 2-mercaptoethanol, 0.05% Triton X-100, 20% glycerol, and 1 mm phenylmethylsulfonyl fluoride). After three freeze cycles, the sample was centrifuged at 12,000g for 10 min and used for further analysis. Enzyme Activity Measurements NAD-ME activity in crude extracts (whole plant tissues or isolated mitochondria) was measured spectrophotometrically using a standard reaction mixture containing 50 mm MES-NaOH, pH 6.5, 4 mm NAD, 10 mm malate, 5 mm dithiothreitol; 10 mm MnCl2, and 10 units of MDH. There was a rapid but small increase of the A 340 as the reaction catalyzed by the MDH reached the equilibrium. With the assay system specified above, the subsequent steady increase of A 340 was attributable to the decarboxylation of l-malate by the NAD-ME (Chapman and Hatch, 1977). In the case of purified recombinant AtNAD-ME, enzymatic activity was determined spectrophotometrically using a standard reaction mixture containing 50 mm HEPES, pH 6.4 or 6.6 (for AtNAD-ME1 and AtNAD-ME2, respectively), 10 mm MnCl2, 4 mm NAD, and 10 mm l-malate in a final volume of 0.5 mL. The reaction was started by the addition of l-malate. Initial velocity studies were performed by varying the concentration of one of the substrates around its K m value while keeping the other substrates concentrations at saturating levels. All kinetic parameters were calculated at least by triplicate determinations and adjusted to nonlineal regression using free concentrations of all substrates. OAA decarboxylation was monitored by measuring the OAA disappearance at 260 nm (ε 260 nm = 850 m −1 cm−1) in an assay medium containing 50 mm MES-NaOH, pH 5.5, 1 mm OAA, and 10 mm MnCl2. One unit is defined as the amount of enzyme that catalyzes the formation of 1 μmol of NADH min−1 under the specified conditions. Protein concentration was determined by the method of Sedmak and Grossberg (1977) using bovine serum albumin as standard. PAGE and Western-Blot Analysis Denaturing PAGE (SDS-PAGE) was performed in 10% (w/v) or 7.5–15% (w/v) linear gradient polyacrylamide gels according to Laemmli (1970). Proteins were visualized with Coomassie Blue or electroblotted onto a nitrocellulose membrane for immunoblotting. Antibodies against Amaranthus hypochondriacus α-NAD-ME (provided by Dr. J.O. Berry, SUNY Buffalo, Buffalo, NY), against phosphoenolcarboxylase (PEPc) from Amaranthus viridis (Colombo et al., 1998), or against AtNAD-ME1 or AtNAD-ME2 were used for detection. Bound antibodies were visualized by linking to alkaline phosphatase-conjugated goat anti-rabbit IgG according to the manufacturer's instructions (Sigma). Alkaline phosphatase activity was detected colorimetrically or by using a chemiluminescent kit (Immun-Star; Bio-Rad). Native PAGE was performed using a 6% (w/v) acrylamide separating gel. Electrophoresis was run at 150 V at 10°C. Gels were assayed for NAD-ME activity by incubating the gel in a solution containing 50 mm HEPES, pH 6.5, 60 mm malate, 4 mm NAD, 10 mm MnCl2, 35 μg/mL nitroblue tetrazolium, and 10 μg/mL phenazine methosulfate at 30°C. Alternatively, native gels were electroblotted onto a nitrocellulose membrane and subjected to western-blot analysis. Semiquantitative RT-PCR To evaluate the expression of the AtNAD-ME genes in the T-DNA insertional mutants, total RNA from leaves were isolated from 100 mg tissue using the TRIzol reagent (Gibco-BRL). RNA was converted into first-strand cDNA using the SuperScriptII Reverse Transcriptase (Invitrogen). PCR reactions were conducted in a final volume of 10 μL using 1 μL of the transcribed product and Taq DNA polymerase (Qiagen). The pairs of primers used were NAD-ME1wtF and NAD-ME1wtR and NAD-ME2wtF and NAD-ME2wtR. Amplification conditions were as follows: 3 min denaturation at 94°C; 35 cycles at 94°C for 30 s, 53 to 55°C for 40 s and 72°C for 30 s, followed by 5 min at 72°C. As control, the actin2 gene was amplified by 28 cycles and the following primers were used: actin2-F (5′-TAACTCTCCCGCTATGTATGTCGC-3′) and actin2-R (5′-GTACGGTAACATTGTGCTCAGTGG-3′). qRT-PCR Relative gene expression was determined by performing qRT-PCR in an iCycler iQ detection system and the Optical System Software version 3.0a (Bio-Rad), using the intercalation dye SYBRGreen I (Invitrogen) as a fluorescent reporter, with 2.5 mm MgCl2, 0.5 μ m of each primer, and 0.04 units/μL GoTaq (Promega). A 2-fold dilution of cDNA was used as template. PCR controls were performed in the absence of added reverse transcriptase to ensure that RNA samples were free of DNA contamination. Cycling parameters were as follows: initial denaturation at 94°C for 2 min; 40 cycles of 96°C for 10 s, and 56°C for 15 s; 72°C for 1 min; and 72°C for 10 min. Melting curves for each PCR reaction were determined by measuring the decrease of fluorescence with increasing temperature (from 65°C to 98°C). The specificity of the PCR reactions was confirmed by melting curve analysis using the software as well as by agarose gel electrophoresis of the products. Relative gene expression was calculated using the comparative 2−ΔΔ C T method (Livak and Schmittgen, 2001) and polyubiquitin 10 (At4g05320) as reference gene. Each RNA sample was run in triplicate and repeated in at least two independent biological samples. The oligonucleotide primers pairs used for AtNAD-ME1 and AtNAD-ME2 were NAD1left (5′-GCACGAATGTTGGGAAATAC-3′) and NAD1right (5′-AAACCAAGAAGCACATCAGG-3′), and NAD2left (5′-GGCATCCTTTACCCTTCAAT-3′) and NAD2right (5′-ACCACATGTTGCGTGTAATG-3′). In the case of ubiquitin, the primers used were UBQleft (5′-AAGCAGCTTGAGGATGGAC-3′) and UBQright (5′-AGATAACAGGAACGGAAACATAGT-3′). Construction of NAD-ME∷GUS Gene Fusions, Plant Transformation, and Histochemical Analysis of GUS Activity For the generation of promoter-GUS constructs, fragments containing a 1.7-kb promoter region upstream the ATG start codon, the first exon and intron and part of the second exon of both AtNAD-ME genes were amplified by PCR from genomic DNA. The following primer pairs were used: pNAD-ME1GWF (5′-CACCTCGAGAGTTCTTAGCTAAACAATCT-3′) and pNAD-ME1GWR (5′-GGGACTGCGTTTACGATGACGGAGAGA-3′), and pNAD-ME2GWF (5′-CACCATGGGTTGGAGCAGATGGATT-3′) and pNAD-ME2GWR (5′-ATACGAGGCTTGCTTCCTCCTCGT-3′). The amplified products were sequenced and cloned into pGWB3, a gateway-compatible binary vector that carries the GUS gene and the kanamycin resistance gene (provided by T. Nakagawa, Shimane University, Izumo, Japan). The resulting constructs were introduced into Arabidopsis by A. tumefaciens transformation using the vacuum infiltration method. Transgenic lines were selected on Murashige and Skoog plates containing kanamycin (50 μg/mL). The histochemical localization of GUS activity was conducted as described by Maurino et al. (2006). Rosette leaves to be sectioned were stained as described above and fixed in 4% glutaraldehyde overnight at 4°C. Fixed tissues were dehydrated through an ethanol series and embedded in Paraplast (Roth). Embedded material was cut into 10-μm sections using a microtome, dewaxed with Rotihistol (Merk), mounted on glass slides with Entellan New (Merk), and observed under a microscope (Nikon Eclipse E800) equipped with a digital camera (ky-F1030; JVC). Chlorophyll Fluorescence Parameters Chlorophyll fluorescence measurements were performed with a PAM-2000 pulse amplitude modulated chlorophyll fluorometer (Walz). At the start of each measurement, a plant was dark adapted for 10 min. Basal fluorescence was measured with modulated weak red light and maximal fluorescence was induced with a saturating white light pulse (5,000 μmol m−2 s−1; duration 0.8 s). Metabolic Analysis by GC-MS Whole rosettes were harvested at the end of the light and dark periods and transferred into liquid nitrogen in less than 10 s. At least 8 rosettes were combined per sample. The leaves were homogenized using liquid nitrogen and stored at −80°C until use. The extraction and GC-MS analysis was conducted as described by Fahnenstich et al. (2007). Statistical Analysis Significance was determined according to the Student's t test using Excel software (Microsoft). Supplemental Data The following materials are available in the online version of this article. Supplemental Figure S1. Cross section of rosette leaves of AtNAD-ME∷GUS plants. Scale bar = 50 μm. Supplemental Table S1. Complete data set of metabolites of rosettes at the end of the light and dark period. ACKNOWLEDGMENTS We thank Andreas Weber for helpful discussions and Ulrike Hebbeker and Claudia Nothelle for technical assistance. LITERATURE CITED Agius SC, Rasmusson AG, Moller IM ( 2001 ) NAD(P) turnover in plant mitochondria. Aust J Plant Physiol 28 : 461 – 470 Allen BL, Harris BG ( 1981 ) Purification of malic enzyme from Ascaris suum using NAD+-agarose. Mol Biochem Parasitol 2 : 367 – 372 Crossref Search ADS PubMed Artus NN, Edwards GE ( 1985 ) Properties of leaf NAD-malic enzyme from the inducible crassulacean acid metabolism species Mesembryanthemum crystallinum. Plant Cell Physiol 26 : 341 – 350 Brailsford MA, Thompson AG, Kaderbhai N, Beechey RB ( 1986 ) Pyruvate metabolism in castor-bean mitochondria. Biochem J 239 : 355 – 361 Crossref Search ADS PubMed Burnell JN ( 1987 ) Photosynthesis in phosphoenolpyruvate carboxykinase-type C4 species: properties of NAD-malic enzyme from Urochloa panicoides. Aust J Plant Physiol 14 : 517 – 525 Casati P, Andreo CS, Edwards GE ( 1999 ) Characterization of NADP-malic enzyme from two species of Chenopodiaceae: Haloxylon persicum (C4) and Chenopodium album (C3). Phytochemistry 52 : 985 – 992 Crossref Search ADS Chapman KSR, Hatch MD ( 1977 ) Regulation of mitochondrial NAD-malic enzyme involved in C4 pathways photosynthesis. Arch Biochem Biophys 184 : 298 – 306 Crossref Search ADS PubMed Caldes T, Fatania HR, Dalziel K ( 1978 ) Purification of malic enzyme from bovine heart mitochondria by affinity chromatography. Anal Biochem 100 : 299 – 303 Colombo SL, Andreo CS, Chollet R ( 1998 ) The interaction of shikimic acid and protein phosphorylation with PEP carboxylase from the C4 dicot Amaranthus viridis. Phytochemistry 48 : 55 – 59 Crossref Search ADS PubMed Davisson VJ, Schulz AR ( 1985 ) The purification and steady-state kinetic behaviour of rabbit heart mitochondrial NAD(P)+ malic enzyme. Biochem J 225 : 335 – 342 Crossref Search ADS PubMed Day AD, Hanson JB ( 1977 ) Pyruvate and malate transport and oxidation in corn mitochondrial. Plant Physiol 59 : 630 – 635 Crossref Search ADS PubMed Drincovich M, Casati P, Andreo CS ( 2001 ) NADP-malic enzyme from plants: a ubiquitous enzyme involved in different metabolic pathways. FEBS Lett 490 : 1 – 6 Crossref Search ADS PubMed Eastmond PJ, Dennis DT, Rawsthorne S ( 1997 ) Evidence that a malate/inorganic phosphate exchange translocators imports carbon across the leucoplast envelope for fatty acid synthesis in developing castor seed endosperm. Plant Physiol 114 : 851 – 856 Crossref Search ADS PubMed Fahnenstich H, Saigo M, Niessen M, Zanor MI, Andreo CS, Fernie A, Drincovich MF, Flügge UI, Maurino VG ( 2007 ) Alteration of organic acid metabolism in Arabidopsis overexpressing the maize C4-NADP-malic enzyme causes accelerated senescence during extended darkness. Plant Physiol 145 : 640 – 652 Crossref Search ADS PubMed Felsenstein J ( 1989 ) PHYLIP: phylogeny inference package (version 3.2). Cladistics 5 : 164 – 166 Gerrard Wheeler MC, Tronconi MA, Drincovich MF, Andreo CS, Flügge UI, Maurino VG ( 2005 ) A comprehensive analysis of the NADP-malic enzyme gene family of Arabidopsis. Plant Physiol 139 : 39 – 51 Crossref Search ADS PubMed Gout E, Bligny R, Pascal N, Douce R ( 1993 ) 13C Nuclear magnetic resonance studies of malate and citrate synthesis and compartmentation in higher plant cells. J Biol Chem 268 : 3986 – 3992 Crossref Search ADS PubMed Grover SD, Canellas PF, Wedding RT ( 1981 ) Purification of NAD malic enzyme from potato and investigation of some physiological and kinetic properties. Arch Biochem Biophys 209 : 396 – 407 Crossref Search ADS PubMed Grover SD, Wedding RT ( 1982 ) Kinetic ramifications of the association-dissociation behaviour of NAD malic enzyme. Plant Physiol 70 : 1169 – 1172 Crossref Search ADS PubMed Haezlewood JL, Tonti-Filippini JS, Gout AM, Day DA, Whelan J, Millar AH ( 2004 ) Experimental analysis of the Arabidopsis mitochondrial proteome highlights signalling and regulatory components, provides assessment of targeting prediction programs, and indicates plant-specific mitochondrial proteins. Plant Cell 16 : 241 – 256 Crossref Search ADS PubMed Hatch MD, Carnal NW ( 1992 ) The role of mitochondria in C4 photosynthesis. In H Lambers, LHW van der Plas, eds, Molecular, Biochemical and Physiological Aspects of Plant Respiration. Academic Publishing, The Hague, The Netherlands, pp 135–148 Hatch MD, Kagawa T ( 1974 ) Activity, location and role of NAD malic enzyme in the leaves of C4 photosynthesis. Aust J Plant Physiol 1 : 357 – 369 Hibberd JM, Quick WP ( 2002 ) Characteristics of C4 photosynthesis in ítems and petiols of C3 flowering plants. Nature 415 : 451 – 454 Crossref Search ADS PubMed Hill SA, Bryce JH, Leaver CJ ( 1994 ) Pyruvate metabolism in mitochondria from cucumber cotyledons during early seedling development. J Exp Bot 45 : 1489 – 1491 Crossref Search ADS Jenner HL, Winning BM, Millar H, Tomlinson KL, Leaver CJ, Hill SA ( 2001 ) NAD malic enzyme and the control of carbohydrate metabolism in potato tubers. Plant Physiol 126 : 1139 – 1149 Crossref Search ADS PubMed Keech O, Dizengremel P, Gardeström P ( 2005 ) Preparation of leaf mitochondria from Arabidopsis. Physiol Plant 124 : 403 – 409 Crossref Search ADS Laemmli UK ( 1970 ) Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 227 : 680 – 685 Crossref Search ADS PubMed Livak KJ, Schmittgen TD ( 2001 ) Analysis of relative gene expression data using realtime quantitative PCR and the 2ΔΔCt method. Methods 25 : 402 – 408 Crossref Search ADS PubMed Long LL, Wang JL, Berry JO ( 1994 ) Cloning and analysis of the C4 NAD-dependent malic enzyme of amaranth mitochondria. J Biol Chem 269 : 2827 – 2833 Crossref Search ADS PubMed Martinoia E, Rentsch D ( 1994 ) Malate compartmentation: responses to a complex metabolism. Annu Rev Plant Physiol Plant Mol Biol 45 : 447 – 467 Crossref Search ADS Maurino VG, Grube E, Zielinski J, Schild A, Fischer K, Flügge UI ( 2006 ) Identification and expression analysis of twelve members of the Nucleobase-Ascorbate Transporter (NAT) gene family in Arabidopsis. Plant Cell Physiol 48 : 1381 – 1393 Maurino VG, Saigo M, Andreo CS, Drincovich MF ( 2001 ) Non-photosynthetic malic enzyme from maize: a constitutively expressed enzyme that responds to plant defense inducers. Plant Mol Biol 45 : 409 – 420 Crossref Search ADS PubMed Moreadith RW, Lehninger AL ( 1984 ) Purification, kinetic behavior, and regulation of NAD(P)+ malic enzyme of tumor mitochondria. J Biol Chem 259 : 6222 – 6227 Crossref Search ADS PubMed Murata T, Oshugi R, Matsuoka M, Nakamoto M ( 1989 ) Purification and characterization of NAD ME from leaves of Eleusine coracana and Panicum dichotomiflorum. Plant Physiol 89 : 316 – 324 Crossref Search ADS PubMed Nagel WO, Sauer LA ( 1982 ) Mitochondrial malic enzymes. Purification and properties of the NAD(P)- dependent malic enzyme from canine small intestinal mucosa. J Biol Chem 257 : 12405 – 12411 Crossref Search ADS PubMed Oshugi R, Murata T ( 1980 ) Leaf anatomy, post-illumination CO2 burst and NAD-malic enzyme activity in Panicum dichotomiflorum. Plant Cell Physiol 21 : 1329 – 1333 Crossref Search ADS Palmer JM, Schwitzguel JP, Moller IM ( 1982 ) Regulation of malate oxidation in plant mitochondria. Responses to rotenone and exogenous NAD+. Biochem J 208 : 703 – 711 Crossref Search ADS PubMed Pascal N, Dumas R, Douce R ( 1990 ) Comparison of the kinetic behavior toward pyridine nucleotides of NAD+-linked dehydrogenases from plant mitochondria. Plant Physiol 94 : 189 – 193 Crossref Search ADS PubMed Plaxton WC ( 1989 ) Molecular and immunological characterization of plastid and cytosolic pyruvate kinase isozymes from castor-oil-plant endosperm and leaf. Eur J Biochem 181 : 443 – 451 Crossref Search ADS PubMed Price J, Laxmi A, St Martin SK, Jang JC ( 2004 ) Global transcription profiling reveals multiple sugar signal transduction mechanisms in Arabidopsis. Plant Cell 16 : 2128 – 2150 Crossref Search ADS PubMed Rasmusson AG, Escobar MA ( 2007 ) Light and diurnal regulation of plant respiratory gene expression. Physiol Plant 129 : 57 – 67 Crossref Search ADS Sedmak J, Grossberg S ( 1977 ) A rapid, sensitive, and versatile assay for protein using Coomassie Brilliant Blue G-250. Anal Biochem 79 : 544 – 552 Crossref Search ADS PubMed Smith RG, Gauthier DA, Dennis DT, Turpin DH ( 1992 ) Malate- and pyruvate-dependent fatty acid synthesis in leucoplasts from developing castor endosperm. Plant Physiol 89 : 1233 – 1238 Thompson JD, Higgins DG, Gibson TJ ( 1994 ) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22 : 4673 – 4680 Crossref Search ADS PubMed Thum KE, Shin MJ, Palenchar PM, Kouranov A, Coruzzi GM ( 2004 ) Genome-wide investigation of light and carbon signalling interations in Arabidopsis. Genome Biol 5 : R10 Crossref Search ADS PubMed Wedding RT, Black MK ( 1983 ) Physical and kinetic properties and regulation of the NAD malic enzyme purified from leaves of Crasula argentea. Plant Physiol 72 : 1021 – 1028 Crossref Search ADS PubMed Willeford KO, Wedding RT ( 1987 ) Evidence for a multiple subunit composition of plant NAD malic enzyme. J Biol Chem 262 : 8423 – 8429 Crossref Search ADS PubMed Winning BM, Bourguignon J, Leaver CJ ( 1994 ) Plant mitochondrial NAD+-dependent malic enzyme. cDNA cloning, deduced primary structure of the 59- and 62-kDa subunit, import, gene complexity and expression analysis. J Biol Chem 269 : 4780 – 4786 Crossref Search ADS PubMed Zimmermann P, Hirsch-Hoffmann M, Hennig L, Gruissem W ( 2004 ) GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox. Plant Physiol 136 : 2621 – 2632 Crossref Search ADS PubMed Author notes 1 This work was supported by the Deutsche Forschungsgemeinschaft (to V.G.M.), and by CONICET and Agencia Nacional de Promoción de Actividades Científicas y Tecnológicas (to M.F.D. and C.S.A.). * Corresponding author; e-mail [email protected]. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Verónica G. Maurino ([email protected]). [W] The online version of this article contains Web-only data. www.plantphysiol.org/cgi/doi/10.1104/pp.107.114975 © 2008 American Society of Plant Biologists This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Cossegal, Magalie; Chambrier, Pierre; Mbelo, Sylvie; Balzergue, Sandrine; Martin-Magniette, Marie-Laure; Moing, Annick; Deborde, Catherine; Guyon, Virginie; Perez, Pascual; Rogowsky, Peter

doi: 10.1104/pp.107.112698pmid: 18287491