TY - JOUR
AU - Couée, Ivan
AB - Abstract Anthropogenic changes and chemical pollution confront plant communities with various xenobiotic compounds or combinations of xenobiotics, involving chemical structures that are at least partially novel for plant species. Plant responses to chemical challenges and stimuli are usually characterized by the approaches of toxicology, ecotoxicology, and stress physiology. Development of transcriptomics and proteomics analysis has demonstrated the importance of modifications to gene expression in plant responses to xenobiotics. It has emerged that xenobiotic effects could involve not only biochemical and physiological disruption, but also the disruption of signalling pathways. Moreover, mutations affecting sensing and signalling pathways result in modifications of responses to xenobiotics, thus confirming interference or crosstalk between xenobiotic effects and signalling pathways. Some of these changes at gene expression, regulation and signalling levels suggest various mechanisms of xenobiotic sensing in higher plants, in accordance with xenobiotic-sensing mechanisms that have been characterized in other phyla (yeast, invertebrates, vertebrates). In higher plants, such sensing systems are difficult to identify, even though different lines of evidence, involving mutant studies, transcription factor analysis, or comparative studies, point to their existence. It remains difficult to distinguish between the hypothesis of direct xenobiotic sensing and indirect sensing of xenobiotic-related modifications. However, future characterization of xenobiotic sensing and signalling in higher plants is likely to be a key element for determining the tolerance and remediation capacities of plant species. This characterization will also be of interest for understanding evolutionary dynamics of stress adaptation and mechanisms of adaptation to novel stressors. chemogenomics, contaminants, gene expression, pollutants, receptors, signalling pathways, stress responses, toxicants, toxicogenomics, xenobiotics Introduction Anthropogenic changes and chemical pollution constantly confront plant communities with a wide array of xenobiotic compounds or combinations of xenobiotics, involving chemical structures that are at least partially novel for plant species. Plant responses to these chemical challenges and stimuli are being characterized in the context of toxicology, ecotoxicology, and stress physiology. The development of genome-wide analysis through transcriptomics and proteomics has demonstrated that gene expression modifications play an important role in plant responses to xenobiotics and that these gene expression modifications follow distinctive patterns of coordination and co-regulation (Raghavan et al., 2005; Ramel et al., 2007, 2009a; Weisman et al., 2010), in line with studies on bacteria, yeast, and animals (Heijne et al., 2003; Jennings et al., 2009; Teixeira et al., 2006). It has thus emerged that xenobiotic effects could involve not only biochemical and physiological disruption (Fufezan et al., 2002; Liu et al., 2009; Ramel et al., 2009a), but also signalling disruption (Ramel et al., 2007, 2009a; Unver et al., 2010). Moreover, in a number of cases, mutations affecting sensing and signalling pathways result in modifications of the responses to xenobiotics (Baruah et al., 2009; Sulmon et al., 2007; Weisman et al., 2010). This suggests at least interference or crosstalk between xenobiotic effects and signalling pathways, especially stress and hormone signalling pathways. The structure and design of some specific xenobiotics, such as phytohormone analogues (Teixeira et al., 2007; Gleason et al., 2011), necessarily involve intrinsic interactions with plant hormone receptors and plant hormone signalling pathways. Besides these specific cases, a wide range of xenobiotics with various structures and designs induce changes at the levels of gene expression, regulation, and signal transduction that strongly point to the possibility of xenobiotic sensing in higher plants (Ramel et al., 2007; Riechers et al., 2010). Several plant stress-signalling pathways have already been dissected (Wagner et al., 2004; Baruah et al., 2009). However, in most cases, the interactions between different signalling pathways and the identity of signalling intermediates and regulators, especially stress sensors, remain largely unknown (Baena-González and Sheen, 2008). Xenobiotics can induce molecular injury and damage (Fufezan et al., 2002; Teixeira et al., 2007; Liu et al., 2009; Ramel et al., 2009a; Xie et al., 2010b; Nobels et al., 2011), mainly related to oxidative stress, membrane disruption, lipid peroxidation, protein damage, or DNA damage. In other words, xenobiotic action is likely to generate numerous secondary entities with signalling potential, such as singlet oxygen (Wagner et al., 2004) or hydrogen peroxide (Wang et al., 2010), and numerous forms of denatured or modified proteins and nucleic acids (Teixeira et al., 2007; Xie et al., 2010b). Sensing of these secondary products and of nucleic acid, membrane, and protein homeostasis may be considered to be sufficient for developing efficient responses to xenobiotics. However, it may be advantageous for cells and organisms to develop rapid primary sensing of xenobiotic chemical structures and rapid stress responses (López-Maury, et al., 2008) when the effects of the xenobiotic are rapidly amplified in the cell, for instance through free radical reactions, and cause irreversible injury. Under such circumstances of selection pressure, primary sensors of xenobiotics may have evolved and may be useful in developing strategies of molecular avoidance. Thus, in the case of heat stress, the sensing of heat-denatured proteins is paralleled with direct sensing involving thermosensors (de Nadal et al., 2011). Xenobiotic sensing has been identified or characterized in yeast (Teixeira et al., 2007; Dias et al., 2010), invertebrates (Kretschmann et al., 2011; Misra et al., 2011), and vertebrates (Ulrich, 2003; Baker, 2005; McMillan and Bradfield, 2007). Thus, in vertebrates, an array of receptors and xenosensors, such as aryl hydrocarbon receptors (AhRs), peripheral benzodiazepine receptors, or Toll-like receptors (TLRs), are involved in different aspects of xenobiotic responses (McMillan and Bradfield, 2007; Ulrich, 2003; Anderson et al., 2011; Ghose et al., 2011). In some cases, such as that of the AhR, evolutionary studies have shown the existence of highly conserved orthologues in different animal lineages (Baker, 2005; McMillan and Bradfield, 2007). In higher plants, xenobiotic-sensing systems seem to be difficult to identify and characterize. This review will assess whether evidence drawn from transcriptomics, transcription factor expression analysis, gene comparative studies, and mutant studies point to the existence of plant xenosensing systems. This assessment will take into account the difficulty to distinguish between the hypothesis of direct xenobiotic sensing and the possibility of indirect sensing of xenobiotic-related modifications and damages. The potential importance of the characterization of xenobiotic sensing and signalling in higher plants will be discussed as a key element for determining the tolerance and remediation capacities of plant species (Rao et al., 2009; Peng et al., 2011) or for using plants as biomonitors of pollutant exposure (Peng et al., 2011; Weisman et al., 2011). The ecological and evolutionary interest of this characterization will also be considered in the context of acclimation to changing environments, of stress adaptation, and of adaptation to novel challenges. Transcriptomics evidence for signalling processes in xenobiotic responses: interactions with stress signalling Serial analysis of gene expression and DNA array analysis have established the transcriptome profile of xenobiotic effects in higher plants (Ekman et al., 2003, 2005; Ramel et al., 2007; Unver et al., 2010; Weisman et al., 2010; Jin et al., 2011; Peng et al., 2011; Skipsey et al., 2011). Despite the relatively small number of such studies, the variety of xenobiotic treatments [trinitrotoluene, royal demolition explosive (also known as RDX), atrazine, glyphosate, phenanthrene, polychlorinated biphenyls, naphtalene, fenclorim] gives consistent insight into the coordinated gene expression responses that result from xenobiotic exposure. Changes to the expression of candidate genes in response to xenobiotics were documented in earlier studies (Wagner et al., 2002) with further characterization involving expression kinetics and tissue-specific patterns (Mezzari et al., 2005). Utilization of genome-wide approaches demonstrated that expression-level effects of xenobiotics in plants were large-scale and coordinated, thus resulting in xenobiotic-response gene networks involving induction and repression of hundreds of genes, as is the case for other abiotic stress responses (Desikan et al., 2001; Mittler et al., 2004) and for xenobiotic responses in yeast (Teixeira et al., 2006, 2007), invertebrates (Chapman et al., 2011; Misra et al., 2011), and vertebrates (Tolson and Wang, 2010). Xenobiotic-response transcriptomics in plants therefore belongs to the wider field of toxicogenomics and chemogenomics that has been developed in yeast and animal cells (Heijne et al., 2003; Dias et al., 2010; Davis et al., 2011). On the one hand, comparative transcriptomics of plant responses to various xenobiotics shows the induction of similar classes of genes involved in metabolization and detoxification, conjugation, transport, antioxidant defence, and cell protection and repair (Ekman et al., 2003; Ramel et al., 2007; Skipsey et al., 2011), such as genes encoding cytochrome P450s, glutathione S-transferases (GSTs), or peroxidases. Thus, the GST AtGSTU24 (At1g17170) gene is induced by herbicides, explosives, and polycyclic aryl hydrocarbons (PAHs; Mezzari et al., 2005; Weisman et al., 2010). Moreover, xenobiotic treatments in plants have strong differential effects on multigene families, such as GSTs, thioredoxins, ascorbate peroxidases, and superoxide dismutases (Ekman et al., 2003; Ramel et al., 2007; Skipsey et al., 2011). These classes of xenobiotic-regulated genes have been described in animals (Tolson and Wang, 2010) and their potential functions can be associated with expected defence mechanisms such as xenobiotic-metabolizing enzymes, xenobiotic-conjugating enzymes, and biochemical systems for cell protection against xenobiotic-mediated injury or repair of xenobiotic-mediated injuries. They can also provide candidate genes of high interest for studying underlying regulatory mechanisms. On the other hand, there are striking differences in gene expression between the different types of xenobiotic treatment. Detailed analysis of gene expression changes in Arabidopsis roots revealed that exposures to TNT or to royal demolition explosive resulted in drastically different patterns of responses (Ekman et al., 2005). These different patterns involve all of the gene classes discussed above. Comparison on a wider scale involving herbicides, heavy metals, and PAHs showed that it was possible to identify PAH-specific response genes (Weisman et al., 2010). However, one xenobiotic molecule can also elicit divergent responses. Ramel et al. (2007) compared physiological situations that depend on carbon status and where treatment with the herbicide atrazine results either in lethal injuries or in tolerance. Both situations are associated with large-scale transcriptomic modifications. However, the same atrazine treatment gives divergent expression patterns in the situation leading to injury and in that leading to tolerance. Genes that are repressed as a result of injury, such as ascorbate peroxidase 1 (At1g07890) and cytochrome P450 CYP710A2 (At2g34490), are not differentially expressed in the situation of tolerance. Genes that are induced in the situation of tolerance, such as glutamyl-tRNA reductase (At1g09940) and sigma-factor-binding protein (SIB1; At3g56710), are not differentially expressed in the situation of injury. Among the xenobiotics that are designed to interact with plants, herbicide safeners protect cereal crops treated with herbicides (Riechers et al., 2010; Behringer et al., 2011; Skipsey et al., 2011). Various transcriptomics studies have shown that safener effects were related to their action at the signalling level, resulting in large-scale changes of gene expression. These effects on gene expression, involving classes of genes that are similar to the xenobiotic response, allow plants to develop effective responses of protection against herbicides. The molecular responses of plants to xenobiotic exposure are therefore clearly dependent on the type of xenobiotic, and play an important role in the outcome of plant–xenobiotic interactions in terms of sensitivity or tolerance. The coordinate expression of genes involved in coherent metabolic and detoxifying pathways and the differential expression of multigene families strongly suggest the importance of underlying regulatory mechanisms. Most of the xenobiotic responses that have been studied to date at the transcriptome profiling level involve expression modifications of genes encoding transcription factors or signal transduction proteins (Ramel et al., 2007; Weisman et al., 2010; Riechers et al., 2010; Jin et al., 2011; Peng et al., 2011). Tables 1 and 2 show the variety of transcription factors that were associated with atrazine sensitivity and tolerance, respectively (Ramel et al., 2007). Moreover, xenobiotic-regulated transcription factors show typical expression time courses associated with early or late responses (Ramel et al., 2007; Skipsey et al., 2011). Early regulation of transcription factors is likely to reflect transduction from stress signals to induction of xenobiotic responses and physiological accommodation, whereas later modifications may combine both responses to xenobiotic stress and changes of physiological status. For instance, time-dependent transcriptome profiling of atrazine response reveals large-scale differences of gene expression between 12 and 48 h of herbicide treatment (Gwenola Gouesbet, Fanny Ramel, Cécile Sulmon, Ivan Couée, unpublished data). Table 1. Identification of induced transcription factors associated with sensitivity to xenobiotic stress. Gene expression data were extracted from the transcriptomic profiling experiments registered as E-MEXP-411 in ArrayExpress (Ramel et al., 2007). The transcriptomes of Arabidopsis plantlets under control conditions (M, mannitol), under conditions of atrazine stress (MA, mannitol plus atrazine), in the presence of exogenous sucrose (S, sucrose), and in the presence of atrazine under conditions of stress tolerance (SA, sucrose plus atrazine) were compared. Differentially expressed genes were those genes showing at least one P value ≤0.05 after Bonferroni correction, in one of the MA/M, S/M, or SA/M comparisons (Ramel et al., 2007). Genes with a Bonferroni P value higher than 5% were considered as being not differentially expressed (nde). Current annotations were updated from the Arabidopsis Information Resource (Lamesch et al., 2012).     Treatment comparison (log2 (ratio))  Accession no.  Gene product  MA/M  S/M  SA/M  At5g17300  Myb family  2.70  –1.86  nde  At2g46830  CCA1  2.06  nde  nde  At5g62320  Myb99  1.92  –0.97  nde  At2g47270  UPBEAT1  1.89  –1.93  nde  At1g76880  Homeodomain-like protein  1.86  nde  nde  At3g52440  Dof-type zinc-finger protein  1.55  nde  nde  At5g63160  BTB/TAZ domain protein 1  1.39  –2.31  nde      Treatment comparison (log2 (ratio))  Accession no.  Gene product  MA/M  S/M  SA/M  At5g17300  Myb family  2.70  –1.86  nde  At2g46830  CCA1  2.06  nde  nde  At5g62320  Myb99  1.92  –0.97  nde  At2g47270  UPBEAT1  1.89  –1.93  nde  At1g76880  Homeodomain-like protein  1.86  nde  nde  At3g52440  Dof-type zinc-finger protein  1.55  nde  nde  At5g63160  BTB/TAZ domain protein 1  1.39  –2.31  nde  View Large Table 2. Identification of induced transcription factors associated with tolerance to xenobiotic stress. See Table 1 for all details.     Treatment comparison (log2 (ratio))  Accession no.  Gene product  MA/M  S/M  SA/M  At2g40340  ERF/AP2 transcription factor family, DREB subfamily, AtERF48  nde  2.21  3.28  At3g50260  ERF/AP2 transcription factor family, DREB subfamily, CEJ1  nde  1.67  3.26  At3g28210  Zinc-finger protein, PMZ  nde  2.75  3.19  At2g47890  B-box type zinc-finger protein  1.19  1.37  3.05  At5g13080  WRKY75  0.79  2.00  2.89  At2g23320  WRKY15  nde  1.05  2.33  At3g61630  AP2/ERF transcription factor family, CRF6  nde  1.04  2.14  At2g30250  WRKY25  0.75  1.14  2.10  At5g59820  Zinc-finger protein, ZAT12  nde  1.15  2.08  At3g56710  Sigma-factor-binding protein 1, SIB1  nde  nde  1.84      Treatment comparison (log2 (ratio))  Accession no.  Gene product  MA/M  S/M  SA/M  At2g40340  ERF/AP2 transcription factor family, DREB subfamily, AtERF48  nde  2.21  3.28  At3g50260  ERF/AP2 transcription factor family, DREB subfamily, CEJ1  nde  1.67  3.26  At3g28210  Zinc-finger protein, PMZ  nde  2.75  3.19  At2g47890  B-box type zinc-finger protein  1.19  1.37  3.05  At5g13080  WRKY75  0.79  2.00  2.89  At2g23320  WRKY15  nde  1.05  2.33  At3g61630  AP2/ERF transcription factor family, CRF6  nde  1.04  2.14  At2g30250  WRKY25  0.75  1.14  2.10  At5g59820  Zinc-finger protein, ZAT12  nde  1.15  2.08  At3g56710  Sigma-factor-binding protein 1, SIB1  nde  nde  1.84  View Large Similarities in terms of injury and defence have led to comparisons with a wider range of signalling molecules and signalling stresses (Riechers et al., 2010; Weisman et al., 2010; Skipsey et al., 2011). Plants are able to elicit responses to a myriad of natural products, such as hormones, regulators, endogenous toxic compounds, reactive oxygen species (ROS), pathogen-associated molecular patterns, and allelochemicals. Comparison of phenanthrene-induced responses with a panel of 27 signalling conditions has revealed significant positive correlations between PAH and ROS responses (Weisman et al., 2010). Safener-induced responses are positively correlated with responses to the reactive electrophilic species oxylipins (Riechers et al., 2010; Skipsey et al., 2011) and with responses to the allelochemical benzoxazolin-2(3H)-one (Baerson et al., 2005; Riechers et al., 2010). These correlations may be ascribed to common chemical properties, such as electrophilic strength, of these compounds, whether exogenous or endogenous. However, it remains difficult to ascribe specific mechanisms to such correlations in the patterns of transcriptomic responses. Interactions between transcription factors or signalling pathways may be involved (Ramel et al., 2007; Ehlting et al., 2008; Riechers et al., 2010). Thus, the ZAT12 and bZIP60 transcription factors, which are associated with the atrazine tolerance response of A. thaliana (Ramel et al., 2007), are respectively involved in the responses to oxidative stress (Davletova et al., 2005) and endoplasmic stress (Iwata and Koizumi, 2005). However, the metabolism of signalling molecules, such as phytohormones, can also be regulated by xenobiotics. Herbicides (Ramel et al., 2007) and herbicide safeners (Riechers et al., 2010; Skipsey et al., 2011) affect genes involved in oxylipin and jasmonate metabolic pathways, and neonicotinoid insecticides induce endogenous synthesis of salicylate (Ford et al., 2010). Herbicides (Ramel et al., 2007) and PAHs (Weisman et al., 2010) affect ethylene-biosynthesis genes. This interplay makes more complex our understanding of the impact and toxicology of xenobiotics in plants. Toxicity is usually ascribed to action on macromolecular or cellular targets (Sulmon et al., 2004; Ge et al., 2008; Jin et al., 2011; Peng et al., 2011), and herbicides are generally designed on the basis of specific protein targets, such as photosystem I and photosystem II components (Fufezan et al., 2002). Transcriptomic and signalling effects of xenobiotics in plants encompass not only coordinated gene networks and defence responses (Ramel et al., 2007) but also incomplete responses (DeRidder et al., 2002) and even deleterious and cell death responses (Ramel et al., 2007; Wang et al., 2012). As in the case of animals (Ulrich, 2003; Kretschmann et al., 2011), complete understanding of xenobiotic effects in plants must take into account how transcriptomic and signalling effects interfere, not only positively, but also negatively, with biochemical effects deriving from xenobiotic-target interactions, and what is the molecular basis for these transcriptomic and signalling effects. Moreover, analysis of transcriptomic and signalling effects is extremely useful for studying xenobiotics that do not have previously described targets, such as safeners and adjuvants, or mixtures of actively toxic and inert components (Nobels et al., 2011). Identification and characterization of transcription factors associated with xenobiotic responses and identification of xenobiotic-response cis-acting regulatory elements Transcriptomics studies show that xenobiotic responses in plants involve expression regulation of transcription factor-encoding genes (Ekman et al., 2005; Ramel et al., 2007; Wang et al., 2012). Ramel et al. (2007) identified transcription factor-encoding genes that were induced in relation with sensitivity to atrazine and with modifications of ROS balance (Table 1). Thus, UPBEAT1 (Table 1), a basic helix-loop-helix (bHLH) transcription factor, regulates ROS distribution and gradients (Tsukagoshi et al., 2010). The BTB/TAZ domain protein 1 (Table 1) is highly responsive to hydrogen peroxide (Du and Poovaiah, 2004) and interacts with ethylene signalling pathways (Weber and Hellmann, 2009). Finally, Yanhui et al. (2006) have shown that CCA1 (Table 1), but not Myb99, is responsive to oxidative stress in the context of cadmium treatment. In contrast, other patterns of expression suggest that transcription factors can be related to the development of xenobiotic stress defence (Table 2). CEJ1, which encodes an ERF/AP2 transcription factor, is not differentially expressed under conditions of atrazine sensitivity and is highly expressed under conditions of atrazine tolerance. Moreover, this gene is induced by toxins such as cantharidin (Bajsa et al., 2011) and ochratoxin A (Wang et al., 2012). Ochratoxin A also induces the WRKY75- and ZAT12-encoding genes (Wang et al., 2012), which are associated with atrazine defence responses (Table 2). The WRKY75-encoding gene is induced by various ROS-generating effectors such as methyl viologen, the Alternaria alternata toxin, 3-aminotriazole, and ozone (Gadjev et al., 2006). Baerson et al. (2005) and Fode et al. (2008) have emphasized the central role of TGA factors in the development of xenobiotic defense responses. These factors, which are involved in biotic interactions (Rochon et al., 2006), respond to auxin analogues, allelochemicals, herbicide safeners, and pharmacological agents (Baerson et al., 2005; Fode et al., 2008; Behringer et al., 2011), through the action of a TGA-interacting protein, SCARECROW-like 14 (SCL14), a member of the GRAS family of regulatory proteins. Induction of xenobiotic defence responses by herbicide safeners also involves class II TGA transcription factors (Behringer et al., 2011). Most of these xenobiotic-associated transcription factors are involved in the response to other abiotic or biotic stressors, thus indicating crosstalk processes between xenobiotic, abiotic, and biotic stresses (Gadjev et al., 2006; Ehlting et al., 2008; Chen et al., 2010; Xie et al., 2010a). Xenobiotic-related transcription factors are likely to be key regulators of the coordinated gene networks that have been identified in transcriptomics studies (Ekman et al., 2005; Ramel et al., 2007; Wang et al., 2012). Various cis-acting regulatory elements (CAREs) have been identified in the promoter regions of xenobiotic-responsive genes, and frequency analysis has revealed that some of these CAREs were over-represented in the promoters of xenobiotic-defence genes, in agreement with the patterns of coordinated expression (Ekman et al., 2005; Ramel et al., 2007; Wang et al., 2012). The as-1 CARE motif is frequently found in the promoters of TGA-regulated genes that are highly responsive to hydrogen peroxide, xenobiotics, heavy metals, or pathogenesis-related patterns (Rama Devi et al., 2006; Fode et al., 2008; Behringer et al., 2011). In the promoters of genes associated with atrazine tolerance, Ramel et al. (2007) identified the over-representation of W-box-, MYB4-, LEAFY-, and RAV1-binding sites. The MYB4-binding site had already been associated with promoters of genes involved in the resistance to cucumber mosaic virus infection and in UV-B responses (Marathe et al., 2004; Zhao et al., 2007). Table 3 shows the frequency analysis of CARE motifs associated with atrazine regulation (Ramel et al., 2007) in the promoters of genes that are induced by atrazine under conditions of sensitivity. The over-representation of typical CAREs in the promoters of xenobiotic-responsive genes is confirmed. Among these xenobiotic-associated CAREs (Table 3), the MYB3-binding site motif, which has been involved in other stress responses (Bang et al., 2008), and the TGA1-binding site, which has been involved in other xenobiotic responses (Fode et al., 2008), are over-represented. Most over-represented binding motifs did not correspond to transcription factors that were identified as atrazine-responsive in transcriptomics analysis (Ramel et al., 2007). This discrepancy may suggest that transcription factor involvement in xenobiotic responses depends not only on transcriptional regulation of transcription factor-encoding genes (Tables 1 and 2; Ekman et al., 2005; Ramel et al., 2007; Wang et al., 2012), but also on post-transcriptional or post-translational mobilization of pre-existing transcription factor mRNAs or proteins. This multifaceted involvement of transcription factors requires further studies that should integrate transcriptomics and expression of candidate genes with mutant analysis. Table 3. Identification of CAREs associated with atrazine-regulated genes. Sets of atrazine-regulated promoters which had been identified by Ramel et al. (2007) were analysed by the Athena tool (O’Connor et al., 2005) to identify transcription factor-binding motifs and assess their occurrence in the promoter set relative to the whole genome. The Athena application contains a database of 30 067 predicted promoter sequences from Arabidopsis and 105 consensus sequences of characterized transcription factor-binding sites. The promoter set from transcriptomics clusters E-H-O described in Ramel et al. (2007) corresponds to genes that are induced by atrazine preferentially under conditions of sensitivity. The P values of the comparisons given below were lower than 0.001.     Percentage of occurrence  Cis-acting element  Consensus sequence  Promoter set  Genome  TATA-box motif  TATAAA  86%  82%  ABRE-like motif  YACGTGGC  29%  20%  Ibox promoter motif  GATAAG  43%  40%  MYB3 binding site  TAACTAAC  9%  5%  TGA1 binding site  TGACGTGG  7%  3%  UPR motif IAT  CCACGTCA  7%  3%      Percentage of occurrence  Cis-acting element  Consensus sequence  Promoter set  Genome  TATA-box motif  TATAAA  86%  82%  ABRE-like motif  YACGTGGC  29%  20%  Ibox promoter motif  GATAAG  43%  40%  MYB3 binding site  TAACTAAC  9%  5%  TGA1 binding site  TGACGTGG  7%  3%  UPR motif IAT  CCACGTCA  7%  3%  View Large Impact of signalling mutations on xenobiotic stress responses Mutant analysis plays an essential role in the study of plant responses to xenobiotic stress. Various phenotypes of xenobiotic tolerance have been ascribed to mutations of genes encoding target proteins or related to target organelles, or to promoter mutations leading to overexpression of detoxifying genes. Mutations of the psbA gene, encoding the D1 protein of photosystem II (Rios et al., 2003), and of the acetolactate synthase (ALS) gene (Ray et al., 2004; Roux, et al., 2005), induce tolerance respectively to triazine herbicides and to sulphonylureas and imidazolinones. Mutations affecting the development of organelles targeted by xenobiotics alter response phenotypes. ‘Happy on norflurazon’ (hon) mutations, which affect plastid homeostasis, induce tolerance to bleaching herbicides by activating stress acclimation (Saini et al., 2011). Different steps of xenobiotic detoxification in plant cells have been validated using overexpressing or knockout mutants. Overexpression of genes encoding cytochrome P450 (Didierjean et al., 2002) or γ-glutamylcysteine synthetase (Gullner et al., 2001) induces xenobiotic tolerance. Mutant analysis has led to the identification of novel xenobiotic-response genes, such as the gene encoding phytochelatin synthase 1, which is involved in the degradation of xenobiotic gluthatione S-conjugates (Blum et al., 2007), or genes encoding pleiotropic drug resistance transporters, which are involved in the regulation of cell efflux and influx of xenobiotics (Ito and Gray, 2006; Xi et al., 2011). Characterization of novel genes through mutant analysis is a method of choice for the study of signalling and regulating processes that control xenobiotic responses. The role of TGA transcription factors has been revealed through mutant and immunoprecipitation approaches (Fode et al., 2008; Behringer et al., 2011; Johnson et al., 2001). These basic leucine zipper domain (bZIP) transcription factors are positive or negative regulators of stress responses, which act by binding to as-1-type elements of target gene promoters (Rama Devi et al., 2006). The tga quadruple mutant (tga2/3/5/6 known as 4tga) was unable to induce several gene families involved in responses to toxins and drugs, to oxidative stress, and to abiotic stresses. Class II TGA factors are therefore key components of xenobiotic signalling pathways (Behringer et al., 2011). Fode et al. (2008) showed the involvement of the GRAS protein SCL14 in this mechanism. Mutants with affected expression of SCL14 increased (SCL14-overexpressing HA3-SCL14 line) or decreased (scl14-knockout mutant) the expression of xenobiotic-inducible genes in response to herbicide treatment. Chromatin immunoprecipitation experiments with scl14 and tga2, 5, 6 mutants showed that the GRAS protein SCL14 was recruited by as-1-bound TGA factors, thus serving as sequence-specific anchor protein. Expression of such xenobiotic-inducible genes is conditioned by the formation of a TGA/SCL14/as-1 complex (Fode et al., 2008) and by xenobiotic-enhanced transcription factor-binding activity (Johnson et al., 2001). Ramel et al. (2007) identified the potential involvement of several transcription factors in the different types of atrazine response in A. thaliana (Tables 1 and 2). For three of these genes, At5g59820, At3g61630, and At3g56710, respectively encoding a zinc-finger family protein (Zat12), an ERF/AP2 transcription factor, and SIB1, corresponding insertional mutants from the SALK collection (Alonso et al., 2003), named zat12-8d, ap2-2d, and sib1-1, were studied for their responses to atrazine (Fig. 1). The behaviour of the ap2-2d and sib1-1 mutant lines was consistent with the involvement of the At3g61630 (ERF/AP2 transcription factor) and At3g56710 (SIB1) genes in sucrose activation of atrazine tolerance response and in the crosstalk between nutritional and xenobiotic signals (Ramel et al., 2007), in contrast with the Zat12 gene, whose corresponding mutant showed a similar behaviour to that of wild type (Fig. 1A). Whereas the three genes under study were not differentially expressed under conditions of atrazine sensitivity (Table 2), ap2-2d and sib1-1 mutant lines exhibited a lower level of atrazine inhibition than the wild-type and the zat12-8d lines (Fig. 1B), thus suggesting the involvement of ERF/AP2 and SIB1 transcription factors in atrazine sensitivity through post-transcriptional mechanisms. Such post-transcriptional effects of atrazine on transcription factors could be related to the repression of antioxidant defence genes in the presence of atrazine (Ramel et al., 2007). All of these results involving post-transcriptional effects of xenobiotics on transcription factors (Fode et al., 2008; Johnson et al., 2001; Fig. 1) strongly suggest sensing and signalling mechanisms that include direct action on transcription factors. Fig. 1. View largeDownload slide Impact of transcription factor mutations on the atrazine responses of A. thaliana. Mutant lines zat12-8d, ap2-2d, and sib1-1, respectively affected in the ZAT12 transcription factor, an AP2/ERF transcription factor, and the SIB1 transcription factor, were obtained from the Nottingham Arabidopsis Stock Centre (NASC) and corresponded to SALK_037357 (zat12-8d), SALK_063548 (ap2-2d), and SALK_127478C (sib1-1) lines. Two-week-old wild-type (Col-0) and mutant seedlings were transferred for 7 days of further growth under control conditions (M, 80 mM mannitol), on atrazine (MA, 80 mM mannitol and 10 mM atrazine), or on sucrose and atrazine (SA, 80mM sucrose and 10 mM atrazine), as previously described (Ramel et al., 2007). Chlorophyll levels in the wild-type and mutant lines under the three growth conditions were determined as described in Ramel et al. (2007). The (SA-MA)/MA (panel A) and (M-MA)/M (panel B) ratios represent the activation of atrazine tolerance by sucrose, and the extent of atrazine sensitivity in the absence of sucrose, respectively. Results are given as the mean±SEM. Fig. 1. View largeDownload slide Impact of transcription factor mutations on the atrazine responses of A. thaliana. Mutant lines zat12-8d, ap2-2d, and sib1-1, respectively affected in the ZAT12 transcription factor, an AP2/ERF transcription factor, and the SIB1 transcription factor, were obtained from the Nottingham Arabidopsis Stock Centre (NASC) and corresponded to SALK_037357 (zat12-8d), SALK_063548 (ap2-2d), and SALK_127478C (sib1-1) lines. Two-week-old wild-type (Col-0) and mutant seedlings were transferred for 7 days of further growth under control conditions (M, 80 mM mannitol), on atrazine (MA, 80 mM mannitol and 10 mM atrazine), or on sucrose and atrazine (SA, 80mM sucrose and 10 mM atrazine), as previously described (Ramel et al., 2007). Chlorophyll levels in the wild-type and mutant lines under the three growth conditions were determined as described in Ramel et al. (2007). The (SA-MA)/MA (panel A) and (M-MA)/M (panel B) ratios represent the activation of atrazine tolerance by sucrose, and the extent of atrazine sensitivity in the absence of sucrose, respectively. Results are given as the mean±SEM. Mutant analysis has also been central in revealing that hormone pathways were involved in the responses to xenobiotics. For reasons of structural design and mechanism of action, mutants of auxin signalling pathways have been widely used for the study of auxin-like analogues (Teixeira et al., 2007; Gleason et al., 2011). However, involvement of hormone pathways has also been demonstrated for xenobiotics that were neither designed nor characterized as hormone analogues. Phenotyping mutants corresponding to key steps of the ethylene signalling pathway, such as the ethylene precursor (1-aminocyclopropane-1-carboxylic acid synthase, eto3 line) biosynthesis enzyme, the ethylene receptors (etr1 and ein4 lines), the negative regulator Raf-like ser/thr kinase CTR1 (ctr1 or sis1 lines), and the EIN2 signal transduction protein (ein2 lines), revealed that different xenobiotic responses were at least partially connected to the ethylene pathway (Sulmon et al., 2006; Weisman et al., 2010). Weisman et al. (2010) showed that phenanthrene negatively interferes with ethylene biosynthesis or signal transduction, independently of the ETR1 receptor. Sulmon et al. (2006) demonstrated that the ethylene pathway was involved in sugar-regulated induction of atrazine tolerance. The involvement of the Raf-like Ser/Thr kinase CTR1 (Sulmon et al., 2006) underlined the relevance of mitogen-activated protein kinases (MAPKs) in stress signalling pathways (Nakagami et al., 2005). The involvement of the salicylic acid pathway in xenobiotic responses has been investigated by Behringer et al. (2011), who described, using safeners, the overlap between the signalling pathways for systemic acquired resistance and xenobiotic detoxification. Analysis of salicylic acid-deficient (sid2-2) and NON-EXPRESSOR of PR-1 (NPR1)-deficient (sai) mutants showed that responses to safeners were mediated in part by salicylic acid, through both TGA factor-dependent and -independent pathways, but independently of the systemic acquired resistance-related NPR1 gene. Jasmonate and jasmonate-related oxylipins are also considered to be part of xenobiotic responses and stress-related detoxification systems (Ramel et al., 2007; Riechers et al., 2010). Moreover, Skipsey et al. (2011) recently described a fad3-2/fad7-2/fad8 triple mutant that is defective in forming the oxylipin precursor linolenic acid, and that exhibits strongly depressed xenobiotic responsiveness. Other pathways may be involved in xenobiotic responses and signalling. However, although mutant lines corresponding to most signalling pathways are available, phenotype analysis in a context of xenobiotic treatment remains to be carried out. For instance, mutants affected in heat-shock proteins and factors should be good candidates for further studies (Cox and Miller, 2004; Miller and Mittler, 2006). Secondary sensing of xenobiotic-induced effects As shown above, the xenobiotic response in plants involves large-scale gene networks, complex regulations,various transcription factors and protein kinases, and signalling effects. Moreover, the impact of xenobiotics on plants is dependent on xenobiotic chemical structure, on plant physiological status and on plant genotype, thus strongly indicating that gene expression regulations must be integrated with mechanisms of xenobiotic sensing. Xenobiotic action induces parallel and complex metabolic and biochemical disturbances, which, in turn, potentially generate numerous signals affecting cell homeostasis and genome regulation (Ramel et al., 2007; Weisman et al., 2010). Various xenobiotics are known to induce ROS production, with important biochemical consequences. However, ROS can function as cellular second messengers that are likely to modulate many different genes and proteins thus leading to a variety of responses (Jaspers and Kangasjärvi, 2010). ROS produced by membrane-bound NAD(P)H oxidases in plant cells activate plasma membrane calcium channels, leading to further increase in cytosolic calcium (Foreman et al., 2003; Mori and Schroeder, 2004). This increase in turn activates downstream signalling involving the MAPK pathway, with ROS seemingly exerting a direct and central role in the induction and stabilization of the MAPK cascade (Nakagami et al., 2005; Dóczi et al., 2007). Thus, the vast network of MAPKs is involved in relaying hydrogen peroxide signals to their targets, which consist of various transcription factors. The involvement of ROS-mediated signalling in plant responses to abiotic stress is therefore well established, but the mechanisms of ROS sensing have not been fully elucidated. Miller and Mittler (2006) have characterized the importance of heat-shock transcription factors in the transduction of ROS signalling and their potential role as direct hydrogen peroxide sensor. The AtGPX3 gene, like the oxidative stress transcription factor Yap1 in yeast (Herrero et al 2008), seems to sense and transduce hydrogen peroxide signal to downstream components in plants (Miao et al 2006) and potentially works as a primary ROS sensor. Disruption of photosynthesis by some xenobiotics leads to production of singlet oxygen (Fufezan et al., 2002; Ramel et al., 2009a), which has a very short half-life, powerfully oxidizes various targets, including carotenoids, and triggers major cell death processes (op den Camp et al., 2003). Cell death associated with 1O2-induced oxidative stress in Arabidopsis has been ascribed to activation of a genetic programme requiring a chloroplast protein named EXECUTER1, rather than to physico-chemical damages. This protein interacts with the EXECUTER2 modulator to transfer 1O2-derived plastid signals to the nucleus (Lee et al., 2007). However, the comparison of different transcriptomic studies performed in atrazine-treated Arabidopsis plants (Ramel et al., 2007, 2009a), in the flu mutants (op den Camp et al., 2003), and in the npq1lut2 mutant (Alboresi et al., 2011) reflects the complexity of 1O2 signalling pathways. Even if all of these situations lead to production and accumulation of 1O2, cellular responses present major differences with activation of different gene networks, thus highlighting the specificities of xenobiotic and high-light stresses. Moreover, it remains difficult to distinguish between direct ROS sensing and perception of ROS-mediated changes. ROS production leads to rapid modifications of target molecules, such as nucleic acids, proteins, and lipids, that can generate stress signals and initiate acclimation or alarm responses in plants. One major example of such indirect sensing of xenobiotic-related damages concerns the non-enzymatic production of oxylipins via the action of ROS. These hydroxy fatty acids and phytoprostanes play important signalling roles in plant stress responses (Sattler et al., 2006) by activating the expression of stress-response genes and enhancing protection from oxidative stress (Thoma et al., 2003; Loeffler et al., 2005). Differences in gene induction between oxylipins suggest the existence of multiple signal transduction pathways (Mueller et al., 2008), but it must be clarified how oxylipin signals are sensed and transduced in plant cells. Many genes that are induced by oxidized fatty acids are controlled by TGA transcription factors (Mueller et al., 2008). Moreover, as discussed above, Fode et al. (2008) showed that the GRAS protein SCL14 interacted with these TGA transcription factors and contributed to activate stress-inducible promoters of genes involved in xenobiotic detoxification. In the case of singlet oxygen production, oxidation of β-carotene leads to rapid accumulation of various aldehydes and endoperoxides (Ramel et al., 2012). These compounds could be potential messengers involved in initial steps of the 1O2 signaling pathway in plants. Finally, it must be pointed out that xenobiotic-derived effects could interact directly with regulatory proteins and transcription factors (Fig. 2). Thus, xenobiotic-induced ROS dynamics (Ramel et al., 2007; Weisman et al., 2010) entail oxidative modifications of proteins, especially at the level of cysteine and methionine residues, and differential targeting for protein degradation. Xenobiotic-induced changes of membrane fluidity (Teixeira et al., 2007) could also modify the stability of membrane-bound protein complexes. Overall, such effects could lead to the activation or inactivation of pre-existing regulatory proteins and transcription factors, and could constitute a sensing mechanism without specific receptors, as was recently shown for plant oxygen-sensing, where constitutively expressed ethylene response factors are mobilized or degraded in response to oxygen–hypoxia transitions (Sasidharan and Mustroph, 2011). Fig. 2. View largeDownload slide Primary and secondary xenobiotic signalling interactions. Hypothetical pathways of xenobiotic (X) sensing and signalling are described: (i) receptor (R) sensing of metabolites (M) and toxic compounds (T) derived from xenobiotic-target interactions, (ii) sensing of cytoplasmic xenobiotic levels by intracellular receptors or transcription factors (TF), (iii) sensing of extracellular xenobiotic levels by membrane-bound receptors (R), and (iv) biochemical modifications of receptors, transcription factors or signal transducers. Arrows indicate ligand-binding and signalling interactions. Explosion pictograms indicate biochemical effects on regulatory proteins. Major classes and examples of xenobiotic-regulated genes characterized in plants (Ekman et al., 2005; Ramel et al., 2007; Weisman et al., 2010) are shown. ACC, 1-aminocyclopropane-1-carboxylic acid. Fig. 2. View largeDownload slide Primary and secondary xenobiotic signalling interactions. Hypothetical pathways of xenobiotic (X) sensing and signalling are described: (i) receptor (R) sensing of metabolites (M) and toxic compounds (T) derived from xenobiotic-target interactions, (ii) sensing of cytoplasmic xenobiotic levels by intracellular receptors or transcription factors (TF), (iii) sensing of extracellular xenobiotic levels by membrane-bound receptors (R), and (iv) biochemical modifications of receptors, transcription factors or signal transducers. Arrows indicate ligand-binding and signalling interactions. Explosion pictograms indicate biochemical effects on regulatory proteins. Major classes and examples of xenobiotic-regulated genes characterized in plants (Ekman et al., 2005; Ramel et al., 2007; Weisman et al., 2010) are shown. ACC, 1-aminocyclopropane-1-carboxylic acid. At a higher level of integration, xenobiotic stress causes global dysfunction of cell homeostasis, protein turnover, carbon and nitrogen metabolism, ionic and redox status, energy balance, and photosynthesis input, which must be re-established through stress-adaptative mechanisms (López-Maury et al., 2008; de Nadal et al., 2011). All of these changes result in variations of endogenous signals, such as soluble sugars (Ramel et al., 2007; Baena-González and Sheen, 2008) and amino acids (Diaz Vivancos et al., 2011), which can activate many signalling cascades and can induce photochemical, metabolic, and molecular reprogramming for stress adaptation and defense (Basanti et al., 2011). In this context, photosynthesis, carbon status, nitrogen status, and redox status can be considered as global stress sensors or parameters in plants (Couée et al., 2006; Ramel et al., 2009b; Basanti et al., 2011; Diaz Vivancos et al., 2011). These global stress sensors are connected with homeostasis sensors such as the sucrose non-fermenting 1-related kinase 1 (SnRK1) and target of rapamycin (TOR) kinase pathways (Baena-González and Sheen, 2008; López-Maury et al., 2008) through mechanisms that remain largely unknown, and that determine how diverse stress and homeostasis signals are integrated into cell death or survival responses. Moreover, these events are different in cells responding to slow and moderate stressors and in cells responding to sudden and severe stressors, thus emphasizing the importance of the kinetics and intensity of xenobiotic stress stimuli. Primary sensing of xenobiotics: comparative evidence for candidate xenobiotic sensors in higher plants and preliminary characterization of these sensors The responses of organisms to environmental changes and stress (López-Maury et al., 2008; de Nadal et al., 2011; Zakrzewska et al., 2011) may combine the perception of internal growth-dependent parameters, of stress-induced endogenous signals (Fig. 2) and of direct stress signals (Fig. 2). Analysis of yeast growth mutants indicates that yeast cells mainly respond to external signals rather than to internal changes and that this response relies on sensors (López-Maury et al., 2008). Perception of xenobiotics as external signals by xenobiotic receptors has been described in detail in animal cells (Ulrich, 2003; Baker, 2005; McMillan and Bradfield, 2007). Most of these animal xenobiotic receptors are nuclear receptors that have transcription factor activity or are part of transcription factor complexes (Ulrich, 2003; Baker, 2005), which closely links environmental cues and genome functioning. Thus, the AhRs, which recognize endogenous ligands and environmental contaminants, are members of the bHLH-Per-ARNT-Sim (bHLH-PAS) family of transcription factors (Ulrich, 2003; McMillan and Bradfield, 2007). Moreover, xenobiotic nuclear receptors show complex interactions with xenobiotic cues and with xenobiotic-related responses: (i) these receptors play essential roles in the regulation of xenobiotic-response genes, especially in the regulation of xenobiotic-metabolizing enzymes (Tolson and Wang, 2010), (ii) they play major roles in energy homeostasis, cell differentiation, and cell growth (Ulrich, 2003; Baker, 2005), (iii) the various effects of receptors on biological processes are partially overlapping (Ulrich, 2003), and (iv) a given xenobiotic can recruit several receptors (Anderson et al., 2011). The final integration of all of these interactions can lead to toxicity and sensitivity or to adaptation and tolerance. Homologues of xenobiotic nuclear receptors have not been found in yeast or in plants, and xenobiotic nuclear receptors are considered to be unique to the evolution of multicellular animals (Baker, 2005). The yeast genome comprises a very small number of bHLH transcription factors relatively to the human genome (Feller et al., 2011). In contrast, plant genomes are endowed with a larger array of bHLH transcription factors than the human genome (Feller et al., 2011) and some plant bHLH transcription factors interact with environment-regulated receptors (Leivar and Quail, 2011). Moreover, Shimazu et al. (2011) have shown that, in engineered transgenic Arabidopsis plants, a fusion protein consisting of guinea pig AhR with DNA-binding (LexA) and transactivating (VP16) domains could discriminate between polychlorinated biphenyl congeners (PCB80 and PCB126) and activate in a PCB126-specific manner a LexA-responsive reporter gene. This clearly indicated that mammalian AhR proteins could function in a plant cell context, with the important caveat that no action on endogenous plant promoters was reported (Shimazu et al., 2011). Given their protective effects that depend on transcriptional activation and given their specificity, herbicide safeners are likely to act by binding to regulatory proteins rather than by eliciting secondary biochemical messengers (Riechers et al., 2010; Behringer et al. 2011; Skipsey et al., 2011). There appears to be little information on the proteins that may be involved (Riechers et al., 2010), a major exception being the identification of a safener-binding protein in maize (Walton and Casida, 1995), whose molecular functions remain to be determined. Detailed analysis of the dynamics of xenobiotic toxicity suggests that physiological effects and secondary biochemical effects resulting from xenobiotic binding to primary targets are not necessarily connected. Although atrazine interacts with the D1 protein of photosystem II and elicit singlet oxygen production (Fufezan et al., 2002; Ramel et al., 2009a), a number of atrazine effects do not seem to depend on singlet oxygen mediation. Arabidopsis plants at different stages of development (non-green seedlings, green-cotyledon seedlings, plants with young sink leaves, plants with young source leaves) are sensitive to atrazine treatment (Sulmon et al., 2006). When Arabidopsis photosynthetic plantlets are treated with atrazine in the presence of tolerance-inducing concentrations of sucrose, atrazine significantly enhances root growth and development, while chlorophyll and carotenoid contents remain constant (Sulmon et al., 2004; Ramel et al., 2007), thus indicating that atrazine could have direct effects on non-photosynthetic tissues. Moreover, the allene oxide synthase gene At5g42650, which is up-regulated in the presence of singlet oxygen (op den Camp et al., 2003), is strongly down-regulated (7-fold repression) in the presence of atrazine despite the production of singlet oxygen (Ramel et al., 2007, 2009a). Such singlet oxygen-independent effects of atrazine on developmental and molecular processes would be in agreement with the hypothesis of direct xenobiotic sensing in plants. In a very limited number of cases, homologues of xenobiotic receptors that are not nuclear receptors have been characterized in plants. A novel Arabidopsis protein, A. thaliana TSPO-related (AtTSPO) has been found to be related to mammalian mitochondrial translocator protein (Guillaumot et al., 2009), to mammalian peripheral benzodiazepine receptors (Lindemann et al., 2004), and to bacterial tryptophan-rich sensory proteins (Guillaumot et al., 2009). Similar proteins exist in Solanum tuberosum (Corsi et al., 2004) and in the moss Physcomitrella patens (Frank et al., 2007). Various abiotic stress and hormone treatments regulate AtTSPO, which is encoded by the At2g47770 gene, at the transcriptional, post-transcriptional, and post-translational levels (Balsemão-Pires et al., 2011). Interestingly, the At2g47770 gene is also up-regulated by atrazine (Ramel et al., 2007). Analysis in a heterologous bacterial cell system showed that Arabidopsis TSPO protein carried out high-affinity uptake of protoporphyrin and that this uptake was stimulated by benzodiazepine (Lindemann et al., 2004). In other words, AtTSPO seems to perceive xenobiotics such as benzodiazepines and to initiate a response involving the tetrapyrrole intermediate protoporphyrin (Lindemann et al., 2004). This relationship is likely to have important physiological consequences: (i) protoporphyrin is photoreactive and related to ROS production (Balsemão-Pires et al., 2011), (ii) it is involved in the toxicity of diphenyl ether herbicides (Jacobs et al., 1991), and (iii) it is also involved in abiotic stress signalling (Zhang et al. 2010, 2011). Plant genomes show high proportions of potential receptor-kinase gene families, such as the receptor-like-kinase (RLK)/Pelle family and the two-component family (Grefen and Harter, 2004; Gish and Clark, 2011). Complete characterization of these large gene families is far from being achieved. However, up to now, no member of these plant gene and protein families has been identified as potential xenobiotic receptors. The plant leucine-rich repeat (LRR)-RLKs that have been characterized to date correspond to a variety of ligands, including endogenous proteins, sulphonated peptides or steroids, and pathogen–plant interaction elicitors (Gish and Clark, 2011). Some mammalian TLRs, which are the counterparts of plant LRR-RLKs involved in plant–pathogen interactions, are involved in crosstalk between the activation of inflammatory responses and of drug-metabolizing responses (Ghose et al., 2011). Components of the xenobiotic response in mammals are regulated by the activation of TLR2 by the lipoteichoic acid ligand from Gram-positive bacteria (Ghose et al., 2011). The plant two-component systems that have been characterized to date are involved in ethylene and cytokinin perception (Grefen and Harter, 2004). However, in prokaryotes, two-component kinases are involved in chemotaxis, abiotic stress signalling, and sensing of monoaromatic compounds (Krell et al., 2010). It may thus be speculated that specific plant LRR-RLKs or two-component systems could have evolved into xenobiotic sensors under xenobiotic pressure. Adaptive value and evolutionary dynamics of xenobiotic sensing The patterns of transcriptomic responses to multiple and complex stressors indicate that anthropogenic contaminants can contribute in situ to the physiological adaptations of organisms (Chapman et al., 2011). The extent of this contribution may not be predominant, when compared with natural physico-chemical factors, as was shown to be the case in oysters (Chapman et al., 2011). However, this contribution depends on pollution levels and dynamics and is context-dependent. Moreover, multiple-stressor studies indicate clear differences of responses between the effects of receptor-dependent contaminants and those of contaminants without corresponding receptors in the organism under consideration (Chapman et al., 2011). Selection of specific xenobiotic receptors that can carry out primary sensing of xenobiotics is indeed likely to provide organisms with a number of adaptive mechanisms (Fig. 2): (i) pre-emptive response by sensing exogenous xenobiotic levels, (ii) rapid induction of defence response prior to initiation of toxic effects, and (iii) modulation of cell homeostasis and of xenobiotic responses independently of toxicity-related responses. Thus, the nuclear receptors of vertebrates and invertebrates, as ligand-activated transcription factors, are rapid and important integrators of genome-environment interactions (Baker, 2005; Ulrich, 2003; McMillan and Bradfield, 2007). Some of the toxic molecules that are generated by xenobiotic action (ROS, peroxides, fatty acids, denatured proteins, denatured nucleic acids) are highly reactive and readily produce toxic cascades with multiple cellular targets and damage amplification (Frenkel et al., 2009; Fufezan et al., 2002; Liu et al., 2009; Teixeira, et al., 2007; Triantaphylidès et al., 2008). Direct sensing of xenobiotic molecules may be useful to contribute to prevent such cascades of damages and to set up defence mechanisms prior to amplification of cellular damages (Fig. 2). The speed of induction of defence mechanisms is indeed an important parameter of optimal survival after stress (de Nadal et al., 2011). In plant cells, singlet oxygen triggers cell death responses through sensing mechanisms and signalling pathways (op den Camp et al., 2003; Wagner et al., 2004). These signalling effects of singlet oxygen may be involved in the toxicity of singlet oxygen-generating herbicides (Ramel et al., 2007, 2009a), although singlet oxygen also initiates photooxidative hydroperoxide cascades (Triantaphylidès et al., 2008). Direct parallel sensing of these herbicides would be useful to modulate ROS induction of cell death. Moreover, efficiency of stress defence is tightly linked to the integration of stress responses and cell homeostasis. Analysis of stress responses in yeast and in bacteria shows that trade-off processes between detoxification and metabolism (Dominguez-Cuevas et al., 2006) or between growth and xenobiotic stress response (López-Maury et al., 2008) are finely regulated. In yeast, plants, or animals, stress signalling interacts with central integrators of nutrient balance and cell growth, such as TOR kinase, sucrose non-fermenting 1 (SNF1) kinase, SnRK1 kinase, or AMP-activated protein kinase (Baena-González and Sheen, 2008; López-Maury et al., 2008; Dobrenel et al., 2011). In yeast and animal cells this interaction involves stress-activated protein kinases (SAPKs) under the control of primary stress sensors (López-Maury et al., 2008; de Nadal et al., 2011). No direct link has yet been made between xenobiotic signalling and the TOR kinase or SnRK1 pathways in yeast or in plants. However, the effects of 2,4-dichlorophenoxyacetic acid on yeast involve modulation of nutrient availability and of the TOR kinase pathway (Teixeira et al., 2006). In plants, the effects of xenobiotics on cell homeostasis (Ramel et al., 2007) and the large-scale effects of exogenous and endogenous soluble sugars on xenobiotic responses (Ramel et al., 2007; Ramel et al., 2009b) point to balances between xenobiotic signalling and nutrient signalling. Thus, atrazine treatment of Arabidopsis plantlets increases mRNA levels of carbon starvation genes even under conditions of carbon feeding by exogenous sucrose (Ramel et al., 2007). Highly conserved eukaryotic SAPK pathways, which involve in particular the MAPK family and the SnRK2/SnRK3 family, are involved in plant responses to abiotic stress (Halford and Hey, 2009), xenobiotics (Sulmon et al., 2006; Wang et al., 2012), and ROS (Wang et al., 2010). As occurs in yeast, insects, and mammals (de Nadal et al., 2011), fine-tuning of xenobiotic responses and cell homeostasis in plants are likely to require the connection of SAPK pathways with specialized sensors. Thus, in Arabidopsis and Nicotiana, SnRK2s are negatively regulated in a calcium-dependent manner at post-translational level by a calcium sensor involved in the abscisic acid pathway (Bucholc et al., 2011). In contrast, atrazine treatment strongly increases the mRNA levels of the At1g78290 SnRK2-encoding gene (Ramel et al., 2007), in agreement with the hypothesis of separate xenobiotic-sensing mechanisms. In vertebrates and invertebrates, some xenobiotic sensors carry out endogenous functions and bind to various endogenous ligands, such as indole compounds, tetrapyroles, sterols, and fatty acid metabolites (McMillan and Bradfield, 2007). In bacteria, two-component sensor kinases can be involved in endogenous sensing, such as redox state sensing, chemotaxis, or sensing of benzene contaminants (Krell et al., 2010). Xenobiotic sensing is therefore likely to be related to chemical sensing at large. As described above, the analysis of transcription factor involvement, of CARE frequency, and of mutant responses reveals numerous links between xenobiotic, biotic, and abiotic stresses. In plants, recognition of chemical patterns by specific receptors is considered to play important roles in symbiotic interactions (Gish and Clark, 2011), in pathogen interactions (Gish and Clark, 2011), and in allelopathy (Baerson et al., 2005). Chemical recognition may also be involved in the protection against endogenous toxicants (Mueller and Berger, 2009; Triantaphylidès et al., 2008), such as endoperoxides, radicals, phenolic compounds, UV adducts, strong oxidants, or strong reductants. Xenobiotic sensing may be linked to these other chemical sensing mechanisms through the recognition of similar chemical properties, such as electrophilic strength (Riechers et al., 2010; Skipsey et al., 2011). Comparative transcriptomics strongly suggests relationships between xenobiotic signalling and biotic interaction signalling (Weisman et al., 2010). The range of chemical sensors and corresponding genes that exist in plants can provide a biochemical basis for fuzzy recognition (Baker, 2005) or stochastic recognition (López-Maury et al., 2008) of xenobiotics or a genetic basis for xenobiotic-dependent gene evolutionary dynamics (López-Maury et al., 2008). This may give plants potential strategies to cope with challenges from novel anthropogenic contaminants (López-Maury et al., 2008; Xie et al., 2010b). It has already been shown that the herbicide paraquat could be recognized and processed as an opportunistic substrate by an endogenous ABC transporter in Arabidopsis (Xi et al., 2011). Finally, examples from bacteria to mammals indicate that primary sensing can rely not only on proteins, but also on DNA, RNA, or lipid entities (de Nadal et al., 2011). Conclusion and future directions Current knowledge of xenobiotic sensing and signalling in plants greatly depends on transcriptome profiling analysis and comprises more information on signalling pathways (transcription factors, protein kinases, hormone crosstalk, metabolite crosstalk) than on sensors. However, as stated above, the potential of receptor and sensor identification in plants remains high, and novel sensors of environmental cues are continuously discovered, mainly through mutant characterization (Gish and Clark, 2011). Disruptome approaches using mutant collections, as has been carried out in yeast (Dias et al., 2010), can reveal regulatory genes, including those that are constitutively expressed and cannot be detected by gene expression approaches. However, up to now, Arabidopsis mutants showing xenobiotic tolerance or hypersensitivity are associated with genes encoding defence proteins or transcription factors rather than with sensing mechanisms. Similarly, the disruptome approach in yeast has revealed transcription factor-level regulatory networks (Dias et al., 2010). One possible way forward would be to systematize the study of xenobiotic-related transcription factors in relation with the characteristics of CAREs in xenobiotic-responsive genes, using dedicated molecular screening tools for stress signalling components (Rama Devi et al., 2006) or transcription factors (Wehner et al., 2011). Characterization of these key components could be the basis for searching protein partnerships with previously unknown proteins through yeast two-hybrid approaches. In this respect, the development of an international plant toxicogenomics database in the mould of the human Comparative Toxicogenomics Database (Davis et al., 2011) would be a great asset. Oriented investigation of candidate sensors can also be envisaged through RNA interference silencing, starting with the current range of potential plant xenobiotic sensors, which includes peripheral benzodiazepine receptor types (Corsi et al., 2004; Frank et al., 2007; Lindemann et al., 2004; Balsemão-Pires et al., 2011), plant-pathogen LRR-RLK types (Gish and Clark, 2011), and two-component receptor types (Grefen and Harter, 2004). Alternatively, detailed analysis of the binding of xenobiotics to their currently known targets may reveal structural motifs or signatures that could be used as anchors for mining corresponding sequence motifs in plant genomic databases and detecting genes encoding xenobiotic-binding proteins. With the development of mass sequencing and of novel analytical methods the molecular and genomic analysis of xenobiotic responses is rapidly expanding to non-model plant species and to emerging contaminants. The discovery of archetypal plant xenobiotic sensors may stem from these expanded genomic resources and novel plant–xenobiotic interactions. More information on xenobiotic sensing and signalling components will be useful in many aspects of plant ecotoxicology and environmental biotechnology. This will yield novel biomarkers that are related to gene networks and therefore more response-integrative and that may be more specific of chemical structures and more sensitive to low pollutant exposure (Zhou et al., 2008; Weisman et al., 2011). Like previously described biomarkers, these novel molecular markers will contribute to determine the response potential of plant species and plant communities subjected to contaminants. However, since xenobiotic sensing and signalling can lead to deleterious or adaptive effects (Ulrich, 2003; Ramel et al., 2007), the use of sensor and signal component genes and proteins as biomarkers will require in-depth characterization of their functions to distinguish potentially sensitive or tolerant plants for risk assessment (Zhou et al., 2008) or for phytoremediation (Rao et al., 2009). The possibility of parallel detection of several markers may improve phytosensing coverage of contaminant diversity and multi-contaminant pollutions (Zhou et al., 2008; Rao et al., 2009; Weisman et al., 2011). If, within a given biomonitoring plant species, different signalling pathways were activated according to contaminant levels, sensing and signalling biomarkers would be useful to detect contaminant variations in the environment. This aspect would be particularly interesting for contaminants and contaminant levels that are difficult to detect, and could be used to assess the time course and extent of depollution during phytoremediation processes. Abbreviations Abbreviations AhR aryl hydrocarbon receptor bHLH basic helix-loop-helix CARE cis-acting regulatory element GST glutathione S-transferase LRR leucine-rich repeat MAPK mitogen-activated protein kinase PAH polycyclic aryl hydrocarbon RLK receptor-like kinase ROS reactive oxygen species SAPK stress-activated protein kinase SCL SCARECROW-like SIB1 sigma-factor-binding protein 1 SnRK1 sucrose non-fermenting 1-related kinase 1 TLR Toll-like receptor TOR target of rapamycin Our research on plant–xenobiotic interactions is funded, in part, by the interdisciplinary programme 'Ingénierie écologique' from the Centre National de la Recherche Scientifique (CNRS, France) and by the Fondation pour la recherche sur la biodiversité (FRB, France). AAS is supported by a doctoral scholarship from the Brittany regional council (France). 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TI - Xenobiotic sensing and signalling in higher plants
JF - Journal of Experimental Botany
DO - 10.1093/jxb/ers102
DA - 2012-04-06
UR - https://www.deepdyve.com/lp/oxford-university-press/xenobiotic-sensing-and-signalling-in-higher-plants-a01MwHkH1e
SP - 3999
EP - 4014
VL - 63
IS - 11
DP - DeepDyve
ER -