Dehydration-Responsive Reversible and Irreversible Changes in the

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Dehydration-Responsive Reversible and Irreversible Changes in the Extracellular Matrix: Comparative Proteomics of Chickpea Genotypes with Contrasting Tolerance Deepti Bhushan,† Dinesh Kumar Jaiswal,† Doel Ray, Debarati Basu, Asis Datta, Subhra Chakraborty,* and Niranjan Chakraborty* National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi-110067, India

bS Supporting Information ABSTRACT:

Dehydration is the most crucial environmental factor that limits plant growth, development, and productivity affecting agriculture throughout the world. Studies on genetic variations for dehydration tolerance in plants is crucial because divergent cultivars with contrasting traits aid the identification of key cellular components that confer better adaptability. The extracellular matrix (ECM) is a dynamic structure that serves as the repository for important signaling components and acts as a front-line defense. To better understand dehydration adaptation, a proteomic study was performed on the extracellular matrix of ICCV-2, a dehydrationsusceptible genotype of chickpea. The proteome was generated with ECM-enriched fractions using two-dimensional gel electrophoresis. The LCESIMS/MS analysis led to the identification of 81 dehydration-responsive proteins. The proteome was then compared with that of JG-62, a tolerant genotype. Comparative proteomics revealed genotype-specific expression of many proteins involved in a variety of cellular functions. Further, the reversible and irreversible changes in the proteomes revealed their differing ability to recover from dehydration-induced damage. We propose that cell wall restructuring and superior homeostasis, particularly the management of reactive oxygen species, may render better dehydration-adaptation. To our knowledge, this is the first report on the comprehensive comparison of dehydration-responsive organellar proteome of two genotypes with contrasting tolerance. KEYWORDS: dehydration, chickpea, contrasting tolerance, extracellular matrix, comparative proteomics, cellular homeostasis

’ INTRODUCTION Most environmental stresses are characterized by the signature feature that at least part of their detrimental effect on plant performance is caused by the disruption of water status. Water deficit or dehydration is the most crucial factor that adversely affects plant growth, development, and crop productivity. One third of the world’s arable land suffers from chronically inadequate supplies of water and virtually in all agricultural regions, yields of rain-fed crops are periodically reduced by dehydration.1 Dehydration induces several changes in the cellular environment, such as reduced hydration of macromolecules and consequent conformational changes, reduced intracellular transport, and changes in ion concentrations.2 There is hardly a physiological process in plants that is not impaired by dehydration. The dehydration response is a complex phenomenon, and the exact structural and functional modification caused by dehydration is poorly understood. Most studies on dehydration to date have r 2011 American Chemical Society

mainly focused on the changes in gene expression, while there is far less information available on protein expression. The changes in gene expression are regulated by a number of different, and potentially overlapping, signal transduction pathways.3,4 Nevertheless, the significance of these genes in dehydration tolerance is incomplete without the knowledge of their functional products. In recent years, much attention has been given to use crop plants of agricultural importance in investigating dehydration tolerance because of the availability of different genotypes with differing degrees of tolerance. This provides correlative evidence for targeted components putatively involved in dehydration response. Furthermore, the transient and moderate dehydration represented in studies of crop species usually describes the most common form of dehydration that most plants are likely to encounter. Indeed, investigation on molecular basis of Received: January 6, 2011 Published: February 24, 2011 2027

dx.doi.org/10.1021/pr200010f | J. Proteome Res. 2011, 10, 2027–2046

Journal of Proteome Research dehydration responses in contrasting genotypes not only helps in unraveling the underlying mechanisms but also in distinguishing dehydration-responsive elements from that conferring dehydration tolerance. Eukaryotic cells are compartmentalized, thus providing distinct environments for biochemical processes such as protein synthesis and degradation, provision of energy-rich metabolites, and DNA replication. The compartmentalized structures are supported by subsets of proteins that are specifically targeted to particular compartments. Therefore, protein localization is linked to cellular function that requires proteome analysis with subcellular resolution. Cell wall or extracellular matrix (ECM) is the most distinct subcellular structure that not only differentiates plant cells from that of animal but acts as the front-line defense.5 It constitutes an important conduit for signal transduction and greatly influences the cell fate decision.6 Although proteins account for only 10% of the ECM mass,7 they play diverse roles involving continuous crosstalk with the plasma membrane proteins and the cytoskeletal network. Whereas cell wall proteomes have been developed in Arabidopsis,810 Medicago,11 chickpea,12 maize,6 and rice,13,14 investigations on their role in stress adaptation are still extremely limited. The legumes are the third largest family of higher plants with nearly 20 000 species and are characterized by their symbiotic relationships with both nitrogen fixing bacteria and arbuscular mycorrhizal fungi. In recent years, legume genomics has been focused primarily on the development of genetic resources and information of two model species, Medicago truncatula and Lotus japonicus, and an economically important species, soybean.15 The development of similar research in other species has been lagging, which has limited the overall impact of legume genomics. Chickpea is one of the most important grain legumes cultivated worldwide and is valued for its nutritive seeds with high protein content, 2529%.16 Dehydration stands to be the most crucial problem in major chickpea growing regions because it is grown on residual moisture and the crop is eventually exposed to terminal dehydration.17 In a previous study, we had established that c.v. JG-62 is a relatively tolerant, while ICCV-2 is a susceptible genotype of chickpea.18 Further, we had developed dehydration-responsive ECM proteome of c.v. JG-62 and identified many candidate protein putatively involved in dehydration tolerance.18 In this study, we have developed dehydration-responsive ECM proteome of c.v. ICCV-2 and compared with that of JG-62 to unravel the underlying mechanism(s) involved in their differential response to dehydration. The critical analysis of the proteome of c.v. ICCV-2 revealed 118 differentially expressed proteins and 81 of those were identified using two-dimensional gel electrophoresis (2-DE) coupled with LCESIMS/MS. The comparison between the proteomes of c.v. ICCV-2 and JG-62 revealed common as well as genotype-specific proteins, suggesting their role in differential response to dehydration. In addition, the reversible and irreversible changes in ECM proteomes revealed their differing ability to recover from dehydration-induced damage. These findings would not only increase our understanding of the mechanism(s) of dehydration tolerance in plants, but also facilitate the targeted manipulation of ECM proteins in crop improvement program.

’ EXPERIMENTAL SECTION Plant Material, Growth Condition and Dehydration

Seeds of chickpea (Cicer arietinum L. c.v. ICCV-2 and JG-62) were obtained from International Crops Research Institute for

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the Semi-Arid Tropics, (ICRISAT, India) and multiplied. The seedlings were grown in pots containing a mixture of soil and soilrite (2:1, w/w) in an environmentally controlled growth room. The seedlings were maintained at 25 ( 2 °C, 50 ( 5% relative humidity under 16 h photoperiod (270 μmol m2 s1 light intensity). The dehydration treatment was given to 3-weekold seedlings as previously described.18 The tissues were harvested at every 24 h up to 192 h. Furthermore, pots containing 192 h dehydrated seedlings were rewatered and allowed recovery for 24 h (R24) and tissues were harvested. The harvested tissues were instantly frozen in liquid nitrogen and stored at 80 °C until further use. Evaluation of Purity of ECM Fraction

The ECM fraction was isolated from unstressed and stressed seedlings, and purified as described earlier.12 An aliquot of the purified ECM fraction was fixed with Karnovsky’s fixative [2% (v/v) paraformaldehyde/2.5% (v/v) glutaraldehyde] overnight at 4 °C. It was then washed in 0.1 M phosphate buffer and treated with 1% osmium tetroxide. The fraction was dehydrated sequentially in acetone and embedded in epoxy resin. Ultrathin sections (70 nm) were made and stained for 10 min, each with uranyl acetate and lead citrate consecutively, and examined by transmission electron micrography (Morgagni 268D). The proteins were extracted by suspending the purified ECM fraction in three volumes (w/v) of extraction buffer [200 mM CaCl2, 5 mM DTT, 1 mM PMSF, 0.3% (w/w) PVPP] on a shaking platform for 45 min at 4 °C. Proteins were separated from the insoluble fraction by centrifugation (10,000g) for 10 min at 4 °C and filtered through 0.45 μm filter. The filtrate was concentrated using Centricon YM3 and then dialyzed overnight against 1000 volumes of deionized water with one change. The protein concentration was determined by Bradford assay (Bio-Rad, Berkeley, CA). The catalase and vanadate inhibited Hþ ATPase activities were determined as described.12 The catalase enzyme assay was performed using 10 μg of proteins. The reaction mixture was prepared by adding 50 μL of protein extract to 940 μL of 70 mM KPO4 buffer (pH 7.5). Reaction was started by addition of 10 μL of H2O2 (3% v/v) and the decrease in absorbance at 240 nm was monitored for 5 min. Baseline correction was done by subtracting the absorbance taken without addition of H2O2. The vanadate inhibited Hþ ATPase activity was determined with 20 μg of protein in 120 μL of assay buffer. The assay was performed in presence and absence of 0.1 mM orthovanadate, freshly prepared and boiled in buffer prior to addition of 0.05% triton X-100. The assay was performed in presence of a detergent to expose all hidden sites for the cell wall bound plasma membrane, if any. The reaction was initiated by addition of ATP and was incubated at 37 °C for 30 min. Blanks lacking MgSO4 were examined in parallel and the released inorganic phosphate was determined. The relative activity of the enzyme was calculated by taking the difference between the absorbance at 700 nm in absence and presence of orthovanadate. 2-D Electrophoresis of ECM Proteins

Isoelectric focusing was carried out with 125 μg of protein in 250 μL 2-D rehydration buffer [8 M urea, 2 M thiourea, 4% (w/v) CHAPS, 20 mM DTT, 0.5% (v/v) Pharmalyte (pH 47), and 0.05% (w/v) bromophenol blue]. The proteins were resolved onto 13 cm IEF strips in the pI range of 47 as described earlier.12 Electrofocusing was performed using IPGphor system (GE Healthcare) at 20 °C for 30 000 VhT. The focused strips were subjected to reduction with 1% (w/v) DTT in 10 mL of 2028

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Journal of Proteome Research equilibration buffer [6 M urea, 50 mM Tris-HCl (pH 8.8), 30% (v/v) glycerol and 2% (w/v) SDS], followed by alkylation with 2.5% (w/v) iodoacetamide in the same buffer. The strips were then loaded on top of 12.5% polyacrylamide gels for SDS-PAGE. The electrophoresed proteins were stained with silver stain plus kit (Bio-Rad, Berkeley, CA). Image Acquisition and in silico Analysis

Gel images were captured with a Bio-Rad FluorS equipped with a 12-bit camera. The PDQuest version 7.2.0 (Bio-Rad, USA) was used to assemble first level matchset (master image) from three replicate 2-DE gels. Experimental molecular mass and pI were calculated from digitized 2-DE images using standard molecular mass marker proteins. Each spot assembled on the standard gel met several criteria: it was present in at least two of the three gels and was qualitatively consistent in size and shape in the replicate gels. We defined “lowquality” spots as those with a quality score less than 30 and these spots were eliminated from further analysis. The remaining “high-quality” spot quantities were used to calculate the mean value for a given spot. The spot densities on the first level matchset were normalized against the total density in the gel image. The replicate gels used for making the first level matchset had, at least, correlation coefficient value of 0.8. A second level matchset was obtained that allowed a comparison of the standard gels from each of the time points. The second normalization was done with a set of three unaltered spots identified from across the time points. From this matchset, the filtered spot quantities were assembled into a data matrix of “high-quality” spots from all the time points for further analysis. Protein Identification by LCESIMS/MS and Database Search

The protein spots were excised from 2-DE gels, destained and trypsin-digested and the peptides were extracted according to standard techniques.19 Peptides were analyzed by electrospray ionization time-of-flight mass spectrometry (LCESIMS/TOF) using an Agilent 1100 Series HPLC system (Agilent Technologies, San Diego, CA) coupled to a Q-STAR Pulsar imass spectrometer (Applied Biosystems, Foster City, CA). The peptides were loaded onto a Zorbax SB-C18 column (length- 15 cm, diameter- 2.1 mm, particle size- 5 μ; Agilent Technologies, USA) and separated with a linear gradient of 2% (v/v) acetonitrile, 0.1% (v/v) formic acid to 80% (v/v) acetonitrile, 0.1% (v/v) formic acid. The MS/MS data were extracted using Analyst Software v.1.4.1 (Applied Biosystems, Foster City, CA). Peptides were identified by searching the peak-list against the MSDB 20050929 (2344227 sequences; 779380795 residues) database using the Mascot v.2.1 (www.matrixscience.com) search engine. Since the chickpea genome sequence is not known, a homology based search was performed. The database search parameters were: taxonomy; Viridiplantae (green plants; 195697 sequences); peptide tolerance, (1.2 Da; fragment mass tolerance, (0.6 Da; maximum allowed missed cleavage, 1; and instrument type, ESI-QUAD-TOF. Protein scores, the sum of a series of peptide scores, were derived from ion scores as a nonprobabilistic basis for ranking protein hits. The score threshold to achieve p < 0.05 is set by Mascot algorithm and is based on the size of the database used in the search. The details regarding the precursor ion mass, expected molecular weight, theoretical molecular weight, delta, score, rank, charge, number of missed cleavages, p value and the peptide sequence and spectra of proteins identified with a single peptide are mentioned in Supporting Information Document 1. Bioinformatics Analysis

The presence of signal peptide in the identified DRPs was predicted using the following programs: SignalP 3.0 (which

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contains two different algorithms, SignalP-NN and SignalP-HMM; http://www.cbs.dtu.dk/services/SignalP), iPSORT (http://ipsort. hgc.jp/) and Signal-3L (http://www.csbio.sjtu.edu.cn/bioinf/ Signal-3L/). SecretomeP 2.0 (http://www.cbs.dtu.dk/services/ SecretomeP/) was used for the prediction of nonclassical protein secretion. The coexpression pattern of the identified DRPs was determined by SOTA (self-organizing tree algorithm) clustering. The fold expression values across all the time points were log transformed and the clustering was carried out by using Multi Experiment Viewer (MEV) software (The Institute for Genomic Research, TIGR). The clustering was done with the Pearson correlation as distance with 10 cycles and a maximum cell diversity of 0.8.20 Determination of Antioxidants

The ECM fraction was suspended and homogenized in 100 mM Triethanolamine (TEA, pH 7.4) for superoxide dismutase (SOD) and 50 mM of KPO4-buffer (pH 7.0) for ascorbate peroxidase (APx), respectively. The homogenate was centrifuged at 16 000 g for 20 min at 4 °C. The supernatant was transferred into fresh tube and used for the assays. SOD activity was determined by spectrophotometric method based on the inhibition of superoxide-driven NADH oxidation.21 The assay mixture contained 100 mM TEA (pH 7.4), 100 mM/50 mM EDTA/MnCl2, 7.5 mM NADH and 10 mM mercaptoethanol in a total volume of 1.0 mL. The oxidation of NADH was followed at 340 nm (an absorbance coefficient of 6.2 mM1 cm1). The oxidation rates were initially low, then increased progressively (usually 24 min after mercaptoethanol addition) to yield a linear kinetics (1215 min), which were used for calculation. The activity of APx was assayed from the decrease in absorbance at 290 nm (an absorbance coefficient of 2.8 mM1 cm1) as ascorbate is oxidized by the enzyme activity.22 The reaction mixture for the peroxidase contained 50 mM KPO4 (pH 7.0), 0.5 mM ascorbate, and 0.1 mM H2O2 in a total volume of 1.0 mL. The reaction was initiated by adding H2O2, and the absorbance was recorded 30 s after the addition. Correction was done for the low, nonenzymatic oxidation of ascorbate by H2O2. Determination of Net Photosynthesis

The photosynthetic rate of the seedlings was determined with a portable photosynthesis measurement system, GFS3000 (Waltz, Germany). The net photosynthetic capability of plants on the basis of single leaf measurement from 57 different leaves per plant was recorded under standard atmospheric (360 ppm CO2) and light condition (750 μmol m2 s1).

’ RESULTS AND DISCUSSION Isolation and Purification of ECM

The ECM fraction was isolated by mechanical disruption and differential centrifugation, and examined by transmission electron microscopy. The electron-micrograph showed that the ECM fraction was free of other ultrastructural cytoplasmic organelles and there were no intact cells which had escaped breakage during homogenization (Figure 1A). The enrichment of the ECM proteins was evaluated by assaying catalase and vanadate inhibited Hþ ATPase activities that could possibly contaminate the ECM preparation. Catalase was used as a marker enzyme for cytosol and vanadate inhibited Hþ ATPase for the plasma membrane.12 The crude cell extracts showed high catalase and ATPase activities, whereas the ECM fraction did not show any significant activities of these enzymes (Figure 1B, 2029


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Figure 1. Analysis of ECM fraction and enrichment of ECM proteins. (A) Electron micrograph showing the purified ECM fraction. (B) Determination of catalase-specific activity and (C) vanadate inhibited Hþ ATPase activity in crude extract and purified ECM fraction.

C). These results altogether demonstrated the enrichment of the ECM fraction and that the proteins had no detectable cytosolic and plasma membrane contaminations. Differential Display of Dehydration-Responsive ECM Proteins in c.v. ICCV-2

The ECM proteins are known to be involved in a broad range of developmental events and metabolic processes and most notably, in response to array of environmental cues. In a previous study, we had developed the ECM-specific dehydration-responsive proteome of a tolerant c.v. JG-62,18 while in this study we developed a comprehensive dehydration-responsive proteome in ICCV-2. The temporal changes in the ECM proteome of c.v. ICCV-2 were monitored under progressive dehydration (0192 h) followed by a rehydration stage (R24). There were two biological and three technical replicates of protein extraction for each time point and, at least, three gels were used to generate a representative standard gel, hereafter referred to as the first-level matchset (Figure 2A,B). To make the higher level matchset, only those protein spots were considered, which passed several stringent criteria. A total of 326 spots were detected at unstressed condition, out of which 298 were classified as “high quality” spots. To overcome the experimental errors possibly introduced due to differential staining, a normalization of the spot densities was performed against the total density present in the respective gel. Further, normalization was done against the densities of unaltered

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protein spots. The higher level matchset contained a total of 504 unique spots (Figure 3A). Nearly, 92% of those protein spots were of high quality, reflecting the reproducibility of the experimental replicates (Table 1). The dehydration-responsive proteome revealed 118 protein spots that changed their intensities by more than 2-fold, at least, at one time point. Out of these, 96 dehydrationresponsive proteins (DRPs) were subjected to MS/MS analysis that led to the identification of 81 proteins with significant match, yielding identification success rate of 84%. The protein spots are marked by arrow (Figure 3A) and designated as CaSE, where Ca refers to Cicer arietinum and SE denotes susceptible ECM, while the accompanying numerals indicate the spot number. Four typical gel regions indicated by box in Figure 3A are enlarged as shown in Figure 3B, displaying differential expression of the proteins. The DRPs listed in Table 2 were functionally classified into various categories, based on their putative functions (Figure 4). The functional classes include metabolism (32%), cell defense and rescue (22%), cell wall modification (15%), and signaling (9%), among others. About 30% of the DRPs were found to be redundant, possibly representing the isoforms/members of multigenic families, with a change in pI and/or molecular weight. The expression pattern of some of these such as aldolase (CaSE-34, 47, 48, and 589), beta amylase (CaSE-322, 351, and 647), enolase (CaSE-49, 119, 404, 586, 604, 607, and 630), leucine aminopeptidase (CaSE516, 600, and 817), ferritin (CaSE-42, 87a, 87b, and 90b), and alpha glucosidase (CaSE-565 and 567) are shown in Figure 5. The identification of isoforms suggests the possible dehydration-induced posttranslational modification(s) of the candidate proteins. It is expected that as genome resources of chickpea will improve, the high-resolution 2-DE maps can be used as a predictive tool to search for unexpected isoelectric species to unravel possible posttranslational regulation. Cell wall assembly, deposition, reorganization and selective disassembly require the activities of a complex battery of cell wall localized enzymes including polysaccharide hydrolases, and other proteins. Proteins belonging to “cell wall modifying” include alpha glucosidase (CaSE-565 and 567), methionine synthase (CaSE-455 and 883) and methyl transferase (CaSE-77, 398, 888, and 925). Alpha glucosidase may play a role in suberin or cutin synthesis.23 The cumulative function of methionine synthases and methyl transferases is to provide activated methyl groups, thereby catalyzing the key steps in the biosynthesis of lignin monomers and thus, playing a crucial role in strengthening the cell wall components and maintaining its integrity. The class “metabolism” was found to be the most abundant. In this category, we identified many proteins such as glyceraldehyde3-phosphate dehydrogenase (GAPDH; CaSE-511 and 536), aldolase (CaSE-34, 47, 48 and 589), enolase (CaSE-49, 119, 404, 586, 604, 607, and 630), NADPH-dependent mannose 6-phosphate (CaSE-483), 6-phosphogluconate dehydrogenase (CaSE-90a), beta amylase (CaSE-322, 351 and 647) and citrate synthase (CaSE-886). Many of these proteins are reported to be present in the cell wall of different organisms as well as in different organelles. It is increasingly evident that proteins can be located in more than one cellular compartment. For example, citrate synthase is an enzyme classically located in the mitochondrion and in peroxisomes or glyoxysomes and also reported to be present in the cell wall.24 The proteins associated with “signaling” act as a surveillance system engaged in efficient signaling cascade to allow the early detection of any impending adverse environmental conditions. The proteins in this group include villin (CaSE-142), 14-3-3-like protein (CaSE-255), GDP dissociation inhibitor (GDI, CaSE-407), 2030



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Figure 2. Dehydration-responsive ECM proteome of the susceptible c.v. ICCV-2 and the representative 2-DE gels. Three-week-old seedlings were subjected to dehydration (0192 h) and then were rehydrated and allowed to recover for 24 h. The ECM proteins were isolated from the seedlings at every 24 h for 192 h of dehydration followed by a rehydrated stage (R24). An equal amount (125 μg) of protein from each time point was resolved by 2-DE and gels were silver stained. Three replicate gels (selected from, at least, two biological and three technical replicates) for each time point (A) were computationally integrated into the “standard gel” (B). U represents the unstressed condition.

Table 1. Reproducibility of 2-Dimensional Gels at Various Treatment Time Points in c.v. ICCV-2 average no of spotsa

high quality spotsb

reproducibility (%)

0

326

298

91.4

48

367

342

93.1

72 96

341 331

320 302

93.84 91.2

120

251

235

93.62

192

245

221

90.20

Recovery

268

241

89.99

Total

2129

1959

92.01

time (h)

a

Average number of spots present in three replicate gels of each time point. b Spots having quality score more than 30 assigned by PDQuest (Ver.7.2.0).

Figure 3. Higher level matchset of the DRPs and temporal changes of few of the representative candidates. The higher level matchset (3A) was created from the “standard gels” for each of the time points as represented in Figure 2B. The identified spots were marked by arrows, and the numbers correspond to the spot Ids mentioned in Table 2. The magnified gel sections (3B) correspond to the framed regions (ad) in (A). U represents the unstressed condition.

translation initiation factor eIF-5A (CaSE-838), and elongation factor EF-2 (CaSE-486 and 518). The “cell defense and rescue” contained several interesting candidates, for example, the heat shock proteins

(GroEL, CaSE-627 and Hsp902-like, CaSE-659), which were previously thought to be restricted to the cell interior. This is not unprecedented since their presence has earlier been reported in the cell walls of Candida albicans, yeast, and barley.25,26 The iron storage protein, ferritin (CaSE-42, 87a, 87b and 90b) is known to sequester the highly reactive Fe3þ and prevent the formation of toxic OH• species, and its presence in the ECM is consistent with our earlier findings in c.v. JG-62.18 ECM peroxidases, apart from being wellknown ROS-metabolizing enzymes, are believed to play a role in cross-linking polysaccharides at the cessation of expansion to rigidify the wall. Lignification requires H2O2, which may be provided by coupled reactions involving cell wall bound peroxidase and malate dehydrogenase (MD, CaSE-21 and 144).27 Several of the proteins identified could not be classified into any of the larger functional categories and were placed in the group “miscellaneous”. This includes HAD-superfamily hydrolase (CaSE256 and 653), LET1 like protein (CaSE-413) and tetratricopeptidelike helical (CaSE-704), among others. The proteins with “no known function” were grouped as “unknown”, accounting 4% of the identified proteins. Analysis of the Secretory Nature of the DRPs

Secreted proteins are generally known to contain a cleavable signal peptide at their N-terminus. To identify such signal peptide in the identified DRPs, we used SignalP-NN, SignalP-HMM, iPSORT and Signal-3L programs. The proteins that displayed positive output 2031



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Table 2. List of Dehydration-Responsive ECM Proteins in c.v. ICCV-2 Identified by LCESIMS/MS

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Table 2. Continued

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Table 2. Continued

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Table 2. Continued

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Table 2. Continued

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Table 2. Continued

a

Spot number as marked on the ECM proteome (Figure 3A). The spot numbers were designated as CaSE, where Ca indicates the organism (Cicer arietinum), SE denotes the Suceptible ECM fraction. b Normalized log transformed expression values of the DRPs across all the time points. c Gene identification number as in GenBank. d NP indicates the number of identified peptides. 2037



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Figure 4. Functional classification of the DRPs of c.v. ICCV-2. The putative functions were assigned to each of the DRPs using Pfam and InterPro databases and the functional categories are represented in the form of pie chart.

Figure 5. Relative abundance of few of the redundant DRPs. The expression profiles of the following proteins are represented in the form of a histogram: (A) aldolase, (B) beta amylase, (C) enolase, (D) leucine aminopeptidase, (E) ferritin, and (F) alpha glucosidase. The y-axis represents the fold change in expression of the protein across all the time points; the time zero bars are all 1 unit. The background value averaged across the replicates for a time point was used to calculate the fold changes. U represents the unstressed condition.

in, at least, two of the above-mentioned programs were considered to be the secreted proteins. Nevertheless, the proteins

that do not contain signal peptide can also be secreted into the ECM and are classified as nonclassical or leaderless secretory 2038



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Figure 6. Expression clustering of the identified DRPs in the ECM of c.v. ICCV-2. Based on the expression profile, 81 differentially expressed proteins grouped into 11 clusters. The SOTA cluster tree is shown at the top, and the expression profiles are shown below. In each cluster, the expression profile of individual protein is represented by gray lines, while the mean expression profile is indicated by pink line. The number of proteins in each cluster is given in the left upper corner, and the cluster number is given in the right lower corner. Detailed information on proteins within each cluster can be found in Supporting Information Figure 1. U represents the unstressed condition.

proteins.28 Therefore, SecretomeP was used to predict the nonclassical secretory proteins. Taken together, the analysis revealed 16 classically secreted proteins and 25 nonclassical secretory proteins (considering nonredundant GenBank Accession No.), thus accounting for two-third of the identified proteins (Supporting Information Table 1). The DRPs that neither displayed signal peptide nor predicted as nonclassical secretory proteins could still be bona fide ECM proteins since the protein prediction process currently available has limitations, more so, for distinguishing members of multiprotein families having different cellular localizations. For instance, the 14-3-3 protein identified in this study, though earlier thought to be cytosolic or intracellular compartment-localized, was shown to be constituents of the insoluble glycoprotein framework of the Chlamydomonas cell wall.29 Another such DRP is carbonic anhydrase, which has been shown by immunogold localization to be in the cell wall of soybean.30 The presence of glycolytic enzymes in the ECM is not unprecedented because seven of the enzymes involved in carbon metabolism were shown by immunochemical studies to be present in the secondary cell

wall of pea.31 Interestingly, two of them, GAPDH and fructose bisphosphate aldolase have been identified in this study. Several other identified DRPs but not predicted to be secretory have been reported in earlier cell wall proteomics studies, such as elongation factor EF-2,32 citrate synthase,24 quinone oxidoreductase,11 HSP-9033 and glyoxalase-1.6 It may be noted that though the list includes candidates whose localization in the ECM is surprising, the evidence that several cytosolic proteins called ‘moonlighting proteins’ perform a second function outside the cell, is gaining credence from an increasing number of studies.34,35 Expression Clustering of DRPs in c.v. ICCV-2

The use of cluster analysis allows integration of expression characteristics of multiple proteins in a time-dependent manner that eventually permits to decipher various regulatory pathways operative at various stages. In order to achieve a comprehensive overview of the dynamics and the coordinated regulation of the dehydration-responsive protein network in terms of expression profile, SOTA clustering was performed. To develop the 2039


Journal of Proteome Research clusterogram, the data were taken in terms of fold expression of the proteins against their values at unstressed condition. The analysis was performed by transforming data sets into log transformed to the base two to level the scale of expression and to reduce the noise. The clusters with n > 4 (n indicates the number of identified proteins) were taken to study the coexpression patterns. The clusterogram yielded 11 expression clusters (Figure 6). Detailed information on proteins within each cluster is shown in Supporting Information Figure 1. The most abundant clusters 1, 2, 4, 7, and 11 contained proteins that were found to be early dehydration-responsive. The cluster 11 comprised maximum number of DRPs, most of which belong to “cell defense and rescue” followed by “metabolism” and “signaling”. A mixed pattern of expression was observed in this cluster. In cluster 4, all the proteins were found to be upregulated during early dehydration while in cluster 7, most of the proteins were downregulated. Proteins involved in signaling, cell wall modification and metabolism displayed a diverse and complex pattern of regulation wherein no clear expression pattern was noticed. The cellular defense response seems to be dependent on the advancement of dehydration and thus both early and late responses could be observed in the clusterogram. Also, the miscellaneous class of proteins showed no clear clustering patterns, which may be attributed to its heterogeneous composition. However, coexpression patterns were observed for proteins with unidentified function as exemplified in cluster 1 and 4. This is interesting as it may provide valuable insight into their putative function based on the kinetics of dehydration response. Comparative Analysis of Dehydration-Responsive ECM Proteome of c.v. ICCV-2 and JG-62

Proteomics information not only enhance our understanding of the physiological and molecular mechanisms underlying stress response but also, guide the identification of candidate proteins, essential for successful, knowledge-based crop improvement. In recent years, there have been an increasing number of reports on stress-responsive proteome in several of the crop species. Nevertheless, comparative proteomics in crop species is rare, possibly because it is difficult due to the difference in genotypes, organs and tissues, developmental stages, stress conditions and duration used in such studies. Our study circumvents these anomalies and therefore, would provide a basis for unambiguous comparison of dehydration-responsive ECM proteomes of two contrasting chickpea genotypes. It is interesting to note that although the proteome map of c.v. ICCV-2 and JG-62 showed 326 and 271 protein spots respectively, the number of DRPs were found to be much higher in JG-62. The comparative analysis of the proteomes of c.v. ICCV-2 and JG-62 under unstressed condition revealed that only 50% of the protein spots were common (Figure 7). The identified proteins that are common in both the genotypes are enlisted in Supporting Information Table 2. These data suggest that the subtle changes in the genome might lead to significantly distinct proteome, contributing toward their specific response to stress. Interdependence of the ECM, plasma membrane and cytoskeletal network is one of the most characteristic features of cellular mechanism that allows cells to respond effectively to various signals. In this interacting system, ECM serves as a repository for the extracellular domains for plasma membrane proteins and various signaling molecules. Proteins involved in cell signaling such as calmodulin like protein, calcium-dependent protein kinase, tubby-like protein (TULP), Ras super family

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Figure 7. Comparison of ECM proteome of c.v. ICCV-2 and JG-62 under unstressed condition. ECM proteome of the susceptible c.v. ICCV-2 under unstressed condition was compared with that of JG-62, the tolerant genotype. The genotype-specific and overlapping profile of the protein spots are indicated in the Venn diagram. The areas in the diagram are not proportional to the number of proteins in the groups.

GTP binding protein, and receptor-like protein kinases were identified in c.v. JG-6212 whereas they could not be detected in ICCV-2. Ras super family GTP binding protein serves as key regulators of extracellular-stimulus-mediated signaling networks.36 Receptor-like protein kinases have been proposed to regulate the plasma membrane-cell wall interface. They also act as linkers between the cell wall and the cytoskeleton37 and transduce the extracellular signal to the cell interior for inducing downstream cascade. Proteins involved in cell defense and rescue such as glutathione transferase and thioredoxin reductase, as well as proteins involved in cell wall modification like glycosyl transferases were also identified in c.v. JG-62, but not in ICCV2. Presence of ROS-catabolising enzymes under unstressed condition in c.v. JG-62 reaffirms its ability to respond to dehydration efficiently than ICCV-2. Altogether these data suggest the preponderance of stress-inducible signaling components in the tolerant genotype even under unstressed condition. However, it cannot be ruled out that many of these ECMassociated proteins could not be identified in c.v. ICCV-2, possibly due to their low expression level. The comparison of dehydration-responsive ECM proteome revealed that the number of DRPs observed in c.v. JG-62 was 163 as compared to 118 in ICCV-2. The DRPs found to be common in both the genotypes are enlisted in Supporting Information Table 3 and the expression pattern of some of these are represented as zoom images in Figure 8. The expression profile of the common DRPs is presented as heat map in Supporting Information Figure 2. The comparison of different functional classes of DRPs in these genotypes showed a significant variation, indicating their differential response to dehydration (Figure 9). 2040



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Figure 8. Temporal changes of few of the common DRPs in c.v. ICCV-2 and JG-62. The changes in the expression profile of few of the common DRPs across all time points are represented in magnified gel sections (AF). U represents the unstressed condition.

Figure 9. Comparison of various functional classes of DRPs in c.v. ICCV-2 and JG-62. The percentage of the identified DRPs categorized to different functional classes, such as GRPs, glycine rich proteins; CWM, cell wall modifying; CDR, cell defense and rescue; SIG, signaling; MET, metabolism; MIS, miscellaneous; and UNK, unknown function, were analyzed for both of the genotypes.

In the “signaling” class, the DRPs identified exclusively in c.v. ICCV-2 were villin (CaSE-142), elongation factor EF-2 (CaSE486 and 518), GDI-2 (CaSE-407) and 14-3-3 like protein (CaSE255), whereas those identified only in JG-62 were wall associated kinase (WAK), Chitinase-specific receptor kinase (CHRK1), TULP, and protein kinases,18 among others. Villin like proteins are known to bind with actin and participate in remodeling of cytoskeleton network in response to various stimuli,38,39 possibly

via Ca2þ-dependent signaling cascades. Villin was found to be downregulated in c.v. ICCV-2. Interestingly, the translation initiation factor, eIF-5A (CaSE-838) showed downregulation in c.v. ICCV-2 in response to progressive dehydration whereas it was found to be upregulated in JG-62. It is proposed to function as a bimodular protein capable of binding to both RNA and proteins, thus involved in multiple aspects of cellular signaling.40 Further, eIF-5A3 has been implicated to play a regulatory role in response to sublethal stress. Its overexpression was shown to influence growth and enhance tolerance to osmotic and nutrient stress.41 Therefore downregulation of eIF-5A may render susceptibility to c.v. ICCV-2. GDI, known to confer resistance to Al stress42 was found to be downregulated in c.v. ICCV-2. The 14-33 like protein was also downregulated in this genotype. The members of this family can act as sugar sensors, transcription factors, and are reported to be involved in the stabilization of many protein complexes.43 Nucleoside diphosphate kinase (NDK) is known to catalyze the transfer of γ-phosphate from ATP to NDP, thereby playing a key role in maintaining nucleotide homeostasis as well as in GTP-mediated signal transduction.44 NDKs are known to involve in plant growth, phytochrome A response, UVB signaling, heat stress, and oxidative stress.45,46 Surprisingly, NDK was found to be downregulated in both the genotypes. The WAKs are attractive candidates among the emerging linkers of the cell wall with cytoskeleton as they have, in addition to cell wall and transmembrane domains, a cytoplasmic Ser/Thr protein kinase domain. Besides cell wall pectins, WAKs are also known to bind to glycine rich proteins (GRPs) and protein phosphatases forming a signalosome complex.37 The GRPs 2041


Journal of Proteome Research constitute a novel class of proteins, which play pleiotropic roles in osmotic and biotic stresses.47 While WAKs and several members of the GRPs were found in c.v. JG-62, none could be detected in ICCV-2. Moreover, WAKs showed initial downregulation up to 48 h followed by upregulation in the later stages of dehydration, while most GRPs showed upregulation.18 The nonrepresentation of major signaling proteins and the GRPs in the ECM of c.v. ICCV-2 may attribute its susceptibility to dehydration. Cell wall modification and accumulation of compatible solute is a characteristic phenomenon involved in the mechanism of dehydration tolerance. Among the “cell wall modifying” class, those identified only in c.v. ICCV-2 were alpha glucosidase (CaSE-565 and 567), UDP-glucose dehydrogenase (UGDH, CaSE-567), galactosidase I (CaSE-949) and germin like protein (GLP, CaSE-939). The DRPs found to be common in both the genotypes included glucan endo-1,3-beta-D-glucosidase (CaSE45), methionine synthase and methyl transferase (CaSE-398, 445, 777, 883, 888, and 925). Alpha glucosidase I catalyzes the first step in N-linked glycan processing during the synthesis of cellulose, the principal component of cell wall. The lack of activity of this enzyme has been shown to cause a reduction in cellulose content,48 indicating reduced cell wall metabolism under dehydration. UGDH converts UDP-glucose to UDPglucuronate, which is a precursor for hemicellulose and pectin, the components of newly formed cell walls.49,50 UDP-glucose is not only a necessary metabolite for cell wall biogenesis, but is also involved in the synthesis of the carbohydrate moiety of glycolipids and glycoproteins. Thus, downregulated activity of both the proteins in c.v. ICCV-2 might be attributed toward the weakening of cell wall under dehydration. The GLPs display oxalate oxidase activity and produce H2O2, which is utilized by peroxidases in cross-linking reaction,51 suggesting its key role in cell wall remodeling. The GLPs were shown to be downregulated during flooding stress,52 while in this study were found to be upregulated in early stage of dehydration. The differential expression of methionine synthases and methyl transferases in both the genotypes indicates an alternate mechanism to avoid water loss under dehydration via cell wall lignifications.18 In c.v. ICCV-2, methionine synthase at spot 925 was upregulated, but at spot 455 was downregulated. It is likely that the upregulated protein could be a dehydration-induced degraded product as its experimental molecular mass was less than the theoretical molecular mass. The class “cell defense and rescue” accounted for 22% of the DRPs in both the genotypes, but in c.v. JG-62, it represented the most abundant class. In c.v. ICCV-2, the proteins belonging to this class were ferredoxin dependent glutamate synthase (CaSE549), ferritin 3 precursor (CaSE-42, 87a, 87b, and 90b), aldehyde dehydrogenase (CaSE-26), neutral leucine amino peptidase (CaSE-817), and thioredoxin peroxidase (CaSE-161). Furthermore, thioredoxin peroxidase, a component of thioredoxin system involved in reducing peroxides,53 was found to be downregulated. While the ROS-catabolizing enzymes viz. ascorbate peroxidase (APx) and thioredoxin could not be detected in c.v. ICCV-2, they were not only present, but showed upregulated expression upon dehydration in JG-62. Glyoxalase-1, a related DRP showed mixed pattern of expression in both the genotypes. It helps in maintenance of the redox balance via keeping a higher ratio of reduced to oxidized glutathione.54 The nondetectable level of expression of major ROS-catabolizing enzymes in c.v. ICCV-2 emphasizes their reduced ability to counteract dehydration-induced cellular damage.

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Figure 10. Comparative analysis of reversible and irreversible changes in the ECM proteome of c.v. ICCV-2 and JG-62. The dehydrationinduced reversible and irreversible changes in the ECM proteomes were analyzed on the basis of percent recovery of the DRPs belonging to various functional classes upon rehydration. GRPs, glycine rich proteins; CWM, cell wall modifying; CDR, cell defense and rescue; SIG, signaling; MET, metabolism; MIS, miscellaneous; and UNK, unknown function.

Another interesting DRP that was not detected in c.v. ICCV-2, but showed dehydration-induced upregulation in JG-62 was mannose lectin. The increase in the activity of cell wall lectins is implicated as a compensatory mechanism, which stabilizes the cytoskeleton structure in conditions tending to disrupt it.55 Glutamate synthase was found to be upregulated in c.v. JG-62, but downregulated in c.v. ICCV-2 upon dehydration. It regulates the accumulation of proline in osmotically stressed plants.56 Moreover, glutamate synthase has been shown to be involved in the sequential pathways of lignin biosynthesis.57 Similarly, MD was upregulated in c.v. JG-62 whereas showed downregulation in ICCV2. The final step in lignification process is initiated by peroxidasedependent formation of phenoxy radicals and MD was shown to produce sufficient amount of NADH to allow subsequent formation of H2O2 required for the process by peroxidases.58 The class “metabolism” contained the highest number of DRPs (32%) in c.v. ICCV-2 as against 8% in JG-62. Although, most of the DRPs categorized in this class have been reported from the cell wall of different organisms, no definitive role for these proteins has been assigned to dehydration response. Nevertheless, some members in this class are known to protect the plants via maintaining the osmolyte concentration under stress. These results suggest that the DRPs associated with metabolism may utilize the cell wall polysaccharides as reservoir to produce sugar monomers to maintain the osmotic adjustment in plants under dehydration.18 Reversible and Irreversible Effect of Dehydration on ECM Proteome

It is understood that the cellular activities in plants are restricted upon dehydration, especially for short duration of treatment, which might revert back following rehydration depending on their adaptive capability. In order to understand the reversible and irreversible effects of dehydration, the chickpea seedlings dehydrated for a period of 192 h were rewatered and allowed to recover for 24 h (R24). A comparison was made between the ECM proteome upon rehydration in both genotypes. We observed that 65% of the identified proteins were upregulated in c.v. JG-62, while 41% in ICCV-2 upon dehydration. Conversely, the downregulated proteins were 35% in c.v. 2042



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Figure 11. Determination of the antioxidants activity, total peroxide, and net photosynthetic rate. The antioxidants viz., (A) SOD and (B) APx were assayed as described in the Experimental Section. Enzyme activities were expressed in terms of fold change against the various time points studied. (C) Total peroxide and (D) in planta photosynthetic rate were measured in both the genotypes and plotted against the treatment time points. The experiments were done in triplicates (n = 3), and average mean values are shown. U represents the unstressed condition.

JG-62 and 59% in ICCV-2. Significantly, the rehydration-induced recovered expression of downregulated proteins was 64% in c.v. JG-62 while 31% in ICCV-2. It is likely that the tolerant genotype might possess an effective recovery mechanism that responded rapidly by activating various cellular machineries. However, the recovery of dehydration-induced upregulated proteins (as evaluated by their reverting to basal expression level) was around 30% in both the genotypes, suggesting that these proteins may be required for maintenance of basic structural and physiological integrity. To obtain a comprehensive overview of the mechanisms underlying the response to dehydration and rehydration, the recovery pattern of the DRPs belonging to various functional classes were compared (Figure 10). The “GRPs” was found to be the most prominent class displaying 75% recovery in c.v. JG-62, while none of its member was identified in ICCV-2. The observed expression profile of the “GRPs” was found to be similar to that reported earlier in resurrection plant.59 The GRPs are known to play a key role in cell wall maintenance and repair under stress condition. The rehydration-induced recovery of the DRPs involved in cell defense and rescue was 17% in c.v. JG-62 and 11% in ICCV-2. The members of this class are known to involve in late dehydration response and protect the cellular system against detrimental effects of dehydration. Thus, the low rate of recovery of these proteins in c.v. ICCV-2 may indicate its inefficiency in recovery from dehydration-induced damage. Intriguingly, the “signaling” DRPs showed recovery of 14% in c.v. JG-62 and 29% in ICCV-2. It may be mentioned here that most of the potential signaling components observed in c.v. JG-62 could not be detected in ICCV-2. Moreover, most “signaling” DRPs were upregulated in c.v. JG-62 and downregulated in ICCV-2. These results altogether suggest that there might be a higher degree of damage in the susceptible genotype wherein dehydrationresponsive events are irreversibly affected to a greater extent as against the tolerant genotype.

Determination of Activity of Antioxidants and Photosynthetic Rate

The critical analysis of the dehydration-responsive ECM proteome did not reveal the presence of major ROS-catabolizing enzymes in c.v. ICCV-2. The major ROS include superoxide, hydrogen peroxide (H2O2) and hydroxyl radicals and their concentrations are known to increase during dehydration.60,61 The SOD acts as a first-line of defense against ROS by dismutating superoxide to H2O2,62 which is subsequently detoxified by APx. Therefore, we investigated the activities of SOD and APx in the ECM of both the genotypes under dehydration. While there was approximately 2-fold increase in their activity in c.v. JG-62 at 72 h of dehydration, ICCV-2 did not show any increase (Figure 11A,B). The increased activity of the antioxidants in c.v. JG-62 is indicative of a compensatory mechanism of defense in response to dehydration. In parallel, the accumulation of peroxide in c.v. ICCV-2 increased by 5.3-fold as compared to 2.5-fold in JG-62 after 192 h of dehydration (Figure 11C). This may be attributed to a greater damage to cellular machineries in c. v. ICCV-2 under progressive dehydration. It is understood that exposure of plants to dehydration leads to decrease in the photosynthetic rate and stomatal conductance, thereby increasing intercellular CO2 concentration. The in planta photosynthetic rate showed drastic reduction upon dehydration in c.v. ICCV-2 when compared with JG-62 (Figure 11D). The net photosynthetic rate in c.v ICCV-2 was reduced by 90% whereas JG-62 could retain 45% of its rate. The above results are in consistence with our previous findings where c.v. ICCV-2 showed a higher level of dehydration-induced lipid peroxidation and electrolyte leakage than JG-62.18 Taken together, these physiochemical characteristics suggest that c.v. ICCV-2 is more susceptible to oxidative injury under dehydration than JG-62. 2043



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Figure 12. Model depicting diverse pathways putatively functional in the ECM of chickpea under dehydration. Proteins identified in this study as well as those reported in our previous study are indicated in the boxes. The purple and the light-green boxes denote the expression profile of the DRPs in c.v. ICCV-2 and JG-62, respectively. The graphs are representative of the expression profile of individual protein, and the number shown below indicates the protein Id. Ald, aldolase; R Gal, alpha galactosidase; R Glu, alpha glucosidase; AP, aminopeptidase; APx, ascorbate peroxidase; Cel-syn, cellulose synthase; CHRK1, Chitinasespecific receptor kinase; EH, epoxide hydrolase; Fer, ferritin; GLPs, germin like proteins; Glu-syn, glutamate synthase; GT, glycosyltransferase; Gly1, glyoxalase1; GRPs, glycine rich proteins; Hsp90, heat shock protein 90; LAP, leucine aminopeptidase; Let, 19S proteasome regulatory subunit; MD, malate dehydrogenase; Man-lec, mannose lectin; MAPKK, mitogen-activated protein kinase kinase; MT, methyltransferase; NADHOx, NADH oxidase; NDK, Nucleoside diphosphate kinase; Pep, peptidase dimerization; RGP, reversibly glycosylated peptides; SH, sedoheptulose; Tpx, thioredoxin peroxidase; Trx, thioredoxin; TULP, tubby-like protein; UBA, UBA like; Vil, villin like protein; WAK, wall associated kinase; XET, xyloglucan endotransglycosylase.

’ CONCLUSION This study summarizes the differential response of two contrasting genotypes of chickpea under dehydration in terms of the dynamic changes in the ECM proteome. While the detected number of protein spots in c.v. ICCV-2 was higher than that in JG-62, the number of DRPs was found to be much less in the former. Moreover, these genotypes seem to follow a distinct dehydration response as revealed by the low overlap of the DRPs. On the basis of our observations, a model elucidating the role of the DRPs and the mechanism(s) underlying dehydration tolerance is depicted in Figure 12. The differential dehydration response in these genotypes may be explained by virtue of earlyand late-dehydration responses by cell wall restructuring and activation of targeted proteins involved in cell defense and rescue. The comparative analysis revealed that the enzymes involved in cell wall lignification, such as methyl transferases and methionine synthases were expressed in both the genotypes, indicating a constitutive physical barrier to avoid water loss in the early stages of dehydration. However, the proteins involved in cell wall modification such as alpha glucosidase were significantly downregulated in c.v. ICCV-2, suggesting weakening of the cell wall under progressive dehydration. The upregulated expression of glycosyl transferases in c.v. JG-62 might be involved in the overproduction of sugar monomers for possible maintenance of osmotic balance under dehydration. Significantly, there was minimal overlap for the proteins involved in cell signaling between the two genotypes. While the signaling machinery in

c.v. JG-62 comprised of WAKs, receptor kinases among others, such proteins could not be detected in ICCV-2. Furthermore, the GRPs that are known to act downstream to WAKs were also not detected in c.v. ICCV-2, indicating the probable difference in stress-induced signal perception and transduction. The major difference emerged in the redox homeostasis wherein the major ROS-catabolising enzymes were either downregulated or not detected in c.v. ICCV-2. These data prompted us to further investigate the activities of antioxidant enzymes in these genotypes during the course of dehydration. The results revealed the reduced activity of these enzymes in c.v. ICCV-2 when compared with JG-62, emphasizing their possible role in conferring dehydration tolerance in the latter. Furthermore, the reversible and irreversible changes in the ECM proteomes revealed that more dehydration-responsive events are irreversibly affected in c.v. ICCV-2, thereby inflicting upon a greater extent of dehydrationinduced damage. This study led to the identification of several potential dehydration-responsive components, which may be utilized to manipulate cell wall composition toward improved adaptation to dehydration through genetic engineering approaches.

’ ASSOCIATED CONTENT

bS

Supporting Information Supporting Information Document 1, Details of mass spectra of proteins identified with single peptide that include the precursor ion mass, expected molecular weight, theoretical 2044


Journal of Proteome Research molecular weight, delta, score, rank, number of missed cleavages, and the peptide sequence, along with the fragment spectra. Supporting Information Figure 1, Detail of the dehydrationresponsive ECM proteins that were used to generate the SOTA expression clustering. Supporting Information Figure 2, Heat map showing the expression profiles of the common dehydration-responsive ECM proteins in c.v. JG-62 and ICCV-2. Supporting Information Table 1, Bioinformatics analysis of the secretory nature of the dehydration-responsive proteins identified in c.v. ICCV-2. Supporting Information Table 2, List of common ECM resident proteins in c.v. ICCV-2 and JG-62. Supporting Information Table 3, List of common dehydrationresponsive proteins in c.v. ICCV-2 and JG-62. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*Dr. Subhra Chakraborty, National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi-110067, India. E-mail: [email protected]. Tel: 00-91-11-26735186. Fax: 00-91-11-26741658. Dr. Niranjan Chakraborty, National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi-110067, India. E-mail: [email protected]. Tel: 00-91-11-26735178. Fax: 00-91-11-26741658. Author Contributions †

These authors contributed equally to this work.

’ ACKNOWLEDGMENT This work was supported by grants from the Department of Biotechnology (DBT), Govt. of India and the National Institute of Plant Genome Research, New Delhi. We thank the DBT and University Grant Commission (UGC), Govt. of India for providing predoctoral fellowship to DKJ and DB. We also thank Mr. Jasbeer Singh for illustrations and graphical representation in the manuscript. ’ REFERENCES (1) Saranga, Y.; Menz, M.; Jiang, C.; Wright, R. J.; Yakir, D.; Paterson, A. H. Genomic dissection of genotype environment interactions conferring adaptation of cotton to arid conditions. Genome Res. 2001, 11, 1988–1995. (2) Senaratna, T.; McKersie, B. D. Loss of desiccation tolerance during seed germination: a free radical mechanism of injury. In Membranes, Metabolism and Dry Organisms; Cornell University Press: New York, 1986; pp 85101. (3) Shinozaki, K.; Yamaguchi-Shinozaki, K. Gene expression and signal transduction in water-stress response. Plant Physiol. 1997, 115, 327–334. (4) Seki, M.; Narusaka, M.; Ishida, J.; Nanjo, T.; Fujita, M.; Oono, Y.; Kamiya, A.; Nakajima, M.; Enju, A.; Sakurai, T.; Satou, M.; Akiyama, K.; Taji, T.; Yamaguchi-Shinozaki, K.; Carninci, P.; Kawai, J.; Hayashizaki, Y.; Shinozaki, K. Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray. Plant J. 2002, 31, 279–292. (5) Ng, C. K. Y.; Carr, K.; Mcains, M. R.; Powell, B.; Hetherington, M. Drought-induced guard cells signal transduction involves sphingosine-1-phosphate. Nature 2001, 410, 596–599. (6) Zhu, J.; Chen, S.; Alvarez, S.; Asirvatham, V. S.; Schachtman, D. P.; Wu, Y.; Sharp, R. E. Cell wall proteome in the maize primary root elongation zone. I. Extraction and identification of water-soluble and lightly ionically bound proteins. Plant Physiol. 2006, 140, 311–325.

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