Hg-Responsive Proteins Identified in Wheat Seedlings Using iTRAQ

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Hg-responsive Proteins Identified in Wheat Seedlings Using iTRAQ Analysis and the Role of ABA in Hg stress Guozhang Kang, Gezi Li, Lina Wang, Liting Wei, Yang Yang, Pengfei Wang, Yingying Yang, Yonghua Wang, Wei Feng, Chenyang Wang, and Tiancai Guo J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/pr5006873 • Publication Date (Web): 21 Oct 2014 Downloaded from http://pubs.acs.org on October 27, 2014

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Journal of Proteome Research

Hg-responsive Proteins Identified in Wheat Seedlings Using iTRAQ Analysis and the Role of ABA in Hg Stress

Guozhang Kang1,2†*, Gezi Li1†, Lina Wang1,3, Liting Wei2, Yang Yang3, Pengfei Wang1, Yingying Yang3,Yonghua Wang2, Wei Feng3, Chenyang Wang3, Tiancai Guo1,3* 1 The Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, 450002, China 2 The National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, 450002, China 3 The National Engineering Research Centre for Wheat, Henan Agricultural University, Zhengzhou, 450002, China

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ABSTRACT Wheat seedlings exposed to 100 µM HgCl2 for 3 days exhibited high-level mercury (Hg) accumulation, which lead to inhibited growth, increased lipid peroxidation, and disrupted cellular ultrastructures. And root growth and ultrastructural changes of wheat seedlings were inhibited more severely than those of leaves. To identify wheat protein response to Hg stress, iTRAQ method was used to determine the proteome profiles of the roots and leaves of wheat seedlings exposed to high Hg condition. 249 proteins were identified with significantly altered abundance. 117 were found in roots and 132 in leaves. These proteins were classified into signal transduction, stress defense, carbohydrate metabolism, protein metabolism, energy production, and transport functional groups. The majority of proteins identified in Hg-stressed roots and leaves displayed differently altered abundance, revealing organ-specific differences in adaption to Hg stress. Pathway Studio software was used to identify the Hg-responsive protein interaction network that included 49 putative key proteins and they were potentially regulated by abscisic acid (ABA). Exogenous ABA application conferred protection against Hg stress and increased activities of peroxidase enzyme, suggesting that it may be an important factor in Hg signaling pathway. These findings can provide useful insights into the molecular mechanisms of Hg responses in higher plants.

Keywords: Mercury, Triticum aestivum L., Ultrastructure, Proteomics, Interaction network, ABA.

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INTRODUCTION Contamination of soils by heavy metals and metalloids is increasing rapidly as a result of human activities (e.g., excessive use of phosphate fertilizer, the metallurgy industry, and irrigation with sewage or polluted water) and has become a major concern globally.1 Heavy metals not only reduce crop yields but also accumulate in the edible parts of plants and can enter the food chain, with subsequent adverse effects on human health.2 Plants have evolved many complex mechanisms to minimize damage caused by heavy metals, the mechanistic basis of which is poorly understood. Amongst the metal pollutants, mercury (Hg) is both the best known and the most hazardous to the environment because of its long biological half-life and accumulation to high levels in living organisms.3,4 Hg exists in several forms, but ionic mercury (Hg2+) is the predominant form in soils and is readily absorbed by plants. Ionic Hg can bind to thiol-containing proteins and cysteine, resulting in the disruption of cell structures and interference with cell signaling pathways, and Hg-induced oxidative damage in plants causes lipid peroxidation, enzyme inactivation, and DNA and membrane damage.5-8 Plant responses to heavy metal stresses are considered to be based on a complex set of traits related to morphological, physiological, developmental, and cellular processes. These processes are well controlled by heavy-metal-responsive genes (proteins).1,6 Thus, the identification of genes or proteins involved in the response to heavy-metal stress is a fundamental step toward understanding the molecular mechanisms of the stress response and may facilitate use of plants for environmental cleanup.1 Studies on Hg-stress-response mechanisms have been performed mainly at the physiological and genetic levels.6,7,9-15 Although these studies have enhanced our understanding of the responses of plants to Hg stress, many questions remain unanswered because gene expression can be regulated at the transcriptional, post-transcriptional, translational, and post-translational levels.16 Proteomics is the large-scale study of proteins in an organism. Changes in protein levels determined using proteomics approaches can better reflect changes in metabolic activity than differences in gene transcript levels, because changes in gene expression at the transcript level are not always reflected at the protein level. Recent studies on heavy metal response have highlighted the emergence of proteomic analysis as a promising tool. To our knowledge, only two studies using proteomic analysis of Hg stress responses in higher plants have 3



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been reported using classical 2-D electrophoresis (2-DE) combined with mass spectrometry (MS).17,18 In these two studies, however, only a few Hg-responsive proteins (17 and 25 Hg-responsive proteins in leaves of Suaeda salsa and roots of rice, respectively) was identified.17,18 Wheat, one of the most important crops globally, feeds ~40% of the world population by providing 20% of the total food calories and protein in the human diet, and is highly sensitive to heavy metals, including Hg.18,19 However, to our knowledge, very few study performed proteomic investigation for the response of common wheat to Hg stress using 2-DE method.20 Isobaric tag for relative and absolute quantification (iTRAQ), a second-generation, gel-free proteomics approach, provides more accurate quantitation of protein levels, particularly low-abundance proteins, than 2-DE.21 In this study, an iTRAQ-based quantitative proteomic analysis was performed for the first time on the roots and leaves of common wheat seedlings exposed to Hg stress, combined with physiological assays and observations of cellular ultrastructure. Our approach was sensitive enough to identify 117 and 132 Hg-responsive proteins in roots and leaves of wheat, respectively. Proteins with markedly altered expression were then analyzed using the Pathway Studio software to identify those that may play crucial roles in the response to Hg-induced stress and they could be regulated by ABA. This study was aimed to reveal the molecular mechanisms underlying the responses to Hg stress in higher plants.

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MATERIALS AND METHODS Plant Growth Conditions and Hg Treatments The design of this study is shown in Figure 1. Common wheat (Triticum aestivum L., ‘Yumai 34’) seeds were surface-sterilized using 1% sodium hypochlorite for 10 min, rinsed in distilled water three times, and germinated in glass dishes (15-cm diameter) in distilled water. The seeds were germinated in an illuminated incubator (Ningbo Laifu Technology Co., Ltd., Beijing, China) under a photoperiod of 16-h light and 8-h dark with temperatures of 23°C and 18°C and relative humidities of 60% and 75% during the day and night, respectively. Uniform seedlings were transferred to full-strength Hoagland’s liquid medium, 22 and each glass dish contained about 60 seedlings. Two-week-old seedlings of similar heights (10.5 ± 0.2 cm) with two fully expanded leaves were exposed to Hg stress by immersing the roots in full-strength Hoagland’s solution supplemented with 0 (control), 25 µM, 50 µM, 100 µM, 200 µM, 400 µM HgCl2 (Sigma, USA), respectively.23 After 3 days of Hg stress, the longest roots and the last fully expanded leaves of the Hg-treated plants and control were excised, pooled, rinsed in deionized water, rapidly frozen in liquid nitrogen, and stored at −80°C for measurement of physiological parameters and extraction of total proteins. The remaining roots and leaves from the same plants were used to determine Hg content. Growth Parameters Growth parameters, such as plant height, root length, and fresh weight (FW) of wheat seedlings, were determined immediately following 5 days of Hg stress. Dry weight (DW) of wheat seedlings were determined after drying the whole plant for 72 h at 60°C. Photosynthetic pigment content was determined in 80% (v/v) acetone leaf extract and calculated according to method of Lichtenthaler (1987).24 Average values of four plants were considered as one replication and three independent biological replications with 12 plants each replication were performed. Determination of Hg Content Roots and leaves were dried in an oven for 72 h at 60°C and then ground to a fine powder. The dried powders were digested with nitric acid and hydrogen peroxide (HNO3:H2O2, 4:1, v/v) and Hg contents were quantified using inductively coupled plasma-atomic emission spectrometry (ICP-AES) (Optimal 2100DV, Perkin Elmer Instruments, Waltham, MA).25 5



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Determination of Hydrogen Peroxide (H2O2) and Malondialdehyde (MDA) Contents H2O2 contents in the roots and leaves of wheat seedlings were determined according to Jessup and his colleagues.26 The endogenous level of H2O2 was estimated spectrophotometrically at 390 nm using a UNICO spectrophotometer [UV-2600, UNICO (Shanghai) Instruments Co., Ltd., Shanghai, China]. MDA contents were determined as described previously.27 MDA contents were calculated from UV absorbance at 600, 532, and 450 nm. Transmission Electron Microscopy After exposure to Hg stress for 3 days, sample sections from tips of the longest root (1–3 mm in length, 2–3 mm behind the apex), and the middle portion of the last developed leaf (1 mm2, top middle section of the fully expanded leaf) were excised and fixed in cold 4% (v/v) glutaraldehyde in 0.1 M potassium–phosphate buffer (PBS, pH 7.2), vacuum-infiltrated until the material sank, and left overnight at 4°C. The samples were then dehydrated in a graded alcohol series and embedded in resin.28 Sample semi-microsections of 0.2-µm thickness were generated using an LKB11800 Pyramitome (Sweden) and then examined using a transmission electron microscope (model 7500; Hitachi, Tokyo, Japan) at 80 kV. At least five sections from each treatment were examined. Proteomics Sample Preparation and iTRAQ Labeling Proteins were extracted using the trichloroacetic acid (TCA)/acetone method, and three biological replications were performed.29 Protein digestion was performed according to the filter-aided sample preparation (FASP) procedure previously described.30,31 The protocol was as follows: 200 µg of protein sample was added with 30 µL of STD buffer (4% SDS, 100 mM DTT, 150 mM Tris-HCl, pH 8.0), incubated in boiling water for 5 min, cooled to room temperature, diluted with 200 µL of UA buffer (800 mM urea, 150 mM Tris-HCl, pH 8.0), and transferred for ultrafiltration. Then, sample was centrifuged at 14, 000 × g for 15 min, and 200 µL of UA buffer was added and centrifuged for 15 min again. Then, the concentrates were mixed with 100 µL of 50 mM iodoacetamide (IAA) in UA buffer, and sample was incubated in darkness for 20 min. After 10 min of centrifugation under the above conditions, the filters were washed twice with UA buffer, 100 µL of DS buffer [50 mM triethylammonium bicarbonate (TEAB), pH 8.5] was then added to the filters and sample was centrifuged for 10 min and repeated twice. Finally, 2 µg trypsin 6


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(Promega) in 40 µL of DS buffer was added to each filter. The circumvent immobilization steps on the spin filters were used in the elution of peptides from MWCO filters. The sample was incubated overnight at 37 °C. The digested peptides were collected by centrifugation. The filters were rinsed with 40 µL 10 × DS buffer and centrifuged again. The reliabilities of iTRAQ differential peptide abundance measurements were evaluated using the three most intense peptide ions (Hi3) in comparison with the Hi3 of a predigested internal standard protein. The peptide content was measured by UV light at 280 nm using an extinctions coeffcient of 1.1 of 0.1% (g/L) solution that was calculated on the basis of the frequency of tryptophan and tyrosine. The resulting peptide mixture was labeled using the 4-plex iTRAQ reagent according to the manufacturer’s instructions (Applied Biosystems, Inc., Foster city, CA). The samples were labeled as (control leaves)-114, (Hg-stressed leaves)-115, (control roots)-116, and (Hg-stressed roots)-117 and were multiplexed and vacuum dried. Separation of Peptides by Strong Cation Exchange (SCX) Chromatography Prior to analysis by liquid chromatography coupled with tandem mass spectroscopy (LC-MS/MS), peptides were purified from excess labeling reagent by SCX chromatography. The labeled samples were dried and then diluted with 20-fold cation-exchange binding buffer A [10 mM KH2PO4, pH 3.0, 25% (v/v) acetonitrile (ACN)]. SCX chromatography was performed to separate the labeled samples into 10 fractions using a poly-sulfoethyl A column. A 4.6 × 100-mm poly-sulfoethyl A column (5 µm, 200 Å) (PolyLC Inc., Maryland, USA) gradient elution was applied to separate peptides at a flow rate of 1 mL/min with elution buffer B [10 mM KH2PO4, pH 3.0, 500 mM KCl, 25% (v/v) ACN] for 2 min, 10–20% buffer B for 25 min, 20–45% buffer B for 5 min, and 50–100% buffer B for 5 min. The elution was monitored by absorbance at 214 nm and fractions were collected at 1-min intervals. Eluted peptides were collected and desalted using an offline fraction collector and C18 Cartridge (Sigma, USA). Each fraction was concentrated by vacuum centrifugation and reconstituted in 40 µL of 0.1% (w/v) trifluoroacetic acid. All samples were stored at –80°C until LC-MS/MS analysis. 2D LC-MS/MS Analysis For each fraction, 10 µL of the solution were injected for nanoLC-MS/MS analysis into an AB SCIEX TripleTOF 5600 MS (Toronto, Concord, Canada) equipped with a splitless Eksigent 7



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nanoUltra 2D Plus nanoLC system and a cHiPLC Nanoflex microchip system (Dublin, CA, USA). The Nanoflex system uses replaceable microfluidic traps and columns packed with ChromXP C18 (3 µm, 120 Å) for online trapping, desalting, and analytical separations. The sample was loaded and trapping and desalting were carried out at 2 µL/min for 10 min with 100% mobile phase A (2% ACN/0.2% formic acid/98% water). The gradient started at 5% mobile phase B (98% ACN/0.2% formic acid/2% water) and increased linearly to 24% in 70 min at a flow rate of 300 nL/min for peptide elution. MS data acquisition was performed in the information dependent acquisition (IDA) mode. IDA survey scans were acquired in 250 ms with a mass range of m/z 350–1250. As many as 30 product ion scans were collected for 100 ms if exceeding a threshold of 120 cps (counts/s) and with a charge state of +2 to +5. Dynamic exclusion was set for 18 s. Collision energies were calculated on-the-fly for all precursor ions using empirical equations based on mass and charge and the enhance iTRAQ function was turned on to improve the efficiency of the collision-induced dissociation. Peptide and Protein Identification and Proteomic Data Analysis MS/MS spectra were searched using the MASCOT engine software (Matrix Science, London, UK; version 2.2) embedded in Proteome Discoverer 1.4 software (Thermo Electron, San Jose, CA.) run against the UniProt Poacese database (548,581 sequences, downloaded August 5, 2013) and the decoy database. For protein identification, the following options were used: peptide mass tolerance = ± 20 ppm, fragment mass tolerance = 0.1 Da, enzyme = trypsin, missed values = monoisotopic, max missed cleavage = 2, mixed modification: carbamidomethyl (C), iTRAQ4plex (N-term), iTRAQ4plex (K), variable modification: oxidation (M), iTRAQ4plex (Y)，integration window tolerance = 20 ppm, minimum quan value threshold = 0, fold change threshold for up-/down-regulation = 2, maximum allowed fold change = 100, and FDR ≤ 0.01.32 Differentially expressed proteins were analyzed for significant downregulation or upregulation, which was calculated using the ProteinPilot software. Ratio was used to assess the fold changes in the abundance of the proteins identified in Hg-treated vs. control plants and Duncan’s multiple range test was used to identify significant (p 1.5- or < 0.66-fold were used as the qualification criterion, which corresponded to a peptide confidence level of 95%.33 The identified 8


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proteins were grouped by the ProGroup algorithm (AB SCIEX) to minimize redundancy. Bias correction for unequal mixes the different labeled samples was performed. All these data were normalized by bias correction, which is an algorithm in ProteinPilot corrects for unequal mixes combining the different labeled samples. Differentially expressed proteins were defined as those showing at least 1.5 fold-change relative to their matched controls.34 Hg-related Protein Interaction Network Analysis The UniProt data base (www.uniprot.org) was used to search for the function/biological process. In this study, the identified proteins were annotated by searching against the UniProt database and then grouped on the basis of their biological functions from Gene Ontology (GO) terms. The biological interaction network (BIN) of the identified protein species was predicted using the Pathway Studio software (version 8.0, Ariadne Genomics, Inc., Rockville, MD).16,29 Effect of Exogenous ABA Application on Hg Tolerance of Wheat Seedlings Remarkable and positive effects on abiotic tolerance in higher plants in response to treatment with 10 µM ABA have been reported.35,36 In this study, 2-week-old wheat seedlings were transferred to Hoagland’s solution containing 100 µM Hg (Hg treatment, Hg) or 100 µM HgCl2 plus 10 µM ABA (Hg and ABA treatment, Hg + ABA) for 3 days. Wheat seedlings were maintained in full-strength Hoagland’s solution without Hg for 3 days as a control. FW, DW, and MDA contents of roots and leaves of control, Hg treated- and Hg+ABA treated seedlings were determined according to the above methods. Total soluble sugar and proteins contents were measured according to the methods previously described.37,38 Experiments were repeated three times. For determination of peroxidase (POD) enzyme activity, 0.5 g of fresh roots were ground with 5 mL ice-cold 50 mM PBS (pH 7.0) containing 0.1 mM EDTA, 0.2 mM ascorbate, and 4% (w/v) polyvinylpyrrolidone (PVP). The homogenates were purified by centrifugation at 12, 000 × g and 4°C for 20 min, and the supernatants were used for determination of protein content and for POD activity assays.39 Statistical Analysis All experiments were repeated independently in triplicate. A one-way analysis of variance (ANOVA) using the SPSS 17.0 statistical software, and Duncan’s multiple range test (DMRT), were used to identify significant (P < 0.05) differences between group means. 9



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RESULTS AND DISCUSSION Phenotypes and Growth Parameters of Wheat Seedlings Exposed to Hg Stress Different plant species have diverse abiotic and biotic tolerances, including Hg stress. Hg stress at high concentrations in Pfaffia glomerata (50 µM), tobacco (350 µM) and cucumber seedlings (500 µM) was previously shown to seriously inhibit plant growth.4,8-10 In the present study, wheat seedlings treated with 0~400 µM Hg showed time- and dose-dependent characteristics (Figure 2). Wheat seedlings exposed to low concentrations (≤50 µM) Hg had not visible changes until 5 days, whereas high concentrations (≥200 µM) quickly exhibited significant deleterious phenotypes for 1 day of Hg treatment. Wheat seedlings also show visible phenotypes after treated with 100 µM Hg for 3 days. These qualitative phenotypic effects were confirmed by quantitative analysis (Figure 3). Similar results have also been reported in cucumber seedlings.10 Because wheat seedlings grew quickly in Hoagland solution and there could be some differences in development stages between control and Hg treated wheat seedlings after 5 days, as indicated by the sizes of shoot tips (Supplemental Figure S1), and thus some identified proteins after 5 days of Hg treatments in further proteomic experiment may be associated with wheat development, not with stress adaptation. However, higher concentrations (≥200 µM) quickly caused deleterious phenotypes in 1 day of Hg treatment, possibly due to pleiotropic responses to acute mercury toxicity. In this study, thus, 100 µM Hg treatment for 3 days was further used to explore the adaptive mechanism to Hg stress in wheat seedlings in further experiments, because at this concentration and this time point, wheat seedlings began to show visible phenotype and significantly inhibited growth parameters (Figures 2 and 3), whereas no visible differences in development stages were observed between control and Hg-stressed wheat seedlings (data no indicated). Contents of Photosynthetic Pigments, H2O2, MDA, and Hg in Roots and Leaves of Wheat Seedlings Exposed to Hg Stress Exposure to heavy metals can intensify the production of ROS such as H2O2, which reacts with cellular components (lipids, proteins, and nucleic acids) causing lipid peroxidation, photosynthetic pigment degradation, membrane damage, and inactivation of enzymes with subsequent inhibition of plant growth.40 In this study, the chlorophyll a and b and carotenoid contents in leaves of wheat 10


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seedlings exposed to 100 µM Hg stress for 3 days, were significantly reduced by 37.2%, 42.9%, and 37.5%, respectively (Figure 4A). This also indicated that wheat growth was seriously inhibited by Hg stress. Membrane lipids are particularly susceptible to attack by ROS and are considered to be reliable indicators of oxidative stress in plants. MDA is a common product of lipid peroxidation and is a sensitive diagnostic indicator of oxidative injury.41 In this study, H2O2 levels increased 1.9- and 4.7-fold in roots and leaves of wheat seedling suffered from 3 days of 100 µM Hg stress, respectively (Figure 4B). MDA contents increased significantly in seedling roots (3.3-fold) and leaves (2.7-fold) and were 57.3% higher in roots than in leaves (Figure 4C), indicating that Hg stress may cause increased ROS accumulation and lipid peroxidation, which in turn may affect the growth of wheat seedlings. Hg accumulation in plants disrupts many functions at the cellular level, and inhibits growth and development. These effects indicate that severe stress is caused by toxic levels of heavy metals.17,42,43 Our results indicated that Hg contents in leaves and roots of wheat seedlings increased markedly after 3 days of Hg stress, with a remarkable 1822.3-fold increase in roots (from 0.03 to 54.67 µg.g-1 DW) and a 45-fold increase in leaves (from 0.04 to 1.8 µg.g-1 DW). The Hg content in roots was 30.4-fold higher than those in leaves after 3 days of Hg exposure (Figure 4D). The differences in Hg content between the roots and leaves indicated that Hg had different toxic effects on roots and leaves, i.e. more on roots than on leaves.10 Due to the differential accumulation of Hg between roots and leaves, H2O2 and MDA concentrations increased to higher levels in the roots than in the leaves after exposure to Hg stress for 3 days (Figure 4A and B). It was speculated that the Hg stress response in plants may involve a number of pathways and stress signals, which differ among tissues. Ultrastructural Changes in Roots and Leaves of Wheat Seedlings Exposed to Hg Stress Heavy metals can be trapped in plant tissues by the negative charges of the cell walls, accumulate in the apoplast, or may accumulate in the cell cytoplasm; thus, the deleterious effects of heavy metals can also be manifested at the ultrastructural level.44 To our knowledge, however, no information on the relationships between the deleterious effects of Hg stress and the ultrastructures of plant cell organelles has been reported. In this study, transmission electron microscopy revealed that root cells of unstressed wheat seedlings (control) had smooth and continuous cell walls, large 11



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nuclei and nucleoli, and well-developed mitochondria (Figure 5A and C). However, adverse effects on cell organelles were observed in the roots of Hg-stressed wheat seedlings. After 3 days of Hg stress, many cell walls in roots became irregular and broken (Figure 5B), some mitochondrial envelopes disintegrated, many mitochondrial cristae disappeared, and large vesicles appeared in the mitochondria (Figure 5D). Similarly, leaf mesophyll cells of unstressed-wheat seedlings had well-developed chloroplasts with a regular arrangement of thylakoid lamella and the mitochondria were rich in cristae and had clear envelopes (Figure 6A, C, and E). However, clear symptoms of Hg toxicity were observed in organelles of the leaf mesophyll cells of Hg-stressed wheat seedlings. The plasma membrane was detached from the cell wall (Figure 6B), 48.3% chloroplasts were degraded (Figure 6B), 72.1% grana thylakoid lamella in these degraded chloroplasts were dissolved, and aberrant vesicles appeared in the chloroplast stroma (Figure 6D). Moreover, mitochondria became swollen, 41.3% mitochondrial envelopes were broken down, and 58.2% cristae disappeared in these swollen mitochondria (Figure 6F). These deleterious changes suggested that the ultrastructures of roots and leaves were highly sensitive to Hg stress. Because Hg had different physiological, cellular and toxic effects on roots and leaves of wheat seedlings, proteomic experiments were performed to identify Hg-responsive proteins differentially expressed in leaves and roots of wheat seedlings exposed to Hg stress. Proteomic Expression Patterns in Wheat Seedling Leaves and Roots in Response to Hg Stress Proteome profiles for roots and leaves of wheat seedlings exposed to 100 µM Hg stress for 3 days were generated using iTRAQ method. A total of 7,783 peptides from trypsin-digested proteins were identified in Hg-stressed wheat seedlings. Using the Mascot software, a total of 19,445 spectra matched to known spectra, 16,949 spectra matched to unique peptides, 8,322 peptides, 7,659 unique peptides, and 2,616 proteins were identified. All proteins identified by MS/MS, and their peptides of proteins are provided in Supplemental Tables S1 and 2. Over 72% of the proteins included at least two peptides, whereas other proteins were based on a single high-confidence peptide assignment with 95% confidence of false discovery rate (FDR)≤1%,33 and their annotated tandem mass spectra are indicated in Supplemental Figures S2 and 3. The peptides of the identified proteins that exhibited significant differential expression in roots and leaves are 12


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provided in Supplemental Tables S3 and 4, respectively. And the quantitative analysis parameters for ion peak strength value of peptides were described in Supplemental Table S5. In the roots and leaves of Hg-stressed wheat seedlings, 117 and 132 differentially expressed proteins were identified, respectively. The functions of the differentially expressed proteins in roots and leaves were annotated by their GO terms and are summarized in Tables 1 and 2, respectively. The expression abundance of many proteins could be restrained to slow the growth rate of wheat seedlings, whereas others were activated to adapt to Hg stress. The number (249) of identified proteins in this study was considerably greater than the 17 and 25 Hg-responsive proteins in leaves of Suaeda salsa and roots of rice.17,18 Because common wheat is a relative of rice, the changes in the Hg-induced root proteomes were compared between wheat and rice to advance the understanding of Hg tolerance in plants. Several of the Hg-responsive proteins were commonly identified in this study and a previous rice proteomic study, whereas many proteins were specially regulated by Hg in wheat or rice (Supplemental Table S6). This difference could be attributed to iTRAQ method, which is a more advanced approach than the classical procedure of staining 2-DE gels with Coomassie brilliant blue, which was used to examine the proteome in roots of Hg-stressed rice seedlings.17,21 Other factors contributing to the differences may include the divergence of DNA sequences between such distantly related species, differences in experimental design, and the different statistical cut-off and fold-change thresholds used in these two studies. Thus, our work provides more proteomic information on higher plant responses to Hg stress. Similarities and Differences in Proteome Patterns Between Roots and Leaves of Wheat Seedlings Exposed to Hg Stress Tables 1 and 2, and Figure 7 showed that the roots and leaves exhibited similar proteome patterns after exposed to Hg stress. Several proteins, such as lipoxygenase 3 (M7XM33), pathogenesis-related protein 4 (Q9SOG8), PR-4 (Q9SQG3), pathogenesis-related protein 1 (N1QT70), and peroxidase 2 (M7Z7N2), were identified in both roots and leaves exposed to Hg stress. Moreover, the amounts of all of the energy-production-related proteins decreased markedly in both roots and leaves of Hg-stressed seedlings (Tables 1 and 2). These results suggested that root and leaf tissues may have some similar responses to Hg stress. 13



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Many differences in the proteome patterns of roots and leaves exposed to Hg stress were also found. The majority of proteins identified in the roots and leaves were different (Figure 7). In Hg-stressed roots, the amounts of most of the proteins with functions related to biological regulation and signal transduction (14 of 16, 87.5%), transport (10 of 13, 76.9%), protein metabolism (28 of 43, 65.1%), and stress defense proteins (19 of 30, 63.3%) decreased markedly, whereas the amounts of most of the carbohydrate-metabolism-related proteins (13 of 21, 61.9%) were increased compared to control (Table 1). In Hg-stressed leaves, the amounts of most of the photosynthesis-related proteins (19 of 20, 95.0%) decreased significantly, whereas the amounts of most of the proteins with functions related to stress defense (41 of 44, 93.2%), carbohydrate metabolism (22 of 31, 71.0%), and protein metabolism (17 of 29, 58.6%) increased. In addition, a transport protein was highly upregulated, and half (4 of 8) of the proteins involved in regulation and signal transduction were up- or down-regulated in leaves exposed to Hg stress (Table 2). This implied that roots and leaves could have differentiated Hg-response mechanisms. Similar results have been reported in higher plants suffered from copper stress.45,46 The differences in the identified proteins between the roots and leaves may be related to the differences in Hg accumulation in the two tissues (Figure 4D) or to the different functions, growth environments, and sensitivities of roots and leaves to Hg stress. The different proteome profiles for roots and leaves further suggested that Hg stress may have profound and different effects on growth in roots and leaves. Proteins Responsive to Hg Stress in Roots and Leaves of Wheat Seedlings The functions of these identified proteins included signal transduction, stress defense, carbohydrate metabolism, protein metabolism, energy production, and transport (Tables 1 and 2). The functions of the 117 proteins identified in the Hg-stressed roots included signal transduction (4 proteins, 3.42%), stress defense (26 proteins, 22.22%), carbohydrate metabolism (19 proteins, 16.24%), protein metabolism (55 proteins, 47.01%), energy production (4 proteins, 3.42%), and transport (9 proteins, 7.69%) (Table 1, Supplemental Figure S4A). The functions of the 132 proteins identified in the Hg-stressed leaves included signal transduction (6 proteins, 4.55%), stress defense (41 proteins, 30.30%), carbohydrate metabolism (22 proteins, 16.67%), protein metabolism (36 proteins, 27.27%), photosynthesis (23 proteins, 18.18%), energy production (3 14


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proteins, 2.27%), and transport (1 protein, 0.76%) (Table 2, Supplemental Figure S4B). Some of the identified Hg-responsive proteins associated with the main biological processes are discussed further below. Signal transduction Protein signaling and regulation play a crucial role in heavy metal tolerance because signaling molecules are capable of coordinating the expression of several downstream target genes or even entire metabolic and developmental pathways.47 Previous proteomic experiments provided limited data on the regulatory proteins involved in signal transduction because their low abundance limits the detection of such proteins using 2-DE proteomics approaches.47 Using the advanced iTRAQ method, 10 proteins belonging to the signal transduction group in roots and leaves of Hg-stressed wheat seedlings were identified (Tables 1 and 2). These identified proteins provide new insight into the complex signal transduction pathway induced by Hg toxicity. For instance, ADP-ribosylation factor GTPase-activating proteins (AGD) (M8AIZ9) modulate the direction of root hair growth, organelle trafficking, and cytoskeletal organization through the activity of an AGD1-dependent ADP-ribosylation factor (ARF) substrate. The severe root hair phenotype of the double AGD and ARF mutant (agd1 and ark1) compared with the single mutants indicated that AGD1 and ARK1 are components of independent but possibly intersecting signaling pathways that specify growth orientation in Arabidopsis root hairs.48 In this study, the abundance of an AGD protein was increased in roots of Hg-stressed wheat seedlings (Table 1), indicating that it may play a partial role in maintaining root growth under Hg stress. Stress defense An increase in the abundance of proteins associated with stress defense has been identified in some higher plants, e.g. rice, Arabidopsis and barley, subjected to heavy metal stresses, and upregulation of these proteins may play an important role in minimizing the ROS damage triggered by heavy metals such as Hg.1,43,49 Peroxidase, glutathione synthesized-relate enzymes, cytochrome P450 family members, glutaredoxin, and thioredoxin have been reported to play key roles in ROS scavenging systems under abiotic stress conditions.50-54 In this study, 15 peroxidases (8 in roots, 7 in leaves), 3 glutathione synthesized-related enzymes in leaves, 3 cytochrome P450 family members in leaves, and 1 thioredoxin in leaves were upregulated markedly by Hg stress (Tables 1 and 2). This suggests that the contents of various antioxidants, 15



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such as antioxidant enzymes, were upregulated in the roots and leaves of wheat seedlings to combat the oxidative stress induced by Hg. Lipoxygenases, PR proteins, disease resistance proteins, endochitinase-antifreeze proteins, universal stress proteins, and Bowman–Birk-type proteinase inhibitor are involved mainly in disease, freezing, drought, and salt resistance in plants,55,56 and they were also identified in this study (Tables 1 and 2). However, some studies have suggested that these proteins play diverse functions in the responses to other abiotic stresses, including heavy metals,57 suggesting that plant cells trigger several common defense mechanisms upon encountering diverse stresses. The number and ratio (39, 95.1%) of stress proteins whose abundance was enhanced in Hg-stressed leaves were considerably higher than those in roots (10, 38.5%), possibly because roots suffered from more serious oxidative injury than leaves after 3 days of Hg stress, as indicated by the contents of Hg, H2O2, and MDA (Figure 4B, C and D). A similar result has been documented in the roots and leaves of soybean subjected to Cd stress.58 Carbohydrate metabolism Efficient carbohydrate metabolism as a source of energy and of carbon skeletons is a basic survival strategy employed by plants subjected to environmental stresses, including heavy metals.59 To maintain normal growth and development in a stressed environment, plants need upregulate the production of factors involved in various metabolic pathways, such as carbohydrate metabolism.43 Our results indicated that the levels of 19 and 22 carbohydrate metabolic enzymes in Hg-stressed roots and leaves, respectively, were altered (Tables 1 and 2). The levels of most of these proteins were increased. Within this group, the functions of the identified proteins were related to glycolysis and lignin synthesis.60,61 In particular, the upregulation of lignin-synthesis proteins may lead to lignin synthesis in roots, resulting in the reduction of vessel formation and translocation of Hg ions from the roots to the aerial parts of the plant.43 Protein metabolism Hg has a high affinity for sulfhydryl (SH) groups and consequently can disturb almost any function in which critical or non-protected proteins with SH groups are involved. A mercury ion may bind to two sites of a protein molecule without deforming the chain, it may bind two neighboring chains together, or a sufficiently high concentration of Hg can lead to protein precipitation, thereby destabilizing many proteins or interrupting their normal functions.62 16


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In our study, 91 proteins were identified in the protein metabolism group in both Hg-stressed roots and leaves; 61 (67.0%) of these proteins were downregulated significantly (Tables 1 and 2). The majority of proteins in this group with decreased abundance were involved in protein synthesis, including histone proteins, ribosomal proteins (Tables 1 and 2). The reduced abundance of these proteins associated with protein metabolism may be an inevitable consequence of a wide range of adverse environmental conditions—including Hg stress. Photosynthesis Downregulation of the photosynthetic machinery is a known response to heavy metal stress. The in vivo substitution of the central atom of chlorophyll, magnesium, by heavy metals (including Hg) is an important mechanism of damage in stressed plants. This substitution prevents photosynthetic light-harvesting in the affected chlorophyll molecules, resulting in a breakdown of photosynthesis.63 In this study, 23 protein species associated with photosynthesis showed changes in abundance in wheat seedling leaves after exposure to Hg stress for 3 days; the levels of the majority of these proteins (21 of 23, 87.5%) significantly decreased (Table 2). Heavy metals, including Hg, have been shown to exert multiple inhibitory effects on the Calvin cycle, photorespiration, electron transfer, and oxygen evolution at the structural and metabolic levels.64 For instance, Hg interferes at the reducing side of PSII and possibly substitutes for Cu in plastocyanin, thereby disturbing electron transport between the two photosystems.65 The proteins identified in this group with decreased abundance were associated with almost all aspects of photosynthesis, implying that photosynthesis in the leaves of Hg-stressed wheat seedlings was greatly inhibited. This suggests that complete disruption of the photosynthetic machinery by Hg stress occurred, as also indicated by the ultrastructural damage to chloroplasts in Hg-stressed wheat leaves (Figure 6). These effects may be associated with decreased photosynthetic CO2 assimilation.63. Energy and transportation A sufficiently high concentration of Hg can reduce production of ATP and transport of water and solutes across membranes.1,15 In this study, all (9, 100%) of energy-metabolism-related proteins, and 9 of 10 (90.0%) transport proteins, were downregulated significantly (Tables 1 and 2), possibly being an inevitable consequence of a wide range of adverse environmental conditions-including Hg stress. Interaction Network Analysis of Hg-responsive Proteins in Wheat Seedlings 17



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Proteins do not perform their functions in cells as single entities, but act together in the context of networks.16 In this study, the protein regulatory network pathways related to Hg were analyzed using the Pathway Studio software and generated protein interaction maps connected to each of the identified proteins in the green plant molecular networks database. Forty-nine proteins were identified in this interaction network (Figure 8). These proteins were classified functionally into carbohydrate metabolism (14 proteins), stress defense (11 proteins), protein metabolism (8 proteins), photosynthesis (7 proteins), signal transduction (6 proteins), transport (2 proteins), and energy production (1 protein) (Figure 8). They may be critical components of the response to Hg stress. For example, other than its assigned role in plant defense against pathogens, PR proteins also play a key role in adaptation to stress environments, including heavy metal toxicity.43 Overexpression of the PR-1 gene resulted in an enhanced tolerance to heavy metals in tobacco.66 The precise role of PR proteins in combating heavy metal stress is not yet clearly understood, but Hossain and Komatsu have speculated that the induced redox imbalance might lead to H2O2 accumulation, which triggers a stress tolerance cascade.43 Effect of Exogenous ABA Application on Hg Tolerance in Wheat Seedlings Our results indicated that most of the proteins in this interaction network were related to one signaling molecule, ABA (Figure 8). Regulation of these proteins (genes) by ABA under some abiotic stress was reported in previous studies.8,67,68 Thus, it is speculated that ABA may also act as an important signaling molecule in the response to Hg stress in wheat seedlings. To verify this speculation, the effects of exogenous ABA application on Hg tolerance in wheat seedlings were explored. In this study, exogenous ABA application alleviated the inhibited growth of wheat seedlings by Hg toxicity, as indicated significantly (Figure 9A). This phenotypic result was confirmed by quantitative analysis, which revealed markedly increased fresh weights, dry weights, and total soluble sugar and proteins contents, whereas the contents of MDA in roots and leaves of Hg-stressed wheat seedlings decreased significantly (Tables 3 and 4). POD is one of the most important antioxidative enzymes, and its overexpression significantly increased Cu, Cd and arsenic (As) tolerance.68,69 In this study, the abundance of many isoforms of POD was enhanced in roots of Hg-stressed wheat seedlings (Table 1), and then POD was used as an example to evaluate whether the proteins identified in the above protein interaction network were regulated by ABA. 18


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Our results indicated that POD activities were enhanced markedly in roots of Hg-stressed wheat seedlings by exogenous ABA application (Figure 9B). Thus, we speculate that ABA may function as an important signal molecule that alters the expression profiles of some proteins (genes), thereby alleviating the damage caused by Hg exposure in wheat seedlings.

CONCLUSIONS Excess Hg application to wheat seedlings caused high accumulation of Hg in roots and leaves, greatly inhibited growth, and caused severe ultrastructural damage to cells in both roots and leaves. Growth and physiological parameters, and ultrastructural changes indicated that root tissue of wheat seedlings suffered from 3 days of Hg stress showed more severe injury than leaf tissue. Our proteomic analysis identified 117 proteins in roots and 132 proteins in leaves of Hg-stressed wheat seedlings that exhibited significant changes in abundance. The functions of these protein species were related to signal transduction, stress defense, carbohydrate metabolism, protein metabolism, photosynthesis, energy production, and transport. Changes in the abundance of the identified proteins may be closely related to the phenotypic, ultrastructural, and physiological changes caused by Hg-induced stress. Protein interaction network analysis suggested that 49 proteins play critical roles in regulatory pathways associated with the Hg-stress response, and they may be regulated by ABA. Exogenous ABA application remarkably enhanced the Hg tolerance in wheat seedlings, indicating that it can play important role in the regulation of these proteins. These findings provide a deeper understanding of the molecular response to Hg stress in higher plants.

ASSOCIATED CONTENTS Supporting Information This material is available free of charge via the Internet at http://pubs.acs.org. Table S1 All proteins were indentified by MS/MS in Hg-stressed wheat seedlings. Table S2 All peptides of identified proteins significantly expressed difference in Hg-stressed wheat seedlings. Table S3 The peptides of identified proteins with significantly expressed in roots of wheat seedlings exposed to Hg stress for 3 days. Table S4 The peptides of identified proteins with significantly expressed in leaves of wheat seedlings exposed to Hg stress for 3 days. Table S5 The quantitative analysis parameters for ion peak strength value of peptides by Proteome Discoverer 1.4 software in 19



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Hg-stressed wheat seedlings. Table S6 Comparison between the root proteomic results in the present study and those of rice seedlings exposed to Hg stress. Figure S1 Microscopic observation on shoot tips of wheat seedlings exposed to 0, 25 µM, 50 µM, 100 µM, 200 µM, and 400 µM Hg stress for 5 days. Figure S2 Annotated tandem mass spectra of the identified proteins based on a single high-confidence peptide assignment with 95% confidence of false discovery rate (FDR) ≤1% in roots of Hg-stressed wheat seedlings. Figure S3 The annotated tandem mass spectra of the identified proteins based on a single high-confidence peptide assignment with 95% confidence of false discovery rate (FDR) ≤1% in leaves of Hg-stressed wheat seedlings. Figure S4 Functional classification and distribution of all identified 117 proteins in roots (A) and 132 in leaves (B) based on analysis of sequence homology as listed in Tables 1 and 2. AUTHOR INFORMATION Corresponding Authors *Tel.: +86-371-63558205. Fax: +86-371-63558200. E-mail: [email protected] (G. Kang); [email protected] (T. Guo). Author Contributions † These authors contributed equally to this work. Notes The authors declare no competing financial interest

Acknowledgements This study is financially supported by the Twelfth Five-Year National Food Production Technology Project (2011BAD16B07) and the Special Fund for Agro-scientific Research in the Public Interest (201203033).

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responses to microbial pathogens. Plant Physiol. 2010, 152, 948–967. (58) Hossain, Z.; Hajika, M.; Komatsu, S. Comparative proteome analysis of high and low cadmium accumulating soybeans under cadmium stress. Amino Acids 2012, 43, 2393–2416. (59) Stobrawa, K.; Lorenc-Plucińska, G. Changes in carbohydrate metabolism in fine roots of the native European black poplar (Populus nigra L.) in a heavy-metal-polluted environment. Sci. Total. Environ. 2007, 373, 157–165. (60) Campbell, M. M.; Sederoff, R. R. Variation in lignin content and composition (mechanisms of control and implications for the genetic improvement of plants). Plant Physiol. 1996, 110, 3–13. (61) Sergeeva, L. I.; Vreugdenhil, D. Plants and the Environment. In situ staining of activities of enzymes involved in carbohydrate metabolism in plant tissues. J. Exp. Bot. 2002, 53, 361–370. (62) Patra, M.; Bhowmik, N.; Bandopadhyay, B.; Sharma, A. Comparison of mercury, lead and arsenic with respect to genotoxic effects on plant systems and the development of genetic tolerance. Environ. Exp. Bot. 2004, 62, 199–223. (63) Kupper, H.; Kupper, F.; Spiller, M. Environmental relevance of heavy metal-substituted chlorophylls using the example of water plants. J. Exp. Bot. 1996, 47, 259–266. (64) Foyer, C. H.; Neukermans, J.; Queval, G.; Noctor, G.; Harbinson J. Photosynthetic control of electron transport and the regulation of gene expression. J. Exp. Bot. 2012, 63, 1637–1661. (65) Verma, S.; Duber, R. S. Lead toxicity induces lipid peroxidation and alters the activities of antioxidant enzymes in growing rice plants. Plant Sci. 2003, 164, 645–655. (66) Sarowar, S.; Kim, Y. J.; Kim, E. N.; Kim, K. D.; Hwang, B. K.; Islam, R.; Shin, J. S. Overexpression of a pepper basic pathogenesis-related protein 1 gene in tobacco plants enhances resistance to heavy metal and pathogen stresses. Plant Cell Rep. 2005, 24, 216–224. (67) Cheng, W. H.; Endo, A.; Zhou, L.; Penney, J.; Chen, H.C.; Arroyo, A.; Leon, P.; Nambara, E.; Asami, T.; Seo, M.; Koshiba, T.; Sheen, J. A unique short-chain dehydrogenase/reductase in Arabidopsis glucose signaling and abscisic acid biosynthesis and functions. Plant Cell 2002, 14, 2723–2743. (68) Lee, S. H.; Ahsan, N.; Lee, K. W.; Kim, D. H.; Lee, D. G.; Kwak, S. S.; Kwon, S. Y.; Kim, T. H.; Lee, B. H. Simultaneous overexpression of both CuZn superoxide dismutase and ascorbate peroxidase in transgenic tall fescue plants confers increased tolerance to a wide range of abiotic stresses. J. Plant Physiol. 2007, 164, 1626–1638. (69) Radmer, R.; Kok, B. Kinetic observation of the system II electron receptor pool isolated by mercuric ion. Biochimica et Biophysica Acta 1974, 357, 177–180.

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Page 26 of 45

Table 1 Functional classifications of identified proteins with significantly expressed in roots of wheat seedlings exposed to Hg stress for 3 days. Accession Protein species MW/pIb noa Signal transduction M8AIZ9 ADP-ribosylation factor GTPase- 72.71/7.83 activating protein AGD14 M8BQJ1 Ran-binding 1-c-like protein 24.02/4.73

Scorec

Coverage (%)

Nup.d

Species

Ratioe

p-value

18.48

1.66

1

T. urartu

1.90

**

0.0085888

111.50

26.58

5

A. tauschii

0.55

**

0.0066361

**

7Z967

High mobility group B protein 4

15.38/6.90

58.89

14.39

2

T. urartu

0.49

Q4W1G2

High mobility group protein

11.90/9.04

60.40

22.32

3

T. aestivum

0.47

**

0.0011297 0.0007498

Stress defense M7Z3F6

Peroxidase 72

33.15/7.02

155.60

17.32

5

T. urartu

2.98

**

7.16E-06

Q9SQG3

PR-4

13.10/7.24

49.65

10.83

1

T. aestivum

2.68

**

5.11E-05

M8A608

Secologanin synthase

49.32/8.47

27.85

3.01

1

T. urartu

2.35

**

0.0004523

R7W4A1

Peroxidase 52

34.14/8.25

175.41

21.12

6

A. tauschii

2.22

**

0.0010841

C6ETA9

Class III peroxidase

18.75/5.20

204.59

37.02

6

A. tauschii

2.01

**

0.0040813

Q43219

Peroxidase

30.06/5.11

164.49

22.57

5

T. aestivum

1.89

Q9SQG8

Pathogenesis-related protein 4

13.09/7.24

40.42

10.83

1

T. aestivum

1.80

C3UZE5 M8B613

17.62/8.46 116.53/4.72

92.17 20.59

38.41 1.16

4 1

T. aestivum A. tauschii

M7XM33

Pathogenesis-related protein 1-1 Disease resistance RPP8-like protein 3 Lipoxygenase 3

71.98/6.21

239.23

20.44

12

T. urartu

M7Z7N2

Peroxidase 2

37.91/6.60

52.87

5.13

2

T. urartu

M8ASA8

Glutathione S-transferase

24.96/6.42

66.92

16.96

2

A. tauschii

Q9FYY1

Germin E

20.34/7.56

101.09

13.51

2

N1QPN2

Monodehydroascorbate reductase

52.41/7.71

258.02

22.45

9

**

0.0093122

*

0.0165366

1.74 * 1.72

*

0.0240477 0.027246

1.61

*

0.0511053

0.63

*

0.0392371

0.61

*

0.027937

H. vulgare

0.61

*

0.0271576

A. tauschii

0.61

*

0.0245161 0.0253678

B6SXF5


16.96/5.54

117.74

20.00

4

Z. mays

0.60

*

M8ASW4

Acidic endochitinase

37.37/5.26

20.52

5.11

1

A. tauschii

0.60

*

0.0211058

M8BMC6 C8CG65

57.41/6.99 17.39/5.31

250.86 190.30

20.95 19.75

9 4

A. tauschii L. chinensis

0.59 * 0.57

*

0.0163567 0.0118781

N1QT70

L-ascorbate peroxidase Thioredoxin-dependent peroxidase Pathogenesis-related protein 1

14.93/4.61

19.13

6.43

1

A. tauschii

0.53

**

0.0042774

R7W736

Peroxidase 66

31.87/6.21

193.06

19.74

5

A. tauschii

0.51

**

0.0023491

M8ATB2


17.06/5.30

234.36

45.00

6

A. tauschii

0.50

**

0.0017802

M8CFS1

Protein SRG1

40.16/4.96

64.19

5.92

2

A. tauschii

0.49

**

0.0012745

M8C7Y6 A7VL26

31.06/9.28 17.50/5.72

38.99 53.66

9.03 11.24

2 2

A. tauschii T. aestivum

0.45 ** 0.43

**

0.0003557 0.0001399

M7ZC09

Oxidoreductase GLYR1 Late embryogenesis abundant protein Peroxidase 12

43.64/7.85

51.54

4.88

2

T. urartu

0.40

O82715

Pathogenesis related protein-1.2

18.79/7.31

161.90

38.15

4

T. aestivum

0.31

**

1.36E-07

**

4.74E-05

Carbohydrate metabolism M7ZPE9

Phosphoglycerate mutase gpmB

89.40/6.92

59.94

4.50

3

T. urartu

2.61

**

7.95E-05

M8C3S5

Malate dehydrogenase (NADP)

41.98/5.53

197.75

25.39

8

A. tauschii

2.33

**

0.0005183

M7YQ36

Malate dehydrogenase [NADP] 1

46.59/7.59

202.62

22.38

8

T. urartu

2.05

**

0.003324

M7YI34

Isocitrate dehydrogenase [NADP]

47.38/6.39

562.00

46.45

18

T. urartu

1.94

**

0.0065195

Q8L6L3 R7WAR0

Glycosyltransferase Isocitrate dehydrogenase (NADP) NADH-ubiquinone oxidoreductase chain 1 Pectinesterase Caffeic acid 3-Omethyltransferase Phosphorylated carbohydrates phosphatase Epidermal p-coumarate 3hydroxylase Glucose-6-phosphate isomerase

31.46/5.26 45.84/6.39

57.64 618.46

8.71 52.32

2 19

H. vulgare A. tauschii

1.75 * 1.70

*

0.0218032 0.0305223

36.05/8.21

15.30

4.31

1

P. edulis

1.68

*

0.0340011

*

Xylose isomerase Glyceraldehyde-3-phosphate dehydrogenase Sucrose synthase

B4XAP3 M0WJS2 R7W8J5 M8CYV8 B5KPW0 M0UWB1 M8AYY4 O22387 C5JA75

25.02/6.39 36.14/6.07

50.83 101.42

8.30 12.01

1 3


1.67 * 1.66

0.0371307 0.0395785

28.63/5.11

23.34

5.73

1

A. tauschii

1.62

*

0.0497209

19.28/5.94

35.33

6.47

1

T.monococcum

1.60

*

0.0544579

34.13/4.96

164.55

25.08

5

H. vulgare

0.64

*

0.0416929

50.13/5.40 28.31/9.57

85.49 457.90

11.33 42.91

5 10

A. tauschii O. sativa

0.61 * 0.56

*

0.0280002 0.0101261

92.17/6.25

1061.73

35.15

23

H. vulgare

0.53

**

0.0048914

26


Page 27 of 45

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Continued Table 1 MW/pIb

Accession Protein species noa Carbohydrate metabolism H9B8E3 Glyceraldehyde-3-phosphate dehydrogenase-like protein H9ZWZ6 Phosphoglycerate kinase

33.62/5.74

Scorec

472.17

Coverage (%) 36.39

Nup.d

10

Species

Ratioe

M. sinensis

0.52

**

0.0032903 0.0022966

p-value

31.04/5.07

611.00

49.66

13

T. carthlicum

0.51

**

Q1XH05

Beta-glucosidase

64.44/6.04

277.76

15.64

8

T. aestivum

0.41

**

8.11E-05

Q6YZX6

Aconitate hydratase

98.02/6.01

461.09

19.15

14

O. sativa

0.29

**

3.36E-08

Proteins metabolism P14655

Glutamine synthetase

46.61/6.34

212.70

23.36

6

O. sativa

2.56

**

0.0001074

M8AGJ9

40S ribosomal protein S18

17.65/10.74

234.84

32.89

5

T. urartu

2.08

**

0.0026705

N1QUW7

Basic 7S globulin 2

32.70/9.06

48.31

12.22

2

A. tauschii

1.98

**

0.0052196

M8C7D4

Adenosine kinase 2

37.19/5.10

365.67

36.05

10

A. tauschii

1.84

*

0.0124001

M8BXN4

Serpin-ZX

28.93/5.34

13.64

4.94

1

A. tauschii

1.83

*

0.0132515

N1QP48

Nitrogen regulatory protein P-II 2

12.28/5.58

29.01

9.82

1

A. tauschii

1.81

*

0.0154793

M8BPS6 M7Z5S3

65.83/8.54 72.00/6.61

50.36 36.14

7.40 4.69

2 2

A. tauschii T. urartu

1.79 * 1.79

*

0.0175121 0.0176071

F2DBJ6

Seryl-tRNA synthetase Molybdopterin biosynthesis protein CNX1 Amidophosphoribosyltransferase

45.55/6.65

29.36

5.49

2

H. vulgare

1.78

*

0.0188839

M0W697

Peptidyl-prolylcis-transisomerase

18.16/8.29

16.91

8.54

1

H. vulgare

1.77

M7Z6I6


16.36/10.56

210.96

45.70

6

T. urartu

1.74

M8AZH6 M8A347

11.78/7.34 19.91/5.43

67.67 10.08

40.19 8.19

4 1


27.88/5.82 100.86/8.00

35.36 43.08

8.33 2.16

2 2

T. urartu A. tauschii

65.99/9.06

19.62

3.67

1

A. tauschii

1.63

Q9SWZ5

Cysteine proteinase inhibitor 1,2-dihydroxy-3-keto-5-Methylthiopentene dioxygenase 4 Protease Do-like 5 LRR receptor-like serine/ threonine- protein kinase H/ACA ribonucleoprotein complex subunit 4 Glycyl-tRNA synthetase 2 Acyl-CoA dehydrogenase family member 10 Secretory protein

M4PPG8

M7ZVH9 M8BSL7 M8B1T7 M7ZJ32 M8CK65

*

0.0191517

*

0.0229939

1.66 * 1.66

*

0.0391666 0.0380877

1.65 * 1.64

*

0.0414219 0.042975

*

0.0454084

*

101.85/5.21 83.64/8.15

33.68 63.97

4.29 2.26

2 2

T. urartu A. tauschii

1.61 * 0.65

0.0519426 0.0491734

24.20/9.31

78.00

14.29

3

T. aestivum

0.63

*

0.0370982

Glycerol kinase

57.24/5.63

112.65

6.74

3

T. aestivum

0.63

*

0.0386316

M7YQD5

Patatin group M-3

45.02/7.31

51.73

6.33

1

T. urartu

0.63

*

0.0364323

M7ZZZ8

Subtilisin-like protease

13.33/7.27

9.16

8.94

1

T.urartu

0.62

*

0.0303958

H6BDK9

60S ribosomal protein L44

8.74/10.39

49.61

32.47

3

L. perenne

0.62

*

0.0286602

M7Z011

Elongation factor 1-beta

30.56/4.83

144.52

16.20

4

T. urartu

0.61

*

0.0267757

N1QUN6

Histone

15.25/11.39

193.54

27.08

3

A. tauschii

0.61

*

0.0275118

R7WC97

60S ribosomal protein L19-2

25.96/11.06

136.15

16.81

3

A. tauschii

0.60

*

0.0196494

M8BFV8 M0VS37

Villin-2 Eukaryotic translation initiation factor 3 subunit L Mitochondrial-processing peptidase subunit alpha SAP domain containing protein

42.79/5.81 45.51/6.99

14.75 116.57

8.79 11.86

2 4

A. tauschii H. vulgare

0.59 * 0.59

*

0.0181355 0.0175315

49.94/7.46

148.20

15.74

4

T. urartu

0.59

*

0.0166826

7.42

1.96

1

B. distachyon

0.59

*

0.0168266

16.18/10.70 9.59/8.35

220.75 115.41

29.68 41.11

5 3

H. vulgare T. dicoccoides

0.58 * 0.57

*

0.0141025 0.0114986

M7ZBV9

Histone H2A Bowman-Birk type woundinduced protease inhibitor 40S ribosomal protein S2-3

29.47/9.74

255.29

31.02

9

T. urartu

0.57

*

0.0115396

M8A407

60S acidic ribosomal protein P2B

11.50/4.41

36.46

10.62

2

T. urartu

0.57

*

0.011574

M8AQF1

Aspartic proteinase nepenthesin-2

33.08/7.65

13.97

4.42

1

T. urartu

0.56

**

0.008975

M7YG38

Histone H2B.2

15.46/10.08

165.80

35.21

5

T. urartu

0.55

**

0.0073084

F2E328

Histone H2B

16.23/10.02

244.79

40.67

6

H. vulgare

0.55

**

0.006883

Q94KK0

Histone H2B-4

8.20/10.14

20.40

14.67

1

L. perenne

0.55

**

0.0071513

B6SP50


7.41/10.80

55.94

18.46

1

Z. mays

0.55

**

0.0068652

M7YWY6

Asparaginyl-tRNA synthetase

54.62/6.44

249.42

22.61

10

T. urartu

0.52

**

0.0034106

P15871

Histone H1.1

2.71/6.55

25.46

36.00

1

T. aestivum

0.52

**

0.0028215

M8A2Q5

20 kDa chaperonin

29.69/7.28

185.65

30.80

5

T. urartu

0.51

**

0.0023272

6L507

Histone H2B

13.74/9.94

141.08

34.68

4

O. sativa

0.49

**

0.0013361

M7ZFJ6 C3SA89 F2CVZ1 B7SKZ2

77.81/4.75

27



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 45

Continued Table 1 MW/pIb

Accession Protein species noa Proteins metabolism

Scorec

Coverage (%)

Nup.d

Species

Ratioe

p-value

Q7X729

Acidic ribosomal protein P2

11.45/4.41

149.67

46.43

4

T. aestivum

0.49

**

0.0012572

M7ZA68

Serine carboxypeptidase-like 51

59.66/6.24

5.73

3.19

1

T. urartu

0.45

**

0.0004021

Q84VE1 M7YW64

Adenosylhomocysteinase Alanine-glyoxylate aminotransferase 2-like protein 3 60S ribosomal protein L27a-3

53.18/5.90 48.29/8.56

544.01 2.43

34.02 4.75

15 1

O. sativa T. urartu

0.42 ** 0.40

**

9.01E-05 4.46E-05

16.01/10.67

159.78

47.59

7

T. urartu

0.39

**

2.31E-05

46.24/8.94 66.29/4.93

370.66 646.17

23.49 30.92

10 19

Z. mays T. urartu

0.38 ** 0.37

**

1.14E-05 5.20E-06

Q8VX00

Elongation factor 1-alpha Stromal 70 kDa heat shockrelated protein 60S ribosomal protein L13

16.05/10.33

39.94

22.54

2

O. sativa

0.34

**

1.51E-06

M8BML0

Coatomer subunit delta-1

59.83/6.01

199.12

17.13

8

A. tauschii

0.34

**

1.39E-06

F2DAZ1 N1QY12

Proteasome subunit alpha type Heat shock cognate 70 kDa protein Patatin group A-3

27.26/8.31 49.66/8.10

123.63 97.38

17.27 6.44

3 3


0.24 ** 0.24

**

2.88E-10 4.26E-07

41.38/6.67

29.56

3.33

1

A. tauschii

0.19

**

1.08E-13 0.0327932

M8A040 Q9M7E3 M7ZCX6

M8BFN4

Energy production A9L9W7

ATP synthase subunit beta

51.42/5.20

1344.44

68.07

24

H. annuus

0.62

*

F2DI09

V-type proton ATPase subunit F

14.37/5.57

46.00

16.15

2

H. vulgare

0.53

**

0.0046522

A9L9W0

ATP synthase subunit beta

52.90/5.21

1344.44

66.12

24

G. ventricosum

0.38

**

9.74E-06

D2K756

ATP synthase 6 kDa subunit

5.93/10.17

19.47

21.57

1

A. crassa

0.36

**

4.20E-06

56.63/9.01 30.36/8.15

21.37 242.75

1.74 20.00

1 4

Z. mays T. aestivum

0.64 * 0.63

*

0.044599 0.036947

Transportation B6T9F4 A7J2I2 M7YS75

Sugar transport protein 14 Plasma membrane intrinsic protein Aquaporin PIP1-5

17.14/6.15

98.46

18.47

2

T. urartu

0.63

*

0.0342208

M8AGD8

Monosaccharide-sensing protein 2 79.07/4.96

158.94

15.61

7

T. urartu

0.63

*

0.0328867

D6PY83

Aquaporin

30.40/7.01

89.56

12.41

3

H. vulgare

0.57

*

0.0128049

M7Z4T9

Aquaporin TIP2-2

25.17/5.69

42.91

4.44

1

T. urartu

0.52

*

0.0030434

Q93WQ8

Inorganic phosphate transporter

57.34/8.50

25.43

2.10

1

T. aestivum

0.49

*

0.0012805

M8B1H6 M8A5M8

Sugar transport protein 1 Inorganic phosphate transporter 1-2

49.24/9.69 57.40/8.63

21.57 32.81

1.77 2.10

1 1


0.45 ** 0.35

**

0.0003105 2.05E-06

a Accession number in Uniprot database. b Protein MW/pI (kDa), MW and pI of predicted protein/molecular mass of predicted protein. c The proteins that had a statistically significant (p

Hg-Responsive Proteins Identified in Wheat Seedlings Using iTRAQ

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