Comparative Proteomic Analysis Reveals That Antioxidant System

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Comparative proteomic analysis reveals that antioxidant system and soluble sugar metabolism contribute to salt tolerance in alfalfa (Medicago sativa L.) leaves Yanli Gao, Ruicai Long, Junmei Kang, Zhen Wang, Tiejun Zhang, Hao Sun, Xiao Li, and Qingchuan Yang J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00521 • Publication Date (Web): 15 Oct 2018 Downloaded from http://pubs.acs.org on October 21, 2018

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Comparative proteomic analysis reveals that antioxidant system and soluble sugar metabolism contribute to salt tolerance in alfalfa (Medicago sativa L.) leaves Yanli Gao†‡, Ruicai Long†‡, Junmei Kang†, Zhen Wang†, Tiejun Zhang†, Hao Sun†, Xiao Li†, Qingchuan Yang†*

Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, No.2 Yuanmingyuan West Road, Beijing



100193, P. R. China

ABSTRACT: Soil salinity poses a serious threat to alfalfa (Medicago sativa L.) productivity. To characterize the molecular mechanisms of salinity tolerance in Medicago, the comparative proteome of leaves from Medicago sativa cv. Zhongmu No.1 (ZM1, salt-tolerant) and Medicago truncatula cv. Jemalong A17 (A17, salt-sensitive) was performed using iTRAQ approach. A total of 438 differentially expressed proteins (DEPs) were identified, among which 282 and 120 DEPs were specific to A17 and ZM1, respectively. In salt-tolerant ZM1, key DEPs were primarily enriched in antioxidant system, starch and sucrose metabolism, and secondary metabolism. ZM1 possessed a greater ability to remove reactive oxygen species and methylglyoxal under salt stress, as demonstrated by enhancement of the antioxidant system and secondary metabolism. Moreover, ZM1 orchestrated starch and sucrose metabolism to accumulate various soluble sugars (sucrose, maltose, glucose and trehalose), which in turn facilitate osmotic homeostasis. Salt stress dramatically inhibited photosynthesis of A17 due to the downregulation of the light-harvesting complex and photosystem II-related protein. Quantitative analyses of photochemical efficiency, antioxidant enzyme activities, hydrogen peroxide, malondialdehyde, and soluble sugar contents were consistent with the predicted alterations based on DEPs functions. These results shed light on our understanding of the mechanisms underlying the salt tolerance of alfalfa

KEY WORDS: Medicago sativa, Medicago truncatula, Leaves, iTRAQ, Salt tolerance

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INTRODUCTION

Salinity has negative effects on the survival of plants. The proportion of salinized soil is estimated to be more than 6 % of global land area, according to data from FAO (Food and Agriculture Organization of the United Nations) 1. Moreover, salinity often generates osmotic stress and ion toxicity, which in turn cause nutritional deficiency and oxidative stress, further contributing to plant growth restriction, wilting or even death 2-4. Thus, salt stress is a limiting factor for improving crop yield, and the enhancement of salt tolerance is therefore an important focus of current crop breeding programs. Plants have developed complex mechanisms to cope with salt stress, including physiological and biochemical changes. These changes involving photosynthesis and energy metabolism, selective ion uptake and exclusion, the antioxidant system and osmotic adjustment play a critical role in salt tolerance

5-7.

Moreover, transcriptional changes and their

corresponding changes in protein profiles have been found to be directly involved in these processes. Recently, an increasing number of studies have focused on clarifying salt tolerance mechanisms using proteomic analysis 8-13. The salt-responsive proteins associated with redox homeostasis, ion uptake and signal transduction are candidates for developing genetically engineered salt-tolerant crops. Alfalfa (Medicago sativa L.), a well-known legume forage crop, is widely planted around the world due to its excellent agronomic traits such as higher yield and protein content. However, as alfalfa growth and yield are restricted under salt conditions, an extensive understanding of salt-responsive mechanisms of Medicago is required to enhance salt tolerance. Previous studies have mainly focused on transcriptome analysis of gene expression in alfalfa roots and leaves under salt stress and further identified various salt-responsive genes, including transcription factors and miRNAs 14-17. Although these data provide potential targets for engineering breeding, the changes in gene expression levels may neither correspond directly to protein expression levels nor to the growth phenotypes in alfalfa. Because the final biological processes involved in adaption to salt stress depend on protein functions, large-scale screening of salt responsive proteins using comparative proteomic analysis is a priority. However, studies on the proteomic responses of alfalfa tissues to salt stress are limited. Previous studies focused on changes in protein profiles of alfalfa seedling roots and germinated seeds under salt stress using the two-dimensional gel electrophoresis (2-DGE) approach 18, 19.

Although leaves are also of great importance for adaptation to salt conditions, few reports are available on how 2

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alfalfa leaves respond to salt stress, particularly via proteomic alterations. M. sativa L. cv. Zhongmu No.1 is widely cultivated in North China and is employed as a salt-tolerant cultivar in laboratory experiments 17, 20. M. truncatula L. cv. Jemalong A17 is an annual forage plant that is sensitive to salinity 3.

The proteomic information for alfalfa is established on the basis of a M. truncatula database. M. sativa and M.

truncatula a share similar morphological appearance and close genetic relationship 21, 22, while they show diversity in adaption to salinity. We have previously conducted comparative a proteomic analysis of M. sativa and M. truncatula seedling roots in response to salinity stress, using a 2-DGE approach and identified diverse salt response mechanisms 3.

Compared to the gel-based method, isobaric tags for relative and absolute quantification (iTRAQ) has technical

advantages, in terms of both accuracy and reliability of protein quantification, as well as identification of lowabundance proteins

23, 24.

Recently, iTRAQ-based proteomic studies have focused on elucidating salt-adaptive

mechanisms in legume crops such as soybean, due to its advantage

25, 26.

Nevertheless, this advanced approach has

seldom been employed to investigate salt tolerance in alfalfa leaves. In the present study, we analyzed the leaf proteomes of M. sativa and M. truncatula under salt stress using an iTRAQbased approach. The results revealed physiological responses based on identification of key differentially expressed proteins (DEPs). Together with supporting data from leaf ultrastructure, transcript analysis, and enzyme activity assays, these results shed light on our understanding of complex molecular mechanisms underlying salt tolerance in M. sativa. From our findings, we expect that key DEPs will be selected as candidate targets for genetic improvement of salt tolerance.

MATERIALS AND METHODS

Plant material and growth conditions

M. sativa L. cv. Zhongmu No.1 (ZM1) and M. truncatula L. cv. Jemalong A17 (A17) were used throughout the study. ZM1 is a salt-tolerant cultivar (2n = 4 x = 32) that is employed to breed alfalfa varieties in China 27. Jemalong A17 is considered to be a salt-sensitive cultivar (2n = 2 x = 16). Seeds of ZM1 and A17 were obtained from the Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China and the Institute of Botany, Chinese Academy of Science, Beijing, China, respectively. The seeds were placed in Petri dishes with wet double-layered filter

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paper. The Petri dishes were then incubated in a growth chamber under 16 h light (300 µmol m-2 s-1) at 25°C and 8 h dark at 22°C, with relative humidity of 60%. Seven-day-old seedlings were transferred to Hoagland nutrient solution (pH 6.0), which was renewed every three days.

Treatments

After two weeks of growth, ZM1 and A17 seedlings were treated as follows: (1) plants were cultivated in control conditions (Hoagland’s solution with 0 mM NaCl) and (2) plants were cultivated in saline conditions (Hoagland’s solution with 100 mM NaCl). At 1, 3, 5 and 7 days after salt treatment, seedling leaf samples were obtained for analysis of the relative water content (RWC), relative electrolyte leakage (REL) and total chlorophyll content. Each treatment at every time point included three biological replicates. The leaves were excised at five days after salt treatment, then snap frozen in liquid nitrogen. The leaf samples were stored at -80°C until proteomic, transcriptional, and physiological analyses were performed.

Transmission electron microscopy

Leaf fragments were immersed in potassium phosphate buffer (0.1 M, pH 7.4) containing 4% glutaraldehyde and vacuum-infiltrated until the leaf fragments sunk. Thereafter, the samples were washed three times with PBS buffer, post-fixed in 1% OsO4 [osmium (VIII) oxide] and rinsed three times with PBS buffer (0.1 M, pH 7.4). The samples were then dipped in ethanol for dehydration and washed with absolute acetone. Finally, the samples were embedded in epoxy resin. Ultrathin sections were obtained using an LKB8800 III ultramicrotome and examined under a transmission electron microscope (Hitachi H-7500).

Physiological analysis

Leaf tissues collected at each time point from both control and salt-stressed plants were used to measure leaf RWC, REL and total chlorophyll content. Leaf RWC and REL were measured following the method described in our previous research 3. Total chlorophyll content was determined according to a method described by Kahlaoui 28. Briefly,

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chlorophyll extraction was performed using a solution of acetone/ddH2O at a ratio of 4:1. After centrifugation, the extraction solution was transferred into a 5 mL centrifuge tube to determine its absorbance. The chlorophyll content was calculated according to a method described by Porra 29. After five days of treatment, physiological characteristics were evaluated. These measurements were conducted with three replicates. Photochemical efficiency (Fv/Fm) was measured with a fluorescence meter (Fim 1500, Dynamax, Houston, TX, USA) after leaves were adapted to dark conditions for 20 min using leaf clips

30.

Malondialdehyde

(MDA), hydrogen peroxide (H2O2), reduced glutathione (GSH) and oxidized glutathione (GSSG) contents as well as superoxide dismutase (SOD), peroxidase (POD) and glutathione peroxidase (GPX) activities, soluble sugar content, and trehalose-6-phosphate synthase (TPS) activity were measured via ELISA (Quanzhou Collodi Biotechnology Co. Ltd., China). All ELISAs were performed following the manufacturer’s instructions using an RT-6100 Microplate Reader (Rayto, USA).

Protein extraction

Five days after salt treatment, leaf tissues were harvested for protein extraction. Three biological replicates were maintained for each treatment, with one replicate containing the leaves of 10-15 seedlings. Total protein was extracted from leaves according to the acetone extraction method 31. In brief, protein extraction was conducted using a lysis buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris-HCl and 1% protease inhibitor cocktail. After centrifugation (20,000 ×g) for 30 min at 4°C, the supernatants were transferred into centrifuge tubes with four volumes of precipitation solution (trichloroacetic acid: acetone, 1:9) and stored at -20°C for 24 h. The precipitate was washed three times with cold acetone for and then resuspended in the lysis buffer. Quantification of proteins was conducted via the Bradford assay 32.

Protein digestion and iTRAQ labeling of samples

From each sample, 100 µg protein was mixed with lysis buffer containing 25 mM DTT and 50 mM iodoacetamide. The mixture was transferred into a 10 K centrifugal unit (Millipore, USA). Thereafter, the filters were washed three times using 100 μL dissolution buffer (20 mM triethylammonium bicarbonate), before being centrifuged at 10,000 ×g

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for 10 min. Subsequently, the proteins were digested at 37°C for 12 h with 2 μg trypsin (Promega, Madison, WI, USA) at a ratio of 1:50 (trypsin: protein). The resulting peptides were labeled with 8-plex iTRAQ tags (Applied Biosystems, USA). The details are as follows: sample A17-CK” (113 tag), sample “A17-S” (115 tag), sample “ZM1-CK” (117 tag) and sample “ZM1-S” (118 tag); the A17-CK, A17-S, ZM1-CK and ZM1-S samples were also pooled (121 tag). Three independent biological experiments were conducted. The labeled mixture was incubated at room temperature for 2 h and vacuum-dried.

High pH reversed-phase (HpRP) chromatography

High pH reversed-phase chromatography was conducted for fractionation of the iTRAQ-labeled peptides using RIGOL L-3000 HPLC system (RIGOL, Beijing, China). Specifically, the peptides were suspended in eluent A (acetonitrile: ddH2O, 2: 98, pH = 10). After centrifugation, the supernatants were transferred onto the Durashell C18 column (5 μm, 0.46 x 25 cm, 100 Å, Agela, DC952505-0) and then washed stepwise with eluent B (acetonitrile: ddH2O, 98: 2, pH = 10). Peptide fractionation was carried out using linear gradients from 5% to 95% with eluent B (acetonitrile/ddH2O 98: 2, pH = 10) for 50 min at a flow rate of 300 nL/min. The system was equilibrated with 5% eluent B for 10 min. Forty fractions were collected at 1.5-min intervals and pooled into 10 final samples, which were dried using a vacuum centrifuge.

LC-MS/MS analysis

LC-MS/MS analysis was conducted with an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) combined with an EASY-nLC 1000 nano system (Waltham, MA, USA). The dried fractions were resuspended in a loading buffer (0.1% formic acid). The peptides separation was performed using a binary solvent system including mobile phase A (0.1% formic acid) and mobile phase B (0.1% formic acid and 80% acetonitrile) at 300 nL/min flow rate. Linear gradients of mobile phase B was set from 4% to 100% for 120 min. The eluent was submitted to the Orbitrap Fusion Lumos MS system. EASY spray voltage was set at 2.2 KV and temperature at 300°C. The full scan sequence started with MS spectrum (automatic gain control (AGC) target 4E6, resolution 60,000 (FWHM), maximum injection time 50 ms, scan range 350-1500 m/z). The MS/MS spectrum

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parameters were set at AGC target 5E5, normalized collision energy 35, resolution 30,000 (FWHM); and maximum injection time120 ms.

Database searching, protein quantitation and functional analysis

All MS and MS/MS spectrum data were analyzed using ProteoWizard (version 3.0.8789). The MS/MS spectra were searched using the Mascot search engine against the NCBI M. truncatula database (57,693 entries, 20 Dec. 2016). For spectrum identification, a peptide fragment with two missed cleavages, ion mass tolerance of 20 mmu, and parent ion tolerance of 10 ppm were permitted. Carbamidomethylation at cysteine was defined as a fixed modification. Oxidation at methionine was defined as a variable modification. The proteomic software Scaffold (Scaffold_4.6.2, Inc., Portland, OR, USA) was used for protein identification. Peptide identification was considered to be successful if the false discovery rate (FDR) was less than 0.01 more than two peptides above 99.0% probability. The relative expression levels of all identified proteins were quantified according to channels 115/113 and 118/117, corresponding to A17-S/A17-CK and ZM1-S/ZM1-CK, respectively. Proteins with fold-change ratios > 1.20 or < 0.83 and P-values < 0.05 were selected as DEPs. Blast2GO software (http://geneontology.org/) was employed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses (http://www.genome.jp/kegg/) were performed on the identified proteins. Hierarchical clustering and heat map generation for the proteins were performed with Multi Experiment Viewer (MeV) 33. Prediction of protein-protein interactions (PPI) was performed using the STRING database (http://string-db.org/).

Real-time PCR analysis

The plant materials used for qRT-PCR analysis came from the same batch of materials employed for proteomics. Total RNA of seedling leaves was extracted using the MiniBEST RNA Extraction Kit (TaKaRa, Japan). cDNA was obtained using the PrimeScript™ RT reagent Kit with gDNA Eraser (RR047A, TaKaRa). qRT-PCR assays were performed with the ABI-7500 Real-Time PCR System (ABI, USA) and the SYBR® Premix Ex Taq™ kit (RR820A, TaKaRa). Relative mRNA expression levels were quantified using the 2-△△CT method

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and the β-actin gene was

selected as the reference gene for normalization. All primers are shown in Table S1. Each experiment included three

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biological replicates.

Statistical analysis

Student’s t-test was performed to determine the differences in mRNA and protein expression levels. Data on the physiological parameters were analyzed by one-way ANOVA and Duncan's tests at a P < 0.05 using SPSS v20.0.

RESULTS

Physiological responses under salt stress

Exposure of seedlings to salt stress resulted in changes in RWC, REL and total chlorophyll content of Zhongmu No.1 (ZM1) and Jemalong A17 (A17) (Fig. 1). Leaf RWC decreased in both species during days 1-7, with that of ZM1-S being significantly higher than that of A17 after five days of treatment. REL was 50% greater in A17 than in ZM1 under salt treatment after five days. The chlorophyll content of ZM1 was stable during salt treatment. Conversely, A17 showed a sharp decline in chlorophyll content following exposure to salt stress after five days. These results indicate that ZM1 is more salt-tolerant than A17, which is similar to findings from our previous study 3. Furthermore, analysis of these physiological indices during days 1-7 revealed that A17 was susceptible to salt stress following five days of treatment. For this reason, five days of treatment was used for selecting leaves for further comparative proteomic and physiological analyses.

Transmission electron microscopy of chloroplasts of A17 and ZM1 under salt stress

The ultrastructure of chloroplasts of leaves from A17 and ZM1 showed different changes after five days of salt stress (Fig. 2). In a control environment, the chloroplasts and thylakoids were clear and intact in A17 and ZM1 (Fig. 2 A and C). Under salt stress, the chloroplasts swelled in both species (Fig. 2 B and D). Severe damage was detected in A17 leaves, and the membranes of the chloroplasts and thylakoids showed a disarrayed arrangement under salt stress (Fig. 2 B). 8

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Quantitative identification of proteins and hierarchical clustering

Based on proteomic analysis, 37567 ± 474 exclusive unique spectra and 32013 ± 413 unique peptides were identified from the raw data and employed for quantitation (FDR < 1% and protein identification probability > 99.0%). A total of 4251 proteins with more than two unique peptides were identified. Amongst these proteins, 23 were 6-10 kDa, 3822 were 11-100 kDa and 406 were >100 kDa (Table S2). To identify differentially expressed proteins (DEPs), we classified the results of iTRAQ analysis into two different ratios containing AS/AC (salt-stressed A17 plants versus the control) and ZS/ZC (salt-stressed ZM1 plants versus the control). We defined DEPs as those with a P value < 0.05 and with a fold-change > 1.200 or < 0.833 between two comparison groups. Hierarchical clustering analysis of all DEPs revealed expression patterns (Fig. 3 A). Three replicates of the control and salt-stressed samples were performed for both species. Correlation coefficients (CCs) of the three replicates from the four experiments (AC, AS, ZC and ZS) are shown in Fig. S1. All of these CCs were more than 0.959, indicating that the data from the replicates were statistically reproducible. In total, 438 DEPs were identified in both species in response to salinity (Fig. 3 B). There were 318 (208 increased and 110 decreased in abundance) and 156 (81 increased and 75 decreased in abundance) DEPs in AS/AC and ZS/ZC, respectively (Table S3). Regarding common DEPs, 30 DEPs showed the same trend, whereas six DEPs presented the opposite trend. Notably, 282 and 120 DEPs were specific to A17 and ZM1, respectively (Table S4).

Functional categories of DEPs

To gain insight into the functional categories of the DEPs, gene ontology (GO) analysis of DEPs was performed for A17 and ZM1. The DEPs were grouped into three categories: biological process (BP), cellular component (CC) and molecular function (MF) (Fig. 4, Table S5). The results showed similar functional annotations for A17 and ZM1, although the annotation order based on the number of DEPs was different. The first three BPs represented metabolic process, cellular process and single-organism process in both A17 and ZM1. The fourth of the functional categories represented localization in A17, but biological regulation in ZM1. The prominent CC categories were cell and cell part for both A17 and ZM. For MF, the DEPs were predominantly distributed in catalytic activity and binding

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categories in A17 and ZM1, respectively. The remaining main MF categories were transporter activity, structural molecule activity and electron carrier activity in A17 and structural molecule activity, antioxidant activity and molecular function regular for ZM1. KEGG pathway analysis of DEPs showed different enrichment results for ZM1 and A17 (Table S6). The KEGG pathways of A17 were significantly enriched (P < 0.05) in metabolic pathways, amino sugar and nucleotide sugar metabolism and photosynthesis-antenna proteins and so on. On the other hand, KEGG pathways including ribosome, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism and aminoacyl-tRNA biosynthesis were significantly enriched in ZM1. On the basis of the KEGG and GO analyses as well as information from the literature 6,

we focused on the main functional classifications in response to salt stress: photosynthesis, antioxidant system,

secondary metabolism, starch and sucrose metabolism, energy metabolism, protein synthesis, signal transduction, and transportation (Table S7).

Analysis of protein-protein interactions

Protein-protein interactions (PPI) were assessed using the String 10.5 database (organism: Arabidopsis thaliana) with a high confidence score of 0.7. All the DEPs shown in Table S7 were analyzed. Eight groups of proteins were identified (Fig. S2). One group included LHCB4.3, LHB1B1, LHCB4.2, PSBC, PSBE, PSBD, PSBB, ATPF, ATPA, PDE334 and RBCL, which are important for photosynthesis. The group including TPS5, SUS4, SPS3F and AT4G33070 (PDC) is related to starch and sucrose as well as energy metabolism and the group including APL3, GBSS1, DEP2, SBE2.1 SEX4, GWD2, MPK3, SOBIR1, LSF2 and PBCP is related to starch and sucrose metabolism and signal transduction. The fourth group included GAD, ASN1, ALDH12A1 and P5CS2, which are related to γ-aminobutyric acid (GABA), aspartate and proline metabolism. In the five-protein network group, PRX52, OMT1 and ELI3-1 are related to phenylpropanoid biosynthesis. The sixth group involved proteins related to translation: BBC1, AT5G27850 (RPL18), AT1G70600 (RPL23AB), AT5G04800 (RPS17), AT1G48830, and RPL27AB. Finally, groups of interacting proteins, FSD2, GPX6 and TRX1 are related to antioxidant metabolism, while HSP70 and ROC3 are related to protein folding.

Confirmation of proteomic results by the physiological response of A17 and ZM1 to salt stress

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Changes in the protein profiles of salt-stressed leaves were hypothesized to result in physiological changes. To confirm this hypothesis, we evaluated the photochemical efficiency (Fv/Fm), oxidative damage, ROS-scavenging antioxidant capacities, soluble sugar content, and TPS activity. Salt stress contributed to a decrease in the photochemical efficiency (Fv/Fm) in both species, but to a greater extent in A17 than in ZM1 (Fig. 5A). The contents of malondialdehyde (MDA) and H2O2 were assayed as oxidative damage markers. H2O2 levels increased significantly in both species following salt stress, while it increased more in A17 than in ZM1 (Fig. 5B). Similarly, MDA levels in salt-stressed A17 were higher than those under control conditions, while MDA levels in ZM1 were not affected by salt stress (Fig. 5C). Antioxidant systems for ROS scavenging including both non-enzymatic antioxidants (i.e., GSH and GSSG) and antioxidant enzymes (i.e., SOD, POD and GPX) play a critical role in the cellular redox balance under stress. SOD and POD enzyme activities were increased in A17 and ZM1 under salt treatment, and the increase was significantly higher in ZM1 than in A17 (Fig. 5D and E). Moreover, GPX activity was increased in ZM1 but was unchanged in A17 (Fig. 5F). The data on enzyme activity support the iTRAQ quantification results. Furthermore, in A17, salt stress increased GSH and GSSG contents and decreased the GSH/GSSG ratio, which is a hallmark of oxidative stress; the GSH/GSSG ratio was not significantly changed in saltstressed ZM1 (Fig. 5G, H and I). Soluble sugars are derived from photosynthesis and/or starch and sucrose metabolism in plants; we observed that the soluble sugar content was higher in ZM1 than in A17 and it increased significantly in both species with 100 mM NaCl (Fig. 5J). These results showed that the activity of TPS decreased in A17, while it increased in ZM1 under salt stress (Fig. 5K). The results are in agreement with our iTRAQ observations.

Transcriptional expression analysis of genes encoding DEPs by qRT-PCR

To elucidate the correlation between mRNA transcript levels and protein expression levels, transcriptional analysis of 11 DEPs was conducted via quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in A17 and ZM1 (Fig. 6). The relative gene expression levels for the DREPP plasma membrane protein (PCAP1), sucrose synthase (SUS4) and asparagine synthase (ASN1), which were common DEPs between A17 and ZM1, showed the same pattern as the protein expression levels. The transcript level of the gene encoding thylakoid membrane phosphoprotein 14 kDa (TMP14) coincided with its protein expression level. Interestingly, the expression of the gene encoding the PS II CP47 chlorophyll A apoprotein (PsbB) was significantly upregulated in salt-stressed ZM1. Moreover, the relative

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expression levels of superoxide dismutase (FSD2/SOD), glutathione peroxidase (GPX6), horseradish peroxidase-like protein (PRX52) and gamma-tocopherol methyltransferase (G-TMT) were all increased in ZM1 under salt stress, whereas only PRX52 was significantly increased in A17. Furthermore, the mRNA expression of the trehalose-6phosphate synthase domain protein (TPS5) and the heat shock cognate 70 kDa protein (HSP 70) coincided with their protein expression levels. The discrepancy between the transcriptional level and the corresponding protein abundance of some proteins (PsbB, FSD2) suggests that the encoding genes may be influenced by posttranscriptional regulation.γ

DISCUSSION

To cope with salt stress, plants have developed a series of strategies that are regulated by changes in gene and protein expression, which change in specific metabolism and signaling pathways. In the present study, several physiological traits including RWC, REL and chlorophyll content, were influenced less detrimentally by salt conditions in ZM1 than in A17. These findings suggest that ZM1 has a stronger ability to adapt to saline conditions than A17. To unravel regulatory mechanisms underlying differences in salt tolerance between M. truncatula (A17) and M. sativa L. (ZM1), we performed a proteomic analysis of leaves in response to salt treatments.

Proteins involved in photosynthesis

Photosynthesis is a complicated biological process including both light-dependent reactions and dark reactions known as the Calvin cycle. Light-dependent reactions take place in the light harvesting system, photosystem II (PS II), cytochrome b6f, plastocyanin, photosystem I (PS I) and ATP synthase 35. Plant photosynthesis is affected by salt stress. The vital components of PSII, a complex in the thylakoid membrane, are highly sensitive to salt stress conditions 8. The DEPs in the light harvesting complex II (Lhcb1, Lhcb2, Lhcb4) and PSII (PsbD, PsbC, PsbB and PsbE) were all significantly decreased in A17 (Fig. 7). Moreover, the PPI results showed that these proteins interact with each other. Importantly, the low abundance of Lhcb1, -2, -4, and Lhcbm5 proteins was in line with the loss of chlorophyll pigments in C. reinhardtii cells under salt stress

36,

which may explain why the chlorophyll content of A17 was

significantly decreased under salt stress. Furthermore, PsbB, PsbC and PsbD are considered critical to the watersplitting and oxygen evolution processes of photosynthesis 5. Downregulation of light reaction proteins limits the 12

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chemical energy supplied for dark reactions of photosynthesis, which is in part reflected by downregulation of Calvin cycle enzymes and ATP synthase in A17. For instance, a decrease in RuBisCo activase in A17 suggests reduced RUBP regeneration and inhibition of Calvin cycle activity. This process in turn leads to a decrease in photosynthetic CO2 assimilation and thus a reduced growth rate. This outcome is in line with the results for Kandelia. candel 37, Tangut nitraria 11, and Leymus chinensis 38 under salt stress. ATP synthase (ATP synthase CF0 subunit I, ATPF), F-type H+transporting ATPase subunit alpha (ATPA), and F-type H+-transporting ATPase subunit b (PDE334) in A17 were downregulated under salt stress. These results are similar to observations in Vigna unguiculata 39. The downregulation of ATP synthase might be associated with restriction of ATP synthesis by salt stress. A 14 kDa thylakoid membrane phosphoprotein (TMP14), a novel subunit of PS I, is involved in the interaction with LHCI 40. The increased abundance of TMP14 augments the light-harvesting capacity of PSI. A recent study has shown that overexpression of TMP14 can enhance rice cold tolerance 41. Another novel ATP-dependent zinc metalloprotease FTSH protein (FTSH 8) has been shown to be required for chloroplast biogenesis and PSII repair

42, 43.

The

upregulation of TMP14 and FTSH 8 may contribute to the stabilization of PSI, protection of PSII, and thus the maintenance of photosynthesis in ZM1 under salt stress, which is in agreement with a higher photochemical efficiency (Fv/Fm) and chlorophyll content in salt-stressed ZM1.

Proteins involved in antioxidant mechanisms and secondary metabolism

Salt-induced malfunction of PSII and consequent electron leakage to oxygen result in the accumulation of harmful reactive oxygen species (ROS) 44, which exposes cells to oxidative stress. In addition to ROS, methylglyoxal (MG) is also generated during salt stress

45.

Excess ROS and MG can cause growth inhibition and even cell death. Plants

scavenge ROS and MG by means of various enzymatic and non-enzymatic antioxidants. Six proteins involved in antioxidant and glyoxalase systems in ZM1, including SOD, phospholipid hydroperoxide glutathione peroxidase (GPX6), glutathione S-transferase tau 5 (GSTZ2), horseradish peroxidase-like protein (PRX52/POD) lactoylglutathione lyase-like protein (GLX1), and linoleate 13S-lipoxygenase 2-1 related protein (LOX2) were found to be increased by salt stress, while only two proteins, glutathione S-transferase (GSTF9) and thioredoxin H-type 1 protein (TRX1), were increased by salt stress in A17 (Fig. 7). Consistent with these observations, the activities of three antioxidant enzymes (SOD, GPX and POD) were more enhanced in ZM1 than in A17 following exposure to

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salt. In other studies, the salt-tolerant wild tomato (Lycopersicon pennellii) showed decreased H2O2 and MDA levels and an enhancement of the efficient chloroplast antioxidant system, including SOD, GST, GPX and POD

46.

Glyoxalase I (Gly I), that is involved in the detoxification of MG, is a component of the glyoxalase system 47, and increasing the activities of GlyI and GlyII has been shown to enhance oxidative stress tolerance 48. Our results therefore indicate that salt-tolerant ZM1 possesses a relatively greater ability to remove ROS and MG via antioxidants and detoxifying enzymes, thereby protecting against oxidative damage, as demonstrated by the absence of changes in MDA levels, the GSH/GSSG ratio and reduced REL during salt stress. Isoflavone reductase (IFR) is a key enzyme in isoflavonoid biosynthesis. Isoflavonoid exerts non-enzymatic antioxidant activity against ROS in soybean in response to salt stress

49.

Likewise, gamma-tocopherol

methyltransferase (G-TMT) is involved in the biosynthesis of vitamin E, which is considered as a ROS scavenger. Overexpression of MsTMT gene in alfalfa led to an increase in α-tocopherol in leaves and delayed leaf senescence 50. Caffeic acid O-methyltransferase (COMT) and cinnamyl-alcohol dehydrogenase-like protein, both of which are involved in lignin biosynthesis, were upregulated in ZM1 and A17 under salt stress. These two proteins were also identified in other plants in response to salt stress

9, 51.

Moreover, COMT methylates N-acetylserotonin to produce

melatonin; and the N-acetylserotonin methyltransferase (ASMT) activity of COMT was detected in the Arabidopsis thaliana enzyme, AtCOMT 52. Furthermore, melatonin has been reported to have beneficial effects on enhancing salt stress tolerance in rice 53. However, as caffeoyl-CoA 3-O-methyltransferase was downregulated in A17, the results reveal a complex mechanism of regulation of the phenylpropanoid pathway in A17. Glutamate decarboxylase (GAD), which is involved in aminobutyric acid (GABA) synthesis, was decreased in A17. Its amino acid sequence is closest to that of AtGAD4 and the GAD4 gene was upregulated in Arabidopsis shoots under salinity 54, suggesting that GAD responded to salt stress.

Proteins involved in starch and sucrose metabolism

Many DEPs associated with carbohydrate metabolism accumulated at higher levels in salt-tolerant ZM1 after salt stress. These proteins were significantly enriched in starch and sucrose metabolism (Fig. 7). Sucrose-phosphate synthase family protein (SPS3F) is a key regulatory control point in sucrose biosynthesis. Sucrose synthase (SUS4) is a sucrose-cleaving enzyme that provides UDP-glucose and fructose. Glucose-1-phosphate adenylyltransferase family

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protein (APL3), granule bound starch synthase I, putative (GBSS1) and starch branching enzyme I (SBE2) are together involved in the starch synthesis pathway. Alpha-glucan water dikinase (GWD2) is a global regulator of starch degradation

55

and its increase accelerates the starch catabolism to sugar. Tyrosine phosphatase (SEX4) and dual

specificity phosphatase domain protein (LSF2) are also involved in the starch degradation process 56. Beta-amylase (BMY1), 4-alpha-glucanotransferase (DPE2) and beta-glucosidase (BGLU40) are critical enzymes responsible for accumulation of maltose and glucose biosynthesis. Sucrose, maltose, fructose, and glucose are soluble sugars that act as key osmo-protectants. Our findings suggest that increases in these enzymes may be response for the accumulation of compatible solutes, which in turn facilitates osmotic homeostasis, thus minimizing cellular dehydration under salt stress 57. This is supported by the increase in soluble sugar content observed in ZM1 under salt stress. The levels of soluble sugars were also found to be increased in salt-stressed alfalfa 19. TPS5 is a rate-limiting enzyme involved in the production of trehalose, a soluble disaccharide. The expression of certain TPS genes in transgenic plants confers tolerance to various abiotic stresses, including salt stress 58. An increased abundance of TPS5, including enhanced activity and increased mRNA expression and protein levels in ZM1 following exposure to salt stress contributes to the production of trehalose and subsequently to the maintenance of the osmotic balance. Collectively, these results indicated that ZM1 showed enhanced osmoregulation by accumulation of various soluble sugars (sucrose, maltose, glucose and trehalose) derived from photosynthesis and starch degradation. This enhanced osmoregulation could contribute to the greater salt tolerance of ZM1 than of A17. As a novel salt induced protein, TPS5 will be selected for further investigation in our future work.

Proteins related to protein synthesis and amino acid metabolism

In the present study, a heat shock cognate 70 kDa protein (HSP 70) was upregulated in both lines under moderate salt stress (100 mM NaCl treatment for 5 d). In our previous study, the expression of HSP 70 in roots was upregulated in ZM1, while it was downregulated in A17 under acute salt stress (300 mM NaCl treatment for 8 h). The HSP family plays a crucial role in stabilizing proteins and in the folding of newly synthesized proteins; HSP 70-overexpressing lines exhibit increased salinity tolerance in sugarcane (Saccharum spp. hybrid) 59. Salinity may induce alterations in ammonium accumulation during amino acid metabolism

60.

Proline (Pro)

metabolism is intimately associated with stress adaptation. We found that delta-1-pyrroline-5-carboxylate

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dehydrogenase (P5CDH) and delta-1-pyrroline-5-carboxylate synthetase (P5CS2), which are two key enzymes for proline production, were both increased in A17. Ammonium is re-assimilated into amides by the glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle and can be assimilated into asparagine via asparagine synthetase. Asparagine synthetase (ASN1) was upregulated in ZM1 but downregulated in A17. Interestingly, TaASN1 from wheat was shown to be upregulated by salt stress, osmotic stress, and ABA 61, which correlates with our findings.

Proteins involved in signaling transduction and transportation

A GTPase-like protein A2D, RAB GTPase-like protein A1D, and GTPase-like protein C2B belong to the RAB GTPase family of proteins, which are key regulators of membrane trafficking. A recent study reported that Arabidopsis RABA1 GTPases are required for salinity stress tolerance by mediating the transport between the trans-Golgi network and the plasma membrane 62. The upregulation of these proteins in either A17 or ZM1 during salt stress may indicate the common involvement of RAB GTPase members in stress tolerance. Interestingly, some DEPs related to protein phosphatase signaling were identified. One protein phosphatase 2C-like protein (PP2C) was up-regulated in ZM1 and two were decreased in A17. Arabidopsis overexpressing the OsPP108 gene, which belongs to the PP2C family, exhibited increased salt tolerance compared to that of the wild-types 63. PBCP is another PP2C protein that is related to PSII repair, and PBCP mutants display decreased biomass and altered PSII functionality 64. Interestingly, the V-type proton ATPase (DET3) and H+-ATPase (HA4) were up-regulated in salt-stressed A17 leaves (Fig. 7). DET3 is a vacuolar proton pump that enables the establishment of the electrochemical potential gradient across the tonoplast, which drives vacuolar Na+ sequestration and the active transport of metabolites 65. Similarly, plasma membrane HA4 functions in the maintenance of a low depolarized membrane potential and consequently, the minimization of K+ efflux activated by high salinity 66. The major intrinsic protein (MIP) family transporter is a water channel protein and changes in its expression can be effectively used to maintain water homeostasis and balance under salt stress 67. Interestingly, these DEPs were only found to be up-regulated in salt-stressed A17 leaves, which can be explained by a higher accumulation of Na+, a greater reduction of water transport rates in leaves during salt stress and thus a greater demand for these proteins to maintain ion and water homeostasis. Our results are consistent with those of a previous study indicating the increased expression of vacuolar H+-ATPase in Arabidopsis (a glycophyte) but not in Thellungiella (a halophyte) under salt stress 7.

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CONCLUSIONS

Overall, this study integrates ultrastructural, biochemical and proteomic approaches to identify the different responses of salt-tolerant (ZM1) and salt-sensitive (A17) Medicago species under salt stress. A comparison of physiological parameters (RWC, REL and chlorophyll content) from a series of time points after salt stress suggested that ZM1 is more tolerant to salt than A17. The proteomic results obtained using the advanced iTRAQ approach indicated that the two species show specific responses to salt stress. The most important mechanism underlying salt tolerance in ZM involves the scavenging of ROS and MG to maintain redox homeostasis, which depends on proteins associated with antioxidant and detoxification enzymes, glutathione metabolism, and secondary metabolism. ZM1 accumulates various soluble sugars to maintain osmotic homeostasis by regulating starch and sucrose metabolism. ZM1 augments the light-harvesting capacity of PSI and PSII repair and thus the maintenance of photosynthesis. In contrast, photosynthesis is systematically inhibited in A17, including the inhibition of light-harvesting complex II (LHCII), PSII, photophosphorylation, and the Calvin cycle. Our study clarifies the strategies and molecular mechanisms of ZM1 and A17 leaves involved in the adaption towards salt stress. The present data provide a basis for future studies aimed at enhancing the salt tolerance of alfalfa.

ASSOCIATED CONTENT Supporting Information Table S1, Primers used in transcriptional analysis of DEPs Table S2, Raw data total identified proteins in A17 and ZM1. See “Table S2 excel file”. Table S3, Differentially expressed proteins (DEPs) were identified in A17 and ZM1. See “Table S3 excel file”. Table S4, Number of DEPs identified from A17 and ZM1. Table S5, Gene ontology (GO) analysis of DEPs in A17 and ZM1. See “Table S5 excel file”. Table S6, KEGG pathway enrichment analysis of the DEPs detected in A17 and ZM1. Table S7, Selected key DEPs with different functions in leaves of A17 and ZM1. See “Table S7 excel file”. Fig.S1, Correlate coefficient (CCs) of the three replicates for the four experiments A17 and ZM1. 17

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Fig. S2, Protein interaction network consisting of DEPs in table S7 in salt-stressed A17 and ZM1.

AUTHOR INFORMATION Corresponding Author *Email: [email protected]. Tel: (010) 62815996 Author Contributions Y.L.G., R. C. L. and Q.C.Y conceived the experiment. Y.L.G. and R. C. L. performed the experiment and Y.L.G. wrote the manuscript. J.M.K., Z. W., T. J. Z., X. L. and H. S. contributed to data analysis. ‡ These

authors have contributed equally to this work.

Notes The authors declare no competing financial interest. ACKNOWLEDGEMENTS This work was supported by China Forage and Grass Research System (CARS-34), Agricultural Science and Technology Innovation Program (ASTIP-IAS14) and the National Natural Science Foundation of China (No. 31601993).

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(49) Jia, T.; An, J.; Liu, Z.; Yu, B.; Chen, J., Salt stress induced soybean GmIFS1 expression and isoflavone accumulation and salt tolerance in transgenic soybean cotyledon hairy roots and tobacco. Plant Cell, Tissue and Organ Culture (PCTOC) 2017, 128, (2), 469-477. (50) Jiang, J.; Jia, H.; Feng, G.; Wang, Z.; Li, J.; Gao, H.; Wang, X., Overexpression of Medicago sativa TMT elevates the α-tocopherol content in Arabidopsis seeds, alfalfa leaves, and delays dark-induced leaf senescence. Plant Science 2016, 249, (Supplement C), 93-104. (51) Capriotti, A. L.; Borrelli, G. M.; Colapicchioni, V.; Papa, R.; Piovesana, S.; Samperi, R.; Stampachiacchiere, S.; Laganà, A., Proteomic study of a tolerant genotype of durum wheat under salt-stress conditions. Analytical and Bioanalytical Chemistry 2014, 406, (5), 1423-1435. (52) Byeon, Y.; Choi, G.-H.; Lee, H. Y.; Back, K., Melatonin biosynthesis requires N-acetylserotonin methyltransferase activity of caffeic acid O-methyltransferase in rice. Journal of experimental botany 2015, 66, (21), 6917-6925. (53) Liang, C.; Zheng, G.; Li, W.; Wang, Y.; Hu, B.; Wang, H.; Wu, H.; Qian, Y.; Zhu, X. G.; Tan, D. X.; Chen, S. Y.; Chu, C., Melatonin delays leaf senescence and enhances salt stress tolerance in rice. J Pineal Res 2015, 59, (1), 91-101. (54) Renault, H.; Roussel, V.; El Amrani, A.; Arzel, M.; Renault, D.; Bouchereau, A.; Deleu, C., The Arabidopsis pop2-1 mutant reveals the involvement of GABA transaminase in salt stress tolerance. BMC Plant Biol 2010, 10, 20. (55) Yano, R.; Nakamura, M.; Yoneyama, T.; Nishida, I., Starch-related alpha-glucan/water dikinase is involved in the cold-induced development of freezing tolerance in Arabidopsis. Plant Physiol 2005, 138, (2), 837-46. (56) Schreiber, L.; Nader-Nieto, A. C.; Schönhals, E. M.; Walkemeier, B.; Gebhardt, C., SNPs in genes functional in starch-sugar interconversion associate with natural variation of tuber starch and sugar content of potato (Solanum tuberosum L). G3: Genes, Genomes, Genetics 2014, g3. 114.012377. (57) Parvaiz, A.; Satyawati, S., Salt stress and phyto-biochemical responses of plants - a review. Plant Soil and Environment 2008, 54, (3), 89. (58) Henry, C.; Bledsoe, S. W.; Griffiths, C. A., Differential Role for Trehalose Metabolism in Salt-Stressed Maize. 2015, 169, (2), 1072-89. (59) Augustine, S. M.; Narayan, J. A.; Syamaladevi, D. P.; Appunu, C.; Chakravarthi, M.; Ravichandran, V.; Subramonian, N., Erianthus arundinaceus HSP70 (EaHSP70) overexpression increases drought and salinity tolerance

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in sugarcane (Saccharum spp. hybrid). Plant Science 2015, 232, 23-34. (60) Silveira, J. A.; Viegas Rde, A.; da Rocha, I. M.; Moreira, A. C.; Moreira Rde, A.; Oliveira, J. T., Proline accumulation and glutamine synthetase activity are increased by salt-induced proteolysis in cashew leaves. J Plant Physiol 2003, 160, (2), 115-23. (61) Wang, H.; Liu, D.; Sun, J.; Zhang, A., Asparagine synthetase gene TaASN1 from wheat is up-regulated by salt stress, osmotic stress and ABA. Journal of plant physiology 2005, 162, (1), 81-89. (62) Asaoka, R.; Uemura, T.; Ito, J.; Fujimoto, M.; Ito, E.; Ueda, T.; Nakano, A., Arabidopsis RABA1 GTPases are involved in transport between the trans-Golgi network and the plasma membrane, and are required for salinity stress tolerance. The Plant Journal 2013, 73, (2), 240-249. (63) Singh, A.; Jha, S. K.; Bagri, J.; Pandey, G. K., ABA inducible rice protein phosphatase 2C confers ABA insensitivity and abiotic stress tolerance in Arabidopsis. PloS one 2015, 10, (4), e0125168. (64) Puthiyaveetil, S.; Woodiwiss, T.; Knoerdel, R.; Zia, A.; Wood, M.; Hoehner, R.; Kirchhoff, H., Significance of the photosystem II core phosphatase PBCP for plant viability and protein repair in thylakoid membranes. Plant and Cell Physiology 2014, 55, (7), 1245-1254. (65) Hasegawa, P. M., Sodium (Na+) homeostasis and salt tolerance of plants. Environmental and Experimental Botany 2013, 92, 19-31. (66) Shabala, S.; Pottosin, I., Regulation of potassium transport in plants under hostile conditions: implications for abiotic and biotic stress tolerance. Physiologia Plantarum 2014, 151, (3), 257-279. (67) Kapilan, R.; Vaziri, M.; Zwiazek, J. J., Regulation of aquaporins in plants under stress. Biological research 2018, 51, (1), 4. Figure legends: Fig. 1 Changes in relative electrolyte leakage (A), relative water content (B), and chlorophyll content (C) in the leaves of A17 and ZM1 under salt treatment (100 mM NaCl) and in the control at different time points. ZM1-CK, ZM1 plants under normal conditions; ZM1-S, ZM1 plants under salt stress; A17-CK, A17 plants under normal conditions; A17S, A17 plants under salt stress. Bar represents the mean ± standard deviation (n = 3); letters (abc) represent the level of significance according to one-way ANOVA with Duncan's multiple comparison tests (P ≤ 0.05).

Fig. 2 Ultrastructure of the chloroplasts in A17 and ZM1 leaves. A and C, chloroplasts of A17 and ZM1, respectively,

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under 0 mM NaCl; B and D, chloroplast of A17 and ZM1 respectively, under 100 mM NaCl for five days. Bars in figures represent 1 μm.

Fig. 3 A, Hierarchical cluster analysis of differentially expressed proteins (DEPs) in A17 and ZM1. Red indicates high relative expression, and green indicates low relative expression. AC (A17-CK), A17 plants under normal conditions; AS (A17-S), A17 plants under salt stress; ZC (ZM1-CK), ZM1 plants under normal conditions, ZS (ZM1-S), ZM1 plants under salt stress. 1, 2 and 3 indicate three biological replicates. B, Venn diagram of differentially expressed proteins (DEPs) in salt treated A17 and ZM1 leaves.

Fig. 4 Functional categorization of differentially expressed proteins (DEPs) in A17 and ZM1 leaves. BP, biological process; CC, cellular component; MF, molecular function.

Fig. 5 Physiological analysis of A17 and ZM1 under salt treatment after five days. (A) Fv/Fm; (B) H2O2 content; (C) MDA content; (D) superoxide dismutase (SOD) activity; (E) peroxidase (POD) activity; (F) glutathione peroxidase (GPX) activity; (G) glutathione (GSH) content; (H) oxidized glutathione (GSSG) content; (I) GSH/GSSG ratio; (K) soluble sugar content; (J) trehalose-6-phosphate synthase (TPS) activity. Bar represents the mean ± standard deviation (n = 3); letters (abc) represents the level of significance according to one-way ANOVA with post hoc Duncan's test (P ≤ 0.05).

Fig. 6 Transcript levels of selected DEPs. The present data shown are the mean ± SD of three biological replicates. PCAP1, DREPP plasma membrane protein; SUS4, sucrose synthase; ASN1, asparagine synthetase [glutaminehydrolyzing] protein; TMP14, thylakoid membrane phosphoprotein 14 kDa protein; GPX6, phospholipid hydroperoxide glutathione peroxidase; G-TMT, gamma-tocopherol methyltransferase; PRX 52, horseradish peroxidase-like protein; PsbB, photosystem II CP47 chlorophyll A apoprotein; FSD2, superoxide dismutase; TPS5, trehalose-6-phosphate synthase domain protein; HSP70, heat shock cognate 70 kDa protein. * above bars indicate significant differences at the P ≤ 0.05 level; ** above bars indicate significant differences at the P ≤ 0.01 level; and *** above bars indicate significant differences exist at the P ≤ 0.001 level.

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Fig. 7 Schematic presentation of key biological processes affected in A17 and ZM1 leaves under salt stress. Key DEPs expression levels were marked with symbols of the red (up-regulated) and green (down-regulated) box, respectively. Symbols indicates the log2 DEPs fold change. The intensity of the colors increases as the expression differences increase, as shown in the bar at the bottom. Abbreviations: CAB1, light-harvesting complex I chlorophyll A/B-binding protein 1; LHCB4.1, light-harvesting complex I chlorophyll A/B-binding protein4, LHCB4.2, lightharvesting complex I chlorophyll A/B-binding protein 4; LHCB2, light-harvesting complex I chlorophyll A/B-binding protein 2; PsbC, photosystem II CP43 chlorophyll apoprotein; PsbD, photosystem II protein D2; PsbB, photosystem II CP47 chlorophyll A apoprotein; PsbE, photosystem II cytochrome b559 alpha subunit; ATPA, F-type H+transporting ATPase subunit alpha; PDE334, F-type H+-transporting ATPase subunit b; ATPF, ATP synthase CF0 subunit I; RBCL, ribulose bisphosphate carboxylase large chain domain protein; TMP14, thylakoid membrane phosphoprotein 14 kDa protein; FTSH8, ATP-dependent zinc metalloprotease FTSH protein; SOD, superoxide dismutase; GPX, phospholipid hydroperoxide glutathione peroxidase; GLX1, lactoylglutathione lyase-like protein; PRx, horseradish peroxidase-like protein; GSTZ2, glutathione S-transferase tau 5; GSTF9, glutathione S-transferase; TRx, thioredoxin H-type 1 protein; G-TMT, gamma-tocopherol methyltransferase; IFR, isoflavone reductase-like protein Bet protein; COMT, caffeic acid O-methyltransferase; ELI3-1, cinnamyl alcohol dehydrogenase-like protein; BGLU40, beta-glucosidase; SPS3F, sucrose-phosphate synthase family protein; SUS4, sucrose synthase; APL3, glucose-1-phosphate adenylyltransferase family protein; SBE2.1, starch branching enzyme I; TPS5, trehalose-6phosphate synthase domain protein; DEP2, 4-alpha-glucanotransferase DPE2; GBSS1, granule bound starch synthase I, putative; BMY1, beta-amylase; GWD, alpha-glucan water dikinase; LSF2, dual specificity phosphatase domain protein; SEX4, tyrosine phosphatase; ASN1, asparagine synthetase [glutamine-hydrolyzing] protein; NDA1, NAD(P)H dehydrogenase B2; GAD, glutamate decarboxylase; ALDH12A1, delta-1-pyrroline-5-carboxylate dehydrogenase; P5CS2, delta-1-pyrroline-5-carboxylate synthetase; HSP70, heat shock cognate 70 kDa protein; ROC3, peptidyl-prolyl cis-trans isomerase; CAM5, EF hand calcium-binding family protein; CIPK3, CBL-interacting kinase; PCAP1, DREPP plasma membrane protein; MPK3, MAP kinase I; SOBIR1, LRR receptor-like kinase family protein; HA4, plasma membrane H+-ATPase; DET3, vacuolar H+-ATPase subunit C; RAB1A, RAB GTPase-like protein A2D; RABA1b, RAB GTPase-like protein A1D; RABC2A, RAB GTPase-like protein C2B. isomerase; CAM5, EF hand calcium-binding family protein; CIPK3, CBL-interacting kinase; PCAP1, DREPP plasma membrane protein; MPK3, MAP kinase I; SOBIR1, LRR receptor-like kinase family protein; HA4, plasma membrane

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H+-ATPase; DET3, vacuolar H+-ATPase subunit C; RAB1A, RAB GTPase-like protein A2D; RABA1b, RAB GTPase-like protein A1D; RABC2A, RAB GTPase-like protein C2B.

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Fig. 1 Changes in relative electrolyte leakage (A), relative water content (B), and chlorophyll content (C) in the leaves of A17 and ZM1 under salt treatment (100 mM NaCl) and in the control at different time points. ZM1-CK, ZM1 plants under normal conditions; ZM1-S, ZM1 plants under salt stress; A17-CK, A17 plants under normal conditions; A17-S, A17 plants under salt stress. Bar represents the mean ± standard deviation (n = 3); letters (abc) represent the level of significance according to one-way ANOVA with Duncan's multiple comparison tests (P ≤ 0.05). 205x64mm (300 x 300 DPI)

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Fig. 2 Ultrastructure of the chloroplasts in A17 and ZM1 leaves. A and C, chloroplasts of A17 and ZM1, respectively, under 0 mM NaCl; B and D, chloroplast of A17 and ZM1 respectively, under 100 mM NaCl for 5 days. Bars in figures represent 1 μm. 244x166mm (300 x 300 DPI)

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Fig. 3 A, Hierarchical cluster analysis of differentially expressed proteins (DEPs) in A17 and ZM1. Red indicates high relative expression, and green indicates low relative expression. AC (A17-CK), A17 plants under normal conditions; AS (A17-S), A17 plants under salt stress; ZC (ZM1-CK), ZM1 plants under normal conditions, ZS (ZM1-S), ZM1 plants under salt stress. 1, 2 and 3 indicate three biological replicates. B, Venn diagram of differentially expressed proteins (DEPs) in salt treated A17 and ZM1 leaves. 207x190mm (300 x 300 DPI)

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Fig. 4 Functional categorization of differentially expressed proteins (DEPs) in A17 and ZM1 leaves. BP, biological process; CC, cellular component; MF, molecular function. 244x293mm (300 x 300 DPI)

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Fig. 5 Physiological analysis of A17 and ZM1 under salt treatment after five days. (A) Fv/Fm; (B) H2O2 content; (C) MDA content; (D) superoxide dismutase (SOD) activity; (E) peroxidase (POD) activity; (F) glutathione peroxidase (GPX) activity; (G) glutathione (GSH) content; (H) oxidized glutathione (GSSG) content; (I) GSH/GSSG ratio; (K) soluble sugar content; (J) trehalose-6-phosphate synthase (TPS) activity. Bar represents the mean ± standard deviation (n = 3); letters (abc) represents the level of significance according to one-way ANOVA with post hoc Duncan's test (P ≤ 0.05). 263x172mm (300 x 300 DPI)

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Fig. 6 Transcript levels of selected DEPs. The present data shown are the mean ± SD of three biological replicates. PCAP1, DREPP plasma membrane protein; SUS4, sucrose synthase; ASN1, asparagine synthetase [glutamine-hydrolyzing] protein; TMP14, thylakoid membrane phosphoprotein 14 kDa protein; GPX6, phospholipid hydroperoxide glutathione peroxidase; G-TMT, gamma-tocopherol methyltransferase; PRX 52, horseradish peroxidase-like protein; PsbB, photosystem II CP47 chlorophyll A apoprotein; FSD2, superoxide dismutase; TPS5, trehalose-6-phosphate synthase domain protein; HSP70, heat shock cognate 70 kDa protein. * above bars indicate significant differences at the P ≤ 0.05 level; ** above bars indicate significant differences at the P ≤ 0.01 level; and *** above bars indicate significant differences exist at the P ≤ 0.001 level. 157x259mm (300 x 300 DPI)

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Fig. 7 Schematic presentation of key biological processes affected in A17 and ZM1 leaves under salt stress. Key DEPs expression levels were marked with symbols of the red (up-regulated) and green (downregulated) box, respectively. Symbols indicates the log2 DEPs fold change. The intensity of the colors increases as the expression differences increase, as shown in the bar at the bottom. Abbreviations: CAB1, light-harvesting complex I chlorophyll A/B-binding protein 1; LHCB4.1, light-harvesting complex I chlorophyll A/B-binding protein4, LHCB4.2, light-harvesting complex I chlorophyll A/B-binding protein 4; LHCB2, light-harvesting complex I chlorophyll A/B-binding protein 2; PsbC, photosystem II CP43 chlorophyll apoprotein; PsbD, photosystem II protein D2; PsbB, photosystem II CP47 chlorophyll A apoprotein; PsbE, photosystem II cytochrome b559 alpha subunit; ATPA, F-type H+-transporting ATPase subunit alpha; PDE334, F-type H+-transporting ATPase subunit b; ATPF, ATP synthase CF0 subunit I; RBCL, ribulose bisphosphate carboxylase large chain domain protein; TMP14, thylakoid membrane phosphoprotein 14 kDa protein; FTSH8, ATP-dependent zinc metalloprotease FTSH protein; SOD, superoxide dismutase; GPX, phospholipid hydroperoxide glutathione peroxidase; GLX1, lactoylglutathione lyase-like protein; PRx, horseradish peroxidase-like protein; GSTZ2, glutathione S-transferase tau 5; GSTF9, glutathione Stransferase; TRx, thioredoxin H-type 1 protein; G-TMT, gamma-tocopherol methyltransferase; IFR, isoflavone reductase-like protein Bet protein; COMT, caffeic acid O-methyltransferase; ELI3-1, cinnamyl alcohol dehydrogenase-like protein; BGLU40, beta-glucosidase; SPS3F, sucrose-phosphate synthase family protein; SUS4, sucrose synthase; APL3, glucose-1-phosphate adenylyltransferase family protein; SBE2.1, starch branching enzyme I; TPS5, trehalose-6-phosphate synthase domain protein; DEP2, 4-alphaglucanotransferase DPE2; GBSS1, granule bound starch synthase I, putative; BMY1, beta-amylase; GWD, alpha-glucan water dikinase; LSF2, dual specificity phosphatase domain protein; SEX4, tyrosine phosphatase; ASN1, asparagine synthetase [glutamine-hydrolyzing] protein; NDA1, NAD(P)H dehydrogenase B2; GAD, glutamate decarboxylase; ALDH12A1, delta-1-pyrroline-5-carboxylate dehydrogenase; P5CS2, delta-1-pyrroline-5-carboxylate synthetase; HSP70, heat shock cognate 70 kDa protein; ROC3, peptidyl-prolyl cis-trans isomerase; CAM5, EF hand calcium-binding family protein; CIPK3, CBL-interacting kinase; PCAP1, DREPP plasma membrane protein; MPK3, MAP kinase I; SOBIR1, LRR receptor-like kinase family protein; HA4, plasma membrane H+-ATPase; DET3, vacuolar H+-ATPase subunit C; RAB1A, RAB GTPase-like protein A2D; RABA1b, RAB GTPase-like protein A1D; RABC2A, RAB GTPase-like protein C2B. 185x109mm (300 x 300 DPI)

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