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Comparative proteomics of contrasting maize genotypes provides insights into salt-stress tolerance mechanisms Meijie Luo, Yanxin Zhao, Yuandong Wang, Zi Shi, Panpan Zhang, Yunxia Zhang, Wei Song, and JIURAN ZHAO J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00455 • Publication Date (Web): 01 Dec 2017 Downloaded from http://pubs.acs.org on December 3, 2017

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Journal of Proteome Research

Comparative proteomics of contrasting maize genotypes provides insights into salt-stress tolerance mechanisms Meijie Luo1† ([email protected]), Yanxin Zhao1† ([email protected]), Yuandong Wang1 ([email protected]), Zi Shi1 ([email protected]), Panpan Zhang1 ([email protected]), Yunxia Zhang1 ([email protected]), Wei Song1*([email protected]), Jiuran Zhao1* ([email protected]) 1

Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding,

Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences (BAAFS), Beijing, 100097, China

Mailing address: Shuguang Garden Middle Road No. 9, Haidian District Beijing 100097, China

ABSTRACT: Salt stress is a major abiotic factor limiting maize yield. To characterize the mechanism underlying maize salt tolerance, we compared the seedling root proteomes of salt-tolerant Jing724 and salt-sensitive D9H. The germination rate and growth parameter values (weight and length) were higher for Jing724 than for D9H under saline conditions. Using an iTRAQ-based method, we identified 513 differentially regulated proteins (DRPs), with 83 and 386 DRPs specific to Jing724 and D9H, respectively. In salt-stressed Jing724, the DRPs were 1

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primarily associated with the pentose phosphate pathway, glutathione metabolism, and nitrogen metabolism. Key DRPs, such as glucose-6-phosphate 1-dehydrogenase, NADPH-producing dehydrogenase, glutamate synthase, and glutamine synthetase, were identified based on pathway enrichment and protein–protein interaction analyses. Moreover, salt-responsive proteins in Jing724 seedlings were implicated in energy management, maintenance of redox homeostasis, detoxification of ammonia, regulation

of

osmotic

homeostasis,

stress defense

and

adaptation,

biotic

cross-tolerance, and regulation of gene expression. Quantitative analyses of superoxide dismutase activity, malondialdehyde content, relative electrolyte leakage, and proline content were consistent with the predicted changes based on DRP functions. Furthermore, changes in the abundance of eight representative DRPs were correlated with the corresponding mRNA levels. Our results may be useful for elucidating the molecular networks mediating salt tolerance.

KEY WORDS: maize, salt tolerance, seedling root, comparative proteomic analysis, iTRAQ

INTRODUCTION

Salinity is a major abiotic stress that restricts plant growth and decreases plant productivity 1. Salt can accumulate in soils irrigated with slightly saline water. More than 6% of the global land area is already considered to be salinized 2. Maize is a critical staple crop worldwide, contributing to both food and economic security in agricultural regions. However, compared with other crops, maize is relatively 2


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sensitive to salt stress 3. Therefore, elucidating the mechanisms that can increase maize salt tolerance may be useful for basic research and for breeding increasingly stress-tolerant cultivars. Plant responses to salt stress have been well characterized. In the Arabidopsis thaliana model system, three functional pathways mediate salt tolerance. Specifically, the Salt Overly Sensitive pathway mediates ion homeostasis, while mitogen activated-protein kinase cascades regulate osmotic homeostasis and antioxidant defense system functions as a detoxifier 1, 4. However, few studies have examined the mechanisms responsible for intraspecific variations in salt tolerance among maize lines. Thus, it is unclear whether some or all of the pathways described above are functional in maize, or if salt-tolerant maize lines apply novel mechanisms. One approach to characterizing the mechanisms responsible for the diversity in tolerance to salt stress, or other abiotic stressors involves the identification of genomic regions controlling the trait variability. In some cases, a single major quantitative trait locus (QTL) regulates the variation in salt tolerance between different accessions of the same species. However, even when a single variant is responsible for intraspecies variations in stress tolerance, the protein underlying that QTL rarely acts alone, but instead participates in a pathway or network 5. Analyzing the transcript- or protein-level changes can reveal the overall stress-induced plant pathways. Proteomic analyses have started to be more widely employed to characterize the responses of different plant species to various abiotic stresses 6. For example, a proteomic analysis of the effects of short-term cold or heat stress treatments in A. thaliana rosette leaves 3



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revealed that many proteins are affected by both temperature extremes 7. In rice, six novel salt-responsive proteins were identified by a comparative proteomic analysis of leaf proteins 8. Additionally, a shotgun proteomic analysis of soybean embryonic axes revealed that the integrated protection against oxidative, aldehydes, and osmotic stresses is critical for plant adaptation to saline conditions 9. Furthermore, 21 of 26 differentially expressed proteins detected in a proteome-level comparison were associated with photosynthesis, and a subsequent investigation of localization and function confirmed the role of chloroplasts in the salt tolerance of a wheat introgression line (cultivar SR3) 10. Moreover, a proteomic investigation identified 22 salt-responsive proteins involved in water conservation, signal processing, protein synthesis, and biotic stress tolerance in salt-stressed maize seedling root cells 3. However, there is still relatively few proteomic datasets characterizing maize responses to salt stress, and the molecular network underlying maize salt tolerance remains unclear. Maize inbred lines Jing724 and D9H are sister lines. During the initial germplasm screening in saline fields, breeders observed that Jing724 plants were salt-tolerant while D9H plants were susceptible to salt stress. Thus, we selected these maize lines with a common pedigree, but significantly different degrees of salt tolerance, for a detailed molecular characterization study. In addition to being relatively salt-tolerant, Jing724 is also the female parent of the maize hybrid Jingke968, which is widely grown in China (i.e., on more than 2 million ha in 2016). This maize line has been adopted because it exhibits several desirable characteristics, including high yield, high 4


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grain quality, broad spectrum stress resistance, wide adaptability, and ease of hybrid seed production 11. Thus, clarifying the molecular mechanism responsible for the salt tolerance of Jing724 plants is significant to maize breeding. In the present study, we attempted to elucidate the molecular networks associated with salt tolerance in maize seedling root cells. We used isobaric tags for relative and absolute quantitation (iTRAQ)-based liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to analyze the proteomes of two inbred lines (Jing724 and D9H) with different phenotypes and physiological responses under saline conditions. We herein provide new insights into the molecular mechanisms associated with salt stress tolerance in maize seedling root cells.

MATERIALS AND METHODS

Plant materials and salt treatments

Jing724 and D9H plants were selected and cultivated at the Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences, China. Seeds were surface-sterilized with 1% NaClO for 10 min, washed three times with sterile water and sown in a maize seedling identification instrument (Chinese patent number: ZL200920177285.0) according to the user manual 12. The instrument was incubated in a greenhouse at 26 ± 1 °C under a 12-h light/12-h dark cycle (150–180 µmol m−2 s−1) with the relative humidity maintained at 70%. Seeds were hydroponically cultured in sterile water with or without 100 mM NaCl for 7 days prior to assessing the germination rate (GR) and seedling growth parameters. Seedlings with three leaves 5



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were obtained by germinating seeds in sterile water for 3 days and then culturing in Hoagland’s nutrient solution (4 mM Ca(NO3)2·4H2O, 6 mM KNO3, 1 mM NH4H2PO4, 2 mM MgSO4·7H2O, 0.047 mM ethylenediamine tetraacetic acid, disodium ferric salt, 0.046 mM H3BO3, 0.0095 MnSO4·4H2O, 0.7 µM ZnSO4·7H2O, 0.3 µM CuSO4·5H2O, and 0.016 µM ammonium molybdate tetrahydrate) for 7 days. The seedlings were then cultured in Hoagland’s nutrient solution with or without 100 mM NaCl for 7 days, and subsequently harvested for a proteomic analysis, quantitative real-time polymerase chain reaction (qRT-PCR), and evaluation of physiological and seedling growth parameters. The culture solutions were changed every 2 days throughout the hydroponic growth period.

Growth parameter measurements and physiological assays

The GR was calculated using three biological replicates of 30 maize seeds hydroponically cultured in control or saline water for 7 days and the following formula: GR = (number of germinated seeds / total number of seeds) × 100%. Meanwhile, the shoot fresh weight (SFW), shoot length (SL), root fresh weight (RFW), and root length (RL) of seedlings were measured 7 days after germination, with five seedlings per replicate and six biological replicates. Additionally, the shoot dry weight (SDW) and root dry weight (RDW) were measured after harvested seedlings were dried at 80 °C for 3 days. To analyze seedling growth parameters, 10-day-old seedlings with three leaves were hydroponically cultured with or without 100 mM NaCl for 7 days. The SL, SFW, and SDW were evaluated at 0, 3, 5, and 7

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days after the salt and control treatments, with three biological replicates of three seedlings per replicate. Leaf and root physiological parameters were assessed after a 7-day treatment with or without 100 mM NaCl. The proline (Pro) content was quantified according to a ninhydrin-based colorimetric assay 13, while superoxide dismutase (SOD) activity was determined using the nitroblue tetrazolium photoreduction method 14. Malondialdehyde (MDA) content was measured by the thiobarbituric acid assay 15, while relative electrolyte leakage (REL) was measured as described by Liu 16. Each physiological parameter was examined with six biological replicates.

Protein extraction

Treated root tissues were immediately frozen in liquid nitrogen. Three biological replicates were analyzed for each treatment, with the roots of 15 seedlings comprising one replicate. Proteins were extracted from frozen roots using cold acetone as previously described 17. Briefly, 1 g root tissue was ground to a powder in liquid nitrogen and then dissolved in 2 mL lysis buffer containing 8 M urea, 2% sodium dodecyl sulfate, and 1× Protease Inhibitor Cocktail (Roche Ltd., Basel, Switzerland). Sample solutions were kept on ice for 30 min and then centrifuged at 18,000 ×g at 4 °C for 30 min. The supernatants were transferred to clean tubes, and the proteins were then precipitated with 12 mL 10% trichloroacetic acid in acetone at −20 °C overnight. The pellets were washed three times with 100% acetone and then resuspended by sonicating in 8M urea on ice.

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Protein digestion and iTRAQ labeling

Protein concentrations were determined using the BCA assay kit (Beyotime Ltd., Beijing, China). For each sample, the solution containing 100 µg protein was transferred to a new tube for a final concentration of 1 µg/µL in 100 µL. After adding 11 µL 1 M DL-dithiothreitol, the protein solution was incubated at 37 °C for 1 h and then transferred to a 10 K centrifugal filter unit (Millipore), which was centrifuged at 14,000 ×g for 10 min. After adding 120 µL 55 mM iodoacetamide, the protein solution was incubated in darkness at room temperature for 20 min. After a 12-min centrifugation at 13,500 ×g, 100 mM tetraethylammonium bromide was added to the centrifugal filter unit, which was centrifuged at 13,500 ×g for 12 min. This step was repeated two times. The proteins were digested at 37 °C overnight with trypsin (Promega), which was added into the protein solution at a ratio of 1 : 50 (trypsin / protein). Digested protein samples from salt-treated Jing724 and D9H seedlings were labeled with iTRAQ tags 114 and 113, respectively, using the iTRAQ Reagent 8-plex Multiplex kit (SCIEX). Additionally, the digested protein samples from control-treated Jing724 and D9H seedlings were labeled with iTRAQ tags 116 and 115, respectively. Labeling efficiencies for all samples were greater than 94% (File S1). The four samples labeled with different iTRAQ tags underwent an LC-MS/MS analysis, which was repeated three times with three biological replicates.

High pH reversed-phase separation

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Labeled samples were evaporated, resuspended in Buffer A (20 mM ammonium formate in water, pH 10.0), and analyzed using the UltiMate 3000 HPLC system (Thermo Fisher Scientific, MA, USA) equipped with the XBridge C18 reversed-phase column (4.6 mm × 250 mm, 5 µm) (Waters Corporation, MA, USA). Peptides were eluted with a linear gradient of 5–45% Buffer B (20 mM ammonium formate in 80% acetonitrile, pH 10.0) over 40 min, with a flow rate of 1 mL/min. The column was re-equilibrated with Buffer A for 15 min before each analysis and was maintained at 30 °C. The eluants were monitored by absorbance at 214 nm and fractions were collected every 100 s. A total of 24 fractions were collected and then combined according to the collection time to produce 12 fractions (e.g., the 1st fraction was combined with the 13th fraction, 2nd fraction was combined with the 14th fraction). Each fraction was dried in a vacuum concentrator.

Low pH nano-HPLC-MS/MS analysis

Each fraction was reconstituted in 30 µL Buffer C (0.1% formic acid in water) and then analyzed using the EASY-nLC 1000 HPLC system (Thermo Fisher Scientific) connected to an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific) with the Nanospray Flex NG Ion Source. Peptide solution (10 µL) was loaded onto the Acclaim PepMap C18 trap column (100 µm × 2 cm; Thermo Fisher Scientific) at a flow rate of 10 µL/min. The subsequent sequential separation of peptides on the Acclaim PepMap C18 column (75 µm × 15 cm) was completed using a linear gradient of 2–40% Buffer D (0.1% formic

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acid in acetonitrile) over 70 min, with a flow rate of 300 nL/min. Columns were re-equilibrated for 10 min before each analysis, and the electrospray voltage was 2 kV. The mass spectrometer was operated in the data-dependent acquisition mode via a top speed strategy. The MS spectra with a mass range of 350–1,550 m/z were acquired at a resolving power of 120 K. The high-energy collisional dissociation (HCD) MS/MS scan was conducted at a resolving power of 30 K. The relative collision energy for HCD was 38% normalized collision energy. The intense signals in the MS spectra (i.e., > 1e4) underwent an additional MS/MS analysis. The automatic gain controls for the MS and MS/MS were set to 4e5 and 8e4, respectively. The maximum ion injection times for the MS and MS/MS were 50 and100 ms, respectively. The isolation window was 1.6 Da and the dynamic exclusion duration was 30 s.

Protein identification and quantification

The raw LC-MS/MS files were transformed to mgf files using the Mascot distiller software (www.matrixscience.com). Proteins were identified based on searches of the maize protein database (https://www.maizegdb.org/; B73 RefGen_v2; 136,770 sequences) with fragmentation spectra as queries using the Mascot search engine (version 2.3.02; Matrix Science, London, UK). The following Mascot search parameters were used: trypsin as the cleavage enzyme, one missed cleavage and monoisotopic mass. Carbamidomethyl of cysteine, iTRAQ 8-plex of the N-terminus,

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and iTRAQ 8-plex of lysine were set as fixed modifications. Conversion of N-terminal glutamine to pyroglutamic acid, oxidation of methionine, and iTRAQ 8-plex of tyrosine were set as variable modifications. The peptide mass tolerance was 20 ppm, and the fragment mass tolerance was set to ± 0.05 Da. The results were filtered at a significance threshold of P < 0.05. By searching against a decoy database in Mascot, the false discovery rates calculated for the 3 experiments searched were 1.03%, 0.77% and 0.77%, respectively. For protein quantification only proteins that were detected in all samples were considered. Shared peptides were excluded from the protein quantification step. Protein relative quantification was based on the ratios of reporter ions which reflect the relative abundance of peptides. For the calculation of reporter ion ratios, peak intensities of reporter ions were used, and the control-treated Jing724 sample served as a reference. Then, the final ratios of protein quantification were further normalized based on the median average protein quantification ratio. The median of the unique peptide ratios was used to represent the protein ratio. Differentially regulated proteins (DRPs) were analyzed using Student’s t-test. The median normalization and Student’s t-test were completed using the Mascot software. Proteins with fold-changes > 1.2 or < 0.83 (P < 0.05) were considered to be DRPs 18.

Classification of DRPs and the construction of protein interaction networks

Differentially regulated proteins were used as queries to search the Eukaryotic Orthologous Groups (KOG) (https://www.ncbi.nlm.nih.gov/COG/), Kyoto

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Encyclopedia of Genes and Genomes (KEGG) (http://www.kegg.jp/kegg/), and Gene Ontology (GO) (http://www.geneontology.org/) databases. Additionally, the significant enrichment of KEGG/GO pathways was determined using the hypergeometric test, with Q (Bonferroni-corrected P value) < 0.05. Enriched KEGG pathways were integrated and visualized using the Cell Designer program (version 4.0). The hierarchical clustering analysis of DRPs was conducted with the Cluster 3 program, and was viewed in Java Treeview. A protein interaction network was constructed using the String program (http://www.string-db.org/) with a confidence score greater than 0.7.

RNA extraction and qRT-PCR Total RNA extracted using the Trizol reagent (Invitrogen, Carlsbad, USA) 19 was then reverse transcribed using the FastQuant RT Kit (with DNase) (Tiangen Biotech, Beijing, China). The qRT-PCR assay was completed using 20-µL reaction solutions containing gene-specific primers (Table S1) and the qPCR MasterMix (Tiangen Biotech). Maize actin 1 was employed as the internal control to normalize gene expression data. Relative expression levels were calculated with the 2−∆∆Ct method 20.

Data analysis

Data were analyzed using the GraphPad Prism 5 program. A two-way ANOVA and Bonferroni post tests were used to compare the growth and physiological parameters between treatments and across genotypes. The qRT-PCR data underwent a one-way ANOVA as well as Tukey’s multiple comparison tests. Meanwhile, Student’s t-test 12


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was used to analyze the differences in protein expression levels between the controland salt-treated maize seedlings of each genotype.

RESULTS

Phenotypic differences between Jing724 and D9H in response to saline conditions

Breeders observed that Jing724 was salt-tolerant and D9H was salt-sensitive when both lines were planted in a saline field 12. To validate this observation and to investigate the molecular mechanism underlying Jing724 salt tolerance, seeds or seedlings with three leaves were treated with or without 100 mM NaCl for 7 days in a hydroponic system. Several salt-induced phenotypic responses were then observed. The D9H GR under saline conditions was significantly lower than that under control conditions (P < 0.001), while the Jing724 GR was unaffected by the salt treatment (Figure 1A). Compared with the 7-day-old seedlings grown under control conditions, the salt-treated seedlings of both lines exhibited retarded growth (Figure 1B–G). However, the decrease in the SFW, SDW, SL, RFW, RDW, and RL was greater in D9H seedlings than in Jing724 seedlings (Table S2). The Jing724 seedlings appeared greener and healthier than the D9H seedlings following the 7-day treatment with 100 mM NaCl (Figure 1H). The salt treatment induced a gradual increase in the SFW, SDW, and SL of Jing724 seedlings, which was in contrast to the decrease in these parameters in D9H seedlings 3–7 days after initiating the salt treatment (Figure 1I–K). Thus, Jing724 was much more salt-tolerant than D9H at the germination and early seedling stages. 13



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Inventory of maize seedling root proteins identified by iTRAQ

Using the Mascot software, 31,793 ± 446.1 spectra, including 19,293 ± 260.3 unique spectra, were matched with known spectra, and 17,296 ± 123.4 peptides, 11,902 ± 118.9 unique peptides, and 4,328 ± 32.97 proteins were identified. Among these proteins (Table S3), 2,882 were 20–70 kDa, 1,171 were 70–100 kDa, 339 were < 10 kDa, and 503 were > 100 kDa (Figure 2A). Additionally, 2,894 proteins were detected based on at least two unique peptides, while the remaining proteins had only one identified peptide (Figure 2B). Protein sequence coverage was generally < 20% (Figure 2C). Proteins with at least two unique peptides were used for a subsequent analysis of DRPs. An overview of the hierarchical clustering analysis of the DRPs in the two analyzed groups revealed that the DRPs in different repeats of the same group exhibited similar expression patterns. Meanwhile, a comparison of the Jing724 and D9H DRPs revealed differences in the expression patterns (Figure 3A). A search for proteins with fold-changes > 1.2 or < 0.83 (P < 0.05) resulted in the identification of 513 DRPs between the control and saline conditions in Jing724 and D9H. Of these DRPs, 127 (34 increased and 93 decreased) and 430 (189 increased and 241 decreased) changed significantly in the Jing724 and D9H lines, respectively. Only 44 DRPs were shared between the two lines, while 83 DRPs were specific to Jing724 and 386 DRPs were specific to D9H (Figure 3B and Table S4–S6).

Classification of salt-responsive DRPs

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Of the 513 DRPs, 398 were assigned to 24 categories using the KOG database. The largest category was general function prediction only (14.1%), followed by amino acid transport and metabolism (13.6%), energy production and conversion (12.1%), translation, ribosomal structure, and biogenesis (12.1%), carbohydrate transport and metabolism (11.8%), posttranslational modification, protein turnover, chaperones (10.8%), and cytoskeleton (8.0%) (Figure 4). A GO functional analysis revealed that 31 GO terms were shared between Jing724 and D9H, including response to stimulus (GO: 0050896), metabolic process (GO: 0008152), and antioxidant activity (GO: 0016209). For nearly all of these shared GO terms, D9H had more increased and decreased DRPs than Jing724. Two terms were unique to Jing724, namely transcription factor activity, protein binding (GO: 0000988) and cell killing (GO: 0001906), whereas GO terms related to nucleic acid binding transcription factor activity (GO: 0001071), molecular transducer activity (GO: 0060089), and immune system process (GO: 0002376) were specifically enriched in D9H (Figure 5). To analyze the functional consequences of the salt-responsive DRPs, we mapped the KEGG pathway enrichment with the public KEGG database. Using a hypergeometric test, KEGG pathways that had a Q value < 0.05 were considered to be significantly affected by salt stress. We observed that the phagosome, galactose metabolism, and alanine, aspartate and glutamate metabolism pathways responded to salt in both lines (Figure S1). Furthermore, some KEGG pathways (e.g., pentose phosphate pathway, nitrogen metabolism, and glutathione metabolism) were 15



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considerably enriched among the Jing724 DRPs (Figure S1A), while other KEGG pathways (e.g., fatty acid degradation, starch and sucrose metabolism, and endocytosis) were significantly enriched among the D9H DRPs (Figure S1B).

Enriched metabolic pathways of DRPs in salt-treated Jing724

Pentose phosphate pathway

The root proteome revealed changes in major metabolic pathways. For the pentose phosphate pathway, the UDP-glucose pyrophosphorylase 1, glucose-6-phosphate 1-dehydrogenase, 6-phosphogluconate dehydrogenase isoenzyme B isoform 1, and NADPH-producing dehydrogenase of the oxidative pentose phosphate pathway were up-regulated, resulting in the abundant production of NADPH, which functions as a reducing agent for various synthetic reactions in cells (Figure 6A).

Glutathione metabolism

Glutathione is one of the main antioxidants involved in eliminating reactive oxygen species (ROS) and is important for redox homeostasis 21. The NADPH derived from the pentose phosphate pathway is the cofactor required for the conversion of oxidized glutathione to reduced glutathione. The up-regulated production of glucose-6-phosphate 1-dehydrogenase and NADPH-producing dehydrogenase in the pentose phosphate pathway also affected the glutathione metabolism pathway to enable the conversion of NADP+ to NADPH (Figure 6B).

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An abundance of ascorbate peroxidase, which is an integral component of the glutathione-ascorbate cycle, is essential for scavenging H2O2 and enhancing tolerance to oxidative stress 22. Moreover, dehydroascorbate reportedly induces the cell cycle arrest at the G2/M DNA damage checkpoint due to oxidative stress 23. Therefore, an increased level of dehydroascorbate induced by up-regulated ascorbate peroxidase production could subsequently regulate the cell cycle progression and defense against oxidative stress (Figure 6B).

Nitrogen metabolism

Nitrogen metabolism plays a significant role in the formation of cellular components and the regulation of cellular activities. Moreover, the conversion of inorganic nitrogen to organic nitrogen is a protective strategy used by plants to detoxify ammonia 24. We observed that glutamine synthetase and glutamate synthase levels in salt-stressed Jing724 roots increased. These two enzymes are involved in glutamate synthesis, which is critical for decreasing ammonia levels 25, 26. Meanwhile, hydroxymethyltransferase, dihydrolipoyl dehydrogenase and NAD-dependent malic enzyme were significantly up-regulated to synthesize serine, aspartate, and alanine, which also help to decrease ammonia levels (Figure 6C).

Other pathways involved in stress defense

The production of chitinase and the chitinase CHEM 5 precursor, which influence chitosan biosynthesis, as well as the pathogenesis-related protein 1 was significantly

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induced under saline conditions. These proteins are known to possess antimicrobial activity 27, 28 (Figure S2).

Analysis of protein–protein interactions

To determine how maize root cells transmit salt stress signals, the identified Jing724 and D9H DRPs were further analyzed using the String 10.5 database (http://www.string-db.org/) with confidence scores higher than 0.7. Five groups of interacting proteins were identified in Jing724 (Figure 7). The first group included glucose-6-phosphate 1-dehydrogenase (GRMZM2G031107, gpm742), 6-phosphogluconate dehydrogenase (GRMZM2G127798, Zm.506), NADPH-producing dehydrogenase (GRMZM2G145715, Zm.406), and UDP-glucose pyrophosphorylase 1 (GRMZM2G032003, csu815). Proteins in this group are important for maintaining antioxidant and redox homeostasis, and carbohydrate metabolism. The second group comprised glutamate synthase (GRMZM2G085078, Zm.24266), glutamine synthetase root isozyme 2 isoform 1 (GRMZM2G024104, GS1-2), hydroxymethyltransferase-like protein (GRMZM2G078143), ascorbate peroxidase (GRMZM2G137839, POD1), and peroxiredoxin-5 (GRMZM2G036921, Zm.9813). These proteins are related to amino acid metabolism and antioxidant defense. In the third protein network group, ribosomal protein S27 (GRMZM2G066222) interacted with other ribosomal proteins such as 40S ribosomal protein S28 (GRMZM2G124143). As expected, they were related to protein translation. Finally, there were two pairs of interacting protein species. Zeamatin

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precursor (GRMZM2G374971, Zlp) interacted with pathogenesis-related protein-like (GRMZM2G092474, Zm.27514). These proteins are involved in host defenses against pathogens. Peroxidase 52 precursor (AC197758.3_FGP004, Zm.82332) interacted with the probable cinnamyl alcohol dehydrogenase 8D (AC234163.1_FGP002). Additionally, eight separate protein interaction networks were predicted for D9H (Figure S3), including a large and complex network, four small networks and three protein pairs.

Physiological responses of Jing724 and D9H to salt stress

To investigate whether the pattern of functional changes predicted by the DRPs results in observable physiological changes, we evaluated SOD activity, Pro content, MDA content, and REL (Figure 8). The leaf SOD activity increased significantly in both inbred lines following the salt treatment (P < 0.001 for Jing724 and P < 0.01 for D9H), although the extent of the increase was greater in Jing724 (Figure 8A). In contrast, the MDA content was decreased significantly in Jing724 (P < 0.05), but was unaffected in D9H. Additionally, the REL was not significantly altered in Jing724, but increased significantly in D9H (P < 0.001). Thus, the MDA content and REL were higher in salt-stressed D9H than in salt-stressed Jing724 (Figure 8B, C). In roots, the Pro content decreased significantly in both inbred lines in response to saline conditions (P < 0.001), but to a much greater degree in D9H (76.7%) than in Jing724 (33.2%) (Figure 8D). Moreover, the MDA content increased significantly in D9H (P < 0.001), but was not significantly altered in Jing724, while the REL of Jing724 and

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D9H increased by 187 and 200%, respectively. These results indicated that salt stress induces a greater increase in MDA content and REL in D9H than in Jing724 (Figure 8E, F). These findings combined with the observed physiological changes revealed that under saline conditions, the SOD activity and Pro content were higher in Jing724, while the MDA content and REL were higher in D9H.

Expression levels of genes encoding DRPs in response to salt stress

The transcription of six representative genes encoding proteins whose abundance increased in response to salt stress in Jing724 seedlings as well as two genes encoding significantly down-regulated proteins in salt-stressed D9H seedlings were examined by qRT-PCR. The transcript levels of genes encoding glucose-6-phosphate 1-dehydrogenase, glutamine synthetase root isozyme 2 isoform 1, NADPH-producing dehydrogenase of the oxidative pentose phosphate pathway, 6-phosphogluconate dehydrogenase isoenzyme B isoform 1, peroxidase 52 precursor, and short-chain dehydrogenase reductase 3a-like increased significantly in salt-stressed Jing724. In contrast, the transcription of the gene encoding glutamine synthetase root isozyme 2 isoform 1 was significantly down-regulated in salt-stressed D9H, while the expression levels of the other five genes were unaffected (Figure 9A–F). Moreover, the expression levels of the genes encoding aquaporins PIP1-5 and PIP2-5 decreased significantly in D9H in response to salt stress, but were unchanged in Jing724 (Figure 9G, H). Overall, the observed transcription patterns for these eight genes were consistent with the results of the proteomic analysis in this study.

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DISCUSSION

Saline soils and water sources restrict the areas where maize can be grown and decrease maize productivity. Therefore, characterizing the mechanism responsible for intraspecies variations in salt tolerance is of critical interest to maize researchers and breeders. In this study, we compared two maize sister lines believed to vary significantly regarding salt tolerance based on field trials. Consistent with field observations, the GR of Jing724 seeds was significantly higher than that of D9H seeds under saline conditions. Furthermore, several growth and development traits, including SFW, SDW, SL, RFW, RDW, and RL, were all less adversely affected by salt stress in Jing724 than in D9H. These observations indicate that Jing724 plants can adapt to saline conditions better than D9H plants. To further elucidate the molecular network responsible for the variability in stress tolerance between these two lines, we compared the proteome-level data for the Jing724 and D9H lines in response to salt treatments.

Differentially regulated proteins in D9H

We identified more DRPs in D9H than in Jing724. However, of the 430 DRPs, 241 were down-regulated and were associated with phenylpropanoid biosynthesis, phagosome, endocytosis, galactose metabolism, starch and sucrose metabolism, and oxidative phosphorylation (Table S7). Phenylpropanoids are indicators and key mediators of plant responses to biotic and abiotic stimuli 29. Phagosome and endocytosis are related to plant defenses against pathogens 30, 31. Starch and sucrose 21



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metabolism as well as oxidative phosphorylation provide energy for all aspects of plant growth and development 32. The observed changes to these proteins imply that D9H defense responses and energy supplies are disrupted under long-term salt stress (Figure 10B). Regarding the 189 up-regulated DRPs, fatty acid degradation pathway was significantly enriched (Table S8). The degradation of fatty acids in D9H maize seedling roots is likely the result of damages to root cell membrane system. This result was in accordance with the increased MDA content and REL in D9H (Figure 8), which are indicators of oxidative damage and membrane damage respectively. Thus, a long-term exposure to saline conditions appears to result in a considerable accumulation of toxic metabolites in salt-sensitive D9H root cells, leading to damage to tissue structures and inhibited growth (Figure 10B).

Differentially regulated proteins in Jing724

Unlike D9H, Jing724 exhibited an increased abundance of proteins associated with the oxygen-dependent pentose phosphate pathway, which is an important multi-functional metabolic pathway, under saline conditions. This pathway produces energy and diverse raw materials for synthetic metabolism 33. Most importantly, this pathway plays a central role in the maintenance of redox homeostasis 34. Additionally, glutathione metabolism was significantly enhanced in salt-treated Jing724. This metabolic pathway is also important for redox regulation and anti-oxidative protection because it results in the production and maintenance of a redox buffer. These results are consistent with the physiological changes observed in the two lines in response to

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salt stress (i.e., higher SOD activity and Pro content in Jing724, but higher MDA content and REL in D9H; Figure 8). Moreover, the abundance of proteins involved in nitrogen metabolism increased more in Jing724 than in D9H under saline conditions. Ammonia, which is produced by the reduction of NO3− or NO2−, is toxic if it accumulates in plant cells 35. The up-regulated production of glutamine synthetase and glutamate synthase during nitrogen metabolism leads to an increase in the abundance of glutamine and glutamate, which can be used for plant growth and development 36, but also for eliminating excess ammonia 25, 26. Salt stress induces a rapid increase in ROS content, including hydrogen peroxide (H2O2), superoxide radicals (•O2− ), and hydroxyl radicals (•OH−) 5, which can damage cellular components and structures. In this study, UDP-glucose pyrophosphorylase1 was one of the DRPs implicated in redox homeostasis (Figure 10). A previous study revealed that that UDP-glucose pyrophosphorylase activity is regulated via a redox mechanism 37. Additionally, glucose-6-phosphate 1-dehydrogenase and 6-phosphogluconate dehydrogenase are key rate-limiting enzymes in the pentose phosphate pathway, and are critical for regulating redox reactions because they produce NADPH 34. Ascorbate peroxidase is important for H2O2 detoxification 22. Moreover, peroxidase, peroxiredoxin-5 and short-chain dehydrogenase reductase 3a-like are all redox enzymes that contribute to antioxidant defenses 38. Amino acids, such as glutamine, glutamate, aspartate, and serine, can affect osmotic adjustment 36, 39, 40. Our findings suggest that glutamine synthetase, glutamate 23



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synthase, and hydroxymethyltransferase, which catalyze the formation of glutamine, glutamate and serine, respectively, may influence the regulation of osmotic homeostasis. The auxin-induced PCNT115 protein is positively correlated with adventitious root formation 41, indicating an increase in the abundance of this protein may represent a stress-adaptive mechanism during exposures to long-term salt stress. The production of pathogenesis-related proteins (e.g., chitinase and zeamatin) is induced by pathogen attacks and environmental stresses, suggesting a cross-tolerance mechanism is activated in salt-stressed Jing724 3. Decreased production of ribosomal proteins was observed in salt-stressed A. thaliana 42 and maize plants 3. This has been interpreted as an adaptive response to conserve energy and enable the plant to overcome the effects of the imposed stress. Aquaporins regulate the movement of water into cells 43. Plasma membrane ATPase plays a major role in nutrient transport 44. Histone H4 together with histone deacetylase HDT1 can regulate gene transcription 45-47. All of these DRPs were significantly down-regulated in salt-treated D9H, but were relatively unaffected in Jing724. Therefore, these proteins may be involved in the salt tolerance of Jing724. Genotyping of Jing724 and D9H using a 200 K SNP chip revealed that 77.7% (42,110 of 54,176) of the detected SNPs were common to both lines (Figure S4). Only 14.2% DRPs (73 of 513) coding regions were located within the polymorphic genomic regions, suggesting that these DRPs might be regulated by differences in gene sequences, while other DRPs were regulated by other mechanisms. Moreover, only one salt tolerance related DRP coding region was located in the polymorphic 24


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genomic region, indicating that most salt tolerance related DRPs might be regulated by transcription, translation or degradation in this study.

Proposed molecular model of Jing724 salt tolerance

We developed a molecular model for maize salt tolerance under salinity stress based on the proteome-level changes observed in this study (Figure 10A and Table 1). The most important salt-tolerance mechanism in maize involves the detoxification of ROS to maintain redox homeostasis. This detoxification requires proteins associated with the pentose phosphate pathway and glutathione metabolism as well as peroxidases, and a dehydrogenase reductase. Glutamine synthetase, glutamate synthase, and other proteins involved in nitrogen metabolism detoxify ammonia and may also mediate osmotic adjustment in response to osmotic stress. LysM domain receptor-like kinase 4 transduces stress signals, leading to the accumulation of proteins exhibiting antimicrobial activities. This suggests that Jing724 plants developed cross-tolerance mechanisms to cope with salt stress. Additionally, the abundance of ribosomal proteins decreases in salt-treated Jing724, implying salinity may induce an overall down-regulation of protein synthesis in this maize line. Moreover, the production of dehydroascorbate, which serves as a cell division gatekeeper to arrest the cell cycle at the G2/M DNA damage checkpoint, increases in response to saline conditions 23, likely because of its role in DNA repair and stress tolerance.

CONCLUSIONS

25



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In the current study, we applied comparative proteomic approaches to unveil the molecular basis of toxicity/salt tolerance in two maize inbred lines with differing salt tolerance levels. We identified 513 DRPs during exposures to salt stress. The down-regulated DRPs in the salt-sensitive maize inbred line D9H were associated with stress defenses and energy supplies, while the up-regulated DRPs were involved in fatty acid degradation. These changes in protein abundance were consistent with the observed salt sensitivity of this line. In contrast, the Jing724 DRPs were related to the pentose phosphate pathway, glutathione metabolism, and nitrogen metabolism. The identified salt-responsive DRPs influence energy management, maintenance of redox homeostasis, ammonia toxicity, osmotic homeostasis, stress defense and adaptation, and gene transcription. Our investigation clarified the strategies employed by maize Jing724 seedlings to tolerate the adverse effects of a prolonged exposure to salt stress, and elucidated the fundamental molecular networks associated with abiotic stress tolerance. The data presented herein provided the basis for further research on the importance of each protein in plant responses to and acclimation to salt stress.

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FIGURES

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Figure 1. Growth parameters of Jing724 and D9H seedlings under control and saline conditions. Data are presented as the mean ± standard error. (A–G), Seedlings 7 days after germination. (A), Germination rate; (B), shoot fresh weight; (C), shoot dry weight; (D), shoot length; (E), root fresh weight; (F), root dry weight; (G), root length (n = 6). (H–K), Seedlings with three leaves after a 7-day treatment with or without salt. (H), Performance of Jing724 and D9H seedlings after a 7-day exposure to control or saline conditions; (I), shoot fresh weight; (J), shoot dry weight; (K), shoot length (n = 3). Bar = 10 cm. * P < 0.05, ** P < 0.01, and *** P < 0.001.

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Figure 2. Basic iTRAQ output details. (A), Mass distribution of the identified proteins; (B), numbers of peptides that were matched to proteins; (C), distribution of protein’s sequences coverage.

29



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Figure 3. Clustering analysis of differentially regulated proteins (DRPs) and number of DRPs in Jing724 and D9H. (A), Clustering analysis of DRPs. The scale bar indicates up-regulated (red) and down-regulated (green) DRPs. 1, 2, 3 and mean refer to the replicate number and mean value; (B), number of DRPs in salt-treated Jing724 and D9H seedlings. The overlapping region of the Venn diagram indicates the DRPs common to Jing724 and D9H seedlings under saline conditions.

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Figure 4. Classification of differentially regulated proteins based on the cluster of orthologous groups of proteins (KOG) database.

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Figure 5. Functional categorization of differentially regulated proteins in Jing724 and D9H seedling roots. Red and green bars represent increased and decreased protein abundances, respectively.

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Figure 6. Changed metabolic pathways in salt-treated Jing724 seedlings. Red box indicates the increased proteins under saline conditions. The green boxes represent substrates and metabolites. (A), Pentose phosphate pathway; (B), glutathione metabolism; (C), nitrogen metabolism. The enriched KEGG pathways were integrated and visualized using the Cell Designer program (version 4.0).

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Figure 7. Protein interaction network consisting of differentially regulated proteins in salt-stressed Jing724 seedlings. The network was constructed using the String program (http://www.string-db.org/) with a confidence score higher than 0.7. Nodes represent proteins, and the thickness of lines between nodes represents the strength of the supporting data.

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Figure 8. Physiological analysis of Jing724 and D9H seedlings under control or saline conditions. Seedlings with three leaves were treated with or without 100 mM NaCl for 7 days, after which the leaves and roots were collected for a physiological assay. (A), Leaf superoxide dismutase (SOD) activity; (B), leaf malondialdehyde (MDA) content; (C), leaf relative electrolyte leakage (REL); (D), root proline (Pro) content; (E), root MDA content; (F), root REL (n = 6).

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Figure 9. Effect of salt stress on the mRNA levels of eight selected DRPs. Maize actin 1 (GRMZM2G126010) was used as the internal reference (n = 3).

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Figure 10. Molecular model in salt stressed Jing724 and D9H. The model was developed based on the annotated biological functions of DRPs and the relevant published literature. (A), Molecular model for salt tolerance in Jing724 seedlings; (B), molecular model for salt sensitivity in D9H seedlings.

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TABLES

Table 1. Details regarding differentially regulated proteins related to salt tolerance. Protein name

Annotation

Coverage (%)

No. of unique peptides

Fold change (Mean ± SD)

P value

Function

GRMZM2G031107

glucose-6-phosphate 1-dehydrogenase

12.2

3

1.20 ± 0.08

0.0385

Coenzyme transport and metabolism

GRMZM2G127798

6-phosphogluconate dehydrogenase isoenzyme B isoform 1

43.8

5

1.27 ± 0.04

0.0058

Oxidoreductase activity

GRMZM2G145715

NADPH producing dehydrogenase

47.9

5

1.22 ± 0.03

0.0065

Carbohydrate transport and metabolism

GRMZM2G137839

ascorbate peroxidase

46.0

2

1.27 ± 0.06

0.0123

Oxidoreductase activity

AC197758.3_FGP0 04

peroxidase 52 precursor

32.7

4

1.62 ± 0.28

0.0400

Antioxidant activity

GRMZM2G036921

peroxiredoxin-5

17.2

3

1.48 ± 0.09

0.0082

Posttranslational modification, protein turnover, chaperones

GRMZM2G308463

short-chain dehydrogenase reductase 3a-like

30.3

5

1.67 ± 0.03

0.0005

Lipid transport and metabolism

GRMZM2G024104

glutamine synthetase root isozyme 2 isoform 1

12.7

3

1.63 ± 0.15

0.0122

Amino acid transport and metabolism

GRMZM2G085078

glutamate synthase

26.7

4

1.61 ± 0.19

0.0203


GRMZM2G078143

hydroxymethyltransferase

24.1

6

1.27 ± 0.04

0.0053


GRMZM2G462140

dihydrolipoyl dehydrogenase

46.0

2

1.29 ± 0.03

0.0030

Energy production and conversion

GRMZM2G085747

NAD-dependent malic enzyme

13.6

7

1.21 ± 0.08

0.0355

Energy production and conversion

GRMZM2G022645

lysM domain receptor-like kinase 4

9.6

5

1.45 ± 0.19

0.0458

Signal transduction mechanisms

GRMZM2G145518

chitinase

12.9

2

1.57 ± 0.18

0.0234

Defense

GRMZM2G453805

chitinase chem 5 precursor

8.8

2

1.40 ± 0.12

0.0205

Cell wall /membrane /envelope biogenesis

GRMZM2G465226

pathogenesis-related protein 1 zeamatin precursor

52.8

4

2.01 ± 0.08

0.0010

Defense

26.9

5

1.40 ± 0.12

0.0227

Defense

GRMZM2G374971

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ASSOCIATED CONTENT

Supporting Information File S1- Labeling efficiencies for all samples in this study. (TXT, 2 K) Table S1- qRT-PCR primers used in this study. (DOC) Table S2- Effect of salt treatment on growth parameters of Jing724 and D9H seedlings 7 days after germination. (DOC) Table S3- Raw data used to identify peptides of Jing724 and D9H seedlings under control and saline conditions. (XLS, 4.8 M) Table S4- Proteins whose abundance changed only in Jing724 seedlings. (XLS, 46 K) Table S5- Proteins whose abundance changed in Jing724 and D9H seedlings. (XLS, 32 K) Table S6- Proteins whose abundance changed only in D9H seedlings. (XLS, 183 K) Table S7- KEGG pathway enrichment of 241 down-regulated DRPs in D9H seedlings. (XLS, 17 K) Table S8- KEGG pathway enrichment of 189 up-regulated DRPs in D9H seedlings. (XLS, 18 K) Figure S1- Top 20 enriched pathways in Jing724 and D9H seedlings. For each pathway, the rich factor was calculated as follows: numbers of DRPs from an annotated pathway / all proteins from an annotated pathway. (DOC) Figure S2- Changed metabolic pathways involved in stress defense in Jing724 seedlings. (DOC)

39



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Figure S3- Protein interaction network consisting of differentially regulated proteins in salt-treated D9H seedlings. Nodes represent proteins, and the thickness of lines between nodes represents the strength of the supporting data. (DOC) Figure S4- Distribution of SNPs on chromosomes between Jing724 and D9H. (DOC)

AUTHOR INFORMATION

Corresponding Author

*Tel: (010) 51503936; fax: (010) 51503404; email: [email protected], [email protected].

Author Contributions

MJL, YXZ (Yanxin Zhao), WS and JRZ conceived the experiment. MJL and YXZ (Yanxin Zhao) performed the research and collected data. MJL, YXZ (Yanxin Zhao), ZS, YDW, YXZ (Yunxia Zhang) and PPZ analyzed the data and wrote the manuscript. All authors made the revision of the manuscript and approved this submission. † These authors contributed equally.

Notes The authors declare no competing financial interest. Funding Sources

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This research was financially supported by the BAAFS Innovation Team of Corn Germplasm Innovation and Breeding of New Varieties (No. JNKYT201603) and the Postdoctoral Fellow Fund of BAAFS (No. JNKYB2016).

ACKNOWLEDGMENT The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD007711 and PXD007802. We would like to thank James C. Schnable (The University of Nebraska-Lincoln) for his help in editing of this manuscript.

ABBREVIATIONS QTL, quantitative trait locus; iTRAQ, isobaric tags for relative and absolute quantitation; LC-MS/MS, liquid chromatography coupled with tandem mass spectrometry; GR, germination rate; qRT-PCR, quantitative real-time polymerase chain reaction; SFW, shoot fresh weight; SL, shoot length; RFW, root fresh weight; RL, root length; SDW, shoot dry weight; RDW, root dry weight; SOD, superoxide dismutase; MDA, malondialdehyde; REL, relative electrolyte leakage; Pro, proline; ROS, reactive oxygen species; HCD, high-energy collisional dissociation; DRP, differentially regulated protein; KOG, Eukaryotic Orthologous Groups; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology. REFERENCES

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