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The physiological and iTRAQ-based proteomic analyses reveal the function of spermidine on improving drought tolerance in white clover Zhou Li, Yan Zhang, Yi Xu, Xinquan Zhang, Yan Peng, Xiao Ma, Linkai Huang, and Yanhong Yan J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 31 Mar 2016 Downloaded from http://pubs.acs.org on March 31, 2016

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Journal of Proteome Research

The physiological and iTRAQ-based proteomic analyses reveal the function of spermidine on improving drought tolerance in white clover Zhou Li1‡, Yan Zhang1‡, Yi Xu2, Xinquan Zhang1, Yan Peng1*, Xiao Ma1, Linkai Huang1, and Yanhong Yan1 1

Department of Grassland Science, College of Animal Science and Technology, Sichuan

Agricultural University, Chengdu, CHN 611130 2

Department of Plant Biology and Pathology, Rutgers University, 59 Dudley Road, New

Brunswick, NJ 08901

KEYWORDS: Differentially expressed proteins, gene expression, hormone, metabolic pathway, photosynthesis, polyamine

ABSTRACT: Endogenous spermidine interacting with phytohormones may be involved in regulation of differentially expressed proteins (DEPs) associated with drought tolerance in white clover. Plants treated with or without spermidine (50 µM) were subjected to 20% PEG 6000 nutrient solution to induce drought stress (50% leaf relative water content). The results showed that increased endogenous spermidine induced by exogenous spermidine altered endogenous phytohormones in association with improved drought tolerance, as demonstrated by the delay in water deficit development, improved photosynthesis and water use efficiency, and lower oxidative damage. As compared to untreated plants, Spd-treated plants maintained higher abundance of DEPs under drought stress involved in 1) proteins biosynthesis 1

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(ribosomal and chaperone proteins); 2) amino acids synthesis; 3) the carbon and energy metabolism; 4) antioxidant and stress defense (ascorbate peroxidase, glutathione peroxidase, and dehydrins; and 5) GA and ABA signaling pathways (gibberellin receptor GID1, ABA-responsive protein 17, and ABA stress ripening protein). Thus, the findings of proteome could explain the Spd-induced physiological effects associated with drought tolerance. The analysis of functional protein-protein networks further proved that the alteration of endogenous spermidine and phytohormones induced the interaction among ribosome, photosynthesis, carbon metabolism, and amino acid biosynthesis. These differences could contribute to improved drought tolerance. INTRODUCTION

Polyamines (PAs), including putrescine (Put), spermidine (Spd) and spermine (Spm), are known as important plant growth regulators (PGRs) required for the normal growth and response to various stresses1,2. It has been documented that drought-resistant plants exhibited significantly higher endogenous PAs content than sensitive plants when subjected to drought stress3,4. Exogenous application of PAs could improve drought tolerance in barley (Hordeum vulgare)5, rice (Oryza sativa)6, and creeping bentgrass (Agrostis stolonifera)7, while the deficiency of PAs via the down-regulation of a Spd synthase gene in transgenic pear (Pyrus communis) or due to the application of PAs biosynthetic inhibitor in white clover caused the negative effects on physiological changes and stress defense under salinity, cadmium, and drought stresses8,9, which suggested the critical function of PAs in plants in response to environmental stresses. A variety of physiological and molecular mechanisms of tolerance induced by PAs have been reported in different plant species associated with antioxidant defense, osmotic adjustment, proline metabolism, and specific gene expression10-12. Recent 2


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increasing findings also indicated that PAs could play an essential role as signaling molecules through regulating signal transduction pathway against abiotic stress9,13,14. In spite of these facts, it is still not fully elucidated that how these processes alter when plants exhibit different endogenous PAs content but suffer from the same level of leaf water deficit. In plants, a great number of biological processes and stress responses are regulated by phytohormones15. Drought defense mechanisms involved in abscisic acid (ABA), cytokinin (CTK), gibberellic acid (GA), and indole-3-acetic acid (IAA) have been documented in earlier reports, with ABA mainly affecting stomatal closure16, CTK mediating leaf senescence17, GA and IAA altering plants growth under drought stress18,19. In addition, previous findings have implied that PAs could interact with other phytohormones to regulate plants growth and stress tolerance. For instance, significantly increased endogenous IAA, ABA, and CTK content were observed through exogenous application of Spd during wheat (Triticum aestivum) grain filling20, whereas exogenous Spd inhibited GA and IAA accumulation in creeping bentgrass (Agrostis stolonifera) during drought stress21. Accompanied by a decrease in ABA content using ABA biosynthesis inhibitor, PAs accumulation also declined in salt-stressed maize (Zea mays) leaf22. However, alterations of stress-induced phytohormones depend on the severity of stress and plant species23,24. Much deeper insight is still required to understand synergetic roles between PAs and phytohormones in drought tolerance. To cope with abiotic stress, protein synthesis and accumulation serve as a central strategy in plants through signal transduction, phosphorylation as well as oxidation, and have a more direct reflection on regulatory mechanism than that on mRNA transcript level25,26. PAs and phytohormones were both involved in modification of protein accumulation and functions. The study of Legocha and Zajchert27 found that Spd could keep thylakoid membrane proteins stable during leaf senescence. Spd and ABA mediated a cytoplasmic protein expression in

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rice in response to salt stress28. Under drought or osmotic stress, PAs could stabilize the conformation of photosystem II proteins29. However, these findings only covered a small part of stress-related proteins which could be regulated by PAs or phytohormones. Recently, iTRAQ-based proteome analysis has been carried out to elucidate mechanisms of stress responses in plant species such as maize under drought stress30, grape (Vitis vinifera) under heat stress31, and Listeria monocytogenes under cold and osmotic stress32, because of technical advantages in higher identification rate of low-abundance proteins and more accurate quantification of proteins as compared to traditional 2D gel electrophoresis analysis33. Nevertheless, little iTRAQ-based studies were conducted to investigate PAs-induced drought tolerance in plants. How the interaction between endogenous PAs and phytohormones in response to drought stress may affect alteration of global proteome that has not been clearly elaborated yet. Therefore, in this study, PAs-regulated drought tolerance interacting with phytohormones in white clover (Trifolium repens) will be further discussed and the iTRAQ-based proteome will provide a more integrated picture of drought tolerance triggered by PAs and phytohormones.

MATERIALS AND METHODS

Plant material and treatments

Seeds of white clover (cv. Ladino, drought-sensitive) were sterilized with 0.1% mercuric chloride solution for 4 min and then washed in distilled water for 3 times. The plastic trays (24 cm length, 20 cm width and 15 cm deep) were used for cultivating plants and 0.1 g seeds were sown in each tray filled with sterilized quartz sand and distilled water. A controlled growth chamber was set at 23/19 °C day/night temperature, 12 h photoperiod, 500 µmol·m-2·s-1 photosynthetically active radiation, and 75% relative humidity. After 7 d of germination in growth chamber, the distilled water in tray was replaced by full-strength 4


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Hoagland’s nutrient solution34 and plants were cultivated for another 23 d with replacing the solution every other day. Drought was induced by polyethylene glycol (PEG) 6000 dissolved in Hoagland’s solution in this study. Osmotic potential of 20% PEG solution was maintained -0.5 MPa (Vapro pressure osmometer, Wescor, Inc. Logan, UT 84321, USA). Plants were subjected to three treatments: 1) C: well-watered control; 2) D: drought; 3) D+S: drought-stressed plants treated with 50 µM Spd (Spermidine trihydrochloride, Sigma, SKU 85578). Plants were pretreated with 50 µM Spd nutrient solution for 3 d before stress. All treatments were arranged randomly inside growth chambers and replicated four times. When the relative water content (RWC) in leaves declined to 49%–51% (no statistically significant difference, moderate drought stress) for drought-stressed plants treated with or without exogenous Spd, leaf samples were taken for all the measurements described below. This meant that drought-stressed control plants were sampled on the sixth day (49% RWC), and samples were collected for drought-stressed plants treated with Spd (51% RWC) and non-stressed control (88% RWC) on the seventh day. The second leaf on several stems from each plant was harvested for all analyses. Each treatment had 4 independent biological replicates, and each biological replicate includes 1 technical replicate.

The measurement of endogenous polyamines and phytohormones

For determination of PAs, 0.2 g leaves were ground in 1 mL cold perchloric acid (5%, v: v) incubating at 4 °C for 1 h and then centrifuged for 30 min (12000 rpm, 4 °C). The supernatant was benzoylated. 500 µL supernatant mixed with 2 mL NaOH (2 M) and 10 µL benzoyl chlorides and then were incubated at 37 °C for 30 min. 2 mL saturated NaCl was added into the mixed solution to terminate the reaction. 2 mL cold diethylether was used for extracting benzoyl polyamine. Finally, 1 mL of the ether phase was evaporated to dryness and re-dissolved in 1 mL methanol for determination of endogenous PAs35. The method of

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Volmaro et al.36 was used for extracting hormones including ABA, GA and IAA with some modification. 0.2 g leaves were homogenized with 2 mL 80% cold methanol and the homogenate was incubated for 12 h at 4 °C in the dark. After centrifugation at 5000 rpm for 15 min at 4°C, 2 mL supernatant was collected in a new centrifuge tube and evaporated to dryness. Finally, 1 mL mixture of methanol and 0.6% acetic acid (50: 50, v: v) was added into the centrifuge tube. The endogenous PAs or hormone content was measured through high performance liquid chromatography (HPLC, Agilent-1200, Agilent Technologies, USA). 20 µL of hormone or benzoyl PAs extract was loaded onto a reverse-phase Tigerkin®C18 column (150mm×4.6mm, 5µm particle size) and 35 °C or 25 °C column temperature was maintained for determination of hormone or PAs, respectively. For hormone, the mobile phase was methanol-0.6% acetic acid (50: 50, v: v) and for PAs, methanol-H2O (64: 36, v: v) was used as the mobile phase. Hormone or PAs peaks were monitored with a UV detector at a flow rate of 1 mL min-1 at 254 nm. The method of enzyme linked immunosorbent assay (ELISA) was used to quantify endogenous CTK content (The CTK assay kit, Shanghai Jining Biological Technology Co. Ltd., China.). 0.2 g leaves were homogenized in 3 mL PBS (0.1 M, pH 7.4, and 4 °C) and then centrifuged for 20 min at 4 °C. The supernatant was collected for measurement of CTK content. The procedure was carried out according to the specification. Simply, 40 µL sample dilution and 10 µL CTK extract were added in microtiter plate coated solid-phase antibody and gently mixed, and then the plate was incubated for 30 min at 37 °C. The solution in plate was discarded and each plate well was washed with 200 µL washing buffer for 5 times. After drying the plate, 50 µL HRP-conjugate reagents were added to each plate well and the plate was incubated for 30 min at 37 °C. After washing plate wells 5 times with washing buffer, the chromogen A and B were added in each well incubating at 37 °C for 15 min in the dark.

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The absorbance of reaction mixture was read at 450 nm after adding stop solution within 15 min on a microplate reader (Synergy HTX, Bio Tek, USA).

The measurement of leaf water status and oxidative damage Leaf RWC was calculated according to the RWC (%) = [(FW – DW)/(TW – DW)]×10037. FW, TW, or DW means fresh weight, turgid weight, and dry weight, respectively. For the measurement of generation of superoxide anion radical (O2.-), the method of Elstner and Heupel was used38. The hydrogen peroxide (H2O2) was assayed according to potassium iodide (KI) method39. Briefly, 0.1 g leaves were homogenized with 5 ml 0.1% TCA and centrifuged at 12000 rmp for 20 min. 0.5 ml 10 mM potassium phosphate and 1 ml 1 M KI were added to 0.5 ml of supernatant. The absorbancy of reaction was recorded at 390 nm. The malondialdehyde (MDA) content was determined and calculated according to the method described by Dhindsa et al.40. Electrolyte leakage (EL) was detected by using a conductivity meter (YSI Model 32, Yellow Spring, OH) and calculated as the percentage of initial conductivity (Cinitial) and maximum conductance (Cmax)41.

The analysis of chlorophyll content and photosynthesis

0.1 g fresh leaves were immerged in 10 mL of dimethyl sulphoxide in the dark for 48 h, and then the leaf extract was measured with a spectrophotometer (Spectronic in Instruments, Rochester, NY, USA) at 663 nm and 645 nm. The formula described in Arnon42 was used for calculating chlorophyll (Chl) content. Net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (gs) were measured using a photosynthetic apparatus (Li-Cor 6400, Li-Cor, Inc., Lincoln, NE). One layer of leaves was placed in the leaf chamber, which provided 400 µL·L-1 CO2 and 800 µmol photon m-2 red and blue light. After measurement, leaf samples were cut from plants and then scanned with Magic WandTM Portable Scanner 7



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(PDS-ST415-VPS, VuPoint Solutions) to calculate actual leaf area. Water use efficiency (WUE) was calculated following the formula: WUE= Pn/Tr.

Protein extraction and iTRAQ labeling

400 mg mixed leaf samples (100 mg leaf sample for each replicate and four replicates for each treatment) were ground in liquid nitrogen and fine powder was extracted in Lysis buffer (2 M Thiourea, 7 M Urea, 40 mM Tris-HCl, 4% CHAPS, 1mM PMSF, and 2mM EDTA pH 8.5). After 5 min, 10 mM DTT was added to the samples. The supernatant was centrifuged (30000 rpm) for 15 min at 4 °C. The supernatant was mixed with 5× chilled acetone and then incubated at -20 °C overnight. After centrifugation (30000 rpm and 4 °C), the supernatant was discarded. Chilled acetone was used to wash the precipitate 3 times. The precipitate was air-dried and then dissolved in Lysis buffer. After sonicated for 15 min at 200 W, the suspension was centrifuged (30000 rpm) at 4 °C for 15 min. 10 mM DTT was added into the supernatant in order to reduce disulfide bonds of proteins, and supernatant was incubated for 1 h at 56 °C. After that, 55 mM IAM was added and the mixture was incubated in dark for 1 h. In order to precipitate proteins, 55× chilled acetone was mixed with the supernatant at -20 °C for 2 h. The mixture was centrifuged at 4°C, and the sediment was air-dried for 5 min, and then dissolved in 500 µL 0.5 M triethylammonium bicarbonate (TEAB). At last, mixture was centrifuged (30000 rpm) for 15 min at 4 °C. The supernatant was the total proteins. 100 µg proteins of each sample solution were digested with Trypsin Gold (30:1, Promega, Madison, WI, USA) for 16 h at 37 °C. The mixture was dried by using vacuum centrifugation. Sediment was reconstituted in 0.5 M TEAB for 8-plex iTRAQ reagent (Applied Biosystems) according to the manufacture’s protocol. Briefly, 24 µL isopropanol mixed with one unit of iTRAQ reagent. Samples were labeled with the iTRAQ tags as follow: sample ‘C’ (119 tag),

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sample ‘D’ (114 tag), and sample ‘D+S’ (115 tag). The labeled peptides with the isobaric tags were incubated at room temperature for 2 h, and then dried by using vacuum centrifugation.

LC-ESI-MS/MS analysis

The iTRAQ-labeled peptides were subjected to a LC-20AB HPLC Pump system (Shimadzu, Kyoto, Japan) for SCX fractionation in an Ultremex SCX column (4.6 × 250 mm) containing 5 µm particles prior to LC-ESI-MS analysis. The eluted peptides were pooled into 20 fractions, and desalted with a Strata X C18 column and then vacuum-dried. Each fraction was resuspended in buffer A (5% ACN, 0.1%FA) and centrifuged at 20000 rpm for 10 min. 10 µL supernatant was loaded on a LC-20AD nanoHPLC (Shimadzu, Kyoto, Japan) with a C18 column trap column (2 cm) and then was eluted onto an analytical C18 column (10 cm, inner diameter 75 µm) packed in-house for 4 min at 8 µL·min-1, and then the samples were run for 35 min gradient at 300 nL·min-1 from 2% to 35% B (95%ACN, 0.1%FA), 5 min linear gradient to 60%, 2 min linear gradient to 80%, and then maintenance at 80% B for 4 min, return to 5% in 1 min at last. A Triple TOF 5600 System (AB SCIEX, Concord, ON) was used (the accuracy of both first and second mass less than 2 ppm) and parameters were set as follows: the ion spray voltage, curtain gas, nebulizer gas, and the interface temperature was 2.5 kV, 30 psi, 15 psi, 150 °C, respectively; the MS survey scan was set to a ≥30000 resolution from 350 to 1600 mass range; only first 30 product ion (precursors) were collected if these precursors with a 2+ to 5+ charge-state exceed a threshold of 120 counts per second (counts/s); the cycle time was 3.3 s. Q2 transmission window was set to 100 Da with 100% efficiency (a pulser frequency value was 11 kHz and monitoring frequency of detector was 40 GHz). Fragmentation was conducted by higher-energy collision dissociation with a 17500 resolution. A normalized

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collision energy was set at 35±5 eV, and dynamic exclusion was set for 1/2 of peak width (15 s) and no more than twice for the fragmentation of same ion.

Database search and protein quantification

Raw data files were acquired from the Triple TOF, and then converted into MGF files by using Proteome Discoverer 1.2 (PD 1.2, Thermo). Proteins identification was performed by using Mascot search engine (Matrix Science, London, UK; version 2.3.02). Mascot search parameters were showed in Table 1. Only peptides with significance scores (>= 20) at the 99% confidence interval were identified as counted confident proteins in order to reduce the probability of false peptide identification. At least one unique peptide was involved in the identification of every confident protein. The relative quantification of protein was based on the strength of reporter ion which reflects the relative abundance of peptide. The protein ratio (fold change) was obtained according to different comparison groups (D/C, (D+S)/C, and (D+S)/D) through reporter ion ration labeled with different isotope as described above. To become differentially expressed protein (DEPs), a protein contains at least two unique spectra, and only these unique spectra can be used for quantification of proteins. Only fold change ≥1.2 or ≤ 0.8 (the ratios with p-values pyro-Glu (N-term Q), Oxidation (M), iTRAQ8plex (Y) ± 0.05 Da Default 1 Carbamidomethyl (C), iTRAQ8plex (N-term), iT RAQ8plex (K) NCBI Trifolieae (114062 seqs before de-redundance, and 58574 seqs after de-redundance)

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Table 2. The number of differentially expressed proteins (DEPs) in leaves of white clover. C, normal water condition; D, drought induced by 20% PEG; D+S, drought induced by 20% PEG containing 50 µM Spd.

Type D/C (D+S)/C (D+S)/D

Increase 90 138 42

Decrease 80 55 21

Each total 170 193 63

Total DEPs 273

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Table 3. The 47 key differentially expressed proteins (DEPs) associated with drought tolerance and physiological parameters or overlapped in all comparison groups in leaves of white clover in response to drought and exogenous spermidine (Spd). Proteins are regard as differentially regulated proteins if the proteins abundance was equal to or greater than 1.2-fold or less than 0.8-fold (P≤0.05). The ‘ns’ indicates no significant difference. C, normal water condition; D, drought induced by 20% PEG; D+S, drought induced by 20% PEG containing 50 µM Spd. Hit number

Accession No.

Protein Name

Fold change D/C

(D+S)/C

(D+S)/D

Translation, ribosomal structure and biogenesis 277 AFK37098.1 Ribosomal protein L2 335 AES74325.1 50S ribosomal protein L3

ns 0.7

1.3 ns

1.3 1.3

407 549 705

0.6 0.8 ns

0.4 1.3 1.4

0.7 1.6 1.2

Amino acid transport and metabolism 78 Q9XQ94.1 Glutamine synthetase leaf isozyme, chloroplastic 107 AES95912.1 Serine hydroxymethyltransferase 348 AES98669.1 Asparagine synthetase 399 AES71934.1 Serine hydroxymethyltransferase 412 CAA43779.1 Aspartate aminotransferase 933 Q43785.1 Glutamine synthetase nodule isozyme 1428 AFK48655.1 Aspartate/tyrosine/aromatic aminotransferase

0.7 0.7 0.7 ns 1.5 0.7 0.7

ns ns ns 1.4 1.5 ns ns

1.3 ns 1.3 ns ns 1.4 ns

Carbohydrate transport and metabolism 10 ADU86354.1 Ribulose-1,5-bisphosphate carboxylase/oxygenase 62 AES66343.1 Phosphoglycerate kinase 85 AES60276.1 Malate dehydrogenase 203 AES82642.1 Chloroplast ribose-5-phosphate isomerase

0.7 ns 1.3 0.7

ns 1.2 1.2 0.7

1.3 1.2 ns ns

Putative plastidic aldolase Pyruvate orthophosphate dikinase Beta-galactosidase

0.8 0.7 0.7

0.6 0.8 0.5

0.8 1.2 0.8

Apocytochrome f Light-harvesting complex II Chl a/b binding 1 L-H complex I Chl a/b BP 3 Photosystem I P700 apoprotein A1 Photosystem I reaction center subunit IV Photosystem I subunit III

ns 0.6 1.3 0.8 ns 1.4

ns ns 1.7 ns 1.4 2.1

1.2 ns 1.3 1.5 1.6 1.4

AES60890.1 AFK48929.1 CAB65281.1

448 ABV54715.1 647 AES91735.1 1087 AES67859.1 Energy production and conversion 53 YP_002456448.1 58 AFK40061.1 131 AFK45661.1 151 YP_002456473.1 165 AFK44960.1 225 AFK41712.1

Ribosome-recycling factor Ribosomal protein L15 L3 Ribosomal protein

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338 558

AES63593.1 AES77744.1

Soluble inorganic pyrophosphatase Photosystem II CP43 chlorophyll apoprotein

0.8 0.8

0.6 ns

0.8 1.3

690 704 708 2199

ACA47401.1 AES71127.1 AFK35397.1 YP_002456487.1

Chloroplast Chl-a/b binding protein Light-harvesting complex II Chl a/b binding 4 Light-harvesting complex I Chl a/b binding 1 Photosystem I subunit VII

0.7 0.8 0.8 ns

0.8 ns ns 1.3

1.5 1.3 ns ns

ns 0.7

1.2 ns

ns ns

0.7

1.6

1.8

ns ns 0.8 0.8 1.5

1.2 1.3 0.3 0.6 1.9

ns ns 0.4 0.7 1.3

0.8

ns

ns

14-3-3-like protein gf14-6

0.7

0.5

0.6

Dehydrin b Abscisic acid stress ripening protein Gibberellin receptor GID1

1.5 ns ns

2.1 2.7 1.4

1.3 1.7 ns

Inorganic ion transport and metabolism 128 AES73783.1 Plasma membrane H+-ATPase 162 AFV96158.1 Catalase, partial 979 AFK44173.1 Ascorbate peroxidase Posttranslational modification, protein turnover, chaperones 255 AES88177.1 DnaJ-class molecular chaperone 530 AET04996.1 Glutathione peroxidase 1091 AES80986.1 Protein grpE 1133 AFK33472.1 20S proteasome 1494 ABN08541.1 GroES-like Signal transduction mechanisms 791 AES66660.1 14-3-3-like protein GF14 883 AET04239.1 Other biological processes 256 ADD09608.1 313 AES62349.1 444 XP_013452514.1 923 1956 Unclear

AES65089.1 AAP92164.1

ABA-responsive protein ABR17 Histone H1

0.5 1.7

1.4 2.3

2.7 1.3

901

AFK38466.1

Unknown

0.6

0.5

0.8

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Table S1-Primer sequences used in this study. (XLS) Table S2-The abundance of all differentially regulated proteins (DEPs) in leaves of white clover in response to drought stress and exogenous spermidine (Spd). (XLS)

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Figure S1-Gene ontology (GO) analysis of all identified 2853 proteins in leaves of white clover including cellular component, molecular function, and biological process under drought stress. (XLS) Figure S2-The clusters of orthologous groups (COG) function of all identified 2853 proteins in leaves of white clover under drought stress. (XLS)

AUTHOR INFORMATION Corresponding Author *Tel: (028) 86290111; fax: 028-(028) 82652669; e-mail: [email protected].

Author Contributions All authors have given approval to the final version of the manuscript. ‡These authors contributed equally.

Notes The authors declare no competing financial interest. ACKNOWLEDGMENT This study was supported by grants from the National 973 Basic Research Project of China (No. 2014CB138705), the National Natural Science Foundation of China (No. 31372371) and Si Chuan Province Support Project (No. 2013NZ0013).

REFERENCES (1) Kaur-Sawhney, R.; Tiburcio, A. F.; Altabella, T.; Galston, A. W. Polyamines in plants: an overview. J. Cell Mol. Biol. 2003, 2, 1–12. (2) Liu, J. H.; Kitashiba, H.; Wang, J.; Ban, Y.; Moriguchi, T. Polyamines and their ability to provide environmental stress tolerance to plants. Plant Biotechnol. 2007, 24, 117–126. 41



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