Metabolic Pathways Regulated by Chitosan Contributing to Drought

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Metabolic pathways regulated by chitosan contributing to drought resistance in white clover Zhou Li, Yan Zhang, Xinquan Zhang, Emily Merewitz, Yan Peng, Xiao Ma, Linkai Huang, and Yanhong Yan J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00334 • Publication Date (Web): 13 Jul 2017 Downloaded from http://pubs.acs.org on July 16, 2017

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Journal of Proteome Research

Metabolic pathways regulated by chitosan contributing to drought resistance in white clover Zhou Li1‡, Yan Zhang1‡, Xinquan Zhang1, Emily Merewitz2,*, Yan Peng1,*, Xiao Ma1, Linkai Huang1, Yanhong Yan1 1

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

Agricultural University, Chengdu 611130, China 2

Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing,

MI 48824, United States

ABSTRACT: Increased endogenous chitosan (CTS) could be associated with improved drought resistance in white clover (Trifolium repens). Plants were pretreated with or without 1 mg/mL CTS and then were subjected to optimal or water-limited condition in controlled growth chambers for 6 days. Phenotypic and physiological results indicate that exogenous CTS significantly improved drought resistance of white clover. Metabolome results showed that exogenous CTS induced a significant increase in endogenous CTS content during dehydration accompanied by the maintenance of greater accumulation of sugars, sugar alcohols, amino acids, organic acids and other metabolites (ascorbate, glutathione, flavonoids, putrescine, and spermidine). These compounds are associated with osmotic adjustment, antioxidant defense, stress signaling, and energy metabolism under stress condition. Similarly, transcriptome revealed that many genes in relation to amino acid and carbohydrate metabolism, energy 1

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production and conversion, ascorbate-glutathione and flavonoid metabolism were significnatly up-regulated by CTS in response to dehydration stress. CTS-induced drought resistance was associated with the accumulation of stress protective metabolites, the enhancement of ascorbate-glutathione and tricarboxylic acid cycle, and increases in the γ-aminobutyric acid shunt, polyamine synthesis, and flavonoids metabolism contributing to improved osmotic adjustment, antioxidant capacity, stress signaling, and energy production for stress defense, thereby maintaining metabolic homeostasis under dehydration stress. KEYWORDS: differentially expressed genes, growth, metabolite, metabolome, osmotic adjustment, transcriptome INTRODUCTION

Predicted climate change could increase drought-induced limitations to crop productivity in the future. Among other environmental stresses, dehydration stress is already one of the most detrimental abiotic stresses that limit crop yield and quality worldwide

1-3

. White clover

(Trifolium repens) is an important cool-season forage legume and widely distributed in temperate grassland systems due to roles in biological nitrogen fixation and high feed value. Compared to other legume forage species such as alfalfa (Medicago sativa), white clover is more susceptible to dehydration stress due to a shallow root system and high leaf transpiration rates. Consequently, white clover often does not achieve potential productivity or yields because of water limitation

4-6

. Therefore, improved drought resistance of white

clover is important for adequate cultivation practices during rising global temperatures and potential decreases in available irrigation water resources. Chitosan (CTS) is a ubiquitous and natural compound in plants acting as an elicitor associated with plant growth and tolerance to various stresses 2


7-9

. Exogenous CTS has been

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applied to increase yield and quality of crops including cowpea (Vigna unguiculata), potato (Solanum tuberosum), common bean (Phaseolus vulgaris), and wheat (Triticum aestivum) under normal or stress conditions

10-13

. The application of exogenous CTS or the change of

endogenous CTS significantly contributes to increased disease resistance and host defense response in a variety of plant species

14-17

. CTS-regulated mechanisms of disease control

might be involved in the protection of cell membranes, the induction of oxidative bursts to regulate signaling transduction, ion flux variations, and the activation of protein phosphorylation and defense-related genes in plants

18-20

. Recent studies have also suggested

that CTS is involved in resistance to abiotic stresses such as dehydration, salt, and cadmium stress via the enhancement of photosynthetic pigments, the accumulation of total sugars and soluble proteins, and the improvement of some antioxidant enzyme activities in plants

21-24

.

Despite these studies, which only evaluated some physiological responses, molecular mechanisms associated with CTS content during plant dehydration stress are still not fully understood. Abiotic stresses including dehydration can induce an abundance of gene expression changes that are regulated through complex transcriptional networks in plants. Transcription levels of genes are closely related to plant stress tolerance and often result in a change in metabolite levels

25-29

.

Transcriptome and metabolome profiling are effective methods for

analyzing differentially expressed genes (DEGs) and metabolites associated with drought resistance 30, 31. Previous studies on white clover have shown that some genes and metabolites associated with antioxidant defense, proline, and sugar metabolism played critical roles in drought resistance 32-34. However, limited research has been done on CTS-induced changes of global DEGs and metabolites linking up with metabolic pathways for plants adaptation to dehydration. Thus, combining metabolomic and transcriptomic analyses will provide a

3



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comprehensive picture to explore the CTS-regulated mechanism of drought resistance in white clover. The objectives of this study were to 1) evaluate the effects of exogenous CTS on improving drought resistance in white clover through phenotypic and physiological analyses; 2) determine major metabolic pathways regulated by CTS associated with drought resistance via metabolic and transcript profiling; and 3) reveal the CTS-regulated mechanism of drought resistance in conjunction with physiological, metabolomic, and transcriptomic data.

MATERIALS AND METHODS

Plant material and treatments White clover (‘Ladino’) seeds were sterilized in 0.1% mercuric chloride for 5 min, and rinsed four times with deionized water (ddH2O), and then 0.1 g seeds were sown in each pot (24 cm length, 15 cm width, and 8 cm deep) filled with sterilized quartz sand and ddH2O in growth chambers (day/night temperatures of 21/18°C and 790 µmol·m-2·s-1 photosynthetically active radiation) for 7 d of germination. After that, the ddH2O was replaced by Hoagland’s solution 35

, and plants were grown for another 23 days under the same growth conditions. For the CTS

treatment, plants were pretreated with Hoagland’s solution containing 1 mg/mL CTS (viscosity: 5-30 mPa·S) for 2 days before being exposed to dehydration stress. The concentration of CTS was chosen based on a preliminary test with a range of concentrations (0.1, 0.5, 1, 2, 4, 8 mg/mL) for the most effective concentration on phenotypic changes based on leaf wilt and growth. CTS-treated plants or untreated control plants were then subjected to dehydration stress induced by -0.3 MPa polyethylene glycol (PEG) 6000, followed by four different treatments in growth chambers: 1) C: water-sufficient control; 2) C+CTS: water-sufficient control pretreated with CTS; 3) P: Hoagland’s solution containing PEG 6000; 4) P+CTS: Hoagland’s 4


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solution containing PEG 6000 and CTS. Six replicates (six pots) for each treatment was arranged in a completely randomized design. Leaf samples were collected during 6 d of dehydration stress. The duration of dehydration stress was determined based on stress symptoms (mainly based on leaf color, the degree of leaf wilt, and the inhibition of growth). Four independent replicates were used for the analysis of growth, physiological parameters, and qRT-PCR in each treatment. For metabolite profiling, six independent replicates were used from within each treatment. Mixed leaf samples from four replicates (total of 400 mg) were used for transcriptome analysis (100 mg from each replicate). Growth and physiological analysis 20 randomly selected plants from within each pot were used for the determination of plant height. The formula RGR= (lnWf–lnWi)/∆t was used to calculate mean relative growth rates (RGR) (Wf and Wi equaling final and initial dry weights of plants, respectively, and ∆t equaling the time elapsed (d) between the two measurements). Chlorophyll content was calculated using the formula described in the Arnon (1949)

36

. Each 0.2 g sample of fresh

leaves were immersed in 10 mL of a solution containing 80% acetone and 95% ethanol (1:1, v/v), left in the dark for 48 h, and then the leaf extract absorbance was measured at 663 nm and 645 nm in a spectrophotometer (Spectronic Instruments, Rochester, NY, USA). Leaf relative water content (RWC) was determined from fresh weight (FW), dry weight (DW), and turgid weight (TW) using the formula RWC (%) = [(FW – DW)/(TW – DW)]×100 37. Leaf water potential was determined using a water potential system (PSYPRO Water Potential Datalogger, Wescor Inc., Logan, UT, USA). For determination of osmotic adjustment (OA), fresh leaves were submerged in ddH2O for 8 h at 4°C to fully hydrate leaves. Leaves were ground to extract leaf sap, and 10 mL sap was inserted into an osmometer (Wescor Inc., Logan, UT, USA) to determine osmolality (mmol·kg-1). Osmolality was converted to osmotic potential (OP) according to the formula OP (MPa) = ([osmolality]×[0.001]×[2.58]). OA was 5



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then calculated as the difference in OP between stressed leaves and water-sufficient control leaves 38. For electrolyte leakage (EL), fresh leaves (0.2 g) were immersed in 15 mL of ddH2O for 24 h on a shaker, and then the conductivity of the solution (Cinitial) was measured using a conductivity meter (YSI Model 32, Yellow Springs Instrument Co.). Leaves were boiled at 100°C for 30 min to determine the maximum conductivity of the immersion solution (Cmax). Relative EL was calculated as Cinitial /Cmax×10039. To analyze the content of malondialdehyde (MDA), 0.2 g fresh sample was ground on ice with 3 mL of 50 mM cold phosphate buffer (pH 7.8). After centrifugation at 12000 rpm for 30 min at 4°C, the supernatant was used for assays of MDA. The mixture (0.5 ml supernatant extract and 1.0 ml reaction solution containing 20% w/v trichloroacetic acid and 0.5% w/v thiobarbituric acid) was heated in a water bath at 95°C for 15 min, and then cooled quickly in ice water. The homogenate was centrifuged at 8000 rpm for 10 min, and the absorbance of the supernatant was measured at 532 and 600 nm

40

(Dhindsa et al., 1981). The total antioxidant capacity, hydroxyl radical

scavenging ability (.OH SB), and protein carbonyl content were measured using Assay Kits (Suzhou Comin Biotechnology Co., Ltd., China) using a microplate reader (Synergy HTX, Bio Tek, USA). The superoxide anion radical (O2.-) and hydrogen peroxide (H2O2) were detected according to the methods of Elstner and Heupel (1976) 41 and Velikova et al. (2000) 42

, respectively. For O2.- or H2O2 staining, fresh leaves were cut from the base of the plants

and then immerged in 1 mM NBT for 6 h or 0.1% (w/v) 3-diaminobenzinidine for 24 h, respectively. The leaves were then decolorated with ethanol until all chlorophyll were removed from leaves 43, 44. Metabolite extraction, separation, and quantification The extraction procedure of metabolites was conducted according to methods of Lytovchenko et al. (2002) 45 with some modifications. Leaf samples were ground to a fine 6


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powder. 20 mg of powder was ground with 100 µL ddH2O before transferring to a microcentrifuge tube, and then 500 µL of aqueous methanol (methanol: formyl trichloride=3: 1) was added into the tube. The mixture in the tube was sonicated for 20 min. After centrifugation at 12000 rpm for 10 min, 300 µL supernatant was transferred to a new tube, and 10 µL chlorophenylalanine (0.3 mg/mL; as an internal standard) was added in the tube prior to desiccation in a centrivap benchtop centrifugal concentrator (Labconco, Kansas City, MO). After fully desiccated, the samples were re-dissolved in 80 µL of methoxyamine hydrochloride (15 mg/mL) at 30°C for 90 min, and mixture was trimethylsilylated with 80 µL N-methyl-N-(trimethylsily) trifluoroacetamide containing 1% trimethylchlorosilane for 60 min at 70°C. Treated samples were analyzed by using Comprehensive Two-dimensional Gas Chromatography/Time-of-flight Mass Spectrometry (GC-TOFMS, Pegasus 4D, LECO Corporation, St Joseph, MI, USA). The analysis procedure of GC-TOFMS was followed by the method of Qiu et al. (2009) 46

. Separation (1 µL extracted liquid) was achieved on a DB-5MS capillary column (30 m ×

250 µm I.D., 0.25 µm film thickness; Agilent J&W Scientific, Folsom, CA, USA), and helium was used as the carrier gas at a constant flow rate of 1.0 mL/min. The injection temperature was set at 280 °C, and the temperature of transfer interface and ion source was set at 270 and 220°C, respectively. The initial GC temperature was maintained at 80°C for 0.2 min, and raised to 180°C with 10°C/min oven temperature, followed by 5°C/min to 240°C, and 20°C/min to 280°C, and finally held at 280°C for 11 min. The measurements were made with electron impact ionization (70 eV) at full scan mode (m/z 20–600), and an acquisition rate of 10 spectrum/second in the TOFMS setting was used. The metabolites were identified by using ChromaTOF software (v. 4.50.8.0, LECO, St. Joseph, MI, USA) coupled with commercially available compound libraries: NIST 2005 (PerkinElmer Inc.,Waltham, MS), Wiley 7.0 (John Wiley & Sons Ltd., Hoboken, NJ).

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The measurement of ascorbate (AsA), glutathione (GSH), CTS, and secondary metabolites Colorimetry was used for the measurement of AsA and GSH content, and the specific analysis procedure was clearly described in the method of Gossett et al. (1994) 47. Total phenols, flavonoids, and

proanthocyanidin content were measured

according to

manufacturer’s instructions of Assay Kits (Suzhou Comin Biotechnology Co., Ltd., China). The content of CTS was measured with the ninhydrin method (Curotto and Aros, 1993). The RNA extraction, library construction, and sequencing The cDNA library was constructed via the mRNA-Seq Sample Preparation Kit™ (Illumina, San Diego, CA, USA). Briefly, RNeasy Mini Kit (Qiagen, Germany) was used for total RNA extraction from leaves according to the manufacturer’s instructions. After DNase I treatment, magnetic beads with Oligo (dT) were used to isolate mRNA. The mRNA was mixed with the fragmentation buffer and then fragmented into short fragments. The cDNA was then synthesized using the mRNA fragments as templates and random hexamer primers, followed by the synthesis of second-strand cDNA using DNA polymerase. The cDNA was purified and resolved with EB buffer for end-repair and the addition of single nucleotide “adenine”. After that, the short fragments were connected to adapters. The suitable fragments (150-200 bp) were selected for PCR (AMPure XP system, Beckman Coulter, USA). Quantification and qualification of the sample library was performed (Agilent 2100 Bioanaylzer and ABI StepOnePlus Real-Time PCR System). Finally, each library was sequenced (Illumina HiSeq™ 2000). Bioinformatics analyses of RNA-Seq data Raw RNA-Seq read data were filtered to remove adaptors and low-quality reads (quality score < 20, reads length > 25 bp, and reads with > 5% unknown nucleotides). For statistical analysis and evaluation of data, total raw reads, total clean reads, Q20 percentage, N

8


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percentage and GC percentage were calculated. Transcriptome assembly was carried out with a short reads assembling program (Trinity, v r20131110), then the distribution of length of Contigs and Unigenes were calculated

48

. The gene expression ratio (log2) was obtained

according to different comparison groups ((C+CTS)/C, (P+CTS)/P, P/C, and (P+CTS)/C), and only the log2 ratio of > 1 or < -1 were considered as differentially expressed genes (DEGs). Unigenes or DEGs were classified and annotated with the databases of Nonredundant NCBI Protein Sequences (NR), Nonredundant NCBI Nucleotide Sequences (NT), a Manually Annotated and Reviewed Protein Sequence Database (Swiss-Prot), Kyoto Encyclopedia of Gene and Genomes (KEGG), the Clusters of Orthologous Groups (COG), and Gene Ontology (GO). Unigenes are also aligned through BlastX in protein databases in the order of NR, Swiss-Prot, KEGG and COG. Proteins with the highest rank in Blast results were taken to decide the coding region sequences of Unigenes, and then the coding region sequences were translated into amino sequences with the standard codon table. Unigenes that were not aligned to any database were scanned by ESTScan. Quantitative real-time PCR (qRT-PCR) For total RNA extraction, 0.15 g of fresh leaves was extracted by using a RNeasy Mini Kit (Qiagen, Germany) according to the manufacturer’s instructions. A revert Aid First Stand cDNA Synthesis Kit (Fermentas, Lithuania) was used for reverse-transcribing RNA to obtain the first-strand of cDNA. Primer sequences for genes are shown in Table S1. Gene expression levels were determined using a qRT-PCR detection system (the Bio-Rad iCycler iQ system) with SYBR Green Supermix (Bio-Rad, USA) The conditions of the PCR protocol for all genes (β-actin as internal control) were as follows: 15 min at 95°C and 40 repeats of denaturation at 95°C for 5 s, annealing at 59-63°C (see the Table S1) for 30 s, following by heating the amplicon from 60 to 95°C to obtain the melting curve (CFX Connect systemsTM

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Real-Time PCR Detection System, Bio-Rad)). The formula 2-∆∆Ct was used for calculating the transcript level of all genes 49. Statistical analysis The experimental design was a split-plot design and a general linear model procedure was used for the analysis of variance (SAS 9.1, SAS Institute, Cary, NC) for all measured parameters. Differences between treatment means were tested using Fisher’s protected least significance (LSD) test at a 0.05 probability level.

RESULTS

Effects of dehydration stress with and without CTS on growth and physiological changes The phenotypes of CTS-treated plants were visually taller and greener than untreated plants under water-sufficient and water-limited conditions. These visual observations are consistent with RGR and chlorophyll content. CTS-treated plants maintained significantly more chlorophyll content in leaves compared to untreated controls (Fig.1 A-F). White clover plants treated with CTS exhibited 23% higher RGR than those plants without the application of CTS under water-sufficient condition. In addition, dehydration stress induced a significant decline in RGR regardless of the CTS application, but the RGR of CTS-treated plants were 3 times higher than untreated plants at 6 d of dehydration stress (Fig. 1G). Leaf water potential significantly declined due to dehydration stress, and CTS-treated plants maintained significantly lower leaf water potential than untreated plants at 6 d of water-limited treatment (Fig. 1 H). In response to dehydration stress, CTS-treated plants had significantly higher RWC and OA as compared to untreated plants from the second to sixth d of dehydration stress. For instance, CTS treated plants had 1.4 times higher RWC and 4 times higher OA relative to untreated plants on day 6 (Fig. 2A, B). In addition, dehydration induced increases in total antioxidant capacity in CTS-treated and untreated plants on the first two days of stress. 10


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Total antioxidant capacity in untreated plants went down during 3 d of dehydration stress, but kept on a rise in CTS-treated plants (Fig. 2C, D). Similarly, .OH scavenging ability in leaves of CTS-treated plants was 1.4 times higher compared to that in untreated plants at 6 d of dehydration stress (Fig. 3C). On the contrary, CTS-treated plants had significantly lower protein carbonyl, O2.-, H2O2, MDA content, and EL than untreated plants at 6 d of dehydration stress (Fig. 2D and 3A-C). Changes in the metabolome in response to dehydration with and without CTS Over 100 peaks were detected within GC-TOFMS analysis. More than 500 putative metabolites were found in leaves of white clover. To identify differentially expressed metabolites (DEMs), four different ratios (comparison groups) were set including (C+CTS)/C, (P+CTS)/P, P/C, and (P+CTS)/C. (C+CTS)/C and (P+CTS)/P ratio indicated effects of CTS under water-sufficient and water-limited condition, respectively. P/C and (P+CTS)/C ratio indicated effects of dehydration stress without and with exogenous CTS application, respectively. Thus, a total of 69 metabolites were differentially regulated in response to exogenous CTS and dehydration stress including 14 amino acids, 16 sugars, 21 organic acids, and 18 other metabolites. The information of all 69 identified DEMs was recorded in Table S2. Changes in 69 DEMs in leaves of white clover under water-sufficient or water-limited condition were detected (Fig. 4A). Exogenous application of CTS changed the accumulation pattern of metabolites under both water-sufficient and water-limited conditions (Fig. 4A). Most of the metabolites did not change due to exogenous application of CTS under water-sufficient conditions (55%), but 36% and 9% of the metabolites were up-regulated and down-regulated in (C+CTS)/C, respectively (Fig. 4B). Under water-limited condition, CTS induced increases in 77% of the metabolites, and only 3% of the metabolites significantly decreased. The remaining metabolites did not significantly change due to CTS treatment. For untreated (P/C) or CTS-treated ((P+CTS)/C) plants, dehydration stress led to increases in 11



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55% and 89% of the metabolites, respectively. In addition, fewer metabolites exhibited a decrease in content in (P+CTS)/C) compared to those in P/C (Fig. 4B). The application of CTS did not alter the total content of amino acids, organic acids, or other metabolites, but CTS significantly up-regulated the accumulation of total sugars under water-sufficient conditions (Fig. 4C). Without exogenous CTS, dehydration stress still significantly increased the total content of amino acids, sugars, and organic acids. Dehydration-stressed plants treated with CTS exhibited 115, 77, 94, and 153% higher total content of amino acids, sugars, organic acids, and other metabolites as compared to dehydration-stressed controls, respectively (Fig. 4C). Metabolic pathways of metabolites affected by CTS and dehydration stress Exogenous application of CTS significantly improved the accumulation of endogenous CTS, AsA, GSH, total phenols and flavonoids under water-sufficient and water-limited conditions, whereas CTS had no significant effect on proanthocyanidin accumulation (Fig. 5). Dehydration stress caused a significant increase in proline, GABA, valine, isoleucine, and phenylalanine content. Exogenous application of CTS further enhanced the accumulation of these amino acids in response to dehydration stress (Fig. S1A). Similarly, the accumulation of 15 different sugars and 14 organic acids were enhanced by exogenous CTS application under dehydration stress (Fig. S1B and C). The 14 organic acids included phosphoric acid, benzoic acid, malic acid, succinic acid, D-glyceric acid, threonic acid, aconitic acid, citric acid, quinic acid, 3,4-Dihydroxycinnamic acid, α-ketoglutaric acid, 4-hydroxycinnamic acid, fumaric acid, and ferulic acid. A decrease in maleic acid content was induced by CTS under dehydration stress (Fig. S1C). In addition, dehydration-stressed plants treated with CTS had significantly higher glycerol,

sorbitol,

myo-inositol,

phytol,

maleimide,

3-hydroxypyridine,

urea,

N-methyl-L-glutamic acid, putrescine, dehydroascorbic acid, allantoic acid, guanine,

12


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spermidine, 1-monopalmitin content than dehydration-stressed plants without exogenous CTS (Fig. S1D). 44 metabolites from primary metabolic pathways such as the TCA cycle, GABA shunt, CTS metabolism, and other primary metabolism processes were detected (Fig. 6). Those 44 metabolites included 14 amino acids, 11 organic acids, 9 sugars, and 10 other metabolites. Exogenous CTS had no significant effects on the TCA cycle under water-sufficient condition ((C+CTS)/C), but enhanced the accumulation of some sugars such as sucrose, mannose, fructose, and trehalose as well as chlorophyll metabolism. For the effect of CTS under water-limited stress ((P+CTS)/P), exogenous CTS induced increases in 8 of 9 sugars, 10 of 14 amino acids, and 8 of 11 organic acids including all detected metabolites involved in TCA cycle (malate, fumarate, citrate, aconitate, and succinate), and also improved GABA shunt, CTS transformation, and the accumulation of polyamine (spermidine and putrescine). Quinic acid, glycerate, and aspartate decreased only in dehydration-stressed plants without exogenous CTS (P/C), whereas serine, lysine, threonine, myo-inositol, glycerol, benzoic acid, citrate, aconitate, and succinate significantly increased only in dehydration-stressed plants treated with CTS ((P+CTS)/C) (Fig. 6). The quantitative identification of DEGs via transcriptome analysis Output statistics of sequencing via transcriptome analysis are listed in Table S3. Hierarchical clustering of DEGs showed that gene expression pattern was different among four comparison groups, and exogenous application of CTS up-regulated more genes under water-sufficient ((C+CTS)/C) and water-limited condition ((P+CTS)/P) (Fig. 7A). As shown in venn diagram, 241 DEGs were commonly regulated in all comparison groups; (C+CTS)/C and (P+CTS)/P had common 295 DEGs, and 1802 DEGs were commonly found in P/C and (P+CTS)/C. 1393, 1629, 2137, or 2407 DEGs was independently expressed in (C+CTS)/C, (P+CTS)/P, P/C, or (P+CTS)/C (Fig. 7B). Among identified 103645 unigenes, 2122 DEGs were up-regulated and 13



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1467 were down-regulated in (C+CTS)/C, and 2460 or 1124 DEGs were up-regulated or down-regulated in (P+CTS)/P, respectively (Fig. 7C). A total of 6303 DEGs were identified in P/C including 2556 up-regulated DEGs and 3747 down-regulated DEGs. (P+CTS)/C had more up-regulated DEGs, but less down-regulated DEGs than P/C. (P+CTS)/C included 3945 up-regulated DEGs and 2484 down-regulated DEGs (Fig. 7C). The GO and COG annotation and enrichment of DEGs via transcriptome analysis The GO annotation provided 3 categories including biological process, molecular function, and cellular component (Fig. S2). According to COG annotation, all detected DEGs could be classified into 18 functional categories (Fig. 8). Under water-sufficient conditions, exogenous application of CTS up-regulated most of DEGs associated with energy production and conversion, carbohydrate transport and metabolism, defense mechanisms, signal transduction mechanisms, translation-ribosomal structure and biogenesis, transcription, and posttranslational modification-protein turnover-chaperones, as reflected by the (C+CTS)/C ratio. Similarly, the majority of the DEGs up-regulated in (P+CTS)/P were related to 18 different functional categories. The number of up-regulated DEGs associated with defense mechanisms in (P+CTS)/P were four times that of the down-regulated ones. As compared to P/C, (P+CTS)/C showed more up-regulated DEGs in the categories of amino acid transport and metabolism, carbohydrate transport and metabolism, defense mechanisms, signal transduction mechanisms, lipid transport and metabolism, translation-ribosomal structure and biogenesis, transcription, and

posttranslational

modification-protein

turnover-chaperones.

In

addition,

less

down-regulated DEGs involved in energy production and conversion, defense mechanisms, inorganic ion transport and metabolism, replication-recombination and repair, carbohydrate transport and metabolism, and translation-ribosomal structure and biogenesis also were observed in (P+CTS)/C than that in P/C (Fig. 8). Exogenous CTS on DEGs of flavonoids biosynthesis in leaves of white clover under dehydration stress ((P+CTS)/P), and most of 14


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these DEGs was up-regulated by exogenous CTS under dehydration stress (Fig. 9). Exogenous application of CTS also up-regulated many DEGs involved in TCA cycle, AsA and GSH metabolism in response to dehydration stress (Fig. S3-5). The qRT-PCR validated the transcriptome results since the CTS-induced DEGs were consistent with the RNA-Seq results (Fig. 10).

DISCUSSION

Growth inhibition, wilt, and leaf senescence are common symptoms when plants are suffering from dehydration stress. In response to dehydration, plants have evolved numerous mechanisms such as phytohormone regulation, antioxidant defense, and osmotic adjustment 50, 51

. In this study, endogenous CTS content was enhanced in leaves due to exogenous

application of CTS. CTS treatment alleviated dehydration-induced growth inhibition and leaf senescence, but also improved plants growth and the synthesis of chlorophyll under water-sufficient condition. This indicates that CTS functioned as a positive regulator of growth under both optimal and water-limited conditions in white clover. This is consistent with previous works that demonstrated pretreatment of bean, potato, and apple (Malus pumila) seedlings with exogenous CTS significantly decreased lipid peroxidation to increase cell membrane stability and reduced the accumulation of ROS, the level of EL and protein oxidation in leaves under dehydration stress 21, 52, 53. In addition, the maintenance of favorable water balance is also primary importance for plants coping with dehydration. OA plays a critical role in the regulation of water conservation during dehydration stress 54. CTS-induced drought resistance could be associated with the enhancement of OA, maintenance of higher RWC, and lower water potential during dehydration stress in white clover. Some osmolytes that were regulated by CTS were involved in the enhancement of OA, antioxidant capacity, and other mechanisms as discussed below.

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The maintenance of metabolic homeostasis related to complex metabolic networks and the accumulation of specific metabolites induced by exogenous CTS was associated with the positive effects of CTS on drought resistance. Carbohydrates are abundant and important in plants stress defense since they can be compatible solutes, energy sources, or signaling molecules

55, 56

. The accumulation of glucose, maltose, fructose, and other sugars associated

with acquired drought resistance has been observed in creeping bentgrass (Agrostis stolonifera), sorghum (Sorghum bicolor), and bermudagrass (Cynodon dactylon) through metabolome analysis31,

57, 58

. Glucose and fructose have various functions in drought

resistance including signal transduction to modulate plant growth, development, and stress responses

59

. Mannose also exhibits multiple functions including the regulation of osmotic

potential and biosynthesis of AsA, which is positively important for plants growth and stress defense

60, 61

. Trehalose is another critical sugar for plants coping with abiotic stress. The

exogenous application of trehalose and insertion of a transgene enhancing trehalose biosynthesis improved drought resistance via the stabilization of biological structures, favorable mineral balance, roots growth, and antioxidant defense in different plant species 62-64

. Sugar alcohols including sorbitol and myo-inositol could function as signaling

molecules, osmoregulants, and scavengers of ROS against abiotic stress

65-67

. In this study,

the application of CTS enhanced the accumulation of fructose, glucose, mannose, trehalose, sorbitol, myo-inositol, and other detected sugars under dehydration stress. In accordance with these metabolome results, CTS up-regulated many genes involved in carbohydrate transport and metabolism in leaves of white clover under dehydration stress. These findings indicate that CTS may have osmoregulatory or osmoprotective function, which are associated with differential carbohydrate and energy metabolism in CTS-treated plants compared to non-treated plants. The increased accumulation of carbohydrates and altered carbohydrate metabolism might greatly contribute to improved drought resistance via increased OA, the

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maintenance of carbon balance and utilization, and other possible critical functions of carbohydrates in response to dehydration stress. As primary metabolites, amino acids are important precursors for synthesis of proteins 68, 69

and vehicles of stress defense in plants

. Proline is one of most well-known osmoyltes

and osmoprotectants in plants due to its role in OA, quenching of ROS, and maintenance of redox balance under abiotic stress

70, 71

. Other amino acids such as isoleucine, threonine,

lysine, and aspartic acid were also identified as significant osmoregulants and supplies of nutrition when plants suffered from dehydration or other abiotic stresses

72-74

. Higher levels

of proline, serine, valine, aspartic acid, and other amino acids were associated with increased drought resistance induced by exogenous melatonin, salicylic acid, and elevated atmospheric CO2 in bermudagrass, sunflower (Helianthus annuus), and sorghum

30, 57, 75

. In addition,

non-protein amino acids such as GABA can enhance OA and antioxidant defenses in various plant species under dehydration stress

76-78

. The GABA shunt occupies a critical crossroad

between amino and organic acid metabolism linked with the tricarboxylic acid (TCA) cycle 79. Both proline and GABA could serve as sources of carbon (C) and nitrogen (N) for the supply of C-N deficiency in plants during abiotic stress 80, 81. In the current study, CTS-enhanced the accumulation and metabolism of amino acids including proline, GABA, aspartic acid, valine, serine, lysine, threonine, isoleucine, and phenylalanine could play critical roles in OA, antioxidants, and the maintenance of metabolic balance contributing to improved drought resistance in white clover. Transcriptomic analysis showed that many genes associated with amino acid transport and metabolism were up-regulated by CTS under water-limited condition, implying that metabolic pathways related to the synthesis and transformation of amino acids were regulated by CTS. Key intermediates of the TCA cycle were maintained at higher levels in CTS-treated plants than in control plants under dehydration stress. Citrate, aconitate, α-ketoglutarate,

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succinate, fumarate, and malate could be critical organic acids regulated by CTS. The TCA cycle is the respiratory pathway that drives ATP biosynthesis for growth and stress defense 82. Other studies on dehydration stress are consistent with our current results for the TCA cycle metabolites. For instance, transgenic creeping bentgrass overexpressing an ipt gene for cytokinin biosynthesis improved drought resistance of plants and enhanced the accumulation of intermediates of the TCA cycle

31

. In view of ABA-regulated changes of metabolic

pathways, aconitate, succinate, and malate accumulation may have been involved in ABA-induced drought resistance in creeping bentgrass

83

. Earlier studies suggest that malic

and maloic acid exhibited a significant function of OA under dehydration stress because a 75% reduction in osmotic potential was associated with the accumulation of malic and maloic acid in chickpeas (Cicer arietinum)

84

. In addition, our results also show that dehydration

stress caused a significant decline in quinic acid content in dehydration-stressed control plants, whereas CTS treatment significantly enhanced the accumulation of quinic acid under both water-sufficient and water-limited conditions. Quinic acid has the well protective effect against the generation of ROS and other cell toxicity 85, 86. Many transcripts related to energy production and conversion were also up-regulated by exogenous CTS under dehydration stress in this study. Thus, our results suggest that CTS-induction of organic acid maintenance or biosynthesis may have been important for energy production, OA, and detoxification leading to enhanced drought resistance in white clover. In response to dehydration stress, CTS induced glycerol, putrescine (Put), spermidine (Spd), and urea to be greater than the levels observed in control plants in leaves of white clover. Glycerol is closely related to the synthesis of glycerol-3-phosphate in plants and both of them participate in glycolysis, lipid formation, and plant defense signaling 87. Polyamines (PAs) including Put, Spd, and spermine (Spm) are implicated in plant growth, senescence, and stress defense 88, 89. An increasing number of studies prove the positive effects of PAs on

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improving drought resistance of plants. For instance, the overexpression of genes encoding PA synthesis or exogenous application of Spd significantly enhanced drought resistance in Arabidopsis, creeping bentgrass, and white clover due to effects on the antioxidant system, carbon and energy metabolism, and photosynthesis

90-92

. Li et al. (2016) 33 demonstrated that

elevated endogenous PA content induced by exogenous Spd could significantly enhance metallothionein accumulation, antioxidant enzyme activities, and proline metabolism leading to improved drought resistance, whereas the inhibition of Spd biosynthesis aggravated dehydration-induced damages in white clover. Spd could mitigate dehydration-induced oxidative damage by activating H2O2 and calcium signaling to regulate antioxidant enzyme activities and genes associated with antioxidant functions 32. Similarly, urea functions as the nitrogen supply in relation to plant growth, nutrient availability, and adaptation to abiotic 93-95

stress

. Foliar urea acted a positive role in provoking nitric oxide signaling and

glycinebetaine metabolism to alleviate the negative effects of dehydration stress in maize 96. Combined with previous studies, our findings suggest that the accumulation of PAs, glycolysis, and urea are involved in CTS-induced drought resistance as the defense signaling, a source of nitrogen, and regulators of antioxidant defense and proline metabolism in white clover. The AsA-GSH cycle and flavonoids metabolism were also affected by CTS treatment in this study. In plants, AsA and GSH as important non-enzymatic antioxidants within the AsA-GSH cycle are critical for the ROS detoxification under abiotic stress 97. Enhancement of the AsA-GSH cycle has improved drought resistance in white clover or other plant species 33, 98, 99

. Similarly, flavonoids, a group of key secondary metabolite, has been found to

function as the scavenger of radicals such as O2.-, singlet oxygen (-O2), and hydroxyl ion (OH-) in plants

100

. Elevated endogenous accumulation of flavonoids could significantly

inhibit ROS production in association with enhancement of plant tolerance to dehydration 33,

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101, 102

. Our data of transcriptome showed that a lot of genes associated with AsA, GSH, and

flavonoids metabolism were remarkably up-regulated by CTS in white clover under dehydration stress. Further analyses of AsA, GSH, and flavonoids content found that CTS-treated white clover exhibited significantly higher accumulation of these metabolites than untreated plants in response to dehydration, which agreed with findings of transcriptone. These key metabolic pathways or metabolites regulated by CTS have the potential contribution to improved antioxidant defense resulting in the increase in cell membrane stability in white clover under dehydration stress.

CONCLUSIONS

In summary, increased endogenous CTS content through exogenous application of CTS effectively alleviated dehydration-induced leaf senescence, growth inhibition, and cellular damages. The combined analyses of metabolomic and transcriptomic profiles revealed that CTS enhanced amino acid and carbohydrate metabolism, energy production and conversion, the AsA-GSH and TCA cycles, and the GABA shunt pathway, as manifested by improved accumulation of abundant metabolites including carbohydrates, amino acids, organic acids, sugar alcohols, AsA, GSH, glycerol, urea, and phenols. Many of these metabolites are known to be involved in OA, antioxidant defense, stress signaling, and energy production. CTS-induced polyamines accumulation and flavonoids metabolism were associated with CTS-regulated drought resistance in white clover due to their positive roles in stress responses. The changes in metabolites and genes induced by CTS provide the evidence for the beneficial role of CTS in drought resistance in plants.

FIGURES

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Figure 1. The effects of chitosan (CTS) on (A) and (B) phenotype, (C) total chlorophyll content, (D) chlorophyll a content, (E) chlorophyll b content, (F) plant height, (G) relative growth rate, and (H) water potential in leaves of white clover at 6 d of treatment. PEG, dehydration stress induced by PEG; PEG + CTS, dehydration stress induced by PEG containing CTS.

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Figure 2. The effects of chitosan (CTS) on (A) RWC, (B) OA, (C) total antioxidant capacity, and (D) protein carbonyl content in leaves of white clover during 6 d of treatment. Vertical bar represent LSD values (n = 4; P≤0.05) at a given day. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 3. The effects of chitosan (CTS) on (A) O2.- staining,(B) H2O2 staining, and (C) oxidative damage and membrane stability (hydroxyl radical scavenging ability (.OH SB), %; generation rate of superoxide anion radical (O2.-), nmolmin-1g-1 DW; hydrogen peroxide (H2O2) content, µmol g−1 DW; malondialdehyde (MDA) content, nmol g-1DW; electrolyte leakage (EL), %) in leaves of white clover at 6 d of treatment. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 4. (A) Changes in 69 metabolites in leaves of white clover at 6 d in response to exogenous chitosan (CTS) application and dehydration stress (The log2 fold change ratios are shown in the results. Red means an up–regulation, and green means a down–regulation), (B) the percentage of metabolites (%), and (C) total relative amino acids, organic acids, sugars and other metabolites content at 6 d of treatment. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 5. The effect of exogenous chitosan (CTS) on the content of chitosan (CTS) (mg g-1 DW), ascorbate (mM g-1 DW), glutathione (mM g-1 DW), total phenols (mg g-1 DW), flavonoid (mg g-1 DW), and proanthocyanidin (mg g-1 DW) in leaves of white clover under dehydration stress. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 6. The assignment of 44 metabolites to metabolic pathways. Red indicates a significant up–regulation, green indicates a significant down–regulation, and gray indicates no significant change. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 7. (A) Clustering analysis of DEGs, (B) and (C) the number of DEPs due to dehydration stress and exogenous application of chitosan (CTS) in leaves of white clover. The color scale bar in the left of hierarchical clustering analysis indicates the increase (red) and the decrease (blue) of genes. Overlapping regions of the circles in Venn diagram indicate DEGs that were regulated in both or all treatments, whereas non-overlapping circles indicate DEGs regulated in only that treatment. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 8. The effect of exogenous chitosan (CTS) under water-sufficient ((C+CTS)/C) and dehydration stress ((P+CTS)/P) as well as the effect of dehydration stress without (P/C) and with ((P+CTS)/P) the application of exogenous CTS on differentially expressed genes (DEGs) within each functional category based on the clusters of orthologous groups (COG) in leaves of white clover. C, control; C+CTS, control+CTS; P, dehydration stress; P+CTS, dehydration+CTS.

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Figure 9. Effect of exogenous chitosan (CTS) on DEGs of flavonoid biosynthesis in leaves of white clover under dehydration stress ((P+CTS)/P). Definition of genes encoding enzymes: (1) 1.1.1.219, bifunctional dihydroflavonol 4-reductase/flavanone 4-reductase; (2) 1.1.1.234, bifunctional

dihydroflavonol

4-reductase/flavanone

4-reductase;

(3)

1.14.11.19,

leucoanthocyanidin dioxygenase; (4) 1.14.11.23, flavonol synthase; (5) 1.14.13.21, flavonoid 3'-monooxygenase; (6) 1.17.1.3, leucoanthocyanidin reductase; (7) 2.1.1.104, caffeoyl-CoA O-methyltransferase; (8) 2.3.1.133, shikimate O-hydroxycinnamoyltransferase; (9) 2.3.1.74, chalcone synthase; (10) 5.5.1.6, chalcone isomerase. Red means an up-regulation, and green means a down-regulation.

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Figure 10. Transcript levels of genes induced by exogenous chitosan (CTS) based on the analysis of qRT-PCR and RNA-seq. The log2 ratio (fold-change of (P+CTS)/P) is shown in the figure. The positive number shows an up-regulation, and the negative number shows a down-regulation.

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ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Table S1: Primers sequences used in qRT-PCR. Table S2: The information of 69 metabolites was identified in white clover. Table S3: Output statistics of sequencing via transcriptome analysis. Figure S1: The change of specific metabolites via the analysis of metabolome at 6 d of treatment. Figure S2: GO analysis of DEGs in leaves of white clover under water-sufficient and dehydration condition. Figure S3: Effect of exogenous CTS on DEGs of TCA cycle in leaves of white clover under dehydration stress ((P+CTS)/P). Figure S4: Effect of exogenous CTS on DEGs of ascorbate and aldarate metabolism in leaves of white clover under dehydration stress ((P+CTS)/P). Figure S5: Effect of exogenous CTS on DEGs of glutathione metabolism in leaves of white clover under dehydration stress ((P+CTS)/P). (XLS) AUTHOR INFORMATION Corresponding Author * Tel: (028) 86291010; fax: (028) 86291010; e-mail: [email protected]; Tel: (517) 3530203; fax: (517) 3535174; [email protected]. Author Contributions All authors have given approval to the final version of the manuscript. ‡These authors contributed equally. * These authors are co-corresponding authors.

Notes The authors declare no competing financial interest.

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ACKNOWLEDGMENT This research was supported by grant CARS-35-05 from Modern Agro-industry Technology Research System, and by grant NSFC 31372371 from National Natural Science Foundation of China.

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For TOC only

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Metabolic Pathways Regulated by Chitosan Contributing to Drought

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