Shotgun Label-Free Quantitative Proteomics of Water-Deficit-Stressed Midmature Peanut (Arachis hypogaea L.) SeedKameswara Rao Kottapalli,† Masoud Zabet-Moghaddam,† Diane Rowland,‡ Wilson Faircloth,§
Mehdi Mirzaei,∥ Paul A. Haynes,⊥ and Paxton Payton*,#
†Center for Biotechnology and Genomics, Texas Tech University, Canton & Main, Experimental Sciences Building, Room 101,Lubbock, Texas 79409, United States‡Agronomy Department, University of Florida, 3105 McCarty Hall B, Gainesville, Florida 32611, United States§National Peanut Research Laboratory, United States Department of Agriculture, 1011 Forrester Drive Southeast, Dawson, Georgia39842, United States∥The Australian School of Advanced Medicine, Macquarie University, Building F10A, Groundfloor, 2 Technology Place, NSW 2109,Australia⊥Department of Chemistry and Biomolecular Sciences, Macquarie University, Building F7B, NSW 2109, Australia#Cropping Systems Research Laboratory, United States Department of Agriculture, 3810 Fourth Street, Lubbock, Texas 79415,United States
*S Supporting Information
ABSTRACT: Legume seeds and peanuts, in particular, are an inexpensivesource of plant proteins and edible oil. A comprehensive understanding of seedmetabolism and the effects of water-deficit stress on the incorporation of themain storage reserves in seeds, such as proteins, fatty acids, starch, and secondarymetabolites, will enhance our ability to improve seed quality and yield throughmolecular breeding programs. In the present study, we employed a label-freequantitative proteomics approach to study the functional proteins altered in themidmature (65−70 days postanthesis) peanut seed grown under water-deficitstress conditions. We created a pod-specific proteome database and identified 93nonredundant, statistically significant, and differentially expressed proteinsbetween well-watered and drought-stressed seeds. Mapping of these differentialproteins revealed three candidate biological pathways (glycolysis, sucrose andstarch metabolism, and fatty acid metabolism) that were significantly altered dueto water-deficit stress. Differential accumulation of proteins from these pathwaysprovides insight into the molecular mechanisms underlying the observed physiological changes, which include reductions in podyield and biomass, reduced germination, reduced vigor, decreased seed membrane integrity, increase in storage proteins, anddecreased total fatty acid content. Some of the proteins encoding rate limiting enzymes of biosynthetic pathways could be utilizedby breeders to improve peanut seed production during water-deficit conditions in the field. The data have been deposited to theProteomeXchange with identifier PXD000308.
KEYWORDS: peanut, water-deficit stress, pod development, label-free proteomics
1. INTRODUCTION
Peanut (Arachis hypogaea L.) is the second most importantcrop legume, cultivated across the world on 21.8 millionhectares with an annual production of 38.6 million tons(FAOSTAT 2011; http://faostat.fao.org/ (accessed June 28,2013)). Peanut is mainly grown for its seed in the United Statesbut represents a rich source of edible fats and a primary sourceof oil in many parts of the world. Whereas peanut is moderatelyadaptive to water-deficit conditions, prolonged drought andlimited water resources are threatening sustainable peanut cropproduction. Reductions in water supply generate water-deficitstress in peanut and subsequent loss of yield and quality. In2012, the U.S. Department of Agriculture declared more than
1000 counties in 26 states as disaster struck due to drought, thelargest natural disaster area in the history of the United States.1
Peanut production in these disaster areas was severely affected,leading to a steep increase in price for peanut commodities likepeanut butter and other peanut-based foods.2 Numerousstudies conducted during the past several decades on theeffects of drought on peanut seed emphasized poor yield andseed quality;3 reduced seed size, seed number, lower oilcontent, shelling percentage, and delayed maturity;4 inadequate
Special Issue: Agricultural and Environmental Proteomics
supply of assimilates5 or calcium;6 and altered protein, total oilcontent, and fatty acid (FA) composition.7 However, to ourknowledge, in peanut or any grain legume there are no reportsof systematic evaluation of transcript or protein responses towater-deficit stress on developing seeds. In maize, water deficitat 9 days after planting (DAP) caused significant differentialtranscriptional response in placenta and endosperm tissues.8
Placenta tissue showed lower water status than endosperm anda concomitant induction of several known stress tolerancegenes. These genes included HSPs, chaperonins, and majorintrinsic proteins. In addition, placenta accumulated a greaterthan four-fold higher concentration of ABA and showed adecrease in sugar flux during stress. In contrast, genes for celldivision and growth and cell-wall-degrading enzymes weredownregulated in endosperm, suggesting a strong inhibition ofcell proliferation during water stress.9 Water deficit alsoupregulated a homeodomain leucine zipper transcription factor(TF) (ZmOCL5), which was proposed to provide tissue-specific stress regulation in kernels.8 In cereals, heat stressgenerally results in decrease in the overall synthesis of starchand storage proteins and ultimately reduction in grainyield.10−12 In severe cases, it also leads to grain abortion. Aninteresting finding is that several heat-stress responses inArabidopsis shoots and drought-stress responses in barley areconserved.11 In barley, short-term heat stress consistentlyinduced HSP-mediated protein folding, reactive oxygen species(ROS) scavenging, and the biosynthesis of compatiblesolutes.11 In parallel, genes involved in embryo development,hormone biosynthesis, and cell signaling were altered,indicating rapid sensing, signal transduction, and adaptationof central processes to abiotic stress. In addition, physiologyand development of barley caryopsis were negatively affected,as evident from decreased starch biosynthesis, lipid metabolism,and amino acid metabolism immediately after heat stress.Interestingly, but perhaps not surprisingly, several abiotic-stressresponses in Arabidopsis and barley are conserved.11
Much of what we know today regarding the molecularresponse of seeds to water-deficit stress comes from the basicstudies carried out in model legumes and Arabidopsis. However,several differences exist between the developmental programsof peanut seeds and those of Arabidopsis and even otherlegumes, especially when plants are grown under productionconditions. The primary difference is that peanut seeds developunderground and have a large endosperm tissue accumulatingproteins and lipids, while Arabidopsis and most model legumeseeds develop aerially in green pods with large embryos.Because seeds harbor the nutritional reserves to support life ofhumans and other living organisms, it is important tounderstand the genetic and biochemical mechanisms altereddue to stress resulting in differential accumulation of main seedreserves, such as proteins, carbohydrates, and lipids in peanutseeds. We discuss the effect of water-deficit stress on seedmetabolism and identify candidate pathways that are our focusfor the development of stress-tolerant peanut cultivars.
2. MATERIALS AND METHODS
2.1. Seed Material and Water-Deficit Stress Treatment
Experimental field plots were established at the USDA-ARSNational Peanut Research Laboratory’s Environmental ControlPlot Facility in Dawson, Georgia (31.7733° N, 84.4467° W).13
In brief, the Environmental Control Plot Facility (ECPF)contains a series of sheltered plots with an artificial soil profile
1.8 m deep. Each 5.5 m × 12.2 m plot was protected fromrainfall by an automated shelter that covers the entire plotwithin 30 s of the onset of rainfall. Under dry conditions, theautomated shelters remain open so that all plots receive fullsunlight during the growing season. Plots were irrigatedthrough the use of sprinkler irrigation mounted to thepreviously described automated shelter. Soil in the ECPF wasa 1:2.75 mixture of locally obtained Tifton series sandy loamand Terrell sand. The drought-prone soil mixture used hadadequate levels of tested soil nutrients (mainly P, K, and Ca)and pH 6.1. Soil was fumigated with dazomet at 305 kg/haapproximately 45 days prior to planting. Aldicarb was includedin-furrow for systemic insect control, and the herbicidespendimethalin, metolachlor, and glyphosate were applied forpreemergence weed control. General management of the studywas based on extension service recommendations and includedhand-weeding and scheduled fungicide application for bothfoliar and soil-borne diseases. The mean daily high and lowtemperatures from June to August were 33 and 20 °C,respectively. After aeration, soil was shallowly tilled, and asmooth seedbed was prepared for planting. Seeds of GeorgiaGreen, a popular runner variety grown in the southeastern U.S.,were sown in four-row plots, 5.5 m long with a row spacing of0.6 m and a plant density of 10 seed m−1 of row. Seeds weresown into a full soil moisture profile to establish uniformgermination and plant stand. Fourteen days after germination,two irrigation regimes (full and deficit) were established wherefull irrigation plots received 50 mm of water per week in asingle irrigation event and deficit plots received 25 mm perweek. Approximately 110 days after sowing, four to five plantsfrom three replicate plots in each treatment were harvested, andpods were binned into size classes (surrogate for developmentalstages), frozen in liquid nitrogen, and stored at −80 °C untilprotein extraction. Because peanut has asynchronous flowering,harvesting pods at any given time point allows for a range ofpod ages to be collected. To capture the representativevariability within a subplot and harvest enough material forearly developmental stages, multiple plants had to be pooledwithin a plot and were defined as n = 1. Three groups weregenerated for each developmental stage (bin) to give n = 3. Forthis study, mid-mature pods (65−70 days postanthesis) wereused for proteomics analysis. On the basis of previous data, themidmature stage of seed development appears to be mostsusceptible to water-deficit stress.14
2.2. Crude Protein and Total Fatty Acid Quantification
Crude protein analysis was conducted by the Dumascombustion method on a Leco model FP-228 as previouslydescribed.15 In this procedure, 100 mg peanut seed sample wastransferred to a tin container and placed in a combustionchamber (850 °C) of an automated FP 228. The mixture ofgases released during combustion in this method wascatalytically converted to N2 quantitatively by passing the gasthrough a conductivity cell. Total FA composition wasmeasured by FAME analysis. Extracts were obtained from100 mg of ground seeds and analyzed by gas chromatographywith an Agilent 6890 series gas chromatograph outfitted with a30 × 0.53 mm EC-WAX column and a flame ionizationdetector. The peak areas of all individual FAs were determinedto establish the amount of total FA in well-watered and water-deficit stressed samples.
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2.3. Protein Extraction and One-Dimensional GelElectrophoresis (1-DGE)
Total pod protein was extracted using the phenol-extractionprotocol previously described.16 In brief, 100 mg of freshlyground pod tissue, pooled from five plants, was added to anextraction medium containing 0.9 M sucrose, 0.1 M Tris·HCl(pH 8.8), 10 mM EDTA (pH 8.0), 0.4% (v/v) 2-mercaptoethanol, and Tris-buffered phenol (pH 8.8) andgently mixed at room temperature (RT). Proteins wereprecipitated by incubating the phenolic phase with 0.1 Mammonium acetate-methanol at −20 °C overnight, followed byprecipitation and washing of the proteins serially in threeorganic solvents (methanol, acetone, and ethanol) to give ahighly purified protein pellet. The protein content wasmeasured by Bradford assay using bovine serum albuminFraction V as the standard.17 One hundred and fiftymicrograms of protein from each replicate was incubated for10 min at 95 °C in sample buffer containing 62 mM Tris-HCL(pH 6.8) containing 10% (v/v) glycerol, 2.5% (w/v) sodiumdodecyl sulfate (SDS), 5% (v/v) 2-mercaptoethanol, and adrop of bromophenol blue, then cooled to RT. After incubationat RT for 10 min, the mixture was centrifuged, and thesupernatant was used for SDS-polyacrylamide gel electro-phoresis on 10% Mini-PROTEAN TGX precast gels (Bio-Rad,Hercules, CA). The proteins were electrophoresed at 70 V in arunning buffer of 1× triglycine sulfate (TGS) (250 mM Trizmabase, 1.92 mM glycine, 1% (w/v) SDS; pH 8.3). Oncompletion of electrophoresis, gels were placed in fixingsolution (50% ethanol, 10% acetic acid, 40% Milli-Q water)for 1 h to fix the protein bands and then stained for 15 min instaining solution (10% phosphoric acid, 10% ammoniumsulfate, 20% methanol, and 0.12% Coomassie G-250). Thegel was washed twice with water to remove the excess stain.Each sample lane was cut into 16 equal pieces that weresubsequently transferred to a 96-well flat bottom plate. Thesegel pieces were decolored by washing with 50% acetonitrile(ACN) in 100 mM ammonium bicarbonate at 37 °C for 30min. This wash was repeated three more times to sufficientlydecolor the gel pieces.2.4. Tryptic in-Gel Digestion
Protein samples were separated on 1D PAGE. Each sample lanewas cut into 16 slices, and each slice was placed into 96-wellplate wells. In-gel digestion was performed on each slice aspreviously described.18 In brief, the gel pieces were washed witha 1:1 mixture of ACN/100 mM NH4HCO3 twice for 10 min todestain the gels. Reduction was performed by adding 50 μL ofdithiothreitol (DTT) solution (10 mM) for 1 h at 56 °C. Afterreduction, the spots were alkylated by adding 50 μL ofiodoacetamide solution (55 mM in 40 mM NH4HCO3) andincubating in the dark for 30 min. The gel pieces were washedone more time with ACN/100 mM NH4HCO3 and thendehydrated by adding 100% ACN and air-dried. The digestionwas started with 30 μL of trypsin solution (12.5 ng/μL in 25mM NH4HCO3) and left overnight at 37 °C. Peptide extractionwas performed twice using 1:1 mix of ACN/water, 0.1% formicacid solution. The extracted peptide solutions were dried in thespeed vacuum centrifuge, and the peptides were resuspended in20 μL of 0.1% formic acid for the nanoflow liquid tandem massspectrometry (nano-LC−MS/MS) analysis.2.5. Nano-LC−MS/MS
The peptides obtained from in-gel digestion were analyzed bynano-LC−MS/MS using an LTQ-XL ion trap mass spec-
trometer (Thermo, CA). Chromatographic separation of thepeptides was performed using a Dionex nano-HPLC (Ultimate3000) with a trapping column (C18, 3 μm, 100 Å, 75 μm × 2cm), followed by a reverse phase column (C18, 2 μm, 100 Å, 75μm × 15 cm, nanoViper). Peptides were first injected onto thetrapping column, which was equilibrated with 1% ACN and0.1% formic acid in water and washed for 10 min with the samesolvent at a flow rate of 300 nL min−1. After washing, thetrapping column was switched to the reverse-phase analyticalcolumn and bound peptides were eluted using solvents A (2%ACN, 0.1% formic acid in water) and B (98% ACN, 2% water,0.1% formic acid). The gradient was kept constant for the first10 min at 4% solvent B, followed by a linear increase to 30%solvent B in 20 min. Solvent B was further increased to 60% in40 min, followed by a fast increase in solvent B to 90% over 5min. The eluted peptides were directed into the nanosprayionization source of the LTQ-XL with a capillary voltage of ∼2kV. The collected spectra were scanned over the mass range of300−2000 atomic mass units. Data-dependent scan settingswere defined to choose the six most intense ions with dynamicexclusion list size of 100, exclusion duration of 30 s, repeatcount of 2, and repeat duration of 15 s. MS/MS spectra weregenerated by collision-induced dissociation of the peptide ionsat a normalized collision energy of 35%.
2.6. Generation of a Peanut Proteome Database
RNA was isolated from well-watered control and water-deficit-stressed pod tissue, and TruSeq RNA libraries were prepared asper manufacturer’s protocol (Illumina). Transcriptome se-quencing of control and stressed samples was performed bypaired-end sequencing on and Illumina Mi-Seq. De novoassembly of the fastq files from each library using N-Gensoftware (DNAStar) generated 20 209 and 16 004 contigs fromcontrol and stressed tissue, respectively. Furthermore, assemblyof the contigs from stressed and control tissue using CAP3software19 generated 24 483 nonredundant consensus sequen-ces. The consensus sequences were translated in all six framesto create a pod proteome database containing 146 898 aminoacid sequences for protein identification (outlined inSupplementary Figure S1 in the Supporting Information).
2.7. Protein Identification and Quantitative Data Analysis
The RAW files of LC−MS/MS runs were converted tomzXML format using the ReAdW program (http://tools.proteomecenter.org/wiki/index.php?title=Software:ReAdW).The mzXML spectra files were searched using GPM (GlobalProteome Machine, version 2.1.1; http://www.thegpm.org)20
software against our in-house protein database generated from apod-specific transcriptome, as previously described. EachmzXML spectra file was also searched against a reversed-sequence database to calculate the false discovery rate (FDR) asprotein FDR = (# reverse proteins identified)/(total proteinidentifications) × 100.21 Additionally, the peptide FDR wascalculated as peptide FDR = 2*(# reverse peptide identi-fications)/(total peptide identifications) × 100.22 The 16output files for each replicate were combined to create a singlemerged result file, and only proteins with FDR less than 1%were used for the analysis. The following parameters were usedfor the search: enzyme: trypsin; allowed missed cleavage: 2;variable modification: methionine oxidation; fixed modification:carbamidomethylation of cysteine; MS and MS/MS masstolerance: ± 2 and ±0.2 Da, respectively.For the quantitative analysis, the normalized spectral
abundance factors (NSAFs) were used to study protein
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abundance as previously described.23 For each identifiedprotein, k, in sample i, the number of spectral counts wasdivided by the length of the identified protein. NSAFi values foreach sample i were obtained by normalizing SpCk/lengthkvalues to the total by dividing by the sum (SpCk/lengthk)over all proteins. The NSAF mean values for all replicates wereapplied to calculate protein abundance. A spectral fraction of0.5 was added to the entire spectral counts for each protein tocompensate for null values and allow for log transformation ofthe NSAF data prior to statistical analysis.24
2.8. Statistical Analysis
A two-sample unpaired t test was used to identify thedifferentially accumulated proteins between control andwater-deficit stressed samples. Only the proteins present in allthree replicates with the minimum total spectral count of fivefor either control or stressed condition were included in thedata set.23 Log-transformed NSAF data were used for the t test,and the proteins with a p value ≤0.05 were considered to bedifferentially expressed.2.9. Annotation and Mapping
Differentially expressed proteins were subsequently annotatedusing Mercator-MapMan annotation tool.25 The resultingmapping file from Mercator along with relative proteinabundance values were imported into MapMan softwareversion 3.5 to identify pathways altered due to stress.
3. RESULTS AND DISCUSSION
3.1. Analysis of Label-Free Quantitative Proteomics Data
A total of 761 nonredundant proteins were identified undercontrol and stressed conditions. Table 1 provides a summary ofproteins identified in all three replicates of well-watered controland water-deficit stress treatments. The number of proteinsreproducibly identified from control and stress treatments were647 and 612, respectively. Low FDR values were observed forboth treatments, indicating a high stringency in selection of thedata set; average protein FDR was 0.56% and average peptideFDR was 0.025%. Supplementary Tables S3 and S4 containdetails of the proteins identified in each treatment, includingtheir NSAF values (Supporting Information).3.2. Effect of Water-Deficit Stress on Peanut SeedComposition
Water-deficit stress during flowering and seed developmentresults in significant reductions in peanut pod yield and podbiomass, reduced germination, reduced vigor, decreased seedmembrane integrity, and reduced embryo RNA contentdepending on the genotype and intensity of the stress.4,16,26−28
Seeds from the moisture-stressed plants when germinated hadlow chlorophyll and dehydrogenase activity in cotyledons,which greatly influenced the growth potential of plants.27
Skelton and Shear6 reported that water deficit reduced thecalcium content of both peanut seed and the pericarp. Here we
present our findings on the impact of water-deficit stress onmidmaturity stage peanut pods grown under field conditionsand discuss the possible mechanisms involved in the stressresponse and potential targets for genetic manipulation andselection to mitigate the negative effects of late-season waterdeficit stress.Figure 1 shows that water-deficit stress resulted in a
significant increase in crude protein content and a decrease in
total FA content of stressed pods compared with well-wateredcontrol pods. This is similar to the results previously reported,7
where they showed significant reductions in total oil andspecific FAs and significantly increased total protein in podsexposed to late season (80 days after sowing) water-deficitstress. To gain insight into the proteome response to waterdeficit in these samples, we employed shotgun label-freeproteomics and identified 761 nonredundant proteins, out ofwhich 93 proteins were statistically significant and differentiallyaccumulated between well-watered and drought-stressedsamples. To date, peanut lacks a publicly available version ofthe tetraploid genome sequence. Therefore, we created a pod-specific transcriptome using next-generation sequencing andsubsequently translated the assembled transcriptome in all six
Table 1. Summary of Proteins Identified by Global Proteome Machine (GPM) search
low stringency no. of proteins identi-fieda
treatments R 1 R 2 R 3 RSD %b reproducibly identified proteinsc protein FDR (%)d peptide FDR (%)
aR1, R2, and R3 denote replicates 1, 2, and 3, respectively. bRelative standard deviation. cProteins common to all three replicates. dFalse discoveryrate.
Figure 1. Total fatty acid and crude protein content of water-deficitstressed seeds and well-water control plants. The values represent themean of six replicates from each treatment. Bars represent mean values± standard error. * indicates significance at p value of 0.006. **indicates significance at p value of 0.05.
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frames to create a pod proteome database for proteinidentification (outlined in Supplementary Figure S1 in theSupporting Information).Mercator tool was used to functionally categorize the
differentially accumulated proteins into 35 different classes(Supplementary Figure S2 in the Supporting Information).Among these functional categories, the majority belonged tothe unassigned/unknown group containing mostly differentforms of storage proteins. The second largest class includeddevelopment-related proteins, and, not surprisingly, stress-related proteins represented the fourth largest group of
differentially accumulated proteins. Subsequently, MapMananalysis of the differential proteins resulted in the identificationof a number of primary processes and metabolic pathways thatwere altered due to stress.Figure 2 provides an overview of water-deficit stress response
in peanut pods used for this study. Upon stress recognition,significant changes in ROS scavenging capacity were seen.These changes can occur due to disruption of electrontransport mechanisms or due to respiratory burst.29,30 Down-regulation of proteins like PDIL1-4 and glutaredoxin suggestsan elevated ER stress and has been shown to affect starch
Figure 2. Overview of water-deficit stress response in seeds. Proteins encoding enzymes, signaling hormones, and different biological intermediatesinduced due to stress are represented in red and those reduced are marked in green. Proteins were annotated by Mercator tool and binned intofunctional categories and pathways by MapMan version 3.5.
Figure 3. Overview of glycolysis pathway including acetyl-CoA biosynthesis and alcoholic fermentation. Proteins significantly reduced are marked ingreen boxes. PD, pyruvate dikinase; AD, alcohol dehydrogenase.
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synthesis31 and cause a decrease in highly disulfide-bondedstorage proteins.32
A primary mechanism for transmission of stress signals to thenucleus is by hormones and other signaling peptides. Wemeasured significant increases in proteins involved in thesynthesis of brassinosteroids (BRs) and reduction in jasmonicacid (JA) biosynthesis. BR is known to induce stress toleranceby downstream increases in heat shock proteins,33 compensatefor biomass reduction,34 and help in increased water uptake,membrane stability, higher CO2, and nitrogen assimilationduring stress.35 JA has been shown to regulate late embryo-genesis abundant (LEA) protein content36 and induce theaccumulation of storage proteins.37 Interestingly, in this study,the decrease in JA biosynthesis was correlated with a decreasein LEA proteins and the storage proteins legumin and glycinin(Supplementary Table S3 in the Supporting Information).However, we have observed a large increase in Arah1, apredominant peanut storage protein, in response to water-deficit stress.Downstream of TFs in the water-deficit stress response
cascade are stress-responsive proteins including the proteolyticubiquitin family of proteins and heat shock proteins.Ubiquitination plays a primary role in post-translationalregulation of expression and can affect protein stability, enzymeactivity, and cellular targeting.38−40 We observed significantchanges in two ubiquitin proteins, UBQ6 and UBQ14 (Figure2 and Supplementary Table S3 in the Supporting Information).Interestingly, these two proteins showed opposite trends inresponse to water-deficit stress, UBQ6 was reduced, andUBQ14 was induced. Several polyubiquitin genes have beenshown to increase in response to environmental stress.38,41−43
Sun and Callis43 reported induction of both UBQ14 andHSP70. Here we measured an increase in HSP 17.4 butreduced levels of HSP 70. We also observed a reduction inUBQ6 protein, which was shown to negatively regulateethylene signaling.44 Although the changes were not statistically
significant, we observed an increase in ethylene responsiveproteins, which could be a result of reduced UBQ6 levels.
3.3. Major Biological Pathways Altered in Seed Due toWater-Deficit Stress
3.3.1. Glycolysis. In Glycolysis, carbohydrates are con-verted to hexose phosphates, which are then split into twotriose phosphates. In a subsequent energy-conserving phase, thetriose phosphates are oxidized and rearranged to yield twomolecules of pyruvate. In the presence of oxygen, pyruvate thenenters the citric acid cycle and undergoes oxidation, producingenergy. In the absence of oxygen, plants metabolize pyruvate byalcoholic fermentation, producing ethanol, carbon dioxide, andenergy. We measured a significant reduction in pyruvatedikinase and alcohol dehydrogenase (Figure 3) in response towater-deficit stress, suggesting a movement of carbohydratetoward acetyl-CoA, ultimately resulting in increased energy inthe form of ATP generated by the TCA cycle. The increase inATP supply may serve to meet increased stress-related energydemands.
3.3.2. Sucrose and Starch Metabolism. Drought stressconsiderably decreases photosynthetic rate and disruptscarbohydrate metabolism in soybean and peanut leaves andcarbon export to sink tissues.16,45,46 Because sucrose is both theprincipal and the preferred form of photosynthate for long-distance transport to sink organs, its concentration in leavesrepresents the current availability of assimilates for reproductivedevelopment.47 In pigeon pea, drought stress resulted in asharp decline in leaf sucrose and starch concentrations, whileglucose and fructose levels increased significantly.48 Further-more, it has been shown that starch and sucrose in plant leavesare depleted due to drought, and a subsequent increase inhexose may be involved in feedback regulation of photosyn-thesis,49 causing a source limitation. Drought can also affectcarbohydrate metabolism in sink tissues with a subsequentincrease in sucrose concentrations in reproductive organs ofdrought-stressed plants.9 Sucrose must be cleaved into hexoses
Figure 4. MapMan-generated schematic representation of sucrose and starch metabolism pathways. Proteins significantly reduced by stress aremarked in green boxes. Other proteins indicated in either green (reduced) or red (induced) were not statistically significant. Proteins SBS, sucrosebinding protein; SUS4, sucrose synthase 4; AI, acid invertase; AGPase, ADP-glucose pyrophosphorylase; GP, glucan phosphorylase.
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for cellular metabolism. Two major enzymes responsible forcleavage are sucrose synthase and acid invertase. We observed adecrease in sucrose synthase and a corresponding increase inacid invertase protein (Figure 4). Additionally, sucrose-bindingprotein, glucan phosphorylase, and starch transporter proteinshowed reduced levels in response to stress (Figure 4). Thissuggests a general reduction in starch synthesis and an increasein sucrose metabolism and hexose production, which maymaintain the sucrose gradient between seed and sourcetissues.50 Apart from reduced sucrose degradation, there wasa reduction in sucrose-binding protein, a sucrose transporter,suggesting a further imbalance in soluble sugar levels potentiallyleading to retardation of seed development.51−53
3.3.3. Fatty Acid Metabolism. FAs in seeds of oilseedcrops are stored in oil bodies (OBs) as triacylglycerol (TAG).In seeds, they not only act as reserves of carbon and energy butalso determine the economic value of seeds in many crops.54
Production of TAG commences during the maturation phase ofseed development and results in a steady increase in seed dryweight. TAGs are esters of glycerol in which FAs are esterifiedto each of the three hydroxyl groups of the glycerol backbone.Once synthesized, TAGs are accumulated in subcellularorganelles called OBs, surrounded by phospholipid mono-layers.55,56 In seeds, sucrose is imported into embryo cells andcleaved by the enzymes, invertase, or SUS.57,58 Sucrose cleavagegenerates hexose phosphates, which are metabolized throughthe oxidative pentose phosphate pathway (OPPP) andglycolytic pathway, providing precursors for FA production inthe form of acetyl-CoA. In Arabidopsis, a multisubunitheteromeric acetyl-CoA carboxylase (ACCase) catalyzes thefirst committed step of the FA biosynthetic pathway (Figure5).59 FAs are produced from acetyl-CoA and malonyl-ACP,where acetyl-CoA is used as the starting unit and malonyl-CoAis used as the elongator. The malonyl thioesters formed in the
Figure 5. Simplified pathway of triacylglycerol (TAG) biosynthesis in seeds. Significantly reduced proteins coding enzymes involved in FA synthesisin plastids are indicated in green boxes. All other enzymes of FA synthesis and FA modification in ER are indicated in gray boxes. Abbreviations: Glc-6-P, glucose-6-phosphate; Fru-1,6-P, fructose-1,6-biphosphate; DHAP, dihydroxyacetone-3-phosphate; GAP, glyceraldehydes-3-phosphate; 1,3-BPG,1,3-biphosphoglycerate; 3-PGA, 3-phosphoglycerate; 2-PGA, 2-phosphoglycerate; 6-PGL, 6-phosphogluconolactone; 6-PG, 6-phosphogluconate;Ru-5-P, ribulose-5-phosphate; Ru-1,5-P, ribulose-1,5-biphosphate; PGK, phosphoglycerate kinase; ENOp, plastidial enolase; PEP, phosphoenolpyr-uvate; PKp, plastidial pyruvate kinase; PDC, pyruvate dehydrogenase complex; Ac-CoA, acetyl-coenzyme A; ACCase, acetyl-CoA carboxylase; ACP,acyl carrier protein; MAT, malonyl-CoA:ACP transacylase; KAS, 3-ketoacyl-ACP synthase; KAR, 3-ketoacyl-ACP reductase; HD, 3-hydoxyacyl-ACPdehydratase; ENR, enoyl-ACP reductase; SAD, stearoyl-ACP desaturase; FAT, fatty acyl-ACP thioesterases; FAE, fatty acid elongase complex; andDAGAT, diacylglycerol acyltransferase.
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above reaction enter into a series of condensation reactionswith acetyl-CoA and acyl-ACP acceptors. Three separatecondensing enzymes, namely, 3-ketoacyl-ACP synthases(KAS) I, II, and III, are necessary for the production of an18-carbon FA. The initial condensation reaction is catalyzed byKASIII, while KASI is responsible for producing chain lengthsfrom 6 to 16 carbons. KASII finally elongates 16:0-ACP to18:0-ACP.60 Three additional reactions are required after eachcondensation step to obtain a saturated FA that is two carbonslonger than at the start of the cycle. These reactions arecatalyzed by 3-ketoacyl-ACP reductase (KAR), 3-hydroxyacyl-ACP dehydratase (HD), and enoyl-ACP reductase (ENR).61
Very long chain FAs (VLCFAs) are synthesized by themultienzyme fatty acid elongase (FAE) complex in the ER.Drought stress reduced three proteins encoding enzymes of
the FA biosynthesis pathway in peanut seed (Figure 5). Themost significant among them was ACCase, the rate-limitingenzyme of FA metabolism. We have also seen reduction inphosphoglycerate kinase possibly limiting the supply of acetylCoal. In addition, there was a significant decrease in an oleosin,protein suggesting an altered OB structure and lipidaccumulation (Siloto et al., 2006) due to stress. Together, theproteomics data obtained in this study potentially explain themolecular basis of reduction in total FA content measured instressed peanut seeds (Figure 1).
4. CONCLUDING REMARKS
Peanut is an important dietary staple and biologically presents aunique model crop in terms of its seed development. However,compared with other legumes, little is known about themolecular mechanism of seed development and the impact ofabiotic stresses on development and quality. In this study, wehave utilized a quantitative shotgun proteomics approach togain insight into the molecular events underlying thephysiological responses of peanut seeds to water-deficit stress.Under adverse growing conditions, peanut seeds sense theexternal stimuli by signaling hormones BR and JA. Additionally,changes in polyubiquitination and induction of heat shockproteins may help to maintain cellular metabolism under stress.Stress induction of glycolysis and inhibition of alcoholicfermentation could provide additional energy to meet increasedmetabolic demands under water-deficit stress. Under water-deficit stress, sucrose mobility/export and starch synthesis aresuppressed along with a concomitant increase in sucrosedegradation by acid invertase, possibly explaining the molecularbasis of reduction in seed size, biomass, and viability. Droughtalters peanut seed composition by reducing the total FAcontent due to suppression of FA metabolism. In future studieswe will adopt an integrated approach of agronomic, genetic,and biochemical methods coupled to emerging -omics data fora deeper insight into the molecular basis of drought tolerance.This integrative approach will be the foundation of our effortsin developing peanut germplasm for production in low-inputregions or for specific nutritive and quality traits.The mass spectrometry proteomics data have been deposited
to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository62 withthe data set identifier PXD000308 (username: review27605;password: 4m8cyH4b).
■ ASSOCIATED CONTENT*S Supporting Information
Supplementary Figure S1: An overview of the label-freequantitative proteomics approach. We have sequenced themidmature peanut-pod transcriptome and generated an in-house pod specific proteome. Supplementary Figure S2:Functional categorization of nonredundant proteins identifiedin this study. MapMan-Mercator tool was used to annotate andfunctionally bin the proteins into different categories.Supplementary Table S3: The complete list of 761 proteinsidentified from control and stress samples in this study. TheTable also includes the numbers of peptides assigned to eachprotein for each replicate as well as the NSAF values. Thestatistically significant proteins are colored red (for up-regulated proteins) and green (for down-regulated proteins),which were obtained from t-test analysis. Supplementary TableS4: The separate lists of identified proteins for control samplewell as stress with their corresponding peptides numbers andNSAF values. This material is available free of charge via theInternet at http://pubs.acs.org.
The authors declare no competing financial interest.
■ ACKNOWLEDGMENTSWe thank Marie Syapin and Pratibha Kottapalli for technicalhelp. We also thank Susan San Francisco for valuablesuggestions during the preparation of the manuscript. Thisresearch was supported by grants from the Ogallala AquiferInitiative and USDA-ARS CRIS 6208-21000-012-00D.
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