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Proteomic and selected metabolite analysis of grape berry tissues under well-watered and water-deficit stress conditions

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In order to investigate the unique contribution of individual wine grape (Vitis vinifera) berry tissues and water-deficit to wine quality traits, a survey of tissue-specific differences in protein and selected metabolites was conducted using pericarp
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  R ESEARCH A RTICLE Proteomic and selected metabolite analysis of grapeberry tissues under well-wateredand water-deficit stressconditions Jérôme Grimplet  1 , Matthew D. Wheatley  1 , Hatem Ben Jouira  2  , Laurent G. Deluc  1 ,Grant R. Cramer  1 and John C. Cushman  1 1 Department of Biochemistry and Molecular Biology, University of Nevada Reno, Reno, NV, USA 2 Center of Biotechnology, Borj Cédria, Hammam-Lif, Tunisia In order to investigate the unique contribution of individual wine grape ( Vitis vinifera ) berry tis-sues and water-deficit to wine quality traits, a survey of tissue-specific differences in protein andselected metabolites was conducted using pericarp (skin and pulp) and seeds of berries fromvines grown under well-watered and water-deficit stress conditions. Of 1047 proteins surveyedfrom pericarp by 2-D PAGE, 90 identified proteins showed differential expression between theskin and pulp. Of 695 proteins surveyed from seed tissue, 163 were identified and revealed thatthe seed and pericarp proteomes were nearly completely distinct from one another. Water-deficitstress altered the abundance of approximately 7% of pericarp proteins, but had little effect onseedprotein expression.Comparisonof protein and available mRNAexpressionpatterns showedthat 32% pericarp and 69% seed proteins exhibited similar quantitative expression patternsindicating that protein accumulation patterns are strongly influenced by post-transcriptionalprocesses. About half of the 32 metabolites surveyed showed tissue-specific differences in abun-dance with water-deficit stress affecting the accumulation of seven of these compounds. Theseresults provide novel insights into the likely tissue-specific srcins and the influence of water-deficit stress on the accumulation of key flavor and aroma compounds in wine. Received: February 15, 2008Revised: December 23, 2008Accepted: December 30, 2008 Keywords: Metabolites / Tissue-specific proteins / Two-dimensional gel electrophoresis /   Vitis vinifera   L. / Water-deficit stress Proteomics   2009,  9,  2503–2528  2503 1 Introduction The berriesof grape vine ( Vitis vinifera  L.) and related speciesare one of the most widely grown and economically mostimportant fruit crops in the world. Since its initial domes-tication more than 7000 years ago [1, 2], berries have beenused for wine production, as well as grape juice, table grapes,raisins, and more recently for leaf, seed, and skin extracts bythe nutraceutical and cosmetic industries [3, 4]. The genetic diversity of grapevine has been narrowed considerably by theselection of only a few familiar cultivars ( e.g  ., Chardonnay,Cabernet Sauvignon, Syrah (Shiraz), and Merlot) now grownworldwide [1]. Quality traits, which are generally linked to aspecific tissue, such as skin color due to the production of anthocyanins and proanthocyanidins, are controlled by rela-tively few genes [5, 6]. However, traits consideredas desirable for one product could be undesirable for another. For exam-ple, seedlessness is a highly desirable trait in table grapes,however, seeds contain a high concentration of condensedtannins ( i.e ., proanthocyanidins), which are considered Correspondence:  Professor John C. Cushman, University of Nevada, Reno, Mail Stop 200, Reno, NV 89557-0200, USA E-mail:  jcushman@unr.edu Fax: 1 1-775-784-1650 Abbreviations: ADH,  alcohol dehydrogenase;  LEA,  late embryo-genesis abundant;  PPO,  polyphenol oxidase;  PR,  pathogenesis-related;  RuBisCO,  ribulose 1,5-bisphosphate carboxylase/oxyge-nase; SAM, S  -adenosylmethionine; UGP, UDP-glucosepyrophos-phorylaseDOI 10.1002/pmic.200800158 © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim  www.proteomics-journal.com  2504  J. Grimplet  et al. Proteomics   2009,  9,  2503–2528 indispensable for conferring astringency and color stabilityto red wines [7]. The skin, pulp, and seed tissues of grapeberries each confer unique properties to wine. The skin con-fers color, aroma, and other organoleptic properties of wine.The pulp contributes the majority of sugars, which aretransformed into alcohol during the fermentation process.Skin and pulp tissues are the main source of volatile aromacompounds, such as terpenes, norisoprenoids, and thiolsstored as sugar or amino acid conjugates [8]. The seed con-tains flavan-3-ol monomers and procyanidins (seed tannins),which contribute important organoleptic properties to wine[7].Analysis of the protein composition of grape berries andmust has been used to examine varietal and developmentaldifferencesas well as to analyze chemical and environmentaleffects in grape. PAGE analysis of must proteins has pro-vided a means to readily identify different grape varieties [9].ESI-MS has also been used to differentiate varieties by iden-tifying different classesof pathogenesis-related (PR) proteinsin grape juice [10]. In contrast, other researchers have con-cluded that 1-D and 2-D PAGE analysis of PR proteins wasinadequate to readily differentiate varieties [11].Protein extraction methods for mature grape berry clus-ters have been optimized with phenol-based methods beingsuperior to TCA/acetone methods [12]. Proteomic compar-ison of ripe berry mesocarp from six different  Vitis  cultivarsrevealed that most 2-D PAGE profiles were , 70% similar toone another with the exception of a few proteins, such asalcohol dehydrogenase (ADH), which displayed large poly-morphisms among the different cultivars [13]. High lightand CO 2  concentrations apparently stabilized ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) in grape-vine plantlets as monitored by 1-D and 2-D PAGE andimmunoblotting [14]. Herbicide stress on grapevine shoots,root, and leaves induced antioxidant and photorespiratoryenzymes, as well as a set of PR proteins [15]. Chronic salinityand water-deficit stress of grapevine shoots revealed distinctdifferences in protein expression patterns in cv. Chardonnayand cv. Cabernet Sauvignon [16].  Vitis  leaves, in which ADHwas over- orunder-expressed,revealedabundance changes incarbon metabolism-associated proteins [17]. Analysis of grape berry skin proteins from cv. Cabernet Sauvignon at thebeginning and end of véraision and in mature, harvest stageberries showed ripening-related protein abundance increas-es associated with anthocyanin biosynthesis and pathogendefense [18]. A similar, yet more comprehensive, analysis of berry ripening in  V. vinifera  cv. Nebbiolo Lampia showed thatmore than 100 proteins were differentially expressed duringberry development [19]. More recently, analysis of changes inthe expression of 67 grape skin proteins were monitoredfrom véraison to fully ripe berries of   V. vinifera  cv. Barberashowing that many proteins with (a)biotic stress responseswere developmentally regulated [20].In orderto better understand the complex transcriptionalregulatory hierarchy controlling tissue-specific gene expres-sion patterns, several studies have investigated the steady-state transcript abundance in discrete berry tissues. Large-scale EST sampling has been used to identify differences inexpression associated with different organ and tissue typesand developmental stages [21–23]. Large-scale mRNAexpression profiling studies have investigated expression inflowers and developing berries of   V. vinifera  [24–27], in afleshless berry mutant (cv. Ugni Blanc) [28], and in the skinof ripening berries of seven different  V. vinifera  cultivars [29].More recently, large-scale mRNA expression profiles withinskin, pulp, and seed tissues of well-watered and water-deficit-stressed vines of Cabernet Sauvignon were surveyed usingthe GeneChip ® V. vinifera  (Grape) Genome Array [30]. How-ever, no proteomic studies have been performed to investi-gate protein expression differences among different berrytissues.In order to obtain information on protein expressionchanges in grape berry tissues in response to well-wateredand water-deficit stress conditions, a comparative 2-D PAGEanalysis was performed using discrete tissue from the peri-carp tissues (skin and pulp) and seed. Approximately 7% of the more than 1000 skin and pulp proteins surveyed showeda two-fold or greater change in abundance in response towater-deficit stress indicating that water-deficit stress canhave a major impact on protein expression profiles in grapepericarp tissues. From the 695 proteins surveyed in the seed,seed protein expression patterns were completely distinctfrom those in the skin and pulp tissues, mainly due to highconcentrations of seed storage proteins. Skin abundant pro-teins were associated mainly with the phenylpropanoidpathway, PR proteins, heat shock proteins (HSPs), and poly-phenol oxidase (PPO), whereas pulp abundant proteinsincluded those involved in primary energy metabolism.Water-deficit stress led to tissue-specific changes in proteinexpression. The skin showed increased abundance of pro-teosome, reactive oxygen detoxification enzymes, and select-ed enzymes involved in flavonoid biosynthesis, whereas pulptissues showed increased in glutamate decarboxylase, PRproteins, and methionine synthase. Changes in the abun-dance of selected metabolites were also monitored in parallelwith protein expression analysis. Tissue-specific and waterstatus-dependent differences in metabolite profiles were alsoevident. 2 Materials and methods 2.1 Plant material and growth conditions V. vinifera  L. cv. Cabernet Sauvignon berrieswere sampled onSeptember 29, 2005, at which time the berries were fully ripeand corresponded to stage 38 (berry harvest) of the modifiedE-L system [31] from 20-year-old vines in the ShenandoahVineyard (Amador County, CA, USA), stored on ice for 3 h,frozenin liquid nitrogen and storedat 2 80 7 C. Therefore,it ispossible that changes in the proteome and metabolome mayhave occurred during the time the berries were stored on ice. © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim  www.proteomics-journal.com  Proteomics   2009,  9,  2503–2528  2505 Pulp, skin, and seeds were then separated without allowingberries to thaw. Skin was peeled off the pulp using a scalpel.The pulp was then cut into two halves from which the seedswere carefully removed. As complete removal of pulp cellsfrom the skin or seed tissues was not possible, the observeddifferences in tissue-specific patterns reported here mayshow some residual contamination from pulp tissues. Forthe well-watered plants, irrigation was performed from E-Lstage 27 [31]. Water-deficit treated vines were never irrigated.Berry clusters were harvested from the sunny (Southern)side of the vine. Six biological replicates were collected andanalyzed from both well-watered and water-deficit treatedvines. 2.2 Stem xylem water potential Fully mature leaves were selected for stem water potentialmeasurements [32]. A single leaf   per   plant was tightly zippedin a plastic bag to eliminate transpiration. Aluminum foilwas then placed around the bag, deflecting light and heat.After 2 h of equilibration time, the excised leaf was placed ina 3005 Plant Water Status Console pressure chamber (Soil-moisture Equipment, Santa Barbara, CA, USA). The foil wasremoved before sealing the bagged leaf in the chamber. Thebalancing pressure required to visibly push stem xylem sapto the cut surface was recorded. 2.3 Brix assay The Brix(total solublesolids)was assayedfrom juicecrushedfrom harvested berries with a refractometer (BRIX30, Leica,Bannockburn, IL, USA). 2.4 Protein extraction Protein extractions were performed in sets of four randomsamples, with the constraint that two biological replicateswere never processed within the same set. Five grams of frozen skin or pulp tissue or 1 g of seed was ground to a finepowder in liquid nitrogen with mortar and pestle. Extractionwas adapted from the phenol extraction protocol 4 as de-scribed [12], which was adapted from previously describedprotocols [33, 34]. Powder was vortexed in 10 mL of sucrose buffer 4 (0.7 M sucrose, 0.5 M Tris-HCl pH 7.5, 50 mMEDTA, 0.1 M potassium chloride, 2 mM phenylmethane-sulfonylfluoride (PMSF), 2%  b -ME, 1 Complete ™ proteaseinhibitor cocktail tablet (Roche Diagnostics, Indianapolis,IN, USA), and 1% polyvinylpyrrolidone (PVPP)) and incu-bated for 10 min at 4 7 C. After incubation, an equal volume of 1 M Tris-saturated phenol (pH 7.9) was added. The mixturewas stored at 2 20 7 C for 30 min with vortexing every 10 min.The phases were separated by centrifugation (30 min at 0 7 Cat 3210 6  g  ). The upper phenol phase was collected and reex-tracted with an equal volume of sucrose buffer 4. Fivevolumes of 0.1 M ammonium acetate in cold MeOH wereaddedtothe phenol phase to precipitate proteins,followedbyincubation at 2 20 7 C overnight. The pellet was washed with5 mL of cold 0.1 M ammonium acetate/MeOH 50:50 w/v,two times with 5 mL of cold acetone and once in 2 mL of coldacetone/ethanol 50:50 v/v. The pellet was then vacuum-dried5 min and resolubilized in 1.5 mL of rehydration buffer (7 Murea, 2 M thiourea, 4% CHAPS, 10 mM DTT, 1% carrierampholyte (CA), pH 5–7, and 1% CA, pH 3–10). PVPP(50 mg) was added to each sample, then each sample wasvortexed, and centrifuged (15 min at 2 4 7 C at 10000 6  g  ) andthe supernatant was stored at 2 80 7 C. 2.5 Protein assays Protein concentrations were determined using an EZQ ™ Protein Quantitation kit (Invitrogen, Carlsbad, CA, USA)with ovalbumin as a standard, according to the manu-facturer’s instructions. Concentration ranged from 3.6 to10.6 mg/mL. 2.6 2-DE and gel staining In order to reduce technical variation, no more than two of the six replicates were processed within the same set of 2-DSDS-PAGE gels. The 2-D SDS-PAGE protocol was adaptedfrom O’Farrell [35]. IEF was carried out using IPG strips(24 cm, pH 4–7, Immobiline ™ DryStrip, GE Healthcare, Pis-cataway, NJ, USA). The loading volume used was 440  m L of protein extract, corresponding to a protein amount of 1.2 mg  per   strip. Protein IEF was performed using a Protean ® IEFCell (Bio-Rad, Hercules, CA, USA) at 20 7 C as follows: activerehydration at 50 V for 12 h, 200 V for 30 min with a linearincreasein voltage, 500 V for30 min with a linear increaseinvoltage, 1000 V for 1 h with a linear increase in voltage, and10000 V with a rapid increase in voltage until a total of 85000 V ? h had been reached. Strips were then stored at 2 20 7 C until further use. Once thawed, the strips werewashed for 30 min in equilibration buffer (6 M urea, 30%glycerol, 2 M Tris-HCl pH 8.8, and 2% SDS) containing 1%w/v DTT followed by washing with equilibration buffer con-taining 2.5% w/v iodoacetamide for 30 min. SDS-PAGE wasperformed using noncommercial 12% polyacrylamide gels(18 cm 6 20 cm 6 1 mm) and run at 40 V for 2 h and 120 Vfor 15 h in a Bio-Rad Protean ® II XL 2-D Multi-Cell. A CBBG-250 procedure was used to stain the 2-D gels [36]. The gelswere washed twice in 50% EtOH/2% phosphoric acid/de-ionized water (diH 2 O) v/v/v for 1 h, then transferred to 2%phosphoric acid for 60 min, and finally allowed to shake for3 days in 15% EtOH/17% ammonium sulfate/2% phos-phoric acid/0.2% CBB G-250/dH 2 O v/w/v/w/v. The 2-D gelswere imaged using a VersaDoc ® Imaging System Model1000 (Bio-Rad). 2.7 Protein identification Spot excision was performed using the ProteomeWorks ™ spot cutter (Bio-Rad); then trypsin digested according to ref. © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim  www.proteomics-journal.com  2506  J. Grimplet  et al. Proteomics   2009,  9,  2503–2528 [37] using the Investigator ™ ProPrep ™ (Genomic Solutions,Ann Arbor, MI, USA). The tryptic fragments were analyzedusing an ABI 4700 Proteomics Analyzer (Applied Biosys-tems, Foster City, CA, USA) MALDI TOF/TOF ™ mass spec-trometer (MS). A 0.5 mL aliquot of a matrix solution con-taining 10 mg/mL CHCA (Sigma–Aldrich, St. Louis, MO,USA) and 10 mM ammonium phosphate (Sigma–Aldrich)in 70% ACN was cospotted with 0.5 mL of sample [38]. Thedata were acquired in reflector mode from a mass range of 700–4000 Da, and 2500 laser shots were averaged for eachmassspectrum. Each sample was internally calibratedifboththe 842.51 and 2211.10 ions from trypsin autolysis werepresent. When both ions were not found, the instrumentused the default calibration. The eight most intense ionsfrom the MS analysis, not present on the exclusion list, weresubjected to MS/MS analysis. To this end, the mass rangewas 70 to precursor ion with a precursor window of 21–3 Dawith an average of 5000 laser shots for each spectrum. Theresulting file was then searched by using automated MAS-COTsoftware (http://www.matrixscience.com/) through theIDQuest (Bio-Rad) interface was used for searching theNCBI nonredundant database (ver. 22_05_2007; 4 970 641sequences), or the Contigs from Vitis Gene Index ver. 5.0(ver. 18_9_2006, 23 871 sequences). Peptide tolerance was20 ppm; 1 missed cleavage was allowed; MS/MS tolerancewas 0.8 Da. The possibility of matching multiple translatedisoforms was examined by manual analysis of peptides cov-ering the sequences. 2.8 Statistical analysis Results from six different gels were compared for well-watered and water-deficit-stressed vines for each tissue andthe results of 12 different gels were compared between skinand pulp. Differences in spot abundance were statisticallyevaluated using the ANOVA method with geneANOVA soft-ware [39]. The number of detected spots showing differenceswith a  p -value of    0.05 was then determined. The spots werecounted as valuable if their normalized intensity was higherthan 0.01% of the total spot intensity. However, for non-detectedspotsa backgroundvaluewasusedin the gels wherethey did not appear in orderto limit the rate offalse positives.Average CV was calculated for each experiment with andwithout background values. Spots were identified and thencuratedmanually with respectto spot quality ( e.g  ., sharpness,resolution) and the quality of spot matching to reduce falsepositives.For protein and mRNA abundance comparisons, log 2 values of the protein and mRNA ratios between pulp andskin values were plotted and the regression curve was deter-mined using Excel. The mRNA expression values deter-mined by microarray expression profiling were obtainedfrom [30]. The proteome analysis reported here was per-formed using berries harvested one year later from the samevines at the same harvest date as were used for mRNA pro-filing. 2.9 Metabolite extraction and derivatization protocol Polar metabolites were extracted and derivatized with awater/chloroform protocol according to previously describedprocedures [40]. Freeze-dried berry tissue (6 mg) was placedin a standard screw-cap-threaded, glass vial. Samples wereincubated in HPLC-grade chloroform for 1 h at 50 7 C in anoven. A volume of Millipore NANOpure ™ water containing12.5 mg/L of ribitol as an internal standard was added toeach sample, and then incubated for an additional hour at50 7 C. Finally, vials were allowed to cool to room temperatureand then spun at 2900 6  g   for 30 min. One milliliter of thepolar phase was dried down in a vacuum concentrator over-night. Polar samples were derivatized by the addition of 120  m L of 15 mg/mL of methoxyamine HCl in pyridine,sonicated for 30 min, and incubated at 50 7 C for 1 h. Onehundred twenty microliters of   N  -methyl- N  -trimethylsilyltri-fluoroacetamide (MSTFA) 1 1% trimethylchlorosilane(TMCS) were added, incubated at 50 7 C for 1 h, and analyzedimmediately with a PolarisQ ™ 230 GC-MS (Thermo FisherScientific, Waltham, MA, USA). Derivatized samples(120  m L) were transferredto a 200  m L silanized vial insert andrun at an injection split of 200:1 to bring the large peaks to aconcentration within the range of the detector and 10:1 fordetection of lower peaks. The inlet and transfer lines wereheld at 240 and 320 7 C, respectively. Separation was achievedwith a temperature program of 80 7 C for 3 min, then rampedat 5 7 C/min to 315 7 C and held for 17 min, using a 60 m DB-5MS column (J&W Scientific, 0.25 mm i.d., 0.25  m m filmthickness) and a constant flow of 1.0 mL/min. All organicacids, sugars, and amino acids were verified with standardspurchased from Sigma–Aldrich. 2.10 Metabolite data processing Metabolites were identified in the chromatograms using twodifferent software packages: AMDIS (ver. 2.64, United StatesDepartment of Defense, USA) and Xcalibur (ver. 1.3;Thermo Fisher Scientific). The software matched the massspectrum in each peak against three different metabolitelibraries: NIST ver. 2.0 library (http://www.nist.gov/srd/),T_MSRI_ID library of the Golm Metabolome Database [41],and a local database containing more than 50 standards.Quantification of the area of the chromatogram peaks wasdetermined using Xcalibur and normalized as a ratio of thearea of the peak of the ribitol internal standard. 3 Results 3.1 Physiological data Fully ripe berry samples were harvested from E-L stage 38berries [31]. This harvest date corresponded to the time of commercial harvest of the vineyard. Stem water potentialdifferences were monitored for well-watered and water-defi- © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim  www.proteomics-journal.com  Proteomics   2009,  9,  2503–2528  2507 cit treated vines as a comprehensive indicator of water-deficitin the vines [42]. Stem water potentials were significantlymore negative for water-deficit treated vines than for well-watered vines at the time of harvest (Table 1). Brix values, anapproximate measure of the mass ratio of dissolved solids towater in fruit juices,were also significantly different betweenberries harvested from well-watered and water-deficit-stresstreated vines. These values are close to the generally recom-mended value (23 7  Brix) for harvest of cv. Cabernet Sau-vignon in central California. However, no significant differ-ences in berry diameter were observed (Table 1). Table 1.  Physiological data for berries harvested from vinesgrown under well-watered and water-deficit stress con-ditions Sample Stem waterpotential (MPa)Berry refractiveindex (Brix)Berry size(mm)Well-wateredvine 2 0.58 ( 6 0.07) a) 19.78 ( 6 1.02) a) 11.23 ( 6 0.33) a) Water-deficitvine 2 0.86 ( 6 0.11) a,b) 21.73 ( 6 0.74) a,b) 11.27 ( 6 0.30) a) a)  n   = 6.b) Difference between well-watered and water-deficit weredeterminedtobesignificant ( p  -value , 0.01)bytheStudent’s t  -test. Standard errors are indicated in parentheses. 3.2 Comparative 2-D PAGE analyses of berry tissueproteins Three different berry tissues ( i.e ., skin, pulp, and seed)were dissected manually as a starting point for 2-D PAGEanalysis. A relatively large number of biological samplereplicates (six) for each tissue type and water status treat-ment were performed to obtain a statistically robustassessment of the differences in protein expression pat-terns. Each replicate was considered a biological replicatebecause it was collected from a different vine. Replicatesamples were extracted and analyzed such that no morethan two gels from the same tissue/condition were pro-cessed at the same time within the same set of samples. Intotal, 1047 spots were detected in skin and pulp from vinessubjected to either well-watered or water-deficit stress con-ditions (Table 2). For these two tissues, an average of 854spots  per   gel with an intensity value greater than 0.01% of the total average spot intensity was detected. In contrast,seeds presented a totally different profile that was not di-rectly comparable to the skin and pulp tissue profiles.Therefore, 2-D PAGE gels for this tissue were processedindependently until final spot matching. In seeds, a total of 695 spots was detected in seeds from vines subjected toeither well-watered or water-deficit stress conditions (Table2). An average of 605 spots  per   gel with intensities higherthan 0.01% of the total spots intensity was detected. Tomaximize the number of proteins identified in this study,such as transcription factor or hormone metabolism-relat-ed proteins that typically are of low abundance, faint spotswere included, not only leading to a relatively high numberof spots  per   gel (Table 2), but also a relatively high averageCV. However, these CV values were within a range thatwas consistent with previously reported average or meanvalues for other plant proteomic analyses (0.26–0.31 [43];0.47–0.75 [44]; and 0.24 [45]). The decision to retain back- ground values tended also to increase CV values.In order to identify differentially expressed proteinsamong the three different berry tissues, 2-D PAGE gels werecompared. Spots that displayed differential abundance afterANOVA (  p , 0.05) and a two-fold ratio or greater differencewere identified and then curated manually with respect tospot quality ( e.g  ., sharpness, resolution) and the quality of spot-matching to reducedfalse positives.Analysis of pericarpproteins revealed 90 spots that displayed differential abun-dance after ANOVA (  p , 0.05) and a two-fold ratio or greaterdifference: 54 were more abundant in the skin (Fig. 1 andTable 3) and 36 were more abundant in the pulp (Fig. 2 andTable 3). A majority of proteins (217 in total) showed a rela-tively constant abundance between the skin and pulp (seeSupporting Information Fig. 1 and Table 5). Table 2.  Average numbers of spots and CV for each berry tissue and water treatment condition Skin WW Skin WD Pulp WW Pulp WD Seed WW Seed WDTotal spots 1046 1046 1046 1046 695 695AverageCV (total spots) 0.84 0.74 0.82 0.81 0.74 0.76Spots ( I  . 0.01%) 835 6 59 870 6 30 855 6 30 855 6 68 608 6 41 602 6 23AverageCV ( I  . 0.01%) 0.65 0.58 0.64 0.63 0.59 0.60Spots ( I  . 0.05%) 462 6 55 509 6 20 457 6 37 482 6 48 365 6 109 366 6 58AverageCV ( I  . 0.05%) 0.55 0.56 0.56 0.55 0.53 0.54 The spots were counted regardless of their intensity (I) or according to CV values greater than 0.01% or 0.05% of thetotal intensity of all spots.WW = well-watered; WD = water-deficit treated.  n   = 6. © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim  www.proteomics-journal.com
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