Physiological and Proteomic Analyses of Drought Stress Response

Article pubs.acs.org/jpr

Physiological and Proteomic Analyses of Drought Stress Response in Holm Oak Provenances José Valero-Galván,*,†,‡ Raquel González-Fernández,‡ Rafael Ma Navarro-Cerrillo,§ Eustaquio Gil-Pelegrín,∥ and Jesús V. Jorrín-Novo‡ †

Department of Chemistry-Biology, Biomedical Sciences Institute, Autonomous University of Ciudad Juárez, Anillo Envolvente del Pronaf y Estocolmo s/n, 32310 Ciudad Juárez, Chihuahua, México ‡ Agricultural and Plant Biochemistry and Proteomics Research Group, Dept. of Biochemistry and Molecular Biology, University of Córdoba, Agrifood Campus of International Excellence (ceiA3), 14071 Córdoba, Spain § Department of Forestry Engineering, ETSIAM, University of Córdoba, Agrifood Campus of International Excellence, ceiA3, 14071 Córdoba, Spain ∥ Forest Resource Unit, Agrifood Research and Technology Centre, Government of Aragón, 50059, Zaragoza, Spain S Supporting Information *

ABSTRACT: Responses to drought stress by water withholding have been studied in 1 year old Holm oak (Quercus ilex subsp. ballota [Desf.] Samp.) seedlings from seven provenances from Andalusia (southern Spain). Several physiological parameters, including predawn xylem water potentials and relative water content in soil, roots, and leaves as well as maximum quantum efficiency and yield of PSII were evaluated for 28 days in both irrigated and nonirrigated seedlings. The leaf proteome map of the two provenances that show the extreme responses (Seville, GSE, is the most susceptible, while Almerı ́a, SSA, is the least susceptible) was obtained. Statistically significant variable spots among provenances and treatments were subjected to MALDI-TOF/TOF-MS/MS analysis for protein identification. In response to drought stress, ∼12.4% of the reproducible spots varied significantly depending on the treatment and the population. These variable proteins were mainly chloroplastic and belonged to the metabolism and defense/stress functional categories. The 2-DE protein profile of nonirrigated seedlings was similar in both provenances. Physiological and proteomics data were generally in good agreement. The general trend was a decrease in protein abundance upon water withholding in both provenances, mainly in those involved in ATP synthesis and photosynthesis. This decrease, moreover, was most marked in the most susceptible population compared with the less susceptible one. KEYWORDS: water potential, chlorophyll fluorescence, biomass, Quercus ilex, Holm oak proteomics, drought stress in Holm oak

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will probably be one of the most important “hot-spots” according to climate change predictions.6 Holm oak (Quercus ilex subsp. ballota [Desf.] Samp.) is the prevailing tree species in forest ecosystems of the Western Mediterranean Basin.7 As a consequence, this species has a great economic and environmental value. Holm oak acorns are a major ingredient in the diet of many Mediterranean domestic livestock and wild species. Likewise, these acorns are the major element in the diet of domestically bred pigs to get high-quality meat.8 In Andalusia (southern Spain), Holm oak extends throughout 735 671 ha, and it is associated with the “dehesa” system, an agrosilvopastoral system used for livestock purposes. Nowadays, the threats that affect oak populations include the poor

INTRODUCTION Forest trees are forced to contend with changing environmental conditions over their long lifetimes. Water disposal is the most important of these environmental fluctuations.1 In point of fact, water availability is a crucial factor of the geographical distribution of tree species due to its enormous influence on tree establishments, survival, and productivity.2,3 Exposure to occasional dry periods may also result in long-term growth decrease in established forests, while it may involve an increased mortality among young trees grown in plantations.2 Trees must accomplish a physiological and developmental adaptation to cope with water limitation. For our study, we should point out that the Mediterranean region is located in a transition zone between the warm and rainy weather of central Europe and the arid climate of North Africa, and it is under the influence of the interactions between the midlatitude and tropical climates.4 Thus, the Mediterranean area is a potentially sensitive region to climatic changes,5 and it © 2013 American Chemical Society

Special Issue: Agricultural and Environmental Proteomics Received: June 21, 2013 Published: October 2, 2013 5110

dx.doi.org/10.1021/pr400591n | J. Proteome Res. 2013, 12, 5110−5123

Journal of Proteome Research

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regeneration of the wood areas of “dehesas”, inappropriate livestock management practices, and the occasional dramatic effect of forest decline.9 This decline is attributed to fungal attacks (e.g., Hypoxylon mediterraneum (De. Not.) Mill., Biscogniauxia mediterranea (De Not.) (Kuntze), or Phytophthora cinnamomi Rands.),9−11 although it may be caused after several years of drought combined with high temperatures. Thus, prolonged environmental stress causes a weakening of the individual trees, which are then highly susceptible to pests and diseases. Drought stress restricts the growth, development, distribution, and production of plants.12 Although Holm oak shows a high tolerance to drought and high temperatures,13−15 water deficiency is the major reason of seedling death in Holmoak woods.16,17 Different drought responses have been observed in distinct Quercus species, and these include both morphology18 and physiological features.14,17,19,20 In particular, changes in the photochemical efficiency in water-stressed Holm oak plants have been previously reported.21−23 Proteomics has already proven their value in assessing genetic changes in several plant species24−29 as well as in characterizing the natural variability of Q. ilex.30,31 Transcriptomics and proteomics approaches have also demonstrated their usefulness for characterizing the responses of forest trees exposed to drought.32,33 Just a few studies, however, have been conducted for oak “omics” and especially for Holm oak. This represents a strong restriction for a comprehensive explanation of the complexity of protein identification.22,30,31,34,35 The drought effects on the leaf proteome of Quercus species has been previously reported.22,35,36 Unfortunately, to the extent of our knowledge, there are few studies relating the different genotype response within a geographical area to drought in terms of their proteome. In this study, we aimed to increase the molecular response knowledge of the mechanisms related to the tolerance of water-deficit stress in different Holm oak provenances and to identify proteins associated with water-deficit responses. We used physiological and proteomic techniques, in a greenhouse experiment, to examine the response of Holm oaks under both irrigation and nonirrigation conditions. We took different physiological measurements on 1 year old Holm oak seedlings from seven Andalusian provenances. Moreover, we also compared the two-dimensional electrophoresis (2-DE) leaf proteome of irrigation and nonirrigation seedlings of the two provenances that show the extreme responses to drought.

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were transplanted into a greenhouse at University of Córdoba (Córdoba, Spain) in February 2008. Two similar plots were established at 2 m spacing. Each plot was divided into seven randomized complete blocks (one plot from each provenance per block). The 1 year old seedlings were transplanted into plastic pots (1 L) with peat and perlite (3:1 v/v). These seedlings were irrigated every 3 days at field capacity for 1 month (April 2008). Once the physiological status of all seedlings was homogeneous, the first plot remained irrigated (used as a control), whereas the second plot was not watered for 28 days (there were 30 seedlings per provenance and treatment in each plot). The seedlings were maintained in the greenhouse for the rest of the experiment at 25−30 °C and a relative humidity of 70 ± 5%. Physiological Measurements

Before the physiological characteristics were assessed, the total pot weight (TPW) (substrate plus plant) and the substrate relative water content (SRWC) were monitored at three different times (i.e., 0, 14, and 28 days) in three individuals of each population and treatment (Supplementary Figure 1 in the Supporting Information). A sample (2 g) of substrate was collected and immediately weighed and dried (70 °C) until a constant weight was reached. The weight data were analyzed as previously reported in Echevarrı ́a-Zomeño et al. (2009).22 Predawn xylem water potentials (PWP) (MPa), the maximum quantum efficiency of PSII (Fv/Fm), and the quantum yield of noncyclic electron transport (ΦPSII) of dark-adapted leaves were measured as reported by Echevarrı ́aZomeño et al. (2009).22 PWP was measured at three different moments (0, 14, and 28 days) in three seedlings per population and treatment using a Scholander pressure chamber (SKPM 1400, Skye Instruments). Photosynthetically active leaves (2 g) and roots (2 g) of five seedlings per population and treatment were harvested at three different times (0, 14, and 28 days). They were immediately weighed and dried (70 °C) until a constant weight was reached. Leaf relative water content (LRWC) and root relative water content (RRWC) were recorded as described previously in Echevarrı ́a-Zomeño et al. (2009).22 The Fv/Fm and ΦPSII were measured with a plant efficiency analyzer (Hansatech Instruments, England). Protein Extraction

Ten fully expanded (photosynthetically active) leaves per plant from each population and treatment were collected (i.e., three biological replicates per population and treatment, with each replicate corresponding to three plants, fresh weight: 8−10 g). Sampled leaves were abundantly washed with tap water, blotdried with filter paper, frozen in liquid N2, and finally stored at −80 °C until protein extraction. Proteins were extracted from 500 mg of leaf tissues by the TCA/acetone-phenol protocol according to Wang et al. (2006).37 The final pellet was solubilized in 100 μL of a solution of 7 M urea, 2 M thiourea, 4% (w/v) CHAPS, 0.5% (w/v) Triton X-100, and 100 mM DTT. Insoluble material was removed by centrifugation. The protein content in the supernatant was quantified according to the Bradford method,38 using bovine serum albumin (BSA) as standard. Finally, the samples were kept at −80 °C.

MATERIALS AND METHODS

Plant Material, Growth Conditions, and Drought Induction

Holm oak mature acorns were collected from seven populations distributed throughout the Andalusia region (southern Spain), mainly located in three major regions: south, northeast, and northwest (RG: Granada; GSE: Seville; BCA: Cádiz; SAA: Almerı ́a; CHU: Huelva; PCO, Córdoba; VJA: Jaen). Geographical coordinates, altitude, mean annual precipitation, and mean maximum and minimum temperatures corresponding to each population are shown in Supplementary Table 1 in the Supporting Information. Undamaged, homogeneous mature acorns were collected from 20 individual trees (3 kg per tree) for each population in November 2006. Once harvested, acorns were kept in airtight polyethylene bags and stored at 4 ± 1 °C until germination. The acorns were sown in forest pot trays (40 cells of 300 mL per tray) with an 80:20 (v/v) mixture of peat and perlite. Homogeneous seedlings (length of 27 ± 2 cm and leaf number of 23 ± 2)

Two-Dimensional Electrophoresis

Protein extracts (300 μg BSA equivalent) were subjected to 2DE using the large system (17 cm), as described by ValeroGalvan et al. (2012, 2011).30,31 In brief, isoelectrofocusing (IEF) was performed using 17 cm, 5−8 pH linear range, IPG 5111



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threshold, and zero permutations. The multivariate analysis was carried out in two steps: first, hierarchical clustering was performed to check the entire data set, and the results were represented in dendrograms using the cluster function of the software; second, the entire data set was analyzed by using the principal component analysis (PCA) method. The settings used for the PCA analysis were: covariance matrix type, three principal components, one-fold change, and 0.4 correlation threshold for clusters. PCA results are shown as a biplot.

strips (Bio-Rad, Hercules, USA). The strips were actively rehydrated for 12 h at 50 V with 250 μL of a solution of 7 M urea, 2 M thiourea, 4% (w/v) CHAPS, 0.2% (v/v) IPG ampholyte buffer pH 5−8, 100 mM DTT, and 0.01% (w/v) bromophenol blue39 with 300 μg BSA equivalent of proteins. The strips were loaded onto a Protean IEF Cell system (BioRad, Hercules) and electrofocused at 20 °C using the following parameters: for 20 min at 250 V, followed by 150 min linear gradient from 250 to 10 000 V, and finally focused to 40 000 V at 10 000 Vh. After IEF, the strips were reduced and alkylated according to Gorg et al. (1992).39 The second dimension was performed on 13% polyacrylamide gels with the use of the Protean Dodeca Cell (Bio-Rad, Hercules). The gels were run at 150 V (constant voltage) until the dye reached the bottom of the gel. Gels were stained by using the colloidal Coomassie method.40 In brief, gels were rinsed in bidistilled water for 1 min and stained overnight in staining solution −10% w/v ammonium sulfate, 2% w/v phosphoric acid (pH 6.5), and 0.1% w/v CBB G250 (Merck, Darmstadt, Germany). The following day, gels were successively washed in 0.1 M trisphosphoric acid for 3 min, in 25% v/v methanol for 1 min, and in 20% w/v ammonium sulfate for 24 h. Images were digitized with a GS-800 calibrated densitometer (Bio-Rad, Hercules), and then analyzed with PD-Quest software v8.0 (Bio-Rad, Hercules), using 10-fold over background as the minimum criterion for presence/absence. The analysis was doublechecked by visual inspection, focusing on the spots found in all three biological replicates for each sample (consistent spots).

MALDI-TOF/TOF Analysis

The proteins selected for analysis were in-gel reduced, alkylated, and digested with trypsin, according to Sechi et al. (1998).44 In brief, spots were washed twice with water, shrunk 15 min with 100% acetonitrile (ACN), and dried in a Savant Speed Vac for 30 min. Then, the samples were reduced with 10 mM DTT in 25 mM ammonium bicarbonate for 30 min at 56 °C, and subsequently alkylated with 55 mM iodoacetamide in 25 mM ammonium bicarbonate for 15 min in the dark. Samples were digested with 12.5 ng/μL sequencing grade trypsin (Roche Molecular Biochemicals) in 25 mM ammonium bicarbonate (pH 8.5) overnight at 37 °C. After digestion, 1 μL was spotted onto a MALDI target plate and allowed to airdry at room temperature. Later, 0.4 μL of a 3 mg/mL of αcyano-4-hydroxy-cinnamic acid matrix (Sigma) in 50% ACN was added to the dried peptide digest spots and allowed again to air-dry at room temperature. The MALDI-TOF/TOF-MS/MS analysis was performed in a 4800 Plus Proteomics Analyzer MALDI-TOF/TOF mass spectrometer (Applied Biosystems, MDS Sciex, Toronto, Canada). The MALDI-TOF/TOF operated in positive reflector mode, with an accelerating voltage of 20 kV. All mass spectra were internally calibrated using peptides from the auto digestion of trypsin (m/z = 842.509 and 2211.104). The analysis by MALDI-TOF/TOF mass spectrometry produces peptide mass fingerprints, and the peptides observed with a signal-to-noise greater than 10 can be collated and represented as a list of monoisotopic molecular weights. Proteins ambiguously identified by peptide mass fingerprints were subjected to MS/MS sequencing analyses. So, from the MS spectra, the eight most abundant precursors were selected for MS/MS analyses with collision-induced dissociation (CID) on (atmospheric gas was used) operated in 1 kV positive ion reflector mode and precursor mass windows ±4 Da. The plate model and default calibration were optimized for the MS/MS spectra processing. For protein identification, the database NCBInr search was conducted, with taxonomic restriction to Viridiplantae (Green Plants) (date 08_2009; 522 519 sequences) using a local license of MASCOT engine v. 2.2 (Matrix Science, London; http://www.matrixscience.com) through the software Global Protein Server v.3.6 from ABSciex. The search parameters were as follows: carbamidomethyl cysteine as fixed modification; oxidized methionine as variable modification; peptide mass tolerance: 50 ppm for PMF, or 80−100 ppm for MS/MS or combined searches; 1 missed trypsin cleavage site; peptide charge state: +1; and MS/MS fragments tolerance: 0.3 Da. The parameters for the combined search (peptide mass fingerprint plus MS/MS spectra) were the same as those previously described. In all protein identification, the probability scores were greater than the score fixed by Mascot as significant, with a p value < 0.05.

Statistical Analyses

The replicate number used for the TPW, SRWC, and PWP measurements and proteomics analysis (per provenances and treatment) was n = 3, whereas the replicate number for LRWC, RRWC, Fv/Fm, and ΦPSII measurements (per provenances and treatment) was n = 5. The normality of frequency distributions was tested on SRWC, TWP, LRWC, RRWC, PWP, Fv/Fm, and ΦPSII by the Kolmogorov−Smirnov test, which showed a normal distribution. The SRWC, TWP, LRWC, RRWC, PWP, Fv/Fm, and ΦPSII data were analyzed using a general linear model (GLM) procedure, with fixed effects of population, treatment, and time. The differences between combinations at each sampling interval were determined using a Duncan range test, with the level of significance set at α = 0.05. All statistical analyses were performed using the SPSS statistical software, version 13.0. The volume of pixels for each spot in 2-DE, and prior to statistical and phylogenetic analyses, was normalized according to the total volume of gel spots. Then, the data were logtransformed. For statistical analysis, the web-based software NIA array analysis tool41 (available at http://lgsun.grc.nia.nih. gov/anova/index.html) was used. Treatment and cluster analysis of protein abundance values were carried out following the recommendations described by Valledor and Jorrin (2011).42 All experimental data were statistically analyzed using the parameters defined by Brumbarova et al. (2008).43 The software tool previously mentioned selects statistically valid protein spots based on analysis of variance (ANOVA). After uploading the data, and together with the indications about biological replicates and technical subreplicates, they were statistically analyzed using the following settings: error model ‘max (average, actual)’, 0.01 proportion of highest variance values to be removed before variance averaging, 10 degrees of freedom for the Bayesian error model, 0.05 FDR 5112



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Figure 1. Time course of predawn water potential (PWP) (A), maximum quantum efficiency of photosystem II (Fv/Fm) (B), quantum yield of PSII electron transport (ΦPSII) (C), leaf relative water content (LRWC) (D), and root relative water content (RRWC) (E) measured at midday (solar time) on seven Andalusia Holm oak provenances (VJA: Jaen; BCA: Cádiz; GR: Granada; PCO: Córdoba; SAA: Almerı ́a; GSE: Seville; and CHU: Huelva). Error bars indicate the SD of the mean of three measurements for PWP and five measurements for Fv/Fm, ΦPSII, LRWC, and RRWC. Differences between combinations at each sampling interval were analyzed using the Duncan range test, with the level of significance set at P ≤ 0.05.

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days 0 and 14, with a statistically significant decrease to 0.66 ± 0.01 at day 28. Three populations (GR, SSA, and PCO) presented the highest values (0.67 ± 0.01), while GSE had the lowest ones (0.64 ± 0.01) at day 28 (Figure 1D). The reduction in Fv/Fm in water-stressed seedlings reflects the change of energy dissipation systems that reduces the amount of light energy required for photosynthesis.23 Under water deficit conditions, this decrease in photosynthesis entails a reduction in the ATP and NADPH consumption rate for CO2 assimilation. This may decrease the linear electron transport rate from the quinone acceptors of PSII and, as a result, induce a Fv/Fm reduction.45 Reductions in photochemical efficiency have been reported for Quercus spp., including Q. ilex, and other species in response to drought stress.20,22,23,46 The ΦPSII values of nonirrigated seedlings were 0.50 ± 0.00 and 0.47 ± 0.01 at days 0 and 14, respectively, with a statistically significant decrease to 0.42 ± 0.01 at day 28 (Figure 1E). At day 28, SSA presented the highest value (0.45 ± 0.01), while GSE had the lowest one (0.39 ± 0.01) (Figure 1E). Q. ilex, as an example of the Mediterranean evergreen oaks, has been widely recognized as a representative of a highdrought-tolerant plant,12,47 as this species is able to withstand long arid periods in summer.21 Q. ilex is a good example for physiological studies that involve relatively high levels of water stress23 as compared with other congeneric species much more sensitive to dehydration.48 Although the specific resistance to drought has been proved by different physiological and morphological responses,49,50 intraspecific variations have also been reported.47 Our results indicate that some differences among the populations here studied can also be found: SSA is the least susceptible population and GSE is the most susceptible population under drought conditions. For this

RESULTS AND DISCUSSION

Physiological Parameters

In the present study, Holm oak responses to drought have been assessed by making a comparison among the physiological traits of irrigated and nonirrigated seedlings from seven different provenances. Results revealed statistically significant differences in PWP, LRWC, RRWC, Fv/Fm, and ΦPSII values among nonirrigated seedlings from the seven Holm oak provenances. No differences were found, however, among well-irrigated controls (Supplementary Tables 2 and 3 in the Supporting Information). Xylem PWP values were −0.23 ± 0.04 MPa at day 0, with a statistically significant (p < 0.05) decrease to −0.42 ± 0.07 and −1.76 ± 0.31 MPa at days 14 and 28, respectively. In nonirrigated seedlings, SSA and PCO had the highest values (−1.5 MPa), while GSE (−2.4 MPa) showed the lowest value at day 28 (Figure 1A). A similar decrease, but with lower PWP values, was found in one of our previous works, in which just one provenance and a treatment period of up to 14 days was used.22,36 A similar trend was observed when determining RWC (Figure 1B,C). In nonirrigated plants, LRWC values decreased from 57.19 ± 2.45 at day 0, to 43.11 ± 2.78 at day 14, and to 35.29 ± 3.78 at day 28, showing statistically significant differences. At day 28, SSA presented the highest LRWC value (39.48 ± 0.58), while GSE presented the lowest value (28.61 ± 1.00). RRWC values were 68.70 ± 1.69 at day 0, decreasing to 62.59 ± 3.41 at day 14 and to 41.27 ± 5.98 at day 28. Nonirrigated SSA seedlings presented the highest value (46.67 ± 0.98), while GSE had the smallest value (33.89 ± 0.89) at day 28. Fluorescence, as an indirect estimation of the photosynthetic activity, was determined in dark adapted leaves (Figure 1D). The Fv/Fm values in nonirrigated seedlings were 0.77 ± 0.01 at 5113



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Figure 2. Representative 2-DE gel of leaf extracts from Quercus ilex subsp. ballota. Proteins were separated on 17 cm, pH 5−8 IPG strips (first dimension) and 13% SDS-PAGE (second dimension). On the left, the position of molecular-weight marker proteins is shown. Identified protein spots are numbered according to Table 2 and Supplementary Table 4 in the Supporting Information.

tool (ANOVA, hierarchical clustering and PCA). The ANOVA of the 235 consistent spots showed 13 spots with significant quantitative differences (common spots in the two treatments or provenances, but with differences in intensity: spots 16, 17, 25, 26, 28, 29, 30, 31, 32, 34, 35, 36, and 37), with a FDR < 0.05. The 28 protein spots showing both qualitative and significant quantitative differences were picked up and subjected to further MALDI-TOF/TOF analysis, and identified proteins from these variable spots are listed in Table 2. The hierarchical clustering analysis showed two clusters that separated the irrigated seedlings from the SSA and GSE populations (SSA IS and GSE IS, at day 0) from the nonirrigated seedlings (SSA NIS and GSE NIS, at day 28) (Figure 3A). A PCA was applied to obtain further information. The use of these components allowed the effective separation of irrigated and nonirrigated seedlings from both populations (Figure 3B). PC1 and PC2 justified 70.82 and 17.89% of total variance, respectively. In the PCA, the two populations were further spread in the control compared with drought conditions. The first major discrimination was the treatment. On the second axes of the PCA, however, GSE was further separated from SSA in the irrigation than under the nonirrigation conditions. These results were similar to those showed by hierarchical clustering analysis (Figure 3A), so at the

reason, these two seedlings were chosen to carry out the 2-DE analysis. Two-DE Protein Profile

Leaf protein maps of the two populations that showed the extreme physiological response to water deficit stress, SSA and GSE (the least and the most susceptible, respectively) were analyzed by 2-DE. The two provenances were compared according to protein yield and number and intensity of spots. No statistically significant differences were observed in the protein yield among treatments and provenances, being 3.0 ± 0.3 mg protein/g fresh weight. Two-DE experiments were performed in 17 cm gels by using 5−8 pH linear range strips (Supplementary Figure 2 in the Supporting Information). A representative 2-DE gel is presented in Figure 2, which shows the spots with significant statistical differences. In the 2-DE analysis, only consistent spots (i.e., detected in all three replicates) were considered. For each provenance, the number of consistent spots was similar (225 ± 15) (Supplementary Table 4 in the Supporting Information). The 2-DE analysis showed 15 spots with qualitative differences (presence vs absence, and spot intensity below the detection limit in at least one treatment or provenance: spots 1, 8, 9, 10, 14, 15, 18, 106, 124, 149, 195, 221, 232, 297, and 308). Statistical analyses were performed with the NIA array analysis 5114



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methionine (SAM) synthetase, and the other spots have not been identified yet. Relationships between different quantitative variable spots and PCs are shown in Table 1. Nine spots showed a high correlation (above |0.98|) with PC1, and four were identified after MALDI-TOF/TOF analysis as the oxygen-evolving enhancer protein 1 precursor (spot 8), the PSII oxygenevolving complex protein 2 (spot 9), and the β-1,3-glucanase (spot 10). Variability studies in Holm oak populations have been performed by our group using leaves, pollen, and acorns as starting material. By analyzing the 2-DE protein profile of leaf tissues, we could not discriminate among populations.36,51 This study, however, was justified because of the high dynamic and plastic leaf proteome, with differences in the proteome map depending on the leaf position, orientation, and sampling time.51 Because of that, we moved to organs such as acorns and pollen with a more stable proteome, so we managed to group and separate populations.30,31 In this study, 15 spots systematically discriminated treatments, and 13 had significant quantitative differences, thus confirming previous studies.22 Only two spots (297 and 149), however, systematically discriminated between well-irrigated SSA and GSE seedlings.

Figure 3. Associations between experimental samples and protein spots were generated by cluster analysis (A) and principal component analysis (B) in leaves transformed data from the provenances of SSA (Almerı ́a) and GSE (Seville). The PCA of samples (left graph) and protein spots (right graph) was plotted in the first two component spaces. A short distance between samples and protein spots in the component space is indicative of similarity between their expression profiles (SSA IS: irrigated seedling from the SSA population; SSA NIS: nonirrigated seedling from the SSA population; GSE IS: irrigated seedling from the GSE population; GSE NIS: nonirrigated seedling from the GSE population).

Protein Identification

Eighteen of the 28 variable spots (excised from gels and subjected to MALDI-TOF/TOF analysis) provided confident matches against the nrNCBI database (restricted to Viridiplantae taxonomy), corresponding to 17 protein species (Table 2, Figure 2). Theoretical molecular masses and pIs for most of the 18 matched proteins were similar to the experimental masses and pIs (Table 2 and Supplementary Data 1 in the Supporting Information). Nevertheless, we observed proteins with some deviations (e.g., spots 9, 10, 28, and 34 showed an apparent molecular mass lower than that corresponding to identified proteins). Some of the identified proteins were detected as multiple spots on 2-DE gels (e.g., spots 17, 26, 31, 32, 35, and 36). These variations in molecular masses and pIs, together with the detection of multiple spots for the same protein, have been reported in previous Holm oak studies.22,31,36 These deviations may derive from various factors, namely, protein isoforms, protein comigrations, protein degradation and partial synthesis of proteins, protein translation from alternatively

protein level, both populations may have a similar response to drought stress, with slight differences. Moreover, PCA supplied information on the importance of each protein implicated in the response to drought. The spots 1, 8, 9, 10, and 106 disappeared in both populations after water withholding. The first four spots correspond to peroxiredoxin, oxygen-evolving enhancer protein 1 precursor, PSII oxygen-evolving complex protein 2, and β-1,3-glucanase (Table 2), respectively. The opposite trend was observed in spots 14, 15, 18, 124, 221, 232, and 308, with spot 15 corresponding to an S-adenosyl-L-

Table 1. Correlations between Different Quantitative Variable Spots and PCsa

a

number

Log10Change

correlation

PCnumber

direction

GSE0d

GSE28d

SSA0d

SSA28d

1 8 9 10 106 29 31 35 18 124 221 232 308 195 149 297

8.162 13.78 12.63 12.99 13.25 0.58 0.63 0.68 −12.62 −12.63 −13.49 −12.41 −12.99 −7.75 13.32 13.2

0.7 0.98 0.98 0.98 0.98 0.7 0.88 0.79 −0.98 −0.98 −0.98 −0.98 −0.98 −0.7 0.82 0.82

1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2

positive positive positive positive positive positive positive positive negative negative negative negative negative negative positive positive

2.16 2.63 1.45 1.82 2.03 1.77 2.79 2.67 n.d. n.d. n.d. n.d. n.d. n.d. 1.95 1.85

n.d. n.d. n.d. n.d. n.d. 0.9 2.41 1.64 1.46 1.57 2.54 1.44 2.32 1.63 1.69 1.58

2.1 2.64 1.79 2.06 2.35 1.83 2.77 2.52 n.d. n.d. n.d. n.d. n.d. 1.44 n.d. n.d.

n.d. n.d. n.d. n.d. n.d. 1.62 1.99 2.32 1.68 1.59 2.22 1.34 1.51 1.39 n.d. n.d.

n.d.: nondetected spot. 5115


5116

28.7/5.27

45.0/5.6

carbon f ixation 30

34.5/5.39

8

29

23.5/6.04

photosynthesis 9

23.85/6.64

39.91/6.54

17

36

58.83/6.12

35

24.49/6.85

58.90/5.79

32

26

59.1/5.70

Mr/pI exp.c

Metabolism ATP synthesis 31

numberb

48.2/8.20

27.9/5.29

28.2/8.29

23.00/6.65

35.3/6.48

1.4/9.71

33.4/6.13

53.5/5.28

53.5/5.28

59.9/5.28

Mr/pI theor.d

Quercus rubra (gi|14718199)

Arabidopsis thaliana (gi| 5708095)

ATP synthase β subunit, chloroplast

ATP synthase γ chain, chloroplast precursor

Malus x domestica (gi|3914605)

Vigna radiata (gi|8954293)

LHCII type I chlorophyll a/b binding protein

ribulose bisphosphate carboxylase/oxygenase activase

Pisum sativum (gi|131390)

Pisum sativum (gi|131390)

Bruguiera gymnorhiza (gi| 119952178)

oxygen-evolving enhancer protein 2, chloroplastic

oxygen-evolving enhancer protein 2, chloroplastic

oxygen-evolving enhancer protein 1 precursor

Arabidopsis thaliana (gi| 1076373)

Quercus rubra (gi|14718199)

ATP synthase β subunit, chloroplast

photosystem II oxygen-evolving complex protein 2 (fragment)

Nicotiana plumbaginifolia (gi| 114421)

species (accession number)e

ATP synthase β subunit, mitochondrial

name

Table 2. List of Holm Oak Proteins Identified by Using 2-DE Combined with MALD-ITOF/TOF Analysisa

439/21/34/ K.FYWAPTR.E (28) R.IGVCIGIFR.S (44) K.FYWAPTREDR.I (33) K.LVDTFPGQSIDFFGALR.A (102)

97/1/92/ AYGEAANVFGKPK.T (84) 147/13/33/ K.RLTYDEIQSK.T (51) 142/8/26/ R.EFPGQVLR.Y (26) K.SITDYGSPEEFLSK.V (40) R.TADGDEGGKHQLITATVK.D (36) 149/8/25/ R.EFPGQVLR.Y (35) R.TADGDEGGKHQLITATVK.D (54) R.KFvEDTASSFSVA. (22) 81/7/23/ K.QVSSGSPWYGPDRVK.Y (50)

376/25/23/ K.VVDLLAPYQR.G (61) K.AHGGFSVFAGVGER.T (117) R.QISELGIYPAVDPLDSTSR.M (72) 848/45/67/ R.IAQIIGPVLDVTFPPR.K (77) R.DTAGQQINVTCEVQQLLGNNR.V (129) R.GMEVIDTGAPLSVPVGGATLGR.I (141) K.AHGGVSVFGGVGER.T (108) 544/40/54/ R.IAQIIGPVLDVTFPPR.K (62) R.GMEVIDTGAPLSVPVGGATLGR.I (79) R.SAPAFIQLDTK.L (36) K.VVDLLAPYRR.G (21) K.AHGGVSVFGGVGER.T (92) K.VALVYGQMNEPPGAR.M (33) K.VALVYGQMNEPPGAR.M Oxidation(M) (20) 186/7/19/ K.SEPVIHTLLPLSPK.G (88) R.ALQESLASELAAR.M (70)

protein score/peptide matched/sequence coverage/MS−MS ions (score)f

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5117

Elaeagnus umbellata (gi| 13540318)

S-adenosyl-L-methionine synthetase

Castanea sativa (gi|8980813)

2-cys peroxiredoxin-like protein β-1,3-glucanase

21.9/4.93 17.6/7.82

Hyacinthus orientalis (gi| 47027073)

peroxiredoxin

Phaseolus vulgaris (gi| 11558242)

Oryza sativa (gi|149390991)

Glycine max (gi|13937041)

glutamine synthetase β 2, cytosolic

2-cys peroxiredoxin bas1

Phaseolus vulgaris (gi|121353)

Helianthus annuus (gi| 121485004)

Solanum tuberosum (gi| 76573375)

species (accession number)e

glutamine synthetase leaf isozyme, chloroplastic

phosphoglycerate kinase, cytosolic

triosphosphate isomerase-like protein

name

28.7/5.17

15.4/5.13

43.5/5.50

9.0/8.31

47.5/6.77

42.3/5.82

27.9/5.90

Mr/pI theor.d

296/7/38/ K.SGGLGDLKYPLISDVTK.S (118) R.GLFIIDKEGVIQHSTINNLAIGR.S (134) 106/7/43/ R.GLFIIDKEGVIQHSTINNLAIGR.S (61) 99/5/4/ K.SYGVLIPDQGIALR.G (69) 82/6/41 R.ADYRPILDPVIR.F (41)

396/9/10/ K.AILNLSLR.H (41) R.HKEHISAYGEGNER.R (92) R.LTGKHETASINTFSWGVANR.G (144) K.HETASINTFSWGVANR.G (94) 278/6/72/ -.HKEHIAAYGEGNER.R (100) R.HETADINTFLWGVANR.G (135) 339/19/34/ R.TIGFvSDDVGLDADNCK.V (108) K.DGTCPWLRPDGK.T (53) R.FvIGGPHGDAGLTGR.K (77)

137/9/32/ K.VIACVGETLEQR.E (58) K.VATPAQAQEVHFELRK.W (43) 127/11/33/ R.VILSSHLGRPK.G (8) K.LASLADLYVNDAFGTAHR.A (53)

R.VPIIVTGNDFSTLYAPLIR.D (125)

protein score/peptide matched/sequence coverage/MS−MS ions (score)f

a Proteins are classified according their functional categories. bNumbers correspond to Figure 2 and Supplementary Table 4 in the Supporting Information. cMolecular weight (kDa) and pI calculated by using molecular weight standards, and analyzed using the PD-Quest Advanced software (version 8.01). dMolecular weight (kDa) and pI annotated in the NCBI database. eNCBI database accession numbers. fMascot score (S = n.d.*log(P)): where P is the probability that the observed match is a random event, peptide matched in MS analysis, percentage of sequence coverage (in brackets), and ions sequence matched (ion score in brackets) from MS/MS analysis.

37.02/6.79

10

46.38/5.68

15

23.0/5.19

41.71/6.0

34

1

43.71/6.01

amino acid metabolism 16

21.6/5.3

42.68/7.01

25

Defense/Stress-Related Proteins 28

30.59/7.39

Mr/pI exp.c

glycolysis 37

Metabolism

numberb

Table 2. continued

Journal of Proteome Research Article



Article

provenances22 and in a peanut tolerant genotype.53 On the other hand, an increase in OEE 1 was observed in natural Q. robur trees during the first three sampling in a seasonal longtime drought exposure and decreased in the last one until it was a similar level as the beginning of drought period.35 An increase in the PSII OEC 2 protein under drought stress has been observed, however, in other plant species.54−56 Proteins involved in carbon fixation have also been identified in the response to drought stress of Holm oak leaves. The RuBisCO activase was found to be less abundant in nonirrigated seedlings from the GSE population, with respect to SSA nonirrigated seedlings. These changes were statistically significant in respect to the provenance but not with regard to the treatment. In previous studies, the RuBisCO activase decreased both in drought36 and biotic52 stresses. A large number of enzymes and proteins involved in glycolysis have been reported to change in response to water deficit.35,36,56,57 Nevertheless, the direction of their expression was not always regular. In this study, a triosephosphate isomerase-like protein and a cytosolic phosphoglycerate kinase showed a trend to increase under drought stress. Recently, similar results have been observed in the expression of these proteins in the SSA Holm oak population in response to biotic stress.52 These results, however, contradict what was reported by Echevarrı ́a-Zomeño et al.22 in the same species (but from a different provenance) and by Sergeant et al.35 in Q. robur, where they found a reduction in the abundance of triosephosphate isomerase in response to drought. Previous poplar proteomic studies have reported genetic variations in drought-induced changes in proteins involved in carbon fixation (e.g., RuBisCO, RuBisCO activase), and glycolysis (e.g., glyceraldehyde-3-P dehydrogenase, phosphoglycerate kinase, or triosephosphate isomerase).57−59 When water deficit is prolonged or intense, the decrease in the RuBisCO activity and ribulose-1,5-bisphosphate regeneration capacity were the most relevant metabolic deficiencies, and they may be connected to shifts in leaf nitrogen content or allocation.60 Photosynthesis is one of the first processes that is altered by drought. The effects can be direct (i.e., carbon assimilation decreasing and alterations of photosynthetic metabolism) or secondary (i.e., oxidative stress). The side effects usually exist under multiple stress conditions and can critically alter leaf photosynthetic machinery. The drought effects on photosynthesis affect from the limitation on CO2 diffusion into the chloroplast (via restrictions on stomatal opening) to the changes in leaf photochemistry and carbon metabolism.61 The reduction in the photosynthetic rate may preserve the photosynthetic device against oxidative damage, or it may be the result of oxidative damage.62 Moreover, under biotic stress, photosynthesis must be repressed to initiate respiration and other processes essential for plant defense against pathogens.52,63 As a response to the consequent defect in photosynthetic activity, Holm oak seedlings might increase the presence of glycolytic proteins, such as the triosephosphate isomerase and the phosphoglycerate kinase. The presented proteomics results are in adequate agreement with the physiological parameters as well as with previously reported results for other plant species. No irrigation caused drought stress, as shown by a reduction in xylem water potential and relative water content. The photosynthetic rate diminished as a consequence of stomatal closure or structural and metabolic impairment, caused by the imbalance between light capture and utilization, which causes the overproduction

spliced mRNAs, or errors in the database sequence (partial protein sequence) due to post-translational modifications. Finally, two different protein species (peroxiredoxin and 2Cys peroxiredoxin related-protein) were presented in the spot 1, belonging to the same protein family and having similar molecular weights and pI values. Reliable identified proteins were grouped according to their biological functions (Table 2). Identified proteins were mostly chloroplastic, and they have been classified into two principal functional categories: metabolism (65%) and stress/defense proteins (15%). When comparing the protein spot abundance among samples, a reduction in protein abundance as a result of water stress among controls (irrigated seedlings) and treatments (nonirrigated seedlings) (∼50% of the identified proteins) was a general trend. Some of these identified proteins decreased in abundance and even disappeared under drought stress in both populations: oxygen-evolving enhancer protein (OEE) 1 precursor (spot 8), PSII oxygen-evolving complex protein 2 (spot 9), β-1,3-glucanase (spot 10), LHCII type I chlorophyll a/b (spot 29), ATP synthase β subunit (spots 32 and 35), OEE 2 (spot 36), and cytosolic glutamine synthetase β 2 (spot 34). The 2-Cys peroxiredoxin bas1 (spot 28) only decreased in the GSE provenance. On the contrary, others increased or even appeared under drought stress conditions in both populations: triosephosphate isomerase-like protein (spot 37), cytosolic phosphoglycerate kinase (spot 25), and SAM synthetase (spot 15). In this study, 6 out of the 17 variable proteins identified had also been detected in previous works on drought-exposed plants:22,35,36 chloroplastic ATP synthase γ chain, OEE 1 and 2, RuBisCO activase, triosephosphate isomerase-like, and cytosolic glutamine synthetase β2. Moreover, 5 of the 17 variable detected proteins were shown to have significant changes in Q. ilex seedling infected with P. cinamomi:52 chloroplastic ATP synthase β subunit, RuBisCO activase, triosephosphate isomerase-like, citosolic phosphoglycerate kinase, and cytosolic glutamine synthetase β2. Previous studies have differences, however, in genotypes and populations, plant developmental stages, drought time-course, and experimental setup (different protocols for protein extraction and separation), and we must add that these results are sometimes contradictory with respect to our results. Comments about the results published in previous works will be related below. When comparing the two provenances, we observed that proteins involved in ATP synthesis, such as the chloroplastic ATP synthase β subunit (spots 32 and 35), were less abundant in the GSE-stressed seedling (Table 2 and Supplementary Table in the Supporting Information). This suggests a smaller amount of energy for the cell to be used through the synthesis of ATP in this genotype. In Quercus spp., these proteins were also reported to decrease in response to water35 and biotic52 stresses. In other species, such as peanut genotypes, where an ATP synthase epsilon chain and an ATP synthase β subunit were highly induced only in tolerant peanut genotypes, this entails their putative role in tolerance to drought.53 In this work, we have also observed a decrease in photosynthesisrelated proteins (Table 2 and Supplementary Table 3 in the Supporting Information). The OEE 1 precursor and PSII oxygen-evolving complex (OEC) protein 2 showed a trend to disappear under drought conditions in both populations, while the OEE 2 only tends to disappear in GSE. On one hand, a decrease in both OEE 1 and 2 under water deficit stress has also been observed in Q. ilex seedlings from other Andalusian 5118



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Figure 4. Qualitative and quantitative significant variations in proteins identified by MALDI-TOF/TOF analysis from Holm oak populations in response to drought.

of reactive oxygen species.22,64 Thus, ATP synthase β subunit (spots 32 and 35), OEE 1 precursor (spot 8), PSII OEC 2 (spot 9), OEE 2 (spot 36), and LHCII type I chlorophyll a/b (spot 29) decreased in nonirrigated plants (Figure 4). Differences among the two studied provenances derive from the extent of photosynthesis inhibition, and this is related to xylem potential and water content values. The inhibition was lower in the least susceptible population (SSA) than in the most susceptible (GSE). Thus, the RuBisCO activase intensity spot was higher in the former than in the latter (Figure 4). An understanding of why SSA keeps higher potential and relative water content remains to be investigated. As previously discussed,22 opposite results of the drought stress effect on glycolytic enzymes are reported in the literature, with a rise in the amount of glycolytic enzymes, such as triosphosphate isomerase (spot 37) and phosphoglycerate kinase (spot 25). We should highlight that we have always found them in our experiments with drought Holm oak seedlings (Figure 4). Responses to drought were also observed in proteins related to oxidative stress. A rise in reactive oxygen species is expected as a consequence of the imbalance between light capture and utilization and generation and use of electrons as a result of PSII down activity.64 In general, an increase in antioxidant enzymes in response to drought stress is a quite common observation in other plant systems.53,58 Plant 2-Cys peroxiredoxins preserve photosynthetic membranes against photo-

oxidative damage in chloroplasts.65 In our case, the antioxidant system response has not been clearly observed. Thus, the 2-Cys peroxiredoxin bas1 (spot 28) showed a trend to decrease in drought-stressed seedlings from the GSE population. In previous reports, this protein species was not found.22,35,36 Nevertheless, a putative mitochondrial peroxiredoxin was found to appear in Holm oak seedlings after 7 days of drought stress22 and in wild Q. robur trees,35 where peroxiredoxin showed a trend to increase considerably in response to water withholding. Additionally, peroxiredoxin has increased in Holm oak in response to biotic stress.52 These differences in the database entries may be due to errors in the annotations. Furthermore, responses to drought were also observed in proteins involved in amino acid metabolism. Protein spots 16 and 34 were identified as a chloroplastic glutamine synthetase leaf isozyme and a cytosolic glutamine synthetase β 2, respectively. Glutamine synthetase has an important role in plant nitrogen assimilation. Molina-Rueda et al. (2013)66 have recently reported that hybrid poplar (Populus tremula x alba, INRA 717−1B4), expressing ectopically a pine cytosolic glutamine synthetase gene (GS1a), displayed enhanced tolerance to drought. In our system, chloroplastic and cytosolic isoforms (spots 16 and 34) decreased in abundance in nonirrigated seedlings from both provenances, as previously reported.22 This decrease might indicate a deficiency in the nitrogen assimilation for the formation of organic nitrogen 5119



Article

Figure 5. Scheme of the chloroplastic, cytoplasmic, and mitochondrial pathways of identified proteins in this work. Arrows indicate: ↓ and ↑, proteins that disappear and appear; bottom right facing arrow and top right facing arrow, down- and up-accumulated proteins in seedlings subjected to drought stress. Blue arrows indicate the pathway step affected by the drought stress. The population in which the identified protein is more or less abundant, or disappears on both, is also indicated. The spot number for each protein is indicated in brackets. PSI and II: photosystems I and II; ETC: electron transport chain; PSII OEC 2: PSII oxygen-evolving complex protein 2; OEE 1 and 2: oxygen-evolving enhancer proteins 1 and 2; LHCP: LHCII type I chlorophyll a/b-binding protein; RuBisCO activase: ribulose bisphosphate carboxylase/oxygenase activase; RuBP: ribulose 1,5biphosphate; 3-PGA: 3-phosphoglycerate; G3P: glyceraldehyde 3-phosphate; TPI: triosephosphate isomerase-like protein; PGK: phosphoglycerate kinase, cytosolic; Glc: glucose; DHAP: dihydroxyacetone phosphate; 1,3-BPG: 1,3-biphosphoglycerate; 3-PG: 3-biphosphoglycerate; Pyr: pyruvate; GS: glutamine synthetase leaf isozyme, chloroplastic ; GS β2: glutamine synthetase β 2, cytosolic; SAMS: S-adenosyl-L-methionine synthetase; 2-OG: 2-oxoglutarate; Glu: glutamate; Gln: glutamine; Met: methionine; AdoMet: S-adenosyl methionine; Prx: peroxiredoxin; 2-Cys Prx: 2-Cys peroxiredoxin bas1.

withholding in both GSE and SSA provenances. The most dramatic decrease was observed in the less tolerant seedling population than in the most tolerant one. However, a more comprehensive analysis, including more seedlings provenances, remains to be done in future studies for understanding the variability in the Q. ilex response to drought stress.

compounds like amino acids. This change differs from what is reported in Populus trichocarpa,57 where an increase in these enzymes after drought stress was observed. These differences may be related to the species or to the intensity of the stress. Finally, protein spot 15 was identified as the SAM synthetase. It was not detected in well-watered seedlings, so it appeared in drought ones with no differences between provenances. This enzyme is related to the biosynthesis of SAM, which is the major donor of methyl groups in the transmethylation of proteins, nucleic acids, polysaccharides, and fatty acids. Additionally, SAM works as a methyl group coenzyme of methyl transferases, some of them involved in the synthesis of stress-related metabolites, such as simple phenolics and lignins,67 polyamines,68 and osmolytes.69 All of these metabolic changes are summarized in Figure 5.

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ASSOCIATED CONTENT

S Supporting Information *

Variation on time of the water availability that was monitored during the whole experiment, using the total pot weight (TPW), the whole plant (substrate plus plant), and soil relative water content (SRWC). Real gels from leaves protein extracts of the two Holm oak provenances analyzed by 2-DE. Coordinates, altitude, mean annual precipitation, and mean maximum and minimum monthly temperatures corresponding to the geographical areas of the 10 Andalusia Holm oak populations used in this study. Temporal evolution of predawn xylem water potentials (PWP), maximum quantum efficiency of photosystem II (Fv/Fm), quantum yield of PSII electron transport (ΦPSII), leaf relative water content (LRWC), and root relative water content (RRWC) in Holm oak provenances under drought stress. Morphological and physiological variables of Andalusia Holm oak provenances after drought stress. Normalized and transformed relative volumes of 2-DE resolved spots. MASCOT search results and protein view data generated

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CONCLUSIONS At the physiological level, drought stress reduces the physiological water status and photosynthesis-related parameters in Holm oak seedlings. Seedlings from different provenances responded differently to drought, where the GSE seedlings were the most susceptible and the SSA seedlings were the least susceptible. At the protein level, both populations present a similar response to drought stress. A general reduction in protein abundance, especially in proteins related to ATP synthesis and photosynthesis, was observed upon water 5120



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for each spot identified by MALDI-TOF/TOF analysis from Holm oak provenances under drought stress. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: (0052) 688 1821, Ext. 1621. Fax: (0052) 688 1821, Ext. 1620. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

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REFERENCES

The MALDI-TOF/TOF-MS/MS analysis was carried out in the UCM-UPCM proteomics facilities, a member of Carlos III Networked Proteomics Platform, ProteoRed-ISCIII, and we are grateful to Lola Gutiérrez Blázquez for their technical support. Finally, we would like to thank Dr. Cristina Huertas for her proofreading of the text. José Valero Galván was recipient of an Alban Program fellowship (I06D00010MX). This work is part of three research projects funded by the Spanish Ministry of Science and Innovation, cofunded by the European Community (FEDER): CGL2011-30285-C02-02, AGL2002-00530, AGL2009-12243C02-02, and Life BioDehesa.

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Physiological and Proteomic Analyses of Drought Stress Response

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