Heat-Treatment-Responsive Proteins in Different ... - ACS Publications

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Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA) Palak Chaturvedi,† Hannes Doerfler,† Sridharan Jegadeesan,‡ Arindam Ghatak,†,§ Etan Pressman,‡ Maria Angeles Castillejo,† Stefanie Wienkoop,† Volker Egelhofer,† Nurit Firon,*,‡ and Wolfram Weckwerth*,† †

Department of Ecogenomics and Systems Biology, Faculty of Sciences, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria ‡ Department of Vegetable Research, Institute of Plant Sciences, The Volcani Centre, Agricultural Research Organization, Bet Dagan, 50250, Israel § School of Biotechnology and Bioinformatics, D.Y. Patil University, Sector 15, CBD Belapur, Navi Mumbai, Maharashtra 400614, India S Supporting Information *

ABSTRACT: Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC−MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperaturesensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC−MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed. KEYWORDS: tMAPA, Protmax, pollen development, heat treatment, tomato, proteotypic peptide, developmental priming, plant productivity, climate change

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INTRODUCTION In the past decade, shotgun proteomics has developed into one of the major technologies for high-throughput proteomics1,2 and is a key discipline for functional genomics and systems biology.3−5 A large problem for shotgun proteomics technology is the presence of protein isoforms with partially identical primary amino acid sequences.6−9 If these regions have even identical tryptic cleavage sites, they cannot be distinguished by shotgun proteomics. Thus, unambiguous identification of unique proteins is only guaranteed if so-called proteotypic peptides are matched.7,8,10−13 Recently, we developed a technique called mass accuracy precursor alignment (MAPA), which is able to extract and align all precursor ions from a typical high-mass-accuracy shotgun proteomics analysis from a multitude of samples.14,15 MAPA makes it possible to extract all precursor ions independent of the identification based on a genomic database and, thus, © 2015 American Chemical Society

also to identify, e.g., polymorphisms which are not included in the databases.14 The MAPA algorithm is freely available and can be downloaded.16 Recently we introduced a novel feature: if a list of precursor ions is known, they can be extracted from the same dataset by using a targeted MAPA (tMAPA) function.16 In the present study, we apply this tMAPA feature to extract all proteotypic peptides from a typical set of non-targeted shotgun proteomics analyses. First, a list of proteotypic peptides is predicted from the genome database, and second, this target list is uploaded to the MAPA software. Then, all LC−MS files are uploaded in mzXML format, and the proteotypic peptides are extracted and aligned in a data matrix. This process is very fast and can be applied to a large set of samples, as demonstrated by Received: December 6, 2014 Published: September 30, 2015 4463

DOI: 10.1021/pr501240n J. Proteome Res. 2015, 14, 4463−4471

Journal of Proteome Research

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Hoehenwarter et al.8,14 In the present study, we have used a dataset of protein analysis in post-meiotic and mature pollen grains isolated from plants exposed to either control or shortterm heat-treatment conditions to reveal heat-responsive protein candidates. Sexual reproduction in flowering plants is a very complex process; gametophytic development is especially highly sensitive to temperature fluctuations and other abiotic stresses such as drought, flooding, and salinity, which thus control agricultural efficiency and production. We applied proteomic analysis to investigate developmental processes during pollen development17 and to understand how plants rapidly adapt to fluctuating temperatures during their gametophytic developmental phase.18 Gametophytic development takes place in male stamen and female pistil.19 Male gametophyte (or pollen grain) development is a well-programmed process involving elementary cell-biological actions such as cell polarity, cell cycle, regulation of gene expression, and cell specification. This process can be divided into several distinct phases which lead to the formation of mature pollen. It takes place in the anther locules by the development of sporogenous tissue producing microsporocytes (pollen mother cells) that undergo meiosis followed by asymmetric mitotic division (PM I) to produce bicellular pollen grain, with the two cells being a larger vegetative cell and a smaller generative cell.20 This whole developmental process occurs in a very short time frame.18 Mature pollen is an autonomous, simplified gametophyte determined to disperse and reach female gametes for the fertilization process.21 Tomato (Solanum lycopersicum L.) is one of the most important food crops in the world, and it shows a highly negative response to extreme temperatures, which have pronounced adverse effects on its reproductive growth, resulting in nearly 70% of loss in tomato production worldwide.22,23 Nevertheless, heat treatment has various effects which also depend upon genotypes, for example, the effect of heat treatment on heattolerant and heat-sensitive tomato cultivars. Temperature stress most pronouncedly affects pollen development and mature pollen grain, thereby reducing viability in heat-sensitive cultivars.24 Recent proteomic studies on tomato, Arabidopsis, and rice revealed that mature pollen pre-synthesizes a large number of proteins which have pre-defined functions, such as cell wall metabolism, energy metabolism, signaling, transport, cytoskeleton formation, and others, for the successful progress of fertilization.17,25−29 In a recent study, we have revealed these processes by systematic proteomic analysis of pollen development and called this phenomenon “developmental priming”. Developmental priming was also recently observed in leaf development.30 These processes are not fully understood; however, there is a simultaneous up- and down-regulation of large numbers of genes/proteins under harsh environmental conditions.31 Therefore, it is necessary to acquire information about how these regulations are affected in pollen development under stress conditions. In the present study we employed a shotgun proteomics approach (GEL-LTQ-Orbitrap MS) to compare the proteome of different tomato pollen developmental stages, i.e., post-meiotic and mature, under control and heat-treatment conditions. The identified peptides were quantified by applying a novel tMAPA strategy considering only “proteotypic peptides”. Subsequent multivariate statistical procedures were applied to identify putative marker proteins for stress responses.

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EXPERIMENTAL PROCEDURE

Sampling and High-Temperature Treatment

Tomato cultivar Hazera 3017 (heat-sensitive; Hazera Genetics, Israel) plants were grown in controlled greenhouse conditions (26 ± 2/22 ± 2 °C day/night temperature). Heat treatment (38 °C for 1 h and recovery for 1 h) was applied to plants (Hazera 3017) grown in a separate greenhouse with the above control conditions. Harvesting of the flower buds of control and heat-treated plants was performed according to Chaturvedi et al. and Ischebeck et al.17,29 Flower buds were collected, anthers of individual buds were sampled, and pollen was separated from the anther tissues, controlled with light microscopy as previously described.17,29,32 Three independent biological replicates were used, each replicate comprised of pollen derived from at least 90 flower buds. For each sample, buds were collected from a different set of plants (20 plants per set), grown in the same greenhouse. Post-meiotic stage samples were harvested before anthesis (i.e., 3 days before anthesis (A-3), 2 days before anthesis (A-2), and 1 day before anthesis (A-1)) and pooled. Quantitative Proteome Analysis

The protein extraction and analysis procedure is detailed by Chaturvedi et al.17 For each sample, proteins were extracted from freeze-dried pollen pellets by grinding them for 2 min in a shaking mill using steel balls (∼2 mm diameter). The homogenized pollen sample was disaggregated into 200 μL of protein extraction buffer (100 mM Tris-HCl, pH 8.0; 5% SDS, 10% glycerol; 10 mM DTT; 1% plant protease inhibitor cocktail (P9599, Sigma, St. Louis, MO, USA)) and incubated for 5 min at room temperature, followed by incubation for 2.5 min at 95 °C and centrifugation at 21000g for 5 min at room temperature. The supernatant was carefully transferred into a new tube. A 200 μL portion of 1.4 M sucrose were added to the supernatant, and proteins were extracted twice with 200 μL of TE buffer-saturated phenol followed by counterextraction with 200 μL of 1.4 M sucrose and 200 μL of distilled water. Precipitation of proteins was carried out by adding 2.5 volumes of 0.1 M ammonium acetate in methanol to the combined phenol phases, followed by incubation for 16 h at −20 °C. After incubation, samples were centrifuged for 5 min at 5000g. The pellet was washed twice with 0.1 M ammonium acetate and once with acetone, and air-dried at room temperature. The pellet was re-dissolved in 6 M urea and 5% SDS. Protein concentration was determined by using the bicinchoninic acid assay. Pre-fractionation of protein was carried out by SDS-PAGE.33 Approximately 40 μg of total protein was loaded onto a gel and run up to 1.5 cm. Gels were fixed and stained with methanol: acetic acid:water:Coomassie brilliant blue R-250 (40:10:50:0.001). Gels were de-stained in methanol:water (40:60), and then each lane was divided into two fractions. Gel pieces were de-stained, equilibrated, and digested with trypsin according to Valledor and Weckwerth.33 Peptides were then desalted employing a Bond-Elute C-18 SPEC plate (Agilent Technologies, Santa Clara, CA, USA) and concentrated in a SpeedVac concentrator. Prior to mass spectrometric measurements, the tryptic peptide pellets were dissolved in 4% (v/v) acetonitrile and 0.1% (v/v) formic acid. Approximately 1.5 μg of digested peptides was injected onto a one-dimensional nanoflow LC−MS/MS system equipped with a pre-column (Eksigent, Redwood City, CA, USA). Peptides were eluted using an Ascentis column (Ascentis Express, peptide ES-C18 HPLC column, Supelco Analytical, 4464


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Journal of Proteome Research USA; dimension 15 cm × 100 μm, pore size 2.7 μm) during an 80 min gradient from 5% to 50% (v/v) acetonitrile, 0.1% (v/v) formic acid. MS analysis was performed on an Orbitrap LTQ XL mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) with a controlled flow rate of 500 nL/min. Specific tune settings for the MS were as follows: mass resolution for precursor ion analysis, 30 000; mass window for precursor ion, 1 Da; selection spray voltage, 1.8 kV; temperature of the heated transfer capillary, 180 °C. Each full MS scan was followed by 10 MS/MS scans, in which the 10 most abundant peptide molecular ions were dynamically selected, with a dynamic exclusion window set to 90 s. Ions with a +1 or unidentified charge state in the full MS were omitted from MS/MS analysis.

can be downloaded and installed from http://www.univie.ac.at/ mosys/software.html.35 For functional categorization of the identified proteins, we exploited the MapMan file Solanum lycopersicum (http://mapman.gabipd.org/web/guest/ mapmanstore). The Venn diagrams were produced using Venny (http://bioinfogp.cnb.csic.es/tools/venny/index.html).

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Targeted MAPA for Quantification and Subsequent Multivariate Statistical Analysis of Proteotypic Peptides in Typical Shotgun Proteomics Data

The workflow of the tMAPA strategy is shown in Figure 1. Extracted protein from pollen (see Experimental Procedure) was digested with trypsin, and peptides were analyzed using a nanoUPLC instrument coupled to an Orbitrap LTQ XL mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). All the raw files obtained from the pollen developmental stages (post-meiotic and mature) under control and heat-treatment samplings were searched with the SEQUEST algorithm of Proteome Discoverer version 1.3 (Thermo, Germany) as described by Valledor and Weckwerth.33 By applying NSAF normalization strategy, in total 1985 proteins were identified from the post-meiotic stage under control and heat-treatment conditions. In mature pollen 1920 proteins in total were identified under control and heat treatment (Supporting Information S1 and S2). Further, identification and comparison of potential heattreatment-related protein candidates was performed using the tMAPA strategy. A strategy was employed in which a target list of “proteotypic peptides” with their corresponding m/z ratio and retention time (RT) was prepared using the output file from proteome discoverer (File type: CSV format, Supporting Information S3 and S4). This precursor ion list was uploaded to ProtMax (a software based on the concept of MAPA14,16) independently for each developmental stage, i.e., post-meiotic and mature pollen stage, along with the raw files converted into mzXML format. The output matrix in excel-format consisted of accurately measured 6088 m/z ratios for post-meiotic stage and 6357 m/z ratios for mature pollen along with their corresponding RT and the scan-number which corresponded to the most intense MS signal from which an MS/MS event was triggered16 (Supporting Information S5 and S6). All the identified proteins, their respective peptide spectra, and detailed information are stored in the plant proteomics database PROMEX (http://promex.pph.univie.ac.at/promex/). Multivariate statistical analysis was performed using the statistical toolbox COVAIN.35 The data matrix generated by ProtMax was used for PCA according to Hoehenwarter et al.14 Further details of the basic principles of MAPAextraction of precursor ions from raw data and subsequent multivariate statistics to rank the precursor ion list according to their impact in sample separationcan be found in Hoehenwarter et al.14 After PCA, the highest positive and negative loadings from principal component 1 from the respective pollen developmental stage are considered as heat-treatment-responsive proteins. Further, ANOVA was performed to determine protein candidates with increased levels under heat-treatment conditions, represented by box plots using the statistical tool box COVAIN (see below, Functional Analysis of Heat-TreatmentResponsive Proteins in Pollen Development).

Peptide and Protein Identification

Raw data were searched with the SEQUEST algorithm present in Proteome Discoverer version 1.3 (Thermo, Germany) as described by Valledor and Weckwerth.33 In brief, identification confidence was set to a 5% false discovery rate (FDR), and the variable modifications were set to acetylation of N-terminus and oxidation of methionine, with a mass tolerance of 10 ppm for the parent ion and 0.8 Da for the fragment ion. The Tomato protein database was employed (Sol genomic network). Peptides were matched against these databases plus decoys, considering a significant hit when the peptide confidence was high, and an Xcorr threshold was established at 2 for +2 ions, 3 for +3 ions, etc. High thresholds were chosen to minimize false identifications. All the spectra of the identified proteins and their meta-information, such as spectral filtering, thresholds, and cell-specificity, are stored in the public plant proteomics database PROMEX (http://promex.pph.univie.ac.at/promex/). The identified proteins were quantitated on the basis of total ion count followed by a NSAF normalization strategy,34 ⎛ PSM ⎞ ⎟ NSAFk = ⎜ ⎝ L ⎠k

N

⎛ PSM ⎞ ⎟ L ⎠i

∑ ⎜⎝ i=1

RESULTS AND DISCUSSION

in which the total number of spectra counts for the matching peptides from protein k (PSM) was divided by the protein length (L), and then divided by the sum of PSM/L for all N proteins. Targeted Mass Accuracy Precursor Alignment (tMAPA) for Quantification of Proteotypic Peptides

The Xcalibur raw files were converted to mzXML format with MassMatrix MS Data File Conversion v3.9 (http://www. massmatrix.net/mm-cgi/downloads.py). A target list of the m/z ratios of all “proteotypic peptides” was prepared either from the full genome database or from the output file of Proteome Discoverer (File type: CSV format). These m/z ratios were cut to the second decimal and uploaded within the ProtMax program. Preferences and settings were chosen according to Egelhofer et al.16 with slight modifications. The main ProtMax settings were employed target list (method), intensity (quantification), and cut after 2 decimals. Accepted charge states included +2, +3, +4, and +5; “unite neighbors” option was active with intensity expected as 1% max peak. This program is a windows forms application in the Common Language Runtime (CLR) environment. It can be downloaded from http://www.univie. ac.at/mosys/software.html.16 Multivariate Statistical and Bioinformatic Data Analysis

Principal component analysis (PCA), box plots, and ANOVA were performed using the statistical toolbox COVAIN35 in Matlab. COVAIN is a graphical user interface application and 4465


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Figure 1. Targeted mass accuracy precursor alignment (tMAPA). Left, schematic representation of the approach for unbiased identification of protein marker based on proteotypic peptides analyzed by shotgun proteomics. Right, Venn diagrams based on proteomics data of control and heattreated pollen samples.

Comparison of tMAPA and NSAF

more than one proteotypic peptide (see Supporting Information S7 and S8 for complete details of proteotypic peptides). These 43 proteins are unambiguously identified by the tMAPA approach and further confirmed by matching to the total list of the 365 ambiguous protein identifications. Similarly, in mature pollen, 137 proteins were exclusively identified under heat-treatment conditions. Using tMAPA strategy, an overlapping 8 unique proteins were identified as potential heattreatment-responsive candidates with at least one or more than one proteotypic peptides (see Supporting Information S7 and S10 for complete details of proteotypic peptides, and Figure S1B).

Multivariate statistics was performed to reduce the dimensionality of the data and to rank m/z precursor masses extracted with ProtMax according to Hoehenwarter et al.7 Two hundred of the most significant positive and negative loadings from PC1 were then compared with the proteins identified with Proteome Discoverer, which is illustrated by Venn diagrams. Figure S1A shows the overlap of all the identified proteins in post-meiotic stage using the typical database search implemented in Proteome Discoverer with the highest ranking proteins which were identified with the tMAPA approach. There is a large number of identified proteins which are different between control and heat treatment. A total of 365 proteins were identified under heat treatment, but they represent protein groups instead of individual proteins because identical tryptic peptides in different protein isoforms cannot be distinguished.7 Because all non-proteotypic peptides are included in the analysis, ambiguous identification due to identical peptide sequences or repeated peptides due to highly homologous protein isoforms cannot be excluded.7 Furthermore, the quantification approach can be problematic because summing up of these nonproteotypic peptides in total abundance scores of a protein can also lead to ambiguous quantification. Using the tMAPA approach, only proteotypic peptides are extracted from the complex raw data. This strategy circumvents the problems of identification and quantification ambiguity as described above. In Figure S1A, tryptic peptide precursor ions, which were identified and quantified with tMAPA and showed a strong influence on the separation of control and heat-treatment samples in PCA, are compared with the total number of identified proteins. Fortythree unique proteins are identified as potential heat-treatmentresponsive candidates in post-meiotic stage with at least one or

Functional Analysis of Heat-Treatment-Responsive Proteins in Pollen Development

High-temperature stress can be fatal for pollen development, which in turn reduces the yield and quality of many food crops, including cereals, grain legumes, and vegetable crops like tomato.36 Tomato plants can grow in a wide range of climatic conditions, but their vegetative and reproductive growth can be severely affected at higher temperatures, reducing fruit yield. On the basis of the quantification approach using tMAPA, unique proteins were identified which potentially could define protein markers for heat treatment in the later developmental stages of pollen (i.e., post-meiotic and mature). In the following, we discuss only selected protein candidates identified and quantified by tMAPA, based on several proteotypic peptides. Furthermore, we also provide protein candidates with increased levels under heat treatment based on ANOVA analysis and box plots. PCA of the data matrix generated by ProtMax for postmeiotic stage (i.e., A-3, A-2, and A-1 before anthesis) clearly separates two conditions (control and heat treatment) by 4466


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Figure 2. (a) Principal component analysis of the post-meiotic stage proteome of pollen development under heat-treatment conditions (PM-C, control vs PM-H, heat treatment). (b) ANOVA of proteins under heat treatment in the post-meiotic stage of pollen development. A red line indicates the median.

the first principal component PC1 (43.76%), which explains the strongest variation (Supporting Information S8 and Figure 2a).

Positive loadings of PC1 represent proteins with higher abundances under heat-treatment conditions, whereas negative loadings depicted higher levels under control conditions. The 4467


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Figure 3. (a) Principal component analysis of the mature pollen proteome under heat-treatment conditions (M-C, control vs M-H, heat treatment). (b) ANOVA of proteins under mild heat treatment in mature pollen. A red line indicates the median.

protein with unknown function (Solyc02g066990), small heat shock proteins HSP 20 and HSP 22 (Solyc03g082420, Solyc08g078700), chaperone protein htpG (Solyc04g081570),

highest positive loadings include protein candidates like late embryogenesis abundant (LEA) protein (Solyc01g097960, Solyc02g085150), cold shock protein 1 (Solyc01g111300), 4468


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view the remaining identified heat-treatment candidates in postmeiotic stage of pollen development. PCA of the data matrix generated by ProtMax for mature pollen separates the two conditions (control and heat treatment) by the first principal component, PC1 (61.26%), which explains the strongest variation (Supporting Information S10 and Figure 3a). Positive loadings of PC1 represent proteins with higher abundances under heat-treatment conditions, whereas negative loadings depict higher levels under control conditions. In angiosperms, before anthesis, individual microspores undergoes mitosis to form bicellular pollen grains in case of tomato consisting of a large vegetative cell and a smaller generative cell. The two celled pollen grain further undergoes dehydration to form mature pollen grain.52 Proteins such as ATP synthase (Solyc11g039980), mitochondrial ATP synthase (Solyc00g009020), citrate synthase (Solyc01g073740), ATP-citrate lyase A-2 (Solyc05g005160), pyruvate dehydrogenase E1 component subunit β (Solyc06g072580), and UTP-glucose 1 phosphate uridylyltransferase (Solyc05g054060) showed increased levels under heat-treatment conditions (Supporting Information S10). These proteins are majorly involved in the glycolysis and tricarboxylic acid (TCA) cycle. As pollen germination and tuber growth are energy-driven processes, many of these proteins are pre-synthesised in advance in the mature pollen of tomato. We demonstrated this recently in a study on the pollen developmental proteome.17 We called this phenomenon “developmental priming”. The majority of proteins identified in mature pollen play an important role in the process of pollen germination and tube growth; hence, it can be concluded that, under mild heattreatment conditions, the process of rapid tuber growth is ensured to determine the fate of maturing pollen to deliver the sperm gametes. However, mild-temperature stress can also be linked to an accelerated plant cycle, leading to the acclimatization for the higher-temperature stresses. In the present analysis, many proteins involved in the translational activity were also identified, such as cytochrome b5 (Solyc03g082600), 60S ribosomal protein L22-2 (Solyc01g099830), and eukaryotic translation initiation factor 3 subunit B (Solyc01g098000) (Supporting Information S10). Further we have identified LEA protein (Solyc01g097960, Solyc09g061960), thioredoxin/protein disulfide isomerase (Solyc01g100320), and dehydration-responsive protein (Solyc01g091640), which also provide protective mechanisms under mild heat-treatment conditions. Figure 3b represents the box plots of heat-treatment-responsive candidates determined by ANOVA (Supporting Information S11).

ribonuclease P protein subunit p25 (Solyc09g091590), and nuclear movement protein nudc (Solyc09g092210) (Supporting Information S8). The post-meiotic stage in pollen development is referred to as the microspore and polarized microspore stage. In the loadings we have identified several m/z ratios of proteotypic peptides which belong to a LEA protein. LEA protein is an important heat-treatment marker which takes part in the stress defense mechanism by protecting the proper folding and conformation of both structural and functional proteins.37 Expression of this protein is assumed to be linked with desiccation tolerance in seed, pollen, and anhydrobiotic plants.38 Under desiccating conditions like heat and drought, this protein provides protection to the enzyme citrate synthase and prevents protein aggregation.39 LEA proteins were identified in the embryogenesis of cotton seeds and maturation of Arabidopsis seeds.40,41 Over-expression of HVA1, group 3 of LEA proteins from barley (Hordeum vulgare L.), conferred dehydration tolerance in transgenic rice plant.42 LEA proteins are expressed in all the developmental stages with different expression levels and no tissue specificity. Examples are Em, RAB21, and dehydrins in seeds which can be also observed in the root, stem, leaf callus, and suspension cultures. Further, several studies that have explored the proteome profile of pollen cells demonstrated that mature pollen grains and seeds of Arabidopsis have the same set of major proteins, for example, high levels of LEA proteins and chaperones.43,44 Under control conditions, LEA proteins were also identified in the mature pollen of tomato and Arabidopsis.45,46 Interestingly, we also observed small heat shock proteins (HSP 20 and HSP 22) which might protect microspore and polarized microspore stages under heat-treatment conditions. Expression of low- and high-molecular-weight HSPs have been widely reported in a number of plant species. These proteins show organelle- and tissue-specific expression and act like chaperones which provide protection to the folding and unfolding process of cellular proteins. They are also involved in the transport of cellular proteins which is important for the cell survival.47 Certain HSPs are expressed in cyclic or developmentally controlled processes,48 e.g., in certain stages of development like embryogenesis, germination, pollen development, and fruit maturation.49 In the study performed by Chaturvedi et al.,17 HSPs 20, 22, and 70 were identified in pollen mother cells (microsporocyte) of tomato under control conditions. These proteins also showed high levels in the transcriptomic analysis of developing microspore in tomato.50 Low-molecular-weight HSPs also play roles in maintaining the cell membrane integrity. Hence, it can be concluded that, under heat treatment, translation of these LMW-HSPs in microspore and polarized microspore stages is crucial, as these stages play very important roles in the developmental process, especially due to the vacuole biogenesis leading to the extreme polarization of the microspore nucleus against the microspore wall. This polarization may provide a signal for the entry into highly asymmetric cell division at pollen mitosis I (PM I). This cell division is crucial for the progress of pollen development. Chaperone protein htpG was also identified which might protect the process of development under heat-treatment conditions. We also identified ribonuclease P protein subunit p25 as heat-responsive protein. In a transcriptomic study, this protein was shown to be involved also in pollen germination and tube growth.51 The above-discussed heat-responsive protein candidates were also obtained by ANOVA, represented by the box plots in Figure 2b. The reader is referred to Supporting Information S9 to

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CONCLUSION In this study, we present a convenient approach to perform quantification of proteins/peptides using targeted MAPA considering a target list of “proteotypic peptides” to avoid the confusion resulting from ambiguous tryptic peptide identification and quantification in protein isoforms. Application of this method to heat treatment of pollen during development led to the identification of 51 unique proteins potentially involved in heat defense mechanisms. Increased levels of heat-responsive proteins might hint to processes of acquired thermotolerance, and these processes will be investigated in future studies. Our observation is that mild heat treatment does not impair mature pollen for undertaking the process of germination but rather leads to rapid acclimatization responses to prepare the pollen for harsh conditions. Altogether, this approach provides a first 4469


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reference set of protein candidates based on proteotypic peptide quantification from post-meiotic and mature pollen under mild heat-treatment conditions in tomato. Peptide spectra of the identified proteins and their detailed information can be reviewed online in the plant proteomics database PROMEX (http://promex.pph.univie.ac.at/promex/). Future studies will focus on determining the proteome of very early stages of pollen development under heat-treatment conditions.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/pr501240n. Detailed summary of the contents of each file (PDF) Figure S1: Venn diagrams comparing the proteotypic peptides PCA-ranked by the tMAPA approach with the identified proteins (A) in control and heat-treatment samples of post-meiotic stage and (B) in control and heat-treatment samples of mature pollen (PDF) S1: protein quantification by NSAF from post-meiotic stage (XLSX) S2: protein quantification by NSAF from mature pollen (XLSX) S3: identified proteotypic peptides from post-meiotic stage (XLSX) S4: identified proteotypic peptides from mature pollen (XLSX) S5: ProtMax Output of post-meiotic stage (XLSX) S6: ProtMax Output of mature pollen (XLSX) S7: putative heat-responsive candidates with one or more proteotypic peptides (XLSX) S8: PCA loadings of post-meiotic stage in control and heat-treatment conditions (XLSX) S9: putative heat-responsive candidates by Anova analysis of post-meiotic stage (XLSX) S10: PCA loadings of mature pollen in control and heattreatment conditions (XLSX) S11: putative heat-responsive candidates by Anova analysis of mature pollen (XLSX)

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AUTHOR INFORMATION

Corresponding Authors

*N.F., E-mail: vcfi[email protected]. * W.W., E-mail: [email protected]. Phone: +43-1-4277-76550. Fax: + 43-1-4277-9 577. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank the whole SPOT-ITN consortium (http://spot-itn. eu/) for great discussions and strong support. We thank the European Commission for the financial support of P.C. and S.J., who are funded by the European Marie-Curie International training network “Solanaceae pollen thermotolerance SPOTITN”, grant agreement no. 289220. We thank the Austrian Science Fond FWF for support of H.D., project no. I 2071.

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REFERENCES

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