Heat-Treatment-Responsive Proteins in Different Developmental

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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, Ma Ángeles Castillejo, Stefanie Wienkoop, Volker Egelhofer, Nurit Firon, and Wolfram Weckwerth J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/pr501240n • Publication Date (Web): 30 Sep 2015 Downloaded from http://pubs.acs.org on October 18, 2015

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Journal of Proteome Research

Heat treatment responsive proteins in different developmental stages of tomato pollen detected by targeted mass accuracy precursor alignment (tMAPA) Palak Chaturvedi1, Hannes Doerfler1, Sridharan Jegadeesan2, Arindam Ghatak3,1, Etan Pressman2, Mª Angeles Castillejo1,Stefanie Wienkoop1, Volker Egelhofer1, Nurit Firon2,* and Wolfram Weckwerth1,* 1

Department of Ecogenomics and Systems Biology, Faculty of Sciences, University of Vienna, Althanstrasse 14, A-1090, Vienna, Austria 2

Department of Vegetable Research, Institute of Plant Sciences, Agricultural Research Organization, The Volcani Centre, Bet Dagan, 50250, Israel 3

School of Biotechnology and Bioinformatics, D.Y. Patil University, Sector No-15, CBD, Belapur, Navi Mumbai, India

*Corresponding Authors Wolfram Weckwerth : [email protected] mobile: Phone: fax:

+ 43- (0)- 664-60277 76550 + 43-1-4277-76550 + 43-1-4277-9 577

Nurit Firon: [email protected]

1 ACS Paragon Plus Environment


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Abstract Recently, we have developed a quantitative shotgun proteomics strategy called MAPA (mass accuracy precursor alignment). The MAPA algorithm uses high mass accuracy to bin mass-tocharge-ratios (m/z) of precursor ions from LC-MS analyses, determine their intensities and to extract a quantitative sample versus m/z-ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm by allowing 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 undistinguishable 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 temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role for 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 which present heat treatment responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.

Keywords: MAPA, tMAPA, Protmax, pollen, pollen development, heat treatment, tomato, proteotypic peptide, developmental priming, plant productivity, climate change.


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Introduction In the last 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 biology3-5. A large problem for shotgun proteomics technology is the presence of protein isoforms with partially identical primary amino acid sequences6-9. 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 MAPA (mass accuracy precursor alignment) 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 allows to

extract all precursor ions independent on the identification based on a genomic database and, thus, can also identify e.g. polymorphisms which are not part of 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 function 16. In the present study we apply this targeted MAPA (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 secondly 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 in Hoehenwarter et al8, 14. In the present study, we have used a dataset of protein analysis in post



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meiotic and mature pollen grains isolated from plants exposed to either control or short-term heat treatment conditions to reveal heat responsive protein candidates. Sexual reproduction in flowering plants is a very complex process and especially gametophytic development is highly sensitive to temperature fluctuations and other abiotic stresses such as drought, flooding and salinity, thus, controlling agricultural efficiency and production. We applied proteomic analysis to investigate developmental processes during pollen development 17

and to understand how plants rapidly adapt to the 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 including 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) undergoing meiosis followed by asymmetric mitotic division (PM I) to produce bicellular pollen grain with two cells, a larger vegetative cell and smaller generative cell developmental process occurs in a very short frame of time

18

20

. This whole

. 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 highly negative response to extreme temperature having pronounced adverse effects on its reproductive growth, which results into nearly 70% of loss in tomato production worldwide


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22, 23

. Nevertheless, heat treatment has various effects which also depends upon genotypes, for

example effect of heat treatment on heat-tolerant 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 presynthesizes a large number of proteins which have predefined 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 by Chaturvedi et al. 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 like post meiotic and mature under control and heat treatment conditions. The quantification of the identified peptides was performed by applying a novel targeted mass accuracy precursor alignment (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 the controlled greenhouse condition (26/22°C ± 2°C day/night temperature). Heat treatment (38°C for 1 hour and the recovery for 1 hour) was applied to plants (Hazera 3017) grown in a separate green house 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 and anthers of individual buds were sampled and pollen

was separated from the anther tissues and 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 was harvested before anthesis (i.e. three days before anthesis (A-3), two days before anthesis (A-2) and one day before anthesis (A-1)) and pooled.

Quantitative proteome analysis 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 (Sigma, St. Louis, MO, USA - P9599)) and incubated for


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5 min at room temperature followed by incubation for 2.5 min at 95°C and centrifugation at 21,000 x g for 5 min at room temperature. The supernatant was carefully transferred into a new tube. Two hundred µl of 1.4 M sucrose were added to the supernatant and proteins were extracted twice with 200 µl TE buffer-saturated phenol followed by counter extraction with 200 µl of 1.4 M sucrose and 200 µl 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 16h at -20°C. After incubation, samples were centrifuged for 5 min at 5000 x g. The pellet was washed twice with 0.1 M ammonium acetate, once with acetone, and air dried at room temperature. The pellet was re-dissolved in 6 M Urea and 5% SDS. Concentration of protein 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 were loaded onto a gel and run up to 1.5 cm. Gels were fixed and stained with in methanol: acetic acid: water: coomassie brilliant blue R-250 (40:10:50:0.001). Gels were destained in methanol: water (40:60) and then each lane was divided into two fractions. Gel pieces were destained, equilibrated and digested with trypsin according to Valledor & Weckwerth

33

. Peptides were then desalted employing Bond - Elute C-18 SPEC plate (Agilent

Technologies, Santa Clara, CA, USA) and concentrated in speedvac. Prior to mass spectrometric measurement, the tryptic peptide pellets were dissolved in 4% (v/v) acetonitrile and 0.1% (v/v) formic acid. Approximately 1.5µg of digested peptides were injected onto a one-dimensional (1D) nano-flow 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, USA), dimension 15 cm x 100 µm, pore size 2.7 µm)) during an 80 7 ACS Paragon Plus Environment


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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 per minute. Specific tune settings for the MS were as follows: mass resolution for precursor ion analysis: 30.000; mass window for precursor ion 1Da, selection spray voltage was set to 1.8 kV; the temperature of the heated transfer capillary was set to 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.

Peptide and Protein Identification Raw data were searched with the SEQUEST algorithm present in Proteome Discoverer version 1.3 (Thermo, Germany) as described in Valledor & 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 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 metainformation such as spectral filtering, thresholds, cell-specificity are stored in the public plant proteomics databases PROMEX (http://promex.pph.univie.ac.at/promex/).


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The identified proteins were quantitated based on total ion count followed by a NSAF normalization strategy 34.

=

∑

In which the total number of spectra counts for the matching peptides from protein k (PSM) were divided by the protein length (L), 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/zratios 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., 2013

16

, with slight modifications. The main employed

ProtMax settings were: target list (method), intensity (quantification), cut after 2 decimals. Accepted charge states included +2, +3, +4, +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.

http://www.univie.ac.at/mosys/software.html

16

It

can

be

downloaded

from

. 9

ACS Paragon Plus Environment


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Multivariate statistical and bioinformatic data analysis Principal component analysis (PCA), box plots and ANOVA were performed using the statistical tool box COVAIN

35

in Matlab. COVAIN is graphical user interface application and 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 diagram was produced by Venny (http://bioinfogp.cnb.csic.es/tools/venny/index.html).


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Results and Discussion Targeted MAPA for the quantification and subsequent multivariate statistical analysis of proteotypic peptides in typical shotgun proteomics data The workflow of the targeted MAPA 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 condition. 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 heat treatment related protein candidates was performed using the targeted MAPA strategy (tMAPA). 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 MAPA

14, 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 11 ACS Paragon Plus Environment


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6357 m/z ratios for mature pollen along with their corresponding retention times (Rt) and the scan-number which corresponded to the most intense MS signal from which an MS/MS event was triggered 16 (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 principal component analysis (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. 2008 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 treatment responsive proteins in pollen development).

Comparison of targeted MAPA and NSAF 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 a Venn diagram ( figure S 12 ACS Paragon Plus Environment

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1 A and S 1 B). Figure S 1 A 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 targeted MAPA approach. There is a large number of identified proteins which are different between control and heat treatment. Three hundred sixty five 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. By including all non-proteotypic peptides 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 non-proteotypic peptides in total abundance scores of a protein can also lead to ambiguous quantification. Using the targeted MAPA 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 S 1 A , tryptic peptide precursor ions which were identified and quantified with targeted MAPA 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. Forty three unique proteins are identified as potential heat treatment responsive candidates in post meiotic stage with at least one or 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 targeted MAPA 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 condition. Using targeted MAPA strategy an overlap of 8



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unique proteins were identified as potential heat treatment responsive candidates with at least one or more than one proteotypic peptides (See Supporting information S7 and S10, complete details of proteotypic peptides ; figure S 1 B).

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. Based on the quantification approach using targeted MAPA (tMAPA), unique proteins were identified which potentially could define protein marker 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. Principal component analysis (PCA) of the data matrix generated by ProtMax for post meiotic stage (i.e. A-3, A-2, A-1 before anthesis) clearly separates two condition (control and heat treatment) by the first principal component PC1 (43.76%) which explains the strongest variation (Supporting information S8, Figure 2A).


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Positive loadings of PC1 represent proteins with higher abundances under heat treatment condition, whereas negative loadings depicted higher levels under control condition. The highest positive loadings include protein candidates like late embryogenesis abundant protein (LEA) (Solyc01g097960, Solyc02g085150), Cold shock protein 1 (Solyc01g111300), Protein with unknown function (Solyc02g066990), small heat shock protein (HSP 20 and 22) (Solyc03g082420, Solyc08g078700), chaperone protein htpG (Solyc04g081570), 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 microspore and polarized microspore stage. In the loadings we have identified several m/z ratios of proteotypic peptides which belong to a late embryogenesis abundant protein (LEA). LEA is an important heat treatment marker which takes part in stress defense mechanism, by protecting proper folding and conformation of both structural and functional proteins37. Expression of this protein is assumed to link with desiccation tolerance in seed, pollen and anhydrobiotic plants38. Under desiccating conditions like heat and drought, this protein provides protection to the enzyme citrate synthase and prevents protein aggregation39. LEA proteins were identified in the embryogenesis of cotton seeds and maturation of Arabidopsis seeds40, 41. Over-expression of HVA1, group 3 of LEA proteins from barely (Hordeum vulgare L.) conferred dehydration tolerance in transgenic rice plant42. 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



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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 condition LEA proteins were also identified in the mature pollen of tomato and Arabidopsis 45, 46. Interestingly, we also observed several 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 control 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, heat shock protein 20, 22 and HSP 70 (HSP 20, HSp 22) were identified in pollen mother cells (microsporocyte) of tomato under control condition. These proteins also showed high levels in the transcriptomic analysis of developing microspore in tomato50. 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 stage is crucial, as these stages play very important role 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 16 ACS Paragon Plus Environment

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mitosis I (PMI). This cell division (PMI) is crucial for the progress of pollen development. Chaperone protein htpG was also identified which might protect the process of development under heat treatment condition. We also identified ribonuclease P protein subunit p25 as heatresponsive 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. However, the reader is also referred to Supporting information S9 to view the remaining identified heat treatment candidates in post meiotic stage of pollen development. The principal component analysis (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, Figure 3A). Positive loadings of PC1 represents proteins with higher abundances under heat treatment condition, whereas negative loadings depicted higher levels under control condition. 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 beta (Solyc06g072580), UTP-glucose 1 phosphate uridylyltransferase (Solyc05g054060) showed increased levels under heat treatment conditions (Supporting information S10). These proteins are majorly involved in glycolysis and



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TCA cycle. As the pollen germination and tuber growth is an energy driven process, many of these proteins are presynthesised 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 heat treatment condition 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), eukaryotic translation initiation factor 3 subunit B (Solyc01g098000). (Supporting information S10). Further

we

have

identified

late

embryogenesis

protein

(LEA)

(Solyc01g097960,

Solyc09g061960), Thioredoxin/protein disulfide isomerase (Solyc01g100320) and dehydration responsive protein (Solyc01g091640) which also provide protective mechanism under mild heat treatment condition. Figure 3B represents the box plots of heat treatment responsive candidates determined by ANOVA (Supporting information S11).


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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 with ambiguous tryptic peptide identification and quantification in protein isoforms. The 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 reference set of protein candidates based on proteotypic peptide quantification from post meiotic and mature pollen under mild heat treatment condition 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.

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 Palak Chaturvedi and Sridharan Jegadeesan who are funded by the European Marie-Curie International training 19 ACS Paragon Plus Environment


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Page 20 of 34

network “Solanaceae pollen thermotolerance SPOT-ITN”, grant agreement number 289220. We thank the Austrian Science Fond FWF for support of Hannes Doerfler, project number I 2071. Financial source: Palak Chaturvedi and Sridharan Jegadeesan are supported by the European Marie-Curie International training network “Solanaceae pollen thermotolerance SPOT-ITN”, grant agreement number 289220. Hannes Doefler is supported by the Austrian Science Fund (FWF) with the project number I 2071.

Supporting information Figure S1 A Venn diagram, comparing the PCA-ranked proteotypic peptides by the targeted MAPA approach with the identified proteins in control and heat treatment samples of post meiotic stage. The comparison identifies 43 proteins which are heat treatment responsive candidates with one or more proteotypic peptides. Figure S1 B Venn diagram, comparing the PCA-ranked proteotypic peptides by the targeted MAPA approach with the identified proteins in control and heat treatment mature pollen. The comparison identifies 8 proteins which are heat treatment responsive candidates with one or more proteotypic peptides. Supporting information S1: Details of pollen analysis, protein quantification by NSAF from post meiotic stage Supporting information S2: Details of pollen analysis, protein quantification by NSAF from mature pollen Supporting information S3: Details of identified proteotypic peptides from post meiotic stage Supporting information S4: Details of identified proteotypic peptides from mature pollen Supporting information S5: ProtMax Output of post meiotic stage Supporting information S6: ProtMax Output of mature pollen


Page 21 of 34

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Supporting information S7: Putative heat treatment responsive candidates with at least one or more proteotypic peptides: NSAF vs. tMAPA Supporting information S8: PCA Loadings of post meiotic in control and heat treatment condition Supporting information S9: Potential putative heat responsive candidates by Anova analysis of post meiotic stage Supporting information S10: PCA Loadings of mature pollen in control and heat treatment condition Supporting information S11: Potential putative heat responsive candidates by Anova analysis of mature pollen



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Page 22 of 34

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Page 28 of 34

FIGURE LEGENDS Figure 1. Targeted MAPA (tMAPA): Schematic representation of the approach for unbiased identification of protein marker based on proteotypic peptides analysed by shotgun proteomics. On the right Venn diagrams are shown based on proteomics data of control and heat treated pollen samples. Figure 2A. Principal component analysis of the post meiotic stage proteome of pollen development under heat treatment conditions (PM-C: Control vs. PM-H: Heat treatment). Figure 2B. ANOVA of proteins under heat treatment in post meiotic stage of pollen development. A red line indicates the median. Figure 3A. Principal component analysis of the mature pollen proteome under heat treatment conditions (M-C: Control vs. M-H: Heat treatment). Figure 3B. ANOVA of proteins under mild heat treatment in mature pollen. A red line indicates the median.


Page 29 of 34

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Quantification Methodology

Comparing the PCA‐ranked proteotypic peptides with the identified proteins by Sequest Algorithm Post meiotic control NSAF

Post meiotic heat stress NSAF

PC1 Loadings Mature control NSAF

Figure 1


Mature heat stress NSAF

PC1 Loadings


25 20 15 10

PC 2 (25.46%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 30 of 34

5 0 -5 -10 -15

PM-C

-20

PM-HS -25 -40

-30

-20

-10

0

PC 1 (43.76%)

Figure 2A


10

20

30

Page 31 of 34

Heat shock protein 22

Late embryogenesis abundant protein

6.5

7.6

6 7.4

5

Levels

Levels

5.5

4.5

7.2 7

4 6.8

3.5 3

PM-C

Conditions

6.6

PM-HS

PM-C

Conditions

PM-HS

Ascorbate peroxidase

Universal stress protein 8.7

7.3 7.2

8.6

7.1 8.5

Levels

7 Levels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


6.9 6.8

8.4

8.3

6.7 6.6

8.2

6.5 8.1

PM-C

Figure 2B

Conditions

PM-HS

PM-C


Conditions

PM-HS


15 10 5 0

PC 2 (15.30%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 32 of 34

-5 -10 -15 -20 -25 -30 -35 -70

M-C M-HS -60

-50

-40

-30

-20

-10

PC 1(61.26%) Figure 3A


0

10

20

30

Page 33 of 34

Calcium-dependent protein kinase 17

Dehydration-responsive family protein 5.6 6.4

5.5 6.2

Levels

Levels

5.4 5.3 5.2

6 5.8 5.6

5.1

5.4

5 M-C

Conditions

M-HS

M-C

Conditions

M-HS

Cellulose synthase-like protein

Citrate synthase 6.8

5.5

6.6

5.4

6.4

Levels

5.3

Levels

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


5.2

6.2 6 5.8

5.1

5.6

5

5.4

4.9

5.2

M-C

Figure 3B

Conditions

M-HS

M-C


Conditions

M-HS

Quantification Methodology

Page 34 of 34 Outcome of Quantification Strategy

25

15

20

10

15

5

10

0

PC 2 (15.30%)

PC 2 (25.46%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42


5 0 -5

-5

-10

-15

-10

-20

-15

-25

PM-C

-20

-30

PM-HS -25 -40

-30

-20

-10

0

10

20

PC 1 (43.76%)

Principal component analysis of Post meiotic Stage (Control vs. Heat stress)

30

M-C M-HS

-35 -70

-60

-50

-40

-30

Comparing ACS Paragon Plus Environment

For TOC only

-10

0

10

20

30

Principal component analysis of mature pollen (Control vs. Heat stress)

Post Meiotic Post Meiotic Mature Control Control - NSAF Heat Stress - NSAF NSAF

PC1 Loadings

-20

PC 1(61.26%)

Mature Heat Stress - NSAF

PC1 Loadings

the PCA-ranked proteotypic peptides with the identified proteins by Sequest Algorithm

Heat-Treatment-Responsive Proteins in Different Developmental

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