Article pubs.acs.org/jpr
Phosphoproteomic Analysis Provides Novel Insights into Stress Responses in Phaeodactylum tricornutum, a Model Diatom Zhuo Chen,†,∥ Ming-kun Yang,‡,∥ Chong-yang Li,‡ Yan Wang,‡ Jia Zhang,‡ Dian-bing Wang,§ Xian-en Zhang,*,†,§ and Feng Ge*,‡ †
State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China Key Laboratory of Algal Biology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China § State Key Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China ‡
S Supporting Information *
ABSTRACT: Protein phosphorylation on serine, threonine, and tyrosine (Ser/ Thr/Tyr) is well established as a key regulatory posttranslational modification used in signal transduction to control cell growth, proliferation, and stress responses. However, little is known about its extent and function in diatoms. Phaeodactylum tricornutum is a unicellular marine diatom that has been used as a model organism for research on diatom molecular biology. Although more than 1000 protein kinases and phosphatases with specificity for Ser/Thr/Tyr residues have been predicted in P. tricornutum, no phosphorylation event has so far been revealed by classical biochemical approaches. Here, we performed a global phosphoproteomic analysis combining protein/peptide fractionation, TiO2 enrichment, and LC−MS/MS analyses. In total, we identified 264 unique phosphopeptides, including 434 in vivo phosphorylated sites on 245 phosphoproteins. The phosphorylated proteins were implicated in the regulation of diverse biological processes, including signaling, metabolic pathways, and stress responses. Six identified phosphoproteins were further validated by Western blotting using phospho-specific antibodies. The functions of these proteins are discussed in the context of signal transduction networks in P. tricornutum. Our results advance the current understanding of diatom biology and will be useful for elucidating the phosphor-relay signaling networks in this model diatom. KEYWORDS: diatom, Phaeodactylum tricornutum, phosphoproteomics, stress responses
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INTRODUCTION Diatoms are a highly diverse group of eukaryotic, unicellular, photosynthetic secondary endosymbionts. They are believed to be responsible for up to 40% of marine and 20% of total global primary production annually.1,2 These photosynthetic workhorses occupy diverse habitats, illustrating their capacity to adapt to different environments. The ecological success of diatoms suggests that they have developed strategies that enable them to cope with various biotic and abiotic stress factors. For example, calcium (Ca2+)-based second messenger signaling pathways play roles in cellular perception of bioavailable Fe concentrations. 3,4 The accumulation of triacylglycerols (TAGs) in diatom cells under growth-limiting conditions is thought to be one of the most effective strategies to adapt and respond to changing growth environments.5 The marine diatom Phaeodactylum tricornutum is one of the most widely studied model organisms in research on diatom physiology, biochemistry,6 genomics,7 and transcriptomics.8−10 This species is also able to be genetically transformed.11,12 Proteomic research has provided new insights into the strategies used by diatoms to adapt to changes in environmental and growth conditions.13−21 These resources provide possibilities to study the stress response mechanisms of diatoms © 2014 American Chemical Society
under adverse environmental conditions. Recent studies have focused on the signaling pathways and cellular processes of P. tricornutum during lipid accumulation under various growth conditions. A study on the responses to nutrient deficiency showed that nitrogen deficiency enhances TAG accumulation and changes lipid profiles in P. tricornutum.9 In numerous other microalgae, high light intensity increases the amount of neutral lipids and decreases the total amount of polar lipids.22−24 Mild iron deficiency can also increase the lipid content in diatoms.25 Reversible protein phosphorylation plays a key role in signal processing, and many metabolic enzymes are regulated by phosphorylation.26 Phosphorylation of thylakoid proteins has been implicated in adaptive responses to a number of environmental stress factors such as high light conditions.26−28 Despite extensive research on protein phosphorylation in plants, the cellular and molecular mechanisms underlying environmentally dependent protein phosphorylation are largely uncharacterized in diatoms. In the current study, we conducted a global phosphoproteomic analysis of the model diatom P. tricornutum during enhanced lipid production in response to Received: December 28, 2013 Published: April 9, 2014 2511
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In-Solution Trypsin Digestion and Reverse-Phase Chromatography
nitrogen starvation, iron depletion, and high light intensity. The aim of this research was to provide detailed information about stimulus-dependent protein phosphorylation in a model diatom. The information gained from these analyses can help to answer fundamental questions, such as how diatoms respond to internal and external stimuli, and which strategies are used to adapt to adverse environmental conditions.
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The precipitated proteins from the subcellular fractions (2−10 mg) were redissolved in 50 mM ammonium bicarbonate and then reduced and carboxyamidomethylated according to Nielsen et al.32 Proteins were then digested with sequencing grade modified trypsin (Promega, Madison, WI, USA, dilution 1:100 w/w) at 37 °C for no more than 24 h. The tryptic digestion was quenched by adding 0.1% trifluoroacetic acid (TFA), and the mixture was dried in a vacuum centrifuge. Subsequently, peptides were separated by centrifugation and the supernatant was fractionated on AGT Cleanert SPE columns packed with C18 material (40 μm, 60 Å pore size, Agilent Technologies, Palo Alto, CA, USA). The columns were washed five times with 2.0 mL of 0.1% TFA to desalt the sample, and then compounds were eluted with a series of elution buffers (each 2.0 mL) consisting of 0.1% TFA with different concentrations of acetonitrile (ACN) (10%, 15%, 20%, 25%, 30%, 35%, 40%, 50%, 60%, and 100%). Fractions were collected, dried with a vacuum centrifuge, and then stored at −20 °C until further use.
EXPERIMENTAL PROCEDURES
Cell Culture and Protein Extraction
Axenic cultures of Phaeodactylum tricornutum Bohlin (CCMP2561) were obtained from the culture collection of the Provasoli−Guillard National Center for Culture of Marine Phytoplankton, Bigelow Laboratory for Ocean Sciences, USA. For phosphoproteomic analysis, cells (4 × 105 cells mL−1) from cultures in the mid logarithmic growth phase were inoculated into artificial seawater enriched with f/2.29 Cells were cultured at 22 °C with bubbling with filtered air under continuous illumination (60 μmol photons m−2 s−1). We performed the experiments for three times using different experimental procedures in order to increase the yield of phosphorylated proteins. First, proteins from cultures in the mid logarithmic growth phase were extracted and both gel-free and gel-based phosphoproteomic analyses were performed as described previously.30 Second, protein extracts were isolated from a mixed culture, which was subjected to different stimuli to mimic various aspects of the environments experienced by P. tricornutum. Briefly, cells in the exponential phase of growth were collected (6000g at 20 °C for 5 min), washed twice with artificial seawater, and then transferred to fresh medium (2 × 106 cells mL−1) in culture tubes (Φ40 mm × 200 mm) and subjected to high light (120 μmol photons m−2 s−1), nitrogen starvation without adding nitrogen-source, or iron deficiency without adding iron source for 24 h. At the end of the stress treatments, NaF, Na3VO4, and Na4P2O7 were added to final concentrations of 10, 1, and 10 mM, respectively, to inhibit the activities of endogenous protein phosphatases.30 The cells were for kept for another 30 min before harvesting by centrifugation (6000g at 4 °C for 5 min). Then, the cells were resuspended in lysis buffer containing 20 mM Tris-Cl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 5 mM β-glycerophosphate, 10 mM NaF, 1 mM Na3VO4, 10 mM Na4P2O7, 1× protease inhibitor cocktail, and 1× phosphatase inhibitor cocktail (Thermo Fisher Scientific, Waltham, MA, USA). Whole cell lysate was prepared by sonication (2 s on, 2 s off) for 30 min on ice with a JY92-IIN sonicator (Ningbo Scientz Biotechnology Co., Ltd., Ningbo, China) with an output of 135 W. Third, cells in the mid logarithmic growth phase were collected and subjected to subcellular prefractionation (i.e., cytosol, membrane, and nuclear fractions). The cellular debris was removed by centrifugation at 3000g for 10 min at 4 °C, and the resulting supernatants were collected for further purification of subcellular fractions. The total membrane fraction and cytosol fraction were separated by ultracentrifugation (45 min at 100000g, 4 °C), while the nuclear fraction was prepared using a NucBuster protein extraction kit (Novagen, Madison, WI, USA). Proteins were extracted from subcellular fractions as described above, precipitated with 5 volumes ice-cold acetone, dried at room temperature, and then redissolved in 50 mM ammonium bicarbonate. The protein concentration was determined using the Bradford assay.31
In-Gel Trypsin Digestion
Protein samples (5 mg) from each subcellular fraction were separated by SDS-PAGE (8%) and stained with Coomassie Blue R250. Each lane of the gel (containing one protein sample) was cut into 12 slices, and each slice was further diced into ∼1 mm3 cubes for in-gel digestion. Each section was destained, reduced, and alkylated prior to tryptic digestion (dilution 1:100 w/w). After digestion at 37 °C overnight, peptides were extracted by formic acid extraction.33 Finally, peptides were dried in a vacuum centrifuge and stored at −80 °C until analysis. Enrichment of Phosphopeptides with TiO2 Resin
Peptides were enriched for phosphorylated peptides using a Phosphopeptide Enrichment TiO2 kit (Calbiochem, San Diego, CA, USA) according to the manufacturer’s instructions, with a slight modification. Each fraction was first redissolved in 200 μL TiO2 Phosphobind buffer with 2,5-dihydroxybenzoic acid. Then, samples were added to 50 μL of TiO2 Phosphobind resin, mixed carefully, and incubated with gentle agitation for 1 h at room temperature. The supernatant was discarded, and the resin was washed with wash buffer. Then, the phosphopeptides were eluted by 20 μL of elution buffer and centrifuged (12000g for 5 min at 4 °C). The supernatants were used for LC−MS/ MS analysis. Peptide Identification by LC−ESI−MS
Chromatographic separation of peptides was conducted using an Ultimate 3000 nano-LC system (Dionex, Sunnyvale, CA, USA), and peptides were further analyzed using an electrospray ion-trap mass spectrometer HCT Ultra (Bruker Daltonics, Bremen, Germany). Each sample was loaded onto a C18 precolumn (Acclaim PepMap, 300 μm i.d. × 5 mm, Dionex) and then separated on a C18 reversed-phase analytical column (Acclaim 75 μm × 150 mm; Dionex). Peptides were eluted from the analytical column with a linear gradient of solvents (A, 0.1% formic acid (FA) in water; B, 100% ACN/ 0.1% FA) over 120 min with a flow rate of 300 nL min−1. The sequential steps of the gradient were as follows: 5 min, 95% (v/ v) buffer A; 95 min, gradient from 5% to 80% buffer B; 10 min, gradually shifting to 20% buffer A and 80% buffer B; 5 min gradient from 80% to 5% buffer B and a final 5 min of 95% 2512
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Figure 1. Schematic representation of enrichment and analysis of phosphopeptides from P. tricornutum, a representative MS/MS spectrum, and general description of identified phosphopeptides. (A) Overview of analytical procedures used in this study. Cells cultured under normal conditions (1), nitrogen starvation (2), iron deficiency (3), and high light exposure (4) were harvested and lysed. Proteins were prefractionated using both gelfree and gel-based methods and then digested by trypsin followed by TiO2 enrichment of phosphopeptides. Enriched phosphopeptides were analyzed individually by LC−MS/MS. (B) Proteins (20 μg) from cells cultured under control, iron-deficient (Fe-), nitrogen-starvation (N-), or high light (HL) conditions were separated by 12% SDS-PAGE along with a molecular mass standard. Then, proteins were immunoblotted with specific antibodies against phospho-Tyr. (C) MS/MS spectrum of doubly charged, serine phosphorylated peptide AGEALDS*EEEELAFEK from ATPbinding cassette (ABC) transporter. (D) Distribution of singly, doubly, and triply phosphorylated peptides as well as phosphorylated serines, threonines, and tyrosines.
20, (ii) a series of at least three successive b- or y-ions were present, and (iii) at least the singly charged peptide fragment ions with Ser (P) and Thr (P) must have a lost phosphoric acid (−98 D). For phosphorylated peptides with multiple potential phosphorylation sites, the probability of each potential phosphorylation site was calculated according to the posttranslational modification (PTM) scores as described previously.42,43 Phosphorylation sites with a probability of ≥0.75 were confirmed and reported as class I phosphorylation sites. All raw data and the converted .mgf file have been deposited at the PeptideAtlas database (http://www.peptideatlas.org).44,45
buffer A to equilibrate the column. The mass spectrometer was run using the data-dependent neutral-loss method with the four most abundant ion scans for CID MS/MS selected. Tandem mass spectra were acquired in ultrascan operating mode at 26000 m/z/s (Bruker Esquire Control software). All MS/MS spectra were acquired using the following parameters: normalized collision energy, 0.5 V; precursor selection threshold, 100000 Abs; dynamic exclusion of selected ions set to 0.25 min. Data Analysis
The raw files were processed by DataAnalysis 4.0 (Bruker Daltonics). The resulting .mgf files were used for simultaneous searches in the P. tricornutum genome v2.0 database at JGI (http://genome.jgi-psf.org/Phatr2/Phatr2.home.html), an inhouse MASCOT server (version: 2.3) (Matrix Science, London, U.K.), and pFind Studio 2.6.34−36 Carbamidomethylation of Cys residues was included as a fixed modification, and oxidation of Met and phosphorylation of Ser, Thr, and Tyr were included as variable modifications. Searches were conducted with tryptic specificity allowing two missed cleavages and mass errors up to 0.4 D for MS data and up to 0.6 D for MS/MS data. Spectra of phosphorylated peptides identified by pFind were extracted by pBuild.34−36 Peptides less than seven amino acids long were excluded. The false discovery rate (FDR) for peptide identification was calculated using the target-decoy search strategy.37−39 The Mascot score threshold was determined as the 1% FDR using the formula FDR = 2[nDecoy/(nDecoy + nTarget)].38 Phosphopeptides with MS/MS spectra were considered to be identified when they met the following criteria:40,41 (i) the peptides had a pFind E score of
Bioinformatics Analysis
Gene Ontology (GO) annotation and statistical assessment of GO term using Blast2GO software assigned the identified phosphoproteins into “biological process”, “molecular function”, and “cellular component” categories.46−49 Functional enrichment analysis of phosphorylated proteins was further performed using the BINGO 2.4450 plugin in the Cytoscape platform.51 Predictions of serine, threonine, and tyrosine phosphorylation sites in phosphoproteins were made using the NetPhos 2.0 Server.52 SCANSITE searches for motifs of identified phosphorylated sites within proteins in P. tricornutum were conducted using default settings.53 We also used the Motif-X (motif extractor) algorithm54 to analyze significant motifs based on predicted phosphorylation sites as well as the surrounding ±6 amino acids with the parameters described elsewhere.55 The whole P. tricornutum proteome was used as the background data set. Predictions of secondary structures were made using NetSurfP.56 The mean secondary structure 2513
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Figure 2. GO classification and statistical analysis on gene function information on phosphorylated proteins by Blast2GO. (A) Distribution of identified phosphoproteins according to GO functional category (biological process, molecular function, and cellular component). (B) Bar chart for functional category statistical analysis of phosphorylated proteins. The Y-axis exhibits significantly enriched GO terms and the X-axis shows the −LOG (p-value).
for the Glu/Leu/Phe/Val dehydrogenase family protein (Glu/ Leu/Phe/ValDH), LGSIDGSSDLpTQLFTR for the sensory box histidine kinase/response regulator (HKRR), GpSAYDLSGPSKDHVDELMEIR for the ammonium transporter AMT2a (AMT2a), pYIDFGWDSFSDEEKAR for the fucoxanthin-chlorophyll a−c binding protein B (FCPB), VNAILPLQTKDDpSSE for the nonphototropic hypocotyl 1 protein (NPH1), and SSASNDASMSMApTGMGVNGFGR for the glyceraldehyde-3-phosphate dehydrogenase precursor (GAPDH). The ratio of the specificity of the antiphosphopep-
probabilities of modified serine, threonine, and tyrosine residues were compared with those of control residues for all phosphorylated proteins identified in this study. The p values were calculated as previously described.57 Kinase domains were aligned using ClustalW, and the Neighbor-Joining (NJ) phylogram was constructed using Mega 4.58 Generation of Phosphorylation Site-Specific Antibodies
All oligopeptides and peptide-specific antibodies were produced and affinity-purified by Anbiotech Co. (Wuhan, Hubei, China). The peptide sequences were as follows: SEYGpSLGDLPSPSK 2514
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the neutral loss of phosphate groups from either phosphoserine or phosphothreonine was a common event in ion-trap CID spectra. Figure 1C shows a representative MS/MS spectrum of a serine phosphopeptide sequence from the ATP-binding cassette (ABC) transporter. There was good coverage of the fragmentation of b- and y-type ion series and a clear neutral loss of phosphate groups (98 D).
tide antibodies for the phosphopeptide antigen to that for the unphosphorylated sequence was >99:1, as determined by ELISA (determined by the manufacturer). Western Blotting
Equal amounts of proteins (10 μg) from each sample (untreated (control) or subjected to nitrogen deprivation (N), iron depletion (Fe-), or high light (HL)) were prepared as described previously, denatured in SDS sample buffer, and then resolved by 12% SDS-PAGE. Then, proteins were stained with Coomassie Brilliant Blue or transferred to polyvinylidene fluoride (PVDF) membranes (GE Healthcare, Piscataway, NJ, USA) and immunoblotted with polyclonal antiphospho-Tyr antibody (1:5000) or antiphosphosite-specific antibodies (1:2000), followed by a peroxidase-conjugated secondary antibody (1:5000) (KPL, Gaithersburg, Maryland). Membranes were washed in TBS-T, and chemiluminescence detection was carried out using the SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific, Rockford, IL, USA). The gray scale of Western blots was recorded using ImageQuant TL (GE Healthcare, Piscataway, NJ, USA).
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Functional Classification of Identified Phosphoproteins
The identified phosphoproteins were assigned to biological process, molecular function, and cellular component categories by Blast2GO (Figure 2A). GO terms for P. tricornutum proteins were extracted from their closest GO-annotated orthologues in the NCBI database. The results of the NCBI searches were complemented by additional functional information from the Joint Genome Institute (JGI) web site and annotation notes. Among the 245 identified phosphoproteins, only 123 have been described in terms of their specific functions in cellular biological processes. This analysis revealed that the phosphoproteins were widespread in the metabolic process (20.0%) and cellular process (15.8%) categories. Because P. tricornutum is highly tolerant to nitrogen starvation, iron deficiency, and high light conditions, it was not surprising that some phosphoproteins were annotated with external stimulus (5.8%) and signaling (3.5%), indicating that phosphorylation may play a vital role in the stress response. In the molecular function category, the number of phosphoproteins in various subcategories were as follows: target-binding, 110; catalytic activity, 87; transporter activity, 19; enzyme regulator activity, 6; and nucleic acid binding transcription factor activity, 5. Although it is important to determine the subcellular localization of a protein to understand its function, from the cellular component perspective, the localization of the majority of the identified phosphoproteins was not predicted. Among the phosphoproteins with predicted subcellular localizations, 36 were predicted to localize in intracellular membrane-bound organelles, 12 in intracellular nonmembrane-bounded organelles, eight in the cytosol, eight in plastids, seven in the nucleus, six in the intracellular organelle lumen, five in the Golgi apparatus, and five in the mitochondrion. These findings indicated that proteins with phosphorylated Ser/Thr/Tyr residues were involved in almost all cellular pathways and processes in the cell under these conditions. A list of all unique matching proteins and a one-line summary of annotations and GO terms is shown in Supporting Information Table S2. The functions and locations of a large proportion of phosphoproteins have not yet been predicted because no homologues have been characterized in other organisms. Additionally, we performed the statistical analysis on gene function information on all identified phosphorproteins using the Fisher’s exact test. As shown in Figure 2B and Supporting Information Table S2, transcription (p = 1.15 × 10−16), ion binding (p = 9.21 × 10−7), and cell (p = 3.93 × 10−12) were most overrepresented in the biological process, molecular function, and cellular component categories, respectively. To gain further insights into the functional roles of the P. tricornutum phosphoproteome, we conducted GO enrichment analyses for the biological process, molecular function, and cellular component categories using the BINGO 2.4450 plugin in the Cytoscape platform.51 In the biological process category, phosphoproteins were overrepresented in the subcategories of transcription, multicellular organismal development, response to endogenous stimulus, signal transduction, and response to
RESULTS
Identification of Phosphopeptides
To increase the yield of phosphorylated proteins, we separated total membrane and nuclear fractions, which contain abundant phosphorylated proteins, from the cytosol fraction. Because phosphorylation of certain proteins may be up-regulated under stress conditions, we analyzed cells subjected to different stimuli: nitrogen starvation, iron deprivation, and high light conditions. We analyzed cells subjected to these conditions to gain a deeper insight into the roles of phosphoproteins in the stress responses of this diatom. We conducted both gel-free and gel-based phosphoproteomic analyses, TiO2 affinity chromatography, and used two different search algorithms (MASCOT and pFind) as described previously.30 These analyses revealed a significant number of phosphoproteins in P. tricornutum. In total, we identified 264 phosphopeptides from 245 phosphoproteins with an estimated FDR of less than 1% (Figure 1A). A set of phosphatase inhibitors (10 mM NaF, 1 mM Na3VO4, 10 mM Na4P2O7) was used during cell rupture to reduce the potential dephosphorylation of proteins.30 To analyze phosphoproteins in the crude lysate, we carried out Western blotting with a polyclonal antiphospho-Tyr antibody. This analysis revealed a few phosphorylated proteins with an apparent mass range of 15−100 kDa. These results showed that Tyr-phosphorylated proteins were low-abundance proteins. There was a significant decrease in protein phosphorylation under nitrogen starvation, but a dramatic increase under Fe depletion (Figure 1B). A global view of the Ser/Thr/Tyr phosphoproteome from P. tricornutum is shown in Figure 1D. We identified 436 phosphorylation sites on Ser/Thr/Tyr with localization probability greater than 0.75. A total of 293 (67.2%) serines, 116 (26.6%) threonines, and 27 (6.2%) tyrosines were phosphorylated in the identified phosphopeptides. Details of the identified phosphopeptides are listed in Supporting Information Table S1, and annotated spectra of all detected phosphopeptides are shown in Supporting Information Figure S1. All raw data has been deposited in the publicly accessible database PeptideAtlas (http://www.peptideatlas.org) and can be accessed with the identifier PASS00379 (http://www. peptideatlas.org/PASS/PASS00379). As reported previously, 2515
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Figure 3. Overview of GO distribution of identified phosphoproteins in P. tricornutum using BINGO 2.44, a plugin of Cytoscape. GO terms enriched in phosphoproteins are shown as nodes connected by directed edges, which indicate hierarchies and relationships between terms. Node size is proportional to number of proteins belonging to that functional category. Node color indicates corrected p-value for the enrichment of the term according to the legend. The corrected p < 0.05 was considered as significant.
mammal62 (60 occurrences in our data) and the [SxxpS] motif (42 occurrences in our data). To further predict potential kinases responsible for phosphorylation of proteins at the identified sites, we used the algorithm SCANSITE,53 which searches peptide library phosphorylation data to predict substrates recognized by specific kinases. Supporting Information Table S4 shows the phosphopeptides that were identified in this analysis and were predicted to be associated with kinase binding motifs at the highest stringency (0.2%), medium stringency (1.0%), and low stringency (5.0%) levels. Figure 4A lists 137 motifs found at 80 phosphorylation sites within the top 1% of SCANSITE hit scores. Among the phosphorylation sites identified in this analysis, 72 were predicted to be phosphorylated by basophilic serine/threonine kinases and 25 were predicted to be phosphorylated by acidophilic serine/threonine kinases. The main basophilic serine/threonine kinase was Akt kinase (18.0%). Among the acidophilic serine/threonine kinases, the main kinase was casein kinase 2 (64.0%). These results were quite consistent with those derived from the Motif-X analysis. The SCANSITE analysis also detected sequences recognized by kinases in the proline-dependent serine/threonine group (15), the phosphoserine/threonine-binding kinase group (14), the DNA damage kinase group (9), the kinase binding site group (1), and the tyrosine kinase group (1). To analyze the structural features of phosphorylation sites in proteins, we used the algorithm NetSurfP.56 We compared the secondary structures of phospho-Ser/Thr/Tyr with those of all Ser/Thr/Tyr in proteins identified in this study. Phospho-Ser/ Thr/Tyr showed different preferences for secondary structure compared with those of Ser/Thr/Tyr, as shown in Figure 4C. Consistent with previous reports, our results showed that phospho-Ser/Thr/Tyr were found more frequently in unstruc-
external stimulus (Figure 3 and Supporting Information Table S6). The most overrepresented process in the “biological process” category was transcription (p-value, 5.17 × 10−9). This finding suggested that Ser/Thr/Tyr phosphorylation may play a vital role in gene expression. As well, 15 phosphoproteins were attributed to response to stress (Supporting Information Table S7), such as response to endogenous stimulus (p = 3.27 × 10−5), indicating the involvement of Ser/Thr/Tyr phosphorylation in the response to various stress conditions. In the molecular function category, phosphoproteins were overrepresented in the nucleotide binding subcategory. Many of the phosphoproteins in the cellular component category were distributed throughout the whole cell, especially in the plasma membrane, indicating that phosphorylated proteins play a role in perception of the environment. Analysis of Kinase-Specific Phosphorylation Sites
Identifying the phosphorylation sites in proteins can yield valuable information about protein kinase activity. Sites phosphorylated by specific protein kinase share a similar sequence motif, which is necessary for the protein kinase to recognize the substrate.59 Analyses of phosphorylation sites have provided details about kinase/substrate relationships and the relative activities of kinases.60 To identify significant phosphorylation motifs in P. tricornutum, we used the MotifX algorithm to extract phosphorylation motifs from the phosphorylation data.54,61 The peptide sequences for phosphorylation sites with localization probability higher than 0.75 were aligned, their lengths were adjusted to ±6 amino acids from the central phosphorylation position, and then they were analyzed using the Motif-X server. Two Ser motifs were identified (Figure 4B), including the acidic motif [pSxxS], which is selectively recognized by casein kinase I (CK1) in 2516
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Figure 4. Bioinformational analysis of phosphorylation sites. (A) Protein kinases and binding motifs of P. tricornutum predicted by SCANSITE within top 1% hit score. (B) Motif-X analysis of in vivo phosphorylation sites against P. tricornutum proteomic background. (C) Comparison of phosphorylated and nonphosphorylated amino acids in protein secondary structures. Probabilities of different secondary structures (α-helix, β-strand, coil) and accessibility of phosphorylated Ser/Thr/Tyr were compared with those of all Ser/Thr/Tyr on all proteins identified in this study.
tured coil regions.63,64 Unstructured coil regions of phosphoSer/Thr/Tyr showed significant differences from those of all Ser/Thr/Tyr in proteins (p < 0.05). In addition to ordered regions, we further evaluated identified phosphorylation sites for solvent accessibility. We found that 79.7% of the identified phosphorylation sites were on the protein surface, compared with 65.9% of all Ser/Thr/Tyr residues.
building a Neighbor-Joining (NJ) phylogram including all of the identified phosphorylated protein kinases and key members of eukaryotic kinase families from KinBase (http://www.kinase. com) (Figure 5). Only a few of the phosphorylated protein kinases have been identified in P. tricornutum. These identified phosphorylated protein kinases belonged to known kinase groups; three to the CAMK group (ProtID 1448, 32172, 17938), one to the CMGC group (ProtID 14432), and one to the AGC kinase group (ProtID 17711).65
Analysis of Identified Phosphorylated Protein Kinases
Most protein kinases function in a network of kinases and other signaling effectors. In total, we found 13 phosphorylated protein kinases (ProtID 1448, 14416, 14432, 17337, 17711, 17938, 22271, 22938, 32172, 33971, 35075, 36704, 38365) according to the sequenced P. tricornutum genome annotation from the JGI database, suggesting that these kinases act as signal transducers in signaling pathways. Most of these kinases have more than one phosphorylation site, suggesting that they act at the crossroads of multiple signaling pathways. We also investigated the protein kinase profile of P. tricornutum by
Comparative Analysis of P. tricornutum Phosphoproteome and other Eukaryotic Phosphoproteomes
To study the conservation of phosphoproteins among singlecell eukaryotes, we compared the P. tricornutum phosphoproteome with those of Chlamydomonas reinhardtii,66−68 Tetrahymena thermophila,69 and Saccharomyces cerevisiae.70 BLAST alignments were performed using BlastP software with the BLOSUM62 matrix. The results are shown in Supporting Information Table S5. Comparisons of identified phosphopro2517
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Figure 5. Phylogenetic tree based on P. tricornutum protein kinases and key members of other kinase families: CAMK (T01C8.1_Cele, SNF1A_Dmel, BRSK2_Hsap, CaMK1g_Hsap, CaMK1b_Hsap), TKL (zak-1_Cele, MLK2_Hsap), CMGC (sgg_Dmel), AGC (PKG1_Hsap) (all from KinBase). Kinase domains were aligned using ClustalW, and NJ phylogram was constructed using Mega 4. NJ bootstrap values (%) for the main eukaryotic and P. tricornutum kinase groups are shown. Scale bar indicates 0.1 substitutions per amino acid position.
Figure 6. Western blot analysis of proteins from P. tricornutum with phospho-amino acid-specific antibodies. (A) Proteins (10 μg) from untreated cells (control) or cells subjected to iron-deficient (Fe-), nitrogen starvation (N-), or high light (HL) conditions were separated by 12% SDS-PAGE, transferred to a PVDF membrane, and either analyzed with a polyclonal antibody (1:2000) or stained with Coomassie Brilliant Blue (B). Western blotting was conducted using antibodies specific to phospho-Glu/Leu/Phe/Val dehydrogenase family protein (Glu/Leu/Phe/ValDH), sensory box histidine kinase/response regulator (HKRR), ammonium transporter AMT2a (AMT2a), fucoxanthin-chlorophyll a−c binding protein B (FCPB), nonphototropic hypocotyl (NPH1), and glyceraldehyde-3-phosphate dehydrogenase precursor (GAPDH).
teins in P. tricornutum with orthologous phosphoproteins in the three organisms revealed modest overlaps: 42 C. reinhardtii phosphoproteins, 70 T. thermophila phosphoproteins, and 54 S. cerevisiae phosphoproteins. We detected 30 phosphoproteins that were common to all three organisms, suggesting an evolutionary conserved and potentially significant role of phosphorylation in their function. This may be explained in part by the fact that diatoms contain many mosaic genes derived from other organisms. In addition, the comparative analysis of phosphoproteomes revealed several proteins in photosynthesis that were conserved between green algae and diatoms, several protein kinases that were conserved between yeast and diatoms, and conservation of the ATP-binding cassette (ABC) transporter among the four eukaryotes. These highly conserved phosphorylation events suggest that protein
phosphorylation played roles in cellular housekeeping even in the earliest life forms. Validation of Phosphorylated Proteins by Western Blotting
A Western blot analysis of proteins extracted in the presence of a phosphatase inhibitor confirmed several stress-induced phosphorylation sites. The comprehensive stress/starvation profile of phosphorylated proteins is shown in Figure 6. We postulated that stress conditions imposed by chemical or physical environmental stimuli induced dynamic changes in protein phosphorylation and that the phosphorylation state of proteins regulated cellular pathways and processes. We analyzed the phosphorylation state of six phosphoproteins in vivo. Nitrogen starvation enhanced phosphorylation of GAPDH (ProtID 14487), which may play a role in TAG 2518
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Figure 7. Working scheme of phosphorylation events involved in stress responses in P. tricornutum. Identified phosphoproteins are highlighted in red. TCA, tricarboxylic acid cycle; PCD, programmed cell death; ROS, reactive oxygen species; NRT, nitrate transporter (10701); AMT2a, ammonium transporter (13135); UAT, urea active transporter-related protein (12699); UGT, UDP-galactose transporter (22739); LCTP, L-lactate permease (39617); BOR, boron transporter (18839); NPH1, nonphototropic hypocotyl 1 (23236); SLC34A2, solute carrier family 34 (sodium phosphate, member 2) (37940); MGT, corA-like Mg2+ transporter protein (40121); HMCT, divalent heavy-metal cations transporter (31814); ABC, ATP-binding cassette transporter G1 variant V (34258); HKRR, sensory box histidine kinase/response regulator (33971); GAPDH, glyceraldehyde-3-phosphate dehydrogenase (14487); PPDK, pyruvate orthophosphate dikinase (14416); AK-HSDH, bifunctional aspartokinase/ homoserine dehydrogenase I (38365); FCPB, fucoxanthin-chlorophyll a−c binding protein B (14420); LHC, light harvesting complex protein (40734); Glu/Leu/Phe/ValDH, Glu/Leu/Phe/Val dehydrogenase family protein (34879); PEPC, phosphoenolpyruvate carboxylase (20851); BC, biotin carboxylase (32320); USP, ubiquitin-specific protease (33336); E3, ubiquitin protein ligase (39555); NMRAL1, nmrA-like family domaincontaining protein 1 (41497); CaM, calmodulin (16558); CDPK, calcium-dependent protein kinase (17938); HSF, heat shock factor protein (49147); LHY, LHY-like protein (40642); AGO, argonaut-like protein (37682); ISWI, imitation switch isoform alias nucleosome remodeling factor (13556); BRR2, pre-mRNA-splicing helicase BRR2 (13724); GYRB, DNA gyrase β subunit (13738); MMRP, DNA mismatch repair protein (37263); IF-3, initiation factor IF-3 (11564); L31, ribosomal protein L31 (11939); cGK, cGMP-dependent protein kinase (17711); PP, protein phosphatase (39463); FLO, flocculin (37296).
insights into the phosphoproteome of the model diatom, P. tricornutum. Our phosphoproteomic data indicated that proteins subject to phosphorylation regulate almost every cellular process, including signal perception and transduction, gene and protein expression, and protein function. GO enrichment analyses showed that phosphoproteins were mainly attributed to stress responses in the biological process category. Stress signals are first perceived by transmembrane transporter proteins or receptors. Such transporters and receptors were among the identified phosphorylated proteins. One of the phosphorylated proteins was AMT2a, which is one of several transporters that play key roles in recognizing and taking up nutrients according to environmental and nutritional conditions.71 Another phosphorylated protein was HKRR, a homologue of a component of the two-component system (TCS) that functions as the main bacterial tool to sense rapid changes in environmental conditions.72 After stress perception, signals are transduced downstream and induce a range of stress-responsive genes involved in various signaling pathways. Several metabolic
accumulation. Under Fe limitation, there was increased phosphorylation of Glu/Leu/Phe/ValDH (ProtID 34879), HKRR (ProtID 33971), AMT2a (ProtID 13135), and FCPB (ProtID 14420). It is interesting to note that nitrogen deprivation triggered strong phosphorylation of GAPDH. Unlike other phosphoproteins, NPH1 (ProtID 23236) showed decreased phosphorylation under certain treatments, compared with that in control conditions. This indicated that phosphorylation events are induced even under normal conditions. Together, all of our results revealed phosphorylated proteins in cells in response to different stimuli.
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DISCUSSION
Diatoms are distributed throughout marine and freshwater environments and are believed to be one of the most successful clades of eukaryotic, single-celled, photosynthetic organisms on Earth.1,2 The ecological success of diatoms suggests that they have an array of mechanisms to cope with changes in environmental conditions. In this study, we gained novel 2519
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tricornutum probably plays a role in the response of high light exposure. Besides, electrophysiological studies on signaling events have shown that NPH1 is responsible for the increase in cytosolic (Ca2+) in higher plants.79 In P. tricornutum, the Ca2+dependent nitric oxide (NO)-based signal transduction pathway plays a role in its responses to a range of environmental stimuli.3,4,80 The activation of this signal transduction pathway was represented by the phosphorylation of nmrA-like family domain-containing protein 1 (ProtID 41497) in our study. Furthermore, NO and Ca2+ may initiate programmed cell death (PCD) in cells.4 Up-regulation of light harvesting can result in excess production of highly toxic ROS.81 When ROS production exceeds the cellular antioxidant capacity, a biochemical cascade leading to PCD can be induced82 as well as DNA damage (e.g., DNA mismatch repair protein (ProtID 37263)). In most cases, diatoms have adaptive strategies to cope with adverse environmental conditions; e.g., antioxidant enzymes to scavenge ROS. Occasionally, cells are prone to aggregate after they produce polysaccharide-associated cell surface proteins as flocculin (ProtID 37296). This is a response to unfavorable conditions that results in cell dormancy, which allows them to escape from damage caused by intracellular and extracellular stresses.
pathways, including neutral lipid biosynthesis, are involved in stress responses to adverse climatic conditions.5 The results of recent genome-enabled studies,7,73 combined with those of the GO enrichment and Western blotting analyses in this study, indicated that phosphorylation events are involved in stress responses in P. tricornutum (Figure 7). Under nitrogen deprivation, phosphorylation of proteins related to transport of nitrogen resources (e.g., AMT2a, a nitrate transporter (ProtID 10701) and a urea active transporter-related protein (ProtID 12699)) may have activated amino acid biosynthesis as an early response. Nevertheless, because of the paucity of extracellular nitrogen compounds, amino acids may not be synthesized under such conditions. Conversely, protein degradation may have increased because the activities of an ubiquitin-specific protease (ProtID 33336) and an ubiquitin protein ligase (ProtID 39555), which function in the ubiquitin-proteasome pathway, may have been enhanced by phosphorylation. The ubiquitin-proteasome pathway functions as a major route for protein degradation in cells.74 The proteomics analyses also provided evidence for catabolism of amino acids (e.g., Glu/Leu/Phe/ValDH). The intermediates of this degradation pathway may direct carbon flux (e.g., acetylCoA) toward the production of storage lipids, an important cellular adaptation to nitrogen deficiency. Apart from acetylCoA, the availability of glycerol-3-phosphate is also important for TAG biosynthesis.75 Therefore, it is not surprising that proteins involved in carbohydrate metabolic processes, including those involved in galactose and lactate uptake (e.g., UDP-galactose transporter (ProtID 22739) and L-lactate permease (ProtID 39617)) and glycolysis (e.g., GAPDH), were phosphorylated during TAG accumulation. Of these, GAPDH showed enhanced phosphorylation under nitrogen depletion, as determined by Western blotting. Previous studies have hypothesized that the process of oil droplet formation (mainly TAGs) in diatoms may eliminate reactive oxygen species (ROS). Oil droplet formation appears to be a protective mechanism in algal cells in response to environmental stress conditions as well as functioning in carbon and energy storage.5 Under Fe-deficient conditions, P. tricornutum appears to take up available cation resources from the environment via the corA-like Mg2+ transporter protein (ProtID 40121) or the divalent heavy-metal cations transporter (ProtID 31814), and it acclimates to low-Fe levels via metabolic reconfigurations. Fe appears to be the critical nutrient regulating diatom abundance, and an insufficient Fe supply leads to down-regulation of photosynthetic activity.76 In diatoms, a range of Fe-sensitive genes involved in light harvesting complex modification and various alternative electron cycling pathways are induced under Fe limitation.76 Previous results indicated that in P. tricornutum, the changes in metabolic pathways under Fe deprivation76 were similar to those that occurred under nitrogen starvation; for example, the increase in protein degradation by the ubiquitinproteasome pathway. Previous research has also shown that exquisitely sensitive calcium-dependent signaling mechanisms are induced by iron limitation.4 Exposed to high light conditions might down-regulate the photosynthesis and cause photodamage to cells. It has been demonstrated that FCPs of 22 kDa were phosphorylated in Cyclotella cryptica,77 which is consistent with our research in P. tricornutum. Phosphorylation of FCP subunits may work as a mechanism for light protection. The photoreceptor NPH1 plays a major role in response to low-intensity blue light in Arabidopsis,78 while NPH1 predicted in the genome of P.
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CONCLUDING REMARKS Our comprehensive mapping of the phosphoproteome of the pennate diatom P. tricornutum has provided clues to elucidate sophisticated sensing mechanisms that control its adaptive responses. Our results indicated two main routes to cope with changes in environmental conditions: the PCD process induced by intracellular ROS and Ca2+-dependent or NO signaling pathways and ROS scavenging, which coincides with oil droplet formation mediated by the ubiquitin-proteasome proteolytic pathway and the amino acid degradation pathway. In conclusion, the phosphoproteome of P. tricornutum provides a foundation for functional analysis of the phosphorylated proteins, and opens an avenue toward better understanding of their precise roles in regulating stress responses.
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ASSOCIATED CONTENT
S Supporting Information *
Annotated spectra of all detected phosphopeptides. Phosphopeptides identified in Phaeodactylum tricornutum; classification of phosphorylated proteins according to their biological process, molecular function, and cellular component; motifs identified by Motif-X using the whole Phaeodactylum tricornutum proteome as background data set; prediction of eukaryotic protein kinases and binding motifs by SCANSITE; comparison of Phaeodactylum tricornutum phosphoproteome with Chlamydomonas reinhardtii, Tetrahymena thermophila, and Saccharomyces cerevisiae phosphoproteomes; complete list of GO terms enriched in Phaeodactylum tricornutum phosphoproteome; phosphosproteins involved in stress responses according to biological process in P. tricornutum phosphoproteome. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Authors
*Feng Ge, E-mail:
[email protected]. Phone/Fax: +86-2768780500. 2520
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*Xian-En Zhang, E-mail:
[email protected]. Phone/Fax: +86-10-64888148.
(11) Siaut, M.; Heijde, M.; Mangogna, M.; Montsant, A.; Coesel, S.; Allen, A.; Manfredonia, A.; Falciatore, A.; Bowler, C. Molecular toolbox for studying diatom biology in Phaeodactylum tricornutum. Gene 2007, 406 (1−2), 23−35. (12) De Riso, V.; Raniello, R.; Maumus, F.; Rogato, A.; Bowler, C.; Falciatore, A. Gene silencing in the marine diatom Phaeodactylum tricornutum. Nucleic Acids Res. 2009, 37 (14), e96. (13) Frigeri, L. G.; Radabaugh, T. R.; Haynes, P. A.; Hildebrand, M. Identification of proteins from a cell wall fraction of the diatom Thalassiosira pseudonanainsights into silica structure formation. Mol. Cell Proteomics 2006, 5 (1), 182−193. (14) Lobanov, A. V.; Fomenko, D. E.; Zhang, Y.; Sengupta, A.; Hatfield, D. L.; Gladyshev, V. N. Evolutionary dynamics of eukaryotic selenoproteomes: large selenoproteomes may associate with aquatic life and small with terrestrial life. Genome Biol. 2007, 8 (9), R198. (15) Nunn, B. L.; Aker, J. R.; Shaffer, S. A.; Tsai, Y. H.; Strzepek, R. F.; Boyd, P. W.; Freeman, T. L.; Brittnacher, M.; Malmstrom, L.; Goodlett, D. R. Deciphering diatom biochemical pathways via wholecell proteomics. Aquat. Microb. Ecol. 2009, 55 (3), 241−253. (16) Carvalho, R. N.; Lettieri, T. Proteomic analysis of the marine diatom Thalassiosira pseudonana upon exposure to benzo(a)pyrene. BMC Genomics 2011, 12, 159. (17) Lyon, B. R.; Lee, P. A.; Bennett, J. M.; DiTullio, G. R.; Janech, M. G. Proteomic analysis of a sea-ice diatom: salinity acclimation provides new insight into the dimethylsulfoniopropionate production pathway. Plant Physiol. 2011, 157 (4), 1926−1941. (18) Bertrand, E. M.; Allen, A. E.; Dupont, C. L.; Norden-Krichmar, T. M.; Bai, J.; Valas, R. E.; Saito, M. A. Influence of cobalamin scarcity on diatom molecular physiology and identification of a cobalamin acquisition protein. Proc. Natl. Acad. Sci. U. S. A. 2012, 109 (26), E1762−E1771. (19) Dyhrman, S. T.; Jenkins, B. D.; Rynearson, T. A.; Saito, M. A.; Mercier, M. L.; Alexander, H.; Whitney, L. P.; Drzewianowski, A.; Bulygin, V. V.; Bertrand, E. M.; Wu, Z. J.; Benitez-Nelson, C.; Heithoff, A. The transcriptome and proteome of the diatom Thalassiosira pseudonana reveal a diverse phosphorus stress response. PLoS One 2012, 7 (3), e33768. (20) Hockin, N. L.; Mock, T.; Mulholland, F.; Kopriva, S.; Malin, G. The response of diatom central carbon metabolism to nitrogen starvation is different from that of green algae and higher plants. Plant Physiol. 2012, 158 (1), 299−312. (21) Lommer, M.; Specht, M.; Roy, A. S.; Kraemer, L.; Andreson, R.; Gutowska, M. A.; Wolf, J.; Bergner, S. V.; Schilhabel, M. B.; Klostermeier, U. C.; Beiko, R. G.; Rosenstiel, P.; Hippler, M.; LaRoche, J. Genome and low-iron response of an oceanic diatom adapted to chronic iron limitation. Genome Biol. 2012, 13 (7), R66. (22) Napolitano, G. E. The relationship of lipids with light and chlorophyll measurement in freshwater algae and periphyton. J. Phycol. 1994, 30, 943−950. (23) Brown, M. R.; Dunstan, G. A.; Norwood, S. J.; Miller, K. A. Effects of harvest stage and light on the biochemical composition of the diatom Thalassiosira pseudonana. J. Phycol. 1996, 32 (1), 64−73. (24) Khotimchenko, S. V.; Yakovleva, I. M. Lipid composition of the red alga Tichocarpus crinitus exposed to different levels of photon irradiance. Phytochemistry 2005, 66 (1), 73−79. (25) Lelong, A.; Bucciarelli, E.; Hegaret, H.; Soudant, P. Iron and copper limitations differently affect growth rates and photosynthetic and physiological parameters of the marine diatom Pseudo-nitzschia delicatissima. Limnol. Oceanogr. 2013, 58 (2), 613−623. (26) Luan, S. Protein phosphatases in plants. Annu. Rev. Plant Biol. 2003, 54, 63−92. (27) Xu, C. C.; Jeon, Y. A.; Hwang, H. J.; Lee, C. H. Suppression of zeaxanthin epoxidation by chloroplast phosphatase inhibitors in rice leaves. Plant Sci. 1999, 146 (1), 27−34. (28) Ebbert, V.; Demmig-Adams, B.; Adams, W. W.; Mueh, K. E.; Staehelin, L. A. Correlation between persistent forms of zeaxanthindependent energy dissipation and thylakoid protein phosphorylation. Photosynth. Res. 2001, 67 (1−2), 63−78.
Author Contributions ∥
These authors contributed equally to this work.
Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (grant no. 31370746) and the Hundred Talents Program of the Chinese Academy of Sciences (to F.G.). The authors also thank the supports from the State Key Laboratory Program.
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REFERENCES
(1) Falkowski, P. G.; Barber, R. T.; Smetacek, V. V. Biogeochemical controls and feedbacks on ocean primary production. Science 1998, 281 (5374), 200−207. (2) Field, C. B.; Behrenfeld, M. J.; Randerson, J. T.; Falkowski, P. Primary production of the biosphere: integrating terrestrial and oceanic components. Science 1998, 281 (5374), 237−240. (3) Falciatore, A.; d’Alcala, M. R.; Croot, P.; Bowler, C. Perception of environmental signals by a marine diatom. Science 2000, 288 (5475), 2363−2366. (4) Vardi, A.; Formiggini, F.; Casotti, R.; De Martino, A.; Ribalet, F.; Miralto, A.; Bowler, C. A stress surveillance system based on calcium and nitric oxide in marine diatoms. PLoS Biol. 2006, 4 (3), e60. (5) Hu, Q.; Sommerfeld, M.; Jarvis, E.; Ghirardi, M.; Posewitz, M.; Seibert, M.; Darzins, A. Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances. Plant J. 2008, 54 (4), 621−639. (6) De Martino, A.; Meichenin, A.; Shi, J.; Pan, K. H.; Bowler, C. Genetic and phenotypic characterization of Phaeodactylum tricornutum (Bacillariophyceae) accessions. J. Phycol. 2007, 43 (5), 992−1009. (7) Bowler, C.; Allen, A. E.; Badger, J. H.; Grimwood, J.; Jabbari, K.; Kuo, A.; Maheswari, U.; Martens, C.; Maumus, F.; Otillar, R. P.; Rayko, E.; Salamov, A.; Vandepoele, K.; Beszteri, B.; Gruber, A.; Heijde, M.; Katinka, M.; Mock, T.; Valentin, K.; Verret, F.; Berges, J. A.; Brownlee, C.; Cadoret, J. P.; Chiovitti, A.; Choi, C. J.; Coesel, S.; De Martino, A.; Detter, J. C.; Durkin, C.; Falciatore, A.; Fournet, J.; Haruta, M.; Huysman, M. J. J.; Jenkins, B. D.; Jiroutova, K.; Jorgensen, R. E.; Joubert, Y.; Kaplan, A.; Kroger, N.; Kroth, P. G.; La Roche, J.; Lindquist, E.; Lommer, M.; Martin-Jezequel, V.; Lopez, P. J.; Lucas, S.; Mangogna, M.; McGinnis, K.; Medlin, L. K.; Montsant, A.; Oudot-Le Secq, M. P.; Napoli, C.; Obornik, M.; Parker, M. S.; Petit, J. L.; Porcel, B. M.; Poulsen, N.; Robison, M.; Rychlewski, L.; Rynearson, T. A.; Schmutz, J.; Shapiro, H.; Siaut, M.; Stanley, M.; Sussman, M. R.; Taylor, A. R.; Vardi, A.; von Dassow, P.; Vyverman, W.; Willis, A.; Wyrwicz, L. S.; Rokhsar, D. S.; Weissenbach, J.; Armbrust, E. V.; Green, B. R.; Van De Peer, Y.; Grigoriev, I. V. The Phaeodactylum genome reveals the evolutionary history of diatom genomes. Nature 2008, 456 (7219), 239−244. (8) Maheswari, U.; Jabbari, K.; Petit, J. L.; Porcel, B. M.; Allen, A. E.; Cadoret, J. P.; De Martino, A.; Heijde, M.; Kaas, R.; La Roche, J.; Lopez, P. J.; Martin-Jezequel, V.; Meichenin, A.; Mock, T.; Parker, M. S.; Vardi, A.; Armbrust, E. V.; Weissenbach, J.; Katinka, M.; Bowler, C. Digital expression profiling of novel diatom transcripts provides insight into their biological functions. Genome Biol. 2010, 11, R85. (9) Valenzuela, J.; Mazurie, A.; Carlson, R. P.; Gerlach, R.; Cooksey, K. E.; Peyton, B. M.; Fields, M. W. Potential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutum. Biotechnol. Biofuels 2012, 5, 40. (10) Yang, Z. K.; Niu, Y. F.; Ma, Y. H.; Xue, J.; Zhang, M. H.; Yang, W. D.; Liu, J. S.; Lu, S. H.; Guan, Y. F.; Li, H. Y. Molecular and cellular mechanisms of neutral lipid accumulation in diatom following nitrogen deprivation. Biotechnol. Biofuels 2013, 6, 67. 2521
dx.doi.org/10.1021/pr401290u | J. Proteome Res. 2014, 13, 2511−2523
Journal of Proteome Research
Article
(29) Guillard, R. R. L. Culture of phytoplankton for feeding marine invertebrates. In Culture of Marine Invertebrate Animals; Smith, W., Chanley, M.., Eds. Springer: New York, 1975; pp 29−60. (30) Yang, M. K.; Qiao, Z. X.; Zhang, W. Y.; Xiong, Q.; Zhang, J.; Li, T.; Ge, F.; Zhao, J. D. Global phosphoproteomic analysis reveals diverse functions of serine/threonine/tyrosine phosphorylation in the model cyanobacterium Synechococcus sp strain PCC 7002. J. Proteome Res. 2013, 12 (4), 1909−1923. (31) Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein−dye binding. Anal. Biochem. 1976, 72, 248−254. (32) Nielsen, P. A.; Olsen, J. V.; Podtelejnikov, A. V.; Andersen, J. R.; Mann, M.; Wisniewski, J. R. Proteomic mapping of brain plasma membrane proteins. Mol. Cell Proteomics 2005, 4 (4), 402−408. (33) Shevchenko, A.; Wilm, M.; Vorm, O.; Mann, M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal. Chem. 1996, 68 (5), 850−858. (34) Fu, Y.; Yang, Q.; Sun, R.; Li, D.; Zeng, R.; Ling, C. X.; Gao, W. Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry. Bioinformatics 2004, 20 (12), 1948−1954. (35) Li, D.; Fu, Y.; Sun, R.; Ling, C. X.; Wei, Y.; Zhou, H.; Zeng, R.; Yang, Q.; He, S.; Gao, W. pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry. Bioinformatics 2005, 21 (13), 3049−3050. (36) Wang, L. H.; Li, D. Q.; Fu, Y.; Wang, H. P.; Zhang, J. F.; Yuan, Z. F.; Sun, R. X.; Zeng, R.; He, S. M.; Gao, W. pFind 2.0: a software package for peptide and protein identification via tandem mass spectrometry. Rapid Commun. Mass Spectrom. 2007, 21 (18), 2985− 2991. (37) Elias, J. E.; Haas, W.; Faherty, B. K.; Gygi, S. P. Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nature Methods 2005, 2 (9), 667−675. (38) Elias, J. E.; Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nature Methods 2007, 4 (3), 207−214. (39) Nesvizhskii, A. I.; Vitek, O.; Aebersold, R. Analysis and validation of proteomic data generated by tandem mass spectrometry. Nature Methods 2007, 4 (10), 787−797. (40) Macek, B.; Mijakovic, I.; Olsen, J. V.; Gnad, F.; Kumar, C.; Jensen, P. R.; Mann, M. The serine/threonine/tyrosine phosphoproteome of the model bacterium Bacillus subtilis. Mol. Cell Proteomics 2007, 6 (4), 697−707. (41) Macek, B.; Gnad, F.; Soufi, B.; Kumar, C.; Olsen, J. V.; Mijakovic, I.; Mann, M. Phosphoproteome analysis of E. coli reveals evolutionary conservation of bacterial Ser/Thr/Tyr phosphorylation. Mol. Cell Proteomics 2008, 7 (2), 299−307. (42) Olsen, J. V.; Blagoev, B.; Gnad, F.; Macek, B.; Kumar, C.; Mortensen, P.; Mann, M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell 2006, 127 (3), 635−648. (43) Olsen, J. V.; Mann, M. Improved peptide identification in proteomics by two consecutive stages of mass spectrometric fragmentation. Proc. Natl. Acad. Sci. U. S. A. 2004, 101 (37), 13417−13422. (44) Desiere, F.; Deutsch, E. W.; King, N. L.; Nesvizhskii, A. I.; Mallick, P.; Eng, J.; Chen, S.; Eddes, J.; Loevenich, S. N.; Aebersold, R. The PeptideAtlas project. Nucleic Acids Res. 2006, 34, D655−D658. (45) Farrah, T.; Deutsch, E. W.; Omenn, G. S.; Campbell, D. S.; Sun, Z.; Bletz, J. A.; Mallick, P.; Katz, J. E.; Malmstrom, J.; Ossola, R.; Watts, J. D.; Lin, B. A. Y.; Zhang, H.; Moritz, R. L.; Aebersold, R. A High-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas. Mol. Cell Proteomics 2011, 10 (9), M110.006353. (46) Conesa, A.; Gotz, S.; Garcia-Gomez, J. M.; Terol, J.; Talon, M.; Robles, M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21 (18), 3674−3676.
(47) Götz, S.; García-Gómez, J. M.; Terol, J.; Williams, T. D.; Nagaraj, S. H.; Nueda, M. J.; Robles, M.; Talón, M.; Dopazo, J.; Conesa, A. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008, 36 (10), 3420−3435. (48) Conesa, A.; Götz, S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int. J. Plant Genomics 2008, 2008, 619832. (49) Götz, S.; Arnold, R.; Sebastián-León, P.; Martín-Rodríguez, S.; Tischler, P.; Jehl, M. A.; Dopazo, J.; Rattei, T.; Conesa, A. B2G-FAR, a species-centered GO annotation repository. Bioinformatics 2011, 27 (7), 919−924. (50) Maere, S.; Heymans, K.; Kuiper, M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 2005, 21 (16), 3448−3449. (51) Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N. S.; Wang, J. T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13 (11), 2498−2504. (52) Blom, N.; Gammeltoft, S.; Brunak, S. Sequence and structurebased prediction of eukaryotic protein phosphorylation sites. J. Mol. Biol. 1999, 294 (5), 1351−1362. (53) Obenauer, J. C.; Cantley, L. C.; Yaffe, M. B. Scansite 2.0: proteome-wide prediction of cell signaling interactions using short sequence motifs. Nucleic Acids Res. 2003, 31 (13), 3635−3641. (54) Schwartz, D.; Gygi, S. P. An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets. Nature Biotechnol. 2005, 23 (11), 1391−1398. (55) Hou, J. J.; Cui, Z. Y.; Xie, Z. S.; Xue, P.; Wu, P.; Chen, X. L.; Li, J.; Cai, T. X.; Yang, F. Q. Phosphoproteome analysis of rat l6 myotubes using reversed-phase c18 prefractionation and titanium dioxide enrichment. J. Proteome Res. 2010, 9 (2), 777−788. (56) Petersen, B.; Petersen, T. N.; Andersen, P.; Nielsen, M.; Lundegaard, C. A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Struct. Biol. 2009, 9, 51. (57) Wagner, S. A.; Beli, P.; Weinert, B. T.; Nielsen, M. L.; Cox, J.; Mann, M.; Choudhary, C. A proteome-wide, quantitative survey of in vivo ubiquitylation sites reveals widespread regulatory roles. Mol. Cell Proteomics 2011, 10, M111.013284. (58) Tamura, K.; Dudley, J.; Nei, M.; Kumar, S. MEGA4: Molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 2007, 24 (8), 1596−1599. (59) Via, A.; Diella, F.; Gibson, T. J.; Helmer-Citterich, M. From sequence to structural analysis in protein phosphorylation motifs. Front. Biosci. 2011, 16, 1261−1275. (60) Linding, R.; Jensen, L. J.; Ostheimer, G. J.; van Vugt, M. A. T. M.; Jorgensen, C.; Miron, I. M.; Diella, F.; Colwill, K.; Taylor, L.; Elder, K.; Metalnikov, P.; Nguyen, V.; Pasculescu, A.; Jin, J.; Park, J. G.; Samson, L. D.; Woodgett, J. R.; Russell, R. B.; Bork, P.; Yaffe, M. B.; Pawson, T. Systematic discovery of in vivo phosphorylation networks. Cell 2007, 129 (7), 1415−1426. (61) Chou, M. F.; Schwartz, D. Biological sequence motif discovery using Motif-X. In Current Protocols in Bioinformatics; Wiley and Sons: New York, 2011; Chapter 13, Unit 13, pp 15−24. (62) Marin, O.; Bustos, V. H.; Cesaro, L.; Meggio, F.; Pagano, M. A.; Antonelli, M.; Allende, C. C.; Pinna, L. A.; Allende, J. E. A noncanonical sequence phosphorylated by casein kinase 1 in betacatenin may play a role in casein kinase 1 targeting of important signaling proteins. Proc. Natl. Acad. Sci. U. S. A. 2003, 100 (18), 10193−10200. (63) Johnson, L. N.; Lewis, R. J. Structural basis for control by phosphorylation. Chem. Rev. 2001, 101 (8), 2209−2242. (64) Iakoucheva, L. M.; Radivojac, P.; Brown, C. J.; O’Connor, T. R.; Sikes, J. G.; Obradovic, Z.; Dunker, A. K. The importance of intrinsic disorder for protein phosphorylation. Nucleic Acids Res. 2004, 32 (3), 1037−1049. (65) Manning, G.; Plowman, G. D.; Hunter, T.; Sudarsanam, S. Evolution of protein kinase signaling from yeast to man. Trends Biochem. Sci. 2002, 27 (10), 514−520. 2522
dx.doi.org/10.1021/pr401290u | J. Proteome Res. 2014, 13, 2511−2523
Journal of Proteome Research
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(66) Turkina, M. V.; Kargul, J.; Blanco-Rivero, A.; Villarejo, A.; Barber, J.; Vener, A. V. Environmentally modulated phosphoproteome of photosynthetic membranes in the green alga Chlamydomonas reinhardtii. Mol. Cell Proteomics 2006, 5 (8), 1412−1425. (67) Wagner, V.; Gessner, G.; Heiland, I.; Kaminski, M.; Hawat, S.; Scheffler, K.; Mittag, M. Analysis of the phosphoproteome of Chlamydomonas reinhardtii provides new insights into various cellular pathways. Eukaryotic Cell 2006, 5 (3), 457−468. (68) Wagner, V.; Ullmann, K.; Mollwo, A.; Kaminski, M.; Mittag, M.; Kreimer, G. The phosphoproteome of a Chlamydomonas reinhardtii eyespot fraction includes key proteins of the light signaling pathway. Plant Physiol. 2008, 146 (2), 772−788. (69) Tian, M.; Chen, X.; Xiong, Q.; Xiong, J.; Xiao, C.; Ge, F.; Yang, F.; Miao, W. Phosphoproteomic analysis of protein phosphorylation networks in Tetrahymena thermophila, a model single-celled organism. Mol. Cell Proteomics 2014, 13, 503−519. (70) Bodenmiller, B.; Wanka, S.; Kraft, C.; Urban, J.; Campbell, D.; Pedrioli, P. G.; Gerrits, B.; Picotti, P.; Lam, H.; Vitek, O.; Brusniak, M. Y.; Roschitzki, B.; Zhang, C.; Shokat, K. M.; Schlapbach, R.; ColmanLerner, A.; Nolan, G. P.; Nesvizhskii, A. I.; Peter, M.; Loewith, R.; von Mering, C.; Aebersold, R. Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast. Sci. Signalling 2010, 3 (153), rs4. (71) Hildebrand, M. Cloning and functional characterization of ammonium transporters from the marine diatom Cylindrotheca fusiformis (Bacillariophyceae). J. Phycol. 2005, 41 (1), 105−113. (72) Goulian, M. Two-component signaling circuit structure and properties. Curr. Opin. Microbiol. 2010, 13 (2), 184−189. (73) Armbrust, E. V.; Berges, J. A.; Bowler, C.; Green, B. R.; Martinez, D.; Putnam, N. H.; Zhou, S.; Allen, A. E.; Apt, K. E.; Bechner, M.; Brzezinski, M. A.; Chaal, B. K.; Chiovitti, A.; Davis, A. K.; Demarest, M. S.; Detter, J. C.; Glavina, T.; Goodstein, D.; Hadi, M. Z.; Hellsten, U.; Hildebrand, M.; Jenkins, B. D.; Jurka, J.; Kapitonov, V. V.; Kroger, N.; Lau, W. W.; Lane, T. W.; Larimer, F. W.; Lippmeier, J. C.; Lucas, S.; Medina, M.; Montsant, A.; Obornik, M.; Parker, M. S.; Palenik, B.; Pazour, G. J.; Richardson, P. M.; Rynearson, T. A.; Saito, M. A.; Schwartz, D. C.; Thamatrakoln, K.; Valentin, K.; Vardi, A.; Wilkerson, F. P.; Rokhsar, D. S. The genome of the diatom Thalassiosira pseudonana: ecology, evolution, and metabolism. Science 2004, 306 (5693), 79−86. (74) Glickman, M. H.; Ciechanover, A. The ubiquitin-proteasome proteolytic pathway: destruction for the sake of construction. Physiol. Rev. 2002, 82 (2), 373−428. (75) Beopoulos, A.; Mrozova, Z.; Thevenieau, F.; Le Dall, M. T.; Hapala, I.; Papanikolaou, S.; Chardot, T.; Nicaud, J. M. Control of lipid accumulation in the yeast Yarrowia lipolytica. Appl. Environ. Microbiol. 2008, 74 (24), 7779−7789. (76) Allen, A. E.; LaRoche, J.; Maheswari, U.; Lommer, M.; Schauer, N.; Lopez, P. J.; Finazzi, G.; Fernie, A. R.; Bowler, C. Whole-cell response of the pennate diatom Phaeodactylum tricornutum to iron starvation. Proc. Natl. Acad. Sci. U. S. A. 2008, 105 (30), 10438−10443. (77) Brakemann, T.; Schlörmann, W.; Marquardt, J.; Nolte, M.; Rhiel, E. Association of fucoxanthin chlorophyll a/c-binding polypeptides with photosystems and phosphorylation in the centric diatom Cyclotella cryptica. Protistology 2006, 157 (4), 463−475. (78) Liscum, E.; Briggs, W. R. Mutations in the NPH1 locus of Arabidopsis disrupt the perception of phototropic stimuli. Plant Cell 1995, 7 (4), 473−485. (79) Baum, G.; Long, J. C.; Jenkins, G. I.; Trewavas, A. J. Stimulation of the blue light phototropic receptor NPH1 causes a transient increase in cytosolic Ca2+. Proc. Natl. Acad. Sci. U. S. A. 1999, 96 (23), 13554−13559. (80) Chung, C. C.; Hwang, S. P. L.; Chang, J. Nitric oxide as a signaling factor to upregulate the death-specific protein in a marine diatom, Skeletonema costatum, during blockage of electron flow in photosynthesis. Appl. Environ. Microbiol. 2008, 74 (21), 6521−6527. (81) Niyogi, K. K. Photoprotection revisited: genetic and molecular approaches. Annu. Rev. Plant Physiol.: Plant Mol. Biol. 1999, 50, 333− 359.
(82) Vardi, A.; Bidie, K. D.; Kwityn, C.; Hirsh, D. J.; Thompson, S. M.; Callow, J. A.; Falkowski, P.; Bowler, C. A diatom gene regulating nitric-oxide signaling and susceptibility to diatom-derived aldehydes. Curr. Biol. 2008, 18 (12), 895−899.
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dx.doi.org/10.1021/pr401290u | J. Proteome Res. 2014, 13, 2511−2523