iTRAQ-based proteomic analysis of the metabolism mechanism associated with silicon response in the marine diatom Thalassiosira pseudonana.

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iTRAQ-based proteomic analysis of the metabolism mechanism associated with silicon response in the marine diatom Thalassiosira pseudonana Chao Du, Jun-Rong Liang, Dan-Dan Chen, Bin Xu, Wen-Hao Zhuo, Ya-Hui Gao, Chan-Ping Chen, Chris Bowler, and Wen Zhang J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 27 Dec 2013 Downloaded from http://pubs.acs.org on January 5, 2014

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Journal of Proteome Research

iTRAQ-based proteomic analysis of the metabolism mechanism associated with silicon response in the marine diatom Thalassiosira pseudonana Chao Du1, Jun-Rong Liang1,2*, Dan-Dan Chen1,a, Bin Xu1,b, Wen-Hao Zhuo1, Ya-Hui Gao1,2, Chan-Ping Chen1,2, Chris Bowler3, Wen Zhang1 1. School of Life Sciences, Xiamen University, Xiamen 361005, China 2. Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, Xiamen University, Xiamen 361005, China 3. Environmental and Evolutionary Genomics Section, Institut de Biologie de l’Ecole Normale Supérieure (IBENS), CNRS UMR8197 INSERM U1024, Ecole Normale Supérieure, 46 rue d’Ulm, 75005, Paris, France *Corresponding author: [email protected]; Tel: 86 592 2184368; Fax: 86 592 2181386 a. Current address: Hainan Provincial Marine Development Plan and Design Research Institute, Hainan 570125, China b. Current address: Guangdong Hisenor Group Co., Ltd, Guangdong 511405, China

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KEYWORDS Proteomics; Diatoms; Thalassiosira pseudonana; Intracellular silicon response; Biosilicification.

ABSTRACT

Silicon is a critical element for diatom growth, however our understanding of the molecular mechanisms involved in intracellular silicon responses are limited. In the study, an iTRAQ-LC-MS/MS quantitative proteomic approach was coupled with an established synchrony technique to reveal the global metabolic silicon-response in the model diatom Thalassiosira pseudonana subject to silicon starvation and re-addition. Four samples, which corresponded to the time of silicon starvation, girdle band synthesis, valve formation, and right after daughter cell separation (0,1,5,7 h), were collected for the proteomic analysis. The results indicated that a total of 1,831 proteins, representing 16% of the predicted proteins encoded by the T. pseudonana genome, could be identified. Of the identified proteins, 165 were defined as being differentially expressed proteins, and these proteins could be linked to multiple biochemical pathways. In particular, a number of proteins related to silicon transport, cell wall synthesis, and cell-cycle progress could be identified. In addition, other proteins that are potentially involved in amino acid synthesis, protein metabolism, and energy generation may have roles in the cellular response to silicon. Our findings provide a range of valuable information that will be of use for further studies of this important physiological response that is unique to diatoms.


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INTRODUCTION Diatoms are among the most successful eukaryotic phytoplankton in the contemporary oceans and account for 40% of the global primary productivity in the ocean1. These organisms are distributed throughout the ocean and freshwater environments and are especially predominant in continental margins, upwelling areas, and along the sea-ice edges2. Because of their important roles in marine ecosystems, diatoms are expected to employ distinctive strategies to adapt and survive under rapid and intense environmental fluctuations3. For example, diatoms can acclimate quickly to iron and phosphorus scarcity through the reallocation or maintenance of intercellular reservoirs4-6. Furthermore, it was revealed that diatoms can recover faster from silicon starvation than from nitrogen starvation7. Such unique abilities could be important traits that enable diatoms to outcompete other phytoplankton in the formation of a bloom or maintain their predominant position in marine ecosystems. However, despite the evident success of diatoms, very little is known about their metabolic characteristics at a detailed molecular level. Diatoms are also important components of the organismal groups involved in the silicon biogeochemical cycle in the oceans due to their compulsive requirement for silicon to generate their siliceous cell wall (frustule). The formation of siliceous cell wall structures of these organisms is very well controlled, enabling them to form unique and exquisitely patterned species-specific forms, which are composed of two halves (thecae) that are connected by hoop-like silicic structures known as girdle bands8. The diatoms’ success may be due in part to their use of a silicified cell wall, which is believed to impart a substantial energy savings and provide protection from predators and grazers9-11. Diatom silicon metabolism differs from that of other essential nutrients such as nitrogen and phosphate10,12. Thus, based on available


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information, it is believed that three major cellular process are closely associated with the silicon response, they are: cell cycle progression, silicon transport, and cell wall formation13. The cell cycle of diatoms follows the same pattern as the cell cycle of eukaryotes. The mitotic cell cycle includes successive rounds of the S (DNA synthesis) and M phases (mitosis), which are separated from each other by the gap phases of G1 and G214. Previous studies have revealed that almost all diatoms exhibit a dependency on silicon for cell cycle progression. The cell cycle would be arrested at particular stages under silicon limitation or starvation, and can be re-initiated by silicon15. The key cell cycle regulators, including cyclins, cyclin-dependent kinases (CDKs), and CDK interactors, as well as a large number of diatom-specific cyclins, were identified in the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum through profile-based annotation of the cell cycle genes16. The mechanisms of how silicon availability controls the cell cycle arrest and progression, and how the cell cycle-related genes respond to silicon nonetheless remain unknown. In principle, silicon transport includes two cellular activities: the transport of silicon from the surrounding media into the cytoplasm17-18, and the transport of imported silicon to the silica deposition vesicle (SDV) to form the new cell wall8. The active transport of silicon is necessary because the silicic acid concentrations in natural waters are often low19-20. The multilevel regulations of SITs, as well as their transport activities, were examined recently on synchronized T. pseudonana and P. tricornutum21-22. It has been suggested that intracellular silicon storage pools in diatoms is required for the production of new valves20,23. The silicon is then transported into the SDV, where the new cell wall is synthesized by the precipitation of silica nanospheres through interactions with multiple organic components24-25. However, the mechanisms


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underlying intracellular silicon processing, transport, and transfer into the SDV are rather poorly understood20,26. Cell wall formation, which mainly comprises valve and girdle band synthesis, occurs inside the expanding SDV during each cell division cycle8,27. As soon as cell wall synthesis is completed, the new cell walls are secreted from the cell8,28. The cell wall structure in diatoms covers three scales, nanoscale, microscale, and mesoscale8,29-31. However, many of the details are only partially understood. To date, several proteins and components that are specifically involved in cell wall formation have been described: silaffins, long chain polyamines32-34, silacidins35, pleuralins36-37, cingulins38, and frustulins39-40. Nevertheless, most of these detected proteins were extracted from the siliceous cell wall structure and so are unlikely to represent all of the components involved in cell wall synthesis. Based on the complexity of the biological process related to cell wall synthesis, the exploration of additional candidate proteins or genes that are closely related with the cell wall synthesis process is an urgent need. The available complete genome sequence of the diatoms T. pseudonana41-42 and P. tricornutum42 provide an opportunity to examine the complex cellular processes using whole-genome or whole-proteome expression profiling technology. Genomics, transcriptomics, and proteomics approaches have recently been used to identify a number of candidate proteins that are potentially involved in silicon metabolism in diatoms12-13,22,31,43. Those previous investigations not only increased our knowledge of the molecular metabolism of silicon response but also confirmed the complexity of the molecular basis of diatom biosilicification. Using these approaches in future studies may illuminate aspects of the diatom silicon response process as yet undiscovered.


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The goal of proteomics studies is to get a comprehensive description of proteins under the specific environment or treatment, including quantitative and active information as well as protein-protein interactions44. The very recent development of isobaric tags for relative and absolute quantitation (iTRAQ) proteomic methods allows unbiased observations associated with relative protein abundances in a cell at the time of harvest45-47 and is well-suited for the examination of changes in the whole-cell proteomic profile under different environmental conditions. Although there are many limitations in proteomics studies, for example, protein abundance can be affected by altered protein stabilities, and do not necessarily represent the activity of the proteins. It nonetheless is a more direct way to clarify cellular functions than mRNA-based studies because protein levels are one step closer to protein function than mRNA. iTRAQ was recently employed in phytoplankton research, including cyanobacteria48-49. Notably, iTRAQ has also been shown to be a very promising approach in diatom research, as was proven by the recent study on the response of T. pseudonana to benzo(a)pyrene that was conducted by Carvalho and co-workers 50. In this study, an iTRAQ-LC-MS/MS proteomics approach was employed to analyze a synchronized culture of T. pseudonana. The purposes of this investigation were to reveal the intracellular processes induced in response to silicon and during cell cycle progression at the molecular level and to characterize new candidate proteins that are potentially involved in the silicon response. The results indicated that various changes occur in the biological processes involved in the responses of diatoms to silicon, including cell cycle progression, silicon transport, and cell wall synthesis. Therefore, the present investigation yields valuable insights into the intracellular metabolic mechanisms related to the silicon response, and facilitates a


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deeper understanding of the mechanisms underlying the successful viability of diatom in the marine ecosystem.

MATERIALS AND METHODS Culture Conditions Thalassiosira pseudonana (Hust.) Hasle et. Heimdal (strain CCMP 1335) was obtained from the Provasoli-Guillard National Center for Marine Algae and Microbiota (NCMA, formerly known as the CCMP, https://ncma.bigelow.org/), and maintained in enriched artificial seawater (ESAW) medium51. The cells used in this investigation were cultured in ESAW under continuous light at an intensity of approximately 50 µmol photons m-2 s-1 and at a temperature of 18 °C. The ESAW media, including the silicon-free medium used in our experiment, was aerated for at least 12 hours before inoculation.

Synchronization Procedure The synchronized growth of T. pseudonana cultures was conducted as previously described52 with little modifications. The main difference in the synchronization procedure between the present investigation and the previous study conducted by Hildebrand and co-workers52 were the lower light intensity, the different culture medium used, the absence of stirring and consequent difference in aeration (the aeration was nonetheless sufficient to prevent the cells from aggregating or sinking).

Fluorescence and Bright field Microscopy


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PDMPO [(2-(4-pyridyl)-5-((4-(2-dimethy-laminoethylamino-carbamoyl)methoxy)phenyl)oxazole), AAT Bioquest, Inc.] is a fluorescent dye that can interact with polymeric silicic acid and is effective in imaging newly deposited silica in living cells53. PDMPO was added to the medium to 1 µM final concentration prior silicate addition. For each sample, 2 ml medium was collected, fixed by 4% paraformaldehyde and observed under fluorescence microscope (Olympus BX-41, Olympus, Inc.). Fluorescence and bright field Images were taken for the same vision and analyzed by Image-pro (Media Cybernetics, Inc.). For each sample, 100 cells was observed carefully under 1,000 X magnification and classified based on the PDMPO incorporation feature of each cell. The cells were classified as follows: with no PDMPO fluorescence, with ring shaped PDMPO fluorescence in the center (girdle band), with plate-shaped PDMPO fluorescence in the center (girdle band & valve), with plate-shaped PDMPO fluorescence in one end of the cell (single valve), with plate-shaped PDMPO fluorescence in one end of the cell and a ring shaped in the center (new girdle band), with plate-shaped PDMPO fluorescence both in one end and the center of the cell (new valves).

Protein Extraction and iTRAQ labeling According to the cell cycle progression during our synchronization experiment, four sampling time points (0 h, 1 h, 5 h, and 7 h) were chosen to investigate the expression of cell wall synthesis-related proteins. At each time point, approximately 1 liter of culture was harvested by filtering through a 2-µm pore-size filter membrane. The membrane was then introduced into a 15-ml centrifugal tube and the cells was resuspended into 10 ml medium, the membrane was then disposed of. The tube was centrifuged at 3,000 × g for 5 minutes. After the supernatant was


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discarded, 10 ml of TRIzol Reagent (Invitrogen, Life Technologies) was added, and the protein was then extracted according to the manufacturer’s recommendations. The protein pellets were suspended in Lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris-HCl, pH 8.5). The samples were then incubated with 10 mM DTT at 56 °C for 1 hour to reduce the disulfide bonds. Then, 55 mM IAM was added, and the samples were incubated in the dark for 45 minutes to block the cysteine residues of the proteins. The samples were then pelleted using chilled acetone and reconstituted in 0.5 M TEAB (triethylammonium bicarbonate, Applied Biosystems). The supernatant was then quantified using the Bradford Protein Assay Kit. 100 µg of proteins were digested with Trypsin Gold (Promega) and dried through vacuum centrifugation, reconstituted in 0.5 M TEAB, and processed according to the manufacturer’s recommendations for 8-plex iTRAQ (Applied Biosystems, Foster City, CA, USA). Eight samples (two biological replicates for four time point samples) were labeled with different iTRAQ tags.

Fractionation and LC-ESI-MS/MS analysis The labeled peptide mixtures were pooled, dried through vacuum centrifugation, and fractionated by SCX (Strong Cationic Exchange) chromatography using the Shimadzu LC-20AB HPLC pump system (Shimadzu). The fractionated peptides were reconstituted in 4 ml of buffer A (25 mM NaH2PO4 in 25% ACN, pH 2.7) and loaded onto a 4.6 × 250 mm Ultremex SCX column containing 5-µm particles (Phenomenex). Fractions were collected every minute. The eluted peptides were pooled as 12 fractions, desalted with a Strata X C18 column (Phenomenex), and vacuum-dried.


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Each fraction was re-suspended in a certain volume of solution A (5% ACN and 0.1% FA) and was loaded on a Shimadzu LC-20AD nano HPLC by the auto-sampler onto a C18 trap column, and the peptides were eluted onto an analytical C18 column (inner diameter of 75 µm) that was packed in-house. The samples were loaded at a rate of 8 µl/min for 4 min. Then, the 40-min gradient was run at a rate of 30 nl/min starting from 2% to 35% solution B (95% ACN and 0.1% FA), followed by a 5-min linear gradient to 80% solution B, maintenance at 80% solution B for 4 min, and return to 5% in 1 min. The peptides were subjected to nanoelectrospray ionization followed by tandem mass spectrometry (MS/MS) in a Q Exactive (Thermo Fisher Scientific, San Jose, CA, USA) coupled online to the HPLC. Intact peptides were detected in the orbitrap at a resolution of 70,000. The peptides were selected for MS/MS using the high-energy collision dissociation (HCD) operating mode with a normalized collision energy setting of 27.0 and a stepped NCE of 12.0%. The ion fragments were detected in the orbitrap at a resolution of 17,500. A data-dependent procedure that alternated between one MS scan followed by 15 MS/MS scans was applied for the 15 most abundant precursor ions above a threshold ion count of 20,000 in the MS survey scan with a subsequent dynamic exclusion duration of 15 seconds.

Data Analysis The instrument data file for each fraction was merged and transformed using the Proteome Discoverer software (ver. 1.3.0.339; Thermo Fisher Scientific, San Jose, CA, USA). The peptide and protein identifications were performed using the Mascot search engine (ver. 2.3.0; Matrix Science, London, UK). Gene ontology enrichment analysis was used first to map all of the identified proteins to GO terms in the database (http://www.geneontology.org/). During this


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process, gene numbers were calculated for every term, and a hypergeometric test was then used to find the significantly enriched GO terms in the identified proteins compared with the genome background. The threshold P-value was set to 0.05.

Quantitative RT-PCR validation of iTRAQ data Quantitative RT-PCR analysis of the gene expression of seven randomly selected proteins and SIT2 was performed to verify the iTRAQ data. The primers were designed using Primer-BLAST54 (Table 1). Each primer pair was designed to span at least one exon-exon junction so that genome DNA digestion was not needed. At each time point (0, 1, 2, 3, 4, 5, and 7 h), approximately 15 ml of culture was filtered and was rapidly placed in liquid nitrogen with the filter, grinded into powder, and immediately transferred to TRIzol Reagent (Invitrogen, Life Technologies). The total RNA was then extracted according to the manufacturer’s recommendations. The cDNA was synthesized immediately after the RNA was extracted (ReverTra Ace® qPCR RT Kit, TOYOBO, Japan). The quantitative PCR was performed with a Rotor-Gene 6000 system (Corbett Life Science) using the SYBR® Green Real-time PCR Master Mix (TOYOBO, Japan). Each gene was triply detected simultaneously with an inner control gene.

RESULTS AND DISCUSSION Cell synchronization In order to determine the most informative times during cell cycle progression to perform proteomic analysis of the silicon response, we first examined the process empirically. Following release from silicon starvation13,52, the cell cycle of most T. pseudonana cells would be started


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from G1 phase13,52. The cells started to synthesis their girdle band first at G1 phase, followed by valve synthesis at G2 + M phase13,52. Thus, the newly formed silicon structure was stained using fluorescent dye PDMPO. Depending on cell wall synthesis status marked by PDMPO, the cells were classified and counted (Figure 1, 2). The result was consistent with previous study done by Hildebrand et al.52. Figure 2 shows that more than 80% cells started to synthesis their girdle bands after 1 hour of silicon replenishment, indicating a G1 restriction point. While at the 5th hour, about 70% cells were synthesizing their new valve, and after 7 hours, most cells were separated. We therefore assigned 0 h, 1 h, 5 h and 7 h as corresponding to silicon starvation, girdle band synthesis, valve formation, and the time after daughter cell separation. These times were therefore selected for the proteomic analysis reported in this study.

General Information on iTRAQ Analysis A total of 356,684 spectra were obtained from the iTRAQ-LC-MS/MS proteomic analysis of four samples collected 0 h, 1 h, 5 h, and 7 h after synchronization. After eliminating the low-scoring spectra, 19,490 unique spectra met the confidence criteria (see Materials and Methods) and were matched to 1,831 proteins, which correspond to slightly more than 16% of the 11,390 predicted or hypothetical proteins encoded by the T. pseudonana genome. Among all of the proteins identified, we found that 1,303 proteins could be relatively quantified in all four samples. Figure 3 shows the basic information from the iTRAQ-LC-MS/MS data. The molecular weights of most of the identified proteins (63%, Figure 3 A) were between 20 and 70 kDa. The analysis of the distribution of the sequence coverage of the identified peptides revealed that 68% of the identified proteins have a coverage higher than 5% (Figure 3 B), which indicates a good


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quality of the data. The reproducibility of the analysis was evaluated by comparing the differences between two biological replicates of each sample (Figure 3 C). The results showed that more than 75% of the proteins exhibited differences of less than 0.2 and that more than 95% of the proteins exhibited differences of less than 0.5. These results suggest that the reproducibility of the analysis was satisfactory. Concerning the COG coverage of the identified proteins, a total of 1,221 proteins could be matched to 23 clusters (Figure 4) and that only two clusters were missing (“nuclear structure” and “extracellular structures”), which could either be due to both the limitation of the method and the poor annotation of the genome. The most frequently detected clusters were “post-translational modification, protein turnover, and chaperones” and “translation and ribosomal structure and biogenesis”, and these corresponded to 15.07% and 14.33% of all of the proteins with a matched COG definition, respectively. Other clusters crucial to diatom cell cycle progression and cell wall synthesis could also be matched with a significant number proteins. These included “cell cycle control, cell division, and chromosome partitioning” (11 proteins), “cell wall/membrane/envelope biogenesis” (34 proteins), and “intracellular trafficking, secretion, and vesicular transport” (27 proteins). Using a cut-off of 1.5-fold and a P-value of less than 0.05, we identified 247 differentially expressed proteins in multiple comparisons between each sample from T. pseudonana. The highest number of differentially expressed proteins was the sample pair composed of the 1 h and 7 h time points (52 upregulated and 38 downregulated proteins), followed by the sample pair composed of the 0 h and 7 h time points (44 upregulated and 27 downregulated). This finding indicates the metabolism activities between these time points show the largest differences. On the other hand, the sample pair composed of the 0 h and 1 h time points showed the minimum


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number of differentially expressed proteins (6 upregulated and 3 downregulated proteins), which could be due to the low metabolic activity of the cells following 24 hours of silicon starvation. In total, 165 proteins that displayed significant differences in at least one sample pair comparison were obtained (Supplementary Material 1). This 165-protein set was named the differently abundant protein (DAP) dataset, and is further investigated below.

Quantitative RT-PCR validation To validate the quantitative results from the iTRAQ analysis, a subset of seven randomly selected genes and SIT2 (Thaps3|41392) were processed through quantitative RT-PCR (Q-PCR) analysis. Primers were designed specifically for Q-PCR using primer-BLAST54, the sequences were listed in Table 1. Although protein abundance may not necessarily correlate with mRNA abundance, six of our quantitative RT-PCR results (Thaps3|25206, 20613, 268480, 20931, 5063, and 41392) were somewhat consistent with the iTRAQ data, while two of them (Thaps3|268546, 8571) were not (Figure 5)

Cell Cycle Proteins To date, seven CDKs, 48 cyclin-like proteins, and several other cell cycle-related proteins have been identified in the T. pseudonana genome55. Among the proteins in the DAP dataset, we found just one CDK protein: Thaps3|35387. This protein is a homolog of the cell division control protein CDKA2 in P. tricornutum16 and contains the PSTALRE cyclin-binding motif, which is evolutionary halfway between the CDKA and the CDKB hallmarks and is a common feature of diatom CDKs16. From our data, Thaps3|35387 was upregulated and reached its maximum abundance at 5 h, corresponding to G2 + M phase of cell cycle. This protein then downregulated


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at 7 h, when mitosis had been completed (Figure 6 A). This result was consistent with the CDKA2 expression level observed previously in P. tricornutum16, in which the mRNA level was upregulated in G2 + M phase. Another cell cycle-related protein, Thaps3|38460, is annotated as “S-phase kinase-associated protein 1” and is a homologue of the S-phase kinase-associated protein 1 (Skp1) in Rattus norvegicus. One alternative name of Skp1 is Cyclin-A/CDK2-associated protein p19. Skp1 is an essential component of the SCF (SKP1-CUL1-F-box protein) ubiquitin ligase complex, which mediates the ubiquitination of proteins involved in S phase and/or G2 phase cell cycle progression, and controls the transitions between G1/S and G2/M56. Skp1 in our study was increasingly upregulated from 0 h to 7 h (Figure 6 A). The data shows Skp1 protein abundance does not respond to G1/S or G2/M transition in T. pseudonana, thus the function of this protein in diatom still needs to be studied.

Silicon Transporters and Co-regulated Proteins Silicon Transporters. Silicon transporters (SITs) in diatoms are membrane-associated proteins that are responsible for silicon transport through the plasma membrane, directly and specifically interact with silicic acid17. Subsequently, this specific protein family was found in different diatom species, including the centric diatoms T. pseudonana and Chaetoceros muelleri and the pennate diatoms P. tricornutum and Synedra acus42,58-59. Three SIT encoding genes were found in the T. pseudonana (CCMP 1335) genome. Previous investigation, which directly examined the SIT protein expression level using immunoblot analysis with the SIT-specific antibody anti-TpEL4, showed that SIT proteins is internally controlled by the rate of silica incorporation21. However, the results obtained by Thamatrakoln and co-workers could not distinguish the


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expression levels of the three SIT proteins separately, because the anti-TpEL4 antibody was designed to recognize all three SITs together21. Two of the SITs could be found in our data set, SIT1 (Thaps3|268895) and SIT2 (Thaps3|41392) albeit not SIT3. For SIT1, only one quantitation spectrum was identified, so the relative quantitation was not possible. On the contrary, SIT2 abundance was readily detectable and is shown in Figure 6 B. The abundance of SIT2 protein peaked at 1 h (1.46-fold of that observed at 0 h), possibly responding girdle band synthesis, then it dropped by 5 h (1.151-fold of that observed at 0 h), when valve synthesis was taking place. By the time mitosis had finished (7 h), SIT2 abundance had decreased to levels below those observed at 0 h (0.79-fold), which indicates a reduced demand for SIT2 at this time. To our knowledge, our data are the first description of the profile of SIT2 protein abundance during cell cycle progression.

SIT2 Co-regulated Proteins. Because many diatom silicon-response genes or proteins (cell wall synthesis-related genes) are unlikely to have homologs in other organisms, one practical approach for their identification is to identify genes/proteins that display similar patterns of expression to a diagnostic gene/protein13. This approach can permit the identification of interesting candidates that can then be targeted for further verification studies. On the other hand, this approach can also be used as a way to explore the specific function of selected genes/proteins. It is known that SIT protein abundance is not related with cellular silicon demands18, but is possibly controlled by silicon incorporation21. Thus, the analysis of the co-regulated proteins could provide information about some other information about how SIT2 related to silicon incorporation. We therefore performed a correlation analysis using the online tool PaGeFinder60 to find SIT2 co-expressed proteins in our iTRAQ data. A total of 69 proteins


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with a high correlation factor (>0.9) was found among the 1,303 quantized proteins (Supplementary Material 2). To verify the functions of these 69 proteins, GO enrichment analysis was conducted. With a cut-off P-value of 0.05, a set of enriched ontology terms and related proteins were obtained, which included 16 component ontology terms (Supplementary Material 3). Interestingly, of these 16 component ontology terms, 15 were related to the vesicle or membrane, and the most enriched cell component term (with the smallest P-value) was “coated vesicle” (Thaps3|269663, 39913, 26212, 34876, and 269540) and will be discussed later in this paper. Despite these annotated proteins, we should note that, of the 69 proteins co-expressed with SIT2, 12 do not have any ontology annotation nor any detected conserved domains. These proteins can also be interesting targets for deciphering the diatom SIT2 mediated silicon transport mechanism in synchronized cultures. What’s more, the SIT2 protein and its similarly expressed proteins are down regulated at the time when the cells silicon incorporation process is most activated (5 h). Thus the correlation of the protein abundance of SIT2 and coatomers provided us a new view of understanding how each SITs might work. It indicates that SIT2 has a strong and tight relationship with the newly formed coated vesicles. One hypothesis is that the vesicles might have its membrane inserted with SIT2 and silicon can be transported into or out of the vesicles. Coated vesicles are vesicles that are enclosed by a protein complex called a vesicle coats, and the specific proteins that constitute vesicle coat are coatomer proteins. To our knowledge, vesicles are involved in multiple levels of biosilification processes, including SDV expansion, nanostructure shaping8, and cell wall components (possibly including silicon) delivery24,61-62. However, until now, it was unclear how and when coated or uncoated vesicles function during diatom cell wall synthesis. In general, there are three types of vesicle coats present in eukaryotic


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cells: COPI, COPII, and clathrin63. COPI and COPII are mainly responsible for budding vesicles from the Golgi apparatus and the endoplasmic reticulum, respectively. On the other hand clathrin, coupled with its adaptin, is involved in budding vesicles from various membrane systems, including the plasma membrane, trans-Golgi network, and endosomal compartments64. Of all the genes in T. pseudonana, 31 genes are annotated as coatomers, encoding six COPI subunit proteins, seven COPII subunit proteins, 17 clathrin subunit proteins, and one protein with both COPI and clathrin annotations. In our proteomic investigation, we observed all known COPI subunits, one COPII subunit, and six clathrin subunits (Table 2). It is interesting that the number of identified COPI and COPII proteins were so different. However, more importantly, four COPI subunits (Thaps3|269663, 39913, 26212, and 34876) and one clathrin subunit (Thaps3|269540) were co-expressed with SIT2 (Table 2, Figure 6 B) indicating the relationship of these proteins with cellular silicon transport system. It is generally believed that COPI is mainly responsible for the retrograde transport from the trans-Golgi apparatus to the cis-Golgi and ER65. On the other hand, clathrin is responsible for endocytosis from the plasma membrane and transport from the trans-Golgi to the lysosomes65. Because the SDV is known to share some common characteristics with lysosomes, such as acidic pH66, it is possible that this clathrin subunit is the carrier of essential SDV components (possibly including organic bonded silicon) from the trans-Golgi to the SDV. The results indicated that vesicle systems and SIT2 are closely connected. But, in order to deduce the relationship of coated vesicles and intracellular silicon transport, the intracellular localization of SIT2 as well as silicon are still needed.

Cell Wall Synthesis-related Proteins


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Of the cell wall proteins that are intrinsic to the cell wall structure (e.g., frustulins, silaffins, silacidins, and cingulins), only silaffin (tpSIL1, Thaps3|11360) was identified in our data. However, the protein level of tpSIL1 was not quantified because only one quantitation spectrum was detected. This failure on detecting cell wall proteins was consistent with a pervious iTRAQ study on the same diatom50. The reason for this failure is most likely because these proteins, located inside the siliceous cell wall structure, were lost with the cell wall during the protein extraction procedures. From another aspect, the absence of these proteins in proteomic studies indicate that these proteins are likely incorporated into the cell wall quite rapidly after they are synthesized in the cytoplasm. Silaffins are the most abundant protein components within the HF extract of the purified cell wall67. These proteins are rich in hydroxyl amino acids, including serine, threonine, and hydroxyproline. Silaffins 1 and 2 have a serine percentage of about 20% and a threonine percentage of about 14%. However, there are around 19% serines but only about 4% of threonines present in silaffin 368. These facts led us to examine the proteins that are involved in serine and threonine synthesis. In the DAP dataset, two such proteins were found: Thaps3|268970 and Thaps3|269704. Thaps3|268970 is a D-3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the first and rate-limiting step in the phosphorylated pathway of serine biosynthesis. Thaps3|269704 is a threonine synthase. The expression patterns of these two proteins are shown in Figure 7 (solid lines) coupled with other amino acid synthases found in the DAP dataset (dashed lines). Compared with the 1 h, it is clear that Thaps3|268970 was upregulated at 5 h, whereas most amino acid synthases were downregulated at this time point. Thaps3|269704 followed the downregulation trend of other proteins at 5 h but was still the second most upregulated synthase at 1 h (Thaps3|693 was the most upregulated and will be


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discussed later). The differences between the expression patterns of PHGDH and threonine synthase were most likely caused by the different requirements of these two amino acids at different times. Because cell wall synthesis was the most significant cellular process occurring at 1 h and 5 h and silaffin is the most abundant protein in the cell wall67, the differences between serine and threonine synthesis might indicate that the required combined amount of silaffins 1 and 2 (both are rich in serine and threonine) at 1 h and 5 h is different from that of silaffin 3 (rich only in serine). This suggestion is consistent with the mRNA expression patterns of SIL1 and SIL3 during girdle band and valve synthesis31. Most cells in our sample synthesized their girdle band at 1 h and synthesized their valve at 5 h. Given the expression patterns of PHGDH and threonine synthase, it was concluded that silaffins 1 and/or 2 were more preferable to function during girdle band synthesis, whereas silaffin 3 was more preferable during valve synthesis. However, this conclusion is highly speculative. We should note that the abundance of amino acid synthases are not always correlated with amino acid synthesizing speed. Also, the correlation between amino acid synthesizing speed and a specific protein is weak. Thus, our speculation needs further confirmation, but it is still valuable information given that the exact abundance of silaffins is still impossible to detect directly. One protein that co-localized with the girdle bands (Thaps3|26041) was detected in our dataset with good peptide coverage (19.7%). This protein can be induced by copper stress and is named p15069. Abundance of this protein stayed constant throughout the four time points, although it did exhibit a minor downregulation at 1 h (Figure 8 A), which showed no correlation with girdle band synthesis (1 h). This expression pattern was consistent with previous descriptions that p150 could be induced by silicon limitation beyond the level of basal expression69. Based on our data, the stable expression level of Thaps3|26041 suggests that the expression pattern of this


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copper-induced girdle band protein does not relate to the synthesis of the girdle band, although it appears to be associated with the girdle region during a particular phase of the cell cycle69. Our speculation is nonetheless not contradictory with the previous deduction that this protein may be involved in the division process, although the function of it can be altered by post-translational modifications or the formation of protein complexes which cannot be illustrated by abundance.

Diatom Silicon Starvation-related Proteins Of the proteins in the DAP dataset, we found that Thaps3|9619 was upregulated and that Thaps3|595 was downregulated specifically in 0 h sample compared with the three other samples (Figure 8 B). We consider these two proteins as silicon starvation-related proteins. Thaps3|9619 was a predicted protein with KOG (EuKaryotic Orthologous Groups) description of ‘Projectin/twitchin and related proteins’, and classified as cytoskeleton protein. It could participate in the cellular structure reallocation during silicon starvation environment. Thaps3|595 is a translation initiation factor (eIF-1A) and has a S1-like RNA-binding domain in its sequence. This protein is essential for the transfer of Met-tRNAf to 40 S ribosomal subunits to form the 40 S preinitiation complex in the absence of mRNA70. Translation initiation is one of the most important molecular processes in eukaryotes. Thus the downregulation of Thaps3|595 at 0 h indicates the tight correlation of some important translation events and silicon depletion.

Other Cellular Processes Correlated with Cell Cycle Progression In our data, methionine (Met) synthase I (Thaps3|693) was strongly induced at 1 h (more than 1.5-fold compared with that at 0 h) after silicon was added (Figure 7, dotted line), decreased to a relatively low level at 5 h, and was then upregulated again at 7 h. The function of this enzyme is


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both the de novo synthesis of Met and the regeneration of S-adenosylmethionine from S-adenosylhomocysteine after methylation reactions71. Met synthase I is related to cell cycle progression, its inhibition will cause G1/S phase delay and apoptosis72. Thus, this protein appears to be upregulated at the G1 and S phases, which is consistent with the upregulation of Thaps3|693 at 1 h and 7 h, when most cells were in G1 phase. Additionally, the methylation process is an important way of protein and gene modification. If protein stability and post-translational modifications were the same for Thaps3|693, it’s upregulation at 1 h may also be indicative of a dramatic change in cellular metabolism. Another possibility is that, because some silaffins are modified with methylation prior to activation35, the upregulation of Thaps3|693 in 1 h could be related to cell wall synthesis. There were 11 amino acid synthases detected in the DAP dataset. The profiles of these 11 proteins were not the same at 1 h. However, most of them were downregulated at 5 h and even further downregulated at 7 h (Figure 7, dashed lines). These expression patterns indicate that there was an overall downregulation of amino acid synthesis in the cells during the later times of synchronization. On the other hand, three proteasome subunit proteins found in the DAP dataset were upregulated at 1 h and 5 h (Figure 8 C), which suggests that the protein degradation activity increases during girdle band and valve formation. Coupled with the hypothesis that diatoms need to digest templating peptides as the pores form in the cell wall73, the presented data raises the hypothesis that, during cell wall formation after silicon was replenished, diatom cells may prefer to accelerate protein degradation to fulfill their amino acid need, instead of synthesizing new ones. In other words, the protein turnover rate may be upregulated during cell wall formation after silicon was replenished. But this hypothesis is only valid when the degradation matches the


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need. If the need for amino acids exceeds the degradation speed, it is possible that the amino acids were accumulated prior to cell division. Figure 9 shows the expression levels of all nine proteins related to energy production and conversion found in the DAP dataset. In general, these nine proteins were downregulated at 5 h and continued this trend at 7 h (Figure 9 A), which likely indicates a lagged response of the general energy metabolism after silicon is replenished. The downregulation of these proteins indicates that energy production and conversion might be decreased at the later time points, i.e., during valve synthesis and cell separation. While this interpretation lacks the support of energetics data, it should be tested further. Figure 9 B shows the abundance of the above 9 proteins separately during the time course. It is obvious that the different responses to silicon addition of these proteins caused the lag of the general response of energy metabolism. Of these proteins, three of them are associated with the citric acid cycle (Figure 9 B, dashed lines). Two of these were downregulated at 1 h, whereas the other protein was upregulated at 1 h. The two downregulated proteins are crucial in the citric acid cycle: the putative citrate synthase (Thaps3|11411) that catalyzes the rate-limiting step of the citric acid cycle and succinate dehydrogenase (Thaps3|42475), which is important in various biological processes74. The downregulation of Thaps3|11411 and Thaps3|42475 at 1 h might be a clear sign of the decreasing activity of the citric acid cycle. The other citric acid cycle protein that was upregulated at 1 h is aconitate hydratase (Thaps3|268965), which is responsible for catalyzing the non-rate limiting step in the citric acid cycle (citrate to D-isocitrate). Thus, its upregulation at 1 h is difficult to explain without other information about post-translational regulation. If the post-translational regulation state remained the same for this protein, one possible explanation that could be tested


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in the future is that citrate or D-isocitrate was increased are specifically required after silicon replenishment, perhaps for cell wall synthesis. Of the nine proteins related to energy production and conversion, two phosphoenolpyruvate carboxylases (PEPCs, Thaps3|268546 and 34543) are responsible for the CO2 concentration (Figure 9 B, dotted line). Recent investigations on the CO2 concentration mechanism in diatoms have shown that this mechanism in T. pseudonana does not respond to low CO2 concentrations75, but could be expressed at a relatively high level under mid-exponential growth47. Thus, our study provides another expression pattern of the T. pseudonana CO2 concentration system. It could imply that the high level of PEPCs under mid-exponential growth reflects a need for them at a specific time of the cell cycle. It has been indicated previously that cell cycle progression is intimately connected with chloroplast division76. In the DAP dataset, we found one FtsZ protein (Thaps3|35728) that was responsible for this process. In bacteria, it has been suggested that FtsZ is an essential cell division protein that is responsible for assembling the Z-ring during cytokinesis on the inner surface of the cytoplasmic membrane77. Conversely, in many eukaryotes, FtsZ is supposed to be responsible for organelle division78-79. The FtsZ-mediated Z-ring structure can promote organelle division by reducing its diameter and pulling the adjacent membranes to the center77. In the diatom Seminavis robusta, the expression levels of the FtsZ gene were used as a biomarker for chloroplast division and were found to be regulated in a cell cycle-dependent manner and upregulated at the S/G2 phase76. In our study, this protein was continuously downregulated after cell cycle progression reinitiated by silicon replenishment (Figure 10 A). This could be an indication that T. pseudonana cells complete chloroplast division independently of the presence of silicon.


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We also found six proteins that belong to the light harvesting complex (LHC) superfamily in the DAP dataset. The expression levels of these proteins are shown in Figure 10 B. These were all downregulated at 7 h after most cells completed mitosis, but their responses to silicon addition were significantly diverse at 1 h and 5 h. More precisely, the proteins that were downregulated at 1 h were upregulated at 5 h (Thaps3|268127, 39813, and 31749) (Figure 10 B, dashed lines), whereas the proteins that were upregulated at 1 h were downregulated at 5 h (Thaps3|262332, 34276, and 33131) (Figure 10 B, solid lines). This expression patterns indicate a potential complementary regulation among the LHC family proteins. There might therefore be some putative functional shift of LHC during the recovery from silicon-limited conditions and the cell wall synthesis process.

CONCLUSIONS The proteomic profiles of synchronized T. pseudonana cultures not only provides us with large-scale information about how the organism responds to silicon replenishment and cell cycle progression, but also the small-scale response patterns of specific proteins. Our observations provide new molecular views about what is known about cell wall synthesis and cell cycle progression responses in diatoms. A large amount of information about previously uncharacterized cellular processes and proteins with uncharacterized functions was also obtained, together with various proteins with uncharacterized domains having roles in known cellular processes. The continued analysis of these proteins is likely to reveal important information about diatom silicon metabolism and cell cycle progression in the future. Our analysis was mainly based on protein abundance, not their actual activities, thus other analysis techniques are needed for further verification. Finally, while our analysis is based principally on


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existing protein annotations and conserved domains found automatically in T. pseudonana, more than five hundred predicted/hypothetical proteins were found in our data that do not have any annotations or conserved domains. These proteins are also likely to be important and need to be further analyzed.

ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (NSFC, Grant No. 41276130), the national 973 project (Grant No. 2010CB428704 and 2011CB200901), the Fujian Province Science Fund for Distinguished University Young Scholars (Grant No. JA10001), and the NSFC (Grant No. 41076080 and 40676082). CB acknowledges the EU Micro B3 project, as well as the ERC “Diatomite” and ANR “DiaDomOil” projects for financial support. Special thanks to the two anonymous reviewers, we benefited greatly from their suggestions.


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Figure 1. Fluorescence micrographs and corresponding bright-field images of PDMPO stained T. pseudonana cells during synchronization. Collecting time is on the upright of each picture. White arrow shows the cell synthesizing its first girdle band; white arrow head shows girdle band synthesized; blue arrow head shows synthesizing valve. Bar = 10 µm


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100% No green fluorescence

80%

Precentage

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Girdle band

60%

Girdle band & Valve 40% Single valve 20%

New girdle band

0% 0

1

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8

9

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New valves

Hours after silicon replenishment

Figure 2. Percentage changes of cells with different dye incorporation type during synchronization. The T. pseudonana cells were stained with PDMPO. 100 cells were counted for each sample under Fluorescent Microscope with 1,000 X magnification. See Methods and Materials for the classification criterion. Generally “Girdle band” in legend entry represents the number of cells in Figure 1 b, d and f; “Girdle band & Valve” represents Figure 1 h; “Single valve” represents Figure 1 j. Other types are not presented in Figure 1.


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A) 350

312

300

Number of proteins

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 48 49 50 51 52 53 54 55 56 57 58 59 60


288 253 221

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82

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B) 3.28% 6.50%

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10%-15% 15%-20%

6.99%

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9.01%

30%-35% 35%-40% 13.16%

20.81%

40%-100%


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C)

100% 90%

Percentage of total proteins

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 48 49 50 51 52 53 54 55 56 57 58 59 60

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80% 75%

70% 60%

0h

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20% 10% 0% 0

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Delta error

Figure 3. General information of the iTRAQ-LC-MS/MS analysis of a synchronized T. pseudonana culture. A) Distribution of proteins of different molecular weights. B) Coverage of proteins by LC-MS/MS identified peptides. C) Repeatability of quantification data between two biological replicates for each time point.


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2.70% 14.33%

13.27%

1.88%

0.16% 4.50% 3.36%

3.28%

1.56%

3.11% 3.36% 2.05% 7.78% 15.07% 5.16%

0.90% 0.57% 2.70% 2.78% 0.08% 0.66% 2.21%

8.52%

Translation, ribosomal structure and biogenesis RNA processing and modification Transcription Replication, recombination and repair Chromatin structure and dynamics Cell cycle control, cell division, chromosome partitioning Defense mechanisms Signal transduction mechanisms Cell wall/membrane/envelope biogenesis Cell motility Cytoskeleton Intracellular trafficking, secretion, and vesicular transport Posttranslational modification, protein turnover, chaperones Energy production and conversion Carbohydrate transport and metabolism Amino acid transport and metabolism Nucleotide transport and metabolism Coenzyme transport and metabolism Lipid transport and metabolism Inorganic ion transport and metabolism Secondary metabolites biosynthesis, transport and catabolism General function prediction only Function unknown

Figure 4. Functional category (COG) coverage of proteins identified in the iTRAQ-LC-MS/MS analysis of a synchronized T. pseudonana culture.


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B)

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Figure 5. Comparison of the protein (histograms) and mRNA (lines) levels of A) Thaps3|5063, B) Thaps3|20613, C) Thaps3|20931, D) Thaps3|25206, E) Thaps3|268480, F) Thaps3|41392


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(SIT2), G) Thaps3|268546, H) Thaps3|8571, during T. pseudonana synchronization. The X axis is the time after silica was added, and the left Y axis shows the relative protein level, the right Y axis shows the relative mRNA level.


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A) 1.8

Relative protein level

1.6 1.4 1.2 1 0.8

Thaps3|35387

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Thaps3|269540_clathrin

1.4 Thaps3|269663_COPI

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1 0.8

Thaps3|26212_COPI


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Thaps3|41392_SIT2

Figure 6. Relative expression patterns of cell cycle proteins (A) and SIT2 co-regulated coatomers (B) during T. pseudonana synchronization. The protein level at 0 h were normalized to 1.


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1.7

Relative expression level

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 48 49 50 51 52 53 54 55 56 57 58 59 60


Thaps3|1247 Thaps3|20613 Thaps3|260953

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Thaps3|27892 Thaps3|2790 0.65

Thaps3|31394 Thaps3|36208

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Figure 7. Relative expression patterns of amino acid synthases during T. pseudonana synchronization. The solid lines show the levels of D-3-phosphoglycerate dehydrogenase (Thaps3|269704) and threonine synthase (Thaps3|268970, with an arrow). The dotted line shows methionine (Met) synthase I (Thaps3|693).


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A) Relative protein level

1.2 1 0.8 0.6 0.4

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C) 1.7


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Thaps3|26706

1.35 Thaps3|40483 1 Thaps3|517

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Figure 8. Relative expression pattern of proteins during T. pseudonana synchronization. A) p150, B) diatom silicon starvation-related proteins, C) proteasome subunits. The expression level at 0 h was set to 1.


37


A)

relative expression level

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1.2

Thaps3|268280

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Thaps3|547

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Thaps3|8778

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Thaps3|22527

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Thaps3|268546 Thaps3|34543

Figure 9. Relative expression patterns of energy production- and conversion-related proteins during T. pseudonana synchronization. The expression level at 0 h was set to 1. A) Average of the relative expression level. The error bars represent the strand deviation of the relative


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expression level of all nine proteins. B) Separate relative expression levels of the nine proteins. The major different occurs at 1 h. The dashed lines represent the citric acid cycle proteins (Thaps3|11411, 42475, and 268965), and the dotted lines represent the phosphoenolpyruvate carboxylases (Thaps3|268546 and 34543).


39



1.2 1 0.8 0.6

Thaps3|35728

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Thaps3|268127 Thaps3|39813

1

Thaps3|31749

0.8 Thaps3|262332

0.6


0.4 0

1

2

3

4

5

6

7


Figure 10. Relative expression pattern of FtsZ and fucoxanthin-chlorophyll a/c light-harvesting proteins during T. pseudonana synchronization. A) FtsZ B) fucoxanthin-chlorophyll a/c light-harvesting proteins. The expression level at 0 h was set to 1. The proteins that are upregulated at 1 h (B, solid lines) are Thaps3|268127, 39813, and 31749, and the proteins that are downregulated at 1 h (B, dashed lines) are Thaps3|262332, 34276, and 33131.


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Table 1. Design of primers used for quantitative PCR. Gene ID

Primer Sequence (5' - 3')

Thaps3|21599 (NADH: ubiquinone oxidoreductase subunit, inner control) Thaps3|5063 Thaps3|20613 Thaps3|20931 Thaps3|25206 Thaps3|268480 Thaps3|41392 (SIT2) Thaps3|268546 Thaps3|8571

Forward

GGAGCATATGTACACTAATGGAGAC

Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse Forward Reverse

GGGTAGTCTACGCGGTTTTC ATATGCAGGATCCTCAACTAATGG CATTTTGGCAGCTTCGTTGG CCCAACGCATTCGGTCTTAC TGGGATACGGAGCAAGCATT GAGAGGCGGATCAAGCATAC AAGCCCATCTCGTCGTAGTT AGCGTAGCCAGCAAGATGTA TACGAATGCGATGAGGCCAG CGTTTTGTGCATTGCTGCTT AGACAACATGATTAGTTGGCTTTC TCGTCTGTATTCTCGCCATC GTCTTTGTAGAGGGTGGGGT GGATGAACGGTTTGTTCCGT AGTCTGTTCGTCAGGACTGG TCCCCGGAGAGAACCGTTA CTTGCATCCAGCACATCCAG


41


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Page 42 of 69

Table 2. Coatomer proteins identified in the iTRAQ proteomic analysis of a synchronized T. pseudonana culture. Coatomer Complex

COPI

COPII

Clathrin

Protein ID

Description

Description Source

Thaps3|23050

Vesicle coat complex COPI, zeta subunit

KOG description

Thaps3|39615

coatomer protein subunit delta (deltaCOP) / Medium subunit of clathrin adaptor complex

JGI user annotations (Nils Kröeger, 2003-03-11) / KOG description

Thaps3|269663*

coatomer protein subunit gamma (gammaCOP)

JGI user annotations (Nils Kröeger, 2003-03-18)

Thaps3|34876*

coatomer protein subunit alpha (alphaCOP)


Thaps3|39913***

coatomer protein subunit epsilon (epsilonCOP)


Thaps3|22092**

coatomer protein subunit beta2 (beta2COP)


Thaps3|26212*

coatomer protein subunit beta 1 (beta1COP)


Thaps3|39497

Vesicle coat complex COPII, GTPase subunit SAR1

KOG description

Thaps3|269540*

clathrin heavy chain (human CLH1, CLH-17)

JGI user annotations (Anton Montsant, 2003-03-11)

Thaps3|37264

mu subunit of tetrameric clathrin adaptor complex AP1 (mu-adaptin, AP1M1, CLTNM)


Thaps3|10527

Vesicle coat protein clathrin, light chain

KOG description

Thaps3|269744

gamma subunit of tetrameric clathrin adaptor complex AP2 (APG2, AP2G1, CLAPG2, ADTG, gamma2-adaptin)


Thaps3|39615

coatomer protein subunit delta (deltaCOP) / Medium subunit of clathrin adaptor complex

JGI user annotations (Nils Kröeger, 2003-03-11) / KOG description

Thaps3|41687

beta subunit of tetrameric clathrin adaptor complex AP1 (APB1, AP1B1, BAM22, beta1-adaptin)


*

co-expressed with SIT2

**

DAP dataset

***

co-expressed with SIT2 and presented in DAP dataset


42

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Supporting Information This material is available free of charge via the Internet at http://pubs.acs.org. Supplementary Table 1. Differently expressed protein (DAP) dataset Supplementary Table 2. SIT2 co-expressed protein list Supplementary Table 3. GO enrichment analysis of SIT2 co-expressed proteins

AUTHOR INFORMATION Corresponding Author * Jun-Rong Liang, Associate professor, School of Life Sciences, Xiamen University, Xiamen 361005, China; Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, Xiamen University, Xiamen 361005, China. Tel: 86 592 2184368, Fax: 86 592 2181386, E-mail: [email protected] Present Addresses Dan-Dan Chen: Hainan Provincial Marine Development Plan and Design Research Institute, Hainan 570125, China Bin Xu: Guangdong Hisenor Group Co., Ltd, Guangdong 511405, China Author Contributions C. Du designed part of the experiments, performed the main part of the experiments, analyzed the data, and wrote the paper. J.R. Liang designed the experiments, analyzed the data, and wrote the paper. D.D Chen, B. Xu, W. H. Zhuo and W. Zhang performed part of the experiments. Y. H. Gao, C. P. Chen and C. Bowler revised the manuscript.


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Page 44 of 69

Funding Sources This work was supported by the National Natural Science Foundation of China (NSFC, Grant No. 41276130), the national 973 project (Grant No. 2010CB428704 and 2011CB200901), the Fujian Province Science Fund for Distinguished University Young Scholars (Grant No. JA10001), and the NSFC (Grant No. 41076080 and 40676082). CB acknowledges the EU Micro B3 project, as well as the ERC “Diatomite” and ANR “DiaDomOil” projects for financial support.


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Figure 1. Fluorescence micrographs and corresponding bright-field images of PDMPO stained T. pseudonana cells during synchronization. Collecting time is on the upright of each picture. White arrow shows the cell synthesizing its first girdle band; white arrow head shows girdle band synthesized; blue arrow head shows synthesizing valve. Bar = 10 μm



100% No green fluorescence

80%

Precentage

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 56 of 69

Girdle band

60%

Girdle band & Valve 40% Single valve 20% New girdle band 0% 0

1

2

3

4

5

6

7

8

9

10

New valves


Figure 2. Percentage changes of cells with different dye incorporation type during synchronization. The T. pseudonana cells were stained with PDMPO. 100 cells were counted for each sample under Fluorescent Microscope with 1,000 X magnification. See Methods and Materials for the classification criterion. Generally “Girdle band” in legend entry represents the number of cells in Figure 1 b, d and f; “Girdle band & Valve” represents Figure 1 h; “Single valve” represents Figure 1 j. Other types are not presented in Figure 1.


Page 57 of 69

A) 350

312

300

Number of proteins

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 48 49 50 51 52 53 54 55 56 57 58 59 60


288 253 221

250

190

200

179 145

150

94

100 50

82 53

14

0

Protein mass (kDa)

B) 3.28% 6.50%

3.50%

0%-5% 5%-10%

4.31% 32.44%

10%-15% 15%-20%

6.99%

20%-25% 25%-30%

9.01%

30%-35% 35%-40% 13.16%

20.81%


40%-100%


C) 100% 90%

Percentage of total proteins

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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 58 of 69

80% 75%

70% 60%

0h

50%

1h

40%

5h

30%

7h

20% 10% 0% 0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Delta error

Figure 3. General information of the iTRAQ-LC-MS/MS analysis of a synchronized T. pseudonana culture. A) Distribution of proteins of different molecular weights. B) Coverage of proteins by LC-MS/MS identified peptides. C) Repeatability of quantification data between two biological replicates for each time point.


Page 59 of 69

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 48 49 50 51 52 53 54 55 56 57 58 59 60


2.70% 14.33%

13.27%

1.88%

0.16% 4.50% 3.36%

3.28%

1.56%

3.11% 3.36% 2.05% 7.78% 15.07% 5.16%

8.52%

0.90% 0.57% 2.70% 2.78% 0.08% 0.66% 2.21%

Translation, ribosomal structure and biogenesis RNA processing and modification Transcription Replication, recombination and repair Chromatin structure and dynamics Cell cycle control, cell division, chromosome partitioning Defense mechanisms Signal transduction mechanisms Cell wall/membrane/envelope biogenesis Cell motility Cytoskeleton Intracellular trafficking, secretion, and vesicular transport Posttranslational modification, protein turnover, chaperones Energy production and conversion Carbohydrate transport and metabolism Amino acid transport and metabolism Nucleotide transport and metabolism Coenzyme transport and metabolism Lipid transport and metabolism Inorganic ion transport and metabolism Secondary metabolites biosynthesis, transport and catabolism General function prediction only Function unknown

Figure 4. Functional category (COG) coverage of proteins identified in the iTRAQ-LCMS/MS analysis of a synchronized T. pseudonana culture.



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 48 49 50 51 52 53 54 55 56 57 58 59 60

A)

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B)

3

15

1.2

10

0.8

2.5

2

1

2 1.5

1.5

0.6

1

5

0.5

1

0.4

0.5

0.2

0

0 0

1

5

0

7

0 0

1

C)

5

7

D)

3

50

2.5

6

2.5

40

2

5

30

1.5

20

1

10

0.5

2 1.5 1 0.5 0

0 0

1

5

4 3 2 1

0

7

0 0

1

E) 5

2

1.5

4

1.5

3

1

2

0.5 0 1

5

2 1.5

1

1

0.5

0

0

7

1 0.5 0 0

1

G) 1 0.8 0.6

8

2.5

6

2

4

0.4 0.2 0 1

5

7

H)

1.2

0

7

F)

2

0

5

5

7

1.2 1 0.8

1.5

0.6

1

2

0.5

0

0

0.4 0.2 0 0

1


5

7

Page 61 of 69

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 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 5. Comparison of the protein (histograms) and mRNA (lines) levels of A) Thaps3|5063, B) Thaps3|20613, C) Thaps3|20931, D) Thaps3|25206, E) Thaps3|268480, F) Thaps3|41392 (SIT2), G) Thaps3|268546, H) Thaps3|8571, during T. pseudonana synchronization. The X axis is the time after silica was added, and the left Y axis shows the relative protein level, the right Y axis shows the relative mRNA level.



A) 1.8


1.6 1.4 1.2 1 0.8

Thaps3|35387

0.6

Thaps3|38460

0.4 0.2 0 0

1

2

3

4

5

6

7


B)

1.6


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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 62 of 69



1.2

Thaps3|39913_COPI

1 0.8

Thaps3|26212_COPI


0.4 0

1

2

3

4

5

6

7


Thaps3|41392_SIT2

Figure 6. Relative expression patterns of cell cycle proteins (A) and SIT2 co-regulated coatomers (B) during T. pseudonana synchronization. The protein level at 0 h were normalized to 1.


Page 63 of 69

1.7


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 48 49 50 51 52 53 54 55 56 57 58 59 60



1.35

Thaps3|268970 Thaps3|269704

1

Thaps3|27892 Thaps3|2790 0.65


0.3 0

1

2

3

4

5

6

7



Figure 7. Relative expression patterns of amino acid synthases during T. pseudonana synchronization. The solid lines show the levels of D-3-phosphoglycerate dehydrogenase (Thaps3|269704) and threonine synthase (Thaps3|268970, with an arrow). The dotted line shows methionine (Met) synthase I (Thaps3|693).



A)


1.2 1 0.8 0.6 0.4

Thaps3|26041

0.2 0 0

1

2

3

4

5

6

7


B) 2.5


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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 64 of 69

2 1.5 Thaps3|595

1

Thaps3|9619

0.5 0 0

2

4

6

8



Page 65 of 69

C) 1.7


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 48 49 50 51 52 53 54 55 56 57 58 59 60


Thaps3|26706

1.35 Thaps3|40483 1 Thaps3|517

0.65

0.3 0

1

2

3

4

5

6

7


Figure 8. Relative expression pattern of proteins during T. pseudonana synchronization. A) p150, B) diatom silicon starvation-related proteins, C) proteasome subunits. The expression level at 0 h was set to 1.



A) 1.2

relative expression level

1.1 1 0.9 0.8 0.7 0.6 0.5 0.4 0

1

2

3

4

5

6

7

8


B)


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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 66 of 69

1.2

Thaps3|268280

1.1

Thaps3|547

1

Thaps3|8778

0.9

Thaps3|22527

0.8 0.7

Thaps3|268965

0.6

Thaps3|11411

0.5

Thaps3|42475

0.4 0

1

2

3

4

5

6

7


Thaps3|268546 Thaps3|34543

Figure 9. Relative expression patterns of energy production- and conversion-related proteins during T. pseudonana synchronization. The expression level at 0 h was set to 1. A) Average of the relative expression level. The error bars represent the strand deviation


Page 67 of 69

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of the relative expression level of all nine proteins. B) Separate relative expression levels of the nine proteins. The major different occurs at 1 h. The dashed lines represent the citric acid cycle proteins (Thaps3|11411, 42475, and 268965), and the dotted lines represent the phosphoenolpyruvate carboxylases (Thaps3|268546 and 34543).




1.2 1 0.8 0.6

Thaps3|35728

0.4 0.2 0 0

1

2

3

4

5

6

7


B) 1.2


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 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 68 of 69

Thaps3|268127 Thaps3|39813

1

Thaps3|31749

0.8 Thaps3|262332

0.6


0.4 0

1

2

3

4

5

6

7


Figure 10. Relative expression pattern of FtsZ and fucoxanthin-chlorophyll a/c lightharvesting proteins during T. pseudonana synchronization. A) FtsZ B) fucoxanthinchlorophyll a/c light-harvesting proteins. The expression level at 0 h was set to 1. The proteins that are upregulated at 1 h (B, solid lines) are Thaps3|268127, 39813, and 31749, and the proteins that are downregulated at 1 h (B, dashed lines) are Thaps3|262332, 34276, and 33131.


Synchronized T. pseudonana cells

iTRAQ


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


Page 69 of 69

1.6


1.4


1.2

Thaps3|269663_COPI

1

Thaps3|39913_COPI

0.8

Thaps3|26212_COPI

0.6

Thaps3|34876_COPI

0.4 0

1

2

3

4

5

6

SIT2 coregulated coatomers

Thaps3|41392_SIT2

7

Hours after silicon replenishment 1.7


1.35

Thaps3|260953 Thaps3|268970

1


0.65


0.3 0

1

2

3

4


5

6

7



Amino acid synthases

Responses of the marine diatom Thalassiosira pseudonana to changes in CO2 concentration: a proteomic approach.

Localization of enzymes relating to C4 organic acid metabolisms in the marine diatom, Thalassiosira pseudonana.

In vivo study of lipid accumulation in the microalgae marine diatom Thalassiosira pseudonana using Raman spectroscopy.

Photosynthetic and molecular responses of the marine diatom Thalassiosira pseudonana to triphenyltin exposure.

Biochemical Composition and Assembly of Biosilica-associated Insoluble Organic Matrices from the Diatom Thalassiosira pseudonana.

Detection of silver nanoparticles inside marine diatom Thalassiosira pseudonana by electron microscopy and focused ion beam.

Transcript level coordination of carbon pathways during silicon starvation-induced lipid accumulation in the diatom Thalassiosira pseudonana.

Influences of temperature and salinity on physicochemical properties and toxicity of zinc oxide nanoparticles to the marine diatom Thalassiosira pseudonana.

Expression of Histophilus somni IbpA DR2 protective antigen in the diatom Thalassiosira pseudonana.

Cellular responses associated with ROS production and cell fate decision in early stress response to iron limitation in the diatom Thalassiosira pseudonana.

Cadmium-containing carbonic anhydrase CDCA1 in marine diatom Thalassiosira weissflogii.

quadrupole time-of-flight mass spectrometry.

The Combination of RNA and Protein Profiling Reveals the Response to Nitrogen Depletion in Thalassiosira pseudonana.

Functionalization of the living diatom Thalassiosira weissflogii with thiol moieties.

Experimental evidence and isotopomer analysis of mixotrophic glucose metabolism in the marine diatom Phaeodactylum tricornutum.

Low CO2 results in a rearrangement of carbon metabolism to support C4 photosynthetic carbon assimilation in Thalassiosira pseudonana.

Cloning, characterization and anion inhibition study of the δ-class carbonic anhydrase (TweCA) from the marine diatom Thalassiosira weissflogii.

Re-print of "Histone extraction protocol from the two model diatoms Phaeodactylum tricornutum and Thalassiosira pseudonana".

DDT uptake and metabolism by a marine diatom.

Development of a silicon limitation inducible expression system for recombinant protein production in the centric diatoms Thalassiosira pseudonana and Cyclotella cryptica.

Effect of cell cycle arrest on intermediate metabolism in the marine diatom Phaeodactylum tricornutum.

Sulfonamide inhibition studies of the δ-carbonic anhydrase from the diatom Thalassiosira weissflogii.

Cellular metabolic responses of the marine diatom Pseudo-nitzschia multiseries associated with cell wall formation.

Characterization of marine diatom-infecting virus promoters in the model diatom Phaeodactylum tricornutum.