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Transcriptome and Quantitative Proteome Analysis Reveals Molecular Processes Associated with Larval Metamorphosis in the Polychaete Pseudopolydora vexillosa Kondethimmahalli H. Chandramouli,†,‡ Jin Sun,§ Flora SY Mok,† Lingli Liu,† Jian-Wen Qiu,§ Timothy Ravasi,‡ and Pei-Yuan Qian*,† †

KAUST Global Collaborative Research, Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong ‡ Integrative Systems Biology Lab, Division of Biological and Environmental Sciences & Engineering, Division of Applied Mathematics and Computer Sciences. King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia § Department of Biology, Hong Kong Baptist University, Hong Kong S Supporting Information *

ABSTRACT: Larval growth of the polychaete worm Pseudopolydora vexillosa involves the formation of segment-specific structures. When larvae attain competency to settle, they discard swimming chaetae and secrete mucus. The larvae build tubes around themselves and metamorphose into benthic juveniles. Understanding the molecular processes, which regulate this complex and unique transition, remains a major challenge because of the limited molecular information available. To improve this situation, we conducted high-throughput RNA sequencing and quantitative proteome analysis of the larval stages of P. vexillosa. Based on gene ontology (GO) analysis, transcripts related to cellular and metabolic processes, binding, and catalytic activities were highly represented during larval-adult transition. Mitogen-activated protein kinase (MAPK), calcium-signaling, Wnt/β-catenin, and notch signaling metabolic pathways were enriched in transcriptome data. Quantitative proteomics identified 107 differentially expressed proteins in three distinct larval stages. Fourteen and 53 proteins exhibited specific differential expression during competency and metamorphosis, respectively. Dramatic up-regulation of proteins involved in signaling, metabolism, and cytoskeleton functions were found during the larval-juvenile transition. Several proteins involved in cell signaling, cytoskeleton and metabolism were up-regulated, whereas proteins related to transcription and oxidative phosphorylation were down-regulated during competency. The integration of high-throughput RNA sequencing and quantitative proteomics allowed a global scale analysis of larval transcripts/proteins associated molecular processes in the metamorphosis of polychaete worms. Further, transcriptomic and proteomic insights provide a new direction to understand the fundamental mechanisms that regulate larval metamorphosis in polychaetes. KEYWORDS: polychaetes, pseudopolydora vexillosa, metamorphosis, transcriptomics, proteomics

1.0. INTRODUCTION

molecular processes that influence larval competency and metamorphosis. This information is crucial to the basic understanding of this system. In polychaete worms, the p38 dependent MAPK pathway was found to be involved in larval settlement and metamorphosis of Hydroides elegans.5 The continuous expression of the calmodulin (CaM) gene was shown to be involved in the calcium binding pathway.6 In Capitella sp. I, the notch signaling pathway mediated the segmentation process during larval metamorphosis.7 In barnacle Balanus amphitrite, p38 MAPK was activated to induce the larval settlement process.8 Wnt signaling pathway ligands were involved in patterning of the polypide in bryozoan

Pseudopolydora vexillosa, the most conspicuous surface-feeding spioniform polychaete, inhabits the soft bottoms of shallow subtidal sediment.1 It plays important roles in sediment biogeochemistry and serves as a potential bioindicator.2 Larval growth involves the formation of segment-specific structures, such as chaetae, and the addition of terminal chaetigers. When the larvae become competent to settle, they discard swimming chaetae and secrete mucus. Then the larvae build tubes around themselves and metamorphose into benthic juveniles.2 This process appears to be regulated by molecular processes mediated by exogenous signals or chemical cues, which interact with proteins/genes to control the acquisition of competency and subsequent metamorphosis.3,4 One of the most important questions of the field of larval biology is to determine the © 2013 American Chemical Society

Received: October 25, 2012 Published: January 8, 2013 1344

dx.doi.org/10.1021/pr3010088 | J. Proteome Res. 2013, 12, 1344−1358

Journal of Proteome Research

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Bugula neritina.9 In this study, we proposed to identify the genes that could possibly regulate the larval competency and metamorphosis in P. vexillosa. Our previous studies used a two-dimensional gel electrophoresis (2-DE) based proteomics approach that has revealed drastic changes in protein expression and protein posttranslational modification patterns during the larval−juvenile transition of P. vexillosa.3,4,10 Although these studies identified several proteins and provided valuable insights into larval metamorphosis, the technologies used were limited in being able to obtain comprehensive information on quantitative proteomic changes. Despite the technical advances which improved resolution and reproducibility of 2-DE, many intrinsic problems, such as limited dynamic range and inability to detect basic and hydrophobic proteins, remain unresolved.11 These limitations have been addressed by the progress in mass spectrometry (MS) and the availability of genome sequence databases.12 The integrated RNA-sequencing and quantitative protein expression data is a promising approach to obtain proteomic and genomic insights in non-model species.13,14 Hence, establishing genomics resources such as expressed sequence tags (EST) databases for polychaete worms would improve the identification of differentially expressed proteins and pave the way toward discovering key molecular processes associated with larval metamorphosis. New sequencing platforms such as 454 pyrosequencing, and advances in LC-MS/ MS-based proteomics techniques yielded valuable biological insights during larval development of non-model marine species.15 Transcript sequence databases of the bryozoan B. neritina and barnacle B. amphitrite have been constructed.13,16 Recently, transcriptomes of several other non-model marine species including coral Acorpora millepora,17 the butterfly Melitaea cinxia,18 and the Antarctic clam Laternula elliptica19 have also being sequenced. In addition, complementary analysis of proteins using transcriptome assembly provides an important validation tool within a given cell, tissue, or organ.20−22 Isobaric tags for relative and absolute quantification (iTRAQ)-labeling coupled with LC-MS/MS proteomics technology are recognized for their ability to relatively quantify thousands of proteins in complex multiple protein samples.23 While comparison of transcriptome and proteome profiling has been reported in B. neritina,13 the integrated application of transcriptomic and proteomic data generated by 454 sequencing and iTRAQ-based quantitative proteomics has not been reported in polychaete worms. In our previous study, we constructed an EST database from five distinct larval stages of P. vexillos.4 The raw reads were submitted to the NCBI public domain with Sequence Reads Archive (SRA) submission number SRA030597.1 and accession SRX047658. In this study, the following specific questions were asked: (i) Are the changes in the proteome comparable with transcriptome data? (ii) By using an improved quantitative proteomics approach, will we be able to quantify more differential proteins during larval metamorphosis? (iii) Are any molecular pathways associated with larval metamorphosis? To test our hypothesis, we analyzed the transcriptome data through bioinformatics databases. Quantitative proteome analysis was performed on precompetent larvae, competent larvae, and juveniles of P. vexillosa. The transcriptome database was used to identify differentially expressed proteins. Many components of key metabolic pathways and differential expression of proteins are reported. Through functional categorization of genes and

proteins, we provided new insights into the molecular mechanisms of larval metamorphosis in P. vexillosa.

2.0. EXPERIMENTAL SECTION 2.1. Selection of Larval Species and Culture

Adult P. vexillosa were collected from the shallow subtidal sediment in Yung Shue O, Sai Kung, Hong Kong (22°25′N, 114°17′E) and maintained in the aquarium as described by Mok et al.3 The collection protocol for 3-chaetiger (newly hatched) larvae, precompetent larvae, competent larvae, juveniles, and adults (Figure1) was reported in ref 4. Briefly,

Figure 1. Developmental stages of polychaete Pseudopolydora vexillosa that were sampled for transcriptomic and proteomics analysis. The stages included 3-chaetiger larvae, precompetent larvae, competent larvae, juvenile, and adults. Two mixed pools of larvae were used for RNA sequencing. Three biological replicates of precompetent larvae, competent larvae, and juveniles were used for proteomic studies. Scale bars = 150 μm.

larval samples were collected at day 0 (newly hatched), day 5 (precompetent larvae), and day 6 (competent larvae). Competent larvae were induced to settle for 3 h, followed by collection of juveniles. Prior to collection, adults were carefully examined to define their species morphologies. Approximately 1800−4000 newly hatched, precompetent, competent larvae, and juveniles were collected at each time of sampling. Total RNA was extracted from a mixed pool of newly hatched larvae, precompetent larvae, competent larvae, juveniles (800−2000 larvae), and adults as reported in ref 4. 454 sequencing was performed according to the Roche 454 GS-FLX pyrosequencer (Roche Diagnostics, Nutley, NJ, USA). The remaining precompetent larvae, competent larvae, and juveniles (1000− 2000 larvae/replicate) were frozen in liquid nitrogen until use for quantitative proteome analysis. 2.2. Functional Annotation of 454 Sequencing Reads

The sequence assembly, gene prediction, and annotation were performed (Roche, Nutley, NJ, USA) as described in refs 4 and 13. Briefly, 454 sequencing raw data were preprocessed to remove low quality reads. The preprocessed sequences were then assembled by using Newbler software (version 2.3) with default parameters (40 bp overlap, 90% identity).7 Nucleic acids were annotated by homology search performed using BLASTx from the NCBI nonredundant database.24 The open reading frames (ORF) were predicted using “getorf ”, and only the longest ORF predicted was selected. The gene ontology analysis was conducted on the annotated sequences through the Blast2GO program.25 The annotated sequences were submitted to the Database for Annotation, Visualization and Integrated Discovery (DAVID) for enrichment pathway analysis (DAVID webpage v6.7)26 as described by Wong et 1345



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al.9 In order to obtain abundantly expressed transcripts, raw reads were assigned to different subsystems of the Metagenomics Rapid Annotation using the Subsystems Technology (MG-RAST) server for automated annotation with the default parameters.27 The filtered reads were analyzed and subjected to KEGG analysis with parameters of maximum E-value of 1e−25, a minimum identity of 50%, and a minimum alignment length of 30.

These peptides fractions were desalted using Sep-Pak C18 cartridges prior to LC-MS/MS analysis. 2.4. LC-ESI-QTOF Analysis

Each of the dried peptide fractions were reconstituted in 10 μL of 0.1% formic acid and then analyzed using a nanoflow UPLC (nanoAcquity, Waters) coupled with an ESI-hybrid Q-TOF tandem mass spectrometer (Premier, Waters). Positive ion mode was selected in a data-dependent acquisition in the mass scanning range of 300−1600 m/z. The three most abundant peptides with +2 to +4 charge states above a 40-count threshold were selected for MS/MS analysis as described by Zhang et al.28

2.3. Protein Extraction, iTRAQ Labeling, and OFFGEL Fractionation

Sample preparation was carried out according to the procedure described by Chandramouli et al.,4 with slight modifications. Larvae from three developmental stages (precompetent larvae, competent larvae, and juvenile) were transferred to lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, and protease inhibitors), sonicated, and centrifuged at 13,000 rpm for 15 min. The supernatant was cleaned with a 2-DE cleanup kit (Bio-Rad, Hercules, CA, USA). The purified protein pellets were resolubilized in 8 M urea and quantified using an RC-DC kit (Bio-Rad, Hercules, CA, USA). The acetone precipitated aliquots containing 100 μg of protein were dissolved in 20 μL of dissolution buffer, and sample reduction was performed at 60 °C for 1 h according to the supplier protocol (Applied Biosystems, Foster City, CA, USA). Five micrograms of (1:40 enzyme to protein mass ratio) of Trypsin Gold (Promega, Madison, WI, USA) was added to each sample and allowed to digest overnight at 37 °C. The protein digests were desalted using Sep-Pak C18 cartridges (Waters, Milford, MA, USA) and dried under vacuum using a Speed Vac (Thermo Electron, Waltham, MA, USA). Labeling of the peptides with the iTRAQ reagents was performed according to the manufacturer’s recommendations. Briefly, each iTRAQ 4-plex reagent was dissolved in 70 μL of ethanol, and the contents were transferred to a corresponding protein digest tube. One hundred micrograms of each digest was labeled with iTRAQ reagent 114 (precompetent larvae), 115 (competent larvae), 116 (juveniles), and 117 (served as internal control and contained equal amounts of peptides from all three samples). The protein digests were incubated at room temperature for 1 h. After labeling, samples were pooled (for a total of 400 μg of peptide digests) and dried by vacuum centrifugation. The dried labeled peptides were desalted using Sep-Pak C18 cartridges prior to the OFFGEL peptides fractionation. Peptides were separated based on their pI using a 24-well setup on a 3100 OFFGEL Fractionator according to the protocol described by the supplier (Agilent Technologies, Böblingen, Germany). Briefly, 24-cm-long IPG gel strips (GE Healthcare, München, Germany) with a linear pH gradient ranging from 3 to 10 were rehydrated with 40 μL of focusing buffer per well. A 150-μL sample volume was loaded into each well. Peptides were focused for approximately 18 h or until the voltage reached 50 kVh with a maximum current of 50 mA. After focusing, 50−150 μL of fractions were recovered for each well and transferred to microtubes. OFFGEL fractionation generated 24 peptide fractions according to their pI values, ranging from 3.0 to 10.0. At the end of the fractionation, acidic fractions (1−3) and basic fractions (22−24) contained very low sample volumes, possibly because of the low quantities of peptides. Hence, the first three acidic fractions (1−3) were pooled in one tube and the last three basic fractions (22−24) were pooled in another tube, thus giving a total of 20 fractions.

2.5. Protein Identification and Quantification

Raw data generated from the LC-MS/MS were converted into pkl files by using Proteinlynx Global Server 2.2.5 (Waters Corp., Milford, MA). Two kinds of pkl files were simultaneously generated for each fraction: one with the option of deisotoping on MS/MS and one without. A python script was applied to extract the reporter mass, i.e. 114−118 Da, from the non-deisotoping file to replace the respective deisotope file of the same mass range. The newly combined pkl files of all of the fractions were merged and submitted to MASCOT version 2.3.0 (Matrix Sciences Ltd., London, U.K.) to search against the concatenated “target” (real sequences) and “decoy” (reversed sequences) translated P. vexillosa transcriptome sequences. The strategy used for protein identification was followed by Sun et al.29 with slight modifications as follows: the search criteria was set as 30 ppm for precursor and 0.5 Da for fragments; fixed modification, methylthio (cysteine); variable modification, oxidation (methionine). Up to one missed trypsin cleavage was allowed. Peptides were identified with ion scores no less than 20 at the 95% confidence interval. The protein was considered positively identified if it matched to at least two unique spectra and had an expect value less than 0.05. The false discovery rate (FDR) in the “target-decoy” database search strategy was dynamically set as less than 1% in each biological replicate. Unlabeled peptides and peptides matched to the decoyed sequences were removed. The iTRAQ reporter intensities were further normalized by the “Summed intensities” method. Protein ratios in each replicate were quantified based on the summed intensities of the spectrum matched. These ratios were further log2 transformed. Student’s t-test following Benjamini and Hochberg correction was applied on the transformed ratio.30 Only corrected p values of less than 0.05 and protein fold change out of the range 0.769−1.3 were considered significant. 2.6. Western-Blot Analysis

Western-blot, following the protocol described in ref 5, was carried out to determine protein expression levels of selected transcripts such as p38 mitogen-activated protein kinase (p38 MAPK), phosphorylated p38 MAPK (pp38 MAPK), heat shock protein-70 (HSP-70), histone H3, and tyrosine hydroxylase (14-3-3). Briefly, 20 μg of protein lysates from precompetent larvae, competent larvae, and juvenile samples were separated on 10% SDS-PAGE and transferred onto Immobilon transfer membranes (Millipore, Billerica, MA, USA). The membranes were incubated with 1:500 diluted antibodies of p38 MAPK (ref 8) and pp38 MAPK (Thr180/ Tyr182) (Cell Signaling, Danvers, MA, USA). HSP-70, histone H3 (Cell Signaling, Danvers, MA, USA), and 14-3-3 antibodies (Abcam, Cambridge, MA, USA) were 1:1000 diluted and 1346



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incubated for ∼16 h at 4°C. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the loading control. The membranes were then probed with horseradish peroxidaseconjugated secondary antibodies (1:5000 dilutions) for 1 h at room temperature, followed by chemiluminescent detection using a WesternBright ECL detection kit (Advansta, Menlopark, CA, USA).

3.0. RESULTS 3.1. Properties of the P. vexillosa Transcriptome Generated by 454 Pyrosequencing

To obtain a global view of transcriptome during larval metamorphosis of P. vexillosa, mixed cDNA pools from five larval stages (Figure 1) were prepared for RNA-sequencing. A total of 139 Mb of transcriptome data consisting of 126,942 sequences and 60.9 M nucleotides (SRR125360, date 1/3/ 2012) was generated. The 454 pyrosequencing transcriptome data is summarized in Table 1. 178,413 reads with an average Table 1. Statistic Summary of the P. vexillosa Transcriptome feature

number

no. of reads after initial quality filtering avg read length after initial quality filtering no. of ESTs assembled as contigs ESTs remained as singletons avg isotig size no. of contigs/isotigs

178,413 352 bp 126,940 51,473 720 bp 4,358

Figure 2. Size distributions of the unique genes (A) and the deduced open reading frames (B). The 367 base pair average length of the contigs was comparable to most Sanger sequencing-based cDNA libraries.

length of 367 bases were obtained from five pooled larval samples. After filtering low quality reads, 126,940 reads were obtained and further assembled into 4,358 unique isotigs, and the remaining 51,473 high-quality reads were classified as singletons. Thus, a total of 55,831 unique ESTs including both isotigs and singletons were obtained. The average length of the isotigs and singletons was 720 and 352 bp, respectively. The size distributions of the unique genes and the deduced open reading frames are shown in Figure 2. Gene ontology (GO) analysis was conducted on the unique sequences by using the Blast2GO program. The annotated sequences (2,162) were successfully assigned to the biological process, the cellular component, and the molecular function GO categories, respectively. Distributions of the GO term (the second level) for the three categories are shown in Figure 3. The most abundant second level terms for the biological process category from larval−adult stages belonged to cellular (20.02%) and metabolic processes (18.2%). The cellular component category included cell (37.29%), organelle (29.55%), and macromolecular complex (23.51%). The molecular function category was highly represented by binding (44.51%), catalytic activity (27.94%), and structural molecule activity (17.53%). For the biological process GO category, 6.42% and 0.89% unique sequences were assigned to developmental process and growth, while 1.35% and 5.69% were assigned to the immune system and response to stimulus, respectively (Figure 3).

ton proteins (15.6%) during the larval−adult transition. Posttranslational modification, protein turnover, and chaperone related genes accounted for approximately 10.9% of the transcriptome. 5% of the transcripts represented energy production and conversion. 1−2% of the transcripts were related to signal transduction, transport, and transcription (Figure S2). The 42 most abundant transcripts are shown in Table 2. Transcripts encoding several housekeeping proteins including ribosomal proteins, elongation factor, cytoskeletons, and histones were highly abundant. The most abundant transcript accounted for 4,770 reads and was annotated as a ribosomal protein. 704 reads were mapped to the elongation factor α. Gene product from transcript GA21728 accounted for 1543 reads. Transcripts encoding ATP synthase, methionine adenosyltransferase, voltage-dependent anion channel 1, calmodulin, ubiquitin, and stress proteins were also highly expressed in the transcriptome. Notably, 9 of the 42 most abundant transcripts encoded enzymes such as methionine adenosyltransferase, protein phosphatase, aldehyde dehydrogenase, phosphosulfate synthase 1, glyceraldehyde 3-phosphate dehydrogenase, malate dehydrogenase, fructose 1,6-bisphosphate aldolase, succinate dehydrogenase, and acyl-CoA dehydrogenase. 3.3. Enriched Metabolic Pathways

The DAVID enrichment analysis categorized twelve transcripts belonging to the MAPK pathway (Table 3-MAPK pathway). Of these, two ERKs and p38 MAPK belong to a superfamily of highly conserved MAPK. Four downstream transcription factors, Ras, cMyc, MAX, and c-Jun, were detected. The calcium signaling pathway (Table 3; calcium signaling) was represented by voltage-gated calcium ion channels, sodium calcium exchangers, ryanodine receptor (RYR), calcium-

3.2. Abundantly Expressed Transcripts

126,942 reads were uploaded to the MG rast server. The postquality control analysis yielded 93,037 sequences of mean length 493 ± 70 bp (Figure S1 of the Supporting Information). KEGG functional analysis revealed that the transcripts related to translation, ribosomal structure, and biogenesis were highly abundant (60.1%) followed by transcripts encoding cytoskele1347



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Figure 3. Gene ontology term distributions (the second level) for three categories: (A) biological process; (B) cellular component; and (C) molecular function. GO analysis was conducted on the unique sequences by using the Blast2GO program.

or more spectra hits per protein at FDR = 0.01, 107 proteins were differentially expressed in three independent biological replicates; Tables 4−6 lists 107 proteins that demonstrated statistically significant changes in expression during larval competency or metamorphosis, along with their expression levels and the corrected p-values associated with these measurements. Fourteen different proteins (of these, 11 were up-regulated and 3 were down-regulated) showed differential expression during precompetent to competent stages (Figure 4, Table 4). Fifty-three proteins (of these, 37 were up-regulated and 16 were down-regulated) showed differential expression during competent to juvenile stages (Figure 4, Table 5). Forty proteins (of these, 24 were up-regulated and 16 were downregulated) showed differential expression during the precompetent to juvenile transition (Figure 4, Table 6).

transporting sarcoplasmic/endoplasmic reticulum ATPase (SERCA), calmodulin (CaM), a calcium/calmodulin-dependent serine protein kinase (CAMK), a myosin light chain kinase (MLCK), a phosphorylase kinase α/β subunit (PHK), and a calnexin (CaN), which are CaM dependent calcium signaling pathways. The notch signaling pathway (Table 3; notch signaling pathway) was represented by notch homologues, a NUMB protein, histone acetyltransferase (HATs), histone deacetylase, and the CBF1 interacting corepressor. Transcripts Wnts, lipoprotein receptor-related protein (LRP), β-catenins, and cyclins belong to a Wnt/β-catenin pathway (Table 3; Wnt/ β-catenin pathway). 3.4. Proteins Identified by LC-MS/MS

OFFGEL fractionation of the pooled iTRAQ-labeled peptides and LC-MS/MS analysis identified a total of 518 proteins from 1247 unique peptides. The reporter ion 117 was labeled with an equal amount of peptides from all three larval stages and used as internal control. Ideally, after the normalization, the protein identity of 1/3 of the total intensity of 114, 115, and 116 should be exactly the same as that of 117. In our study, over 90% of the quantitative ratio generated from these two numbers was within the range of the 0.769−1.3 threshold. Thus, we applied this range combined with the corrected t-test p-value to determine the significant differential expression of proteins. Based on two

3.5. Proteins Involved in Cell Signaling, Metabolism, Transcription and Translation, and Cytoskeletal and Oxidative Phosphorylation Processes Were Differentially Expressed

All differentially expressed proteins were grouped into several categories (Figure 5). Twelve proteins were classified as signaling proteins involved in chemical cue or stress response. The signaling proteins were predominantly calcium binding proteins. Eighteen proteins were classified under general 1348



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Table 2. Most Abundant Transcripts Expressed during Larval Metamorphosis of Pseudopolydora vexillosa rank

no. of reads

annotation

E-value (−)

identity (%)

align length

contig no.

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

4770 1543 704 582 576 553 492 395 340 185 184 173 104 101 91 80 67 60 59 53 49 45 44 44 40 38 34 33 28 28 26 24 21 19 18 15 14 11 11 10 8 5

ribosomal protein gene product from transcript GA21728-RA elongation factor α tubulin hypothetical 40S ribosomal protein 60S ribosomal protein actin H3 histone guanine nucleotide binding protein iodotyrosinedehalogenase protein AGAP000651-PA myosin heavy chain ATP synthase α chain, mitochondrial nascent polypeptide-associated complex α subunit dynein heavy chain methionine adenosyltransferase voltage-dependent anion channel 1 calmodulin ubiquitin dynein light chain hsp90 protein, putative heat shock 70 kDa protein solute carrier family DNA-binding protein A protein phosphatase aldehyde dehydrogenase phosphosulfate synthase 1 glyceraldehyde 3-phosphate dehydrogenase malate dehydrogenase ubiquitin-conjugating enzyme E2D fructose 1,6-bisphosphate aldolase 14-3-3 protein tropomyosin cytochrome b-c1 complex ATP-binding cassette peroxiredoxin calreticulin succinate dehydrogenase acyl-CoA dehydrogenase thioredoxin cathepsin A

30 55 36 55 36 48 47 53 40 54 34 54 34 55 32 43 42 46 37 47 34 31 56 36 34 29 48 43 46 34 38 34 53 40 28 27 28 57 44 38 27 39

99 96 83 96 71 88 75 96 87 84 81 86 70 84 83 78 79 74 79 81 84 79 85 78 80 67 71 70 78 70 83 74 83 69 78 74 77 75 79 70 70 70

72 108 86 108 100 111 109 106 80 116 90 116 101 131 88 104 102 116 98 112 83 84 125 94 87 93 122 113 113 101 88 100 130 121 81 77 78 124 102 109 82 104

3752 12290 3740 6413 GG70GXE04H5QQL_10 11174 11231 14047 F5K2Q4C01BC7H4 10284 F5K2Q4C01BJB38 F5K2Q4C01A9BVH 00736_21 4849 10118 8113 4201 10261 F5K2Q4C01BOAQ6 1008 F5K2Q4C01BLN64 5081 13611 11454 15788 10864 15628 6855 F5K2Q4C01CEJEM 15049 12018 5284 06726_6 16006 F5K2Q4C01AUFOG F5K2Q4C01BKHAR 10511 2865 10777 F5K2Q4C01B0GZZ 15388 F5K2Q4C01A5HJ7

metabolism, such as glycolysis, citric acid cycle, and fatty acid metabolism. The glycolytic enzymes, such as fructose 1,6bisphosphate aldolase, enolase-phosphoglycerate dehydratase, and phosphoglycerate mutase, were up-regulated during competency and metamorphosis (Table 6). The enzymes related to the citric acid cycle, such as malate dehydrogenase, were up-regulated during the competency (Table 4) whereas citrate synthase and adenylate kinase were up-regulated during metamorphosis (Table 5). Succinate dehydrogenase was upregulated during competency and metamorphosis (Tables 4 and 6). The fatty acid synthetic enzyme propionyl coenzyme A carboxylase was up-regulated during metamorphosis (Table 5). Eighteen proteins were grouped into the transcription and translation category. Sixteen proteins were represented in the cytoskeletal category. Five were grouped as respiratory chain proteins. In addition, about 25% of the proteins identified in this study had no annotated function and have been classified

under the unknown function category. The proteins related to signaling (constituted 11%), cytoskeleton (15%), and metabolism (16.8%) processes were also identified. Most differentially expressed proteins in this category were overexpressed during larval competency and metamorphosis (Figure 5A and B). Proteins implicated in oxidative phosphorylation and transcription were down-regulated during competency (Figure 5B). Notably, most of the unknown function proteins were downregulated during competency and up-regulated during metamorphosis. Several other proteins involved in transport and muscle contraction were also shown to be overexpressed during competency (Figure 5A). 3.6. Differential Analysis of Transcripts at the Translational Level

In this study, we identified 12 transcripts which belonged to the MAPK pathway (Table 2). We suspected that these selected MAPK transcripts (p38 MAPK and pp38 MAPK) could trigger 1349



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Table 3. Identified Transcripts Belonged To Molecular Pathways Associated with Larval Metamorphosis in Pseudopolydora vexillosa P. vexillosa contig no.

size (bp)

accession no.

GG7OGXE04IQ6U9 GG7OGXE04J2AGL F5K2Q4C01A9FMF GG7OGXE04JF0X2 GG7OGXE04JED7U GG7OGXE04IZGHO GG7OGXE04H513S GG7OGXE04JYIG4 F5K2Q4C01A24D1 GG7OGXE04H8YA1 GG7OGXE04JDH50 F5K2Q4C01BTN7T

88 135 114 127 130 115 114 88 140 69 140 101

XP_002740492.1 XP_002733724.1 XP_002661361.1 XP_791124.1 XP_002664692.1 CBJ55871.1 XP_001950050.1 XP_783732.1 AAI57176.1 XP_002415812.1 AAP76461.1 XP_002734622.1

GG7OGXE04JIW4E GG7OGXE04H7NKJ F5K2Q4C01CCLKA GG7OGXE04IR9L0 GG7OGXE04I4FIU GG7OGXE04I81JI GG7OGXE04JA0D8 GG7OGXE04JPQNA

156 112 141 151 149 164 144 152

ACX47560.1 NP_001037979.1 XP_002740373.1 AAO83853.1 AAA31450.1 XP_002758796.1 NP_001121714.1 AAC63909.1

GG7OGXE04JGZ61 GG7OGXE04H8WM GG7OGXE04JBN7L GG7OGXE04IA49V GG7OGXE04IQNEG GG7OGXE04ISUGR

161 136 162 125 144 147

AAT71303.3 XP_002573471.1 XP_001647823.1 EDL97656.1 ACN43221.1 AAO83853.1

F5K2Q4C01AYKV8 GG7OGXE04I1CEH GG7OGXE04ILZ0O GG7OGXE04JVYJH GG7OGXE04JGFJ0 GG7OGXE04IPQPA F5K2Q4C01BCJYH GG7OGXE04JK4LV GG7OGXE04I3X2Z GG7OGXE04IVHUT GG7OGXE04JQ504 F5K2Q4C01BNZ8C

143 163 146 109 116 155 75 131 120 55 115 90

XP_002127912.1 AAP20605.1 CAJ38792.1 XP_002130810.1 XP_001846251.1 XP_002425981.1 XP_001190179.1 XP_780717.2 XP_001602930.1 XP_001096929.2 ACI33577.1 XP_535968.2

GG7OGXE04IYU5V GG7OGXE04JWGK0 GG7OGXE04I0O1A GG7OGXE04JTU6Q GG7OGXE04IIVPT GG7OGXE04IBQP4 GG7OGXE04JZRZH GG7OGXE04IVUP0 GG7OGXE04I45YJ GG7OGXE04JSVPR

88 161 79 152 82 129 138 97 96 114

BAD12590.1 CAD37169.1 XP_001606342.1 XP_001202408.1 NP_001079233.1 ABQ85061.1 XP_001161927.1 AAY29569.1 ABY21456.1 AAA51928.1

E-value

proteins MAPK Pathway mitogen-activated protein kinase kinasekinase 12-like (MAPKKK) mitogen-activated protein kinase 1-like (MAPKK) Ras-like, estrogen-regulated, growth inhibitor (RAS) Ras homologue gene family, member T1 (RAS) neurofibromin 1 (NF1) extracellular signal-regulated kinase 1/2 (ERK) p38 MAP kinase (p38 MAPK) mitogen-activated protein kinase 1 interacting protein 1 (MNK1/2) phospholipase A2 MAP/microtubule affinity-regulating kinase Myc proto-oncogene protein (c-Myc) growth factor receptor-binding protein 2 (GRB2) Calcium-Signaling Pathway ryanodine receptor, putative (RYR) caveolin 3 (CaV3) calmodulin (CALM) calcium/calmodulin-dependent serine protein kinase (CAMK) phosphorylase kinase α/β subunit (PHK) myosin-light-chain kinase (MLCK) Ca2+ transporting ATPase, plasma membrane (PMCA) calcium-transporting atpase sarcoplasmic/endoplasmic reticulum type (calcium pump) (SERCA) C. briggsae CBR-NCX-2 protein (NCX, sodium calcium exchanger) high voltage-activated calcium channel Cav2A calnexin (CaN) calcium/calmodulin-dependent serine protein kinase (CAMK) calcium/calmodulin-dependent protein kinase (CaM kinase) II calcium/calmodulin-dependent serine protein kinase (CAMK) Notch Signaling Pathway notch homologue 1, translocation-associated notch homologue 2 (Drosophila) notch notch homologue 1b numb protein (NUMB) histone acetyltransferase HTATIP histone acetyltransferase (HATs) C-terminal binding protein histone deacetylase histone deacetylase 1/2 histone deacetylase 1/2 CBF1 interacting corepressor Wnt/β-Catenin Pathway Wnt16 like (Wnt) WNT-2 precursor, putative (Wnt) Wnt7-1 (Wnt) low density lipoprotein receptor-related protein 5/6 low density lipoprotein receptor-related protein 5/6 (LRP5/6) catenin (cadherin-associated protein), β 1 cyclin D binding myb-like transcription factor 1 catenin (cadherin-associated protein), β 1 catenin (cadherin-associated protein), β 1 cyclin D2

× 10−4

5 0 2 2 4 8 3 8 7 2 7 4

× × × × × × × × × ×

10−12 10−39 10−21 10−52 10−29 10−18 10−15 10−31 10−14 10−24

9 4 7 3 2 9 2 2

× × × × × × × ×

10−31 10−21 10−08 10−60 10−45 10−26 10−34 10−50

3 8 4 5 9 2

× × × × × ×

10−41 10−52 10−57 10−30 10−76 10−58

3 3 1 4 2 7 2 1 1 2 7 6

× × × × × × × × × × × ×

10−12 10−62 10−35 10−23 10−21 10−17 10−24 10−60 10−50 10−21 10−04 10−15

4 2 7 6 3 2 1 3 2 7

× × × × × × × × × ×

10−25 10−54 10−3 10−3 10−12 10−66 10−48 10−48 10−43 10−37

observed an abundant expression of transcripts of histone H3 (rank 9), HSP-70 (rank 23), and 14-3-3 (rank 33), as listed in Table 2. From proteomic data, 14-3-3 (Table 6) was upregulated in competent larvae whereas histone was downregulated (Tables 4 and 6). To validate these trends of

larval competency by regulating the MAPK signaling cascade. Our Western blot results clearly showed the up-regulation of p38 MAPK and pp38 MAPK in the competent stage (Figure 6A), suggesting the possible regulatory role of the MAPK signaling cascade in the metamorphosis of P. vexillosa. We also 1350



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Table 4. Pseudopolydora vexillosa Proteins Showing Differential Expression during Competency (com/pcom) com/pcom (115/114) P. vexillosa accession no.a Signaling isotig12753_11 isotig11879_11 GG7OGXE04J30XI_11 Transcription isotig13309_9 GG7OGXE04JR7E8_6 Glycolysis isotig02489_9 isotig03268_2 Citric Acid Cycle isotig06858_8 GG7OGXE04I9DNL_10 F5K2Q4C01CEPA4_5 Transport isotig00499_4 Proteolysis F5K2Q4C01BPP1I_1 Detoxification isotig12886_15 a

mean sequence coverage (%)c

FCd

t-test

107

15.1

1.3

3.6 × 10−06

2 10

57.3 215.0

10.4 25.7

1.3 1.4

0.00484 0.00513

gi|33114058 gi|232136

4 3

124.3 34.7

13.0 8.5

0.6 0.6

0.01148 0.00159

fructose 1,6-bisphosphate aldolase phosphoglycerate kinase 1

gi|166406769

11

172.3

44.2

1.3

0.00309

gi|291233231

2

54.7

27.0

1.3

0.01813

cytosolic malate dehydrogenase NAD(P) transhydrogenase succinate dehydrogenase

gi|73656362

8

167.7

15.2

1.3

0.00016

gi|47550793 gi|27229021

2 2

44.3 95.3

6.6 22.8

0.6 1.7

0.01700 0.00040

hemoglobin A2b chain

gi|84618895

19

204.7

20.6

1.6

3.1 × 10−05

ubiquitin-protein ligase

gi|325302630

2

47.0

28.3

1.4

0.00286

aldehyde dehydrogenase

gi|209154764

9

180.0

40.5

1.3

0.01651

protein name

match to NCBI

MS spectra (95%)b

actin-depolymerizing factor ADF6 protein disulfide isomerase 1 Filamin-C

gi|320167203

5

gi|332271599 gi|307210403

histone H1 guanine nucleotide-binding protein

mean protein score

b

Accession nos. refer to contig no. in transcriptome database. Values indicate the number of MS spectra used for identification and quantification of the proteins. cEstimate only, based on a match to an EST which may represent an incomplete sequence. dFC: Fold change (p < 0.05). Protein ratios in three biological replicates with 1.3 up-regulated.

4.0. DISCUSSION Integration of 454 RNA sequencing and LC-MS/MS quantitative analysis were used to survey the transcriptome and proteome, respectively, in larval stages of P. vexillosa. The depth of each data set provides new direction to the studies on regulation of larval metamorphosis and allows an assessment of OMICS technologies as tools to study larval metamorphosis in polychaetes that currently lack genome sequence resources. This led to the functional analysis of 126,940 sequences, of which 7.31% of unique sequences were related to development and 5.65% of transcripts were assigned to the response to stimulus. 4.1. Improved Identification of Differentially Expressed Proteins in Polychaete Larvae by Quantitative Proteomics

Protein identification is a challenging task in non-model species due to the lack of genomic information.31 In addition, 2-DE based proteomics is likely to identify the most abundant proteins.32 To date, the number of total proteins and differential proteins identified by the 2-DE based proteomics approach was relatively small in polychaetes worms.3,4,10,33,34 For instance, the 2-DE approach identified only 11 total proteins,3 38 phosphoproteins4 and 14 glycoproteins10 in P. vexillosa. In other polychaete worms, such as Capitella sp. I and Neanthes arenaceodentata, 21 and 23 total proteins were identified respectively.33,34 The majority of these proteins were involved in cytoskeletal and energy metabolism processes. Alternately, the database (EST or transcriptome sequences) dependent strategy is a promising approach for protein identification in nonsequenced organisms.35 In the contest of protein quantification, iTRAQ is probably the most dependable

Figure 4. Differentially expressed proteins during precompetent to competent (pcom/com), competent to juvenile (com/juv), and precompetent to juvenile (pcom/juv) stages. Only statistically (p < 0.05 and >95% confidence level) significant protein expression changes are shown. Cutoff fold change range 0.765−1.3. The complete proteins list and iTRAQ quantitative data are provided in Tables 4−6.

expression at the translational level, we selected histones H3, HSP-70, and 14-3-3 for Western blot analysis. Our analyses showed the expression trends of these proteins were similar to transcriptomic and proteomic results. We observed an abundant expression of HSP-70 in all three larval stages (Figure 6A). 14-3-3 was up-regulated whereas histone was down-regulated in the competent stage of the larvae (Figure 6B). 1351



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Table 5. Pseudopolydora vexillosa Proteins Showing Differential Expression during Metamorphosis (juv/com) juv/com (116/115)

a

P. vexillosa accession no.

Signaling isotig06173_7 GG7OGXE04IMXEW_7 isotig11733_7 contig06957_4 Oxidative Phosphorylation isotig03146_3 isotig12702_5 F5K2Q4C01CAT0X_1 Transcription isotig09522_29 isotig04488_3 isotig06566_3 Translation isotig07768_5 isotig06231_6 F5K2Q4C01AWDGH_11 isotig03100_2 isotig08766_12 Glycolysis isotig04875_8 GG7OGXE04J31LT_9 Citric Acid Cycle GG7OGXE04ICDQA_7 isotig08702_4 isotig03731_10 isotig07064_4 GG7OGXE04I4S7T_8 Muscle Contraction GG7OGXE04ISV9A_9 contig00707_6 isotig01887_4 isotig08546_44 Structure and Integrity GG7OGXE04J0CYQ_3 GG7OGXE04JX7QT_8 GG7OGXE04I3XGD_6 F5K2Q4C01BF1TF_3 GG7OGXE04IAEAW_3 GG7OGXE04JIAUX_4 Fatty Acid Synthesis isotig09389_8 Nicotinate Metabolism GG7OGXE04JE59A_4 Immune Response isotig02553_6 Unknown Function GG7OGXE04I2W6K_11 GG7OGXE04H9B1K_4 isotig04999_2 contig14227_4 GG7OGXE04IEQW7_11 isotig01027_19 isotig01199_17

MS spectra (95%)b

mean protein score


FCd

t test

protein name

match to NCBI

member RAS oncogene family like flotillin-1 glucose-regulated protein 94 actophorin

gi|291237085 gi|296531416 gi|148717303 gi|584723

7 2 4 5

157.7 113.7 146.0 197.3

19.1 28.4 18.7 21.7

0.3 5.3 3.8 4.7

2.1 × 10−05 3.9 × 10−05 0.00350 0.00068

cytochrome c oxidase, subunit VB cytochrome c oxidase subunit 5A cytochrome c oxidase subunit 6A1

gi|170037183 gi|307181008 gi|332016579

5 5 3

55.0 89.7 119.3

7.4 12.8 42.2

0.5 0.6 4.5

3.5 × 10−06 0.00161 0.00573

polyadenylate-binding protein histone variant H2A.Z poly(A) binding protein, cytoplasmic

gi|242025596 gi|92430141 gi|119627666

2 8 2

63.3 132.0 111.7

4.4 21.5 15.7

3.4 0.3 17.3

1.8 × 10−05 3.1 × 10−05 0.01205

60S acidic ribosomal protein P2 eukaryotic translation initiation factor 5A ribosomal protein L11 ribosomal protein L23 40S ribosomal protein S10

gi|156541150 gi|45594242

10 3

307.7 98.7

45.0 9.3

0.3 9.2

0.00055 0.00067

gi|149898923 gi|237862652 gi|149287004

2 3 6

38.3 114.7 149.0

9.3 25.9 26.3

2.8 1.8 4.4

0.00366 0.00373 0.02818

10

223.7

16.9

1.5

0.00012

enolase-phosphoglycerate dehydratase glycogen phosphorylase

gi|3023702 gi|256078113

3

94.0

23.8

4.9

0.02495

citrate synthase malate dehydrogenase ATP synthase subunit α adenylate kinase isoenzyme 1 alanine aminotransferase 2

gi|211970692 gi|30313543 gi|327259463 gi|46048771 gi|301604186

2 11 55 4 3

107.3 436.7 724.7 193.3 118.3

16.7 45.4 37.7 25.3 37.2

11.1 3.0 0.7 2.1 4.3

0.00027 0.00130 0.00071 0.00072 3.2E05

tropomyosin tropomyosin troponin C myosin heavy chain

gi|219806586 gi|40548509 gi|11596085 gi|332016579

24 30 17 108

388.0 536.7 272.7 1540.3

42.7 67.6 23.5 37.9

0.4 1.7 1.7 0.6

7.4 × 10−05 0.02381 0.00181 0.00691

β-tubulin tubulin β chain tubulin α-1 chain β-tubulin cytoplasmic intermediate filament α-actinin

gi|112983456 gi|18202612 gi|135393 gi|162138821 gi|4468777 gi|23394914

10 9 18 20 9 2

105.7 129.0 142.3 229.7 125.0 99.0

34.1 34.9 29.5 38.1 19.0 9.4

2.7 3.2 2.0 2.0 0.6 4.3

7.1 × 10−05 0.00051 0.01048 0.00058 0.00025 0.00160

propionyl Coenzyme A carboxylase

gi|291231485

3

107.3

44.5

7.6

0.00074

NAD(P) transhydrogenase

gi|291237202

2

151.7

16.1

7.7

0.00389

peroxiredoxin 5

gi|68348725

4

126.7

14.5

0.5

0.00544

AGAP006539-PA ENSANGP00000031917 MGC52856 protein translationally controlled tumor protein homologue tissue specific transplantation antigen P35B HsjCib isoform3 GK22596

gi|158296019 gi|156544915 gi|156550773 gi|6094441

3 19 8 8

85.3 312.0 112.7 169.0

17.8 37.1 18.5 16.8

5.2 0.5 1.5 0.6

7.0 × 10−05 0.00111 0.00015 0.00067

gi|198429145

2

81.7

15.3

9.6

0.00084

gi|301016775 gi|195449180

3 3

141.0 101.0

27.3 35.1

1.9 1.4

0.01393 0.02920

1352



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Table 5. continued juv/com (116/115)

a

P. vexillosa accession no. Unknown Function isotig09000_2 isotig11297_7 isotig02332_7 isotig11971_3 GG7OGXE04I0L1W_5 isotig07008_14 isotig10914_11 GG7OGXE04J2739_5 isotig07283_11 isotig09602_5 isotig04973_18 isotig08763_12

protein name hypothetical protein LOC100437967 predicted protein predicted protein hypothetical protein BRAFLDRAFT_125432 hypothetical protein DAPPUDRAFT_306867 hypothetical protein BRAFLDRAFT_119024 hypothetical protein hypothetical protein hypothetical protein HMPREF9373_1309 hypothetical protein BRAFLDRAFT_57028 hypothetical protein BRAFLDRAFT_91427 hypothetical protein LOC100563079

match to NCBI

MS spectra (95%)b

mean protein score


FCd

t test

gi|297700717

3

80.7

17.9

3.0

4.7 × 10−05

gi|156371397 gi|198419013 gi|260787771

4 7 2

90.3 201.0 42.3

13.5 21.1 5.8

0.4 6.3 0.5

7.3 × 10−05 0.02041 0.00011

gi|321464090

3

95.0

23.5

3.4

0.00024

gi|260801054

16

425.0

25.0

0.6

0.00032

gi|257206712 gi|82539920 gi|333368738

3 9 28

70.7 69.7 382.0

13.0 4.8 33.5

2.8 0.2 1.7

0.02321 0.00049 0.00052

gi|260804392

3

74.0

10.1

0.3

0.00318

gi|260826283

4

86.3

8.3

1.3

0.00432

gi|327272654

8

280.7

30.2

5.9

0.01158

a Accession nos. refer to contig no. in transcriptome database. bValues indicate the number of MS spectra used for identification and quantification of the proteins. cEstimate only, based on a match to an EST which may represent an incomplete sequence. dFC: Fold change (p < 0.05). Protein ratios in three biological replicates with 1.3 up-regulated.

abundant cytoskeleton transcripts during the larval−juvenile transition at the translational level may be related to muscular tissue development and structural reorganization of body patterns. This morphological rearrangement may be mediated by other sets of proteins, such as ATP synthase, methionine adenosyltransferase, voltage-dependent anion channel 1, calmodulin, ubiquitin, and stress proteins which regulate apoptosis, protein degradation, cell proliferation, and cell differentiation processes.2−4 Furthermore, cytoskeleton proteins play an important role in cell and tissue assembly and the movement and disassembly of muscle filaments during metamorphosis.39 Abundant expression of transcripts encoding metabolic enzymes and proteins could play an important role in transport and carbohydrate and fatty acid metabolisms. Abundant expression and accumulation of energy metabolism transcripts and their protein products at the competent stage may be required to advance competency and the metamorphosis process. The increased expression of HSPs and 14-3-3 proteins (Figure 6B, Table 5) at the competent stage may be related to external stimuli. Polychaete larvae respond to various chemical cues for attachment and metamorphosis.2 Larvae swim for several hours before attaining competency, and then begin searching the substratum to settle.40,41 The abundant expression of stress proteins may be required to counter the damage caused by oxidative stress.42 This argument was further supported by our previous report on up-regulation of stress proteins in competent larvae of P. vexillosa.3,4 Food deprivation in nonfeeding larvae could stimulate abundant expression of these proteins. Taken together, stress proteins might play an important role in attaining larval competency. The interplay between transcriptional dynamics and protein signaling mechanisms is particularly important to regulate molecular processes in invertebrate development.43 The specific regulatory pathways in a given species may be either unique or conserved across the species.44 The underlying molecular

method to identify hundreds of differentially expressed proteins.36,37 In our study, we used the transcriptome database of the tested species (P. vexillosa) for protein identification. Furthermore, we repeated the homology-based identification search algorithm using the same database containing the reversed or decoy sequences. We have identified the potential false positives and subsequently removed them from the data set. Using this improved method, we identified a total of 107 differentially expressed proteins of polychaete worm with a high confidence (95%) level. Furthermore, these proteins represented a wide range of biological processes, such as cell signaling, metabolism (glycolysis, citric acid cycle, and fatty acid synthesis), transcription, translation, transport, muscle contraction, immune response, and oxidative phosphorylation during polychaete larval development and metamorphosis. Our results demonstrate that the substantial increase in number of differential proteins highlights advantages of genome databases and gel-free proteomics methods to increase the depth of polychaete worm’s larval proteome. Furthermore, the up/down regulation of these proteins may lead to turning signaling pathways “on” or “off” to regulate competency and metamorphic processes. 4.2. Signaling Molecules at the Transcription/Translation Level Regulate Larval Metamorphosis

On the basis of the current findings and previous reports, transcriptional and translational regulation via signaling molecules and metabolic enzymes/proteins possibly controls competency and metamorphosis.5,6,8,38 The abundant ribosomal and gene products of GA21728-RA transcripts likely encode proteins required for transcriptional regulation and protein synthetic machinery. In general, polychaetes larval growth primarily involves the formation of segment-specific structures (chaetae) and the addition of terminal chaetigers throughout their development.1,2 Up-regulation of several 1353



Article

Table 6. Pseudopolydora vexillosa Proteins Showing Differential Expression during the Competency (com/pcom) and Metamorphosis (juv/com) com/pcom (115/114)

P. vexillosa accession no.a Signaling isotig06693_6 isotig13013_5 isotig09326_6 isotig00694_1 GG7OGXE04JDTT X_11 Oxidative Phosphorylation isotig01047_4 isotig07242_10 Transcription isotig06675_20 GG7OGXE04JO4CS_2 isotig05665_23 Translation isotig01877_5 F5K2Q4C01BC62U_4 isotig07958_12 isotig00375_18 contig03176_15 Glycolysis GG7OGXE04II6NM_9 isotig04559_7 Citric Acid Cycle isotig00627_7 Transport contig11757_8 isotig01393_14 GG7OGXE04H5PNK_6 ATP Synthesis isotig05898_11 isotig12272_8 Cell Adhesion isotig12998_7 amino-acid synthesis isotig03166_3 Muscle Contraction isotig09793_5 contig03478_8 isotig03113_21 Structure and Integrity isotig01330_11 GG7OGXE04IC3E1_2 GG7OGXE04JTLJP_6 Unknown Function F5K2Q4C01AOVN0_2 F5K2Q4C01BVDO5_6

juv/com (116/115)

match to NCBI

MS spectra (95%)b

mean protein score


FCd

t test

FCd

t test

gi|291230121

7

225.0

18.4

1.4

2.7 × 10−7

0.5

0.00040

gi|75003550

4

91.7

13.4

1.5

0.00056

6.3

2.0 × 10−5

gi|66774602 gi|219113539 gi|66472746

4 4 3

72.7 65.3 91.0

9.9 18.8 18.3

1.4 1.3 0.7

0.00057 0.00108 0.01236

0.4 2.3 4.2

0.00046 0.00585 0.01741

cytochrome c oxidase polypeptide VIc cytochrome c oxidase subunit II

gi|323510614

2

64.0

19.5

0.5

0.01358

6.4

1.9 × 10−9

gi|5835796

2

75.7

13.7

0.2

0.00170

6.1

0.00036

heterogeneous nuclear ribonucleoprotein D histone H2B polypyrimidine tract binding protein

gi|291243919

12

183.0

11.7

1.3

7.5 × 10−6

0.2

2.3 × 10−9

gi|297677453 gi|66472746

27 4

265.3 169.3

56.3 6.4

0.5 0.4

6.3 × 10−5 0.00019

0.2 2.7

0.00085 0.01601

elongation factor 1-β ribosomal protein S3 ribosomal protein rpl31 eukaryotic translation elongation factor 1 elongation factor 1-γ

gi|311272937 gi|328683380 gi|158187882 gi|89266868

5 4 2 6

158.7 54.0 76.3 264.0

13.7 7.4 12.3 15.8

0.6 1.5 1.5 0.6

0.01081 0.00174 0.00038 0.00330

gi|296434302

12

217.3

18.6

1.3

4.0 × 10−5

0.5

0.00177

4

67.0

12.5

1.5

0.00937

3.7

1.4 × 10−5

gi|260063826

14

509.0

46.3

1.4

4.6 × 10−6

3.9

0.00113

succinate dehydrogenase iron−sulfur protein

gi|56435063

3

142.0

13.4

1.3

0.00047

1.7

0.00047

extracellular hemoglobin linker globin major vault protein

gi|81337684

12

338.7

32.1

1.5

0.00073

1.9

0.00012

gi|13810245 gi|291227613

15 2

270.3 72.7

25.9 12.0

2.0 1.4

0.00024 0.00214

0.6 0.5

0.00013 0.00328

SNaK1 calcium-transporting ATPase variant

gi|15824396 gi|260181326

9 3

273.0 69.7

10.6 9.0

0.6 1.3

0.00240 0.00345

1.7 0.4

0.01375 0.00120

bryohealin precursor

gi|192758422

22

459.7

30.6

0.5

0.00088

1.9

0.01451

adenosylhomocysteine kinase B

gi|213513453

4

164.0

40.0

1.4

0.00037

5.3

0.02456

paramyosin Troponin I myosin regulatory light chain

gi|318609972 gi|226481381 gi|10440990

7 15 27

180.3 383.0 394.7

31.0 25.2 26.4

1.3 1.5 1.7

0.00291 0.00006 1.2 × 10−6

0.5 0.2 0.5

6.6 × 10−5 3.0 × 10−5 0.01805

β-actin spectrin, α β-tubulin

gi|330858318 gi|149738010 gi|37651156

52 2 6

511.7 125.7 54.0

47.6 11.9 17.2

0.6 1.4 1.6

0.01165 8.8 × 10−6 0.00029

3.6 3.9 0.7

0.00109 0.00194 0.01210

predicted protein predicted protein

gi|156382186 gi|156408806

3 3

89.7 97.7

8.5 14.7

0.5 0.5

0.00278 0.00684

protein name guanine nucleotidebinding protein guanine nucleotidebinding protein 14-3-3-like protein calcium binding protein rho guanine dissociation factor isoform

fructose-bisphosphate aldolase phosphoglycerate mutase

gi|6225038

1354

14.6 0.4 0.5 12.5

19.4 26.2

3.1 × 10−5 4.7 × 10−5 6.6 × 10−5 0.00012

8.1 × 10−5 0.00027



Article

Table 6. continued com/pcom (115/114)

P. vexillosa accession no. Unknown Function isotig11394_8 F5K2Q4C01CF4OT_4 GG7OGXE04IY16R_10 isotig11518_4 isotig06268_7 isotig12977_10

a

juv/com (116/115)

mean protein score


FCd

t test

FCd

t test

protein name

match to NCBI

MS spectra (95%)b

unnamed protein product hypothetical protein CRE_00778 hypothetical protein CRE_04863 hypothetical protein DAPPUDRAFT_208250 hypothetical protein BRAFLDRAFT_70615 hypothetical protein BRAFLDRAFT_118409

gi|313227726 gi|308511873

3 42

67.7 284.3

12.1 36.1

1.7 0.5

0.00659 0.00340

0.4 4.8

0.02754 7.4 × 10−5

gi|308497032

5

176.3

27.0

0.6

0.02224

0.8

0.00015

gi|321475473

3

123.3

12.6

1.7

0.02493

4.0

8.1 × 10−6

gi|261289579

2

106.3

13.4

0.4

0.00033

3.5

2.0 × 10−5

gi|260835699

2

66.7

5.6

0.2

2.9 × 10−5

2.3

0.01886

a

Accession nos. refer to contig no. in transcriptome database. bValues indicate the number of MS spectra used for identification and quantification of the proteins. cEstimate only, based on a match to an EST which may represent an incomplete sequence. dFC: Fold change (p < 0.05). Protein ratios in three biological replicates with 1.3 up-regulated.

Figure 6. Differential expression of abundant transcripts at the translational level in precompetent larvae (P), competent larvae (C), and juveniles (J) of P. vexillosa. 20 μg of protein lysate was separated on a 10% SDS-PAGE gel and transferred onto Immobilon transfer membranes. The membranes were incubated with 1:500 diluted primary antibodies and then probed with horseradish peroxidaseconjugated secondary antibodies. The X-ray film was developed with a WesternBright ECL detection kit. Three biological replicate protein samples were used for Western blot analysis.

Figure 5. Functional categories of differentially expressed proteins: (A) precompetent to competent stages; (B) competent to juvenile stages. Up-regulation or down-regulation assignment was done for statistically (p < 0.05) significant proteins.

competency and metamorphosis of polychaete worms. This observation supports our hypothesis that key molecular pathways may regulate larval metamorphosis in polychaetes. MAP kinases respond to external stimuli such as oxidation stress and chemical cues to regulate cell proliferation, differentiation, and apoptosis, through the MAPK signaling cascade.45,46 In a previous study, we reported that the p38 MAPK-dependent pathway plays an important role in regulating larval metamorphosis of polychaete worm H. elegans.5 The up-regulation of p38 MAPK and pp38 MAPK in a competent stage (Figure 6A) may initiate the signaling cascade to induce larval competency. In recent studies, p38 MAPK was shown to be activated during larval settlement of barnacle B.amphitrite.8 The MAPK signaling pathway in marine mollusks and shrimps was found be regulated by Ras proteins.47,48 The downstream transcription factor, c-Myc,

changes during larval developmentsuch as competence, settlement, response to cues, and initiation of metamorphosisare likely to be regulated by transcriptional and translational controls. It would be essential to elucidate the functions of known individual transcripts and their relative abundance. EST data sets provide a ready source of test genes for this purpose. 4.3. Molecular Pathways Associated with Larval Metamorphosis in Polychaetes Worms and Other Marine Invertebrates

The identification of several transcripts belonged to the p38 MAPK pathway, the calcium signaling pathway, the notch signaling pathway, and the Wnt/β-catenin pathway indicates the importance of signal transduction pathways during larval 1355



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could drive cell proliferation, differentiation, and apoptosis by activating the MAPK/ERK pathway.49 The calcium binding pathway directs many cellular processes, including cellular excitability, exocytosis, motility, apoptosis, and gene transcriptions during metamorphosis.50 Calcium serves as a secondary messenger during metamorphosis in a number of marine invertebrates.51 In polychaete H. elegans, the continuous expression of calcium dependent CaM gene was shown to be involved in tissue differentiation and development.6 In barnacle B. amphitrite, CaM inhibition led to reduction of the enzymatic activities of MLCK and CAMK, which subsequently inhibited settlement and metamorphosis. CaM also affected downstream kinases of calmodulin kinase II (CaMK) and myosin light chain kinases during larval attachment of B. amphitrite.52 Taken together, CaM has important functions in the larval metamorphosis of polychaete worms and other marine invertebrates. Notch signaling pathways represent a highly conserved cell signaling system present in most multicellular organisms.53 The CapI-notch gene was shown to be expressed in the segments and terminal proliferation site in larval and juvenile stages of polychaete Capitella sp. I.7 In zebrafish, somitogenesis was regulated by the notch pathway.54 Wnt/β-catenin signaling was shown to be regulated segmentation process of the marine polychaetes Capitella capitata and H. elegans.55 The high abundance of β-catenin transcripts indicated potential significance of the canonical Wnt pathway in the development of C. capitata. Recently, we identified abundant expression of transcripts related to Wnt signaling pathways in bryozoan B. neritina.9 Temporal-spatial gene expression of several Wnt pathway genes revealed Wnt ligands BnWnt10 and BnsFRP could be involved in patterning of the developing polypide. In other marine invertebrates, such as cnidarians, sea urchins, and ascidians, Wnt/β-catenin pathway regulated developmental events, including body axis formation, central nervous system formation, axial patterning, and body regeneration.56−58

expressed transcripts of histones, HSP-70, and 14-3-3 at the translational level. The results of this comparison showed that transcripts and their coding proteins representing the majority of the biological processes indicate the complex regulatory mechanisms during larval metamorphosis of polychaetes. The complex relationship between the transcriptome and proteome may be due to tight regulation of multiple processes during larval metamorphosis.13 In contrast to the proteomics data, transcriptome data showed many transcripts involved in several molecular pathways. Surprisingly, most of the proteins coded by these transcripts were not identified in the proteome data set. However, the expression of p38 MAPK and pp38 MAPK transcripts was confirmed at the translational level by Westernblot analysis. A possible explanation for this discrepancy may be related to low-abundant expression of these proteins. Furthermore, usage of whole larvae for proteome analysis most likely limits the identification of low abundant proteins. To support this argument, none of these transcripts were identified as abundant transcripts (Table 2). Another likely explanation could be the statistical approach chosen to define differential expression of these proteins. In our proteomic study, the quantitative ratio used to determine the level of significance was within the range of the 0.769−1.3 threshold. The proteins identified beyond this range were not considered for quantitative analysis. Although we identified a total of 518 proteins from 1247 unique peptides, only 107 proteins were statistically significant for quantification. 4.5. Application of P. vexillosa Transcriptome Data

There are a number of meaningful applications of the raw data or the annotated genes from the P. vexillosa EST database. Mass spectra can be used to search against the EST translated protein database to facilitate protein identifications in the absence of complete genome sequences.59 Gene expression protocols can be designed to identify and analyze genes with similar expression patterns at a certain time point.60 Co-expressed genes are of interest because they are functionally related, and their co-expression signifies a common regulatory system.61 Raw reads of P. vexillosa are available in the public domain (http://www.ncbi.nlm.nih.gov/sra?term= pseudopolydora%20vexillosa), which might suggest new directions in understanding regulatory mechanisms of larval metamorphosis in marine polychaetes. The function of most genes in polychaete worms is not yet known. A search of a transcriptome database can give researchers a list of all the related transcripts in which a gene is expressed, providing clues to its possible function in a given pathway.

4.4. Comparison of Transcriptome and Proteome Data Sets

Comparison of different “OMICS” data sets is a promising approach to elucidate the regulatory processes at the transcriptional and translational levels.20−22 In this study, transcriptome and proteome profiles revealed that the majority of abundant transcripts (Table 2) and proteins (Table 4−6) were overlapped in two data sets of larval-adults stages. An abundance of 41 transcripts was observed in the transcriptome while the majority of differentially expressed proteins (overlapped with transcriptome) were up-regulated during larval competency and metamorphosis. For example, many abundantly expressed transcripts belonging to biological processes such as translation, transcription, signal transduction, cytoskeleton, and metabolism were also identified in the protein data set. Similarly, molecular functions such as protein binding, catalytic enzyme activity, and response to stress were equally represented. Abundant expression of transcripts corresponded well to the differentially expressed proteins. For instance, glycolysis and citric acid cycle enzymes including malate dehydrogenase, succinate dehydrogenase, and fructose 1,6bisphosphate were differentially expressed in protein data (Tables 5 and 6) while all three transcripts coding to these enzymes were abundantly expressed in transcriptome data. This indicates that transcribed abundant mRNA is linked to differential expression of these transcripts at the translational level. Further, we observed a positive correlation of abundantly

5.0. CONCLUSION We report for the first time the comprehensive transcriptome and proteome profiling during larval development and metamorphosis of a marine polychaete. In terms of biological processes, transcripts related to cellular and metabolic processes were abundant and four key metabolic pathways were enriched. Transcripts related to molecular function such as binding and catalytic activity were highly represented. The establishment of transcript database facilitated the identification of a large number of proteins. LC-MS/MS-based proteome data showed differential expressed proteins in active biological processes. A substantial number of metabolic enzymes relevant to glucose and fatty acid metabolism were differentially regulated. The glycolytic enzymes were up-regulated during competency and metamorphosis. The enzyme related to citric acid cycle was up1356



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phosis in the spionid polychaete Pseudopolydora vexillosa. BMC. Dev. Biol. 2011, 25 (11), 31. (5) Wang, H.; Qian, P. Y. Involvement of a novel p38 mitogenactivated protein kinase in larval metamorphosis of the polychaete Hydroides elegans (Haswell). J. Exp. Zool. (Mol. Dev. Evol.) 2010, 314B, 390−402. (6) Chen, Z. F.; Wang, H.; Qian, P. Y. Characterization and expression of calmodulin gene during larval settlement and metamorphosisof the polychaete Hydroides elegans. Comp. Biochem. Physiol. B 2012, 162 (4), 113−119. (7) Thamm, K.; Seaver, E. C. Notch signaling during larval and juvenile development in the polychaete annelid Capitella sp. I. Dev. Biol. 2008, 320, 304−318. (8) Li-Sheng, H. E.; Xu, Y.; Matsumura, K.; Zhang, Y.; Zhang, G.; Qi, S. H.; Qian, P. Y. Evidence for the involvement of p38 MAPK activation in barnacle larval settlement. PLoS One 2012, 7 (10), e47195. (9) Wong, Y. H.; Wang, H.; Ravasi, T.; Qian, P. Y. Involvement of Wnt signaling pathways in the metamorphosis of the bryozoan Bugula neritina. PLoS One 2012, 7 (3), e33323. (10) Chandramouli, K. H.; Zhang, Y.; Wong, Y. H.; Qian, P. Y. Comparative glycoproteome analysis: Dynamics of protein glycosylation during metamorphic transition from pelagic to benthic life stages in three invertebrates. J. Proteome Res. 2012, 11, 1330−1340. (11) Patterson, S. D.; Aebersold, R. H. Proteomics: The first decade and beyond. Nat. Genet. 2003, 33, 311−323. (12) Chamrad, D. C.; Korting, G.; Stuhler, K.; Meyer, H. E.; Klose, J.; Blüggel, M. Evaluation of algorithms for protein identification from sequence databases using mass spectrometry data. Proteomics 2004, 4, 619−628. (13) Wang, H.; Zhang, H.; Wong, Y. H.; Voolstra, C.; Ravasi, T.; Bajic, V. B.; Qian, P. Y. Rapid transcriptome and proteome profiling of a non-model marine invertebrate, Bugula neritina. Proteomics 2010, 10, 1−10. (14) Zhang, W.; Li, F.; Nie, L. Integrating multiple ’omics’ analysis for microbial biology: application and methodologies. Microbiology 2010, 156, 287−301. (15) Meyer, E.; Aglyamova, G. V.; Wang, S.; Buchanan-Carter, J.; Abrego, D.; Colbourne, J. K.; Willis, B. L.; Matz, M. V. Sequencing and de novo analysis of a coral larval transcriptome using 454 GS Flx. BMC Genomics 2009, 10, 219. (16) Chen, Z. F.; Matsumura, K.; Wang, H.; Arellano, S. M.; Yan, X.; Alam, I.; Archer, J. A.; Bajic, V. B.; Qian, P. Y. Toward an understanding of the molecular mechanisms of barnacle larval settlement: a comparative transcriptomic approach. PLoS One 2011, 6 (7), e22913. (17) Moya, A.; Huisman, L.; Ball, E. E.; Hayward, D. C.; Grasso, L. C.; Chua, C. M.; Woo, H. N.; Gattuso, J. P.; Forêt, S.; Miller, D. J. Whole transcriptome analysis of the coral Acropora millepora reveals complex responses to CO2-driven acidification during the initiation of calcification. Mol. Ecol. 2012, 21 (10), 2440−54. (18) Vera, J. C.; Wheat, C. W.; Fescemyer, H. W.; Frilander, M. J.; Crawford, D. L.; Hanski, I.; Marden, J. H. Rapid transcriptome characterization for a non-model organism using 454 pyrosequencing. Mol. Ecol. 2008, 17, 1636−1647. (19) Clark, M. S.; Thorne, M. A. S.; Vieira, F. A.; Cardoso, J. C. R.; Power, D. M.; Peck, L. S. Insights into shell deposition in the Antarctic bivalve Laternula elliptica: gene discovery in the mantle transcriptome using 454 pyrosequencing. BMC Genomics 2010, 11, 362. (20) Desgagné-Penix, I.; Khan, M. F.; Schriemer, D. C.; Cram, D.; Nowak, J.; Facchini, P. J. Integration of deep transcriptome and proteome analyses reveals the components of alkaloid metabolism in opium poppy cell cultures. BMC Plant Biol. 2010, 10, 252. (21) Hornshøj, H.; Bendixen, E.; Conley, L. N.; Andersen, P. K.; Hedegaard, J.; Panitz, F.; Bendixen, C. Transcriptomic and proteomic profiling of two porcine tissues using high-throughput technologies. BMC Genomics 2009, 19, 10−30. (22) Lippert, D. N.; Ralph, S. G.; Phillips, M.; White, R.; Smith, D.; Hardie, D.; Gershenzon, J.; Ritland, K.; Borchers, C. H.; Bohlmann, J.

regulated during the competency whereas citrate synthase and adenylate kinase and propionyl coenzyme A carboxylase were up-regulated during metamorphosis. Overall, the abundant genes/proteins identified by both technologies were well correlated. Identified genes and proteins linked to various metabolic pathways reflect the existence of active biological processes regulating larval development and metamorphosis of polychaete worms. Furthermore, the above findings bring new insights or generate new hypotheses for further investigation of molecular mechanisms that regulate larval development and metamorphosis of polychaetes.

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ASSOCIATED CONTENT

S Supporting Information *

Figures showing (1) average length of quality filtered sequences as determined by MG-RAST, and (2) KEGG-based functional assignment of transcripts. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel: 0852-2358-7331. Fax: 0852-2358-1559. E-mail addresses: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank Dr. Salim Bougouffa for technical help in MG-RAST data analysis, Dr. Taewoo Ryu for reviewing the transcriptome data, Ms. Cherry Kwan for proofreading the manuscript, and Dr. Wang Yong for figures preparation. This study was supported by a grant from China Ocean Mineral Resources Research and Development (DY125-15-T-02), a grant from Sanya Institute of Deep-Sea Science and Engineering (SIDSSE-201206), and award SA-C0040/UK-C0016 from the King Abdullah University of Science and Technology to PY Qian.

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ABBREVIATIONS GO, gene ontology; MAPK, mitogen-activated protein kinase; CaM, calmodulin; 2-DE, two-dimensional gel electrophoresis; MS, mass spectrometry; EST, expressed sequence tags; iTRAQ, isobaric tags for relative and absolute quantification; SRA, sequence reads archive; ORF, open reading frame; DAVID, Database for Annotation, Visualization and Integrated Discovery; MG-RAST, Metagenomics Rapid Annotation using Subsystems Technology; FDR, False Discovery Rate; HSP-70, heat shock protein-70; 14-3-3, tyrosine hydroxylase; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; CaMK, calmodulin kinase II

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REFERENCES

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