Dynamics of the Striped Bass (Morone saxatilis) - American Chemical

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Dynamics of the Striped Bass (Morone saxatilis) Ovary Proteome Reveal a Complex Network of the Translasome Benjamin J. Reading,*,† Valerie N. Williams,† Robert W. Chapman,‡ Taufika Islam Williams,§ and Craig V. Sullivan† †

Department of Biology and §Mass Spectrometry Facility, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, United States ‡ South Carolina Department of Natural Resources, Charleston, South Carolina, United States S Supporting Information *

ABSTRACT: We evaluated changes in the striped bass (Morone saxatilis) ovary proteome during the annual reproductive cycle using label-free quantitative mass spectrometry and a novel machine learning analysis based on K-means clustering and support vector machines. Modulated modularity clustering was used to group co-variable proteins into expression modules and Gene Ontology (GO) biological process and KEGG pathway enrichment analyses were conducted for proteins within those modules. We discovered that components of the ribosome along with translation initiation and elongation factors generally decrease as the annual ovarian cycle progresses toward ovulation, concomitant with a slight increase in components of the 26S-proteasome. Co-variation within more than one expression module of components from these two multi-protein complexes suggests that they are not only co-regulated, but that co-regulation occurs through more than one sub-network. These components also co-vary with subunits of the TCP-1 chaperonin system and enzymes of intermediary metabolic pathways, suggesting that protein folding and cellular bioenergetic state play important roles in protein synthesis and degradation. We provide further evidence to suggest that protein synthesis and degradation are intimately linked, and our results support function of a proteasome−ribosome supercomplex known as the translasome. KEYWORDS: ribosome, proteasome, translasome, ovary, reproduction, mass-spectrometry, support vector machines, teleost, fish

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INTRODUCTION

stability of proteins involved in a wide range of cellular processes. If the cell produces more proteins than the UPS can effectively turnover, then apoptosis occurs.3 Likewise, if protein synthesis cannot keep up with degradation, then the cell will eventually become devoid of protein over time. Therefore, a regulatory mechanism linking protein synthesis and degradation must exist if homeostasis is maintained,4 and several studies have already established elementary linkages between these processes.1,5−10 On average, 30% of eukaryotic cellular proteins are mistranslated by the ribosome or improperly folded during synthesis, and these defective products are cotranslationally degraded by the 26S-proteasome.2,11 A supercomplex termed the translasome resulting from co-localization of ribosomes and proteasomes has been hypothesized to perform this co-translational degradation.12 However, a comprehensive listing of all interacting components of the translasome remains to be reported. Growing oocytes are in transcriptional stasis, acting as storehouses of specific maternal RNAs, proteins, and other

Cellular protein homeostasis depends on the balance of continuous protein synthesis and degradation. Rates of protein synthesis and degradation also define protein turnover, which underlies adaptation of eukaryotic cells and organisms to changing developmental states and physiological environments. Damaged proteins must be recycled and mistranslated proteins eliminated before they can act in dysfunctional manners. Complexes responsible for protein synthesis include the ribosome and associated translation initiation and elongation factors. The ribosome is a multi-protein complex comprised of a 60S-large and 40S-small subunit, which catalyzes protein translation through polymerization of amino acids using mRNA as template.1 Most intracellular proteins are degraded by another multi-protein complex, the 26S-proteasome.2 The 26Sproteasome comprises two subcomplexes: the 20S-catalytic core and the 19S-regulatory particle. Targeted destruction of proteins by the 26S-proteasome requires covalent linkage of ubiquitin and this process is mediated by a series of activating, conjugating, and ligating enzymes. These systems responsible for eukaryotic protein degradation are collectively termed the ubiquitin-proteasome (UPS), and together they regulate the © 2013 American Chemical Society

Received: November 1, 2012 Published: February 15, 2013 1691

dx.doi.org/10.1021/pr3010293 | J. Proteome Res. 2013, 12, 1691−1699

Journal of Proteome Research

Article

to the North Carolina State University Mass Spectrometry Facility (Raleigh, NC).

molecules required for fertilization competency and initiation of zygotic development,13,14 and therefore are appropriate models for study of protein turnover. In the present study, we characterize interactions of translasome components in the striped bass (Morone saxatilis) ovary proteome using a labelfree quantitative mass spectrometry based approach and our recently reported ovary transcriptome as a reference database.15 Additionally, since complex relationships are not maximally captured using traditional linear statistics,16 we report a novel analysis of proteomics data based on machine learning.

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Mass Spectrometry

Digests were reconstituted in 100 μL of liquid chromatography (LC) mobile phase A [H2O/acetonitrile/formic acid (90/10/ 0.2 vol %)]. All samples were subjected to ultrafiltration for 30 min at 15,000 rpm. Reversed phase HPLC separation and tandem mass spectrometry detection (nanoLC−MS/MS) was performed using an Eksigent (Dublin, CA) nanoLC-1D+ system with autosampler coupled to a hybrid Thermo Fisher LTQ Orbitrap XL mass spectrometer (Thermo Scientific, San Jose, CA). The nanoLC−MS/MS was operated with a continuous vented column configuration for inline trap and elute.20 The analytical column was a self-packed 75 μm internal diameter (i.d.) fused silica PicoFrit capillary (New Objective, Woburn, MA) with 15 cm of Magic C18AQ stationary phase (Michrom BioResources, Auburn, CA) in a methanolic slurry. The trap and dummy columns were self-packed 75 μm i.d. fused silica IntegraFrit capillaries (New Objective, Woburn, MA) with 5 and 20 cm of Magic C18AQ stationary phase (Michrom Bioresources, CA), respectively. The LC solvents used were mobile phase A and mobile phase B [H2O/ acetonitrile/formic acid (10/90/0.2 vol %)]. Blank runs (injections of mobile phase A) were performed after every sample run to minimize carryover. Sample and blank injections were 2 μL on column. Each of the three biological replicates from the four time points had three technical nanoLC−MS/MS runs. Analytical separations were performed on the nanoflow pump at 350 nL/min, initially maintaining 2% mobile phase B. The mass spectrometry (MS) method consisted of nine events: a precursor scan followed by eight data dependent tandem MS scans of the first−eighth most abundant peaks in the ion trap. A high resolving power precursor scan of the eluted peptides was obtained using the Orbitrap (60,000 resolution) with the eight most abundant ions selected for MS/MS in the ion trap through dynamic exclusion. This method aims at good coverage of low and high abundance peptides. The instrument was externally tuned and calibrated according to the manufacturer and polycyclodimethylsiloxane (PCM; MH+ = 445.120024) from ambient air was employed as the lock mass for internal calibration.21

METHODS

Sample Collection and Preparation

Female striped bass were reared in outdoor tanks at the North Carolina State University Pamlico Aquaculture Field Laboratory.17 Females were anesthetized with Finquel MS-222 (Argent Chemical Laboratories, Redmond, WA), and whole ovary tissues were collected by dissection or by biopsy using a plastic cannula inserted through the urogenital pore.18 Tissues were collected at four time points (N = 3 fish per point, all values are given as mean ± standard error of the mean): August (body weight 1.90 ± 0.35 kg; total length 512 ± 10.4 mm), November (3.80 ± 0.08 kg; 625 ± 3.45 mm), February (4.40 ± 0.54 kg; 626 ± 27 mm), and April (4.54 ± 0.79 kg; 663 ± 43 mm). As the striped bass is a group synchronous, single clutch, iteroparous spawner, the most advanced clutch of oocytes represented one of four stages of oocyte growth during these time points: early secondary growth (ESG), mid-vitellogenic (MVG), late-vitellogenic (LVG), or post-vitellogenic (PVG). The stage of ovarian development was initially judged from the season, the appearance of biopsy samples under a dissecting stereomicroscope fitted with a calibrated ocular micrometer, and the maximum diameter of oocytes in the biopsy samples (ESG 310 ± 12.6 μm; MVG, 503 ± 34.7 μm; LVG, 831 ± 160 μm; PVG, 986 ± 19.1 μm). The accuracy of the initial assignment of ovaries to stages was confirmed by histological examination and oocyte staging following Berlinsky and Specker.19 Tissues were fixed in a solution of 4% formaldehyde/1% glutaraldehyde solution in 0.1 M phosphate buffer (pH 7.2−7.4), dehydrated in an ethanol series, embedded in paraffin, sectioned at 4 μm, and routinely stained with hematoxylin and eosin at the North Carolina State University College of Veterinary Medicine Histology Laboratory (Raleigh, NC). Ovary tissues were frozen in liquid nitrogen and stored at −80 °C before being homogenized 1:4 (w/v) in Milli-Q ultrapure water (EMD Millipore Corporation, Billerica, MA). Extracts were centrifuged for 10 min at 13,000 rpm and 4 °C. The supernatant was diluted to 0.50 μg protein/μL with MilliQ water. Ten microliters of each sample was added to 15.5 μL of 50 mM ammonium bicarbonate and 1.5 μL 100 mM dithiothreitol and incubated at 95 °C for 5 min. Upon cooling, 3 μL of 100 mM iodoacetic acid was added, and samples were incubated at room temperature in the dark for 20 min. One microliter of 0.1 μg/μL porcine trypsin (Sigma, St. Louis, MO) was added, and samples were incubated at 37 °C for 3 h. An additional 1 μL of 0.1 μg/μL trypsin was added to each tube and incubated at 30 °C overnight. Formic acid (1.5 μL of a 5% aqueous solution) was added to each sample to quench the trypsin, and digests were dried to residues in a Savant speed vacuum (Thermo, San Jose, CA) for 30 min before submission

Protein Identifications

NanoLC−MS/MS data were processed by MASCOT (Matrix Science, Boston, MA). Protein sequences for human keratins, porcine trypsin, and the striped bass ovary transcriptome (GenBank: SRX007394)15 translated in all six open reading frames with OrfPredictor22 were manually combined into one FASTA file for MASCOT batch search (Supplementary File S1, Supporting Information). Vitellogenin gene transcripts are not expressed in the striped bass ovary,15,23 thus vitellogeninderived yolk proteins were not queried. The following variable and fixed amino acid modifications were allowed: variable methionine (M) oxidation, asparagine (N) and glutamate (Q) deamidation, and fixed cysteine (C) carbamindomethylation. MASCOT search parameters were as follows: maximum missed cleavages 2, peptide charge 1+, 2+ and 3+, peptide tolerance ±5 ppm, and MS/MS tolerance ±0.6 Da. Only those proteins with a probability >0.95 were reported. Protein Quantifications and Analysis

ProteoIQ (NuSep, Bogart, GA) recently made available a method of label-free quantitation of MS data. Briefly, spectral 1692



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Figure 1. Hierarchical clustering heat map of proteins expressed in striped bass ovary. The left panel shows the entire heat map of 355 proteins, and the right panels show select regions indicated by the brackets that are enlarged. Proteins are listed by contig number, name, and approved gene abbreviation if known. “NA” indicates proteins of unknown orthology. Contig open reading frames are given in parenthetical brackets. Ovary stages with different letters (a, b, or c) have significantly different proteomes by K-means clustering and support vector machines. Components of the ubiquitin-proteasome, protein synthetic machineries (ribosome and TCP-1), and intermediary enzymes are indicated to the right of the heat map in red, green, and blue text, respectively. A complete version of this figure, with protein names, is included as Supplementary File S4 (Supporting Information). 1693



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Figure 2. (A) Modulated modularity clustering (MMC) heat map of 355 correlated striped bass ovary proteins (29 modules). (B) Relevance networks of ovary proteins correlated within MMC modules (|r| ≥ 0.7). Color-coding of networks corresponds to the horizontal bar shown under the heat map in panel A. Only those relevance networks with 3 or more co-variable proteins are depicted. A ribosomal protein subcluster within module 25 is indicated by the black arrow. (C) Interactions between MMC modules 1−29 (|r| ≥ 0.3).

values were subjected to a one-way ANOVA (α = 0.05) using JMP Pro 9 (SAS Institute, Cary, NC), and residuals were input for modulated modularity clustering (MMC) performed using Pearson correlation coefficient.32 Relevance association networks were generated from the MMC modules using a locally written MATLAB pipeline to select those with |r| ≥ 0.7, which were then fed into Cytoscape (www.cytoscape.org). Interactions between MMC modules 1−29 were computed from the average associations among modules and used to generate relevance association networks as described above (|r| ≥ 0.3). The DAVID Functional Classification Tool33 was used to group proteins on the basis of functional similarity within MMC modules. Default parameters for DAVID were used and therefore only those MMC modules with 4 or more protein members were considered, as this is the minimum number of members required to detect Gene Ontology (GO) enrichment. The KEGG Orthology System34 was used to further explore the molecular systems of the proteasome, ribosome, and intermediary pathways.

counts for identified proteins were normalized to total spectral counts from MASCOT for each replicate. Shared peptides were apportioned among protein groups24 and normalized to protein length (NSAF).25,26 These normalized spectral counts (N-SC) for each of the three technical replicates per biological sample were exported from ProteoIQ and transformed to account for zero values [log10(y + 1), where y = N-SC]. We performed K-means clustering as an unsupervised learning tool to map protein expression [log10(y + 1) transformed N-SC values] to different stages of the annual reproductive cycle (ESG, MVG, LVG, and PVG) using WEKA version 3.6.7 (http://www.cs.waikato.ac.nz/ml/weka/). The Kmeans clusters n objects into k partitions based on attributes, in this case protein expression. We then evaluated the precision of clustering into 2, 3, and 4 clusters using WEKA sequential minimal optimization algorithm support vector machines (SVM) classifier.27 Hold-out estimates of classifier performance were conducted using a stratified cross-validation with n = 10 folds, where one fold was used for testing and n − 1 folds of the randomly reordered data set were used for training.

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RESULTS Representative images of the histological sections of the striped bass ovaries at the ESG, MVG, LVG, and PVG stage of development are provided as Supplementary File S2 (Supporting Information). Maximum oocyte diameters significantly differed between all ovarian stages except for LVG and PVG (analysis of variance F = 13.79, P = 0.002; followed by Newman−Keuls multiple range test, P ≤ 0.05). Data from the nanoLC−MS/MS and ProteoIQ are provided as Supplementary File S3 (Supporting Information). A total of

Graphic Representation of the Data

Approved gene abbreviations for all proteins were manually collected from the NCBI or GeneCards.28 Average N-SC values for identified proteins were exported from ProteoIQ as baseline log2 scale transformations. These values were normalized to the mean of each protein expressed across ovary stages and Cluster 3.0 was used to create a centroid linkage hierarchical clustering heat map (Spearman Rank Correlation)29,30 that was visualized using Java Treeview.31 The log10(y + 1) transformed N-SC 1694



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Table 1. Enrichment of Striped Bass Ovary Proteins by Gene Ontology (GO) Class within Modulated Modularity Clustering (MMC) Modules 12, 25, 26, and 28 Using DAVID MMC module 12 25

26

28

P-value

GO Class and protein members (contig)

enrichment score

3.06 Ribosome 4.10 × 10−5 Rps28 (11087), Rps16 (00157), Rpl31 (00051), Rpl38 (11185), Rpl22 (00840) Ribosome 3.7 × 10−52 24.44 Rpl13 (10709), Rps25 (00696), Rpl3 (09795), Rpl22l1 (02249), Rpl14 (11115), Rps3a (09669), Rps12 (10932), Rpl17 (02265), Rpl22 (03561), Rps14 (01136), Rps8 (09963), Rps18 (00105), Rpl15 (10800), Rps24 (11078), Rpl21 (09314), Rps11 (10659), Rps6 (01972), Rpl9 (10830), Rps4x (09952), Rpl7a (02265), Rps2 (10955), Rpl12 (09345), Rpl30 (09645), Rps23 (09464), Rpl7 (10144), Rplp0 (10309) Proteasome 6.4 × 10−11 3.15 Psmb1 (01203), Psma3 (01407), Psma4 (09310), Psma6 (09001), Psmd1 (01972) Ribosome 4.1 × 10−12 5.07 Rpl26 (11079), Rpl10a (10894), Rplp2 (10044), Rpl8 (00527), Rps10 (00848), Rps19 (10401), Rpl37a (00866) Proteasome 6.4 × 10−11 3.12 Psmd3 (10524), Psmc6 (00671), Psmd7 (09369), Psmb5 (03293), Psmb2 (02024) Chaperonin 5.4 × 10−7 2.77 Cct7 (03096), Hsp90ab1 (10309), Tcp1 (00465), Cct4 (09681) Proteasome 2.7 × 10−20 5.86 Psmc2 (10820), Psmc1 (00084), Psmb3 (10149), Vcp (10277), Psmd11 (05603), Psmc6 (03192), Psmd2 (09229), Psma1 (10845), Psmc3 (10514), Psma2 (00069) Ribosome 1.9 × 10−10 4.80 Rplp2 (01948), Rplp1 (00477), Rps13 (10658), Rps7 (10658), Rps5 (11189) Chaperonin 5.4 × 10−7 3.97 Hspa8 (09917), Cct5 (09515), Cct2 (00164), Cct6a (01964)

355 individual proteins were identified in ovary of striped bass, and only 11 (∼3%) were unknown, unique sequences (Supplementary File S4, Supporting Information). A total of 318, 307, 279, and 259 different proteins were detected in the ESG, MVG, LVG, and PVG samples, respectively. Therefore, between 73% and 90% of the total individual proteins indentified were expressed during each of the ovary stages. A total of 202 different proteins (57% of the total 355 proteins) had N-SC values >0 in all 4 ovary stages. Venn diagrams depicting different proteins expressed by ovary stage are provided as Supplementary File S5 (Supporting Information). Validation of K-means clustering by SVM indicates that grouping the expression data into 3 clusters (ESG, MVG, and LVG + PV) gives the best correct classification percentage (83.3%). Significant differences between the ovary proteome occur from PVG to ESG, ESG to MVG, and from MVG to LVG stages; there is no difference in the proteome from LVG to PVG stages (Figure 1). This clustering matches that of maximum oocyte diameter by stage, reinforcing the notion that PVG is a translationally quiescent stage during which females with fully grown oocytes await environmental conditions appropriate to commence final maturation. Proteins were organized on the basis of co-variable expression into 29 modules using MMC, and these are depicted in Figure 2A (see Supplementary File S6, Supporting Information). Relevance association networks within modules are depicted with edges between protein nodes determined by correlations exceeding a threshold value (|r| ≥ 0.7) (Figure 2B). Relevance association networks between modules are similarly depicted with edges representing average correlations where |r| ≥ 0.3 (Figure 2C). These are undirected networks, and therefore causality is unknown. We used DAVID to assess for each MMC module the degree to which GO biological processes and pathways are overrepresented. Four MMC modules (12, 25, 26, and 28) showed significant enrichment for proteasome, ribosome, and protein

chaperone (Table 1). The following KEGG pathways were enriched for all proteins in the data set (1.0 × 10−3 cutoff): ribosome (1.8 × 10−59), proteasome (5.5 × 10−25), pentose pathway (1.8 × 10−5), and glycolysis/gluconeogenesis (2.0 × 10−4).

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DISCUSSION We recently reported the first transcriptome database for species of the genus Morone15 and the present study provides the first proteomic characterization using this reference database. Proteome resources are currently available for other commercially important finfishes, including Atlantic salmon (Salmo salar),35,36 channel catfish (Ictalurus punctatus),37 rainbow trout (Oncorhynchus mykiss),38−40 Senegalese sole (Solea senegalensis),41 yellow perch (Perca f lavescens),42 gilthead seabream (Sparus aurata),43,44 and European seabass (Dicentrarchus labrax).45 Zebrafish (Danio rerio) is the only fish species with a published ovary proteome including over 1000 proteins.13,14,44,46 Many of these proteins were similarly identified in striped bass ovary and include metabolic enzymes, chaperones, and regulators of protein synthesis and degradation. MMC modules with the greatest intra-associations are located in the upper left of the heat map (Figure 2A), and such association deceases from left to right down the diagonal. Most groupings with the greatest intra-association (modules 1− 21) contain only 2−5 protein members, consisting mostly of dyads and triads (Supplementary File S6, Supporting Information). These small networks may represent feedforward loops, feedback loops, or bifans, which are common network motifs that carry out key regulatory functions within larger biological networks.47,48 As examples, the following proteins within these MMC modules have known regulatory functions: Nop58 (module 8); Lsm14b (module 11); Piwi11 (module 13); Nop56 (module 14); Snrpd2 (module 15); Ncl, Lsm14b and Pa2g4 (module 16); Ddx3y (module 17); Ddx4 1695



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(module 18); and Zar1 (module 19). Furthermore, the high degree of interdependent association between these modules suggests they may perform regulatory roles (Figure 2C). Sparsely populated MMC modules such as 3, 6, 11, 13, 21, and 22 appear as network hubs with more edges (7 to 8) than members (2 to 5 proteins). Identifying the presence of network motifs does not provide information to speculate directionality, since even 4-node bifans can have widely varying responses.49 The network motifs identified in the present study, however, will serve as the basis for additional experimentation aimed at understanding the intricacies of these interactions. In contrast, highly intraconnected MMC modules (23, 25, 26, and 28) are not interdependent, indicating that regulation of these units is divorced from other aspects of the protein networks. Modules 25, 26, and 28 collectively contain 187 proteins, representing over half of the proteome characterized in this study (Supplementary File S6, Supporting Information). Therefore, number of protein members within a module does not appear to positively correlate with putative regulatory importance evaluated as a measure of network interdependence. We used DAVID to evaluate GO class enrichment and discovered that three cellular pathways co-vary: (1) protein synthesis machinery, including the ribosome and associated components, such as translation initiation and elongation factors; (2) proteasome; and (3) chaperonin system. Three MMC modules (25, 26, and 28) are significantly enriched for proteasome (including regulation of ubiquitin ligase activity) and ribosome (including translational elongation), and two (26 and 28) are significantly enriched for protein chaperone system (including chaperonin TCP-1) (Table 1). Proteins in modules 25, 26, and 28 account for 64% (9 of the 14 components) and 47% (9 of the 19 components) of the 20S-catalytic core and 19S-regulatory particle of the proteasome, respectively and 50% (16 of the 32 components) and 39% (18 of the 46 components) of the ribosomal 40S-small and 60S-large subunits, respectively. An interesting feature of MMC module 25 is a subcluster of 30 proteins that includes 25 ribosomal components (Figure 2B), indicating a definitive role of protein synthesis. Six of the 8 proteins that form the hetero-oligomeric TCP-1 are present in MMC modules 26 (Tcp1, Cct4, and Cct7) and 28 (Cct2, Cct5, and Cct6a), and this complex acts as a molecular chaperone to fold nascent proteins.50 DAVID did not detect GO enrichment for intermediary pathways within MMC modules 25, 26, and 28; however, a small number of key metabolic enzymes were shown to also co-vary with protein synthetic and degradation machineries (Table 2). Co-variation of different components representing the 26Sproteasome and ribosome within three MMC modules suggests not only that these multi-protein complexes are co-regulated but that such co-regulation may occur in more than one manner. This phenomenon may not be accidental, since separating large supernetworks into smaller subnetwork partitions reduces complexity and has previously been identified in regulation of the different ribosomal subunits.1,48 Therefore, the ribosome and 26S-proteasome may communicate through multiple subnetworks and this may be the case for other cellular multi-protein complexes as well. As the ovary progresses from recrudescence (ESG) through the annual reproductive cycle (to PVG), an apparent reduction in protein synthetic capacity is observed (Figure 1). The TCP-1 components vary in their expression as the ovary progresses toward ovulation. The Cct5, Cct6a, and Cct7 increase, whereas

Table 2. Enzymes from Intermediary Pathways Assigned to Modulated Modularity Clustering (MMC) Modules 25, 26, and 28 intermediary pathway pyruvate metabolism

glycolysis and gluconeogenesis

tricarboxylic acid cycle

enzyme (contig) Pkm2 (03943, 02192) Glo1 (09544) Aldh7a1 (00630, 03089) Mdh1 (03576, 02200) Dld (04396) Gapdh (10005) Tpi1 (00660) Aldob (01458) Pkm2 (03943, 02192) Dld (04396) Aldh7a1 (00630, 03089) Adh5 (09434) Dld (04396) Mdh2 (00220) Idh2 (02438, 04323)

MMC module 26, 26 25, 26, 26 26 26 28 26, 26 25, 26 26 26 28

28 28 28

28 28

Cct4 decreases and Tcp1 and Cct2 remain stable. A slight increase in some protein translational components is observed during MVG, concomitant with active vitellogenesis.19,23 Reduction in synthesis of ribosomal proteins by late stage oocytes is characterized in the mouse,51 and cytoplasmic lattices have been shown to store ribosomal components within oocytes during a period of selective translational repression prior to ovulation.52,53 Due to our particular sample preparation, any such stored ribosomes would have been discarded along with other insoluble cell membranes following tissue homogenization. Therefore, the observed decrease in ribosomal proteins during LVG and PVG in striped bass ovary may reflect degradation or translocation to cytoplasmic lattices. Since such structures have not yet been described in fish oocytes, future study will be required to validate this possibility. In contrast, components of the protein degradation machineries are either slightly upregulated or remain unchanged as the ovary progresses through the annual reproductive cycle (Figure 1). This indicates that capacity for protein degradation remains intact even during periods of apparent translational quiescence (PVG). Reduction in ribosomes with concurrent increase in 20S-proteasomes is observed during stress1 and translation elongation factors are linked to UPS activity.9,11 A decrease in rate of protein translation during stress allows cells time to repair damage via the UPS, since they need not dedicate efforts toward monitoring nascent polypeptides.3 Additionally, maintaining the 26S-proteasome during nutrient deprivation provides the cell with a means to cannibalize extant proteins for energy.8 The role(s) of elongation factors during such perturbations is less clear; however they may act to inhibit premature degradation of polypeptides through their interactions with the UPS and substrates thereof. Six translation elongation factors were identified including Eef1g, Eef1a1, Eef1d, Eef1b2, Eef2, and Eef1a2. The Eef1a1 and Eef2 are assigned to MMC module 25, and Eef1d is assigned to MMC module 28 (Figure 2). Expression of some of these translation elongation factors decreases toward ovulation, whereas others remain unchanged (Figure 1). Other studies have provided evidence to suggest that translation initiation factors also associate with components of the proteasome.12 This poses an interesting, additional regulatory component to the system, since translation initiation 1696



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factor 3f (EIF3e) also acts as a deubiquitinase.54 Four translation initiation factors were identified in striped bass ovary, including Eif4h, Eif4e, Eif4a1, and Eif3b, and all four decrease in abundance toward ovulation. The Eif3b is assigned to MMC module 25 (Figure 2). The bioenergetic cost of proteins is not based on just synthesis, but degradation as well, especially for proteins with short half-lives, since ribosomes and proteasomes both consume ATP. Therefore, the rate of protein turnover is intrinsically dependent on bioenergetic affordability, and delegate metabolic enzymes from glycolysis, gluconeogenesis, pyruvate cycle, and tricarboxylic acid cycle (TCA) were identified in MMC modules 25, 26, and 28 (Table 2). A multipurpose regulatory role has already been reported for Gapdh, an enzyme that participates in not only glycolysis but also transcriptional activation.55 In addition to generating ATP, glycolysis provides biosynthetic intermediates that can be used for amino acid and nucleic acid synthesis and thus is an important cycle for anabolic processes such as protein synthesis.56 Pkm2 governs the fate of glucose in this regard. Mdh and Idh catalyze two of the TCA steps that generate reducing power (i.e., NADH), and each enzyme has isoforms that are expressed in the mitochondrion and cytosol. Additionally, Idh catalyzes the rate-limiting step of the TCA.

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ABBREVIATIONS UPS, ubiquitin-proteasome system; ESG, early secondary growth; MVG, mid-vitellogenic growth; LVG, late-vitellogenic growth; PVG, post-vitellogenic; LC, liquid chromatography; MS, mass spectrometry; MS/MS, tandem mass spectrometry; nanoLC−MS/MS, reversed phase HPLC separation and tandem mass spectrometry; N-SC, normalized spectral count; SVM, support vector machines; MMC, modulated modularity clustering; TCA, tricarboxylic acid cycle

CONCLUSIONS We used a novel analytical approach based on isotope-free quantitative MS/MS, machine learning, and MMC to show a direct and complex linkage between the cellular protein synthesis and degradation machineries and major bioenergetic metabolic pathways in the ovary. Although we are not the first to suggest the existence of a cellular translasome, we provide the first substantial index of proteins that potentially interact in such a manner. We report the structures of protein networks; however, our observations require additional experimental validations. Future studies aimed at uncovering the directionality of these interactions will allow us to understand how these combinations of proteins contribute to ovarian development, gamete quality, or pathology in striped bass and other vertebrate species. Since changes in cellular translational capacity, bioenergetics, and ribosome biogenesis rates are associated with various cancers, our findings and methodologies are relevant to human medicine as well.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Additional experimental data and figures. This material is available free of charge via the Internet at http://pubs.acs.org

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ACKNOWLEDGMENTS

We thank Andy S. McGinty and Michael S. Hopper (NCSU Pamlico Aquaculture Field Laboratory) for care and maintenance of the striped bass. This is an NAGRP Aquaculture Genome (NRSP-8) Project and C.V.S. is the striped bass NRSP-8 species coordinator. This work was supported by by the Center of Excellence in Oceans and Human Health CoEE Center for Marine Genomics at Hollings Marine Laboratory and by research grants R/MG-1019 and R/12-SSS from the North Carolina Sea Grant Program and the National Oceanic and Atmospheric Administration, by special grant NC09211 from the U.S. Department of Agriculture National Institute of Food and Agriculture, and by the North Carolina Agricultural Foundation, Inc. This manuscript is contribution number 703 of the Marine Resources Division of the South Carolina Department of Natural Resources.

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AUTHOR INFORMATION

Corresponding Author

*Tel: (919) 515-3830. Fax: (919) 515-2698. E-mail: bjreadin@ ncsu.edu. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. 1697



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Dynamics of the Striped Bass (Morone saxatilis) - American Chemical

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