An In-Depth Coho Salmon (Oncorhynchus kisutch) Ovarian Follicle Proteome Reveals Coordinated Changes Across Diverse Cellular Processes during the Transition From Primary to Secondary Growth
Corresponding Author
Emma Timmins-Schiffman
Department of Genome Sciences, University of Washington, Seattle, Washington, USA
Correspondence: Emma Timmins-Schiffman ([email protected])
Search for more papers by this authorJennifer Telish
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorChelsea Field
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorChris Monson
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorJosé M. Guzmán
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorBrook L. Nunn
Department of Genome Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorGraham Young
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorKristy Forsgren
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorCorresponding Author
Emma Timmins-Schiffman
Department of Genome Sciences, University of Washington, Seattle, Washington, USA
Correspondence: Emma Timmins-Schiffman ([email protected])
Search for more papers by this authorJennifer Telish
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorChelsea Field
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorChris Monson
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorJosé M. Guzmán
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorBrook L. Nunn
Department of Genome Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorGraham Young
School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA
Search for more papers by this authorKristy Forsgren
Fullerton, Biological Sciences, California State University, Fullterton, California, USA
Search for more papers by this authorFunding: Our work was supported by the National Science Foundation to Young (IOS-1921746) and Forsgren (IOS-1922541). Additional support came from the University of Washington's Proteomics Resource (UWPR95794).
ABSTRACT
Teleost fishes are a highly diverse, ecologically essential group of aquatic vertebrates that include coho salmon (Oncorhynchus kisutch). Coho are semelparous and all ovarian follicles develop synchronously. Owing to their ubiquitous distribution, teleosts provide critical sources of food worldwide through subsistence, commercial fisheries, and aquaculture. Enhancement of hatchery practices requires detailed knowledge of teleost reproductive physiology. Despite decades of research on teleost reproductive processes, an in-depth proteome of teleost ovarian development has yet to be generated. We have described a coho salmon ovarian proteome of over 5700 proteins, generated with data independent acquisition, revealing the proteins that change through the transition from primary to secondary ovarian follicle development. This transition is critical during the onset of puberty and for determining egg quality and embryonic development. Primary follicle development was marked by differential abundances of proteins in carbohydrate metabolism, protein turnover, and the complement pathway, suggesting elevated metabolism as the follicles develop through stages of oogenesis. The greatest proteomic shift occurred during the transition from primary to secondary follicle growth, with increased abundance of proteins underlying cortical alveoli formation, extracellular matrix reorganization, iron binding, and cell–cell signaling. This work provides a foundation for identifying biomarkers of salmon oocyte stage and quality.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The authors have nothing to report.
Supporting Information
Filename | Description |
---|---|
pmic13910-sup-0001-SuppMat.docx21.6 KB | Supporting Information |
pmic13910-sup-0002-figureS1.pdf289.9 KB | Figure S1. Total proteins identified at each ovarian follicle stage/time point and volcano plots of pairwise differentially abundant proteins for EPN vs. LPN, LPN vs. ECA, and ECA vs. LCA. |
pmic13910-sup-0003-figureS2.png91.1 KB | Figure S2. Nonmetric multidimensional scaling plot of all coho salmon analyzed, including the three fish that were smaller than their cohort and outliers in this plot for the LPN (August) group. Color intensity of the dots increases with the progression of time from April (EPN fish), to August (LPN), to December (ECA), and February (LCA). |
pmic13910-sup-0004-tableS1.csv1.4 KB | Table S1: Fish length, weight, and ovarian follicle stage for each ovarian tissue fragment analyzed with mass spectrometry proteomics. The .raw MS file name is provided with the fish ID, the month of sampling, and the described metrics. |
pmic13910-sup-0005-tableS2.csv16.4 KB | Table S2: Ovarian follicle volume and stage for fish from the same experiment sampled at the same time points as those analyzed with proteomics mass spectrometry. |
pmic13910-sup-0006-tableS3.txt822 B | Table S3: Additional sequences not in the published coho genome added to fasta. |
pmic13910-sup-0007-tableS4.txt1.8 MB | Table S4: For the 5,773 proteins identified in this dataset: protein accession, median normalized abundance for each mass spectrometry replicate, the annotation taken from the coho salmon genome fasta, the UniProt accession resulting from BLASTp against UniProt trembl, and the percent sequence coverage for each protein. |
pmic13910-sup-0008-tableS5.xlsx166.3 KB | Table S5: Each tab of the workbook contains a list of differentially abundant proteins for the pairwise comparisons of EPN vs. LPN, LPN vs. ECA, and ECA vs. LCA. The protein accession number is listed, along with the statistical output of Limma, the annotation pulled from the coho salmon fasta, and the BLASTp annotation against UniProt trembl. |
pmic13910-sup-0009-tableS6.xlsx28.6 KB | Table S6: GO enrichment results (from compGO) of the Limma differentially abundant proteins. Each workbook tab contains the GO enrichment output for GO biological process (BP), cellular component (CC), or molecular function (MF) for the three pairwise comparisons: EPN vs. LPN, LPN vs. ECA, and ECA vs. LCA. |
pmic13910-sup-0010-tableS7.csv87.3 KB | Table S7: Differentially abundant proteins for comparison of smaller and larger LPN fish. BLASTp annotations are provided. |
pmiic202400311-sup-0011-tableS8.csv108.2 KB | Table S8: WGCNA module membership for proteins in modules with significant correlations to variables. |
pmic13910-sup-0012-tableS9.xlsx73.9 KB | Table S9: GO enrichment (compGO) of WGCNA modules with significant correlations (blue, brown, green, magenta and turquoise). Enrichment results are presented for the GO categories of biological process (BP), cellular component (CC), and molecular function (MF). |
pmic13910-sup-0013-tableS10.csv50.4 MB | Table S10: For each protein inferred in this dataset, this file contains the following: all peptide sequence detected, percent sequence coverage, precursor charge, precursor m/z, sequence modifications, missed cleavages, and detection Q value score. This report was exported directly from the Skyline document, available on PanoramaWeb. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1S. Kornbluth and R. Fissore, “Vertebrate Reproduction,” Cold Spring Harbor Perspectives in Biology 7 (2015): a006064.
- 2S. W. Yoo, T. Bolbot, A. Koulova, et al., “Complement Factors Are Secreted in Human Follicular Fluid by Granulosa Cells and Are Possible Oocyte Maturation Factors,” Journal of Obstetrics and Gynaecology Research 39 (2013): 522–527.
- 3J. Q. Lin, J. Yu, H. Jiang, Y.i Zhang, Q. H. Wan, and S. G. Fang, “Multi-Omics Analysis Reveals That Natural Hibernation Is Crucial for Oocyte Maturation in the Female Chinese Alligator,” BMC Genomics [Electronic Resource] 21 (2020): 774.
- 4N. Garcia-Reyero, A. Tingaud-Sequeria, M. Cao, Z. Zhu, E. J. Perkins, and W. Hu, “Endocrinology: Advances Through Omics and Related Technologies,” General and Comparative Endocrinology 203 (2014): 262–273.
- 5B. Campbell, J. Dickey, B. Beckman, G. Young, A. Pierce, and P. Swanson, “Endocrine Changes Associated With the Growth of Pre-Vitellogenic Oocytes in Coho Salmon, Oncorhynchus kisutch,” Fish Physiology and Biochemistry 28 (2003): 287–289.
- 6E. Lubzens, J. Bobe, G. Young, and C. V. Sullivan, “Maternal Investment in Fish Oocytes and Eggs: The Molecular Cargo and Its Contributions to Fertility and Early Development,” Aquaculture 472 (2017): 107–143.
- 7R. A. Wallace and K. Selman, “Cellular and Dynamic Aspects of Oocyte Growth in Teleosts,” American Zoologist 21 (1981): 325–343.
10.1093/icb/21.2.325 Google Scholar
- 8B. Campbell, B. R. Beckman, W. T. Fairgrieve, J. T. Dickey, and P. Swanson, “Reproductive Investment and Growth History in Female Coho Salmon,” Transactions of the American Fisheries Society 135 (2011): 164–173.
10.1577/T05-115.1 Google Scholar
- 9B. Campbell, J. Dickey, B. Beckman, et al., “Previtellogenic Oocyte Growth in Salmon: Relationships Among Body Growth, Plasma Insulin-Like Growth Factor-1, Estradiol-17beta, Follicle-Stimulating Hormone and Expression of Ovarian Genes for Insulin-Like Growth Factors, Steroidogenic-Acute Regulatory Protein and Receptors for Gonadotropins,” Growth Hormone, and Somatolactin Biology of Reproduction 75 (2006): 34–44.
- 10L. Weitkamp, T. C. Wainwright, G. J. Bryant, D. J. Teel, and R. G. Kope, “ Review of the Status of Coho Salmon From Washington, Oregon, and California,” in Sustainable Fisheries Management, eds. E. E. Knudsen and D. McDonald (CRC Press, Boca Raton, Florida, USA 2000), 111–118.
- 11M. J. Bradford and J. R. Irvine, “Land Use, Fishing, Climate Change, and the Decline of Thompson River, British Columbia, Coho Salmon,” Canadian Journal of Fisheries and Aquatic Sciences 57 (2000): 13–16.
- 12L. G. Crozier, M. M. Mcclure, T. Beechie, et al., “Climate Vulnerability Assessment for Pacific Salmon and Steelhead in the California Current Large Marine Ecosystem,” PLOS ONE 14 (2019): e0217711.
- 13E. Lubzens, G. Young, J. Bobe, and J. Cerdà, “Oogenesis in Teleosts: How Fish Eggs Are Formed,” General and Comparative Endocrinology 165 (2010): 367–389.
- 14J. A. Luckenbach, D. B. Iliev, F. W. Goetz, and P. Swanson, “Identification of Differentially Expressed Ovarian Genes During Primary and Early Secondary Growth in Coho Salmon, Oncorhynchus kisutch,” Reproductive Biology and Endocrinology 6 (2008): 2.
- 15J. M. Guzmán, J. A. Luckenbach, Y. Yamamoto, and P. Swanson, “Expression Profiles of Fsh-Regulated Ovarian Genes During Oogenesis in Coho Salmon,” PLOS ONE 9 (2014): e114176.
- 16C. Monson, K. Forsgren, G. Goetz, L. Harding, P. Swanson, and G. Young, “A Teleost Androgen Promotes Development of Primary Ovarian Follicles in Coho Salmon and Rapidly Alters the Ovarian Transcriptome†,” Biology of Reproduction 97 (2017): 731–745.
- 17L. B. Harding, I. R. Schultz, G. W. Goetz, et al., “High-Throughput Sequencing and Pathway Analysis Reveal Alteration of the Pituitary Transcriptome by a 17a-Ethynylestradiol (EE2) in Female Coho Salmon, Oncorhynchus kisutch,” Aquatic Toxicology 142–143 (2013): 146–163.
- 18I. Nakamura, M. Kusakabe, and G. Young, “Differential Suppressive Effects of Low Physiological Doses of Estradiol-17β in Vivo on Levels of mRNAs Encoding Steroidogenic Acute Regulatory Protein and Three Steroidogenic Enzymes in Previtellogenic Ovarian Follicles of Rainbow Trout,” General and Comparative Endocrinology 163 (2009): 318–323.
- 19K. Gen, K. Okuzawa, N. Kumakura, S. Yamaguchi, and H. Kagawa, “Correlation Between Messenger RNA Expression of Cytochrome P450 Aromatase and Its Enzyme Activity During Oocyte Development in the Red Seabream (Pagrus major)1,” Biology of Reproduction 65 (2001): 1186–1194.
- 20T. Ziv, T. Gattegno, V. Chapovetsky, et al., “Comparative Proteomics of the Developing Fish (Zebrafish and Gilthead Seabream) Oocytes,” Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 3 (2008): 12–35.
- 21K. J. Groh, V. J. Nesatyy, H. Segner, R. I. L. Eggen, and M. J.-F. Suter, “Global Proteomics Analysis of Testis and Ovary in Adult Zebrafish (Danio rerio),” Fish Physiology and Biochemistry 37 (2011): 619–647.
- 22A. Beyer, J. Hollunder, H. P. Nasheuer, and T. Wilhelm, “Post-transcriptional Expression Regulation in the Yeast Saccharomyces Cerevisiae on a Genomic Scale,” Molecular & Cellular Proteomics 3 (2004): 1083–1092.
- 23M. Jovanovic, M. S. Rooney, P. Mertins, et al., “Dynamic Profiling of the Protein Life Cycle in Response to Pathogens,” Science 347 (2015): 6226.
10.1126/science.1259038 Google Scholar
- 24C. Monson, G. Goetz, K. Forsgren, P. Swanson, and G. Young, “In Vivo Treatment With a Non-Aromatizable Androgen Rapidly Alters the Ovarian Transcriptome of Previtellogenic Secondary Growth Coho Salmon (Onchorhynchus kisutch),” PLOS ONE 19 (2024): e0311628.
- 25K. L. Forsgren and G. Young, “Stage-Specific Effects of Androgens and Estradiol-17beta on the Development of Late Primary and Early Secondary Ovarian Follicles of Coho Salmon (Oncorhynchus kisutch) In Vitro,” Biology of Reproduction 87 (2012): 1–14.
- 26B. C. Searle, K. E. Swearingen, C. A. Barnes, et al., “Generating High Quality Libraries for DIA MS With Empirically Corrected Peptide Predictions,” Nature Communications 11 (2020): 1548.
- 27S. Gessulat, T. Schmidt, D. P. Zolg, et al., “Prosit: Proteome-Wide Prediction of Peptide Tandem Mass Spectra by Deep Learning,” Nature Methods 16 (2019): 509–518.
- 28B. C. Searle, L. K. Pino, J. D. Egertson, et al., “Chromatogram Libraries Improve Peptide Detection and Quantification by Data Independent Acquisition Mass Spectrometry,” Nature Communications 9 (2018): 5128.
- 29B. Maclean, D. M. Tomazela, N. Shulman, et al., “Skyline: An Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments,” Bioinformatics 26 (2010): 966–968.
- 30M. E. Ritchie, B. Phipson, D.i Wu, et al., “limma Powers Differential Expression Analyses for RNA-Sequencing and Microarray Studies,” Nucleic Acids Research 43 (2015): e47.
- 31P. Langfelder and S. Horvath, “WGCNA: An R Package for Weighted Correlation Network Analysis,” BMC Bioinformatics [Electronic Resource] 9 (2008): 559.
- 32N. R. Bromage and P. R. T. Cumaranatunga (1988) “ Egg Production in Rainbow Trout,” in Recent Advances in Aquaculture, eds. J. F. Muir and R. J. Roberts (Croom Helms, 1988), 65–138.
10.1007/978-94-011-9743-4_2 Google Scholar
- 33C. Fernández-Costa, S. Martínez-Bartolomé, D. B. Mcclatchy, A. J. Saviola, N. K. Yu, and J. R. Yates, “Impact of the Identification Strategy on the Reproducibility of the DDA and DIA Results,” Journal of Proteome Research 19 (2020): 3153–3161.
- 34M. C. Chambers, B. Maclean, R. Burke, et al., “A Cross-Platform Toolkit for Mass Spectrometry and Proteomics,” Nature Biotechnology 30 (2012): 918–920.
- 35L. R. Heil, W. E. Fondrie, C. D. Mcgann, et al., “Building Spectral Libraries From Narrow-Window Data-Independent Acquisition Mass Spectrometry Data,” Journal of Proteome Research 21 (2022): 1382–1391.
- 36V. Sharma, J. Eckels, G. K. Taylor, et al., “Panorama: A Targeted Proteomics Knowledge Base,” Journal of Proteome Research 13 (2014): 4205–4210.
- 37J. Oksanen, R. G. Blanchet, M. Friendly, et al., vegan: Community Ecology Package. R package version 2.6-4 (2020). Retrieved from, https://CRAN.R-project.org/package=vegan.
- 38R. Core Team, “ R: A Language and Environment for Statistical computing,” R Foundation for Statistical Computing (Vienna, Austria, 2023), https://www.R-project.org/.
- 39E. B. Timmins-Schiffman, G. A. Crandall, B. Vadopalas, M. E. Riffle, B. L. Nunn, and S. B. Roberts, “Integrating Discovery-Driven Proteomics and Selected Reaction Monitoring To Develop a Noninvasive Assay for Geoduck Reproductive Maturation,” Journal of Proteome Research 16 (2017): 3298–3309.
- 40H. Boulekbache, “Energy Metabolism in Fish Development,” American Zoologist 21 (1981): 377–389.
- 41P. Barciela, J. L. Soengas, P. Rey, M. Aldegunde, and G. Rozas, “Carbohydrate Metabolism in Several Tissues of Rainbow Trout, Oncorhynchus Mykiss, Is Modified During Ovarian Recrudescence,” Comparative Biochemistry and Physiology Part B: Comparative Biochemistry 106 (1993): 943–948.
10.1016/0305-0491(93)90055-A Google Scholar
- 42J. L. Soengas, P. Barciela, and M. Aldegunde, “Variations in Carbohydrate Metabolism During Gonad Maturation in Female Turbot (Scophthalmus maximus),” Marine Biology 123 (1995): 11–18.
- 43P. G. W. Gettins, “Serpin Structure, Mechanism, and Function,” Chemical Reviews 102 (2002): 4751–4804.
- 44G. Marteil, L. Richard-Parpaillon, and J. Z. Kubiak, “Role of Oocyte Quality in Meiotic Maturation and Embryonic Development,” Reproductive Biology 9 (2009): 203–224.
- 45K. Richani, E. Soto, R. Romero, et al., “Normal Pregnancy Is Characterized by Systemic Activation of the Complement System,” Journal of Maternal-Fetal & Neonatal Medicine 17 (2005): 239–245.
- 46D. J. Anderson, A. F. Abbott, and R. M. Jack, “The Role of Complement Component C3b and Its Receptors in Sperm-oocyte Interaction,” Proceedings National Academy of Science USA 90 (1993): 10051–10055.
- 47R. J. Llanos, C. M. Whitacre, and D. C. Miceli, “Potential Involvement of C3 Complement Factor in Amphibian Fertilization,” Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 127 (2000): 29–38.
- 48Y Yang, C. Zhao, B. Chen, et al., “Follicular Fluid C3a-Peptide Promotes Oocyte Maturation Through F-actin Aggregation,” BMC Biology 21 (2023): 285.
- 49A. S. Ginsburg, “The Block to Polyspermy in Sturgeon and Trout With Special Reference to the Role of Cortical Granules (Alveoli),” Development (Cambridge, England) 9 (1961): 173–190.
- 50H. Tateno, T. Ogawa, K. Muramoto, H. Kamiya, and M. Saneyoshi, “Rhamnose-binding Lectins From Steelhead Trout (Oncorhynchus mykiss) Eggs Recognize Bacterial Lipopolysaccharides and Lipoteichoic Acid,” Bioscience, Biotechnology, and Biochemistry 66 (2002): 604–612.
- 51C. R. Tyler and K. Lubberink, “Identification of Four Ovarian Receptor Proteins That Bind Vitellogenin but Not Other Homologous Plasma Lipoproteins in the Rainbow Trout, Oncorhynchus Mykiss,” Journal of Comparative Physiology B 166 (1996): 11–20.
- 52N. Hiramatsu, W. Luo, B. J. Reading, et al., “Multiple Ovarian Lipoprotein Receptors in Teleosts,” Fish Physiology and Biochemistry 39 (2012): 29–32.
- 53Y. Mushirobira, H. Mizuta, W. Luo, et al., “Molecular Cloning and Partial Characterization of a Low-Density Lipoprotein Receptor-related Protein 13 (Lrp13) Involved in Vitellogenin Uptake in the Cutthroat Trout (Oncorhynchus clarki),” Molecular Reproduction and Development 82 (2015): 986–1000.
- 54F. Prat, K. Coward, J. P. Sumpter, and C. R. Tyler, “Molecular Characterization and Expression of Two Ovarian Lipoprotein Receptors in the Rainbow Trout, Oncorhynchus Mykiss 1,” Biology of Reproduction 58 (1998): 1146–1153.
- 55T. M. Kortner, E. Rocha, P. Silva, L. F. C. Castro, and A. Arkuwe, “Genomic Approach in Evaluating the Role of Androgens on the Growth of Atlantic Cod (Gadus mohura) Previtellogenic Oocytes,” Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 3 (2008): 205–218.
- 56S. L. Divers, H. J. Mcquillan, H. Matsubara, T. Todo, and P. M. Lokman, “Effects of Reproductive Stage and 11-Ketotestosterone on LPL mRNA Levels in the Ovary of the Shortfinned Eel,” Journal of Lipid Research 51 (2010): 3250–3258.
- 57B. J. Reading, V. N. Williams, R. W. Chapman, T. I. Williams, and C. V. Sullivan, “Dynamics of the Striped Bass (Morone saxatilis) Ovary Proteome Reveal a Complex Network of the Translasome,” Journal of Proteome Research 12 (2013): 1691–1699.
- 58L. K. Pino, B. C. Searle, H.-Y. Yang, A. N. Hoofnagle, W. S. Noble, and M. J. MacCoss, "Matrix–Matched Calibration Curves for Assessming Analytical Figures of Merit in Quantitative Proteomics," Journal of Proteome Research 19 (2020): 1147–1153.
- 59L. K. Pino, S. C. Just, M. J. MacCoss, B. C. Searle, "Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries," Molecular and Cellular Proteomics 19 (2020): 1088–1103.