Compartment proteomics analysis of white perch (Morone americana) ovary using support vector machines

Journal of Proteome Research

Volumn 13, Issue 3, 2014, Pages 1515-1526

  Schilling, Justin ^a   Nepomuceno, Angelito ^a   Schaff, Jennifer E ^a   Muddiman, David C ^a   Daniels, Harry V ^a   Reading, Benjamin J ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

alternatively spliced variants; compartment proteomics; mitochondria; modulated modularity clustering; oocytes; ovary; support vector machines; transcriptome; vitellogenin

Indexed keywords

MEMBRANE PROTEIN; MITOCHONDRIAL PROTEIN; PROTEOME; TRANSCRIPTOME;

ANIMAL TISSUE; ARTICLE; CELL ORGANELLE; CYTOSOLIC FRACTION; FEMALE; FRACTIONATION; MITOCHONDRION; NONHUMAN; OVARY; PERCH; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEOMICS; QUANTITATIVE ANALYSIS; SUPPORT VECTOR MACHINE; TANDEM MASS SPECTROMETRY;

ANIMALS; BASS; CHEMICAL FRACTIONATION; FEMALE; FISH PROTEINS; MEMBRANE PROTEINS; MITOCHONDRIAL PROTEINS; MOLECULAR SEQUENCE ANNOTATION; OVARY; PROTEOMICS; SUPPORT VECTOR MACHINES; TANDEM MASS SPECTROMETRY;

EID: 84896752149     PISSN: 15353893     EISSN: 15353907     Source Type: Journal    
DOI: 10.1021/pr401067g     Document Type: Article

References (76)

1. Barnthouse, L. W.; Glaser, D.; DeSantis, L. Polychlorinated biphenyls and Hudson River white perch: Implications for population-level ecological risk assessment and risk management Integr. Environ. Assess. Manag. 2009, 5, 435
2. King, R. S.; Beaman, J. R.; Whigham, D. F.; Hines, A. H.; Baker, M. E.; Weller, D. E. Watershed land use is strongly linked to PCBs in white perch in Chesapeake Bay subestuaries Environ. Sci. Technol. 2013, 38, 6546-52
3. Hiramatsu, N.; Matsubara, T.; Fujita, T.; Sullivan, C. V.; Hara, A. Multiple piscine vitellogenins: biomarkers of fish exposure to estrogenic endocrine disruptors in aquatic environments Marine Biol. 2006, 149, 35-47
4. Reading, B. J.; Chapman, R. W.; Schaff, J. E.; Scholl, E. H.; Opperman, C. H.; Sullivan, C. V. An ovary transcriptome for all maturational stages of the striped bass (Morone saxatilis), a highly advanced perciform fish BMC Res. Notes 2012, 5 (111) 1-12
5. Reading, B. J.; Williams, V. N.; Chapman, R. W.; Williams, T. I.; Sullivan, C. V. Dynamics of the striped bass (Morone saxatilis) ovary proteome reveal a complex network of the translasome J. Proteome Res. 2013, 12, 1691-99
6. Tao, Y.; Berlinsky, D. L.; Sullivan, C. V. Characterization of a vitellogenin receptor in white perch (Morone americana) Biol. Reprod. 1996, 55, 646-56
7. Hiramatsu, N.; Luo, W.; Reading, B. J.; Sullivan, C. V. Multiple ovarian lipoprotein receptors in teleosts Fish Physiol. Biochem. 2013, 39, 29-32
8. Reading, B. J.; Hiramatsu, N.; Sawaguchi, S.; Matsubara, T.; Hara, A.; Lively, M. O.; Sullivan, C. V. Conserved and variant molecular and functional features of multiple egg yolk precursor proteins (vitellogenins) in white perch (Morone americana) and other teleosts Mar. Biotechnol. 2009, 11, 169-87
9. Reading, B. J.; Hiramatsu, N.; Sullivan, C. V. Disparate binding of three types of vitellogenin to multiple forms of vitellogenin receptor in white perch Biol. Reprod. 2011, 84, 392-99
10. Hiramatsu, N.; Matsubara, T.; Hara, A.; Donato, D. M.; Hiramatsu, K.; Denslow, N. D.; Sullivan, C. V. Identification, purification and classification of multiple forms of vitellogenin from white perch (Morone americana) Fish Physiol. Biochem. 2002, 26, 355-70
11. Hiramatsu, N.; Chapman, R. W.; Lindzey, J. K.; Haynes, M. R.; Sullivan, C. V. Molecular characterization and expression of vitellogenin receptor from white perch (Morone americana) Biol. Reprod. 2004, 70, 1720-30
12. Hiramatsu, N.; Luo, W.; Reading, B. J.; Sullivan, C. V.; Mizuta, H.; Ryu, Y. W.; Nishimiya, O.; Todo, T.; Hara, A. Multiple ovarian lipoprotein receptors in teleosts Fish Physiol. Biochem. 2012, 39, 29-32
13. Nilsson, T.; Mann, M.; Aebersold, R.; Yates, J. R. Mass spectrometry in high-throughput proteomics: ready for the big time Nature 2010, 7, 681-85
14. Rockstroh, M.; Müller, S.; Jende, C.; Kerzhner, A.; Bergen; Von, M.; Tomm, J. M. Cell fractionation-an important tool for compartment proteomics JIOMICS 2011, 1, 135-43
15. Witten, I. H.; Frank, E.; Hall, M. A. Data Mining: Practical Machine Learning Tools and Techniques, 3 rd ed.; Elsevier: Burlington, 2011.
16. Chapman, R. W.; Mancia, A.; Beal, M.; Veloso, A.; Rathburn, C.; Blair, A.; Sanger, D.; Holland, A. F.; Warr, G. W.; Didonato, G. A transcriptomic analysis of land-use impacts on the oyster, Crassostrea virginica, in the South Atlantic bight Mol. Ecol. 2009, 18, 2415-25
17. Johansson, P.; Ringnér, M. Classification of Genomic and Proteomic Data Using Support Vector Machines. Fundamentals of Data Mining in Genomics and Proteomics; Springer: Boston, 2007; pp 187-202.
18. King, W. V.; Berlinsky, D. L.; Sullivan, C. V. Involvement of gonadal steroids in final oocyte maturation of white perch (Morone americana) and white bass (M. chrysops): in vivo and in vitro studies Fish Physiol. Biochem. 1995, 14, 489-500
19. Jackson, L. F.; Sullivan, C. V. Reproduction of white perch: The annual gametogenic cycle Trans. Am. Fish. Soc. 2005, 124, 563-77
20. Huang, X.; Madan, A. CAP3: A DNA sequence assembly program Genome Res. 1999, 9, 868-77
21. Altschul, S. F.; Gish, W.; Miller, W.; Myers, E. W.; Lipman, D. J. Basic local alignment search tool J. Mol. Biol. 1990, 215, 403-10
22. Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H.; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T.; Harris, M. A.; Hill, D. P.; Issel-Tarver, L.; Kasarskis, A.; Lewis, S.; Matese, J. C.; Richardson, J. E.; Ringwald, M.; Rubin, G. M.; Sherlock, G. Gene ontology: tool for the unification of biology Nat. Genet. 2000, 25, 25-29
23. Götz, S.; García-Gómez, J. M.; Terol, J.; Williams, T. D.; Nagaraj, S. H.; Nueda, M. J.; Robles, M.; Talón, M.; Dopazo, J.; Conesa, A. High-throughput functional annotation and data mining with the Blast2GO suite Nucleic Acids Res. 2008, 36, 3420-35
24. Conesa, A.; Götz, S. Blast2GO: A Comprehensive suite for functional analysis in plant genomics Int. J. Plant Genomics 2008, 1-12
25. Conesa, A.; Götz, S.; García-Gómez, J. M.; Terol, J.; Talón, M.; Robles, M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research Bioinformatics 2005, 21, 3674-6
26. Wiśniewski, J. R.; Zougman, A.; Nagaraj, N.; Mann, M. Universal sample preparation method for proteome analysis Nat. Methods 2009, 6, 359-62
27. Andrews, G. L.; Shuford, C. M.; Burnett, J. C.; Hawkridge, A. M.; Muddiman, D. C. Coupling of a vented column with splitless nanoRPLC-ESI-MS for the improved separation and detection of brain natriuretic peptide-32 and its proteolytic peptides J. Chromatogr. B 2009, 877, 948-54
28. Michalski, A.; Damoc, E.; Hauschild, J. P.; Lange, O.; Wieghaus, A.; Makarov, A.; Nagaraj, N.; Cox, J.; Mann, M.; Horning, S. Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer Mol. Cell Proteomics 2011, 10, 1-11
29. Randall, S. M.; Cardasis, H. L.; Muddiman, D. C. Factorial experimental designs elucidate significant variables affecting data acquisition on a quadrupole orbitrap mass spectrometer J. Am. Soc. Mass Spectrom. 2013, 24, 1501-12
30. Perkins, D. N.; Pappin, D. J.; Creasy, D. M.; Cottrell, J. S. Probability-based protein identification by searching sequence databases using mass spectrometry data Electrophoresis 1999, 20, 3551-67
31. Min, X. J.; Butler, G.; Storms, R.; Tsang, A. OrfPredictor: predicting protein-coding regions in EST-derived sequences Nucleic Acids Res. 2005, 33, W677-80
32. Keller, A.; Nesvizhskii, A. I.; Kolker, E.; Aebersold, R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search Anal. Chem. 2002, 74, 5383-92
33. Nesvizhskii, A. I.; Keller, A.; Kolker, E.; Aebersold, R. A statistical model for identifying proteins by tandem mass spectrometry Anal. Chem. 2003, 75, 4646-58
34. Weatherly, D. B.; Atwood, J. A.; Minning, T. A.; Cavola, C.; Tarleton, R. L.; Orlando, R. A heuristic method for assigning a false-discovery rate for protein identifications from mascot database search results Mol. Cell. Proteomics 2005, 4, 762-72
35. Wu, X.; Chau-Wen, T.; Edwards, N. HMMatch: Peptide identification by spectral matching of tandem mass spectra using hidden Markov models J. Comput. Biol. 2007, 14 (8) 1025-43
36. Gocke, E.; Shuford, C. M.; Franck, W. L.; Dean, R. A.; Muddiman, D. C. Evaluation of normalization methods on GeLC-MS/MS label-free spectral counting data to correct for variation during proteomic workflows J. Am. Soc. Mass Spectrom. 2011, 22, 2199-208
37. Stone, E. A.; Ayroles, J. F. Modulated modularity clustering as an exploratory tool for functional genomic inference PLoS Genet. 2009, 5, e1000479
38. Chan, Y. C.; Raengpradub, S.; Boor, K. J.; Wiedmann, M. Microarray-based characterization of the Listeria monocytogenes cold regulon in log- and stationary-phase cells Appl. Environ. Microbiol. 2007, 73 (20) 6484
39. Dennis, G., Jr; Sherman, B. T.; Hosack, D. A.; Yang, J. DAVID: database for annotation, visualization, and integrated discovery Genome Biol. 2003, 4 (9) R60.1-11
40. Rebhan, M.; Chalifa-Caspi, V.; Prilusky, J.; Lancet, D. GeneCards: a novel functional genomics compendium with automated data mining and query reformulation support Bioinformatics 1998, 14, 656-64
41. Booth, N. J.; Bilodeau-Bourgeois, A. L. Proteomic analysis of head kidney tissue from high and low susceptibility families of channel catfish following challenge with Edwardsiella ictaluri Fish Shellfish Immun. 2009, 26, 193-6
42. Provan, F.; Bjørnstad, A.; Pampanin, D. M.; Lyng, E.; Fontanillas, R.; Andersen, O. K.; Koppe, W.; Bamber, S. Mass spectrometric profiling-a diagnostic tool in fish? Mar. Environ. Res. 2006, 62 (Suppl) S105-8
43. Liu, X.; Afonso, L.; Altman, E.; Johnson, S.; Brown, L.; Li, J. O-acetylation of sialic acids in N-glycans of Atlantic salmon (Salmo salar) serum is altered by handling stress Proteomics 2008, 8, 2849-57
44. Martin, S. A. M.; Vilhelmsson, O.; Médale, F.; Watt, P.; Kaushik, S.; Houlihan, D. F. Proteomic sensitivity to dietary manipulations in rainbow trout Biochim. Biophys. Acta, Proteins Proteomics 2003, 1651, 17-29
45. Rime, H.; Guitton, N.; Pineau, C.; Bonnet, E.; Bobe, J.; Jalabert, B. Post-ovulatory ageing and egg quality: a proteomic analysis of rainbow trout coelomic fluid Reprod. Biol. Endocrinol. 2004, 2, 26
46. Wulff, T.; Hoffmann, E. K.; Roepstorff, P.; Jessen, F. Comparison of two anoxia models in rainbow trout cells by a 2-DE and MS/MS-based proteome approach Proteomics 2008, 8, 2035-44
47. Forné, I.; Agulleiro, M. J.; Asensio, E.; Abián, J.; Cerdà, J. 2-D DIGE analysis of Senegalese sole (Solea senegalensis) testis proteome in wild-caught and hormone-treated F1 fish Proteomics 2009, 9, 2171-81
48. Reddish, J. M.; St-Pierre, N.; Nichols, A.; Green-Church, K.; Wick, M. Proteomic analysis of proteins associated with body mass and length in yellow perch, Perca flavescens Proteomics 2008, 8, 2333-43
49. Zilli, L.; Schiavone, R.; Storelli, C.; Vilella, S. Molecular mechanisms determining sperm motility initiation in two sparids (Sparus aurata and Lithognathus mormyrus) Biol. Reprod. 2008, 79, 356-66
50. Ziv, T.; Gattegno, T.; Chapovetsky, V.; Wolf, H.; Barnea, E.; Lubzens, E.; Admon, A. Comparative proteomics of the developing fish (zebrafish and gilthead seabream) oocytes Comp. Biochem. Physiol., Part D 2008, 3, 12-35
51. Zilli, L.; Schiavone, R.; Zonno, V.; Rossano, R.; Storelli, C.; Vilella, S. Effect of cryopreservation on sea bass sperm proteins Biol. Reprod. 2005, 72, 1262-67
52. Knoll-Gellida, A.; André, M.; Gattegno, T.; Forgue, J.; Admon, A.; Babin, P. J. Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals BMC Genomics 2006, 7, 46
53. Groh, K. J.; Nesatyy, V. J.; Segner, H.; Eggen, R. I. L.; Suter, M. J.-F. Global proteomics analysis of testis and ovary in adult zebrafish (Danio rerio) Fish Physiol. Biochem. 2011, 37, 619-47
54. Groh, K. J.; Schönenberger, R.; Eggen, R. I. L.; Segner, H.; Suter, M. J.-F. Analysis of protein expression in zebrafish during gonad differentiation by targeted proteomics Gen. Comp. Endocr. 2013, 193, 210-20
55. Martyniuk, C. J.; Alvarez, S. Proteome analysis of the fathead minnow (Pimephales promelas) reproductive testes J. Proteomics 2013, 79, 28-42
56. Elmore, S. Apoptosis: A review of programmed cell death Toxicol. Pathol. 2007, 35, 495-516
57. Dumollard, R.; Duchen, M.; Carroll, J. The role of mitochondrial function in the oocyte and embryo Curr. Top. Dev. Biol. 2007, 77, 21-49
58. Wang, G.; Yan, S. Mitochondrial DNA content and mitochondrial gene transcriptional activities in the early development of loach and goldfish Int. J. Dev. Biol. 1992, 36, 477-82
59. Marinos, E.; Billett, F. S. Mitochondrial number, cytochrome oxidase and succinic dehydrogenase activity in Xenopus laevis oocytes J. Embryol. Exp. Morph. 1981, 62, 395-409
60. Marinos, E. The number of mitochondria in Xenopus laevis ovulated oocytes Cell Differ. 1985, 16, 139-43
61. Billett, F. S.; Adam, E. The structure of the mitochondrial cloud of Xenopus laevis oocytes J. Embryol. Exp. Morph. 1976, 33, 697-710
62. Greenwood, J.; Gautier, J. From oogenesis through gastrulation: developmental regulation of apoptosis Semin. Cell Dev. Biol. 2005, 16, 215-24
63. Kerby, J. H. Striped bass and striped bass hybrids. In Culture of Nonsalmonid Freshwater Fishes; Stickney, R. R., Ed; CRC Press: Boca Raton, 1986; pp 127-47.
64. Barbosa-Morais, N. L.; Irimia, M.; Pan, Q.; Xiong, H. Y.; Gueroussov, S.; Lee, L. J.; Slobodeniuc, V.; Kutter, C.; Watt, S.; Colak, R.; Kim, T.; Misquitta-Ali, C. M.; Wilson, M. D.; Kim, P. M.; Odom, D. T.; Frey, B. J.; Blencowe, B. J. The evolutionary landscape of alternative splicing in vertebrate species Science 2012, 338, 1587-93
65. Buljan, M.; Chalancon, G.; Eustermann, S.; Wagner, G. P.; Fuxreiter, M.; Bateman, A.; Madan Babu, M. Tissue-specific splicing of disordered segments that embed binding motifs rewires protein interaction networks Mol. Cell 2012, 46, 871-83
66. Wang, R. L.; Bencic, D.; Biales, A.; Lattier, D.; Kostich, M.; Villenueve, D.; Ankley, G. T.; Lazorchak, J.; Toth, G. DNA Microarray-based ecotoxological biomarker discovery in a small fish model species Environ. Toxicol. Chem. 2008, 27 (3) 664-75
67. Wang, R. L.; Bencic, D.; Biales, A.; Flick, R.; Laz orchak, J.; Villeneuve, D.; Ankley, G. T. Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio) BMC Genomics 2012, 13, 358
68. Ornostay, A.; Cowie, A M.; Hindle, M.; Baker, C. J. O.; Martyniuk, C. J. Classifying chemical mode of action using gene networks and machine learning: A case study with the herbicide linuron Comp. Biochem. Physiol., Part D 2013, 8 (4) 263-74
69. Sawaguchi, S.; Ohkubo, N.; Amano, H.; Hiramatsu, N.; Hara, A.; Sullivan, C. V.; Matsubara, T. Controlled accumulation of multiple vitellogenins into oocytes during vitellogenesis in the barfin flounder Verasper moseri Cybium, Int. J. Ichthyol. 2008, 32 (2) 262
70. Williams, V. N.; Reading, B. J.; Amano, H.; Hiramatsu, N.; Schilling, J.; Salger, S. A.; Islam Williams, T.; Gross, K.; Sullivan, C. V. Proportional accumulation of yolk proteins derived from multiple vitellogenins is precisely regulated during vitellogenesis in striped bass (Morone saxatilis). J. Exp. Zool. Part A 2013, submitted for publication
71. Williams, V. N.; Reading, B. J.; Hiramatsu, N.; Amano, H.; Glassbrook, N.; Hara, A.; Sullivan, C. V. Multiple vitellogenins and product yolk proteins in striped bass, Morone saxatilis: molecular characterization and processing during oocyte growth and maturation Fish Physiol. Biochem. 2013, 10.1007/s10695-013-9852-0
72. Hassler, T. J. Species profiles: Life histories and environmental requirements of coastal fishes and invertebrates (Pacific Southwest)-striped bass. In U.S. Fish and Wildlife Service Biological Report. 82 (11.82). U.S. Army Corps of Engineers, TR EL-82-4, 1988; pp 1-29.
73. Amano, H.; Fujita, T.; Hiramatsu, N.; Kagawa, H.; Matsubara, T.; Sullivan, C. V.; Hara, A. Multiple vitellogenin-derived yolk proteins in gray mullet (Mugil cephalus): disparate proteolytic patterns associated with ovarian follicle maturation Mol. Reprod. Dev. 2008, 75, 1307-17
74. Sawaguchi, S.; Ohkubo, N.; Koya, Y.; Matsubara, T. Incorporation and utilization of multiple forms of vitellogenin and their derivative yolk proteins during vitellogenesis and embryonic development in the mosquitofish Gambusia affinis Zool. Sci. 2005, 22, 701-10
75. Kolarevic, J.; Nerland, A.; Nilsen, F.; Finn, R. N. Goldsinny wrasse (Ctenolabrus rupestris) is an extreme vtgAa -type pelagophil teleost Mol. Reprod. Dev. 2008, 75, 1011-20
76. Wu, C. C.; Yates, J. R. The application of mass spectrometry to membrane proteomics Nat. Biotechnol. 2003, 21, 262-67