Spotlite: Web application and augmented algorithms for predicting co-complexed proteins from affinity purification - Mass spectrometry data

Journal of Proteome Research

Volumn 13, Issue 12, 2014, Pages 5944-5955

  Goldfarb, Dennis ^a,b   Hast, Bridgid E ^b,d   Wang, Wei ^a,c   Major, Michael B ^a,b  

^a Brooks Computer Science Building   (United States)

^b UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^c University of California   (United States)

^d EAST CAROLINA UNIVERSITY   (United States)

Author keywords

affinity purification mass spectrometry; bioinformatics; KEAP1; machine learning; protein protein interactions

Indexed keywords

KELCH LIKE ECH ASSOCIATED PROTEIN 1; MESSENGER RNA; PROTEIN BINDING; PROTEOME;

ACCURACY; AFFINITY PURIFICATION MASS SPECTROMETRY; ALGORITHM; ARTICLE; BINDING AFFINITY; COMPLEX FORMATION; CONTROLLED STUDY; GENE ONTOLOGY; HUMAN; MASS SPECTROMETRY; PROTEIN DOMAIN; PROTEIN EXPRESSION; PROTEIN PROTEIN INTERACTION; RECEIVER OPERATING CHARACTERISTIC; AFFINITY CHROMATOGRAPHY; ANIMAL; COMPUTER PROGRAM; INTERNET; ISOLATION AND PURIFICATION; MOLECULAR GENETICS; MOUSE; PHENOTYPE; PHYSIOLOGY; PROTEIN ANALYSIS; SUPPORT VECTOR MACHINE;

ANIMALS; CHROMATOGRAPHY, AFFINITY; HUMANS; INTERNET; MASS SPECTROMETRY; MICE; MOLECULAR SEQUENCE ANNOTATION; PHENOTYPE; PROTEIN BINDING; PROTEIN INTERACTION MAPPING; PROTEIN INTERACTION MAPS; PROTEOME; ROC CURVE; SOFTWARE; SUPPORT VECTOR MACHINE;

EID: 84915798945     PISSN: 15353893     EISSN: 15353907     Source Type: Journal    
DOI: 10.1021/pr5008416     Document Type: Article

References (72)

1. Stark, C.; Breitkreutz, B.-J.; Chatr-Aryamontri, A.; Boucher, L.; Oughtred, R.; Livstone, M. S.; Nixon, J.; Van Auken, K.; Wang, X.; Shi, X. The BioGRID interaction database: 2011 update Nucleic Acids Res. 2011, 39, D698-D704
2. Human Interactome Project. CCSB Interactome Database; Center for Cancer Systems Biology: Boston, MA, 2013. http://interactome.dfci.harvard.edu/H-sapiens/index.php (accessed October 5, 2013).
3. Gavin, A.-C.; Aloy, P.; Grandi, P.; Krause, R.; Boesche, M.; Marzioch, M.; Rau, C.; Jensen, L. J.; Bastuck, S.; Dümpelfeld, B. Proteome survey reveals modularity of the yeast cell machinery Nature 2006, 440, 631-636
4. Collins, S. R.; Kemmeren, P.; Zhao, X.-C.; Greenblatt, J. F.; Spencer, F.; Holstege, F. C. P.; Weissman, J. S.; Krogan, N. J. Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae Mol. Cell. Proteomics 2007, 6, 439-450
5. Bader, G. D.; Hogue, C. W. V. Analyzing yeast protein-protein interaction data obtained from different sources Nat. Biotechnol. 2002, 20, 991-997
6. Bader, G. D.; Hogue, C. W. V. An automated method for finding molecular complexes in large protein interaction networks BMC Bioinf. 2003, 4, 2
7. Gilchrist, M. A.; Salter, L. A.; Wagner, A. A statistical framework for combining and interpreting proteomic datasets Bioinformatics 2004, 20, 689-700
8. Hart, G. T.; Lee, I.; Marcotte, E. R. A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality BMC Bioinf. 2007, 8, 236
9. Zhang, B.; Park, B.-H.; Karpinets, T.; Samatova, N. F. From pull-down data to protein interaction networks and complexes with biological relevance Bioinformatics 2008, 24, 979-986
10. Choi, H.; Larsen, B.; Lin, Z.-Y.; Breitkreutz, A.; Mellacheruvu, D.; Fermin, D.; Qin, Z. S.; Tyers, M.; Gingras, A.-C.; Nesvizhskii, A. I. SAINT: Probabilistic scoring of affinity purification-mass spectrometry data Nat. Methods 2011, 8, 70-73
11. Teo, G.; Liu, G.; Zhang, J.; Nesvizhskii, A. I.; Gingras, A.-C.; Choi, H. SAINTexpress: Improvements and additional features in significance analysis of INTeractome software J. Proteomics 2014, 100, 37-43
12. Jäger, S.; Cimermancic, P.; Gulbahce, N.; Johnson, J. R.; McGovern, K. E.; Clarke, S. C.; Shales, M.; Mercenne, G.; Pache, L.; Li, K. Global landscape of HIV-human protein complexes Nature 2012, 481, 365-370
13. Sowa, M. E.; Bennett, E. J.; Gygi, S. P.; Harper, J. W. Defining the human deubiquitinating enzyme interaction landscape Cell 2009, 138, 389-403
14. Guruharsha, K. G.; Rual, J.-F.; Zhai, B.; Mintseris, J.; Vaidya, P.; Vaidya, N.; Beekman, C.; Wong, C.; Rhee, D. Y.; Cenaj, O. A protein complex network of Drosophila melanogaster Cell 2011, 147, 690-703
15. Choi, H.; Glatter, T.; Gstaiger, M.; Nesvizhskii, A. I. SAINT-MS1: Protein-protein interaction scoring using label-free intensity data in affinity purification-mass spectrometry experiments J. Proteome Res. 2012, 11, 2619-2624
16. Beyer, A.; Bandyopadhyay, S.; Ideker, T. Integrating physical and genetic maps: From genomes to interaction networks Nat. Rev. Genet. 2007, 8, 699-710
17. Myers, C. L.; Troyanskaya, O. G. Context-sensitive data integration and prediction of biological networks Bioinformatics 2007, 23, 2322-2330
18. Qiu, J.; Noble, W. S. Predicting co-complexed protein pairs from heterogeneous data PLoS Comput. Biol. 2008, 4, e1000054
19. Qi, Y.; Bar-Joseph, Z.; Klein-Seetharaman, J. Evaluation of different biological data and computational classification methods for use in protein interaction prediction Proteins 2006, 63, 490-500
20. Resnik, P. Using information content to evaluate semantic similarity in a taxonomy; International Joint Conference for Artificial Intelligence: Quebec, Canada, 1995.
21. Jain, S.; Bader, G. D. An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology BMC Bioinf. 2010, 11, 562
22. Yang, H.; Nepusz, T.; Paccanaro, A. Improving GO semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty Bioinformatics 2012, 28, 1383-1389
23. Deng, M.; Mehta, S.; Sun, F.; Chen, T. Inferring domain-domain interactions from protein-protein interactions Genome Res. 2002, 12, 1540-1548
24. Ben-Hur, A.; Noble, W. S. Kernel methods for predicting protein-protein interactions Bioinformatics 2005, 21 (Suppl. 1) i38-i46
25. Koike, A.; Takagi, T. Prediction of protein-protein interaction sites using support vector machines Protein Eng., Des. Sel. 2004, 17, 165-173
26. Lin, N.; Wu, B.; Jansen, R.; Gerstein, M.; Zhao, H. Information assessment on predicting protein-protein interactions BMC Bioinf. 2004, 5, 154
27. Jansen, R.; Yu, H.; Greenbaum, D.; Kluger, Y.; Krogan, N. J.; Chung, S.; Emili, A.; Snyder, M.; Greenblatt, J. F.; Gerstein, M. A Bayesian networks approach for predicting protein-protein interactions from genomic data Science 2003, 302, 449-453
28. Bader, J. S.; Chaudhuri, A.; Rothberg, J. M.; Chant, J. Gaining confidence in high-throughput protein interaction networks Nat. Biotechnol. 2004, 22, 78-85
29. Havugimana, P. C.; Hart, G. T.; Nepusz, T.; Yang, H.; Turinsky, A. L.; Li, Z.; Wang, P. I.; Boutz, D. R.; Fong, V.; Phanse, S. A census of human soluble protein complexes Cell 2012, 150, 1068-1081
30. Liu, G.; Zhang, J.; Larsen, B.; Stark, C.; Breitkreutz, A.; Lin, Z.-Y.; Breitkreutz, B.-J.; Ding, Y.; Colwill, K.; Pasculescu, A. ProHits: Integrated software for mass spectrometry-based interaction proteomics Nat. Biotechnol. 2010, 28, 1015-1017
31. Mellacheruvu, D.; Wright, Z.; Couzens, A. L.; Lambert, J.-P.; St-Denis, N. A.; Li, T.; Miteva, Y. V.; Hauri, S.; Sardiu, M. E.; Low, T. Y. The CRAPome: A contaminant repository for affinity purification-mass spectrometry data Nat. Methods 2013, 10, 730-736
32. Franceschini, A.; Szklarczyk, D.; Frankild, S.; Kuhn, M.; Simonovic, M.; Roth, A.; Lin, J.; Minguez, P.; Bork, P.; von Mering, C. STRING v9.1: Protein-protein interaction networks, with increased coverage and integration Nucleic Acids Res. 2013, 41, D808-D815
33. McDowall, M. D.; Scott, M. S.; Barton, G. J. PIPs: Human protein-protein interaction prediction database Nucleic Acids Res. 2009, 37, D651-D656
34. Turner, B.; Razick, S.; Turinsky, A. L.; Vlasblom, J.; Crowdy, E. K.; Cho, E.; Morrison, K.; Donaldson, I. M.; Wodak, S. J. iRefWeb: Interactive analysis of consolidated protein interaction data and their supporting evidence Database (Oxford) 2010, 2010, baq023
35. Kersey, P. J.; Duarte, J.; Williams, A.; Karavidopoulou, Y.; Birney, E.; Apweiler, R. The International Protein Index: An integrated database for proteomics experiments Proteomics 2004, 4, 1985-1988
36. UniProt Consortium. Reorganizing the protein space at the Universal Protein Resource (UniProt) Nucleic Acids Res. 2012, 40, D71-D75
37. Punta, M.; Coggill, P. C.; Eberhardt, R. Y.; Mistry, J.; Tate, J.; Boursnell, C.; Pang, N.; Forslund, K.; Ceric, G.; Clements, J. The Pfam protein families database Nucleic Acids Res. 2012, 40, D290-D301
38. Obayashi, T.; Kinoshita, K. COXPRESdb: A database to compare gene coexpression in seven model animals Nucleic Acids Res. 2011, 39, D1016-D1022
39. 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. Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium Nat. Genet. 2000, 25, 25-29
40. Smith, C. L.; Eppig, J. T. The mammalian phenotype ontology: Enabling robust annotation and comparative analysis Wiley Interdiscip Rev.: Syst. Biol. Med. 2009, 1, 390-399
41. Robinson, P. N.; Köhler, S.; Bauer, S.; Seelow, D.; Horn, D.; Mundlos, S. The human phenotype ontology: A tool for annotating and analyzing human hereditary disease Am. J. Hum. Genet. 2008, 83, 610-615
42. Osborne, J. D.; Flatow, J.; Holko, M.; Lin, S. M.; Kibbe, W. A.; Zhu, L. J.; Danila, M. I.; Feng, G.; Chisholm, R. L. Annotating the human genome with disease ontology BMC Genomics 2009, 10 (Suppl. 1) S6
43. Pesquita, C.; Faria, D.; Bastos, H.; Ferreira, A. E. N.; Falcão, A. O.; Couto, F. M. Metrics for GO-based protein semantic similarity: A systematic evaluation BMC Bioinf. 2008, 9 (Suppl. 5) S4
44. Venkatesan, K.; Rual, J.-F.; Vazquez, A.; Stelzl, U.; Lemmens, I.; Hirozane-Kishikawa, T.; Hao, T.; Zenkner, M.; Xin, X.; Goh, K.-I. An empirical framework for binary interactome mapping Nat. Methods 2009, 6, 83-90
45. Phipson, B.; Smyth, G. K. Permutation P -values should never be zero: Calculating exact P -values when permutations are randomly drawn Stat. Appl. Genet. Mol. Biol. 2010, 9, 39
46. Benjamini, Y.; Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing J. R. Stat. Soc. 1995, 57 (1) 289-300
47. Behrends, C.; Sowa, M. E.; Gygi, S. P.; Harper, J. W. Network organization of the human autophagy system Nature 2010, 466, 68-76
48. Sardiu, M. E.; Cai, Y.; Jin, J.; Swanson, S. K.; Conaway, R. C.; Conaway, J. W.; Florens, L.; Washburn, M. P. Probabilistic assembly of human protein interaction networks from label-free quantitative proteomics Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 1454-1459
49. Joshi, P.; Greco, T. M.; Guise, A. J.; Luo, Y.; Yu, F.; Nesvizhskii, A. I.; Cristea, I. M. The functional interactome landscape of the human histone deacetylase family Mol. Syst. Biol. 2013, 9, 672
50. Malovannaya, A.; Lanz, R. B.; Jung, S. Y.; Bulynko, Y.; Le, N. T.; Chan, D. W.; Ding, C.; Shi, Y.; Yucer, N.; Krenciute, G. Analysis of the human endogenous coregulator complexome Cell 2011, 145, 787-799
51. Hast, B. E.; Goldfarb, D.; Mulvaney, K. M.; Hast, M. A.; Siesser, P. F.; Yan, F.; Hayes, D. N.; Major, M. B. Proteomic analysis of ubiquitin ligase KEAP1 reveals associated proteins that inhibit NRF2 ubiquitination Cancer Res. 2013, 73 (7) 2199-2210
52. Smialowski, P.; Pagel, P.; Wong, P.; Brauner, B.; Dunger, I.; Fobo, G.; Frishman, G.; Montrone, C.; Rattei, T.; Frishman, D. The Negatome database: A reference set of non-interacting protein pairs Nucleic Acids Res. 2010, 38, D540-D544
53. Cullinan, S. B.; Gordan, J. D.; Jin, J.; Harper, J. W.; Diehl, J. A. The Keap1-BTB protein is an adaptor that bridges Nrf2 to a Cul3-based E3 ligase: Oxidative stress sensing by a Cul3-Keap1 ligase Mol. Cell. Biol. 2004, 24, 8477-8486
54. Furukawa, M.; Xiong, Y. BTB protein Keap1 targets antioxidant transcription factor Nrf2 for ubiquitination by the Cullin 3-Roc1 ligase Mol. Cell. Biol. 2005, 25, 162-171
55. Zhang, D. D.; Lo, S.-C.; Cross, J. V.; Templeton, D. J.; Hannink, M. Keap1 is a redox-regulated substrate adaptor protein for a Cul3-dependent ubiquitin ligase complex Mol. Cell. Biol. 2004, 24, 10941-10953
56. Padmanabhan, B.; Tong, K. I.; Ohta, T.; Nakamura, Y.; Scharlock, M.; Ohtsuji, M.; Kang, M.-I.; Kobayashi, A.; Yokoyama, S.; Yamamoto, M. Structural basis for defects of Keap1 activity provoked by its point mutations in lung cancer Mol. Cell 2006, 21, 689-700
57. Singh, A.; Misra, V.; Thimmulappa, R. K.; Lee, H.; Ames, S.; Hoque, M. O.; Herman, J. G.; Baylin, S. B.; Sidransky, D.; Gabrielson, E. Dysfunctional KEAP1-NRF2 interaction in non-small cell lung cancer PLoS Med. 2006, 3, e420
58. Ohta, T.; Iijima, K.; Miyamoto, M.; Nakahara, I.; Tanaka, H.; Ohtsuji, M.; Suzuki, T.; Kobayashi, A.; Yokota, J.; Sakiyama, T. Loss of Keap1 function activates Nrf2 and provides advantages for lung cancer cell growth Cancer Res. 2008, 68, 1303-1309
59. Satoh, H.; Moriguchi, T.; Taguchi, K.; Takai, J.; Maher, J. M.; Suzuki, T.; Winnard, P. T.; Raman, V.; Ebina, M.; Nukiwa, T. Nrf2-deficiency creates a responsive microenvironment for metastasis to the lung Carcinogenesis 2010, 31, 1833-1843
60. Solis, L. M.; Behrens, C.; Dong, W.; Suraokar, M.; Ozburn, N. C.; Moran, C. A.; Corvalan, A. H.; Biswal, S.; Swisher, S. G.; Bekele, B. N. Nrf2 and Keap1 abnormalities in non-small cell lung carcinoma and association with clinicopathologic features Clin. Cancer Res. 2010, 16, 3743-3753
61. Takahashi, T.; Sonobe, M.; Menju, T.; Nakayama, E.; Mino, N.; Iwakiri, S.; Nagai, S.; Sato, K.; Miyahara, R.; Okubo, K. Mutations in Keap1 are a potential prognostic factor in resected non-small cell lung cancer J. Surg Oncol. 2010, 101, 500-506
62. Konstantinopoulos, P. A.; Spentzos, D.; Fountzilas, E.; Francoeur, N.; Sanisetty, S.; Grammatikos, A. P.; Hecht, J. L.; Cannistra, S. A. Keap1 mutations and Nrf2 pathway activation in epithelial ovarian cancer Cancer Res. 2011, 71, 5081-5089
63. Li, Q. K.; Singh, A.; Biswal, S.; Askin, F.; Gabrielson, E. KEAP1 gene mutations and NRF2 activation are common in pulmonary papillary adenocarcinoma J. Hum. Genet. 2011, 56, 230-234
64. Muscarella, L. A.; Parrella, P.; D'Alessandro, V.; la Torre, A.; Barbano, R.; Fontana, A.; Tancredi, A.; Guarnieri, V.; Balsamo, T.; Coco, M. Frequent epigenetics inactivation of KEAP1 gene in non-small cell lung cancer Epigenetics 2011, 6, 710-719
65. Sykiotis, G. P.; Bohmann, D. Stress-activated cap"n"collar transcription factors in aging and human disease Sci. Signaling 2010, 3, re3
66. Ogura, T.; Tong, K. I.; Mio, K.; Maruyama, Y.; Kurokawa, H.; Sato, C.; Yamamoto, M. Keap1 is a forked-stem dimer structure with two large spheres enclosing the intervening, double glycine repeat, and C-terminal domains Proc. Natl. Acad. Sci. U.S.A. 2010, 107, 2842-2847
67. Hoyt, M. A.; Totis, L.; Roberts, B. T. S. Cerevisiae genes required for cell cycle arrest in response to loss of microtubule function Cell 1991, 66, 507-517
68. Li, R.; Murray, A. W. Feedback control of mitosis in budding yeast Cell 1991, 66, 519-531
69. Sotillo, R.; Hernando, E.; Díaz-Rodríguez, E.; Teruya-Feldstein, J.; Cordón-Cardo, C.; Lowe, S. W.; Benezra, R. Mad2 overexpression promotes aneuploidy and tumorigenesis in mice Cancer Cell 2007, 11, 9-23
70. Schvartzman, J.-M.; Duijf, P. H. G.; Sotillo, R.; Coker, C.; Benezra, R. Mad2 is a critical mediator of the chromosome instability observed upon Rb and p53 pathway inhibition Cancer Cell 2011, 19, 701-714
71. Osmundson, E. C.; Ray, D.; Moore, F. E.; Gao, Q.; Thomsen, G. H.; Kiyokawa, H. The HECT E3 ligase Smurf2 is required for Mad2-dependent spindle assembly checkpoint J. Cell Biol. 2008, 183, 267-277
72. Kim, W.; Bennett, E. J.; Huttlin, E. L.; Guo, A.; Li, J.; Possemato, A.; Sowa, M. E.; Rad, R.; Rush, J.; Comb, M. J. Systematic and quantitative assessment of the ubiquitin-modified proteome Mol. Cell 2011, 44, 325-340