Multi-species identification of polymorphic peptide variants via propagation in spectral networks

Molecular and Cellular Proteomics

Volumn 15, Issue 11, 2016, Pages 3501-3512

  Na, Seungjin ^a   Payne, Samuel H ^b   Bandeira, Nuno ^a,c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^c UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACTERIAL PROTEIN; BIOFUEL; PEPTIDE;

AMINO ACID SEQUENCE; ARTICLE; BACTERIAL GENOME; BIOENERGY; BIOFUEL PRODUCTION; COMPARATIVE STUDY; CYANOTHECE; ENERGY RESOURCE; GENE SEQUENCE; ION EXCHANGE CHROMATOGRAPHY; NITROGEN FIXATION; NONHUMAN; PHYCOBILISOME; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN FAMILY; PROTEOMICS; SIGNAL NOISE RATIO; SPECIES IDENTIFICATION; TANDEM MASS SPECTROMETRY; ALGORITHM; CLASSIFICATION; CLUSTER ANALYSIS; METABOLISM; PROCEDURES; PROTEIN DATABASE; SEQUENCE ANALYSIS; SOFTWARE;

ALGORITHMS; BACTERIAL PROTEINS; CLUSTER ANALYSIS; CYANOTHECE; DATABASES, PROTEIN; GENOME, BACTERIAL; PEPTIDES; PROTEOMICS; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; TANDEM MASS SPECTROMETRY;

EID: 84995393699     PISSN: 15359476     EISSN: 15359484     Source Type: Journal    
DOI: 10.1074/mcp.O116.060913     Document Type: Article

References (45)

1. Falkowski, P. G., Fenchel, T., and Delong, E. F. (2008) The microbial engines that drive Earth's biogeochemical cycles. Science 320, 1034-1039
2. Rittmann, B. E. (2008) Opportunities for renewable bioenergy using micro-organisms. Biotechnol. Bioeng. 100, 203-212
3. Rittmann, B. E., Krajmalnik-Brown, R., and Halden, R. U. (2008) Pregenomic, genomic and post-genomic study of microbial communities involved in bioenergy. Nat. Rev. Microbiol. 6, 604-612
4. Ferreira, K. N., Iverson, T. M., Maghlaoui, K., Barber, J., and Iwata, S. (2004) Architecture of the photosynthetic oxygen-evolving center. Science 303, 1831-1838
5. Eng, J. K., McCormack, A. L., and Yates, J. R. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976-989
6. Perkins, D. N., Pappin, D. J., Creasy, D. M., and Cottrell, J. S. (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551-3567
7. Craig, R., and Beavis, R. C. (2003) A method for reducing the time required to match protein sequences with tandem mass spectra. Rapid Commun. Mass Spectrom. 17, 2310-2316
8. Wright, J. C., Beynon, R. J., and Hubbard, S. J. (2010) Cross species proteomics. Methods Mol. Biol. 604, 123-135
9. Habermann, B., Oegema, J., Sunyaev, S., and Shevchenko, A. (2004) The power and the limitations of cross-species protein identification by mass spectrometry-driven sequence similarity searches. Mol. Cell. Proteomics 3, 238-249
10. Han, Y., Ma, B., and Zhang, K. (2005) SPIDER: software for protein identification from sequence tags with de novo sequencing error. J. Bioin-form. Comput. Biol. 3, 697-716
11. Searle, B. C., Dasari, S., Wilmarth, P. A., Turner, M., Reddy, A. P., David, L. L., and Nagalla, S. R. (2005) Identification of protein modifications using MS/MS de novo sequencing and the OpenSea alignment algorithm. J. Proteome Res. 4, 546-554
12. Tsur, D., Tanner, S., Zandi, E., Bafna, V., and Pevzner, P. A. (2005) Identification of post-translational modifications by blind search of mass spectra. Nat. Biotechnol. 23, 1562-1567
13. Chalkley, R. J., Baker, P. R., Medzihradszky, K. F., Lynn, A. J., and Burlingame, A. L. (2008) In-depth analysis of tandem mass spectrometry data from disparate instrument types. Mol. Cell. Proteomics 7, 2386-2398
14. Chen, Y., Chen, W., Cobb, M. H., and Zhao, Y. (2009) PTMap-a sequence alignment software for unrestricted, accurate, and full-spectrum identi-fication of post-translational modification sites. Proc. Natl. Acad. Sci. U.S.A. 106, 761-766
15. Baliban, R. C., DiMaggio, P. A., Plazas-Mayorca, M. D., Young, N. L., Garcia, B. A., and Floudas, C. A. (2010) A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Mol. Cell. Proteomics 9, 764-779
16. Dasari, S., Chambers, M. C., Slebos, R. J., Zimmerman, L. J., Ham, A. J., and Tabb, D. L. (2010) TagRecon: high-throughput mutation identifica-tion through sequence tagging. J. Proteome Res. 9, 1716-1726
17. Han, X., He, L., Xin, L., Shan, B., and Ma, B. (2011) PeaksPTM: Mass spectrometry-based identification of peptides with unspecified modifi-cations. J. Proteome Res. 10, 2930-2936
18. Na, S., Bandeira, N., and Paek, E. (2012) Fast multi-blind modification search through tandem mass spectrometry. Mol. Cell. Proteomics 11, M111.010199
19. Ahrne, E., Muller, M., and Lisacek, F. (2010) Unrestricted identification of modified proteins using MS/MS. Proteomics 10, 671-686
20. Na, S., and Paek, E. (2015) Software eyes for protein post-translational modifications. Mass Spectrom. Rev. 34, 133-147
21. Lam, H. (2011) Building and searching tandem mass spectral libraries for peptide identification. Mol. Cell. Proteomics 10, R111.008565
22. Bandeira, N., Tsur, D., Frank, A., and Pevzner, P. A. (2007) Protein identification by spectral networks analysis. Proc. Natl. Acad. Sci. U.S.A. 104, 6140-6145
23. Guthals, A., Watrous, J. D., Dorrestein, P. C, and Bandeira, N. (2012) The spectral networks paradigm in high throughput mass spectrometry. Mol. Biosyst. 8, 2535-2544
24. Payne, S. H., Monroe, M. E., Overall, C. C, Kiebel, G. R., Degan, M., Gibbons, B. C, Fujimoto, G. M., Purvine, S. O., Adkins, J. N., Lipton, M. S., and Smith, R. D. (2015) The Pacific Northwest National Laboratory library of bacterial and archaeal proteomic biodiversity. Sci. Data 2, 150041
25. Ram, R. J., Verberkmoes, N. C, Thelen, M. P., Tyson, G. W., Baker, B. J., Blake R. C, 2nd, Shah, M., Hettich, R. L., and Banfield, J. F. (2005) Community proteomics of a natural microbial biofilm. Science 308, 1915-1920
26. VerBerkmoes, N. C, Denef, V. J., Hettich, R. L., and Banfield, J. F. (2009) Systems biology: Functional analysis of natural microbial consortia using community proteomics. Nat. Rev. Microbiol. 7, 196-205
27. Quintana, N., Van der Kooy, F., Van de Rhee, M. D., Voshol, G. P., and Verpoorte, R. (2011) Renewable energy from Cyanobacteria: energy production optimization by metabolic pathway engineering. Appl. Micro-biol. Biotechnol. 91, 471-490
28. Shih, P. M., Wu, D., Latifi, A., Axen, S. D., Fewer, D. P., Talla, E., Calteau, A., Cai, F., Tandeau de Marsac, N., Rippka, R., Herdman, M., Sivonen, K., Coursin, T., Laurent, T., Goodwin, L., Nolan, M., Davenport, K. W., Han, C. S., Rubin, E. M., Eisen, J. A., Woyke, T., Gugger, M., and Kerfeld, C. A. (2013) Improving the coverage of the cyanobacterial phylum using diversity-driven genome sequencing. Proc. Natl. Acad. Sci. U.S.A. 110, 1053-1058
29. Aryal, U. K., Stockel, J., Krovvidi, R. K., Gritsenko, M. A., Monroe, M. E., Moore, R. J., Koppenaal, D. W., Smith, R. D., Pakrasi, H. B., and Jacobs, J. M. (2011) Dynamic proteomic profiling of a unicellular cyanobacterium Cyanothece ATCC51142 across light-dark diurnal cycles. BMC Syst. Biol. 5, 194
30. Stockel, J., Jacobs, J. M., Elvitigala, T. R., Liberton, M., Welsh, E. A., Polpitiya, A. D., Gritsenko, M. A., Nicora, C. D., Koppenaal, D. W., Smith, R. D., and Pakrasi, H. B. (2011) Diurnal rhythms result in significant changes in the cellular protein complement in the cyanobacterium Cyanothece 51142. PLoS ONE 6, e16680
31. Frank, A. M., Bandeira, N., Shen, Z., Tanner, S., Briggs, S. P., Smith, R. D., and Pevzner, P. A. (2008) Clustering millions of tandem mass spectra. J. Proteome Res. 7, 113-122
32. Kim, S., and Pevzner, P. A. (2014) MS-GF+ makes progress towards a universal database search tool for proteomics. Nat. Commun. 5, 5277
33. Elias, J. E., and Gygi, S. P. (2007) Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spec-trometry. Nat. Methods 4, 207-214
34. Frank, A., and Pevzner, P. (2005) PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal. Chem. 77, 964-973
35. Wang, J., Bourne, P. E., and Bandeira, N. (2014) MixGF: spectral probabilities for mixture spectra from more than one peptide. Mol. Cell. Proteom-ics 13, 3688-3697
36. Bandyopadhyay, A., Stockel, J., Min, H., Sherman, L. A., and Pakrasi, H. B. (2010) High rates of photobiological H2 production by a cyanobacterium under aerobic conditions. Nat. Commun. 1, 139
37. Michalski, A., Cox, J., and Mann, M. (2011) More than 100, 000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. J. Proteome Res. 10, 1785-1793
38. Kwon, T., Choi, H., Vogel, C, Nesvizhskii, A. I., and Marcotte, E. M. (2011) MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines. J. Proteome Res. 10, 2949-2958
39. Savitski, M. M., Nielsen, M. L., and Zubarev, R. A. (2006) ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures. Mol. Cell. Proteomics 5, 935-948
40. Falkner, J. A., Falkner, J. W., Yocum, A. K., and Andrews, P. C. (2008) A spectral clustering approach to MS/MS identification of post-transla-tional modifications. J. Proteome Res. 7, 4614-4622
41. Wilhelm, T., and Jones, A. M. (2014) Identification of related peptides through the analysis of fragment ion mass shifts. J. Proteome Res. 13, 4002-4011
42. Guthals, A., Clauser, K. R., and Bandeira, N. (2012) Shotgun protein sequencing with meta-contig assembly. Mol. Cell. Proteomics 11, 1084-1096
43. Savitski, M. M., Mathieson, T., Becher, I., and Bantscheff, M. (2010) H-score, a mass accuracy driven rescoring approach for improved peptide identification in modification rich samples. J. Proteome Res. 9, 5511-5516
44. Guthals, A., Clauser, K. R., Frank, A. M., and Bandeira, N. (2013) Sequencing-grade de novo analysis of MS/MS triplets (CID/HCD/ETD) from over-lapping peptides. J. Proteome Res. 12, 2846-2857
45. Fu, Y., Xiu, L. Y., Jia, W., Ye, D., Sun, R. X., Qian, X. H., and He, S. M. (2011) DeltAMT: a statistical algorithm for fast detection of protein modifications from LC-MS/MS data. Mol. Cell. Proteomics 10, M110.000455