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dc.contributor.authorDe Souza, Gustavo A.en_US
dc.contributor.authorArntzen, Magnus Øverlieen_US
dc.contributor.authorFortuin, Sueretaen_US
dc.contributor.authorSchürch, Anitaen_US
dc.contributor.authorMålen, Hiwaen_US
dc.contributor.authorMcEvoy, Christopher R.en_US
dc.contributor.authorVan Soolingen, Dicken_US
dc.contributor.authorThiede, Bernden_US
dc.contributor.authorWarren, Robin M.en_US
dc.contributor.authorWiker, Harald G.en_US
dc.date.accessioned2013-02-22T09:23:56Z
dc.date.available2013-02-22T09:23:56Z
dc.date.issued2011-01eng
dc.PublishedMolecular & Cellular Proteomics 10(1)eng
dc.identifier.issn1535-9484
dc.identifier.issn1535-9476
dc.identifier.urihttps://hdl.handle.net/1956/6362
dc.description.abstractPrecise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to wholegenome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 Nterminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.en_US
dc.language.isoengeng
dc.publisherAmerican Society for Biochemistry and Molecular Biologyeng
dc.titleProteogenomic Analysis of Polymorphisms and Gene Annotation Divergences in Prokaryotes using a Clustered Mass Spectrometry-Friendly Databaseen_US
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2011 by The American Society for Biochemistry and Molecular Biology, Inc
dc.identifier.doihttps://doi.org/10.1074/mcp.m110.002527
dc.identifier.cristin348228
dc.source.journalMolecular & Cellular Proteomics
dc.source.4010
dc.source.141


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