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Computational prediction and experimental assessment of secreted/surface proteins from Mycobacterium tuberculosis H37Rv

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dc.creatorVizcaíno, Carolina
dc.creatorRestrepo-Montoya, Daniel
dc.creatorRodríguez Burbano, Diana Consuelo
dc.creatorNiño, Luis F.
dc.creatorOcampo, Marisol
dc.creatorVanegas, Magnolia
dc.creatorReguero, María T.
dc.creatorMartínez, Nora L.
dc.creatorPatarroyo, Manuel E.
dc.creatorPatarroyo, Manuel A.
dc.creator.googleVizcaíno, Carolinaspa
dc.creator.googleRestrepo-Montoya, Danielspa
dc.creator.googleRodríguez, Dianaspa
dc.creator.googleNiño, Luis F.spa
dc.creator.googleOcampo, Marisolspa
dc.creator.googleVanegas, Magnoliaspa
dc.creator.googleReguero, María T.spa
dc.creator.googleMartínez, Nora L.spa
dc.creator.googlePatarroyo, Manuel E.spa
dc.creator.googlePatarroyo, Manuel A.spa
dc.date.accessioned2018-11-29T15:13:09Z
dc.date.available2018-11-29T15:13:09Z
dc.date.created2010
dc.date.issued2010
dc.description.abstractThe mycobacterial cell envelope has been implicated in the pathogenicity of tuberculosis and therefore has been a prime target for the identification and characterization of surface proteins with potential application in drug and vaccine development. In this study, the genome of Mycobacterium tuberculosis H37Rv was screened using Machine Learning tools that included feature-based predictors, general localizers and transmembrane topology predictors to identify proteins that are potentially secreted to the surface of M. tuberculosis, or to the extracellular milieu through different secretory pathways. The subcellular localization of a set of 8 hypothetically secreted/surface candidate proteins was experimentally assessed by cellular fractionation and immunoelectron microscopy (IEM) to determine the reliability of the computational methodology proposed here, using 4 secreted/surface proteins with experimental confirmation as positive controls and 2 cytoplasmic proteins as negative controls. Subcellular fractionation and IEM studies provided evidence that the candidate proteins Rv0403c, Rv3630, Rv1022, Rv0835, Rv0361 and Rv0178 are secreted either to the mycobacterial surface or to the extracellular milieu. Surface localization was also confirmed for the positive controls, whereas negative controls were located on the cytoplasm. Based on statistical learning methods, we obtained computational subcellular localization predictions that were experimentally assessed and allowed us to construct a computational protocol with experimental support that allowed us to identify a new set of secreted/surface proteins as potential vaccine candidates. © 2010 Vizcaíno et al.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1000824
dc.identifier.issnISSN 1553-734X
dc.identifier.urihttp://repository.urosario.edu.co/handle/10336/18754
dc.language.isoengspa
dc.relation.citationEndPage14
dc.relation.citationIssueNo. 6
dc.relation.citationStartPage1
dc.relation.citationTitlePLoS Computational Biology
dc.relation.citationVolumeVol. 6
dc.relation.ispartofPLoS Computational Biology, ISSN: 1553-734X, Vol. 6/No. 6 (2010) pp. 1-14spa
dc.relation.urihttps://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000824&type=printablespa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.rights.cchttps://creativecommons.org/licenses/by/4.0/spa
dc.source.bibliographicCitation(2009) Global Tuberculosis Control: Surveillance, Planning, Financing, , WHO, World Health Organization. Genova: WHO, World Health Organizationspa
dc.source.instnameinstname:Universidad del Rosario
dc.source.reponamereponame:Repositorio Institucional EdocUR
dc.subjectProteína bacterianaspa
dc.subjectBacterianaspa
dc.subjectLinfocito Bspa
dc.subjectGel de poliacrilamidaspa
dc.subjectProteína de citoplasmaspa
dc.subjectProteína de membranaspa
dc.subjectVacuna peptídicaspa
dc.subjectProteína Rv178spa
dc.subjectProteína Rv361spa
dc.subjectProteína Rv43Cspa
dc.subjectProteína Rv835spa
dc.subjectProteína Rv122spa
dc.subjectProteína Rv36spa
dc.subjectMedicamento no clasificadospa
dc.subjectAnticuerpo bacterianospa
dc.subjectEpítopospa
dc.subjectProteína de membrana externaspa
dc.subjectPéptidospa
dc.subjectExperimento con animalesspa
dc.subjectGenoma bacterianospa
dc.subjectCepa bacterianaspa
dc.subjectFraccionamiento Celularspa
dc.subjectPredicción por computadoraspa
dc.subjectEstudio controladospa
dc.subjectCitoplasmaspa
dc.subjectIdentificación de drogasspa
dc.subjectAprendizaje automáticospa
dc.subjectComputación Matemáticaspa
dc.subjectEstructura de la membranaspa
dc.subjectTuberculosis micobacterianaspa
dc.subjectLocalización de proteínasspa
dc.subjectSecreción de proteínasspa
dc.subjectProducción de vacunasspa
dc.subjectInteligencia artificialspa
dc.subjectEscherichia Colispa
dc.subjectinmunotransferenciaspa
dc.subjectMicroscopía inmunoelectrónicaspa
dc.subjectInmunologíaspa
dc.subjectMetabolismospa
dc.subjectMetodologíaspa
dc.subjectMycobacterium Smegmatisspa
dc.subjectElectroforesis en gel de poliacrilamidaspa
dc.subjectModelo estadísticospa
dc.subjectUltrasonidospa
dc.subjectTuberculosis micobacterianaspa
dc.subjectAnticuerposspa
dc.subjectInteligencia artificialspa
dc.subjectProteínas de la membrana externa bacterianaspa
dc.subjectFraccionamiento Celularspa
dc.subjectBiología Computacionalspa
dc.subjectElectroforesisspa
dc.subjectEpítoposspa
dc.subjectFracciones subcelularesspa
dc.subject.keywordSubcellular Fractionseng
dc.subject.keywordImmunoelectroneng
dc.subject.keywordElectrophoresisspa
dc.subject.keywordMicroscopyeng
dc.subject.keywordModelseng
dc.subject.keywordComputational Biologyeng
dc.subject.keywordEpitopeseng
dc.subject.keywordCell Fractionationeng
dc.subject.keywordBacterial Outer Membrane Proteinseng
dc.subject.keywordArtificial Intelligenceeng
dc.subject.keywordAntibodieseng
dc.subject.keywordMycobacterium Tuberculosiseng
dc.subject.keywordUltrasoundeng
dc.subject.keywordStatistical Modeleng
dc.subject.keywordPolyacrylamide Gel Electrophoresiseng
dc.subject.keywordMethodologyeng
dc.subject.keywordMetabolismeng
dc.subject.keywordImmunologyeng
dc.subject.keywordImmunoelectron Microscopyeng
dc.subject.keywordImmunoblottingeng
dc.subject.keywordArtificial Intelligenceeng
dc.subject.keywordVaccine Productioneng
dc.subject.keywordProtein Secretioneng
dc.subject.keywordProtein Localizationeng
dc.subject.keywordMycobacterium Tuberculosiseng
dc.subject.keywordMembrane Structureeng
dc.subject.keywordMathematical Computingeng
dc.subject.keywordMachine Learningeng
dc.subject.keywordDrug Identificationeng
dc.subject.keywordCytoplasmeng
dc.subject.keywordControlled Studyeng
dc.subject.keywordComputer Predictioneng
dc.subject.keywordCell Fractionationeng
dc.subject.keywordBacterial Straineng
dc.subject.keywordBacterial Genomeeng
dc.subject.keywordPeptideeng
dc.subject.keywordAnimal Experimenteng
dc.subject.keywordOuter Membrane Proteineng
dc.subject.keywordOuter Membrane Proteineng
dc.subject.keywordBacterium Antibodyeng
dc.subject.keywordUnclassified Drugeng
dc.subject.keywordProtein Rv363eng
dc.subject.keywordProtein Rv122eng
dc.subject.keywordProtein Rv43Ceng
dc.subject.keywordProtein Rv835eng
dc.subject.keywordProtein Rv361eng
dc.subject.keywordProtein Rv178eng
dc.subject.keywordPeptide Vaccineeng
dc.subject.keywordCytoplasm Proteineng
dc.subject.keywordMembrane Proteineng
dc.subject.keywordPolyacrylamide Geleng
dc.subject.keywordB-Lymphocyteeng
dc.subject.keywordBacterialeng
dc.subject.keywordBacterial Proteineng
dc.subject.lembMycobacterium tuberculosisspa
dc.subject.lembMycobacteriumspa
dc.subject.lembImmunoblottingspa
dc.titleComputational prediction and experimental assessment of secreted/surface proteins from Mycobacterium tuberculosis H37Rvspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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