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Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models

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dc.audienceComunidad Rosaristaspa
dc.creatorRestrepo-Montoya, Daniel
dc.creatorBecerra, David
dc.creatorCarvajal Patino, Juan
dc.creatorMongui, Alvaro
dc.creatorNiño, Luis F.
dc.creatorPatarroyo, Manuel E.
dc.creatorPatarroyo, Manuel A.
dc.creator.googleRestrepo-Montoya, Daniel
dc.creator.googleBecerra, David
dc.creator.googleCarvajal-Patiño, Juan G.
dc.creator.googleMongui, Alvaro
dc.creator.googleNiño, Luis F.
dc.creator.googlePatarroyo, Manuel E.
dc.creator.googlePatarroyo, Manuel A.
dc.date.accessioned2014-08-13T19:38:44Z
dc.date.available2014-08-13T19:38:44Z
dc.date.created2011-10-03
dc.date.issued2011
dc.description.abstractBackground: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.eng
dc.format.mediumRecurso electrónicospa
dc.format.mimetypeapplication/pdf
dc.format.tipoDocumentospa
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0025189
dc.identifier.issnISSN:ISSN:1932-6203
dc.identifier.urihttp://repository.urosario.edu.co/handle/10336/8839
dc.language.isoeng
dc.publisherUniversidad del Rosariospa
dc.relation.citationIssueNo. 10
dc.relation.citationTitlePLOS ONE
dc.relation.citationVolumeVol. 6
dc.relation.ispartofPLOS ONE ISSN: 1932-6203 V. 6 N. 10 Oct, 3, 2011spa
dc.relation.urihttp://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0025189
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto completo)spa
dc.rights.licenciaEL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma.spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.ddcEnfermedades
dc.subject.decsMalariaspa
dc.subject.decsToxoplasmosisspa
dc.subject.decsPlasmodiumspa
dc.subject.keywordApicomplexan parasiteseng
dc.subject.keywordMalaria parasiteseng
dc.subject.keywordIN-silicoeng
dc.subject.keywordSubcellular - localizationeng
dc.subject.keywordToxoplasma-gondiieng
dc.subject.keywordAotus monkeyseng
dc.subject.keywordFalciparumeng
dc.subject.keywordPredictioneng
dc.subject.keywordDatabaseeng
dc.subject.keywordPeptideseng
dc.titleIdentification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov modelsspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersion
dc.type.spaArtículospa
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