bacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria.

dc.contributor.authorGuerrero-Egido, Guillermo
dc.contributor.authorPintado Calvillo, Adrián
dc.contributor.authorBretscher, Kevin
dc.contributor.authorArias-Giraldo, Luisa-Maria
dc.contributor.authorPaulson, Joseph
dc.contributor.authorSpaink, Herman
dc.contributor.authorClaessen, Dennis
dc.contributor.authorRamos-Rodríguez, Cayo Juan
dc.contributor.authorCazorla-López, Francisco Manuel
dc.contributor.authorMedema, Marnix
dc.contributor.authorRaaijmakers, Jos M.
dc.contributor.authorCarrión Bravo, Víctor José
dc.date.accessioned2025-10-20T11:08:41Z
dc.date.available2025-10-20T11:08:41Z
dc.date.issued2024
dc.departamentoBiología Celular, Genética y Fisiologíaes_ES
dc.description.abstractBacteria have an extensive adaptive ability to live in close association with eukaryotic hosts, exhibiting detrimental, neutral or beneficial effects on host growth and health. However, the genes involved in niche adaptation are mostly unknown and their functions poorly characterized. Here, we present bacLIFE (https://github.com/Carrion-lab/bacLIFE) a streamlined computational workflow for genome annotation, large-scale comparative genomics, and prediction of lifestyle-associated genes (LAGs). As a proof of concept, we analyzed 16,846 genomes from the Burkholderia/Paraburkholderia and Pseudomonas genera, which led to the identification of hundreds of genes potentially associated with a plant pathogenic lifestyle. Site-directed mutagenesis of 14 of these predicted LAGs of unknown function, followed by plant bioassays, showed that 6 predicted LAGs are indeed involved in the phytopathogenic lifestyle of Burkholderia plantarii and Pseudomonas syringae pv. phaseolicola. These 6 LAGs encompassed a glycosyltransferase, extracellular binding proteins, homoserine dehydrogenases and hypothetical proteins. Collectively, our results highlight bacLIFE as an effective computational tool for prediction of LAGs and the generation of hypotheses for a better understanding of bacteria-host interactions.es_ES
dc.identifier.citationGuerrero-Egido, G., Pintado, A., Bretscher, K. M., Arias-Giraldo, L.-M., Paulson, J. N., Spaink, H. P., Claessen, D., Ramos, C., Cazorla, F. M., Medema, M. H., Raaijmakers, J. M., & Carrión, V. J. (2024). bacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria. Nature Communications, 15, 2072. https://doi.org/10.1038/s41467-024-46302-yes_ES
dc.identifier.doi10.1038/s41467-024-46302-y
dc.identifier.urihttps://hdl.handle.net/10630/40336
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGenómicaes_ES
dc.subjectBioinformáticaes_ES
dc.subjectAprendizaje automático (Inteligencia artificial)es_ES
dc.subjectRelaciones huésped-bacteriaes_ES
dc.subject.otherGenómica comparativaes_ES
dc.subject.otherInteracción bacteria-huéspedes_ES
dc.subject.otherbacLIFEes_ES
dc.subject.otherMachine Learninges_ES
dc.subject.otherMutagénesis dirigidaes_ES
dc.titlebacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria.es_ES
dc.typejournal articlees_ES
dc.type.hasVersionAMes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication00be32a4-e0df-4f77-b832-835236a7d1d0
relation.isAuthorOfPublicationf7a5dfc9-8c29-4e68-b877-5ecf24a6b1ba
relation.isAuthorOfPublication.latestForDiscovery00be32a4-e0df-4f77-b832-835236a7d1d0

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