RT Journal Article
T1 bacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria.
A1 Guerrero-Egido, Guillermo
A1 Pintado Calvillo, Adrián
A1 Bretscher, Kevin
A1 Arias-Giraldo, Luisa-Maria
A1 Paulson, Joseph
A1 Spaink, Herman
A1 Claessen, Dennis
A1 Ramos-Rodríguez, Cayo Juan
A1 Cazorla-López, Francisco Manuel
A1 Medema, Marnix
A1 Raaijmakers, Jos M.
A1 Carrión Bravo, Víctor José
K1 Genómica
K1 Bioinformática
K1 Aprendizaje automático (Inteligencia artificial)
K1 Relaciones huésped-bacteria
AB Bacteria 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.
PB Springer Nature
YR 2024
FD 2024
LK https://hdl.handle.net/10630/40336
UL https://hdl.handle.net/10630/40336
LA eng
NO Guerrero-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-y
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 23 ene 2026