Pangenomic Identification of Metabolic Switches in Kosakonia cowanii: A Consolidated Network Biology Approach
Resumo
Kosakonia cowanii acts as both a plant growth-promoting rhizobacterium (PGPR) and an opportunistic pathogen. To characterize this lifestyle transition, we built a pangenomic pipeline across 77 genomes, consolidating strain-specific interactomes into a species-level graph. Biological coherence filters discarded 12,000 false-positive orthology mappings. Applying Bridging Centrality (BriCe) with functional bridging criteria identified 46 conserved metabolic switches at the PGPR-pathogen interface. These switches, including flagellar regulators and MFS transporters, are tractable targets for experimental validation.Referências
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Venturi, V. (2006). Regulation of bacterial virulence genes by quorum sensing and beyond. FEMS microbiology reviews, 30(2):274–291.
Angles, R. (2017). Arangodb-a graph database for the next generation. Proceedings of the 32nd Annual ACM Symposium on Applied Computing, pages 877–882.
Barabási, A.-L. and Oltvai, Z. N. (2004). Network biology: understanding the cell’s functional organization. Nature reviews genetics, 5(2):101–113.
Berg, G. (2014). Plant growth-promoting bacteria. Frontiers in microbiology, 5:491.
Blondel, V. D. et al. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment, 2008(10):P10008.
Brady, C. et al. (2013). Taxonomic evaluation of the genus enterobacter based on multilocus sequence analysis (mlsa). Systematic and applied microbiology, 36(5):309–319.
Eberl, L. and Vandamme, P. (2016). Members of the genus burkholderia: good and bad guys. F1000Research, 5.
Gonçalves, R. and Santos, A. (2025). Pannotator integrated with medpipe provides immunological and subcellular location features using a microservice. Biomedical Informatics, 1(1).
Guimera, R. and Amaral, L. A. N. (2005). Functional cartography of complex metabolic networks. Nature, 433(7028):895–900.
Hwang, W. et al. (2008). Bridging centrality: identifying bridging nodes in scale-free networks. Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 336–344.
Jeong, H. et al. (2001). Lethality and centrality in protein networks. Nature, 411(6833):41–42.
Peregrín-Alvarez, J. M. et al. (2011). Protein function prediction. Methods in molecular biology, 702:227–244.
Pereira, G., Ghosh, P., and Santos, A. (2021). A bridging centrality plugin for gephi and a case study for mycobacterium tuberculosis h37rv. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(6):2741–2746.
Saier Jr, M. H. et al. (2016). The transporter classification database (tcdb): recent advances. Nucleic acids research, 44(D1):D372–D379.
Silva, A., Marquez, C., Godoy, I., et al. (2025). Improving protein interaction prediction in genppi: a novel interaction sampling approach preserving network topology. BMC Bioinformatics, 26:296.
Stover, C. et al. (2000). Complete genome sequence of pseudomonas aeruginosa pao1. Nature, 406:959–964.
Tebaldi, N. D. et al. (2025). First report of kosakonia cowanii causing bacterial blight on coffea arabica in brazil. Plant Disease.
Tettelin, H. et al. (2005). Genome analysis of multiple pathogenic isolates of streptococcus agalactiae: implications for the microbial pan-genome. Proceedings of the National Academy of Sciences, 102(39):13950–13955.
Venturi, V. (2006). Regulation of bacterial virulence genes by quorum sensing and beyond. FEMS microbiology reviews, 30(2):274–291.
Publicado
15/06/2026
Como Citar
CAMPOS, Davi Mota et al.
Pangenomic Identification of Metabolic Switches in Kosakonia cowanii: A Consolidated Network Biology Approach. In: ESCOLA REGIONAL DE INFORMÁTICA DO TRIÂNGULO MINEIRO (ERI-TM), 1. , 2026, Uberlândia/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 67-71.
DOI: https://doi.org/10.5753/eritm.2026.27154.
