An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851.

Autor:	Chagas MDS; Fundação Oswaldo Cruz-Fiocruz, Programa de Computação Científica, Rio de Janeiro, RJ, Brasil., Medeiros Filho F; Fundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia, Laboratório de Pesquisa Clínica em Doenças Febris Agudas, Rio de Janeiro, RJ, Brasil., Dos Santos MT; Laboratório Nacional de Computação Científica, Petrópolis, RJ, Brasil., de Menezes MA; Universidade Federal Fluminense, Instituto de Física, Niterói, RJ, Brasil., Carvalho-Assef APD; Fundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de Pesquisa em Infecção Hospitalar, Rio de Janeiro, RJ, Brasil., Silva FABD; Fundação Oswaldo Cruz-Fiocruz, Programa de Computação Científica, Rio de Janeiro, RJ, Brasil.
Jazyk:	angličtina
Zdroj:	Memorias do Instituto Oswaldo Cruz [Mem Inst Oswaldo Cruz] 2022 Oct 14; Vol. 117, pp. e220111. Date of Electronic Publication: 2022 Oct 14 (Print Publication: 2022).
DOI:	10.1590/0074-02760220111
Abstrakt:	Background: Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. Objectives: In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. Methods: We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. Findings: Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. Main Conclusions: Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.
Databáze:	MEDLINE
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