Antibiotics (Aug 2024)

Unveiling the High Diversity of Clones and Antimicrobial Resistance Genes in <i>Escherichia coli</i> Originating from ST10 across Different Ecological Niches

  • Maxsueli Aparecida Moura Machado,
  • Pedro Panzenhagen,
  • Cesar Lázaro,
  • Miguel Rojas,
  • Eduardo Eustáquio de Souza Figueiredo,
  • Carlos Adam Conte-Junior

DOI
https://doi.org/10.3390/antibiotics13080737
Journal volume & issue
Vol. 13, no. 8
p. 737

Abstract

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In this pioneering in silico study in Peru, we aimed to analyze Escherichia coli (E. coli) genomes for antimicrobial resistance genes (ARGs) diversity and virulence and for its mobilome. For this purpose, 469 assemblies from human, domestic, and wild animal hosts were investigated. Of these genomes, three were E. coli strains (pv05, pv06, and sf25) isolated from chickens in our previous study, characterized for antimicrobial susceptibility profile, and sequenced in this study. Three other genomes were included in our repertoire for having rare cgMLSTs. The phenotypic analysis for antimicrobial resistance revealed that pv05, pv06, and sf25 strains presented multidrug resistance to antibiotics belonging to at least three classes. Our in silico analysis indicated that many Peruvian genomes included resistance genes, mainly to the aminoglycoside class, ESBL-producing E. coli, sulfonamides, and tetracyclines. In addition, through Multi-locus Sequence Typing, we found more than 180 different STs, with ST10 being the most prevalent among the genomes. Pan-genome mapping revealed that, with new lineages, the repertoire of accessory genes in E. coli increased, especially genes related to resistance and persistence, which may be carried by plasmids. The results also demonstrated several genes related to adhesion, virulence, and pathogenesis, especially genes belonging to the high pathogenicity island (HPI) from Yersinia pestis, with a prevalence of 42.2% among the genomes. The complexity of the genetic profiles of resistance and virulence in our study highlights the adaptability of the pathogen to different environments and hosts. Therefore, our in silico analysis through genome sequencing enables tracking the epidemiology of E. coli from Peru and the future development of strategies to mitigate its survival.

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