The Trade-Off Between Sanitizer Resistance and Virulence Genes: Genomic Insights into <i>E. coli</i> Adaptation

Background: <i>Escherichia coli</i> is one of the most studied bacteria worldwide due to its genetic plasticity. Recently, in addition to characterizing its pathogenic potential, research has focused on understanding its resistance profile to inhibitory agents, whether these be antibioti...

Full description

Saved in:
Bibliographic Details
Main Authors: Vinicius Silva Castro, Yuri Duarte Porto, Xianqin Yang, Carlos Adam Conte Junior, Eduardo Eustáquio de Souza Figueiredo, Kim Stanford
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Antibiotics
Subjects:
Online Access:https://www.mdpi.com/2079-6382/14/3/291
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background: <i>Escherichia coli</i> is one of the most studied bacteria worldwide due to its genetic plasticity. Recently, in addition to characterizing its pathogenic potential, research has focused on understanding its resistance profile to inhibitory agents, whether these be antibiotics or sanitizers. Objectives: The present study aimed to investigate six of the main serogroups of foodborne infection (O26, O45, O103, O111, O121, and O157) and to understand the dynamics of heterogeneity in resistance to sanitizers derived from quaternary ammonium compounds (QACs) and peracetic acid (PAA) using whole-genome sequencing (WGS). Methods: Twenty-four <i>E. coli</i> strains with varied resistance profiles to QACs and PAA were analyzed by WGS using NovaSeq6000 (150 bp Paired End reads). Bioinformatic analyses included genome assembly (Shovill), annotation via Prokka, antimicrobial resistance gene identification using Abricate, and core-genome analysis using Roary. A multifactorial multiple correspondence analysis (MCA) was conducted to explore gene–sanitizer relationships. In addition, a large-scale analysis utilizing the NCBI Pathogen Detection database involved a 2 × 2 chi-square test to examine associations between the presence of <i>qac</i> and <i>stx</i> genes. Results: The isolates exhibited varying antimicrobial resistance profiles, with O45 and O157 being the most resistant serogroups. In addition, the <i>qac</i> gene was identified in only one strain (S22), while four other strains carried the <i>stx</i> gene. Through multifactorial multiple correspondence analysis, the results obtained indicated that strains harboring genes encoding Shiga toxin (<i>stx</i>) presented profiles that were more likely to be sensitive to QACs. To further confirm these results, we analyzed 393,216 <i>E. coli</i> genomes from the NCBI Pathogen Detection database. Our results revealed a significant association (<i>p</i> < 0.001) between the presence of <i>qac</i> genes and the absence of <i>stx1</i>, <i>stx2</i>, or both toxin genes. Conclusion: Our findings highlight the complexity of bacterial resistance mechanisms and suggest that non-pathogenic strains may exhibit greater tolerance to QAC sanitizer than those carrying pathogenicity genes, particularly Shiga toxin genes.
ISSN:2079-6382