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

TL;DR

This study explores how E. coli strains balance resistance to sanitizers and their ability to cause disease, using genomic data to reveal patterns in resistance and virulence.

Contribution

The study reveals a significant inverse relationship between sanitizer resistance genes and virulence genes in E. coli using large-scale genomic analysis.

Findings

O45 and O157 E. coli serogroups showed the highest resistance to sanitizers.

Strains with stx genes (encoding Shiga toxin) were more likely to be sensitive to QAC sanitizers.

A significant association was found between qac genes and the absence of stx1 and stx2 toxin genes.

Abstract

Background: Escherichia coli 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 E. coli 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 qac and stx genes. Results: The isolates exhibited varying antimicrobial resistance profiles, with O45 and O157 being the most resistant serogroups. In addition, the qac gene was identified in only one strain (S22), while four other strains carried the stx gene. Through multifactorial multiple correspondence analysis, the results obtained indicated that strains harboring genes encoding Shiga toxin (stx) presented profiles that were more likely to be sensitive to QACs. To further confirm these results, we analyzed 393,216 E. coli genomes from the NCBI Pathogen Detection database. Our results revealed a significant association (p < 0.001) between the presence of qac genes and the absence of stx1, stx2, 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.

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