Tackling drug resistant infection outbreaks of global pandemic Escherichia coli ST131 using evolutionary and epidemiological genomics

TL;DR

This paper discusses how genomic analysis of E. coli ST131 can help understand and predict the development and spread of antimicrobial resistance, aiming to improve treatment strategies and prevent future outbreaks.

Contribution

It introduces a comprehensive genomic and phylogenetic approach to study the evolution, transmission, and resistance mechanisms of E. coli ST131 to inform better intervention strategies.

Findings

Mutations increased virulence and adhesion in ST131

SNPs enabled widespread fluoroquinolone resistance

Frequent gain and loss of beta-lactamase resistance genes

Abstract

High-throughput molecular screening is required to investigate the origin and diffusion of antimicrobial resistance in pathogen outbreaks. The most frequent cause of human infection is Escherichia coli, which is dominated by sequence type 131 (ST131), a set of rapidly radiating pandemic clones. The highly infectious clades of ST131 originated firstly by a mutation enhancing virulence and adhesion. Secondly, single-nucleotide polymorphisms occurred enabling fluoroquinolone-resistance, which is near-fixed in all ST131. Thirdly, broader resistance through beta-lactamases has been gained and lost frequently, symptomatic of conflicting environmental selective effects. This flexible approach to gene exchange is worrying and supports the proposition that ST131 will develop an even wider range of plasmid and chromosomal elements promoting antimicrobial resistance. To stymie ST131, deep genome sequencing is required to understand the origin, evolution and spread of antimicrobial resistance genes. Phylogenetic methods that decipher past events can predict future patterns of virulence and transmission based on genetic signatures of adaptation and gene exchange. Both the effect of partial antimicrobial exposure and cell dormancy caused by variation in gene expression may accelerate the development of resistance. High-throughput sequencing can decode measurable evolution of cell populations within patients associated with systems-wide changes in gene expression during treatments. A multi-faceted approach can enhance assessment of antimicrobial resistance in E. coli ST131 by examining transmission dynamics between hosts to achieve a goal of pre-empting resistance before it emerges by optimising antimicrobial treatment protocols.