English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The fitness cost to bacteria of acquisition of resistance determinants is critically under-investigated, and the identification and exploitation of these fitness costs may lead to novel therapeutic strategies that prevent the emergence of antimicrobial resistance. Here we used  Escherichia coli  and amoxicillin–clavulanic acid (AMC) resistance as a model to understand how the artificial environments utilized in studies of bacterial fitness could affect the emergence of resistance and associated fitness costs. Further, we explored the predictive value of this data when strains were grown in the more physiologically relevant environments of urine and urothelial organoids. Resistant  E. coli  isolates were selected for following 24-h exposure to sub-inhibitory concentrations of AMC in either M9, ISO, or LB, followed by growth on LB agar containing AMC. No resistant colonies emerged following growth in M9, whereas resistant isolates were detected from cultures grown in ISO and LB. We observed both within and between media-type variability in the levels of resistance and fitness of the resistant mutants grown in LB. MICs and fitness of these resistant strains in different media (M9, ISO, LB, human urine, and urothelial organoids) showed considerable variation. Media can therefore have a direct effect on the isolation of mutants that confer resistance to AMC and these mutants can exhibit unpredictable MIC and fitness profiles under different growth conditions. This preliminary study highlights the risks in relying on a single culture protocol as a model system to predict the behavior and treatment response of bacteria  in vivo  and highlights the importance of developing comprehensive experimental designs to ensure effective translation of diagnostic procedures to successful clinical outcomes.

Effect of Environment on the Evolutionary Trajectories and Growth Characteristics of Antibiotic-Resistant Escherichia coli Mutants