Towards forecasting antimicrobial resistance evolution: concordance of in vitro and in vivo studies
- 1FU Berlin
Abstract
Antimicrobial resistance is a major global health concern, and current measures to address the problem are new drugs, prudent use and rapid diagnostics. Recently, the idea of forecasting resistance evolution experimentally to prevent resistance a priori has gained attention. But how well do experimental data on antimicrobial resistance evolution reflect resistance in strains from patients? We conducted a systematic review and analysis to compare in vitro and in vivo data. We collect-ed and analysed literature on experimental resistance evolution published between 1977 and 2024 available on PubMed for ESKAPE pathogens plus E. coli (ESKAPEE). We catalogued the magnitude of resistance evolution via minimum inhibitory concentration (MIC) changes across antimicrobial classes. We then focussed on P. aeruginosa and E. coli under ciprofloxacin (CIP) selection, as these were most frequent bacterial species used in experimental evolution. CIP-selected gene mutations and amino acid substitutions, as well as the associated MICs in experimentally evolved P. aeruginosa and E. coli isolates, were compared with corresponding in vivo data. In vitro and in vivo isolates of E. coli showed high concordance in the selected gene mutations and the specific amino acid changes. Similar results were found for P. aeruginosa Evolved MIC values differed significantly depending on the respective gene mutation and the total num-ber of mutations, but not due to the origin of the strains, in vitro or in vivo. Our findings clearly show that experimental resistance evolution in vitro could predict the emergence of antimicrobial resistance evolution in vivo. This study supports the idea that experimental data can be used to forecast the risks of resistance emergence and therefore contribute to antimicrobial stewardship. It will be important to investigate how generalizable these findings are for other bacteria-antimicrobial combinations.
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BibTeX
@misc{herzog2026towards,
title = {{Towards forecasting antimicrobial resistance evolution: concordance of in vitro and in vivo studies}},
author = {M. Herzog and R. Murphy and J. Rolff},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.22.760874},
url = {https://www.biorxiv.org/content/10.64898/2026.10.22.760874v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Towards forecasting antimicrobial resistance evolution: concordance of in vitro and in vivo studies
AU - M. Herzog
AU - R. Murphy
AU - J. Rolff
PY - 2026
DA - 2026/10/22
PB - bioRxiv
DO - 10.64898/2026.10.22.760874
UR - https://www.biorxiv.org/content/10.64898/2026.10.22.760874v1
AB - Antimicrobial resistance is a major global health concern, and current measures to address the problem are new drugs, prudent use and rapid diagnostics. Recently, the idea of forecasting resistance evolution experimentally to prevent resistance a priori has gained attention. But how well do experimental data on antimicrobial resistance evolution reflect resistance in strains from patients? We conducted a systematic review and analysis to compare in vitro and in vivo data. We collect-ed and analysed literature on experimental resistance evolution published between 1977 and 2024 available on PubMed for ESKAPE pathogens plus E. coli (ESKAPEE). We catalogued the magnitude of resistance evolution via minimum inhibitory concentration (MIC) changes across antimicrobial classes. We then focussed on P. aeruginosa and E. coli under ciprofloxacin (CIP) selection, as these were most frequent bacterial species used in experimental evolution. CIP-selected gene mutations and amino acid substitutions, as well as the associated MICs in experimentally evolved P. aeruginosa and E. coli isolates, were compared with corresponding in vivo data. In vitro and in vivo isolates of E. coli showed high concordance in the selected gene mutations and the specific amino acid changes. Similar results were found for P. aeruginosa Evolved MIC values differed significantly depending on the respective gene mutation and the total num-ber of mutations, but not due to the origin of the strains, in vitro or in vivo. Our findings clearly show that experimental resistance evolution in vitro could predict the emergence of antimicrobial resistance evolution in vivo. This study supports the idea that experimental data can be used to forecast the risks of resistance emergence and therefore contribute to antimicrobial stewardship. It will be important to investigate how generalizable these findings are for other bacteria-antimicrobial combinations.
ER -