Summary
A bioRxiv preprint reports that ciprofloxacin resistance mutations selected in laboratory experiments largely matched those found in in vivo data for E. coli and P. aeruginosa. The authors say this supports using experimental evolution to help forecast resistance risks, while noting that other bacteria–drug combinations need study.
A bioRxiv preprint reports that laboratory experiments selecting for ciprofloxacin resistance produced genetic changes broadly concordant with those found in in vivo data for Escherichia coli and Pseudomonas aeruginosa. The authors say the result supports using experimental evolution to help forecast how resistance may emerge, though they identify other bacteria–antimicrobial combinations as an important next test.
How the researchers compared resistance evolution
The researchers systematically reviewed and analysed literature on experimental resistance evolution published from 1977 to 2024 and available through PubMed. Their survey covered ESKAPE pathogens plus E. coli, a group of bacteria associated with difficult-to-treat infections. They catalogued changes in minimum inhibitory concentration (MIC) across antimicrobial classes. MIC is the lowest concentration of an antimicrobial that prevents visible bacterial growth under specified test conditions; a higher MIC indicates that more drug is needed to inhibit growth in that test.
For a more detailed comparison, the researchers focused on E. coli and P. aeruginosa exposed to ciprofloxacin. They compared mutations in selected genes, the specific amino-acid changes those mutations produced, and the MICs reported for experimentally evolved isolates with corresponding in vivo data.
What matched—and what influenced MIC
For E. coli, the preprint reports high concordance between in vitro and in vivo data in both the selected gene mutations and the specific amino-acid changes. The authors report similar findings for P. aeruginosa.
MIC values differed according to which gene mutation was present and the total number of mutations. In the analysis, they did not differ according to whether the strains originated from laboratory evolution or in vivo data. This suggests that, for the two organism–drug combinations examined, laboratory selection can reproduce important features of resistance evolution seen outside the laboratory.
That matters because controlled experiments make it possible to examine how resistance-associated changes arise under drug selection. If such experiments reliably anticipate which changes may emerge, they could contribute evidence for assessing resistance risks and informing antimicrobial stewardship. The study supports that possibility; it does not describe a clinical forecasting tool for choosing treatment for an individual patient.
The work is a bioRxiv preprint. Its detailed comparison centres on ciprofloxacin resistance in two bacterial species, and the authors say the findings need to be tested across other bacteria and antimicrobials before their broader applicability is known.