High-throughput method rapidly characterizes hundreds of novel antibiotic resistance mutations

Jago, M. J.; Soley, J. K.; Denisov, S.; Walsh, C. J.; Gifford, D. R.; Howden, B. P.; Lagator, M.

doi:10.1101/2024.07.19.604246

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bioRxiv · 10.1101/2024.07.19.604246

High-throughput method rapidly characterizes hundreds of novel antibiotic resistance mutations

Jago, M. J.·Soley, J. K.·Denisov, S.·Walsh, C. J.·Gifford, D. R.·Howden, B. P.·Lagator, M.

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Abstract

A fundamental obstacle to tackling the antimicrobial resistance crsisis is identifying mutations that lead to resistance in a given genomic background and environment. We present a high-throughput technique - Quantitative Mutational Scan Sequencing (QMS-Seq) - that enables quantitative comparison of which genes are under antibiotic selection and captures how genetic background influences resistance evolution. We compared four E. coli strains exposed to ciprofloxacin, cycloserine, or nitrofurantoin and identified 975 resistance mutations, many in genes and regulatory regions not previously associated with resistance. QMS-Seq revealed that multi-drug and antibiotic-specific resistance are acquired through categorically different types of mutations, and that minor genotypic differences significantly influence evolutionary routes to resistance. By quantifying mutation frequency with single base pair resolution, QMS-Seq informs about the underlying mechanisms of resistance and identifies mutational hotspots within genes. Our method provides a way to rapidly screen for resistance mutations while assessing the impact of multiple confounding factors.

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Jago, M. J., Soley, J. K., Denisov, S., Walsh, C. J., Gifford, D. R., Howden, B. P., Lagator, M.. 2024-07-19. High-throughput method rapidly characterizes hundreds of novel antibiotic resistance mutations. https://doi.org/10.1101/2024.07.19.604246

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