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Engelstädter, J.

Publications and source records attributed to Engelstädter, J..

2 recordsLinked to original sources

Mutations associated with streptomycin resistance predicted to be highly prevalent and evolvable across bacteria

Antimicrobial resistance is an evolutionary response to antimicrobial exposure that has been extensively studied across some bacteria, including pathogens and model organisms. Yet, for most species the capacity to develop resistance remains unresolved. Here, we used computational methods to assess patterns of streptomycin resistance evolution across the bacterial tree of life. We curated a panel of high-confidence streptomycin resistance mutations, including eight mutations in the rpsL gene and four mutations in the rrs gene. We then used this panel to screen over 20 000 bacterial genomes from diverse clades. We assessed both evolvability, defined by codon-level accessibility to resistance-conferring mutations via single-nucleotide substitutions, and intrinsic resistance, where resistance-associated variants are already present. Our results suggest that most bacterial species can readily acquire rpsL-resistant mutations. Furthermore, we find that approximately 7% of bacterial species intrinsically carry rpsL resistance variants, with a wide taxonomic distribution but notable enrichment within Alphaproteobacteria. Our study provides a global view of the streptomycin resistance mutational landscape and generates testable predictions for future research.

evolutionary biology↗

Drug mode of action and resource constraints modulate antimicrobial resistance evolution

One of the key characteristics of an antibiotic drug is its mode of action: bacteriostatic or bactericidal. The effect of drug mode of action on the evolution of resistance has been surprisingly underinvestigated to date. We present a theoretical model comparing the efficacy of bacteriostatic and bactericidal drugs, and drugs of intermediate type, at preventing the evolutionary rescue of an initially susceptible bacterial population in a patient. Our results suggest that in resource-abundant environments bacteriostatic drugs are best, as they constrain cell divisions and thus cause fewer resistance mutations to occur. When multiple drugs are employed, using one bacteriostatic and one bactericidal drug is usually optimal, because the cell division rate cannot fall below zero, so there are diminishing returns to bacteriostatic activity from two drugs. We also provide a web-based simulation engine for other researchers to intuitively explore related dynamics without requiring programming expertise.

evolutionary biology↗