An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species.

ABSTRACT: Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set

SUBMITTER: Chung HC 

PROVIDER: S-EPMC10449230 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature