U.S. Department of Agriculture: Animal and Plant Health Inspection Service
A model for the prediction of antimicrobial resistance in Escherichia coli based on a comparative evaluation of fatty acid profiles
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The U.S. Government Works
Antimicrobial resistance is a threat to agricultural production and public health. In this proof-of-concept study, we investigated predicting antimicrobial sensitive/resistant (S/R) phenotypes and host sources of Escherichia coli (n = 128) based on differential fatty acid abundance. Myristic (14:0), pentadecanoic acid (15:0), palmitic (16:0), elaidic (18:19) and steric acid (18:0) were significantly different (α = 0.05) using a two-way ANOVA for predicting nalidixic acid, ciprofloxacin, aztreonam, cefatoxime, and ceftazidime S/R phenotypes. Additionally, analyses of palmitoleic (16:1), palmitic acid (16:0), methyl palmitate (i-17:0), and cis-9,10-methyleneoctadecanoic acid (19:0Δ) showed these markers were significantly different (α = 0.05) between isolates obtained from cattle and raccoons. S/R phenotype prediction for the above antibiotics or host source, based on linear regression models of fatty acid abundance, were made using a replicated-randomized subsampling and modeling approach. This model predicted S/R phenotype with 79% and 81% accuracy for nalidixic acid and ciprofloxacin, respectively. The isolate host source was predicted with 63% accuracy.
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https://doi.org/10.1016/j.diagmicrobio.2019.114966 0732-8893/Published by Elsevier Inc.