Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in <named-content content-type="genus-species">Escherichia coli</named-content> and Unravel the Underlying Metabolic Adaptation Mechanisms

Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in <named-content content-type="genus-species">Escherichia coli</named-content> and Unravel the Underlying Metabolic Adaptation Mechanisms

ABSTRACT Antimicrobial resistance (AMR) is becoming one of the largest threats to public health worldwide, with the opportunistic pathogen Escherichia coli playing a major role in the AMR global health crisis. Unravelling the complex interplay between drug resistance and metabolic rewiring is key to...

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Bibliographic Details
Main Authors: Nicole Pearcy, Yue Hu, Michelle Baker, Alexandre Maciel-Guerra, Ning Xue, Wei Wang, Jasmeet Kaler, Zixin Peng, Fengqin Li, Tania Dottorini
Format: Article
Language:English
Published: American Society for Microbiology 2021-08-01
Series:mSystems
Subjects:
antimicrobial resistance
Escherichia coli
genome-scale metabolic model
machine learning
Online Access:https://journals.asm.org/doi/10.1128/mSystems.00913-20

Internet

https://journals.asm.org/doi/10.1128/mSystems.00913-20

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