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Author Spotlight: Advancing Mycobacterial Biofilm Protocols for Enhanced Bacterial Metabolism Research
Published on: July 12, 2024
Sequencing-based methods and resources to study antimicrobial resistance
Manish Boolchandani1, Alaric W D'Souza1, Gautam Dantas2,3,4,5
1The Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
Abstract:
Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.
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