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Genomic and Metagenomic Approaches for Predictive Surveillance of Emerging Pathogens and Antibiotic Resistance
Author(s) -
Sukhum Kimberley V.,
DiorioToth Luke,
Dantas Gautam
Publication year - 2019
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.1535
Subject(s) - metagenomics , antibiotic resistance , antibiotics , biology , computational biology , resistome , microbiology and biotechnology , drug resistance , genetics , gene , integron
Antibiotic‐resistant organisms ( ARO s) are a major concern to public health worldwide. While antibiotics have been naturally produced by environmental bacteria for millions of years, modern widespread use of antibiotics has enriched resistance mechanisms in human‐impacted bacterial environments. Antibiotic resistance genes ( ARG s) continue to emerge and spread rapidly. To combat the global threat of antibiotic resistance, researchers must develop methods to rapidly characterize ARO s and ARG s, monitor their spread across space and time, and identify novel ARG s and resistance pathways. We review how high‐throughput sequencing‐based methods can be combined with classic culture‐based assays to characterize, monitor, and track ARO s and ARG s. Then, we evaluate genomic and metagenomic methods for identifying ARG s and biosynthetic pathways for novel antibiotics from genomic data sets. Together, these genomic analyses can improve surveillance and prediction of emerging resistance threats and accelerate the development of new antibiotic therapies to combat resistance.