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Understanding antimicrobial discovery and resistance from a metagenomic and metatranscriptomic perspective: advances and applications

Asante, Jonathan, Osei Sekyere, John
Environmental microbiology reports 2019 v.11 no.2 pp. 62-86
DNA methylation, anthropogenic activities, antibiotic resistance genes, antibiotics, bacteria, bioinformatics, databases, diagnostic techniques, humans, metagenomics, microbiome, pathogens, screening, transcriptomics, xenobiotics
Our inability to cultivate most microorganisms, specifically bacteria, in the laboratory has for many years restricted our view and understanding of the bacterial meta‐resistome in all living and nonliving environments. As a result, reservoirs, sources and distribution of antibiotic resistance genes (ARGS) and antibiotic‐producers, as well as the effects of human activity and antibiotics on the selection and dissemination of ARGs were not well comprehended. With the advances made in the fields of metagenomics and metatranscriptomics, many of the hitherto little‐understood concepts are becoming clearer. Further, the discovery of antibiotics such as lugdinin and lactocillin from the human microbiota, buttressed the importance of these new fields. Metagenomics and metatranscriptomics are becoming important clinical diagnostic tools for screening and detecting pathogens and ARGs, assessing the effects of antibiotics, other xenobiotics and human activity on the environment, characterizing the microbiome and the environmental resistome with lesser turnaround time and decreasing cost, as well as discovering antibiotic‐producers. However, challenges with accurate binning, skewed ARGs databases, detection of less abundant and allelic variants of ARGs and efficient mobilome characterization remain. Ongoing efforts in long‐read, phased‐ and single‐cell sequencing, strain‐resolved binning, chromosomal‐conformation capture, DNA‐methylation binning and deep‐learning bioinformatic approaches offer promising prospects in reconstructing complete strain‐level genomes and mobilomes from metagenomes.