Title |
Overview of bioinformatic methods for analysis of antibiotic resistome from genome and metagenome data |
Author |
Kihyun Lee1,2, Dae-Wi Kim3, and Chang-Jun Cha1* |
Address |
1Department of Systems Biotechnology and Center for Antibiotic Resistome, Chung-Ang University, Anseong 17546, Republic of Korea, 2ChunLab, Inc., Seoul 06194, Republic of Korea, 3Division of Life Sciences, Jeonbuk National University, Jeonju 54896, Republic of Korea |
Bibliography |
Journal of Microbiology, 59(3),270–280, 2021,
|
DOI |
10.1007/s12275-021-0652-4
|
Key Words |
antimicrobial resistance, antibiotic resistome, genome,
metagenome |
Abstract |
Whole genome and metagenome sequencing are powerful
approaches that enable comprehensive cataloging and profiling
of antibiotic resistance genes at scales ranging from a
single clinical isolate to ecosystems. Recent studies deal with
genomic and metagenomic data sets at larger scales; therefore,
designing computational workflows that provide high
efficiency and accuracy is becoming more important. In this
review, we summarize the computational workflows used in
the research field of antibiotic resistome based on genome or
metagenome sequencing. We introduce workflows, software
tools, and data resources that have been successfully employed
in this rapidly developing field. The workflow described in
this review can be used to list the known antibiotic resistance
genes from genomes and metagenomes, quantitatively profile
them, and investigate the epidemiological and evolutionary
contexts behind their emergence and transmission. We also
discuss how novel antibiotic resistance genes can be discovered
and how the association between the resistome and
mobilome can be explored. |