Related Experiment Video
Updated: Mar 11, 2026

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Genomic and metagenomic technologies to explore the antibiotic resistance mobilome
José L Martínez1, Teresa M Coque2,3,4, Val F Lanza2,3,4
1Centro Nacional de Biotecnología, CSIC, Darwin 3, Madrid, Spain.
Abstract:
Antibiotic resistance is a relevant problem for human health that requires global approaches to establish a deep understanding of the processes of acquisition, stabilization, and spread of resistance among human bacterial pathogens. Since natural (nonclinical) ecosystems are reservoirs of resistance genes, a health-integrated study of the epidemiology of antibiotic resistance requires the exploration of such ecosystems with the aim of determining the role they may play in the selection, evolution, and spread of antibiotic resistance genes, involving the so-called resistance mobilome. High-throughput sequencing techniques allow an unprecedented opportunity to describe the genetic composition of a given microbiome without the need to subculture the organisms present inside. However, bioinformatic methods for analyzing this bulk of data, mainly with respect to binning each resistance gene with the organism hosting it, are still in their infancy. Here, we discuss how current genomic methodologies can serve to analyze the resistance mobilome and its linkage with different bacterial genomes and metagenomes. In addition, we describe the drawbacks of current methodologies for analyzing the resistance mobilome, mainly in cases of complex microbiotas, and discuss the possibility of implementing novel tools to improve our current metagenomic toolbox.
Related Concept Videos
Antibiotic Selection
Development of Antibiotic Resistance
Genomic DNA in Prokaryotes
Genomic Diversity in Bacteria
Although bacterial genomes are much...
Modern Molecular Taxonomy
Transformation
Genome Size and the Evolution of New Genes

