Probing the Mobilome: Discoveries in the Dynamic Microbiome. Issue 2 (February 2021)

• Record Type: Journal Article
• Authors: Carr, Victoria R.; Shkoporov, Andrey; Hill, Colin; Mullany, Peter; Moyes, David L.
• Is Part Of: Trends in microbiology. Volume 29:Issue 2(2021)
• Page Start: 158
• Page End: 170
• Publication Date: 2021-02
• Subjects: Microbiology -- Periodicals; Infection -- Periodicals; Virulence (Microbiology) -- Periodicals; Infection -- Periodicals; Microbiology -- Periodicals; Virulence -- Periodicals; Microbiologie -- Périodiques; Infection -- Périodiques; Virulence (Microbiologie) -- Périodiques; Infection; Microbiology; Virulence (Microbiology); 579
• DOI: 10.1016/j.tim.2020.05.003
• Languages: English
• ISSNs: 0966-842X

Abstract

Abstract : There has been an explosion of metagenomic data representing human, animal, and environmental microbiomes. This provides an unprecedented opportunity for comparative and longitudinal studies of many functional aspects of the microbiome that go beyond taxonomic classification, such as profiling genetic determinants of antimicrobial resistance, interactions with the host, potentially clinically relevant functions, and the role of mobile genetic elements (MGEs). One of the most important but least studied of these aspects are the MGEs, collectively referred to as the 'mobilome'. Here we elaborate on the benefits and limitations of using different metagenomic protocols, discuss the relative merits of various sequencing technologies, and highlight relevant bioinformatics tools and pipelines to predict the presence of MGEs and their microbial hosts. Highlights: The mobilome, defined as all mobile genetic elements (MGEs) of the microbiome, influences the composition of microbial communities and the spread of antimicrobial resistance genes and virulence factors via horizontal gene transfer. In contrast to targeted metagenomics, that specifically extracts a type of MGE prior to sequencing, whole metagenomes can potentially contain all MGEs of the microbiome, but de novo MGE identification is limited by current sequencing technologies and bioinformatics. Approaches, such as SMRT sequencing and proximity ligation, and bioinformatic methods, such as CRISPR spacer recognition, are able to predict the microbial hosts of MGEs. A combination of short- and long-read sequencing technologies and bioinformatic tools applied to whole metagenomes would generate the most comprehensive representation of the mobilome and its microbial hosts.