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eISSN
2300-8733
First Published
25 Nov 2011
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4 times per year
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English
access type Open Access

Understanding microbial networks of farm animals through genomics, metagenomics and other meta-omic approaches for livestock wellness and sustainability

Published Online: 09 Mar 2022
Volume & Issue: AHEAD OF PRINT
Page range: -
Received: 03 Oct 2021
Accepted: 17 Nov 2021
Journal Details
License
Format
Journal
eISSN
2300-8733
First Published
25 Nov 2011
Publication timeframe
4 times per year
Languages
English
Abstract

The association of microorganisms with livestock as endosymbionts, opportunists, and pathogens has been a matter of debate for a long time. Several livestock-associated bacterial and other microbial species have been identified and characterized through traditional culture-dependent genomic approaches. However, it is imperative to understand the comprehensive microbial network of domestic animals for their wellness, disease management, and disease transmission control. Since it is strenuous to provide a niche replica to any microorganisms while culturing them, thus a substantial number of microbial communities remain obscure. Metagenomics has laid out a powerful lens for gaining insight into the hidden microbial diversity by allowing the direct sequencing of the DNA isolated from any livestock sample like the gastrointestinal tract, udder, or genital system. Through metatranscriptomics and metabolomics, understanding gene expression profiles of the microorganisms and their molecular phenotype has become unchallenging. With large data sets emerging out of the genomic, metagenomic, and other meta-omics methods, several computational tools have also been developed for curation, assembly, gene prediction, and taxonomic profiling of the microorganisms. This review provides a detailed account of the beneficial and pathogenic organisms that dwell within or on farm animals. Besides, it highlights the role of meta-omics and computational tools in a comprehensive analysis of livestock-associated microorganisms.

Keywords

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