Abstract
With the recent advances in high throughput next-generation sequencing
technologies and bioinformatics approach, gut microbiome research, especially in
livestock species, has expanded immensely, elucidating the greatest potential to
investigate the unacknowledged understanding of rumen microbiota in host physiology
at the molecular level. The association of a complex aggregated community of
microbes to host metabolism is of great importance due to their crucial participation in
metabolic, immunological, and physiological tasks. The knowledge of this
sophisticated network of a symbiotic association of gut microbiota to host organisms
may lead to novel insights for improving health, enhancing production, and reducing
the risk of disease progression in livestock species necessary to meet the demands of the
human race. The full picture of microorganisms present in a particular area can be
achieved with the help of culture-independent omics-based approaches. The integration
of metagenomics, metatranscriptomics, metaproteomics, and meta-metabolomics
technologies with systems biology emphasizes the taxonomic composition,
identification, functional characterization, gene abundance, metabolic profiling, and
phylogenetic information of microbial population along with the underlying
mechanism for pathological processes and their involvement as probiotic. The rumen
secretions or partially digested feed particles, as well as fecal samples, are generally
employed for gut microbiome investigation. The 16S rRNA gene sequencing
amplicon-based technology is the most employed technique for microbiome profiling
in livestock species to date. The use of software and biological databases in the field of
gut microbiome research gives an accurate in-depth analysis of the microbial
population greatly.
Keywords: 16S rRNA gene sequencing, Archaea, Bacteria, Biomarker, BLAST, Databases, Fungi, Gut microbiome, Goat, KEGG, Livestock, Metagenomics, Meta-metabolomics, Metaproteomics, Metatranscriptomics, Next-generation sequencing, Ruminants, Sheep, Shotgun sequencing, Swine.