Systems Biology, Bioinformatics and Livestock Science

System Biology and Livestock Gut Microbiome

Author(s): Shyamalima Saikia, Minakshi Puzari and Pankaj Chetia * .

Pp: 96-128 (33)

DOI: 10.2174/9789815165616123010010

* (Excluding Mailing and Handling)

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.

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