A metagenomics analysis of rumen microbiome

Abstract

Climate change and food security are significant global challenges facing society. The dairy industry is inextricably linked to these challenges as it is concerned with the economies of food production, while acknowledging that it is a major contributor to greenhouse gas production. Action by microbial communities in the rumen is responsible for efficient breakdown of plant matter for food conversion, but a by-product of this action is substantial methane production. Insight into food conversion and methane production in rumen microbiota is possible through metagenomics analysis, which is the analysis of microbial communities and their interactions with the environment. However, metagenomic analysis is hampered by the sheer volume and complexity of data that needs to be processed. This paper presents a bioinformatics pipeline and visualisation platform that facilitates deep analysis of microbial communities, under various conditions in cattle rumen, with the aim of leading to significant impact on probiotic supplement usage, methane production and feed conversion efficiency. This pipeline was developed as part of the EU H2020 MetaPlat project and will pave the way for a more optimal usage of metagenomic datasets, thus reducing the number of animals necessary to be engaged in such studies. This will ensure better and more economic animal welfare, better use of resources and lessen the impact of the dairy industry on climate change.

A Comprehensive Study on Predicting Functional Role of Metagenomes Using Machine Learning Methods

“…Research has also been performed on other varied phenotype hosts such as the ocean, soil, and cattle where microbe-host interactions have great potential in uncovering the influence on an environmental condition being studied [21][22][23][24][25][26][27][28]. Wang et al [26] provided an integrated metagenomic analysis of rumen microbiome responsible for methane emissions and biomass degradation.…”

“…Wang et al [26] provided an integrated metagenomic analysis of rumen microbiome responsible for methane emissions and biomass degradation. Walsh et al [27] proposed a pipeline for metagenomics analysis for rumen microbiome. Toyama et al [28] proposed an analysis of microbial communities in freshwater lakes of Amazon Basin.…”

“…The Earth Microbiome project [4] has emerged to characterize the curation and analysis of microbial species across the globe. Supervised learning using OTU (microbiome) feature space to train models has been used to classify microbiomes into functional classes as indicated in [8], [9], [23][24][25][26][27][28][29]. The studies related to ML models for discriminating OTUs or taxa to predict the functional class of a new sample have been conducted [23][24][25][26][27][28][29][30][31][32].…”

PCR and qPCR-based applications in rumen microbiology research: a review

“…In metagenomics, the template DNA is sequenced without prior amplification of specific genes which results in a snapshot of the gene pool and functional potential of the microbiome while in transcriptomics, mRNA is analyzed to provide a measure of gene expression within the intestinal microbiome (Suchodolski, 2012). A deeper and clearer insight into taxonomic and functional characteristics of the rumen mi- crobiome and its interaction with the environment offers researchers the opportunity to optimize the digestion process in the rumen for enhanced and efficient sustainable utilization of dietary nutrients (Walsh et al, 2017). Metagenomic and metatranscriptomic inventions are considered more accurate and are widely used with conventional PCR and qPCR based protocols for routine identification, for result justifications and taxonomic assessment of the microbiota (Urich et al, 2008;Hong et al, 2009;Huber et al, 2009;Ross et al, 2012).…”

An Integrative Framework for Functional Analysis of Cattle Rumen Microbiomes

“…The combinations of different dietary supplement strategies are expected to reduce the methane emissions (CH4) in livestock systems to further improve the cattle productivity. Previous work [3,4,5], has highlighted the potential of controlled feeding of cattle with nitrate or oil treated diet and its effects on cattle rumen metabolism. Our aim is to perform data analysis to identify a predictive model for differentiating cattle microbiomes into four categories of diets: -oil-based, nitrate-based, combined diet (Oil-Nitrate) and controls.…”