Mining metagenomic and transcriptomic data for clues about microbial metabolic functions in ruminants.
Rumen microbiology research has evolved in the last decade to understand their diversity, metabolic functions and different interactions between host and microbes, particularly with the intervention of molecular biology techniques. To date, hundreds to thousands of microbial phylotypes have been identified from various rumen systems using the culture-independent molecular-based approaches. Exploring compositional and functional characteristics of the rumen microbiome can improve the understanding of its role in rumen function. Recent research has applied targeted high-throughput sequencing to assess the microbiota by the determination of presence or absence of unique microbial taxa. However, such information does not provide the functional aspect of the microbiota, such that this type of research is lacking in ruminants. In the past, we have developed various approaches aiming at enhancing the functional outcomes of rumen microbiota. First, we have developed a pipeline to enhance the outcomes of rumen metagenomic data set using a microbial genome reference based approach. Second, we developed a method to study the active rumen microbiomes at both taxonomic and functional levels using total RNA-sequencing based metatranscriptomics approach. These methods were then applied to study rumen microbiome from cattle raised under different dietary feeding, with different feed efficiencies and/or methane emissions. The in-depth understanding of rumen microbiome from numerous animal trials provides a more thorough understanding of rumen microbial metabolic functions and how they can be affected by various factors. Such knowledge is vital for enhancing nutrient utilization and improving animal productivity through enhanced rumen function