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Altering the Gut Microbiome of Cattle: Considerations of Host-Microbiome Interactions for Persistent Microbiome Manipulation

Author:
Clemmons, Brooke A., Voy, Brynn H., Myer, Phillip R.
Source:
Microbial ecology 2019 v.77 no.2 pp. 523-536
ISSN:
0095-3628
Subject:
beef cattle, beef industry, biomarkers, diet, energy, feed conversion, feeds, host specificity, host-pathogen relationships, intestinal microorganisms, methane production, microbiome, nitrogen, phenotype, red meat, rumen, selection criteria
Abstract:
The beef cattle industry represents a significant portion of the USA’s agricultural sect, with beef cattle accounting for the most red meat consumed in the USA. Feed represents the largest input cost in the beef industry, accounting for approximately 70% of total input cost. Given that, novel methods need to be employed to optimize feed efficiency in cattle to reduce monetary cost as well as environmental cost associated with livestock industries, such as methane production and nitrogen release into the environment. The rumen microbiome contributes to feed efficiency by breaking down low-quality feedstuffs into energy substrates that can subsequently be utilized by the host animal. Attempts to manipulate the rumen microbiome have been met with mixed success, though persistent changes have not yet been achieved beyond changing diet. Recent technological advances have made analyzing host-wide effects of the rumen microbiome possible, as well as provided finer resolution of those effects. This manuscript reviews contributing factors to the rumen microbiome establishment or re-establishment following rumen microbiome perturbation, as well as host-microbiome interactions that may be responsible for possible host specificity of the rumen microbiome. Understanding and accounting for the variety of factors contributing to rumen microbiome establishment or re-establishment in cattle will ultimately lead to identification of biomarkers of feed efficiency that will result in improved selection criteria, as well as aid to determine methods for persistent microbiome manipulation to optimize production phenotypes.
Agid:
6316104