A Comparison of Three Artificial Rumen Systems for Rumen Microbiome Modeling

Abstract

The rumen contains a complex mixture of microbes, crucial for the animal’s ability to degrade feed. Some of the feed-derived carbon is released as methane, a potent greenhouse gas, into the atmosphere. There is growing interest in reducing the loss of feed-derived carbon, making it available to the animal and improving animal productivity. Artificial rumen systems (ARSs) have been widely used to evaluate novel feed additives in terms of their ability to reduce methane production in the rumen and their effect on the rumen microbiome function prior to conducting resource-intensive animal trials. While the value of ARSs is widely acknowledged, it remains unclear which of these in vitro systems simulate the natural system most accurately. Here, we evaluated three different ARSs and compared them to in vivo rumen metrics. The results showed that all systems were capable of maintaining stable pH, redox potential, and temperature over time. The batch-style ARS simulated the rumen over 48 h. The semi-continuous ARS mimicked the volatile fatty acid profile and microbiota of the in vivo rumen for up to 120 h. Similarly, all ARSs maintained the prokaryotic and eukaryotic rumen populations over the duration of the study, with the semi-continuous ARS maintaining the natural rumen microbiome more accurately and for up to 120 h. In sum, our results suggest that three of the widely used ARSs simulate the rumen ecosystem adequately for many short-term rumen microbiome studies, with the more advanced semi-continuous ARS being more accurate when rumen simulation is extended to over 48 h.

Keywords

• artificial rumen systems
• greenhouse gases
• methane
• microbial ecology
• rumen microbiome
• rumen modeling