Sensitivity analysis of a mechanistic model of rumen fermentation and methane production by rumen microbiota in the presence of Asparagopsis taxiformis

Ruminant animals rely on microbes for the conversion of complex plant material into host accessible metabolites. During this anaerobic conversion of plant biomass, termed enteric fermentation, methanogenic archaea convert hydrogen into the potent greenhouse gas methane (CH4). The search for methane mitigation strategies to combat climate change has identified the red seaweed Asparagopsis taxiformis as a promising feed additive that, when added to a regular cattle diet, reduced enteric CH4 by over 80%. A more complete understanding of microbial interactions during enteric fermentation is needed for ongoing improvement to mitigation methods. Mathematical models that permit in silico simulation of enteric fermentation allow for the identification of key parameters that drive rumen methane production. Here we built upon an existing rumen fermentation model and calibrated it using a preliminary classification of functional microbial groups and gas emission data from a previously published in vitro rumen fermentation experiment, but many microbes remained functionally unclassified. The model was then used to conduct an in silico experiment to explore how the partition of functionally unclassified microbes into functional groups affects methane output. These in silico experiments identified that model methane production is more sensitive to microbial variation in the presence of A. taxiformis versus without. The use of local and global sensitivity analysis approaches revealed other rumen parameters to also be drivers of enteric methane production. In the presence of A. taxiformis, parameters modulating methane production include bromoform concentration, methanogen abundance, total microbial concentration, a parameter effecting the inhibition of methanogen growth rate by the action of bromoform, and the maximum specific utilization rate of hydrogen. Without A. taxiformis, feed composition parameters, the hydrolysis rate constant of cell wall carbohydrates, and a parameter affecting the yield factors during sugar utilization were found to be most significant. For possible methane reduction without A. taxiformis, we propose an adjustment in feed composition parameters that reduces predicted methane by 25.6%.