Integrating microbial abundance time series with fermentation dynamics of the rumen microbiomeviamathematical modelling

Abstract

The rumen represents a dynamic microbial ecosystem where fermentation metabolites and microbial concentrations change over time in response to dietary changes. The integration of microbial genomic knowledge and dynamic modelling can enhance our system-level understanding of rumen ecosystem’s function. However, such an integration between dynamic models and rumen microbiota data is lacking. The objective of this work was to integrate rumen microbiota time series determined by 16S rRNA gene amplicon sequencing into a dynamic modelling framework to link microbial data to the dynamics of the volatile fatty acids (VFA) production during fermentation. For that, we used the theory of state observers to develop a model that estimates the dynamics of VFA from the data of microbial functional proxies associated with the specific production of each VFA. We determined the microbial proxies using CowPi to infer the functional potential of the rumen microbiota and extrapolate their functional modules from KEGG (Kyoto Encyclopedia of Genes and Genomes). The approach was challenged using data from anin vitroRUSITEC experiment and from anin vivoexperiment with four cows. The model performance was evaluated by the coefficient of variation of the root mean square error (CRMSE). For thein vitrocase study, the mean CVRMSE were 9.8% for acetate, 14% for butyrate and 14.5% for propionate. For thein vivocase study, the mean CVRMSE were 16.4% for acetate, 15.8% for butyrate and 19.8% for propionate. The mean CVRMSE for the VFA molar fractions were 3.1% for acetate, 3.8% for butyrate and 8.9% for propionate. Ours results show the promising application of state observers integrated with microbiota time series data for predicting rumen microbial metabolism.

Integrating microbial abundance time series with fermentation dynamics of the rumen microbiome via mathematical modelling

“…The scripts for the inference of the functional microbial modules are available at https://github.com/frubino/cowpi and https://doi.org/10.5281/zenodo.8401851 . The abundances of each module for each case study are in the Tables modules.Rusitec.xls and modules.Cows in [ 48 ]. A total of 308 modules were identified.…”

“…The microbial proxies for VFA production are named as M00579 ( m ac ), M99999 ( m bu ), M00013 ( m pr ). The implementation of the observer for each case study is available at [ 48 ].…”

“…The model performance was assessed by computing the coefficient of variation of the root mean squared error (CVRMSE). The Matlab scripts are available at [ 48 ] https://doi.org/10.5281/zenodo.8386786 .…”