A heat diffusion multilayer network approach for the identification of functional biomarkers in rumen methane emissions

M Wang, H Wang, Huiru Zheng*, RJ Dewhurst, R Roehe

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A better understanding of rumen microbial interactions is crucial for the study of rumen metabolism and methane emissions. Metagenomics-based methods can explore the relationship between microbial genes and metabolites to clarify the effect of microbial function on the host phenotype. This study investigated the rumen microbial mechanisms of methane metabolism in cattle by combining metagenomic data and network-based methods. Based on the relative abundance of 1461 rumen microbial genes and the main volatile fatty acids (VFAs), a multilayer heterogeneous network was constructed, and the functional modules associated with metabolite-microbial genes were obtained by heat diffusion algorithm. The PLS model by integrating data from VFAs and microbial genes explained 72.98% variation of methane emissions. Compared with single-layer networks, more previously reported biomarkers of methane prediction can be captured by the multilayer network. More biomarkers with the rank of top 20 topological centralities were from the PLS models of diffusion subsets.
The heat diffusion algorithm is different from the strategy used by the microbial metabolic system to understand methane phenotype. It inferred 24 novel biomarkers that were preferentially affected by changes in specific
VFAs. Results showed that the heat diffusion multilayer network approach improved the understanding of the microbial patterns of VFAs affecting methane emissions which represented by the functional microbial genes.
Original languageEnglish
Article number2020.09.014
Number of pages10
JournalMethods
Early online date15 Oct 2020
DOIs
Publication statusFirst published - 15 Oct 2020

Bibliographical note

Funding Information:
This research is jointly supported by Ulster University and Scotland's Rural College, U.K.

Publisher Copyright:
© 2020 Elsevier Inc.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Multilayer networks
  • Methane emissions
  • Metabolites
  • Network diffusion algorithm

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