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Identification of microbial determinants of low and high methane emission in cows through rumen whole microbiome sequencing

Projekter: ProjektForskning

Se relationer på Aarhus Universitet


Cattle plays an important role in food security by converting low-value lignocellulosic plant material into high-value animal proteins, milk and meat(1). Microorganisms present in the rumen ferment polysaccharides to yield short-chain fatty acids (acetate, butyrate and propionate) that are absorbed across the rumen epithelium and used by the ruminant for maintenance, growth and production. Rumen microbiome plays a critical role in the digestion of feed and production of gut methane for ruminants(2). However, methane emission from ruminant account for 16% of global greenhouse gas emissions(3) and represent 2–12% of feed energy loss(4-5). Therefore, decrease methane emissions from ruminants is urgently needed. Hydrogen is the primary substrate for methane production in rumen. Ruminal microorganisms associated with hydrogen metabolism largely affect ruminal methane productions(6). Hydrogen-utilizing bacteria are good ruminal modifiers for methane mitigation. However, availability of sequenced genomes and functional information for most methane producing microbes remains limited. Large-scale reference genome catalogs of bacteria and archaea in the cow rumen will help us to understand microbiome functions, diversity and interactions with the host. The knowledge can be utilized to increase feed efficiency and reduce enteric methane emission from cows.
Currently there is lack in knowledge on the relationships between high-throughput measures (e.g., host animal, microbial communities, proteomes, and metabolomes) with indicators of health, production efficiency and GHG emission in cattle. Such knowledge is necessary for sustainable cattle breeding. New analyses approach and tools are necessary for routine use of high-throughput data in commercial animal production (e.g., genomic selection, precision management,). Rumen microbiome play a pivotal role in digestion of feed staff and production enteric methane. Several studies have used 16sRNA to characterize the rumen microbiome, and their relationship with feed efficiency and methane emission(7). However, ribosomal RNA does not provide a complete picture of the different microbes in the microbial community.
In this PhD project, we have two strategies 1) sequence and assemble the genome of whole microbes in the rumen. 2) focusing on the genes present in the combined microbial population which alter the metabolite content in the rumen. To accomplish our strategies, we use rumen sample for whole genome sequencing. The rumen content samples will be drawn from individual cows by oral insertion of the probe “Flora Rumen Scoop”(8). Meanwhile, the NMR will be used to test rumen and blood metabolites. 
The PhD project proposes a comparative metagenome analysis of the rumen microbiome by using next-generation sequencing. The final outcoming of the project will be a list of microbial species and some which could affect the methane emission, understanding the microbial gene content on target phenotypes and candidate cattle genes that would affect the interaction between host genome and rumen microbiome. Through metagenomic full sequence data from the microbiota in cow rumen, we expect to get the full repertoire of genes involved in methane production, their role in hydrogen metabolism. In the scientific view, this study fills gaps of the functional (molecular) aspect of cattle rumen microbes and interaction with metabolites (intermediate phenotypes). The de novo rumen microbiome assembling of cattle will be a substantial improvement. The association study of methane emission with assembled rumen microbial species and the association between WGS marker set with microbiome are novel in livestock. The outputs of this project would facilitate breeding cows for increase feed efficiency and low methane emission.


1. Matthews, C.; Crispie, F.; Lewis, E.; Reid, M.; O’Toole, P. W.; Cotter, P. D., The rumen microbiome: a crucial consideration when optimising milk and meat production and nitrogen utilisation efficiency. Gut Microbes 2019, 10 (2), 115-132.
2. Ghanbari Maman, L.; Palizban, F.; Fallah Atanaki, F.; Elmi Ghiasi, N.; Ariaeenejad, S.; Ghaffari, M. R.; Hosseini Salekdeh, G.; Kavousi, K., Co-abundance analysis reveals hidden players associated with high methane yield phenotype in sheep rumen microbiome. Scientific Reports 2020, 10 (1), 4995.
3. Asselstine, V.; Lam, S.; Miglior, F.; Brito, L. F.; Sweett, H.; Guan, L.; Waters, S. M.; Plastow, G.; Cánovas, A., The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies. Journal of Animal Science 2021, 99 (10).
4. de Azevedo, E. B.; Savian, J. V.; do Amaral, G. A.; de David, D. B.; Gere, J. I.; Kohmann, M. M.; Bremm, C.; Jochims, F.; Zubieta, A. S.; Gonda, H. L.; Bayer, C.; de Faccio Carvalho, P. C., Feed intake, methane yield, and efficiency of utilization of energy and nitrogen by sheep fed tropical grasses. Tropical Animal Health and Production 2021, 53 (5), 452.
5. Nibedita, S.; Swati, P.; Pattnaik, M.; Mohapatra, S., Methane Emission and Strategies for Mitigation in Livestock. In Environmental and Agricultural Microbiology, 2021; pp 257-274.
6. Wallace, R. J.; Rooke, J. A.; McKain, N.; Duthie, C.-A.; Hyslop, J. J.; Ross, D. W.; Waterhouse, A.; Watson, M.; Roehe, R., The rumen microbial metagenome associated with high methane production in cattle. BMC Genomics 2015, 16 (1), 839.
7. Bica, R.; Palarea-Albaladejo, J.; Kew, W.; Uhrin, D.; Pacheco, D.; Macrae, A.; Dewhurst, R. J., Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle. Scientific Reports 2020, 10 (1), 5578.
8. Difford, G. F.; Plichta, D. R.; Løvendahl, P.; Lassen, J.; Noel, S. J.; Højberg, O.; Wright, A.-D. G.; Zhu, Z.; Kristensen, L.; Nielsen, H. B.; Guldbrandtsen, B.; Sahana, G., Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows. PLOS Genetics 2018, 14 (10), e1007580.

Effektiv start/slut dato01/09/202131/08/2024

ID: 223908504