ArticleGigaScience2022
Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 39 citations in OpenAlex.
- Animal gut microbes and microbiomes in the 21st century and beyond.Science China. Life sciences · 2026Review
- Rumen DNA virome plasticity and viral metabolic potential are associated with seasonal adaptation in grazing yak and cattle on the Qinghai-Tibet Plateau.Journal of animal science and biotechnology · 2026Article
- Reliable enteric methane prediction from the cattle (Bos taurus) rumen microbiome.Communications biology · 2026Article
- Rumen Mycobiome Thiamine Metabolism Contributes to Subacute Rumen Acidosis Tolerance in Goats Through Enhancing Epithelial Cell Proliferation via IGFBP2/IGF1 Axis Activation.Exploration (Beijing, China) · 2026Article
- Host-microbiome interplay supports heat stress resilience in zebu calves.Animal microbiome · 2026Article
- Review
- The association of the rumen virome with methane emissions in dairy cattle.Communications biology · 2025Article
- Anaerobic fungi: effective warriors in lignocellulosic biomass degradation and fermentation.FEMS microbiology ecology · 2025Review
- Article
- The crosstalk between host and rumen microbiome in cattle: insights from multi-omics approaches and genome-wide association studies.World journal of microbiology & biotechnology · 2025Review
- Effects of feeding high-moisture corn on growth performance and rumen metabolism in young Simmental bulls.Frontiers in veterinary science · 2025Article
- A review of key microbial and nutritional elements for mechanistic modeling of rumen fermentation in cattle under methane-inhibition.Frontiers in microbiology · 2024Review
- Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy.Scientific reports · 2023Article
- Effect of Chitosan on Ruminal Fermentation and Microbial Communities, Methane Emissions, and Productive Performance of Dairy Cattle.Animals : an open access journal from MDPI · 2023Article
- The effects of Selenohomolanthionine supplementation on the rumen eukaryotic diversity of Shaanbei white cashmere wether goats.Scientific reports · 2023Article
- Evolving understanding of rumen methanogen ecophysiology.Frontiers in microbiology · 2023Review
- Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle.GigaScience · 2022Article
- Fungi and cercozoa regulate methane-associated prokaryotes in wetland methane emissions.Frontiers in microbiology · 2022Article
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions.
resultsThe β-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals.
conclusionsMethane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.
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