Dietary inclusion of Asparagopsis taxiformis significantly reduces methane emissions in dairy ruminants by mechanistically altering vitamin B12 coenzyme production and other methanogenesis precursor pathways.
Lawther, K.; Dimonaco, N. J.; Guinguina, A.; Krizsan, S. J.; Huws, S. A.
Show abstract
Ruminant products are consumed widely on a global level due to their high protein and micronutrient density. However, ruminant production is a major source of greenhouse gas emissions, particularly with respect to methane (CH), with ruminants contributing 33% of all anthropogenic CH emissions. CH is produced due to the natural fermentative processes undertaken by the complex rumen microbiome, primarily via the utilisation of hydrogen by rumen archaea to form CH. Previous studies have shown that feeding the red seaweed Asparagopsis taxiformis (ASP) to ruminants can reduce CHemissions from beef cattle by up to 80% (Roque et al., 2021). Nevertheless, the mechanism of action of this seaweed in terms of effects on the rumen microbiome is largely unknown, which is the main focus of this study. Six Nordic Red cows at 122 {+/-} 13.7 (mean {+/-} SD) days in milk were divided into 3 blocks by milk yield in Latin square design and fed grass silage and a commercial concentrate (60:40) either with or without 0.5% ASP on an organic matter basis. Rumen fluid was collected 19 days into each experimental period, with a holistic approach using both assembly and read mapping based approaches to interrogate taxonomic, functional, and ecological shifts applied to metagenomic data. We show that ASP reduces methane production not only through direct inhibition of methanogens but also by disrupting cobamide-dependent metabolic pathways and redirecting carbon flow toward pyruvate and propionate rather than acetate and methane. For the first time, specific enzymes involved in vitamin B12 (cobamide) biosynthesis are identified as suppressed by ASP, and microbial taxa contributing to these functional changes are elucidated showing both niche displacement and resilience within the rumen microbiome. These findings offer new mechanistic insight into how red seaweed supplementation modulates the rumen microbiome, supporting its potential role in sustainable ruminant production.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Dietary emulsifiers alter composition and activity of the human gut microbiota in vitro, irrespective of chemical or natural emulsifier origin. 96%
- Antibiotic prophylaxis and hospitalization of horses subjected to median laparotomy: gut microbiota trajectories and abundance increase of Escherichia 95%
- Specialized Bacteroidetes dominate the Arctic Ocean during marine spring blooms 95%
Similar papers in this journal
- Microbiomes attached to fresh perennial ryegrass- are temporally resilient and adapt to changing ecological niches 97%
- Development of a three-compartment in vitro simulator of the Atlantic Salmon GI tract and associated microbial communities: SalmoSim 96%
- Association of gut microbiota with metabolism in juvenile Atlantic Salmon 94%
Similar papers in this journal
- Pouch microbiome changes during lactation in the short-beaked echidna (Tachyglossus aculeatus) 94%
- Marine particle microbiomes during a spring diatom bloom contain active sulfate-reducing bacteria 93%
- Exploring methanogenic archaea and their thermal responses in the glacier-fed stream sediments of Rongbuk River Basin, Mt. Everest 93%
Similar papers in this journal
- Multi-omics analyses reveal rumen microbes and secondary metabolites that are unique to livestock species 95%
- Carbon Assimilation Strategies in Ultrabasic Groundwater: Clues from the Integrated Study of a Serpentinization-Influenced Aquifer 94%
- Validating the Cyc2 neutrophilic Fe oxidation pathway using meta-omics of Zetaproteobacteria iron mats at marine hydrothermal vents 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.