Identification of Complex Rumen Microbiome Interaction Within Diverse Functional Niches as Mechanisms Affecting the Variation of Methane Emissions in Bovine

Abstract

Martínez-Álvaro et al. Microbiome Network Explains Methane Emissions lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low-and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH 4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH 4 , which will benefit the development of efficient CH 4 mitigation strategies.

Bovine host genome acts on specific metabolism, communication and genetic processes of rumen microbes host-genomically linked to methane emissions

“…Our previous research has shown that the abundance of microbial communities, in particular their genes and interactions, are excellent biomarkers for the phenotypic prediction of CH 4 emissions 6,9,28 . The present study represents a large step further by discovering 36 heritable microbial gene abundances strongly host-genomically correlated with CH 4 emissions.…”

“…Among the significant microbial communities, most were bacteria (22 genera/17 RUGs) belonging to Bacteroidetes (5/14), Firmicutes (6/2) and Proteobacteria (9/1) phyla. Most microbial genes with strong r gCH4 were not directly involved in CH 4 metabolism pathways, but rather mechanisms indirectly affecting CH 4 production -most likely by limiting substrates for methanogenesis 9,68 , inhibiting methanogens, playing a role coordinating actions among microbial communities and the host or leading microbial genetic processes. Only H 2 -oxidizing Methanoregula (RA=0.003%) with unknown activity in rumen 42 and the microbial gene cofG involved in F 420 coenzyme biosynthesis 69,70 resulted in significant negative r gCH4 (-0.82 and -0.71, P 0 ≥0.95), suggesting that these are abundant under ruminal conditions unfavourable for other high CH 4 producing methanogens.…”

“…Ruminal methanogenesis is a complex process dependent on the cooperation of taxonomic communities with different metabolic activities [6][7][8][9] . A diverse community of bacteria, ciliate protozoa and anaerobic fungi 10 convert complex diet carbohydrates, proteins and lipids into volatile fatty acids, lactate, microbial proteins and vitamins, whilst releasing CO 2 , H 2 and other compounds.…”

New Insights into the Ecology and Physiology of Methanomassiliicoccales from Terrestrial and Aquatic Environments

“…At this threshold of 0.83, no OTU was branched with OTU21 or OTU926. Thus, to observe their associated connectivity, a slightly lower threshold was used (0.7) ( Figure S5 ) [ 117 ]. At this value, the Methanomassiliicoccales OTUs 21, 30, 101, and 926 showed significant non-random co-occurrences (weights: 0.70–0.87) with, respectively, 3, 5, 6, and 11 OTUs.…”

Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. II: Relation with solid passage rate and pH on neutral detergent fiber degradation and microbial function in continuous culture

“…Thus, the most likely reason for increased methanogenesis after dosing BCVFA is a result of increased NDF degradation increasing the [2H] pool from a shift toward pathways that liberate more H 2 or formate per unit of acetate produced (Janssen, 2010). Increased relative abundance of Fibrobacter (Roman-Garcia et al, 2021b) would not initially support this hypothesis because they do not produce H 2 , but they do increase crossfeeding by H 2 -producing bacteria (Martínez-Álvaro et al, 2020). However, inferences are limited because only half of our fermentors measured gas emission (i.e., n = 2 per treatment).…”