Dataset Information

Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows.

ABSTRACT: Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH₄ ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH₄ yield (CH₄ y = CH₄ /DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH₄ y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH₄ y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl-coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial least-squares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH₄ y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH₄ emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH₄ y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane-reduction selection programmes in the dairy cattle industry provided they are heritable.

SUBMITTER: Ramayo-Caldas Y

PROVIDER: S-EPMC6972549 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows.

Ramayo-Caldas Yuliaxis Y Zingaretti Laura L Popova Milka M Estellé Jordi J Bernard Aurelien A Pons Nicolas N Bellot Pau P Mach Núria N Rau Andrea A Roume Hugo H Perez-Enciso Miguel M Faverdin Philippe P Edouard Nadège N Ehrlich Dusko D Morgavi Diego P DP Renand Gilles G

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie 20190816 1

Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4 ) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH4 yield (CH4 y = CH4 /DMI) per cow. We implemented a combination of clustering, ...[more]

PMID: 31418488

Similar Datasets

Project description:Enteric methane (CH4) emission from cattle is strongly linked to the feeding regime and the rumen microbial community structure. Here, we report that feed-induced CH4-reducing effects correlate with specific alterations in the profile of the microbiome-encoded carbohydrate-active enzymes predicted from the rumen fluid metagenome. Rumen microbiome samples were obtained by mouth-tube sampling from 12 lactating Holstein cows after 3-4 weeks of feeding with three different concentrate-to-forage-ratio diets, i.e., standard, high, and extremely high levels of concentrate (4 cows per group; constant dry matter intake in the three groups). Increased inclusion of concentrate involved increased starch levels in the diet at the expense of fiber. The extreme diet resulted in 48% reduction of the CH4 emission per kg dry matter intake compared to the standard diet. From metagenome sequencing of the rumen fluid samples from each cow, 561 different microbial strains (bins) could be derived from analysis of 260 billion DNA base pairs. In the cows fed, the extreme diet, the relative abundance of the majority of the bins, was significantly altered compared to the other groups. Fibrobacterota and Verrucomicrobiota were less abundant in the Extreme group. Surprisingly, no significant abundance changes were observed among Archaea and Bacteroidota, although abundance changes of individual bins of these phyla were found. For each of the 561 bins, the functions of the metagenome-encoded carbohydrate-active enzymes were predicted by bioinformatics using conserved unique peptide pattern (CUPP) analysis. By linking each of the predicted molecular functions of the enzymes to their substrates, changes were found in the predicted abundance of the different enzyme types. Notably, the decreased CH4 emission of the extreme diet group was concurrent with a profound decrease in the xylan-active enzymes, targeting the xylan backbone β-1,4-linkages, acetyl-, feruloyl-, and methyl-glucuronoyl substitutions in xylan. This work provides a first enzyme-conversion-based characterization of how extreme feeding, i.e., lowered forage, can drive rumen microbiome changes that support decreased CH4 emission via a changed carbohydrate-active enzyme profile. The data, furthermore, provide a metagenome-wide catalog of enzymes, underpinning the microbial conversion of different feed fibers (the enzymes attacking specific carbohydrate linkages) in the rumen of Holstein cows.

Project description:Fermentation of pasture grasses and grains in the rumen of dairy cows and other ruminants produces methane as a by-product, wasting energy and contributing to the atmospheric load of greenhouse gasses. Many feeding trials in farmed ruminants have tested the impact of dietary components on feed efficiency, productivity and methane yield (MeY). Such diets remodel the rumen microbiome, altering bacterial, archaeal, fungal and protozoan populations, with an altered fermentation outcome. In dairy cows, some dietary grains can reduce enteric methane production. This is especially true of wheat, in comparison to corn or barley. Using a feeding trial of cows fed rolled wheat, corn or barley grain, in combination with hay and canola, we identified wheat-associated changes in the ruminal microbiome. Ruminal methane production, pH and VFA concentration data together with 16S rRNA gene amplicon sequences were used to compare ruminal bacterial and archaeal populations across diets. Differential abundance analysis of clustered sequences (OTU) identified members of the bacterial families Lachnospiraceae, Acidaminococcaceae, Eubacteriaceae, Prevotellaceae, Selenomonadaceae, Anaerovoracaceae and Fibrobacteraceae having a strong preference for growth in wheat-fed cows. Within the methanogenic archaea, (at >99% 16S rRNA sequence identity) the growth of Methanobrevibacter millerae was favoured by the non-wheat diets, while Methanobrevibacter olleyae was unaffected. From the wheat-preferring bacteria, correlation analysis found OTU strongly linked to reduced MeY, reduced pH and raised propionic acid levels. OTU from the genera Shuttleworthia and Prevotella_7 and especially Selenomonadaceae had high anti-methane correlations. An OTU likely representing (100% sequence identity) the fumarate-reducing, hydrogen-utilising, rumen bacterium Mitsuokella jalaludinii, had an especially high negative correlation coefficient (-0.83) versus MeY and moderate correlation (-0.6) with rumen pH, strongly suggesting much of the MeY suppression is due to reduced hydrogen availablity. Other OTU, representing as yet unknown species from the Selenomonadaceae family and the genera Prevotella_7, Fibrobacter and Syntrophococcus also had high to moderate negative MeY correlations, but low correlation with pH. These latter likely represent bacterial species able to reduce MeY without causing greater ruminal acidity, making them excellent candidates, provided they can be isolated, for development as anti-methane probiotics.

Project description:BackgroundRuminant livestock production is a considerable source of enteric methane (CH4) emissions. In a previous study, we found that dietary inclusions of Bacillus subtilis (BS) and Macleaya cordata extract (MCE) increased dry matter intake and milk production, while reduced enteric CH4 emission in dairy cows. The objective of this study was to further elucidate the impact of feeding BS and MCE on rumen methanogenesis in dairy cows using rumen metagenomics techniques.ResultsSixty dairy cows were blocked in 20 groups of 3 cows accordingly to their live weight, milk yield, and days in milk, and within each group, the 3 cows were randomly allocated to 1 of 3 treatments: control diet (CON), control diet plus BS (BS), and control diet plus MCE (MCE). After 75 days of feeding experimental diets, 12 cows were selected from each treatment for collection of rumen samples for the metagenomic sequencing. Results showed that BS decreased ruminal acetate and butyrate, while increased propionate concentrations, resulting in decreased acetate:propionate ratio. The metagenomics analysis revealed that MCE reduced relative abundances of Methanobrevibacter wolinii, Methanobrevibacter sp. AbM4, Candidatus Methanomassiliicoccus intestinalis, Methanobrevibacter cuticularis, Methanomicrobium mobile, Methanobacterium formicicum, and Methanobacterium congolense. Both BS and MCE reduced relative abundances of Methanosphaera sp. WGK6 and Methanosphaera stadtmanae. The co-occurrence network analysis of rumen bacteria and archaea revealed that dietary treatments influenced microbial interaction patterns, with BS and MCE cows having more and stronger associations than CON cows. The random forest and heatmaps analysis demonstrated that the Halopenitus persicus was positively correlated with fat- and protein-corrected milk yield; Clostridium sp. CAG 269, Clostridium sp. 27 14, Haloarcula rubripromontorii, and Methanobrevibacter curvatus were negatively correlated with rumen acetate and butyrate concentrations, and acetate:propionate ratio, whereas Selenomonas rumiantium was positively correlated with those variables.ConclusionsThe present results provided new information for mitigation of enteric methane emissions of dairy cows by feeding BS and MCE to influence rumen microbial activities. This fundamental knowledge is essential for developing enteric CH4 reduction strategies to mitigate climate change and reduce dietary energy waste. Video Abstract.

Project description:Methane (CH4) is produced as an end product from feed fermentation in the rumen. Yield of CH4 varies between individuals despite identical feeding conditions. To get a better understanding of factors behind the individual variation, 73 dairy cows given the same feed but differing in CH4 emissions were investigated with focus on fiber digestion, fermentation end products and bacterial and archaeal composition. In total 21 cows (12 Holstein, 9 Swedish Red) identified as persistent low, medium or high CH4 emitters over a 3 month period were furthermore chosen for analysis of microbial community structure in rumen fluid. This was assessed by sequencing the V4 region of 16S rRNA gene and by quantitative qPCR of targeted Methanobrevibacter groups. The results showed a positive correlation between low CH4 emitters and higher abundance of Methanobrevibacter ruminantium clade. Principal coordinate analysis (PCoA) on operational taxonomic unit (OTU) level of bacteria showed two distinct clusters (P < 0.01) that were related to CH4 production. One cluster was associated with low CH4 production (referred to as cluster L) whereas the other cluster was associated with high CH4 production (cluster H) and the medium emitters occurred in both clusters. The differences between clusters were primarily linked to differential abundances of certain OTUs belonging to Prevotella. Moreover, several OTUs belonging to the family Succinivibrionaceae were dominant in samples belonging to cluster L. Fermentation pattern of volatile fatty acids showed that proportion of propionate was higher in cluster L, while proportion of butyrate was higher in cluster H. No difference was found in milk production or organic matter digestibility between cows. Cows in cluster L had lower CH4/kg energy corrected milk (ECM) compared to cows in cluster H, 8.3 compared to 9.7 g CH4/kg ECM, showing that low CH4 cows utilized the feed more efficient for milk production which might indicate a more efficient microbial population or host genetic differences that is reflected in bacterial and archaeal (or methanogens) populations.

Dataset Information

Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows.

Publications

Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets