Complete genome sequence of Methanosphaera sp. ISO3-F5, a rumen methylotrophic methanogen.

Methanosphaera spp. are methylotrophic methanogenic archaea and members of the order Methanobacteriales with few cultured representatives. Methanosphaera sp. ISO3-F5 was isolated from sheep rumen contents in New Zealand. Here, we report its complete genome, consisting of a large chromosome and a megaplasmid (GenBank accession numbers CP118753 and CP118754, respectively).

Diversity and community structure of anaerobic gut fungi in the rumen of wild and domesticated herbivores.

The rumen houses a diverse community that plays a major role in the digestion process in ruminants. Anaerobic gut fungi (AGF) are key contributors to plant digestion in the rumen. Here, we present a global amplicon-based survey of the rumen AGF mycobiome by examining 206 samples from 15 animal species, 15 countries, and 6 continents. The rumen AGF mycobiome was highly diverse, with 81 out of 88 currently recognized AGF genera or candidate genera identified. However, only six genera (Neocallimastix, Orpinomyces, Caecomyces, Cyllamyces, NY9, and Piromyces) were present at >4% relative abundance. AGF diversity was higher in members of the families Antilocapridae and Cervidae compared to Bovidae. Community structure analysis identified a pattern of phylosymbiosis, where host family (10% of total variance) and species (13.5%) partially explained the rumen mycobiome composition. As well, diet composition (9%-19%), domestication (11.14%), and biogeography (14.1%) also partially explained AGF community structure; although sampling limitation, geographic range restrictions, and direct association between different factors hindered accurate elucidation of the relative contribution of each factor. Pairwise comparison of rumen and fecal samples obtained from the same subject (n = 13) demonstrated greater diversity and inter-sample variability in rumen versus fecal samples. The genera Neocallimastix and Orpinomyces were present in higher abundance in rumen samples, while Cyllamyces and Caecomyces were enriched in fecal samples. Comparative analysis of global rumen and feces data sets revealed a similar pattern. Our results provide a global view of AGF community in the rumen and identify patterns of AGF variability between rumen and feces in herbivores Gastrointestinal (GI) tract.IMPORTANCERuminants are highly successful and economically important mammalian suborder. Ruminants are herbivores that digest plant material with the aid of microorganisms residing in their GI tract. In ruminants, the rumen compartment represents the most important location where microbially mediated plant digestion occurs, and is known to house a bewildering array of microbial diversity. An important component of the rumen microbiome is the anaerobic gut fungi (AGF), members of the phylum Neocallimastigomycota. So far, studies examining AGF diversity have mostly employed fecal samples, and little is currently known regarding the identity of AGF residing in the rumen compartment, factors that impact the observed patterns of diversity and community structure of AGF in the rumen, and how AGF communities in the rumen compare to AGF communities in feces. Here, we examined the rumen AGF diversity using an amplicon-based survey targeting a wide range of wild and domesticated ruminants (n = 206, 15 different animal species) obtained from 15 different countries. Our results demonstrate that while highly diverse, no new AGF genera were identified in the rumen mycobiome samples examined. Our analysis also indicate that animal host phylogeny, diet, biogeography, and domestication status could play a role in shaping AGF community structure. Finally, we demonstrate that a greater level of diversity and higher inter-sample variability was observed in rumen compared to fecal samples, with two genera (Neocallimastix and Orpinomyces) present in higher abundance in rumen samples, and two others (Cyllamyces and Caecomyces) enriched in fecal samples. Our results provide a global view of the identity, diversity, and community structure of AGF in ruminants, elucidate factors impacting diversity and community structure of the rumen mycobiome, and identify patterns of AGF community variability between the rumen and feces in the herbivorous GI tract.

Distinct microbial hydrogen and reductant disposal pathways explain interbreed variations in ruminant methane yield.

Ruminants are essential for global food security, but these are major sources of the greenhouse gas methane. Methane yield is controlled by the cycling of molecular hydrogen (H2), which is produced during carbohydrate fermentation and is consumed by methanogenic, acetogenic, and respiratory microorganisms. However, we lack a holistic understanding of the mediators and pathways of H2 metabolism and how this varies between ruminants with different methane-emitting phenotypes. Here, we used metagenomic, metatranscriptomic, metabolomics, and biochemical approaches to compare H2 cycling and reductant disposal pathways between low-methane-emitting Holstein and high-methane-emitting Jersey dairy cattle. The Holstein rumen microbiota had a greater capacity for reductant disposal via electron transfer for amino acid synthesis and propionate production, catalyzed by enzymes such as glutamate synthase and lactate dehydrogenase, and expressed uptake [NiFe]-hydrogenases to use H2 to support sulfate and nitrate respiration, leading to enhanced coupling of H2 cycling with less expelled methane. The Jersey rumen microbiome had a greater proportion of reductant disposal via H2 production catalyzed by fermentative hydrogenases encoded by Clostridia, with H2 mainly taken up through methanogenesis via methanogenic [NiFe]-hydrogenases and acetogenesis via [FeFe]-hydrogenases, resulting in enhanced methane and acetate production. Such enhancement of electron incorporation for metabolite synthesis with reduced methanogenesis was further supported by two in vitro measurements of microbiome activities, metabolites, and public global microbiome data of low- and high-methane-emitting beef cattle and sheep. Overall, this study highlights the importance of promoting alternative H2 consumption and reductant disposal pathways for synthesizing host-beneficial metabolites and reducing methane production in ruminants.

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy.

Methane (CH4) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH4. To address this limitation, we developed novel CH4 prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH4 production (g CH4/animal·d, ANIM-B models) and CH4 yield (g CH4/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin's concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH4 prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH4 emissions from sheep, providing valuable insights for future research and mitigation strategies.

Characterization of the Ruminal Microbiome of Water Buffaloes (Bubalus bubalis) Kept in Different Ecosystems in the Eastern Amazon.

Increasing the efficiency of rumen fermentation is one of the main ways to maximize the production of ruminants. It is therefore important to understand the ruminal microbiome, as well as environmental influences on that community. However, there are no studies that describe the ruminal microbiota in buffaloes in the Amazon. The objective of this study was to characterize the rumen microbiome of the water buffalo (Bubalus bubalis) in the eastern Amazon in the dry and rainy seasons in three grazing ecosystems: Baixo Amazonas (BA), Continente do Pará (CP), Ilha do Marajó (IM), and in a confinement system: Tomé-Açu (TA). Seventy-one crossbred male buffaloes (Murrah × Mediterranean) were used, aged between 24 and 36 months, with an average weight of 432 kg in the rainy season and 409 kg in the dry season, and fed on native or cultivated pastures. In the confinement system, the feed consisted of sorghum silage, soybean meal, wet sorghum premix, and commercial feed. Samples of the diet from each ecosystem were collected for bromatological analysis. The collections of ruminal content were carried out in slaughterhouses, with the rumen completely emptied and homogenized, the solid and liquid fractions separated, and the ruminal pH measured. DNA was extracted from the rumen samples, then sequenced using Restriction Enzyme Reduced Representation Sequencing. The taxonomic composition was largely similar between ecosystems. All 61 genera in the reference database were recognized, including members of the domains Bacteria and Archaea. The abundance of 23 bacterial genera differed significantly (p < 0.01) between the Tomé-Açu confinement and other ecosystems. Bacillus, Ruminococcus, and Bacteroides had lower abundance in samples from the Tomé-Açu system. Among the Archaea, the genus Methanomicrobium was less abundant in Tomé-Açu, while Methanosarcina was more abundant. There was a difference caused by all evaluated factors, but the diet (available or offered) was what most influenced the ruminal microbiota.

Rumen Lachnospiraceae isolate NK3A20 exhibits metabolic flexibility in response to substrate and coculture with a methanogen.

Hydrogen (H2) is the primary electron donor for methane formation in ruminants, but the H2-producing organisms involved are largely uncharacterized. This work integrated studies of microbial physiology and genomics to characterize rumen bacterial isolate NK3A20 of the family Lachnospiraceae. Isolate NK3A20 was the first recognized isolate of the NK3A20 group, which is among the ten most abundant bacterial genera in 16S rRNA gene surveys of rumen microbiota. NK3A20 produced acetate, butyrate, H2, and formate from glucose. The end product ratios varied when grown with different substrates and at different H2 partial pressures. NK3A20 produced butyrate as a major product using glucose or under high H2 partial pressures and switched to mainly acetate in the presence of galacturonic acid (an oxidized sugar) or in coculture with a methanogen. Growth with galacturonic acid was faster at elevated H2 concentrations, while elevated H2 slowed growth with glucose. Genome analyses revealed the presence of multiple hydrogenases including a membrane-bound Ech hydrogenase, an electron bifurcating butyryl-CoA dehydrogenase (Bcd-Etf), and an Rnf complex that may be involved in modulating the observed metabolic pathway changes, providing insight into H2 formation in the rumen. IMPORTANCE The genus-level NK3A20 group is one of the ten most abundant genera of rumen bacteria. Like most of the rumen bacteria that produce the hydrogen that is converted to methane in the rumen, it is understudied, without any previously characterized isolates. We investigated isolate NK3A20, a cultured member of this genus, and showed that it modulates hydrogen production in response to its growth substrates and the hydrogen concentration in its environment. Low-hydrogen concentrations stimulated hydrogen formation, while high concentrations inhibited its formation and shifted the fermentation to more reduced organic acid products. We found that growth on uronic acids, components of certain plant polymers, resulted in low hydrogen yields compared to glucose, which could aid in the selection of low-methane feeds. A better understanding of the major genera that produce hydrogen in the rumen is part of developing strategies to mitigate biogenic methane emitted by livestock agriculture.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host.

BACKGROUND: Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.

BACKGROUND: Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. RESULTS: Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. CONCLUSIONS: This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Patterns and determinants of the global herbivorous mycobiome.

Despite their role in host nutrition, the anaerobic gut fungal (AGF) component of the herbivorous gut microbiome remains poorly characterized. Here, to examine global patterns and determinants of AGF diversity, we generate and analyze an amplicon dataset from 661 fecal samples from 34 mammalian species, 9 families, and 6 continents. We identify 56 novel genera, greatly expanding AGF diversity beyond current estimates (31 genera and candidate genera). Community structure analysis indicates that host phylogenetic affiliation, not domestication status and biogeography, shapes the community rather than. Fungal-host associations are stronger and more specific in hindgut fermenters than in foregut fermenters. Transcriptomics-enabled phylogenomic and molecular clock analyses of 52 strains from 14 genera indicate that most genera with preferences for hindgut hosts evolved earlier (44-58 Mya) than those with preferences for foregut hosts (22-32 Mya). Our results greatly expand the documented scope of AGF diversity and provide an ecologically and evolutionary-grounded model to explain the observed patterns of AGF diversity in extant animal hosts.

Aristaeella hokkaidonensis gen. nov. sp. nov. and Aristaeella lactis sp. nov., two rumen bacterial species of a novel proposed family, Aristaeellaceae fam. nov.

Two strains of Gram-negative, anaerobic, rod-shaped bacteria, from an abundant but uncharacterized rumen bacterial group of the order 'Christensenellales', were phylogenetically and phenotypically characterized. These strains, designated R-7T and WTE2008T, shared 98.6-99.0 % sequence identity between their 16S rRNA gene sequences. R-7T and WTE2008T clustered together on a distinct branch from other Christensenellaceae strains and had <88.1 % sequence identity to the closest type-strain sequence from Luoshenia tenuis NSJ-44T. The genome sequences of R-7T and WTE2008T had 83.6 % average nucleotide identity to each other, and taxonomic assignment using the Genome Taxonomy Database indicates these are separate species within a novel family of the order 'Christensenellales'. Cells of R-7T and WTE2008T lacked any obvious appendages and their cell wall ultra-structures were characteristic of Gram-negative bacteria. The five most abundant cellular fatty acids of both strains were C16 : 0, C16 : 0 iso, C17 : 0 anteiso, C18 : 0 and C15 : 0 anteiso. The strains used a wide range of the 23 soluble carbon sources tested, and grew best on cellobiose, but not on sugar-alcohols. Xylan and pectin were fermented by both strains, but not cellulose. Acetate, hydrogen, ethanol and lactate were the major fermentation end products. R-7T produced considerably more hydrogen than WTE2008T, which produced more lactate. Based on these analyses, Aristaeellaceae fam. nov. and Aristaeella gen. nov., with type species Aristaeella hokkaidonensis sp. nov., are proposed. Strains R-7T (=DSM 112795T=JCM 34733T) and WTE2008T (=DSM 112788T=JCM 34734T) are the proposed type strains for Aristaeella hokkaidonensis sp. nov. and Aristaeella lactis sp. nov., respectively.

Genomic insights into the physiology of Quinella, an iconic uncultured rumen bacterium.

Quinella is a genus of iconic rumen bacteria first reported in 1913. There are no cultures of these bacteria, and information on their physiology is scarce and contradictory. Increased abundance of Quinella was previously found in the rumens of some sheep that emit low amounts of methane (CH4) relative to their feed intake, but whether Quinella contributes to low CH4 emissions is not known. Here, we concentrate Quinella cells from sheep rumen contents, extract and sequence DNA, and reconstruct Quinella genomes that are >90% complete with as little as 0.20% contamination. Bioinformatic analyses of the encoded proteins indicate that lactate and propionate formation are major fermentation pathways. The presence of a gene encoding a potential uptake hydrogenase suggests that Quinella might be able to use free hydrogen (H2). None of the inferred metabolic pathways is predicted to produce H2, a major precursor of CH4, which is consistent with the lower CH4 emissions from those sheep with high abundances of this bacterium.

Impact of breeding for reduced methane emissions in New Zealand sheep on maternal and health traits.

Enteric methane emissions from ruminants account for ∼35% of New Zealand's greenhouse gas emissions. This poses a significant threat to the pastoral sector. Breeding has been shown to successfully lower methane emissions, and genomic prediction for lowered methane emissions has been introduced at the national level. The long-term genetic impacts of including low methane in ruminant breeding programs, however, are unknown. The success of the New Zealand sheep industry is currently heavily reliant on the prolificacy, fecundity and survival of adult ewes. The objective of this study was to determine genetic and phenotypic correlations between adult maternal ewe traits (live weight, body condition score, number of lambs born, litter survival to weaning, pregnancy scanning and fleece weight), faecal and Nematodirus egg counts and measures of methane in respiration chambers. More than 9,000 records for methane from over 2,200 sheep measured in respiration chambers were collected over 10 years. Sheep were fed on a restricted diet calculated as approximately twice the maintenance. Methane measures were converted to absolute daily emissions of methane measured in g per day (CH4/day). Two measures of methane yield were recorded: the ratio of CH4 to dry matter intake (g CH4/kg DMI; CH4/DMI) and the ratio of CH4 to total gas emissions (CH4/(CH4 + CO2)). Ewes were maintained in the flocks for at least two parities. Non-methane trait data from over 8,000 female relatives were collated to estimate genetic correlations. Results suggest that breeding for low CH4/DMI is unlikely to negatively affect faecal egg counts, adult ewe fertility and litter survival traits, with no evidence for significant genetic correlations. Fleece weight was unfavourably (favourably) correlated with CH4/DMI (rg = -0.21 ± 0.09). Live weight (rg = 0.3 ± 0.1) and body condition score (rg = 0.2 ± 0.1) were positively correlated with methane yield. Comparing the two estimates of methane yield, CH4/DMI had lower heritability and repeatability. However, correlations of both measures with adult ewe traits were similar. This suggests that breeding is a suitable mitigation strategy for lowering methane yield, but wool, live weight and fat deposition traits may be affected over time and should be monitored.

Genetic parameters for residual feed intake, methane emissions, and body composition in New Zealand maternal sheep.

There is simultaneous interest in improving the feed efficiency of ruminant livestock and reducing methane (CH4) emissions. The relationship (genetic and phenotypic) between feed efficiency (characterized as residual feed intake: RFI) and greenhouse gases [methane (CH4) and carbon dioxide (CO2)] traits in New Zealand (NZ) maternal sheep has not previously been investigated, nor has their relationship with detailed estimates of body composition. To investigate these relationships in NZ maternal sheep, a feed intake facility was established at AgResearch Invermay, Mosgiel, NZ in 2015, comprising automated feeders that record individual feeding events. Individual measures of feed intake, feeding behavior (length and duration of eating events), and gas emissions (estimated using portable accumulation chambers) were generated on 986 growing maternal ewe lambs sourced from three pedigree recorded flocks registered in the Sheep Improvement Limited database (www.sil.co.nz). Additional data were generated from a subset of 591 animals for body composition (estimated using ultrasound and computed tomography scanning). The heritability estimates for RFI, CH4, and CH4/(CH4+CO2) were 0.42 ± 0.09, 0.32 ± 0.08, and 0.29 ± 0.06, respectively. The heritability estimates for the body composition traits were high for carcass lean and fat traits; for example, the heritability for visceral fat (adjusted for body weight) was 0.93 ± 0.19. The relationship between RFI and CH4 emissions was complex, and although less feed eaten will lead to a lowered absolute amount of CH4 emitted, there was a negative phenotypic and genetic correlation between RFI and CH4/(CH4+CO2) of -0.13 ± 0.03 and -0.41 ± 0.15, respectively. There were also genetic correlations, that were different from zero, between both RFI and CH4 traits with body composition including a negative correlation between the proportion of visceral fat in the body and RFI (-0.52 ± 0.16) and a positive correlation between the proportion of lean in the body and CH4 (0.54 ± 0.12). Together the results provide the first accurate estimates of the genetic correlations between RFI, CH4 emissions, and the body composition (lean and fat) in sheep. These correlations will need to be accounted for in genetic improvement programs.

Cross-reactivity of antibodies to different rumen methanogens demonstrated using immunomagnetic capture technology.

Methane is produced in the rumen of ruminant livestock by methanogens, accounting for approximately 14.5% of anthropogenic greenhouse gas emissions in terms of global warming potential. The rumen contains a diversity of methanogens species, and only a few of these have been cultured. Immunomagnetic capture technology (ICT) is a simple and effective method to capture and concentrate target organisms in samples containing complex microflora. We hypothesized that antibody-coated magnetic beads could be used to demonstrate antibody specificity and cross-reactivity to methanogens in rumen samples. Sheep polyclonal antibodies raised against four isolates of rumen dwelling methanogens, Methanobrevibacter ruminantium strain M1, Methanobrevibacter sp. AbM4, Methanobrevibacter sp. D5, and Methanobrevibacter sp. SM9 or an equal mix of all four isolates, were used to coat paramagnetic beads. ICT was used together with flow cytometry and qPCR to optimize key parameters: the ratio of antibody to beads, coupling time between antibody and paramagnetic beads to produce immunomagnetic beads (IMBs), and optimal incubation time for the capture of methanogen cells by IMBs. Under optimized conditions, IMBs bound strongly to their respective isolates and showed a degree of cross-reactivity with isolates of other Methanobrevibacter spp. in buffer and in rumen fluid, and with resident methanogens in rumen content samples. The evidence provided here indicates that this method can be used to study the interaction of antibodies with antigens of rumen methanogens, to understand antigen cross-reactivity and antibody binding efficiency for the evaluation of antigens used for the development of a broad-spectrum anti-methanogen vaccine for the abatement of methane production.

Evaluation of Feed Near-Infrared Reflectance Spectra as Predictors of Methane Emissions from Ruminants.

Feed chemical composition is associated with methane (CH4) formation in the rumen, and thus CH4 yields (Ym; CH4 emitted from per unit of dry matter intake) could be predicted using near-infrared reflectance spectroscopy (NIRS) of feeds fed to ruminants. Two databases of NIRS data were compiled from feeds used in experiments in which CH4 yields had been quantified in respiration chambers. Each record in the databases represented a batch of feed offered to a group of experimental animals and the mean CH4 yield for the group. A near-infrared reflectance spectrum was obtained from each feed, and these spectra were used to generate a predictive equation for Ym. The predictive model generated from brassica crops and pasture fed at a similar feeding level (n = 40 records) explained 53% of the variation in Ym and had a reasonably good agreement (concordance correlation coefficient of 0.77). The predictive ability of the NIRS calibration could be useful for screening purposes, particularly for predicting the potential Ym of multiple feeds or feed samples, rather than measuring Ym in animal experiments at high expenses. It is recommended that the databases for NIRS calibrations are expanded by collecting feed information from future experiments in which methane emissions are measured, using alternative algorithms and combining other techniques, such as terahertz time-domain spectroscopy.

Substituting ryegrass-based pasture with graded levels of forage rape in the diet of lambs decreases methane emissions and increases propionate, succinate, and primary alcohols in the rumen.

Feeding 100% forage rape to sheep consistently lowers methane emissions per unit of intake (CH4/DMI) compared to those fed 100% ryegrass pasture. However, forage rape is usually supplemented with other feeds, which might impact the mitigation potential provided by forage rape. The objective of this study was to determine the effect of substituting ryegrass with graded levels of forage rape in the diet of lambs on methane emissions and rumen fermentation characteristics. Seventy wether lambs (n = 14/treatment) were fed a ryegrass-based pasture substituted with 0%, 25%, 50%, 75%, and 100% of forage rape (Brassica napus; FR0, FR25, FR50, FR75, and FR100, respectively) on a dry matter basis. Methane emissions and dry matter intake were measured for 48 h in respiration chambers and a rumen fluid sample was collected. CH4/DMI decreased (P < 0.01) with increasing forage rape inclusion in the diet so that sheep fed FR100 and FR75 emitted 34% and 11% less, respectively, than those fed FR0. CH4/DMI differences for lambs fed FR25 and FR50 were much smaller (<6%) relative to FR0. The pH of rumen fluid decreased (P < 0.01) at higher levels of forage rape inclusion in the diet (FR75 and FR100) compared to low levels of inclusion (FR0, F25, and F50). The proportion of ruminal acetate was least in FR100 (30%) followed by FR75 (10%), FR50 (8%), and FR25 (4%) compared with FR0 (P < 0.001). The proportion of propionate plus succinate was greater for FR100 (+40%), FR75 (+28%), and FR50 (+29%) compared with FR0, with FR25 intermediate (P < 0.001). The methanol concentration, and ethanol and propanol proportions in rumen fluid were greater for FR100 compared with any other treatment (P < 0.001). In conclusion, CH4/DMI decreased at high levels of forage rape inclusion in the diet and especially feeding FR100 was associated with a pronounced shift in rumen fermentation profile, with a significant presence of succinate, ethanol, propanol, methanol, valerate, and caproate.

The methane yield (g methane/kg dry matter intake) was 34% lower in sheep fed 100% forage rape and 11% lower in sheep fed 75% forage rape compared to sheep fed 100% ryegrass-based pasture. Sheep fed 25% and 50% forage rape as part of their diet had similar methane yields to sheep fed 100% ryegrass pasture. Sheep fed 100% forage rape had a ruminal fermentation profile with a smaller proportion of acetate and greater proportions of fermentation products like propionate, succinate, and valerate. Acetate formation is associated with hydrogen gas formation, which in turn is converted to methane in the rumen. Propionate, succinate, and valerate are alternatives to acetate plus hydrogen production and so fermentation shifts to them result in less methane formation.

Mapping immunogenic epitopes of an adhesin-like protein from Methanobrevibacter ruminantium M1 and comparison of empirical data with in silico prediction methods.

In silico prediction of epitopes is a potentially time-saving alternative to experimental epitope identification but is often subject to misidentification of epitopes and may not be useful for proteins from archaeal microorganisms. In this study, we mapped B- and T-cell epitopes of a model antigen from the methanogen Methanobrevibacter ruminantium M1, the Big_1 domain (AdLP-D1, amino acids 19-198) of an adhesin-like protein. A series of 17 overlapping 20-mer peptides was selected to cover the Big_1 domain. Peptide-specific antibodies were produced in mice and measured by ELISA, while an in vitro splenocyte re-stimulation assay determined specific T-cell responses. Overall, five peptides of the 17 peptides were shown to be major immunogenic epitopes of AdLP-D1. These immunogenic regions were examined for their localization in a homology-based model of AdLP-D1. Validated epitopes were found in the outside region of the protein, with loop like secondary structures reflecting their flexibility. The empirical data were compared with epitope predictions made by programmes based on a range of algorithms. In general, the epitopes identified by in silico predictions were not comparable to those determined empirically.

Low-cost sample preservation methods for high-throughput processing of rumen microbiomes.

BACKGROUND: The use of rumen microbial community (RMC) profiles to predict methane emissions has driven interest in ruminal DNA preservation and extraction protocols that can be processed cheaply while also maintaining or improving DNA quality for RMC profiling. Our standard approach for preserving rumen samples, as defined in the Global Rumen Census (GRC), requires time-consuming pre-processing steps of freeze drying and grinding prior to international transportation and DNA extraction. This impedes researchers unable to access sufficient funding or infrastructure. To circumvent these pre-processing steps, we investigated three methods of preserving rumen samples for subsequent DNA extraction, based on existing lysis buffers Tris-NaCl-EDTA-SDS (TNx2) and guanidine hydrochloride (GHx2), or 100% ethanol. RESULTS: Rumen samples were collected via stomach intubation from 151 sheep at two time-points 2 weeks apart. Each sample was separated into four subsamples and preserved using the three preservation methods and the GRC method (n = 4 × 302). DNA was extracted and sequenced using Restriction Enzyme-Reduced Representation Sequencing to generate RMC profiles. Differences in DNA yield, quality and integrity, and sequencing metrics were observed across the methods (p < 0.0001). Ethanol exhibited poorer quality DNA (A260/A230 < 2) and more failed samples compared to the other methods. Samples preserved using the GRC method had smaller relative abundances in gram-negative genera Anaerovibrio, Bacteroides, Prevotella, Selenomonas, and Succiniclasticum, but larger relative abundances in the majority of 56 additional genera compared to TNx2 and GHx2. However, log10 relative abundances across all genera and time-points for TNx2 and GHx2 were on average consistent (R2 > 0.99) but slightly more variable compared to the GRC method. Relative abundances were moderately to highly correlated (0.68 ± 0.13) between methods for samples collected within a time-point, which was greater than the average correlation (0.17 ± 0.11) between time-points within a preservation method. CONCLUSIONS: The two modified lysis buffers solutions (TNx2 and GHx2) proposed in this study were shown to be viable alternatives to the GRC method for RMC profiling in sheep. Use of these preservative solutions reduces cost and improves throughput associated with processing and sequencing ruminal samples. This development could significantly advance implementation of RMC profiles as a tool for breeding ruminant livestock.

Hydrogen and formate production and utilisation in the rumen and the human colon.

Molecular hydrogen (H2) and formate (HCOO-) are metabolic end products of many primary fermenters in the mammalian gut. Both play a vital role in fermentation where they are electron sinks for individual microbes in an anaerobic environment that lacks external electron acceptors. If H2 and/or formate accumulate within the gut ecosystem, the ability of primary fermenters to regenerate electron carriers may be inhibited and microbial metabolism and growth disrupted. Consequently, H2- and/or formate-consuming microbes such as methanogens and homoacetogens play a key role in maintaining the metabolic efficiency of primary fermenters. There is increasing interest in identifying approaches to manipulate mammalian gut environments for the benefit of the host and the environment. As H2 and formate are important mediators of interspecies interactions, an understanding of their production and utilisation could be a significant entry point for the development of successful interventions. Ruminant methane mitigation approaches are discussed as a model to help understand the fate of H2 and formate in gut systems.

Electron flow: key to mitigating ruminant methanogenesis.

Disposal of electrons generated during the fermentation of ingested feed is a fundamental feature of anaerobic microbial gut ecosystems. Here, we focus on the well-studied rumen environment to highlight how electrons are transferred through anaerobic fermentation pathways and how manipulating this electron flow is important to reducing methane emissions from ruminants. Priorities for research that can accelerate understanding in this area are highlighted.