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Abstract 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.

Abstract 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.

Abstract 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.

Abstract 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.

Uncultured bacteria of the genus Quinella are found in the rumen of ruminant animals, especially in sheep that emit low amounts of methane. Here, Kumar et al. reconstruct genomic sequences from Quinella cells to provide insights into their metabolic capabilities, including lactate and propionate formation as major fermentation pathways and an apparent lack of production of H2, a major precursor of methane.

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.

Abstract 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.

Abstract 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 0.99) 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.

Abstract 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.

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.

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.

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.

Abstract Anthelmintic treatment of adult ewes is widely practiced to remove parasite burdens in the expectation of increased ruminant productivity. However, the broad activity spectra of many anthelmintic compounds raises the possibility of impacts on the rumen microbiota. To investigate this, 300 grazing ewes were allocated to treatment groups that included a 100-day controlled release capsule (CRC) containing albendazole and abamectin, a long-acting moxidectin injection (LAI), and a non-treated control group (CON). Rumen bacterial, archaeal and protozoal communities at day 0 were analysed to identify 36 sheep per treatment with similar starting compositions. Microbiota profiles, including those for the rumen fungi, were then generated for the selected sheep at days 0, 35 and 77. The CRC treatment significantly impacted the archaeal community, and was associated with increased relative abundances of Methanobrevibacter ruminantium, Methanosphaera sp. ISO3-F5, and Methanomassiliicoccaceae Group 12 sp. ISO4-H5 compared to the control group. In contrast, the LAI treatment increased the relative abundances of members of the Veillonellaceae and resulted in minor changes to the bacterial and fungal communities by day 77. Overall, the anthelmintic treatments resulted in few, but highly significant, changes to the rumen microbiota composition.

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.

Summary: This protocol describes the application of breath testing and ex vivo fermentations to study the association between breath methane and the composition and functionality of the gut microbiome. The protocol provides a useful systems biology approach for studying the gut microbiome in humans, which combines standardized methods in human breath testing and fecal sampling. The model described is accessible and easy to repeat, but its relative simplicity means that it can deviate from human physiological conditions.

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p

The taxonomy and associated nomenclature of many taxa of rumen bacteria are poorly defined within databases of 16S rRNA genes. This lack of resolution results in inadequate definition of microbial community structures, with large parts of the community designated as incertae sedis, unclassified, or uncultured within families, orders, or even classes. We have begun resolving these poorly-defined groups of rumen bacteria, based on our desire to name these for use in microbial community profiling. We used the previously-reported global rumen census (GRC) dataset consisting of >4.5 million partial bacterial 16S rRNA gene sequences amplified from 684 rumen samples and representing a wide range of animal hosts and diets. Representative sequences from the 8,985 largest operational units (groups of sequence sharing >97% sequence similarity, and covering 97.8% of all sequences in the GRC dataset) were used to identify 241 pre-defined clusters (mainly at genus or family level) of abundant rumen bacteria in the ARB SILVA 119 framework. A total of 99 of these clusters (containing 63.8% of all GRC sequences) had no unique or had inadequate taxonomic identifiers, and each was given a unique nomenclature. We assessed this improved framework by comparing taxonomic assignments of bacterial 16S rRNA gene sequence data in the GRC dataset with those made using the original SILVA 119 framework, and three other frameworks. The two SILVA frameworks performed best at assigning sequences to genus-level taxa. The SILVA 119 framework allowed 55.4% of the sequence data to be assigned to 751 uniquely identifiable genus-level groups. The improved framework increased this to 87.1% of all sequences being assigned to one of 871 uniquely identifiable genus-level groups. The new designations were included in the SILVA 123 release (https://www.arb-silva.de/documentation/release-123/) and will be perpetuated in future releases.

Background Many bacteria are facultative anaerobes, and can proliferate in both anoxic and oxic environments. Under anaerobic conditions, fermentation is the primary means of energy generation in contrast to respiration. Furthermore, the rates and spectra of spontaneous mutations that arise during anaerobic growth differ to those under aerobic growth. A long-term selection experiment was undertaken to investigate the genetic changes that underpin how the facultative anaerobe, Escherichia coli, adapts to anaerobic environments. Methods Twenty-one populations of E. coli REL4536, an aerobically evolved 10,000th generation descendent of the E. coli B strain, REL606, were established from a clonal ancestral culture. These were serially sub-cultured for 2,000 generations in a defined minimal glucose medium in strict aerobic and strict anaerobic environments, as well as in a treatment that fluctuated between the two environments. The competitive fitness of the evolving lineages was assessed at approximately 0, 1,000 and 2,000 generations, in both the environment of selection and the alternative environment. Whole genome re-sequencing was performed on random colonies from all lineages after 2,000-generations. Mutations were identified relative to the ancestral genome, and based on the extent of parallelism, traits that were likely to have contributed towards adaptation were inferred. Results There were increases in fitness relative to the ancestor among anaerobically evolved lineages when tested in the anaerobic environment, but no increases were found in the aerobic environment. For lineages that had evolved under the fluctuating regime, relative fitness increased significantly in the anaerobic environment, but did not increase in the aerobic environment. The aerobically-evolved lineages did not increase in fitness when tested in either the aerobic or anaerobic environments. The strictly anaerobic lineages adapted more rapidly to the anaerobic environment than did the fluctuating lineages. Two main strategies appeared to predominate during adaptation to the anaerobic environment: modification of energy generation pathways, and inactivation of non-essential functions. Fermentation pathways appeared to alter through selection for mutations in genes such as nadR, adhE, dcuS/R, and pflB. Mutations were frequently identified in genes for presumably dispensable functions such as toxin-antitoxin systems, prophages, virulence and amino acid transport. Adaptation of the fluctuating lineages to the anaerobic environments involved mutations affecting traits similar to those observed in the anaerobically evolved lineages. Discussion There appeared to be strong selective pressure for activities that conferred cell yield advantages during anaerobic growth, which include restoring activities that had previously been inactivated under long-term continuous aerobic evolution of the ancestor.

The complex microbiota that resides within the rumen is responsible for the break-down of plant fibre. The bacteria that attach to ingested plant matter within the rumen are thought to be responsible for initial fibre degradation. Most studies examining the ecology of this important microbiome only offer a 'snapshot' in time. We monitored the diversity of rumen bacteria in four New Zealand dairy cows, grazing a rye-grass and clover pasture over five consecutive seasons, using high throughput pyrosequencing of bacterial 16S rRNA genes. We chose to focus on the digesta-adherent bacterial community to learn more about the stability of this community over time. 16S rRNA gene sequencing showed a high level of bacterial diversity, totalling 1539 operational taxonomic units (OTUs, grouped at 96% sequence similarity) across all samples, and ranging from 653 to 926 OTUs per individual sample. The nutritive composition of the pasture changed with the seasons as did the production phase of the animals. Sequence analysis showed that, overall, the bacterial communities were broadly similar between the individual animals. The adherent bacterial community was strongly dominated by members of Firmicutes (82.1%), followed by Bacteroidetes (11.8%). This community differed between the seasons, returning to close to that observed in the same season one year later. These seasonal differences were only small, but were statistically significant (p < 0.001), and were probably due to the seasonal differences in the diet. These results demonstrate a general invariability of the ruminal bacterial community structure in these grazing dairy cattle.

Methane is produced in the rumen of ruminant livestock by methanogens and is a major contributor to agricultural greenhouse gases. Vaccination against ruminal methanogens could reduce methane emissions by inducing antibodies in saliva which enter the rumen and impair ability of methanogens to produce methane. Presently, it is not known if vaccination can induce sufficient amounts of antibody in the saliva to target methanogen populations in the rumen and little is known about how long antibody in the rumen remains active. In the current study, sheep were vaccinated twice at a 3-week interval with a model methanogen antigen, recombinant glycosyl transferase protein (rGT2) formulated with one of four adjuvants: saponin, Montanide ISA61, a chitosan thermogel, or a lipid nanoparticle/cationic liposome adjuvant (n = 6/formulation). A control group of sheep (n = 6) was not vaccinated. The highest antigen-specific IgA and IgG responses in both saliva and serum were observed with Montanide ISA61, which promoted levels of salivary antibodies that were five-fold higher than the second most potent adjuvant, saponin. A rGT2-specific IgG standard was used to determine the level of rGT2-specific IgG in serum and saliva. Vaccination with GT2/Montanide ISA61 produced a peak antibody concentration of 7 × 1016 molecules of antigen-specific IgG per litre of saliva, and it was estimated that in the rumen there would be more than 104 molecules of antigen-specific IgG for each methanogen cell. Both IgG and IgA in saliva were shown to be relatively stable in the rumen. Salivary antibody exposed for 1-2 hours to an in vitro simulated rumen environment retained approximately 50% of antigen-binding activity. Collectively, the results from measuring antibody levels and stablility suggest a vaccination-based mitigation strategy for livestock generated methane is in theory feasible.

The objectives of this study were to examine long-term effects of feeding forage rape (Brassica napus L.) on methane yields (g methane per kg of feed dry matter intake), and to propose mechanisms that may be responsible for lower emissions from lambs fed forage rape compared to perennial ryegrass (Lolium perenne L.). The lambs were fed fresh winter forage rape or ryegrass as their sole diet for 15 weeks. Methane yields were measured using open circuit respiration chambers, and were 22-30% smaller from forage rape than from ryegrass (averages of 13.6 g versus 19.5 g after 7 weeks, and 17.8 g versus 22.9 g after 15 weeks). The difference therefore persisted consistently for at least 3 months. The smaller methane yields from forage rape were not related to nitrate or sulfate in the feed, which might act as alternative electron acceptors, or to the levels of the potential inhibitors glucosinolates and S-methyl L-cysteine sulfoxide. Ruminal microbial communities in forage rape-fed lambs were different from those in ryegrass-fed lambs, with greater proportions of potentially propionate-forming bacteria, and were consistent with less hydrogen and hence less methane being produced during fermentation. The molar proportions of ruminal acetate were smaller and those of propionate were greater in forage rape-fed lambs, consistent with the larger propionate-forming populations and less hydrogen production. Forage rape contained more readily fermentable carbohydrates and less structural carbohydrates than ryegrass, and was more rapidly degraded in the rumen, which might favour this fermentation profile. The ruminal pH was lower in forage rape-fed lambs, which might inhibit methanogenic activity, shifting the rumen fermentation to more propionate and less hydrogen and methane. The significance of these two mechanisms remains to be investigated. The results suggest that forage rape is a potential methane mitigation tool in pastoral-based sheep production systems.

Methane is formed by methanogenic archaea in the rumen as one of the end products of feed fermentation in the ruminant digestive tract. To develop strategies to mitigate anthropogenic methane emissions due to ruminant farming, and to understand rumen microbial differences in animal feed conversion efficiency, it is essential that methanogens can be identified and taxonomically classified with high accuracy. Currently available taxonomic frameworks offer only limited resolution beyond the genus level for taxonomic assignments of sequence data stemming from high throughput sequencing technologies. Therefore, we have developed a QIIME-compatible database (DB) designed for species-level taxonomic assignment of 16S rRNA gene amplicon data targeting methanogenic archaea from the rumen, and from animal and human intestinal tracts. Called RIM-DB (Rumen and Intestinal Methanogen-DB), it contains a set of 2,379 almost full-length chimera-checked 16S rRNA gene sequences, including 20 previously unpublished sequences from isolates from three different orders. The taxonomy encompasses the recently-proposed seventh order of methanogens, the Methanomassiliicoccales, and allows differentiation between defined groups within this order. Sequence reads from rumen contents from a range of ruminant-diet combinations were taxonomically assigned using RIM-DB, Greengenes and SILVA. This comparison clearly showed that taxonomic assignments with RIM-DB resulted in the most detailed assignment, and only RIM-DB taxonomic assignments allowed methanogens to be distinguished taxonomically at the species level. RIM-DB complements the use of comprehensive databases such as Greengenes and SILVA for community structure analysis of methanogens from the rumen and other intestinal environments, and allows identification of target species for methane mitigation strategies.

The potent greenhouse gas methane (CH4) is produced in the rumens of ruminant animals from hydrogen produced during microbial degradation of ingested feed. The natural animal-to-animal variation in the amount of CH4 emitted and the heritability of this trait offer a means for reducing CH4 emissions by selecting low-CH4 emitting animals for breeding. We demonstrate that differences in rumen microbial community structure are linked to high and low CH4 emissions in sheep. Bacterial community structures in 236 rumen samples from 118 high- and low-CH4 emitting sheep formed gradual transitions between three ruminotypes. Two of these (Q and S) were linked to significantly lower CH4 yields (14.4 and 13.6 g CH4/kg dry matter intake [DMI], respectively) than the third type (H; 15.9 g CH4/kg DMI; p

The internal transcribed spacer (ITS) is a popular barcode marker for fungi and in particular the ITS1 has been widely used for the anaerobic fungi (phylum Neocallimastigomycota). A good number of validated reference sequences of isolates as well as a large number of environmental sequences are available in public databases. Its highly variable nature predisposes the ITS1 for low level phylogenetics; however, it complicates the establishment of reproducible alignments and the reconstruction of stable phylogenetic trees at higher taxonomic levels (genus and above). Here, we overcame these problems by proposing a common core secondary structure of the ITS1 of the anaerobic fungi employing a Hidden Markov Model-based ITS1 sequence annotation and a helix-wise folding approach. We integrated the additional structural information into phylogenetic analyses and present for the first time an automated sequence-structure-based taxonomy of the ITS1 of the anaerobic fungi. The methodology developed is transferable to the ITS1 of other fungal groups, and the robust taxonomy will facilitate and improve high-throughput anaerobic fungal community structure analysis of samples from various environments.

Molecular microbial ecology techniques are widely used to study the composition of the rumen microbiota and to increase understanding of the roles they play. Therefore, sampling and DNA extraction methods that result in adequate yields of microbial DNA that also accurately represents the microbial community are crucial. Fifteen different methods were used to extract DNA from cow and sheep rumen samples. The DNA yield and quality, and its suitability for downstream PCR amplifications varied considerably, depending on the DNA extraction method used. DNA extracts from nine extraction methods that passed these first quality criteria were evaluated further by quantitative PCR enumeration of microbial marker loci. Absolute microbial numbers, determined on the same rumen samples, differed by more than 100-fold, depending on the DNA extraction method used. The apparent compositions of the archaeal, bacterial, ciliate protozoal, and fungal communities in identical rumen samples were assessed using 454 Titanium pyrosequencing. Significant differences in microbial community composition were observed between extraction methods, for example in the relative abundances of members of the phyla Bacteroidetes and Firmicutes. Microbial communities in parallel samples collected from cows by oral stomach-tubing or through a rumen fistula, and in liquid and solid rumen digesta fractions, were compared using one of the DNA extraction methods. Community representations were generally similar, regardless of the rumen sampling technique used, but significant differences in the abundances of some microbial taxa such as the Clostridiales and the Methanobrevibacter ruminantium clade were observed. The apparent microbial community composition differed between rumen sample fractions, and Prevotellaceae were most abundant in the liquid fraction. DNA extraction methods that involved phenol-chloroform extraction and mechanical lysis steps tended to be more comparable. However, comparison of data from studies in which different sampling techniques, different rumen sample fractions or different DNA extraction methods were used should be avoided.

Ruminants rely on a complex rumen microbial community to convert dietary plant material to energy-yielding products. Here we developed a method to simultaneously analyze the community's bacterial and archaeal 16S rRNA genes, ciliate 18S rRNA genes and anaerobic fungal internal transcribed spacer 1 genes using 12 DNA samples derived from 11 different rumen samples from three host species (Ovis aries, Bos taurus, Cervus elephas) and multiplex 454 Titanium pyrosequencing. We show that the mixing ratio of the group-specific DNA templates before emulsion PCR is crucial to compensate for differences in amplicon length. This method, in contrast to using a non-specific universal primer pair, avoids sequencing non-targeted DNA, such as plant- or endophyte-derived rRNA genes, and allows increased or decreased levels of community structure resolution for each microbial group as needed. Communities analyzed with different primers always grouped by sample origin rather than by the primers used. However, primer choice had a greater impact on apparent archaeal community structure than on bacterial community structure, and biases for certain methanogen groups were detected. Co-occurrence analysis of microbial taxa from all three domains of life suggested strong within- and between-domain correlations between different groups of microorganisms within the rumen. The approach used to simultaneously characterize bacterial, archaeal and eukaryotic components of a microbiota should be applicable to other communities occupying diverse habitats.

Anaerobic fungi are key players in the breakdown of fibrous plant material in the rumen, but not much is known about the composition and stability of fungal communities in ruminants. We analyzed anaerobic fungi in 53 rumen samples from farmed sheep (4 different flocks), cattle, and deer feeding on a variety of diets. Denaturing gradient gel electrophoresis fingerprinting of the internal transcribed spacer 1 (ITS1) region of the rrn operon revealed a high diversity of anaerobic fungal phylotypes across all samples. Clone libraries of the ITS1 region were constructed from DNA from 11 rumen samples that had distinctly different fungal communities. A total of 417 new sequences were generated to expand the number and diversity of ITS1 sequences available. Major phylogenetic groups of anaerobic fungi in New Zealand ruminants belonged to the genera Piromyces, Neocallimastix, Caecomyces and Orpinomyces. In addition, sequences forming four novel clades were obtained, which may represent so far undetected genera or species of anaerobic fungi. We propose a revised phylogeny and pragmatic taxonomy for anaerobic fungi, which was tested and proved suitable for analysis of datasets stemming from high-throughput next-generation sequencing methods. Comparing our revised taxonomy to the taxonomic assignment of sequences deposited in the GenBank database, we believe that >29% of ITS1 sequences derived from anaerobic fungal isolates or clones are misnamed at the genus level.

BackgroundMethane (CH(4)) is a potent greenhouse gas (GHG), having a global warming potential 21 times that of carbon dioxide (CO(2)). Methane emissions from agriculture represent around 40% of the emissions produced by human-related activities, the single largest source being enteric fermentation, mainly in ruminant livestock. Technologies to reduce these emissions are lacking. Ruminant methane is formed by the action of methanogenic archaea typified by Methanobrevibacter ruminantium, which is present in ruminants fed a wide variety of diets worldwide. To gain more insight into the lifestyle of a rumen methanogen, and to identify genes and proteins that can be targeted to reduce methane production, we have sequenced the 2.93 Mb genome of M. ruminantium M1, the first rumen methanogen genome to be completed.Methodology/principal findingsThe M1 genome was sequenced, annotated and subjected to comparative genomic and metabolic pathway analyses. Conserved and methanogen-specific gene sets suitable as targets for vaccine development or chemogenomic-based inhibition of rumen methanogens were identified. The feasibility of using a synthetic peptide-directed vaccinology approach to target epitopes of methanogen surface proteins was demonstrated. A prophage genome was described and its lytic enzyme, endoisopeptidase PeiR, was shown to lyse M1 cells in pure culture. A predicted stimulation of M1 growth by alcohols was demonstrated and microarray analyses indicated up-regulation of methanogenesis genes during co-culture with a hydrogen (H(2)) producing rumen bacterium. We also report the discovery of non-ribosomal peptide synthetases in M. ruminantium M1, the first reported in archaeal species.Conclusions/significanceThe M1 genome sequence provides new insights into the lifestyle and cellular processes of this important rumen methanogen. It also defines vaccine and chemogenomic targets for broad inhibition of rumen methanogens and represents a significant contribution to worldwide efforts to mitigate ruminant methane emissions and reduce production of anthropogenic greenhouse gases.