Impact and legacy of the highly cited paper by Blaxter and Clapperton (1965) 'Prediction of the amount of methane produced by ruminants [Br J Nutr 19, 511-522]'.

The paper by K. L. Blaxter and J. L. Clapperton (1965) 'Prediction of the amount of methane produced by ruminants. Br J Nutr 19, 511-522' has been cited 656 times according to Web of Science and continues to be cited with increasing frequency to the present day. The analysis described in the paper, or meta-analysis as it would be known now, is of methane production from cattle and sheep based on forty-eight trials using closed-circuit respiration chambers, all carried out at the Hannah Research Institute, Ayr, UK, between 1955 and 1965. Methane emissions per unit of diet fed were shown to vary depending on diet, level of feeding and individual animal. As such, previous notions that methane emissions were essentially proportional to energy intake were set aside. The main reasons for the paper's continuing citation are the set of equations that can be used to predict methane emissions from ruminants when the technically demanding respiration chambers are unavailable, and that it was the first definitive study to describe the complexities of methane emissions with respect to animals and diets. The paper thus provided abundant insights of the relations between ruminant methane emissions and nutritional biology, and rumen microbiology, in particular, that have informed countless research projects in the intervening half-century. Given the importance of methane as a greenhouse gas in the climate change scenario, these insights are at least as relevant today as they were in 1965.

The rumen microbiome: balancing food security and environmental impacts.

Ruminants produce edible products and contribute to food security. They house a complex rumen microbial community that enables the host to digest their plant feed through microbial-mediated fermentation. However, the rumen microbiome is also responsible for the production of one of the most potent greenhouse gases, methane, and contributes about 18% of its total anthropogenic emissions. Conventional methods to lower methane production by ruminants have proved successful, but to a limited and often temporary extent. An increased understanding of the host-microbiome interactions has led to the development of new mitigation strategies. In this Review we describe the composition, ecology and metabolism of the rumen microbiome, and the impact on host physiology and the environment. We also discuss the most pertinent methane mitigation strategies that emerged to balance food security and environmental impacts.

Metagenomic analysis of the cow, sheep, reindeer and red deer rumen.

The rumen microbiota comprises a community of microorganisms which specialise in the degradation of complex carbohydrates from plant-based feed. These microbes play a highly important role in ruminant nutrition and could also act as sources of industrially useful enzymes. In this study, we performed a metagenomic analysis of samples taken from the ruminal contents of cow (Bos Taurus), sheep (Ovis aries), reindeer (Rangifer tarandus) and red deer (Cervus elaphus). We constructed 391 metagenome-assembled genomes originating from 16 microbial phyla. We compared our genomes to other publically available microbial genomes and found that they contained 279 novel species. We also found significant differences between the microbiota of different ruminant species in terms of the abundance of microbial taxonomies, carbohydrate-active enzyme genes and KEGG orthologs. We present a dataset of rumen-derived genomes which in combination with other publicly-available rumen genomes can be used as a reference dataset in future metagenomic studies.

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

A network analysis including relative abundances of all ruminal microbial genera (archaea, bacteria, fungi, and protists) and their genes was performed to improve our understanding of how the interactions within the ruminal microbiome affects methane emissions (CH4). Metagenomics and CH4 data were available from 63 bovines of a two-breed rotational cross, offered two basal diets. Co-abundance network analysis revealed 10 clusters of functional niches. The most abundant hydrogenotrophic Methanobacteriales with key microbial genes involved in methanogenesis occupied a different functional niche (i.e., "methanogenesis" cluster) than methylotrophic Methanomassiliicoccales (Candidatus Methanomethylophylus) and acetogens (Blautia). Fungi and protists clustered together and other plant fiber degraders like Fibrobacter occupied a seperate cluster. A Partial Least Squares analysis approach to predict CH4 variation in each cluster showed the methanogenesis cluster had the best prediction ability (57.3%). However, the most important explanatory variables in this cluster were genes involved in complex carbohydrate degradation, metabolism of sugars and amino acids and Candidatus Azobacteroides carrying nitrogen fixation genes, but not methanogenic archaea and their genes. The cluster containing Fibrobacter, isolated from other microorganisms, was positively associated with CH4 and explained 49.8% of its variability, showing fermentative advantages compared to other bacteria and fungi in providing substrates (e.g., formate) for methanogenesis. In other clusters, genes with enhancing effect on CH4 were related to lactate and butyrate (Butyrivibrio and Pseudobutyrivibrio) production and simple amino acids metabolism. In comparison, ruminal genes negatively related to CH4 were involved in carbohydrate degradation via lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low- and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH4, which will benefit the development of efficient CH4 mitigation strategies.

Correction to: The rumen microbiome as a reservoir of antimicrobial resistance and pathogenicity genes is directly affected by diet in beef cattle.

Following publication of the original article [1], the authors reported an error in the Additional file 1.

A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions.

A 1000-cow study across four European countries was undertaken to understand to what extent ruminant microbiomes can be controlled by the host animal and to identify characteristics of the host rumen microbiome axis that determine productivity and methane emissions. A core rumen microbiome, phylogenetically linked and with a preserved hierarchical structure, was identified. A 39-member subset of the core formed hubs in co-occurrence networks linking microbiome structure to host genetics and phenotype (methane emissions, rumen and blood metabolites, and milk production efficiency). These phenotypes can be predicted from the core microbiome using machine learning algorithms. The heritable core microbes, therefore, present primary targets for rumen manipulation toward sustainable and environmentally friendly agriculture.

Genoprotective Effects of Essential Oil Compounds Against Oxidative and Methylated DNA Damage in Human Colon Cancer Cells.

Essential oils (EO) are widely used in foods as flavoring and preservative agents. Many of the biological activities of EO have been attributed to major essential oil compounds (EOC) but their direct interaction with colonic epithelial cells and their genotoxic and genoprotective effects are not well established. In this study, the cytotoxicity and genotoxicity of EOC including nerolidol, thymol, geraniol, methylisoeugenol, eugenol, linalool, and a commercial blend (Agolin) were determined. Furthermore, the genoprotective effects of EOC against oxidative and methylating damage were assessed using the comet assay in HT-29 colorectal adenocarcinoma cells. The majority of EOC were cytotoxic to HT-29 cells at or above 250 ppm after 24 hr exposure. At noncytotoxic doses, none of the EOC was genotoxic in the comet assay. Genoprotection against oxidative DNA damage was observed for nerolidol (at 62.5 ppm), thymol (at 12.5 ppm), geraniol, and methylisoeugenol (both at 125 ppm), as well as linalool and Agolin (both at 250 ppm). Thymol was the most protective compound against oxidative DNA damage and geraniol (at 125 ppm) also protected cells against methylating DNA damage. This study highlights the potential of EOC such as thymol to protect the colonic epithelium against oxidative DNA damage and geraniol against methylating DNA damage. Further in vivo studies are needed to confirm these findings for safety and efficacy to exploit their potential pharmaceutical or nutraceutical uses for colonic health.

Evaluation of reticuloruminal pH measurements from individual cattle: Sampling strategies for the assessment of herd status.

The application of pH observations to clinical practice in dairy cattle is based on criteria derived primarily from single time-point observations more than 20 years ago. The aims of this study were to evaluate these criteria using data collected using continuous recording methods; to make recommendations that might improve their interpretation; and to determine the relationship between the number of devices deployed in a herd and the accuracy of the resulting estimate of the herd-mean reticuloruminal pH. The study made use of 815,475 observations of reticuloruminal pH values obtained from 75 cattle in three herds (one beef and two twice-daily milking herds) to assess sampling strategies for the diagnosis of sub-acute rumen acidosis (SARA), and to evaluate the ability of different numbers of bolus devices to accurately estimate the true herd-mean reticuloruminal pH value at any time. The traditional criteria for SARA provide low diagnostic utility, the probability of detection of animals with pH values below specified thresholds being affected by a strong effect of time of day and herd. The analysis suggests that regardless of time of feeding, sampling should be carried out in the late afternoon or evening to obtain a reasonable probability of detection of animals with pH values below the threshold level. The among-cow variation varied strongly between herds, but for a typical herd, if using reticuloruminal pH boluses to detect a predisposition to fermentation disorders while feeding a diet that is high in rapidly fermentable carbohydrates, it is recommended to use a minimum of nine boluses.

Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows.

The ruminal microbiome, comprising large numbers of bacteria, ciliate protozoa, archaea and fungi, responds to diet and dietary additives in a complex way. The aim of this study was to investigate the benefits of increasing the depth of the community analysis in describing and explaining responses to dietary changes. Quantitative PCR, ssu rRNA amplicon based taxa composition, diversity and co-occurrence network analyses were applied to ruminal digesta samples obtained from four multiparous Nordic Red dairy cows fitted with rumen cannulae. The cows received diets with forage:concentrate ratio either 35:65 (diet H) or 65:35 (L), supplemented or not with sunflower oil (SO) (0 or 50 g/kg diet dry matter), supplied in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments and four 35-day periods. Digesta samples were collected on days 22 and 24 and combined. QPCR provided a broad picture in which a large fall in the abundance of fungi was seen with SO in the H but not the L diet. Amplicon sequencing showed higher community diversity indices in L as compared to H diets and revealed diet specific taxa abundance changes, highlighting large differences in protozoal and fungal composition. Methanobrevibacter ruminantium and Mbb. gottschalkii dominated archaeal communities, and their abundance correlated negatively with each other. Co-occurrence network analysis provided evidence that no microbial domain played a more central role in network formation, that some minor-abundance taxa were at nodes of highest centrality, and that microbial interactions were diet specific. Networks added new dimensions to our understanding of the diet effect on rumen microbial community interactions.

A Review of Bioinformatics Tools for Bio-Prospecting from Metagenomic Sequence Data.

The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such "bioprospecting" requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes.

The ruminal microbiome associated with methane emissions from ruminant livestock.

Methane emissions from ruminant livestock contribute significantly to the large environmental footprint of agriculture. The rumen is the principal source of methane, and certain features of the microbiome are associated with low/high methane phenotypes. Despite their primary role in methanogenesis, the abundance of archaea has only a weak correlation with methane emissions from individual animals. The composition of the archaeal community appears to have a stronger effect, with animals harbouring the Methanobrevibacter gottschalkii clade tending to be associated with greater methane emissions. Ciliate protozoa produce abundant H2, the main substrate for methanogenesis in the rumen, and their removal (defaunation) results in an average 11% lower methane emissions in vivo, but the results are not consistent. Different protozoal genera seem to result in greater methane emissions, though community types (A, AB, B and O) did not differ. Within the bacteria, three different 'ruminotypes' have been identified, two of which predispose animals to have lower methane emissions. The two low-methane ruminotypes are generally characterized by less abundant H2-producing bacteria. A lower abundance of Proteobacteria and differences in certain Bacteroidetes and anaerobic fungi seem to be associated with high methane emissions. Rumen anaerobic fungi produce abundant H2 and formate, and their abundance generally corresponds to the level of methane emissions. Thus, microbiome analysis is consistent with known pathways for H2 production and methanogenesis, but not yet in a predictive manner. The production and utilisation of formate by the ruminal microbiota is poorly understood and may be a source of variability between animals.

The rumen microbial metaproteome as revealed by SDS-PAGE.

BACKGROUND: Ruminal digestion is carried out by large numbers of bacteria, archaea, protozoa and fungi. Understanding the microbiota is important because ruminal fermentation dictates the efficiency of feed utilisation by the animal and is also responsible for major emissions of the greenhouse gas, methane. Recent metagenomic and metatranscriptomic studies have helped to elucidate many features of the composition and activity of the microbiota. The metaproteome provides complementary information to these other -omics technologies. The aim of this study was to explore the metaproteome of bovine and ovine ruminal digesta using 2D SDS-PAGE. RESULTS: Digesta samples were taken via ruminal fistulae and by gastric intubation, or at slaughter, and stored in glycerol at -80 °C. A protein extraction protocol was developed to maximise yield and representativeness of the protein content. The proteome of ruminal digesta taken from dairy cows fed a high concentrate diet was dominated by a few very highly expressed proteins, which were identified by LC-MS/MS to be structural proteins, such as actin and α- and ß-tubulins, derived from ciliate protozoa. Removal of protozoa from digesta before extraction of proteins revealed the prokaryotic metaproteome, which was dominated by enzymes involved in glycolysis, such as glyceraldehyde-3-phosphate dehydrogenase, phosphoenolpyruvate carboxykinase, phosphoglycerate kinase and triosephosphate isomerase. The enzymes were predominantly from the Firmicutes and Bacteroidetes phyla. Enzymes from methanogenic archaea were also abundant, consistent with the importance of methane formation in the rumen. Gels from samples from dairy cows fed a high proportion of grass silage were consistently obscured by co-staining of humic compounds. Samples from beef cattle and fattening lambs receiving a predominantly concentrate diet produced clearer gels, but the pattern of spots was inconsistent between samples, making comparisons difficult. CONCLUSION: This work demonstrated for the first time that 2D-PAGE reveals key structural proteins and enzymes in the rumen microbial community, despite its high complexity, and that taxonomic information can be deduced from the analysis. However, technical issues associated with feed material contamination, which affects the reproducibility of electrophoresis of different samples, limits its value.

Simple and Versatile Turbidimetric Monitoring of Bacterial Growth in Liquid Cultures Using a Customized 3D Printed Culture Tube Holder and a Miniaturized Spectrophotometer: Application to Facultative and Strictly Anaerobic Bacteria.

Here we introduce a novel strategy for turbidimetric monitoring of bacterial growth in liquid culture. The instrumentation comprises a light source, a customized 3D printed culture tube holder and a miniaturized spectrophotometer, connected through optical cables. Due to its small footprint and the possibility to operate with external light, bacterial growth was directly monitored from culture tubes in a simple and versatile fashion. This new portable measurement technique was used to monitor the growth of facultative (Escherichia coli ATCC/25922, and Staphylococcus aureus ATCC/29213) and strictly (Butyrivibrio fibrisolvens JW11, Butyrivibrio proteoclasticus P18, and Propionibacterium acnes DSMZ 1897) anaerobic bacteria. For E. coli and S. aureus, the growth rates calculated from normalized optical density values were compared with those ones obtained using a benchtop spectrophotometer without significant differences (P = 0.256). For the strictly anaerobic species, a high precision (relative standard deviation < 3.5%) was observed between replicates up to 48 h. Regarding its potential for customization, this manifold could accommodate further developments for customized turbidimetric monitoring, such as the use of light-emitting diodes as a light source or flow cells.

Metabolism of α-linolenic acid during incubations with strained bovine rumen contents: products and mechanisms.

Description of α-linolenic acid (cis-9,cis-12,cis-15-18 : 3, ALA) metabolism in the rumen is incomplete. Ruminal digesta samples were incubated with ALA and buffer containing water or deuterium oxide to investigate the products and mechanisms of ALA biohydrogenation. Geometric Δ9,11,15-18 : 3 isomers were the main intermediates formed from ALA. An increase in the n+1 isotopomers of Δ9,11,15-18 : 3 was due to 2H labelling at C-13. Isomers of Δ9,11,13-18 : 3, cis-7,cis-12,cis-15-18 : 3 and cis-8,cis-12,cis-15-18 : 3 were also formed. No increase in n+1 isotopomers of Δ7,12,15-18 : 3 or Δ8,12,15-18 : 3 was detected. Enrichment in n+2 isotopomers of 18 : 2 products indicated that ALA metabolism continued via the reduction of 18 : 3 intermediates. Isomers of Δ9,11,15-18 : 3 were reduced to Δ11,15-18 : 2 labelled at C-9 and C-13. ALA resulted in the formation of Δ11,13-18 : 2 and Δ12,14-18 : 2 containing multiple 2H labels. Enrichment of the n+3 isotopomer of Δ12,15-18 : 2 was also detected. Metabolism of ALA during incubations with rumen contents occurs by one of three distinct pathways. Formation of Δ9,11,15-18 : 3 appears to be initiated by H abstraction on C-13. Octadecatrienoic intermediates containing cis-12 and cis-15 double bonds are formed without an apparent H exchange with water. Labelling of Δ9,11,13-18 : 3 was inconclusive, suggesting formation by an alternative mechanism. These findings explain the appearance of several bioactive fatty acids in muscle and milk that influence the nutritional value of ruminant-derived foods.

Oral Samples as Non-Invasive Proxies for Assessing the Composition of the Rumen Microbial Community.

Microbial community analysis was carried out on ruminal digesta obtained directly via rumen fistula and buccal fluid, regurgitated digesta (bolus) and faeces of dairy cattle to assess if non-invasive samples could be used as proxies for ruminal digesta. Samples were collected from five cows receiving grass silage based diets containing no additional lipid or four different lipid supplements in a 5 x 5 Latin square design. Extracted DNA was analysed by qPCR and by sequencing 16S and 18S rRNA genes or the fungal ITS1 amplicons. Faeces contained few protozoa, and bacterial, fungal and archaeal communities were substantially different to ruminal digesta. Buccal and bolus samples gave much more similar profiles to ruminal digesta, although fewer archaea were detected in buccal and bolus samples. Bolus samples overall were most similar to ruminal samples. The differences between both buccal and bolus samples and ruminal digesta were consistent across all treatments. It can be concluded that either proxy sample type could be used as a predictor of the rumen microbial community, thereby enabling more convenient large-scale animal sampling for phenotyping and possible use in future animal breeding programs aimed at selecting cattle with a lower environmental footprint.

Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance.

Methane produced by methanogenic archaea in ruminants contributes significantly to anthropogenic greenhouse gas emissions. The host genetic link controlling microbial methane production is unknown and appropriate genetic selection strategies are not developed. We used sire progeny group differences to estimate the host genetic influence on rumen microbial methane production in a factorial experiment consisting of crossbred breed types and diets. Rumen metagenomic profiling was undertaken to investigate links between microbial genes and methane emissions or feed conversion efficiency. Sire progeny groups differed significantly in their methane emissions measured in respiration chambers. Ranking of the sire progeny groups based on methane emissions or relative archaeal abundance was consistent overall and within diet, suggesting that archaeal abundance in ruminal digesta is under host genetic control and can be used to genetically select animals without measuring methane directly. In the metagenomic analysis of rumen contents, we identified 3970 microbial genes of which 20 and 49 genes were significantly associated with methane emissions and feed conversion efficiency respectively. These explained 81% and 86% of the respective variation and were clustered in distinct functional gene networks. Methanogenesis genes (e.g. mcrA and fmdB) were associated with methane emissions, whilst host-microbiome cross talk genes (e.g. TSTA3 and FucI) were associated with feed conversion efficiency. These results strengthen the idea that the host animal controls its own microbiota to a significant extent and open up the implementation of effective breeding strategies using rumen microbial gene abundance as a predictor for difficult-to-measure traits on a large number of hosts. Generally, the results provide a proof of principle to use the relative abundance of microbial genes in the gastrointestinal tract of different species to predict their influence on traits e.g. human metabolism, health and behaviour, as well as to understand the genetic link between host and microbiome.

Risks associated with endotoxins in feed additives produced by fermentation.

Increasingly, feed additives for livestock, such as amino acids and vitamins, are being produced by Gram-negative bacteria, particularly Escherichia coli. The potential therefore exists for animals, consumers and workers to be exposed to possibly harmful amounts of endotoxin from these products. The aim of this review was to assess the extent of the risk from endotoxins in feed additives and to calculate how such risk can be assessed from the properties of the additive. Livestock are frequently exposed to a relatively high content of endotoxin in the diet: no additional hazard to livestock would be anticipated if the endotoxin concentration of the feed additive falls in the same range as feedstuffs. Consumer exposure will be unaffected by the consumption of food derived from animals receiving endotoxin-containing feed, because the small concentrations of endotoxin absorbed do not accumulate in edible tissues. In contrast, workers processing a dusty additive may be exposed to hazardous amounts of endotoxin even if the endotoxin concentration of the product is low. A calculation method is proposed to compare the potential risk to the worker, based on the dusting potential, the endotoxin concentration and technical guidance of the European Food Safety Authority, with national exposure limits.

The rumen microbial metagenome associated with high methane production in cattle.

BACKGROUND: Methane represents 16 % of total anthropogenic greenhouse gas emissions. It has been estimated that ruminant livestock produce ca. 29 % of this methane. As individual animals produce consistently different quantities of methane, understanding the basis for these differences may lead to new opportunities for mitigating ruminal methane emissions. Metagenomics is a powerful new tool for understanding the composition and function of complex microbial communities. Here we have applied metagenomics to the rumen microbial community to identify differences in the microbiota and metagenome that lead to high- and low-methane-emitting cattle phenotypes. METHODS: Four pairs of beef cattle were selected for extreme high and low methane emissions from 72 animals, matched for breed (Aberdeen-Angus or Limousin cross) and diet (high or medium concentrate). Community analysis was carried out by qPCR of 16S and 18S rRNA genes and by alignment of Illumina HiSeq reads to the GREENGENES database. Total genomic reads were aligned to the KEGG genes databasefor functional analysis. RESULTS: Deep sequencing produced on average 11.3 Gb per sample. 16S rRNA gene abundances indicated that archaea, predominantly Methanobrevibacter, were 2.5× more numerous (P = 0.026) in high emitters, whereas among bacteria Proteobacteria, predominantly Succinivibrionaceae, were 4-fold less abundant (2.7 vs. 11.2 %; P = 0.002). KEGG analysis revealed that archaeal genes leading directly or indirectly to methane production were 2.7-fold more abundant in high emitters. Genes less abundant in high emitters included acetate kinase, electron transport complex proteins RnfC and RnfD and glucose-6-phosphate isomerase. Sequence data were assembled de novo and over 1.5 million proteins were annotated on the subsequent metagenome scaffolds. Less than half of the predicted genes matched matched a domain within Pfam. Amongst 2774 identified proteins of the 20 KEGG orthologues that correlated with methane emissions, only 16 showed 100 % identity with a publicly available protein sequence. CONCLUSIONS: The abundance of archaeal genes in ruminal digesta correlated strongly with differing methane emissions from individual animals, a finding useful for genetic screening purposes. Lower emissions were accompanied by higher Succinovibrionaceae abundance and changes in acetate and hydrogen production leading to less methanogenesis, as similarly postulated for Australian macropods. Large numbers of predicted protein sequences differed between high- and low-methane-emitting cattle. Ninety-nine percent were unknown, indicating a fertile area for future exploitation.

Essential oils have different effects on human pathogenic and commensal bacteria in mixed faecal fermentations compared with pure cultures.

A static batch culture system inoculated with human faeces was used to determine the influence of essential oil compounds (EOCs) on mixed faecal microbiota. Bacteria were quantified using quantitative PCR of 16S rRNA genes. Incubation for 24 h of diluted faeces from six individuals caused enrichment of Bifidobacterium spp., but proportions of other major groups were unaffected. Thymol and geraniol at 500 p.p.m. suppressed total bacteria, resulting in minimal fermentation. Thymol at 100 p.p.m. had no effect, nor did eugenol or nerolidol at 100 or 500 p.p.m. except for a slight suppression of Eubacterium hallii. Methyl isoeugenol at 100 or 500 p.p.m. suppressed the growth of total bacteria, accompanied by a large fall in the molar proportion of propionate formed. The relative abundance of Faecalibacterium prausnitzii was unaffected except with thymol at 500 p.p.m. The ability of EOCs to control numbers of the pathogen Clostridium difficile was investigated in a separate experiment, in which the faecal suspensions were amended by the addition of pure culture of C. difficile. Numbers of C. difficile were suppressed by thymol and methyl isoeugenol at 500 p.p.m. and to a lesser extent at 100 p.p.m. Eugenol and geraniol gave rather similar suppression of C. difficile numbers at both 100 and 500 p.p.m. Nerolidol had no significant effect. It was concluded from these and previous pure-culture experiments that thymol and geraniol at around 100 p.p.m. could be effective in suppressing pathogens in the small intestine, with no concern for beneficial commensal colonic bacteria in the distal gut.

Diversity and community composition of methanogenic archaea in the rumen of Scottish upland sheep assessed by different methods.

Ruminal archaeomes of two mature sheep grazing in the Scottish uplands were analysed by different sequencing and analysis methods in order to compare the apparent archaeal communities. All methods revealed that the majority of methanogens belonged to the Methanobacteriales order containing the Methanobrevibacter, Methanosphaera and Methanobacteria genera. Sanger sequenced 1.3 kb 16S rRNA gene amplicons identified the main species of Methanobrevibacter present to be a SGMT Clade member Mbb. millerae (≥ 91% of OTUs); Methanosphaera comprised the remainder of the OTUs. The primers did not amplify ruminal Thermoplasmatales-related 16S rRNA genes. Illumina sequenced V6-V8 16S rRNA gene amplicons identified similar Methanobrevibacter spp. and Methanosphaera clades and also identified the Thermoplasmatales-related order as 13% of total archaea. Unusually, both methods concluded that Mbb. ruminantium and relatives from the same clade (RO) were almost absent. Sequences mapping to rumen 16S rRNA and mcrA gene references were extracted from Illumina metagenome data. Mapping of the metagenome data to 16S rRNA gene references produced taxonomic identification to Order level including 2-3% Thermoplasmatales, but was unable to discriminate to species level. Mapping of the metagenome data to mcrA gene references resolved 69% to unclassified Methanobacteriales. Only 30% of sequences were assigned to species level clades: of the sequences assigned to Methanobrevibacter, most mapped to SGMT (16%) and RO (10%) clades. The Sanger 16S amplicon and Illumina metagenome mcrA analyses showed similar species richness (Chao1 Index 19-35), while Illumina metagenome and amplicon 16S rRNA analysis gave lower richness estimates (10-18). The values of the Shannon Index were low in all methods, indicating low richness and uneven species distribution. Thus, although much information may be extracted from the other methods, Illumina amplicon sequencing of the V6-V8 16S rRNA gene would be the method of choice for studying rumen archaeal communities.