Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific.

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

The nutritional manipulations of the rumen microbiome to enhance productivity and health are rather limited by the resilience of the ecosystem once established in the mature rumen. Based on recent studies, it has been suggested that the microbial colonization that occurs soon after birth opens a possibility of manipulation with potential to produce lasting effects into adult life. This paper presents the state-of-the-art in relation to early life nutritional interventions by addressing three areas: the development of the rumen as an organ in regards to the nutrition of the new-born, the main factors that determine the microbial population that first colonizes and establishes in the rumen, and the key immunity players that contribute to shaping the commensal microbiota in the early stage of life to understand host-microbiome specificity. The development of the rumen epithelium and muscularization are differently affected by the nature of the diet and special care should be taken with regards to transition from liquid (milk) to solid feed. The rumen is quickly colonized by all type of microorganisms straight after birth and the colonization pattern may be influenced by several factors such as presence/absence of adult animals, the first solid diet provided, and the inclusion of compounds that prevent/facilitate the establishment of some microorganisms or the direct inoculation of specific strains. The results presented show how early life events may be related to the microbial community structure and/or the rumen activity in the animals post-weaning. This would create differences in adaptive capacity due to different early life experiences and leads to the idea of microbial programming. However, many elements need to be further studied such as: the most sensitive window of time for interventions, the best means to test long term effectiveness, the role of key microbial groups and host-immune regulations.

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Enteric methane (CH 4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

Ruminants, such as cows, sheep, and goats, predominantly ferment in their rumen plant material to acetate, propionate, butyrate, CO2, and methane. Whereas the short fatty acids are absorbed and metabolized by the animals, the greenhouse gas methane escapes via eructation and breathing of the animals into the atmosphere. Along with the methane, up to 12% of the gross energy content of the feedstock is lost. Therefore, our recent report has raised interest in 3-nitrooxypropanol (3-NOP), which when added to the feed of ruminants in milligram amounts persistently reduces enteric methane emissions from livestock without apparent negative side effects [Hristov AN, et al. (2015) Proc Natl Acad Sci USA 112(34):10663–10668]. We now show with the aid of in silico, in vitro, and in vivo experiments that 3-NOP specifically targets methyl-coenzyme M reductase (MCR). The nickel enzyme, which is only active when its Ni ion is in the +1 oxidation state, catalyzes the methane-forming step in the rumen fermentation. Molecular docking suggested that 3-NOP preferably binds into the active site of MCR in a pose that places its reducible nitrate group in electron transfer distance to Ni(I). With purified MCR, we found that 3-NOP indeed inactivates MCR at micromolar concentrations by oxidation of its active site Ni(I). Concomitantly, the nitrate ester is reduced to nitrite, which also inactivates MCR at micromolar concentrations by oxidation of Ni(I). Using pure cultures, 3-NOP is demonstrated to inhibit growth of methanogenic archaea at concentrations that do not affect the growth of nonmethanogenic bacteria in the rumen.

This study evaluated the effects of tannins on ruminal biohydrogenation (BH) due to shifts in the ruminal microbial environment in sheep. Thirteen lambs (45 days of age) were assigned to two dietary treatments: seven lambs were fed a barley-based concentrate (control group) while the other six lambs received the same concentrate with supplemental quebracho tannins (9.57% of dry matter). At 122 days of age, the lambs were slaughtered, and the ruminal contents were subjected to fatty acid analysis and sampled to quantify populations of Butyrivibrio fibrisolvens, which converts C 18:2 c9-c12 (linoleic acid [LA]) to C 18:2 c9-t11 (rumenic acid [RA]) and then RA to C 18:1 t11 (vaccenic acid [VA]); we also sampled for Butyrivibrio proteoclasticus, which converts VA to C 18:0 (stearic acid [SA]). Tannins increased (P < 0.005) VA in the rumen compared to the tannin-free diet. The concentration of SA was not affected by tannins. The SA/VA ratio was lower (P < 0.005) for the tannin-fed lambs than for the controls, suggesting that the last step of the BH process was inhibited by tannins. The B. proteoclasticus population was lower (؊30.6%; P < 0.1), and B. fibrisolvens and protozoan populations were higher (؉107% and ؉56.1%, respectively; P < 0.05) in the rumen of lambs fed the tanninsupplemented diet than in controls. These results suggest that quebracho tannins altered BH by changing ruminal microbial populations.The fatty acid profile of the meat and milk of ruminants is strongly affected by diet (2, 15). When ingested, the dietary polyunsaturated fatty acids (PUFA) undergo a process known as biohydrogenation (BH) carried out by ruminal microorganisms (20). During the BH of C 18:2 (n-6) (linoleic acid [LA]) and C 18:3 (n-3) (linolenic acid [LNA]) a number of C 18:1 and C 18:2 isomers are formed (6). The last step in the BH process leads to the formation of C 18:0 (stearic acid [SA]). Among the intermediate products formed during this process, the isomer C 18:2 c9t11 (rumenic acid [RA]) is active in preventing cancer in mammals (17). Only a small amount of the RA found in meat and milk originates during BH. It is produced to a larger extent in muscle and mammary glands from the desaturation of Devillard et al. (11) have reported that protozoa do not have the capability of hydrogenating LA. The proportion of BH intermediates in the rumen can vary depending on changes in ruminal microbial populations (7, 51). Changes in ruminal fatty acid profiles are also reflected in intramuscular fatty acid composition (48,52).Tannins are phenolic compounds that are widespread in plants. When ingested by ruminants in large amounts, tannins can reduce the activity and the proliferation of ruminal microorganisms (34). Tannins from Lotus corniculatus (33) or from Acacia spp. (12) reduce the proliferation of B. proteoclasticus B316 T and B. proteoclasticus P18, respectively. Durmic et al. (12) reported that VA increased and SA decreased when extracts from Acacia iteaphylla, which contains condensed tannins (1), were incubated in vitro w...