Enteric methane research and mitigation strategies for pastoral-based beef cattle production systems

Network analyses unraveled the complex interactions in the rumen microbiota associated with methane emission in dairy cattle

BACKGROUND

Methane emissions from livestock, particularly from dairy cattle, represent a significant source of greenhouse gas, contributing to the global climate crisis. Understanding the complex interactions within the rumen microbiota that influence methane emissions is crucial for developing effective mitigation strategies.

RESULTS

This study employed Weighted Gene Co-expression Network Analysis to investigate the complex interactions within the rumen microbiota that influence methane emissions. By integrating extensive rumen microbiota sequencing data with precise methane emission measurements in 750 Holstein dairy cattle, our research identified distinct microbial communities and their associations with methane production. Key findings revealed that the blue module from network analysis was significantly correlated (0.45) with methane emissions. In this module, taxa included the genera Prevotella and Methanobrevibactor, along with species such as Prevotella brevis, Prevotella ruminicola, Prevotella baroniae, Prevotella bryantii, Lachnobacterium bovis, and Methanomassiliicoccus luminyensis are the key components to drive the complex networks. However, the absence of metagenomics sequencing is difficult to reveal the deeper taxa level and functional profiles.

CONCLUSIONS

The application of Weighted Gene Co-expression Network Analysis provided a comprehensive understanding of the microbiota-methane emission relationship, serving as an innovative approach for microbiota-phenotype association studies in cattle. Our findings underscore the importance of microbiota-trait and microbiota-microbiota associations related to methane emission in dairy cattle, contributing to a systematic understanding of methane production in cattle. This research offers key information on microbial management for mitigating environmental impact on the cattle population.

Perspectives in cattle reproduction for the next 20 years - A European context

Following a significant increase in herd and farm sizes after the removal of milk quotas in Europe, the past 10 years have seen a slight yet steady decline in the population of cattle. This includes a reduction of approximately 5 % in dairy and beef cattle. This trend is driven by various factors, such as changing market demands, economic shifts, and sustainability challenges in the livestock sector. Despite this, technological advancements in reproductive management have continued to enhance efficiency and sustainability, particularly in dairy production. The main areas of rapid development, which will continue to grow for improving fertility and management, include: i) genetic selection (including improved phenotypes for use in breeding programs), ii) nutritional management (including transition cow management), iii) control of infectious disease, iv) rapid diagnostics of reproductive health, v) development of more efficient ovulation/estrous synchronization protocols, vi) assisted reproductive management (and automated systems to improve reproductive management), vii) increased implementation of sexed semen and embryo transfer, viii) more efficient handling of substantial volumes of data, ix) routine implementation of artificial intelligence technology for rapid decision-making at the farm level, x) climate change and sustainable cattle production awareness, xi) new (reproductive) strategies to improve cattle welfare, and xii) improved management and technology implementation for male fertility. This review addresses the current status and future outlook of key factors that influence cattle herd health and reproductive performance, with a special focus on dairy cattle. These insights are expected to contribute to improved performance, health, and fertility of ruminants in the next 20 years.

Improving Human Diets and Welfare through Using Herbivore-Based Foods: 2. Environmental Consequences and Mitigations

Animal-sourced foods are important for human nutrition and health, but they can have a negative impact on the environment. These impacts can result in land use tensions associated with population growth and the loss of native forests and wetlands during agricultural expansion. Increased greenhouse gas emissions, and high water use but poor water quality outcomes can also be associated. Life cycle analysis from cradle-to-distribution has shown that novel plant-based meat alternatives can have an environmental footprint lower than that of beef finished in feedlots, but higher than for beef raised on well-managed grazed pastures. However, several technologies and practices can be used to mitigate impacts. These include ensuring that grazing occurs when feed quality is high, the use of dietary additives, breeding of animals with higher growth rates and increased fecundity, rumen microbial manipulations through the use of vaccines, soil management to reduce nitrous oxide emission, management systems to improve carbon sequestration, improved nutrient use efficacy throughout the food chain, incorporating maize silage along with grasslands, use of cover crops, low-emission composting barns, covered manure storages, and direct injection of animal slurry into soil. The technologies and systems that help mitigate or actually provide solutions to the environmental impact are under constant refinement to enable ever-more efficient production systems to allow for the provision of animal-sourced foods to an ever-increasing population.

Sward type alters enteric methane emissions, nitrogen output and the relative abundance of the rumen microbial ecosystem in sheep

Observed improvements in animal and sward performance, coupled with a desire for more sustainable pasture-based feeding systems, has triggered a surge in the implementation of more botanically diverse pastures. However, thus far, there has been limited research investigating the effects of botanically diverse sward types on enteric methane (CH4) or nitrogen (N) excretion, alongside the ruminal microbiota and fermentation profile, in sheep. Hence, this study investigates the effect of sward type on CH4 production and N excretion, in addition to assessing the rumen microbiome, volatile fatty acid proportions, and ammonia nitrogen (NH3-N) concentration in sheep. A 5 × 5 Latin square design experiment was implemented to investigate 5 dietary treatments; perennial ryegrass (Lolium perenne L.; PRG) only or PRG plus white clover (Trifolium repens L.; PRG + WC), red clover (Trifolium pratense L.; PRG + RC), chicory (Chicorium intybus L.; PRG + Chic) or plantain (Plantago lanceolata L.; PRG + Plan). Diets were mixed at a ratio of 75% PRG and 25% of the respective companion forage and 100% PRG for the PRG treatment, on a dry matter basis. Twenty castrated male sheep were housed in metabolism crates across 5 feeding periods. Methane measurements were acquired utilizing portable accumulation chambers. Rumen fluid was harvested using a transoesophageal sampling device. Microbial rumen DNA was extracted and subjected to 16S rRNA amplicon sequencing and fermentation analysis. Data were analyzed using PROC MIXED in SAS. Results show that animals consuming PRG + WC ranked lower for CH4 production (g/d) than sheep offered PRG, PRG + Chic or PRG + Plan (P < 0.01) while the addition of any companion forage ranked CH4 yield (g/kg dry matter intake (DMI)) lower (P < 0.001) than PRG. There was a moderate positive correlation between DMI and CH4 (g/d; r = 0.51). Ruminal NH3-N was lowest in animals consuming the PRG diet (P < 0.01). There was a greater abundance of Methanobrevibacter and reduced abundance of Methanosphaera (P < 0.001) in sheep offered PRG, compared with any binary sward. On average, herb diets (PRG + Chic or PRG + Plan) reduced the urinary nitrogen concentration of sheep by 34% in comparison to legume diets (PRG + WC or PRG + RC) and 13% relative to the PRG diet (P < 0.001). Sheep offered PRG + Chic had a greater dietary nitrogen use efficiency than PRG + RC (P < 0.05). This study demonstrates the potential for sward type to influence rumen function and the microbial community, along with CH4 and N output from sheep.

Effects of dietary supplementation with 3-nitrooxypropanol on enteric methane production, rumen fermentation, and performance in young growing beef cattle offered a 50:50 forage:concentrate diet

There is an urgent requirement internationally to reduce enteric methane (CH4) emissions from ruminants to meet greenhouse gas emissions reduction targets. Dietary supplementation with feed additives is one possible strategy under investigation as an effective solution. The effects of the CH4 inhibitor 3-nitrooxypropanol (3-NOP) at reducing CH4 emissions in beef have been shown mainly in adult cattle consuming backgrounding and high-energy finishing diets. In this study, the effects of dietary supplementation of young growing (≤6 mo) beef cattle with 3-NOP were examined in a 50:50 forage:concentrate diet. A total of 68 Dairy × Beef (Aberdeen Angus and Hereford dairy cross) male calves (≤6 mo of age at the start of experiment, body weight: 147 ± 38 kg) underwent a 3-wk acclimatization period and were then assigned to one of two treatments in a completely randomized block design. Dietary treatments were (1) control, placebo (no 3-NOP), and (2) 3-NOP applied at 150 mg kg-1 DM. Calves were fed a partial mixed ration for 12 wk. Body weight was recorded weekly and feed intake daily using the Calan Broadbent feeding system. Methane and hydrogen emissions were measured using the GreenFeed system. Total weight gained, dry matter intake (DMI), and average daily gain were not affected by 3-NOP (P > 0.05) supplementation. On average, the inclusion of 3-NOP decreased (P < 0.001) CH4 emissions: g d-1; g kg-1 DMI; by 30.6% and 27.2%, respectively, during the study with a greater reduction occurring over time. Incorporating 3-NOP into beef cattle diets is an efficient solution to decrease CH4 emissions during indoor feeding and when offered 50:50 forage:concentrate diet.

Unveiling microbial biomarkers of ruminant methane emission through machine learning

Background

Enteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine learning algorithms have shown success in associating human gut microbiome with various human diseases, there have been limited efforts to employ these algorithms to establish microbial biomarkers for methane emissions in ruminants.

Methods

In this study, we aim to identify potential methane biomarkers for methane emission from ruminants by employing regression algorithms commonly used in human microbiome studies, coupled with different feature selection methods. To achieve this, we analyzed the microbiome compositions and identified possible confounding metadata variables in two large public datasets of Holstein cows. Using both the microbiome features and identified metadata variables, we trained different regressors to predict methane emission. With the optimized models, permutation tests were used to determine feature importance to find informative microbial features.

Results

Among the regression algorithms tested, random forest regression outperformed others and allowed the identification of several crucial microbial taxa for methane emission as members of the native rumen microbiome, including the genera Piromyces, Succinivibrionaceae UCG-002, and Acetobacter. Additionally, our results revealed that certain herd locations and feed composition markers, such as the lipid intake and neutral-detergent fiber intake, are also predictive features for methane emissions.

Conclusion

We demonstrated that machine learning, particularly regression algorithms, can effectively predict cow methane emissions and identify relevant rumen microorganisms. Our findings offer valuable insights for the development of microbiome-based precision feed strategies aiming at reducing methane emissions.

Adult Bovine-Derived Small and Large Intestinal Organoids: In Vitro Development and Maintenance

Recent progress in bovine intestinal organoid research has expanded opportunities for creating improved in vitro models to study intestinal physiology and pathology. However, the establishment of a culture condition capable of generating organoids from all segments of the cattle intestine has remained elusive. Although previous research has described the development of bovine jejunal, ileal, and colonic organoids, this study marks the first report of successful bovine duodenal and rectal organoid development. Maintenance of these organoids through serial passages and cryopreservation was achieved, with higher success rates observed in large intestinal organoids compared to their small intestinal counterparts. A novel approach involving the use of biopsy forceps during initial tissue sampling streamlined the subsequent tissue processing, simplifying the procedure compared to previously established protocols in cattle. Additionally, our study introduced a more cost-effective culture medium based on Advanced DMEM/F12, diverging from frequently used commercially available organoid culture media. This enhancement improves accessibility to organoid technology by reducing culture costs. Crucially, the derived organoids from jejunum, ileum, colon and rectum faithfully preserved the structural, cellular, and genetic characteristics of in vivo intestinal tissue. This research underscores the significant potential of adult bovine intestinal organoids as a physiologically and morphologically relevant in vitro model. Such organoids provide a renewable and sustainable resource for a broad spectrum of studies, encompassing investigations into normal intestinal physiology in cattle and the intricate host-pathogen interactions of clinically and economically significant enteric pathogens.