The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Integrating Omics Technologies for a Comprehensive Understanding of the Microbiome and Its Impact on Cattle Production

Ruminant production holds a pivotal position within the global animal production and agricultural sectors. As population growth escalates, posing environmental challenges, a heightened emphasis is directed toward refining ruminant production systems. Recent investigations underscore the connection between the composition and functionality of the rumen microbiome and economically advantageous traits in cattle. Consequently, the development of innovative strategies to enhance cattle feed efficiency, while curbing environmental and financial burdens, becomes imperative. The advent of omics technologies has yielded fresh insights into metabolic health fluctuations in dairy cattle, consequently enhancing nutritional management practices. The pivotal role of the rumen microbiome in augmenting feeding efficiency by transforming low-quality feedstuffs into energy substrates for the host is underscored. This microbial community assumes focal importance within gut microbiome studies, contributing indispensably to plant fiber digestion, as well as influencing production and health variability in ruminants. Instances of compromised animal welfare can substantially modulate the microbiological composition of the rumen, thereby influencing production rates. A comprehensive global approach that targets both cattle and their rumen microbiota is paramount for enhancing feed efficiency and optimizing rumen fermentation processes. This review article underscores the factors that contribute to the establishment or restoration of the rumen microbiome post perturbations and the intricacies of host-microbiome interactions. We accentuate the elements responsible for responsible host-microbiome interactions and practical applications in the domains of animal health and production. Moreover, meticulous scrutiny of the microbiome and its consequential effects on cattle production systems greatly contributes to forging more sustainable and resilient food production systems, thereby mitigating the adverse environmental impact.

A serum NMR metabolomic analysis of the Corynebacterium pseudotuberculosis infection in goats

Caseous lymphadenitis (CLA), an infectious disease caused by Corynebacterium pseudotuberculosis in small ruminants, is highly prevalent worldwide. Economic losses have already been associated with the disease, and little is known about the host-pathogen relationship associated with the disease. The present study aimed to perform a metabolomic study of the C. pseudotuberculosis infection in goats. Serum samples were collected from a herd of 173 goats. The animals were classified as controls (not infected), asymptomatic (seropositives but without detectable CLA clinical signs), and symptomatic (seropositive animals presenting CLA lesions), according to microbiological isolation and immunodiagnosis. The serum samples were analyzed using nuclear magnetic resonance (¹H-NMR), nuclear Overhauser effect spectroscopy (NOESY), and Carr-Purcell-Meiboom-Gill (CPMG) sequences. The NMR data were analyzed using chemometrics, and principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were performed to discover specific biomarkers responsible for discrimination between the groups. A high dissemination of the infection by C. pseudotuberculosis was observed, being 74.57% asymptomatic and 11.56% symptomatic. In the evaluation of 62 serum samples by NMR, the techniques were satisfactory in the discrimination of the groups, being also complementary and mutually confirming, demonstrating possible biomarkers for the infection by the bacterium. Twenty metabolites of interest were identified by NOESY and 29 by CPMG, such as tryptophan, polyunsaturated fatty acids, formic acid, NAD⁺, and 3-hydroxybutyrate, opening promising possibilities for the use of these results in new therapeutic, immunodiagnosis, and immunoprophylactic tools, as well as for studies of the immune response against C. pseudotuberculosis. KEY POINTS: • Sixty-two samples from healthy, CLA asymptomatic, and symptomatic goats were screened • Twenty metabolites of interest were identified by NOESY and 29 by CPMG • ¹H-NMR NOESY and CPMG were complementary and mutually confirming.

Technology for Carbon Neutral Animal Breeding

Animal breeding techniques are to genetically select highly productive animals with less GHG emission intensity, thereby reducing the number of animals required to produce the same amount of food. Shotgun metagenomics provides a platform to identify rumen microbial communities and genetic markers associated with CH4 emissions, allowing the selection of cattle with less CH4 emissions. Moreover, breeding is a viable option to make real progress towards carbon neutrality with a very high rate of return on investment and a very modest cost per tonne of CO2 equivalents saved regardless of the accounting method. Other high technologies include the use of cloned livestock animals and the manipulation of traits by controlling target genes with improved productivity.

Host genetics associated with gut microbiota and methane emission in cattle

In livestock sector, dairy animals alone produce 18% of the total greenhouse gas emissions globally as methane (CH₄). This Enteric methane is the largest component of total carbon footprints produced by livestock production system and its reduction is today's new challenge to make livestock farming sustainable for earth's environment. The production of enteric methane in ruminants is a complex phenomena involving different host factors like host genotype, rumen microbiome, host physiology along with dietary factors. Efforts have been made to reduce methane emissions largely through nutritional interventions and dietary supplements, but permanent reductions can be obtained through genetic means by selecting and breeding of low methane emitting animals. From genome-wide association studies, many important genomic QTL regions and single nucleotide polymorphisms involved in shaping the composition of the ruminal microbiome and thus their carbon footprints have been recognised, implying that methane emission traits are quantitative traits. The major bottleneck in implementation of reduced methane emission traits in the breeding programs is wide variation at phenotypic level, lack of precise methane measurements at individual level. Overall, the heritability for CH₄ production traits is moderate, and it can be used in breeding programmes to target changes in microbial composition to reduce CH₄ emission in the dairy industry for far-reaching environmental benefits at the cost of a minor reduction in genetic gain in production traits.