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

Protozoa populations are ecosystem engineers that shape prokaryotic community structure and function of the rumen microbial ecosystem

Unicellular eukaryotes are an integral part of many microbial ecosystems where they interact with their surrounding prokaryotic community-either as predators or as mutualists. Within the rumen, one of the most complex host-associated microbial habitats, ciliate protozoa represent the main micro-eukaryotes, accounting for up to 50% of the microbial biomass. Nonetheless, the extent of the ecological effect of protozoa on the microbial community and on the rumen metabolic output remains largely understudied. To assess the role of protozoa on the rumen ecosystem, we established an in-vitro system in which distinct protozoa sub-communities were introduced to the native rumen prokaryotic community. We show that the different protozoa communities exert a strong and differential impact on the composition of the prokaryotic community, as well as its function including methane production. Furthermore, the presence of protozoa increases prokaryotic diversity with a differential effect on specific bacterial populations such as Gammaproteobacteria, Prevotella and Treponema. Our results suggest that protozoa contribute to the maintenance of prokaryotic diversity in the rumen possibly by mitigating the effect of competitive exclusion between bacterial taxa. Our findings put forward the rumen protozoa populations as potentially important ecosystem engineers for future microbiome modulation strategies.

Translational multi-omics microbiome research for strategies to improve cattle production and health

Cattle microbiome plays a vital role in cattle growth and performance and affects many economically important traits such as feed efficiency, milk/meat yield and quality, methane emission, immunity and health. To date, most cattle microbiome research has focused on metataxonomic and metagenomic characterization to reveal who are there and what they may do, preventing the determination of the active functional dynamics in vivo and their causal relationships with the traits. Therefore, there is an urgent need to combine other advanced omics approaches to improve microbiome analysis to determine their mode of actions and host-microbiome interactions in vivo. This review will critically discuss the current multi-omics microbiome research in beef and dairy cattle, aiming to provide insights on how the information generated can be applied to future strategies to improve production efficiency, health and welfare, and environment-friendliness in cattle production through microbiome manipulations.

Host Genome-Metagenome Analyses Using Combinatorial Network Methods Reveal Key Metagenomic and Host Genetic Features for Methane Emission and Feed Efficiency in Cattle

Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25–0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales.

The effects of the Green-Mediterranean diet on cardiometabolic health are linked to gut microbiome modifications: a randomized controlled trial

BACKGROUND

Previous studies have linked the Mediterranean diet (MED) with improved cardiometabolic health, showing preliminary evidence for a mediating role of the gut microbiome. We recently suggested the Green-Mediterranean (Green-MED) diet as an improved version of the healthy MED diet, with increased consumption of plant-based foods and reduced meat intake. Here, we investigated the effects of MED interventions on the gut microbiota and cardiometabolic markers, and the interplay between the two, during the initial weight loss phase of the DIRECT-PLUS trial.

METHODS

In the DIRECT-PLUS study, 294 participants with abdominal obesity/dyslipidemia were prospectively randomized to one of three intervention groups: healthy dietary guidelines (standard science-based nutritional counseling), MED, and Green-MED. Both isocaloric MED and Green-MED groups were supplemented with 28g/day walnuts. The Green-MED group was further provided with daily polyphenol-rich green tea and Mankai aquatic plant (new plant introduced to a western population). Gut microbiota was profiled by 16S rRNA for all stool samples and shotgun sequencing for a select subset of samples.

RESULTS

Both MED diets induced substantial changes in the community structure of the gut microbiome, with the Green-MED diet leading to more prominent compositional changes, largely driven by the low abundant, "non-core," microorganisms. The Green-MED diet was associated with specific microbial changes, including enrichments in the genus Prevotella and enzymatic functions involved in branched-chain amino acid degradation, and reductions in the genus Bifidobacterium and enzymatic functions responsible for branched-chain amino acid biosynthesis. The MED and Green-MED diets were also associated with stepwise beneficial changes in body weight and cardiometabolic biomarkers, concomitantly with the increased plant intake and reduced meat intake. Furthermore, while the level of adherence to the Green-MED diet and its specific green dietary components was associated with the magnitude of changes in microbiome composition, changes in gut microbial features appeared to mediate the association between adherence to the Green-MED and body weight and cardiometabolic risk reduction.

CONCLUSIONS

Our findings support a mediating role of the gut microbiome in the beneficial effects of the Green-MED diet enriched with Mankai and green tea on cardiometabolic risk factors.

TRIAL REGISTRATION

The study was registered on ClinicalTrial.gov ( NCT03020186 ) on January 13, 2017.

Association between host genetics of sheep and the rumen microbial composition

A synergy between the rumen microbiota and the host genetics has created a symbiotic relationship, beneficial to the host's health. In this study, the association between the host genetics and rumen microbiome of Damara and Meatmaster sheep was investigated. The composition of rumen microbiota was estimated through the analysis of the V3-V4 region of the 16S rRNA gene, while the sheep blood DNA was genotyped with Illumina OvineSNP50 BeadChip and the genome-wide association (GWA) was analyzed. Sixty significant SNPs dispersed in 21 regions across the Ovis aries genome were found to be associated with the relative abundance of seven genera: Acinetobacter, Bacillus, Clostridium, Flavobacterium, Prevotella, Pseudomonas, and Streptobacillus. A total of eighty-four candidate genes were identified, and their functional annotations were mainly associated with immunity responses and function, metabolism, and signal transduction. Our results propose that those candidate genes identified in the study may be modulating the composition of rumen microbiota and further indicating the significance of comprehending the interactions between the host and rumen microbiota to gain better insight into the health of sheep.

Host Genetic Determinants of the Microbiome Across Animals: From Caenorhabditis elegans to Cattle

Animals harbor diverse communities of microbes within their gastrointestinal tracts. Phylogenetic relationship, diet, gut morphology, host physiology, and ecology all influence microbiome composition within and between animal clades. Emerging evidence points to host genetics as also playing a role in determining gut microbial composition within species. Here, we discuss recent advances in the study of microbiome heritability across a variety of animal species. Candidate gene and discovery-based studies in humans, mice, Drosophila, Caenorhabditis elegans, cattle, swine, poultry, and baboons reveal trends in the types of microbes that are heritable and the host genes and pathways involved in shaping the microbiome. Heritable gut microbes within a host species tend to be phylogenetically restricted. Host genetic variation in immune- and growth-related genes drives the abundances of these heritable bacteria within the gut. With only a small slice of the metazoan branch of the tree of life explored to date, this is an area rife with opportunities to shed light into the mechanisms governing host-microbe relationships.

Serum Biochemical Parameters, Rumen Fermentation, and Rumen Bacterial Communities Are Partly Driven by the Breed and Sex of Cattle When Fed High-Grain Diet

Hybridization in bovines is practiced with the main aim of improving production performance, which may imply the microbial variations in the rumen from the parental breed cross to their progeny. Besides, the interactions of offspring breed with sex in terms of rumen bacteria are not clear. This study aims to evaluate the variations in rumen bacterial communities in different breeds and sexes, and the correlations among fattening performance, serum biochemical parameters, and rumen fermentation. Forty-two 19.2 ± 0.67-month-old beef cattle (390 ± 95 kg of initial body weight) comprising two genetic lines (Yiling and Angus × Yiling) and two sexes (heifers and steers) were raised under the same high-grain diet for 120 d. On the last two days, blood samples were collected from each animal via the jugular vein before morning feeding for analyzing serum biochemical parameters; rumen fluid samples were obtained via esophageal intubation 2 h after morning feeding for analyzing rumen fermentation parameters and bacterial communities. The results show that both breed and sex had a certain impact on fattening performance, serum biochemical parameters, and rumen fermentation. No differences in the diversity and structure of rumen bacterial communities were observed. Significant interactions (p < 0.05) of breed and sex were observed for Succinivibrionaceae UCG-002 and Prevotellaceae UCG-001. The relative abundances of the Rikenellaceae RC9 gut group, Prevotellaceae UCG-003, and Succinivibrio were different (p < 0.05) between breeds. Heifers had a higher (p = 0.008) relative abundance of the Rikenellaceae RC9 gut group than steers. Correlation analysis showed a significant relationship (p < 0.05) of rumen bacteria with serum biochemical parameters, rumen pH, and rumen fermentation patterns. Additionally, only two genera, Prevotellaceae UCG-003 and Prevotellaceae UCG-001, had positive correlations with feed efficiency. In conclusion, serum biochemical parameters, rumen fermentation, and rumen bacterial communities are partly driven by the breed and sex of cattle fed a high-grain diet.

Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle

BACKGROUND

Mitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions.

RESULTS

The β-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals.

CONCLUSIONS

Methane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.

Concepts and Consequences of a Core Gut Microbiota for Animal Growth and Development

Animal microbiomes are occasionally considered as an extension of host anatomy, physiology, and even their genomic architecture. Their compositions encompass variable and constant portions when examined across multiple hosts. The latter, termed the core microbiome, is viewed as more accommodated to its host environment and suggested to benefit host fitness. Nevertheless, discrepancies in its definitions, characteristics, and importance to its hosts exist across studies. We survey studies that characterize the core microbiome, detail its current definitions and available methods to identify it, and emphasize the crucial need to upgrade and standardize the methodologies among studies. We highlight ruminants as a case study and discuss the link between the core microbiome and host physiology and genetics, as well as potential factors that shape it. We conclude with main directives of action to better understand the host-core microbiome axis and acquire the necessary insights into its controlled modulation. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle

Simple Summary

Sensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.

Abstract

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.

Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study

Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999 and 2021, which applied machine learning algorithms to dairy farming-related problems to identify trends in the geographical origins of data, as well as the algorithms, features and evaluation metrics and methods used. This mapping study was carried out in line with PRISMA guidelines, with six pre-defined research questions (RQ) and a broad and unbiased search strategy that explored five databases. In total, 129 publications passed the pre-defined selection criteria, from which relevant data required to answer each RQ were extracted and analyzed. This study found that Europe (43% of studies) produced the largest number of publications (RQ1), while the largest number of articles were published in the Computers and Electronics in Agriculture journal (21%) (RQ2). The largest number of studies addressed problems related to the physiology and health of dairy cows (32%) (RQ3), while the most frequently employed feature data were derived from sensors (48%) (RQ4). The largest number of studies employed tree-based algorithms (54%) (RQ5), while RMSE (56%) (regression) and accuracy (77%) (classification) were the most frequently employed metrics used, and hold-out cross-validation (39%) was the most frequently employed evaluation method (RQ6). Since 2018, there has been more than a sevenfold increase in the number of studies that focused on the physiology and health of dairy cows, compared to almost a threefold increase in the overall number of publications, suggesting an increased focus on this subdomain. In addition, a fivefold increase in the number of publications that employed neural network algorithms was identified since 2018, in comparison to a threefold increase in the use of both tree-based algorithms and statistical regression algorithms, suggesting an increasing utilization of neural network-based algorithms.

Technologies and perspectives for achieving carbon neutrality

Global development has been heavily reliant on the overexploitation of natural resources since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other forms of land-use change, anthropogenic activities have contributed to the ever-increasing concentrations of greenhouse gases (GHGs) in the atmosphere, causing global climate change. In response to the worsening global climate change, achieving carbon neutrality by 2050 is the most pressing task on the planet. To this end, it is of utmost importance and a significant challenge to reform the current production systems to reduce GHG emissions and promote the capture of CO2 from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

Effect of Olive Cake and Cactus Cladodes Incorporation in Goat Kids' Diet on the Rumen Microbial Community Profile and Meat Fatty Acid Composition

Simple Summary

Throughout the world, the ruminant diet is based on conventional feedstuffs, which their price constantly fluctuates, and their use presents a concurrence to human nutrition. The use of alternative feed resources seems to be a solution to reduce charges and diversify ruminants’ diet. Olive cake and cactus cladodes are two alternative feed resources that are recommended to be used in ruminant feed. However, their effect on the bacterial community of ruminants is not widely investigated. This study aims to evaluate the effect of olive cake and cactus cladodes on the ruminal microbial ecosystem and meat fatty acids of goat kids. The incorporation of these feedstuffs did not change the bacterial abundance and diversity. Goat kids’ rumen liquor seemed to be able to adapt to alternative feed resources incorporation. The introduction of olive cake and cactus cladodes slightly affect meat fatty acids without a negative effect. Thus, ruminants seem to have the ability to adapt to the alternative feed resources digestion, and their use as a feed could diversify feed and reduce feed cost.

Abstract

The olive cake (OC) and the cactus cladodes (CC) are two alternative feed resources widely available in the southern Mediterranean region that could be used in ruminants’ diet. Their impact on the rumen bacterial ecosystem is unknown. This work aims to evaluate their effects on the microbial community and meat fatty acids of goat’s kids. Forty-four goat kids were divided into four groups receiving diets with conventional concentrate, or 35% OC, or 30% CC, or 15% OC, and 15% CC. After 3 months, these animals were slaughtered, and the rumen liquor and longissimus dorsi and semimembranosus muscles samples were collected. Animals receiving a control diet had rumen liquor with high acidity than test groups (p < 0.001). Test rumen liquor was more adapted to digest efficiently their matching diet than control liquor (p < 0.05). These feedstuffs did not affect rumen bacteria abundance and alpha diversity (richness, evenness, and reciprocal Simpson indexes), and these results were confirmed by beta-diversity tests (NMDS plot, HOMOVA, PERMANOVA). The test diets slightly affected the individual fatty acids of meat (p < 0.05) without effect on fatty acids summaries, indexes, and ratios. Thus, these alternative feed resources could take place in goat kids’ diet to diversify their feed and to reduce feed costs.

In Vitro Incubations Do Not Reflect In Vivo Differences Based on Ranking of Low and High Methane Emitters in Dairy Cows

This study evaluated if ranking dairy cows as low and high CH₄ emitters using the GreenFeed system (GF) can be replicated in in vitro conditions using an automated gas system and its possible implications in terms of fermentation balance. Seven pairs of low and high emitters fed the same diet were selected on the basis of residual CH₄ production, and rumen fluid taken from each pair incubated separately in the in vitro gas production system. In total, seven in vitro incubations were performed with inoculums taken from low and high CH₄ emitting cows incubated in two substrates differing in forage-to-concentrate proportion, each without or with the addition of cashew nutshell liquid (CNSL) as an inhibitor of CH₄ production. Except for the aimed differences in CH₄ production, no statistical differences were detected among groups of low and high emitters either in in vivo animal performance or rumen fermentation profile prior to the in vitro incubations. The effect of in vivo ranking was poorly replicated in in vitro conditions after 48 h of anaerobic fermentation. Instead, the effects of diet and CNSL were more consistent. The inclusion of 50% barley in the diet (SB) increased both asymptotic gas production by 17.3% and predicted in vivo CH₄ by 26.2%, when compared to 100% grass silage (S) substrate, respectively. The SB diet produced on average more propionate (+28 mmol/mol) and consequently less acetate compared to the S diet. Irrespective of CH₄ emitter group, CNSL decreased predicted in vivo CH₄ (26.7 vs. 11.1 mL/ g of dry matter; DM) and stoichiometric CH₄ (CH₄VFA; 304 vs. 235 moles/mol VFA), with these being also reflected in decreased total gas production per unit of volatile fatty acids (VFA). Microbial structure was assessed on rumen fluid sampled prior to in vitro incubation, by sequencing of the V4 region of 16S rRNA gene. Principal coordinate analysis (PCoA) on operational taxonomic unit (OTU) did not show any differences between groups. Some differences appeared of relative abundance between groups in some specific OTUs mainly related to Prevotella. Genus Methanobrevibacter represented 93.7 ± 3.33% of the archaeal sequences. There were no clear differences between groups in relative abundance of Methanobrevibacter.

Dietary Energy Level Impacts the Performance of Donkeys by Manipulating the Gut Microbiome and Metabolome

Considerable evidence suggests that dietary energy levels and gut microbiota are pivotal for animal health and productivity. However, little information exists about the correlations among dietary energy level, performance, and the gut microbiota and metabolome of donkeys. The objective of this study was to investigate the mechanisms by which dietary energy content dictates the growth performance by modulating the intestinal microbiome and metabolome of donkeys. Thirty-six nine-month-old male Dezhou donkeys with similar body weights were randomly assigned to two groups fed low- or high-energy diets (LE or HE). The results showed that donkeys fed HE had increased (p < 0.05) the average daily gain (ADG) and feed efficiency (G/F) compared with those that received LE diet. The gut microbiota in both groups was dominated by the phyla Firmicutes and Bacteroidetes regardless of the dietary energy level. However, feeding HE to donkeys significantly decreased (p < 0.05) the ratio of Firmicutes to Bacteroidetes (F/B). Compared to the LE group, feeding HE specifically increased the abundances of unidentified_Prevotellaceae (p = 0.02) while decreasing the richness of unidentified_Ruminococcaceae (p = 0.05). Compared to the LE group, feeding the HE diet significantly (p < 0.05) upregulated certain metabolic pathways involving the aspartate metabolism and the urea cycle. In addition, the increased bacteria and metabolites in the HE-fed group exhibited a positive correlation with improved growth performance of donkeys. Taken together, feeding the HE diet increased the richness of Prevotellaceae and upregulated growth-related metabolic pathways, which may have contributed to the ameliorated growth performance of donkeys. Thus, it is a recommendable dietary strategy to feed HE diets to fattening donkeys for superior product performance and feed efficiency.

Genomic loci and genetic parameters for uterine diseases in first-parity Holstein cows and associations with milk production and fertility

Based on the clinical stage (e.g., vaginal discharge) and bacterial species, several forms of uterine diseases (UD) exist and can be classified as different traits [i.e., different stages of endometritis (EM) and metritis (MET)], which may differ in their genetic background and causal physiological mechanisms. Consequently, the present study aimed to study (1) the effect of UD on 305-d lactation and fertility, (2) the estimation of heritabilities for UD traits using pedigree- and SNP-based relationships, and (3) genome-wide associations to detect significant SNP markers and to infer candidate genes for UD traits. The data set contained herd manager and veterinarian recorded UD traits of 14,810 first-lactating genotyped Holstein cows from 63 large-scale contract herds. Binary defined UD traits (healthy or diseased) according to the clinical stage were endometritis catarrhalis (EM I), endometritis mucopurulenta (EM II), endometritis purulenta (EM III), pyometra (EM IV), endometritis (EM_SOD; superordinate diagnosis = no specific clinical stage defined), and MET. The binary defined trait UDall included all EM and MET diagnoses. The prevalence of UDall was 26.7%. The effect of UD on 305-d lactation and fertility was estimated via linear and generalized linear mixed models. We applied linear single-trait animal models and threshold models to estimate pedigree- and SNP-based heritabilities for UD traits, and bivariate linear models for genetic correlation estimations between UDall with 305-d lactation and fertility traits. A diagnosis for UDall had significant unfavorable effects on the female fertility traits calving interval, interval from calving to first service, days open, and nonreturn rate after 90 d, but was unrelated to 305-d lactation records for production traits milk yield, protein yield, and fat yield. Heritabilities for UDall and EM stages were close to zero, displaying maximal values of 0.05 for pedigree and 0.07 for SNP-based relationship matrices. For MET, pedigree- and SNP-based heritabilities were <0.001 and 0.07, respectively. Genetic correlations ranged from 0.20 to 0.31 between UDall with 305-d milk, protein, and fat yield, and from 0.17 to 0.40 with fertility traits. The GWAS revealed 5 SNP on bovine chromosomes (BTA) 1, 8, 10, 23 for UDall, 5 SNP on BTA 26 for EM I, 1 SNP on BTA 19 for EM II, 4 SNP on BTA 2, 18, 20, 25 for EM III, and 4 SNP on BTA 4, 16, 20 for EM IV above the significance threshold. For EM_SOD, we identified 15 significantly associated SNP on 4 chromosomes, and 4 significant SNP on BTA 3, 20, 22, 28 for MET. Marker associations for UD traits were annotated to 24 potential candidate genes using the ENSEMBL database. Six of these genes were previously reported to be involved in uterine defense mechanisms or in endometritis. Further detected genes contribute to immune response mechanisms during bacterial infections. Different SNP significantly influenced different UD stages, explaining the inter-individual variations in clinical severity of uterine infections.

Analysis of mouse faecal dysbiosis, during the development of cachexia, induced by transplantation with Lewis lung carcinoma cells

Cachexia (CC) is a complex wasting syndrome that significantly affects life quality and life expectancy among cancer patients. Original studies, in which CC was induced in mouse models through inoculation with BaF and C26 tumour cells, demonstrated that CC development correlates with bacterial gut dysbiosis in these animals. In both cases, a common microbial signature was observed, based on the expansion of Enterobacteriaceae in the gut of CC animals. However, these two types of tumours induce unique microbial profiles, suggesting that different CC induction mechanisms significantly impact the outcome of gut dysbiosis. The present study sought to expand the scope of such analyses by characterizing the CC-associated dysbiosis that develops when mice are inoculated with Lewis lung carcinoma (LLC) cells, which constitutes one of the most widely employed mechanisms for CC induction. Interestingly, Enterobacteriaceae expansion is also observed in LLC-induced CC. However, the dysbiosis identified herein displays a more complex pattern, involving representatives from seven different bacterial phyla, which were consistently identified across successive levels of taxonomic hierarchy. These results are supported by a predictive analysis of gene content, which identified a series of functional/structural changes that potentially occur in the gut bacterial population of these animals, providing a complementary and alternative approach to microbiome analyses based solely on taxonomic classification.

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.

Gut microbiome colonization and development in neonatal ruminants: Strategies, prospects, and opportunities

Colonization and development of the gut microbiome is a crucial consideration for optimizing the health and performance of livestock animals. This is mainly attributed to the fact that dietary and management practices greatly influence the gut microbiota, subsequently leading to changes in nutrient utilization and immune response. A favorable microbiome can be implanted through dietary or management interventions of livestock animals, especially during early life. In this review, we explore all the possible factors (for example gestation, colostrum, and milk feeding, drinking water, starter feed, inoculation from healthy animals, prebiotics/probiotics, weaning time, essential oil and transgenesis), which can influence rumen microbiome colonization and development. We discuss the advantages and disadvantages of potential strategies used to manipulate gut development and microbial colonization to improve the production and health of newborn calves at an early age when they are most susceptible to enteric disease. Moreover, we provide insights into possible interventions and their potential effects on rumen development and microbiota establishment. Prospects of latest techniques like transgenesis and host genetics have also been discussed regarding their potential role in modulation of rumen microbiome and subsequent effects on gut development and performance in neonatal ruminants.

Rumen Fermentation, Digestive Enzyme Activity, and Bacteria Composition between Pre-Weaning and Post-Weaning Dairy Calves

Simple Summary

Weaning is very important for young ruminants. At this stage, calves’ main source of nutrients is transferred from milk into solid feed, such as starter and roughage. At the same time, the rumen function of calves undergoes tremendous changes, such as bacteria, which are the main players in rumen function. Our research found that the rumen bacteria network of post-weaning calves was more complex. The fermentation end products, such as acetate, propionate, and butyrate, were higher in the post-weaning calves than the pre-weaning group. However, digestive enzymes such as protease, carboxymethyl cellulase, cellobiohydrolase, and glucosidase were lower in the post-weaning calves than the pre-weaning calves. These findings provided useful information for reference regarding the feeding management of calves.

Abstract

To better understand the transition of rumen function during the weaning period in dairy calves, sixteen Holstein dairy calves were selected and divided into two groups: pre-weaning (age = 56 ± 7 day, n = 8) and post-weaning (age = 80 ± 6 day, n = 8). The rumen fluid was obtained by an oral gastric tube. The rumen fermentation profile, enzyme activity, bacteria composition, and their inter-relationship were investigated. The results indicated that the post-weaning calves had a higher rumen acetate, propionate, butyrate, and microbial crude protein (MCP) than the pre-weaning calves (p < 0.05). The rumen pH in the post-weaning calves was lower than the pre-weaning calves (p < 0.05). The protease, carboxymethyl cellulase, cellobiohydrolase, and glucosidase in the post-weaning calves had a lower trend than the pre-weaning calves (0.05 < p < 0.1). There was no difference in α and β diversity between the two groups. Linear discriminant analysis showed that the phylum of Fibrobacteres in the post-weaning group was higher than the pre-weaning group. At the genus level, Shuttleworthia, Rikenellaceae, Fibrobacter, and Syntrophococcus could be worked as the unique bacteria in the post-weaning group. The rumen bacteria network node degree in the post-weaning group was higher than the pre-weaning group (16.54 vs. 9.5). The Shuttleworthia genus was highly positively correlated with MCP, propionate, total volatile fatty acid, glucosidase, acetate, and butyrate (r > 0.65, and p < 0.01). Our study provided new information about the rumen enzyme activity and its relationship with bacteria, which help us to better understand the effects of weaning on the rumen function.

The microbiome extends host evolutionary potential

The microbiome shapes many host traits, yet the biology of microbiomes challenges traditional evolutionary models. Here, we illustrate how integrating the microbiome into quantitative genetics can help untangle complexities of host-microbiome evolution. We describe two general ways in which the microbiome may affect host evolutionary potential: by shifting the mean host phenotype and by changing the variance in host phenotype in the population. We synthesize the literature across diverse taxa and discuss how these scenarios could shape the host response to selection. We conclude by outlining key avenues of research to improve our understanding of the complex interplay between hosts and microbiomes.

Data of bacterial community dynamics resulting from total rumen content exchange in beef cattle

OBJECTIVES

Extensive efforts have been made to characterize the rumen microbiome under various conditions. However, few studies have addressed the long-term impacts of ruminal microbiome dysbiosis and the extent of host control over microbiome stability. These data can also inform host-microbial symbioses. The objective was to develop preliminary data to measure the changes that occur in the rumen bacterial communities following a rumen content exchange to understand the effects major perturbations may impart upon the rumen microbiome, which may be host-driven.

DATA DESCRIPTION

We report here an initial rumen content exchange between two SimAngus (Simmental/Angus) non-pregnant, non-lactating cows of ~ 6 years of age weighing 603.4 ± 37.5 kg. To measure bacterial community succession and acclimation following the exchange, rumen content was collected via rumen cannula at the beginning of the study immediately prior to and following the rumen content exchange, and weekly for 12 weeks. The V4 hypervariable region of the 16S rRNA gene was targeted for DNA sequencing and bacterial analysis. Over 12 weeks, numerous genera and diversity varied, before partial return to pre-exchange metrics. These preliminary data help support potential host control for the rumen microbiome, aiding in efforts to define bovine host-microbe relationships.

Opportunities and limits of combining microbiome and genome data for complex trait prediction

Background

Analysis and prediction of complex traits using microbiome data combined with host genomic information is a topic of utmost interest. However, numerous questions remain to be answered: how useful can the microbiome be for complex trait prediction? Are estimates of microbiability reliable? Can the underlying biological links between the host’s genome, microbiome, and phenome be recovered?

Methods

Here, we address these issues by (i) developing a novel simulation strategy that uses real microbiome and genotype data as inputs, and (ii) using variance-component approaches (Bayesian Reproducing Kernel Hilbert Space (RKHS) and Bayesian variable selection methods (Bayes C)) to quantify the proportion of phenotypic variance explained by the genome and the microbiome. The proposed simulation approach can mimic genetic links between the microbiome and genotype data by a permutation procedure that retains the distributional properties of the data.

Results

Using real genotype and rumen microbiota abundances from dairy cattle, simulation results suggest that microbiome data can significantly improve the accuracy of phenotype predictions, regardless of whether some microbiota abundances are under direct genetic control by the host or not. This improvement depends logically on the microbiome being stable over time. Overall, random-effects linear methods appear robust for variance components estimation, in spite of the typically highly leptokurtic distribution of microbiota abundances. The predictive performance of Bayes C was higher but more sensitive to the number of causative effects than RKHS. Accuracy with Bayes C depended, in part, on the number of microorganisms’ taxa that influence the phenotype.

Conclusions

While we conclude that, overall, genome-microbiome-links can be characterized using variance component estimates, we are less optimistic about the possibility of identifying the causative host genetic effects that affect microbiota abundances, which would require much larger sample sizes than are typically available for genome-microbiome-phenome studies. The R code to replicate the analyses is in https://github.com/miguelperezenciso/simubiome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00658-7.

Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

In response to the increased concern over agriculture's contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH₄) per cow per year after accounting for replacement costs, ranging 8.9-323 kg CH₄/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.

Microbiomes of Various Maternal Body Systems Are Predictive of Calf Digestive Bacterial Ecology

Body systems once thought sterile at birth instead have complex and sometimes abundant microbial ecosystems. However, relationships between dam and calf microbial ecosystems are still unclear. The objectives of this study were to (1) characterize the various maternal and calf microbiomes during peri-partum and post-partum periods and (2) examine the influence of the maternal microbiome on calf fecal microbiome composition during the pre-weaning phase. Multiparous Holstein cows were placed in individual, freshly bedded box stalls 14 d before expected calving. Caudal vaginal fluid samples were collected approximately 24 h before calving and dam fecal, oral, colostrum, and placenta samples were collected immediately after calving. Calf fecal samples were collected at birth (meconium) and 24 h, 7 d, 42 d, and 60 d of age. Amplicons covering V4 16S rDNA regions were generated using DNA extracted from all samples and were sequenced using 300 bp paired end Illumina MiSeq sequencing. Spearman rank correlations were performed between genera in maternal and calf fecal microbiomes. Negative binomial regression models were created for genera in calf fecal samples at each time point using genera in maternal microbiomes. We determined that Bacteroidetes dominated the calf fecal microbiome at all time points (relative abundance ≥42.55%) except for 24 h post-calving, whereas Proteobacteria were the dominant phylum (relative abundance = 85.10%). Maternal fecal, oral, placental, vaginal, and colostrum microbiomes were significant predictors of calf fecal microbiome throughout pre-weaning. Results indicate that calf fecal microbiome inoculation and development may be derived from various maternal sources. Maternal microbiomes could be used to predict calf microbiome development, but further research on the environmental and genetic influences is needed.

Compositional analysis of ruminal bacteria from ewes selected for somatic cell score and milk persistency

Ruminants are dependent on their rumen microbiota to obtain energy from plants. The composition of the microbiome was well-known to be associated with health status, and production traits, but published results are difficult to reproduce due to large sources of variation. The objectives of this study were to evaluate the associations of ruminal microbiota and its association with genetic lines selected by somatic cell score (SCS) or milk persistency (PERS), as well as milk production, somatic cell score, fat and protein contents, and fatty acids and proteins of milk, using the principles of compositional data. A large sample of 700 Lacaune dairy ewes from INRAE La Fage feeding the same diet and belonging to two divergent genetic lines selected for SCS or PERS was used. The ruminal bacterial metagenome was sequenced using the 16S rRNA gene, resulting in 2,059 operational taxonomic units affiliated with 112 genera. The abundance data were centred log-transformed after the replacement of zeros with the geometric Bayesian method. Discriminant analysis of the SCS showed differences between SCS+ and SCS- ewes, while for PERS no difference was obtained. Milk traits as fat content, protein content, saturated fatty acids and caseins of milk were negatively associated with Prevotella (R = [-0.08;-0.16]), Suttonella (R = [-0.09;-0.16]) and Ruminococcus (R = [-0.08;-0.16]), and positively associated with Lachnospiraceae (R = [0.09;0.16]) and Christensenellaceae (R = [0.09;0.16]). Our findings provide an understanding of the application of compositional data to microbiome analysis, and the potential association of Prevotella, Suttonella, Ruminococcaceae and Lachnospiraceae with milk production traits such as milk fatty acids and proteins in dairy sheep.

Review: Perspective on high-performing dairy cows and herds

Milk and dairy products provide highly sustainable concentrations of essential amino acids and other required nutrients for humans; however, amount of milk currently produced per dairy cow globally is inadequate to meet future needs. Higher performing dairy cows and herds produce more milk with less environmental impact per kg than lower performing cows and herds. In 2018, 15.4% of the world's dairy cows produced 45.4% of the world's dairy cow milk, reflecting the global contribution of high-performing cows and herds. In high-performing herds, genomic evaluations are utilized for multiple trait selection, welfare is monitored by remote sensing, rations are formulated at micronutrient levels, health care is focused on prevention and reproduction is managed with precision. Higher performing herds require more inputs and generate more waste products per cow, thus innovations in environmental management on such farms are essential for lowering environmental impacts. Our focus is to provide perspectives on technologies and practices that contribute most to sustainable production of milk from high-performing dairy cows and herds.

Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. III: Relation with solid passage rate and pH on prokaryotic fatty acid profile and community in continuous culture

Our objectives were to evaluate potential interactions in culture conditions that influence how exogenously dosed branched-chain VFA (BCVFA) would be recovered as elongated fatty acids (FA) or would affect bacterial populations. A 2 × 2 × 2 factorial arrangement of treatments evaluated 3 factors: (1) without versus with BCVFA (0 vs. 2 mmol/d each of isobutyrate, isovalerate, and 2-methylbutyrate; each dose was partially substituted with ¹³C-enriched tracers before and during the collection period); (2) high versus low pH (ranging diurnally from 6.3 to 6.8 vs. 5.7 to 6.2); and (3) low versus high particulate-phase passage rate (k_p; 2.5 vs. 5.0%/h) in continuous cultures administered a 50:50 forage:concentrate diet twice daily. Samples of effluent were collected and composited before harvesting bacteria from which FA and DNA were extracted. Profiles and enrichments of FA in bacteria were evaluated by gas chromatography and isotope-ratio mass spectrometry. The ¹³C enrichment in bacterial FA was calculated as percentage recovery of dosed ¹³C-labeled BCVFA. Dosing BCVFA increased the even-chain iso-FA, preventing the reduced concentration at higher k_p and potentially as a physiological response to decreased pH. However, decreasing pH decreased recovery of ¹³C in these even-chain FA, suggesting greater reliance on isobutyrate produced from degradation of dietary valine. The iso-FA were decreased, whereas anteiso-FA and 16:0 increased with decreasing pH. Thus, 2-methylbutyrate still appeared to be important as a precursor for anteiso-FA to counter the increased rigidity of bacterial membranes that had more saturated straight-chain FA when pH decreased. Provision of BCVFA stimulated the relative sequence abundance of Fibrobacter and Treponema, both of which require isobutyrate and 2-methylbutyrate. Numerous bacterial community members were shifted by low pH, including increased Prevotella and genera within the phylum Proteobacteria, at the expense of members within phylum Firmicutes. Because of relatively few interactions with pH and k_p, supplementation of BCVFA can stimulate neutral detergent fiber degradability via key fibrolytic bacteria across a range of conditions. Decreasing pH shifted bacterial populations and their FA composition, suggesting that further research is needed to distinguish pH from dietary changes.

Review: More effective linkages between science and policy are needed to minimize the negative environmental impacts of livestock production

Animals form an integral part of our planetary ecosystem but balance is critical to effective ecosystem functioning as demand for livestock products has increased, greater numbers of domesticated livestock have created an imbalance and hence had a negative impact on a number of ecosystem services which means that life as we know it will become unsustainable. Policies and technology advances have helped to manage the impact but more needs to be done. The aim of this paper is to highlight ways in which better knowledge of animal science, and other disciplines, can both harness technology and inform policy to work towards a sustainable balance between livestock and the environment. Effective policies require simple, quantifiable indicators against which to set targets and monitor progress. Indicators are clear for water pollution, but more complex for biodiversity. Hence, more progress has been made with the former. It is not yet possible to measure the impacts of changes in livestock management on greenhouse gas emissions per se at a farm level and progress has been slower, although new technologies are emerging. With respect to land use, the simple indicator of area has been used, but total area is oversimplistic. Our analysis of land suitability and use highlights a relatively overlooked role of livestock in acting as a 'buffer' to use by-products and grains which do not meet the standards for processing by industry during years of inclement weather, which in the past has provided an 'insurance policy' for farmers. Since extreme weather events are increasing in frequency with climate change, this role for livestock may be more important in future. The conclusions of the review with respect to strengthening the links between research and policy are i) to encourage animal scientists to identify the relevant environmental indicators, work with the cutting edge experts developing technologies to measure these cost-effectively and across a range of relevant livestock systems and ii) to work with the feed industry to optimize diets not just in terms of least cost financially but also least 'cost' in terms of global carbon flux and engage in dialogue with the food industry and policy makers on regulations for grain quality.

Using Structural Equation Modeling to Understand Interactions Between Bacterial and Archaeal Populations and Volatile Fatty Acid Proportions in the Rumen

Microbial syntrophy (obligate metabolic mutualism) is the hallmark of energy-constrained anaerobic microbial ecosystems. For example, methanogenic archaea and fermenting bacteria coexist by interspecies hydrogen transfer in the complex microbial ecosystem in the foregut of ruminants; however, these synergistic interactions between different microbes in the rumen are seldom investigated. We hypothesized that certain bacteria and archaea interact and form specific microbial cohorts in the rumen. To this end, we examined the total (DNA-based) and potentially metabolically active (cDNA-based) bacterial and archaeal communities in rumen samples of dairy cows collected at different times in a 24 h period. Notably, we found the presence of distinct bacterial and archaeal networks showing potential metabolic interactions that were correlated with molar proportions of specific volatile fatty acids (VFAs). We employed hypothesis-driven structural equation modeling to test the significance of and to quantify the extent of these relationships between bacteria-archaea-VFAs in the rumen. Furthermore, we demonstrated that these distinct microbial networks were host-specific and differed between cows indicating a natural variation in specific microbial networks in the rumen of dairy cows. This study provides new insights on potential microbial metabolic interactions in anoxic environments that have broader applications in methane mitigation, energy conservation, and agricultural production.

Green Milk From Contented Cows: Is It Possible?

The dairy industry is open to criticism on several fronts: obesity and ill health among the affluent, high demand for crops that could be consumed more sustainably and more equitably by ourselves, environmental damage and climate change, and abuse of animal welfare through production diseases and denial of normal patterns of behaviour. All these criticisms are valid. It is necessary therefore to examine in depth the nature and extent of specific problems to see which, if any, are inevitable, which can be mitigated and which can be avoided altogether. Dairy cattle, like all ruminants, can be sustained wholly, or in part on complementary feeds; grasses and crop residues that cannot be fed directly to humans. Fed appropriate diets dairy cows can produce more energy and protein for human consumption than they consume. The greenhouse gas, methane is an inevitable consequence of rumen fermentation. High yielding cows in confinement produce less methane per litre of milk. There is some scope for reducing methane production through manipulation of rumen fermentation but the impact is likely to be small. The most serious welfare abuses can be linked to genetic and management strategies designed to maximise milk yield from individual cows. These manifest in production diseases and metabolic exhaustion, both leading to premature culling. All these problems; too much milk, too much food waste, too much methane, too many stressed cows, are matters of degree. The poison is in the dose. Thus, solutions will not come from radical advances in biological science but public and political exercises in moderation.

Assessing the Response of Ruminal Bacterial and Fungal Microbiota to Whole-Rumen Contents Exchange in Dairy Cows

A major goal for the dairy industry is to improve overall milk production efficiency (MPE). With the advent of next-generation sequencing and advanced methods for characterizing microbial communities, efforts are underway to improve MPE by manipulating the rumen microbiome. Our previous work demonstrated that a near-total exchange of whole rumen contents between pairs of lactating Holstein dairy cows of disparate MPE resulted in a reversal of MPE status for ∼10 days: historically high-efficiency cows decreased in MPE, and historically low-efficiency cows increased in MPE. Importantly, this switch in MPE status was concomitant with a reversal in the ruminal bacterial microbiota, with the newly exchanged bacterial communities reverting to their pre-exchange state. However, this work did not include an in-depth analysis of the microbial community response or an interrogation of specific taxa correlating to production metrics. Here, we sought to better understand the response of rumen communities to this exchange protocol, including consideration of the rumen fungi. Rumen samples were collected from 8 days prior to, and 56 days following the exchange and were subjected to 16S rRNA and ITS amplicon sequencing to assess bacterial and fungal community composition, respectively. Our results show that the ruminal fungal community did not differ significantly between hosts of disparate efficiency prior to the exchange, and no change in community structure was observed over the time course. Correlation of microbial taxa to production metrics identified one fungal operational taxonomic unit (OTU) in the genus Neocallimastix that correlated positively to MPE, and several bacterial OTUs classified to the genus Prevotella. Within the Prevotella, Prevotella_1 was found to be more abundant in high-efficiency cows whereas Prevotella_7 was more abundant in low-efficiency cows. Overall, our results suggest that the rumen bacterial community is a primary microbial driver of host efficiency, that the ruminal fungi may not have as significant a role in MPE as previously thought, and that more work is needed to better understand the functional roles of specific ruminal microbial community members in modulating MPE.

Degradation of the Indospicine Toxin from Indigofera spicata by a Mixed Population of Rumen Bacteria

The leguminous plant species, Indigofera linnaei and Indigofera spicata are distributed throughout the rangeland regions of Australia and the compound indospicine (L-2-amino-6-amidinohexanoic acid) found in these palatable forage plants acts as a hepatotoxin and can accumulate in the meat of ruminant livestock and wild camels. In this study, bovine rumen fluid was cultivated in an in vitro fermentation system provided with Indigofera spicata plant material and the ability of the resulting mixed microbial populations to degrade indospicine was determined using UPLC–MS/MS over a 14 day time period. The microbial populations of the fermentation system were determined using 16S rRNA gene amplicon sequencing and showed distinct, time-related changes occurring as the rumen-derived microbes adapted to the fermentation conditions and the nutritional substrates provided by the Indigofera plant material. Within eight days of commencement, indospicine was completely degraded by the microbes cultivated within the fermenter, forming the degradation products 2-aminopimelamic acid and 2-aminopimelic acid within a 24 h time period. The in vitro fermentation approach enabled the development of a specifically adapted, mixed microbial population which has the potential to be used as a rumen drench for reducing the toxic side-effects and toxin accumulation associated with ingestion of Indigofera plant material by grazing ruminant livestock.

Phylogeny- and Abundance-Based Metrics Allow for the Consistent Comparison of Core Gut Microbiome Diversity Indices Across Host Species

The filtering of gut microbial datasets to retain high prevalence taxa is often performed to identify a common core gut microbiome that may be important for host biological functions. However, prevalence thresholds used to identify a common core are highly variable, and it remains unclear how they affect diversity estimates and whether insights stemming from core microbiomes are comparable across studies. We hypothesized that if macroecological patterns in gut microbiome prevalence and abundance are similar across host species, then we would expect that increasing prevalence thresholds would yield similar changes to alpha diversity and beta dissimilarity scores across host species datasets. We analyzed eight gut microbiome datasets based on 16S rRNA gene amplicon sequencing and collected from different host species to (1) compare macroecological patterns across datasets, including amplicon sequence variant (ASV) detection rate with sequencing depth and sample size, occupancy-abundance curves, and rank-abundance curves; (2) test whether increasing prevalence thresholds generate universal or host-species specific effects on alpha and beta diversity scores; and (3) test whether diversity scores from prevalence-filtered core communities correlate with unfiltered data. We found that gut microbiomes collected from diverse hosts demonstrated similar ASV detection rates with sequencing depth, yet required different sample sizes to sufficiently capture rare ASVs across the host population. This suggests that sample size rather than sequencing depth tends to limit the ability of studies to detect rare ASVs across the host population. Despite differences in the distribution and detection of rare ASVs, microbiomes exhibited similar occupancy-abundance and rank-abundance curves. Consequently, increasing prevalence thresholds generated remarkably similar trends in standardized alpha diversity and beta dissimilarity across species datasets until high thresholds above 70%. At this point, diversity scores tended to become unpredictable for some diversity measures. Moreover, high prevalence thresholds tended to generate diversity scores that correlated poorly with the original unfiltered data. Overall, we recommend that high prevalence thresholds over 70% are avoided, and promote the use of diversity measures that account for phylogeny and abundance (Balance-weighted phylogenetic diversity and Weighted Unifrac for alpha and beta diversity, respectively), because we show that these measures are insensitive to prevalence filtering and therefore allow for the consistent comparison of core gut microbiomes across studies without the need for prevalence filtering.

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.

Stability Assessment of the Rumen Bacterial and Archaeal Communities in Dairy Cows Within a Single Lactation and Its Association With Host Phenotype

Better characterization of changes in the rumen microbiota in dairy cows over the lactation period is crucial for understanding how microbial factors may potentially be interacting with host phenotypes. In the present study, we characterized the rumen bacterial and archaeal community composition of 60 lactating Holstein dairy cows (33 multiparous and 27 primiparous), sampled twice within the same lactation with a 122 days interval. Firmicutes and Bacteroidetes dominated the rumen bacterial community and showed no difference in relative abundance between samplings. Two less abundant bacterial phyla (SR1 and Proteobacteria) and an archaeal order (Methanosarcinales), on the other hand, decreased significantly from the mid-lactation to the late-lactation period. Moreover, between-sampling stability assessment of individual operational taxonomic units (OTUs), evaluated by concordance correlation coefficient (C-value) analysis, revealed the majority of the bacterial OTUs (6,187 out of 6,363) and all the 79 archaeal OTUs to be unstable over the investigated lactation period. The remaining 176 stable bacterial OTUs were mainly assigned to Prevotella, unclassified Prevotellaceae, and unclassified Bacteroidales. Milk phenotype-based screening analysis detected 32 bacterial OTUs, mainly assigned to unclassified Bacteroidetes and Lachnospiraceae, associated with milk fat percentage, and 6 OTUs, assigned to Ruminococcus and unclassified Ruminococcaceae, associated with milk protein percentage. These OTUs were only observed in the multiparous cows. None of the archaeal OTUs was observed to be associated with the investigated phenotypic parameters, including methane production. Co-occurrence analysis of the rumen bacterial and archaeal communities revealed Fibrobacter to be positively correlated with the archaeal genus vadinCA11 (Pearson r = 0.76) and unclassified Methanomassiliicoccaceae (Pearson r = 0.64); vadinCA11, on the other hand, was negatively correlated with Methanobrevibacter (Pearson r = –0.56). In conclusion, the rumen bacterial and archaeal communities of dairy cows displayed distinct stability at different taxonomic levels. Moreover, specific members of the rumen bacterial community were observed to be associated with milk phenotype parameters, however, only in multiparous cows, indicating that dairy cow parity could be one of the driving factors for host–microbe interactions.

Gut Microbial Composition Differs Extensively among Indian Native Chicken Breeds Originated in Different Geographical Locations and a Commercial Broiler Line, but Breed-Specific, as Well as Across-Breed Core Microbiomes, Are Found

Gut microbiota plays an important role in the health and performance of the host. Characterizations of gut microbiota, core microbiomes, and microbial networks in different chicken breeds are expected to provide clues for pathogen exclusion, improving performance or feed efficiency. Here, we characterized the gut microbiota of “finishing” chickens (at the end of production life) of indigenous Indian Nicobari, Ghagus, and Aseel breeds, originating from the Nicobari island, coastal India, and the Indian mainland, respectively, as well as a global commercial broiler line, VenCobb 400, using 16S rDNA amplicon sequencing. We found that diversity, as well as richness of microbiota, was higher in indigenous breeds than in the broiler line. Beta diversity analysis indicated the highest overlap between Ghagus and Nicobari breeds and a very low overlap between the broiler line and all indigenous breeds. Linear discriminant analysis effect size (LEfSe) revealed 82 breed- or line-specific phylotype operational taxonomic unit (OTU) level biomarkers. We confirm the presence of breed specific and across-breed core microbiomes. Additionally, we show the existence of breed specific complex microbial networks in all groups. This study provides the first (and comprehensive) insight into the gut microbiota of three indigenous breeds and one commercial broiler line of chickens reared without antimicrobials, and underscores the need to study microbial diversity in other indigenous breeds.

A method to the madness: Disentangling the individual forces that shape the rumen microbiome

The rumen microbiome - a remarkable example of obligatory symbiosis with high ecological and social relevance.

A multi-kingdom metabarcoding study on cattle grazing Alpine pastures discloses intra-seasonal shifts in plant selection and faecal microbiota

Diet selection by grazing livestock may affect animal performance as well as the biodiversity of grazed areas. Recent DNA barcoding techniques allow to assess dietary plant composition in faecal samples, which may be additionally integrated by the description of gut microbiota. In this high throughput metabarcoding study, we investigated the diversity of plant, fungal and bacterial taxa in faecal samples of lactating cows of two breeds grazing an Alpine semi-natural grassland during summer. The estimated plant composition of the diet comprised 67 genera and 39 species, which varied remarkably during summer, suggesting a decline of the diet forage value with the advancing of the vegetative season. The fungal community included Neocallimastigomycota gut symbionts, but also Ascomycota and Basidiomycota plant parasite and coprophilous taxa, likely ingested during grazing. The proportion of ingested fungi was remarkably higher than in other studies, and varied during summer, although less than that observed for plants. Some variation related to breed was also detected. The gut bacterial taxa remained stable through the summer but displayed a breed-specific composition. The study provided insights in the reciprocal organisms' interactions affecting, and being affected by, the foraging behaviour: plants showed a high temporal variation, fungi a smaller one, while bacteria had practically none; conversely, the same kingdoms showed the opposite gradient of variation as respect to the animal host breed, as bacteria revealed to be the group mostly characterized by host-specificity.

Genomic and functional analyses of fungal and bacterial consortia that enable lignocellulose breakdown in goat gut microbiomes

The herbivore digestive tract is home to a complex community of anaerobic microbes that work together to break down lignocellulose. These microbiota are an untapped resource of strains, pathways and enzymes that could be applied to convert plant waste into sugar substrates for green biotechnology. We carried out more than 400 parallel enrichment experiments from goat faeces to determine how substrate and antibiotic selection influence membership, activity, stability and chemical productivity of herbivore gut communities. We assembled 719 high-quality metagenome-assembled genomes (MAGs) that are unique at the species level. More than 90% of these MAGs are from previously unidentified herbivore gut microorganisms. Microbial consortia dominated by anaerobic fungi outperformed bacterially dominated consortia in terms of both methane production and extent of cellulose degradation, which indicates that fungi have an important role in methane release. Metabolic pathway reconstructions from MAGs of 737 bacteria, archaea and fungi suggest that cross-domain partnerships between fungi and methanogens enabled production of acetate, formate and methane, whereas bacterially dominated consortia mainly produced short-chain fatty acids, including propionate and butyrate. Analyses of carbohydrate-active enzyme domains present in each anaerobic consortium suggest that anaerobic bacteria and fungi employ mostly complementary hydrolytic strategies. The division of labour among herbivore anaerobes to degrade plant biomass could be harnessed for industrial bioprocessing.

Advances in Microbiome Research for Animal Health

Host-associated microbiomes contribute in many ways to the homeostasis of the metaorganism. The microbiome's contributions range from helping to provide nutrition and aiding growth, development, and behavior to protecting against pathogens and toxic compounds. Here we summarize the current knowledge of the diversity and importance of the microbiome to animals, using representative examples of wild and domesticated species. We demonstrate how the beneficial ecological roles of animal-associated microbiomes can be generally grouped into well-defined main categories and how microbe-based alternative treatments can be applied to mitigate problems for both economic and conservation purposes and to provide crucial knowledge about host-microbiota symbiotic interactions. We suggest a Customized Combination of Microbial-Based Therapies to promote animal health and contribute to the practice of sustainable husbandry. We also discuss the ecological connections and threats associated with animal biodiversity loss, microorganism extinction, and emerging diseases, such as the COVID-19 pandemic.

Fungal Dysbiosis Correlates with the Development of Tumor-Induced Cachexia in Mice

Cachexia (CC) is a devastating metabolic syndrome associated with a series of underlying diseases that greatly affects life quality and expectancy among cancer patients. Studies involving mouse models, in which CC was induced through inoculation with tumor cells, originally suggested the existence of a direct correlation between the development of this syndrome and changes in the relative proportions of several bacterial groups present in the digestive tract. However, these analyses have focus solely on the characterization of bacterial dysbiosis, ignoring the possible existence of changes in the relative populations of fungi, during the development of CC. Thus, the present study sought to expand such analyses, by characterizing changes that occur in the gut fungal population (mycobiota) of mice, during the development of cancer-induced cachexia. Our results confirm that cachectic animals, submitted to Lewis lung carcinoma (LLC) transplantation, display significant differences in their gut mycobiota, when compared to healthy controls. Moreover, identification of dysbiotic fungi showed remarkable consistency across successive levels of taxonomic hierarchy. Many of these fungi have also been associated with dysbioses observed in a series of gut inflammatory diseases, such as obesity, colorectal cancer (CRC), myalgic encephalomyelitis (ME) and inflammatory bowel disease (IBD). Nonetheless, the dysbiosis verified in the LLC model of cancer cachexia seems to be unique, presenting features observed in both obesity (reduced proportion of Mucoromycota) and CRC/ME/IBD (increased proportions of Sordariomycetes, Saccharomycetaceae and Malassezia). One species of Mucoromycota (Rhyzopus oryzae) stands out as a promising probiotic candidate in adjuvant therapies, aimed at treating and/or preventing the development of CC.

Effect of SOP “STAR COW” on Enteric Gaseous Emissions and Dairy Cattle Performance

Feed additives have received increasing attention as a viable means to reduce enteric emissions from ruminants, which contribute to total anthropogenic methane (CH4) emissions. The aim of this study was to investigate the efficacy of the commercial feed additive SOP STAR COW (SOP) to reduce enteric emissions from dairy cows and to assess potential impacts on milk production. Twenty cows were blocked by parity and days in milk and randomly assigned to one of two treatment groups (n = 10): supplemented with 8 g/day SOP STAR COW, and an unsupplemented control group. Enteric emissions were measured in individual head chambers over a 12-h period, every 14 days for six weeks. SOP-treated cows over time showed a reduction in CH4 of 20.4% from day 14 to day 42 (p = 0.014), while protein % of the milk was increased (+4.9% from day 0 to day 14 (p = 0.036) and +6.5% from day 0 to day 42 (p = 0.002)). However, kg of milk protein remained similar within the SOP-treated cows over the trial period. The control and SOP-treated cows showed similar results for kg of milk fat and kg of milk protein produced per day. No differences in enteric emissions or milk parameters were detected between the control and SOP-treated cows on respective test days.

Genetic mechanisms underlying feed utilization and implementation of genomic selection for improved feed efficiency in dairy cattle

The economic importance of genetically improving feed efficiency has been recognized by cattle producers worldwide. It has the potential to considerably reduce costs, minimize environmental impact, optimize land and resource use efficiency, and improve the overall cattle industry’s profitability. Feed efficiency is a genetically complex trait that can be described as units of product output (e.g., milk yield) per unit of feed input. The main objective of this review paper is to present an overview of the main genetic and physiological mechanisms underlying feed utilization in ruminants and the process towards implementation of genomic selection for feed efficiency in dairy cattle. In summary, feed efficiency can be improved via numerous metabolic pathways and biological mechanisms through genetic selection. Various studies have indicated that feed efficiency is heritable, and genomic selection can be successfully implemented in dairy cattle with a large enough training population. In this context, some organizations have worked collaboratively to do research and develop training populations for successful implementation of joint international genomic evaluations. The integration of “-omics” technologies, further investments in high-throughput phenotyping, and identification of novel indicator traits will also be paramount in maximizing the rates of genetic progress for feed efficiency in dairy cattle worldwide.

Lower methane emissions were associated with higher abundance of ruminal Prevotella in a cohort of Colombian buffalos

Background

Ruminants burp massive amounts of methane into the atmosphere and significantly contribute to the deposition of greenhouse gases and the consequent global warming. It is therefore urgent to devise strategies to mitigate ruminant’s methane emissions to alleviate climate change. Ruminal methanogenesis is accomplished by a series of methanogen archaea in the phylum Euryarchaeota, which piggyback into carbohydrate fermentation by utilizing residual hydrogen to produce methane. Abundance of methanogens, therefore, is expected to affect methane production. Furthermore, availability of hydrogen produced by cellulolytic bacteria acting upstream of methanogens is a rate-limiting factor for methane production. The aim of our study was to identify microbes associated with the production of methane which would constitute the basis for the design of mitigation strategies.

Results

Moderate differences in the abundance of methanogens were observed between groups. In addition, we present three lines of evidence suggesting an apparent higher abundance of a consortium of Prevotella species in animals with lower methane emissions. First, taxonomic classification revealed increased abundance of at least 29 species of Prevotella. Second, metagenome assembly identified increased abundance of Prevotella ruminicola and another species of Prevotella. Third, metabolic profiling of predicted proteins uncovered 25 enzymes with homology to Prevotella proteins more abundant in the low methane emissions group.

Conclusions

We propose that higher abundance of ruminal Prevotella increases the production of propionic acid and, in doing so, reduces the amount of hydrogen available for methanogenesis. However, further experimentation is required to ascertain the role of Prevotella on methane production and its potential to act as a methane production mitigator.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-020-02037-6.

Association of gut microbiota with metabolism in juvenile Atlantic salmon

The gut microbiome plays a key role in animal health and metabolism through the intricate functional interconnection between the feed, gut microbes, and the host. Unfortunately, in aquaculture, the links between gut microbes and fish genetics and production phenotypes are not well understood.In this study, we investigate the associations between gut microbial communities, fish feed conversion, and fish genetics in the domestic Atlantic salmon. Microbial community composition was determined for 230 juvenile fish from 23 full-sib families and was then regressed on growth, carbon and nitrogen metabolism, and feed efficiency. We only found weak associations between host genetics and microbial composition. However, we did identify significant (p < 0.05) associations between the abundance of three microbial operational taxonomical units (OTUs) and fish metabolism phenotypes. Two OTUs were associated with both carbon metabolism in adipose tissue and feed efficiency, while a third OTU was associated with weight gain.In conclusion, this study demonstrates an intriguing association between host lipid metabolism and the gut microbiota composition in Atlantic salmon. Video Abstract.

Anaerobic Fungi: Past, Present, and Future

Anaerobic fungi (AF) play an essential role in feed conversion due to their potent fiber degrading enzymes and invasive growth. Much has been learned about this unusual fungal phylum since the paradigm shifting work of Colin Orpin in the 1970s, when he characterized the first AF. Molecular approaches targeting specific phylogenetic marker genes have facilitated taxonomic classification of AF, which had been previously been complicated by the complex life cycles and associated morphologies. Although we now have a much better understanding of their diversity, it is believed that there are still numerous genera of AF that remain to be described in gut ecosystems. Recent marker-gene based studies have shown that fungal diversity in the herbivore gut is much like the bacterial population, driven by host phylogeny, host genetics and diet. Since AF are major contributors to the degradation of plant material ingested by the host animal, it is understandable that there has been great interest in exploring the enzymatic repertoire of these microorganisms in order to establish a better understanding of how AF, and their enzymes, can be used to improve host health and performance, while simultaneously reducing the ecological footprint of the livestock industry. A detailed understanding of AF and their interaction with other gut microbes as well as the host animal is essential, especially when production of affordable high-quality protein and other animal-based products needs to meet the demands of an increasing human population. Such a mechanistic understanding, leading to more sustainable livestock practices, will be possible with recently developed -omics technologies that have already provided first insights into the different contributions of the fungal and bacterial population in the rumen during plant cell wall hydrolysis.

Infectious Diseases, Livestock, and Climate: A Vicious Cycle?

Ruminant livestock are a significant contributor to global methane emissions. Infectious diseases have the potential to exacerbate these contributions by elevating methane outputs associated with animal production. With the increasing spread of many infectious diseases, the emergence of a vicious climate–livestock–disease cycle is a looming threat.

Genomic predictions for enteric methane production are improved by metabolome and microbiome data in sheep (Ovis aries)

Methane production from rumen methanogenesis contributes approximately 71% of greenhouse gas emissions from the agricultural sector. This study has performed genomic predictions for methane production from 99 sheep across 3 yr using a residual methane phenotype that is log methane yield corrected for live weight, rumen volume, and feed intake. Using genomic relationships, the prediction accuracies (as determined by the correlation between predicted and observed residual methane production) ranged from 0.058 to 0.220 depending on the time point being predicted. The best linear unbiased prediction algorithm was then applied to relationships between animals that were built on the rumen metabolome and microbiome. Prediction accuracies for the metabolome-based relationships for the two available time points were 0.254 and 0.132; the prediction accuracy for the first microbiome time point was 0.142. The second microbiome time point could not successfully predict residual methane production. When the metabolomic relationships were added to the genomic relationships, the accuracy of predictions increased to 0.274 (from 0.201 when only the genomic relationship was used) and 0.158 (from 0.081 when only the genomic relationship was used) for the two time points, respectively. When the microbiome relationships from the first time point were added to the genomic relationships, the maximum prediction accuracy increased to 0.247 (from 0.216 when only the genomic relationship was used), which was achieved by giving the genomic relationships 10 times more weighting than the microbiome relationships. These accuracies were higher than the genomic, metabolomic, and microbiome relationship matrixes achieved alone when identical sets of animals were used.