Fecal microbiota colonization dynamics in dairy heifers associated with early-life rumen microbiota modulation and gut health.

Early-life modulation of rumen microbiota holds promise for enhancing calf growth, health, and long-term production in ruminants. However, limited attention has been given to the impact of rumen microbiota modulation on the establishment of hindgut microbiota. In this study, fecal microbiota development was examined in identical twin calves for 12 months. The treatment group (T-group) received adult cow fresh rumen liquid inoculum during the pre-weaning period, while the control group did not (C-group). The effects of inoculum were assessed on calf gut health and as microbial seeding route into the hindgut. The early rumen modulation had no effect on age-related fecal microbiota development. The fecal bacterial community evolved gradually following dietary changes and categorized into pre-weaning and post-weaning communities. Bacterial richness increased with age and stabilized at month 9, while between-sample variation reduced in post-weaning samples. Archaeal load in fecal samples increased after month 4, while archaeal richness increased and stabilized in both groups by month 9. Between-sample similarity was higher during the pre-weaning period, with increased dissimilarity from month 4 onward. Anaerobic fungi were detected in feces at month 4, with richness peaking at month 7. Before month 6, fungal community composition distinctly differed from mature communities. When colostrum, calf rumen, and donor inoculum were evaluated as seeding sources for hindgut colonization, the calf's own rumen was identified as the primary seeding source for fecal bacteria and fungi. Colostrum was a source for several bacteria detected in feces, but these were of temporary importance until weaning. The donor inoculum had limited impact on gut health as diarrhea rates were similar between the T-group and C-group. In conclusion, early-life microbiota modulation shows potential in ruminant development. However, a more targeted approach with bacteria adapted to the hindgut environment may be necessary to modulate hindgut effectively. This research contributes to our understanding of the complex relationship between gut microbiota and calf health and growth.

Integrating microbial abundance time series with fermentation dynamics of the rumen microbiome via mathematical modelling.

The rumen represents a dynamic microbial ecosystem where fermentation metabolites and microbial concentrations change over time in response to dietary changes. The integration of microbial genomic knowledge and dynamic modelling can enhance our system-level understanding of rumen ecosystem's function. However, such an integration between dynamic models and rumen microbiota data is lacking. The objective of this work was to integrate rumen microbiota time series determined by 16S rRNA gene amplicon sequencing into a dynamic modelling framework to link microbial data to the dynamics of the volatile fatty acids (VFA) production during fermentation. For that, we used the theory of state observers to develop a model that estimates the dynamics of VFA from the data of microbial functional proxies associated with the specific production of each VFA. We determined the microbial proxies using CowPi to infer the functional potential of the rumen microbiota and extrapolate their functional modules from KEGG (Kyoto Encyclopedia of Genes and Genomes). The approach was challenged using data from an in vitro RUSITEC experiment and from an in vivo experiment with four cows. The model performance was evaluated by the coefficient of variation of the root mean square error (CRMSE). For the in vitro case study, the mean CVRMSE were 9.8% for acetate, 14% for butyrate and 14.5% for propionate. For the in vivo case study, the mean CVRMSE were 16.4% for acetate, 15.8% for butyrate and 19.8% for propionate. The mean CVRMSE for the VFA molar fractions were 3.1% for acetate, 3.8% for butyrate and 8.9% for propionate. Ours results show the promising application of state observers integrated with microbiota time series data for predicting rumen microbial metabolism.

The effects of residual energy intake on nutrient use, methane emissions and microbial composition in dairy cows.

For sustainable food production selection and breeding of feed efficient animals is crucial. The objective of this study was to evaluate whether multiparous dairy cows, ranked during their first lactation based on residual energy intake (REI) as efficient (low; L-REI) or inefficient (high; H-REI), differ in terms of nutrient use efficiency, methane emissions, rumen fermentation, and gut microbiota composition. Six L-REI and 6 H-REI cows were offered two diets with either a low or high proportion of concentrates (30 vs. 50% of DM) on two consecutive periods of 21 d. Gas exchanges, milk yield, feces and urine excretions were measured in open-circuit respiratory chambers. The results indicated that L-REI cows had higher methane yields (22.6 vs. 20.4 g/kg DM intake) and derived more energy (energy balance - 36.6 vs. - 16.9 MJ/d) and protein (N balance - 6.6 vs. 18.8 g/d) from the tissues to support similar milk yields compared to H-REI cows. Nutrient intake and digestibility were not affected by REI, and there were no interactions between REI and diet. Milk yield, milk production efficiency, and milk composition were not affected by REI except for milk urea concentration that was higher for L-REI cows (14.1 vs. 10.8 mg/100 ml). The rumen and fecal microbiota community structure and function were associated with both the diet and REI, but the diet effect was more pronounced. The current study identified several physiological mechanisms underlying the differences between high and low REI cows, but further studies are needed to distinguish the quantitative role of each mechanism.

Genomic selection for survival under naturally occurring Saprolegnia oomycete infection in farmed European whitefish Coregonus lavaretus.

Saprolegnia oomycete infection causes serious economic losses and reduces fish health in aquaculture. Genomic selection based on thousands of DNA markers is a powerful tool to improve fish traits in selective breeding programs. Our goal was to develop a single nucleotide polymorphism (SNP) marker panel and to test its use in genomic selection for improved survival against Saprolegnia infection in European whitefish Coregonus lavaretus, the second most important farmed fish species in Finland. We used a double digest restriction site associated DNA (ddRAD) genotyping by sequencing method to produce a SNP panel, and we tested it analyzing data from a cohort of 1,335 fish, which were measured at different times for mortality to Saprolegnia oomycete infection and weight traits. We calculated the genetic relationship matrix (GRM) from the genome-wide genetic data, integrating it in multivariate mixed models used for the estimation of variance components and genomic breeding values (GEBVs), and to carry out Genome-Wide Association Studies for the presence of quantitative trait loci (QTL) affecting the phenotypes in analysis. We identified one major QTL on chromosome 6 affecting mortality to Saprolegnia infection, explaining 7.7% to 51.3% of genetic variance, and a QTL for weight on chromosome 4, explaining 1.8% to 5.4% of genetic variance. Heritability for mortality was 0.20 to 0.43 on the liability scale, and heritability for weight was 0.44 to 0.53. The QTL for mortality showed an additive allelic effect. We tested whether integrating the QTL for mortality as a fixed factor, together with a new GRM calculated excluding the QTL from the genetic data, would improve the accuracy estimation of GEBVs. This test was done through a cross-validation approach, which indicated that the inclusion of the QTL increased the mean accuracy of the GEBVs by 0.28 points, from 0.33 to 0.61, relative to the use of full GRM only. The area under the curve of the receiver-operator curve for mortality increased from 0.58 to 0.67 when the QTL was included in the model. The inclusion of the QTL as a fixed effect in the model increased the correlation between the GEBVs of early mortality with the late mortality, compared to a model that did not include the QTL. These results validate the usability of the produced SNP panel for genomic selection in European whitefish and highlight the opportunity for modeling QTLs in genomic evaluation of mortality due to Saprolegnia infection.

Saprolegnia infection causes serious economic losses and reduces fish health in aquaculture. We created a novel set of genetic markers to use in the selective breeding of European whitefish to reduce mortality due to the fungus. Using genetic markers, we estimated how much different fish traits are determined by genetic variation, and thus what potential traits have to be selected. We observed that resistance to infection was controlled by both a genetic variant with a major effect on mortality and by many other variants with a small effect distributed across the genome. We tested whether we could increase the precision of genomic breeding values used in the selective breeding by explicitly adding the major genetic variant to the analysis, and we observed an increase in precision in our results. We conclude that directly including information about the major genetic variant increases the precision of our predictions, rather than assuming that all genetic variants each explain a small amount of the genetic variation.

Rumen Microbiota Predicts Feed Efficiency of Primiparous Nordic Red Dairy Cows.

Efficient feed utilization in dairy cows is crucial for economic and environmental reasons. The rumen microbiota plays a significant role in feed efficiency, but studies utilizing microbial data to predict host phenotype are limited. In this study, 87 primiparous Nordic Red dairy cows were ranked for feed efficiency during their early lactation based on residual energy intake, and the rumen liquid microbial ecosystem was subsequently evaluated using 16S rRNA amplicon and metagenome sequencing. The study used amplicon data to build an extreme gradient boosting model, demonstrating that taxonomic microbial variation can predict efficiency (rtest = 0.55). Prediction interpreters and microbial network revealed that predictions were based on microbial consortia and the efficient animals had more of the highly interacting microbes and consortia. Rumen metagenome data was used to evaluate carbohydrate-active enzymes and metabolic pathway differences between efficiency phenotypes. The study showed that an efficient rumen had a higher abundance of glycoside hydrolases, while an inefficient rumen had more glycosyl transferases. Enrichment of metabolic pathways was observed in the inefficient group, while efficient animals emphasized bacterial environmental sensing and motility over microbial growth. The results suggest that inter-kingdom interactions should be further analyzed to understand their association with the feed efficiency of animals.

Effect of a garlic and citrus extract supplement on performance, rumen fermentation, methane production, and rumen microbiome of dairy cows.

The aim of this trial was to determine the effect of a garlic and citrus extract supplement (GCE) on the performance, rumen fermentation, methane emissions, and rumen microbiome of dairy cows. Fourteen multiparous Nordic Red cows in mid-lactation from the research herd of Luke (Jokioinen, Finland) were allocated to 7 blocks in a complete randomized block design based on body weight, days in milk, dry matter intake (DMI), and milk yield. Animals within each block were randomly allocated to a diet with or without GCE. The experimental period for each block of cows (one for each of the control and GCE groups) consisted of 14 d of adaptation followed by 4 d of methane measurements inside the open circuit respiration chambers, with the first day being considered as acclimatization. Data were analyzed using the GLM procedure of SAS (SAS Institute Inc.). Methane production (g/d) and methane intensity (g/kg of energy-corrected milk) were lower by 10.3 and 11.7%, respectively, and methane yield (g/kg of DMI) tended to be lower by 9.7% in cows fed GCE compared with the control. Dry matter intake, milk production, and milk composition were similar between treatments. Rumen pH and total volatile fatty acid concentrations in rumen fluid were similar, whereas GCE tended to increase molar propionate concentration and decrease the molar ratio of acetate to propionate. Supplementation with GCE resulted in greater abundance of Succinivibrionaceae, which was associated with reduced methane. The relative abundance of the strict anaerobic Methanobrevibacter genus was reduced by GCE. The change in microbial community and rumen propionate proportion may explain the decrease in enteric methane emissions. In conclusion, feeding GCE to dairy cows for 18 d modified rumen fermentation and microbiota, leading to reduced methane production and intensity without compromising DMI or milk production in dairy cows. This could be an effective strategy for enteric methane mitigation of dairy cows.

Long-term effects of early-life rumen microbiota modulation on dairy cow production performance and methane emissions.

Rumen microbiota modulation during the pre-weaning period has been suggested as means to affect animal performance later in life. In this follow-up study, we examined the post-weaning rumen microbiota development differences in monozygotic twin-heifers that were inoculated (T-group) or not inoculated (C-group) (n = 4 each) with fresh adult rumen liquid during their pre-weaning period. We also assessed the treatment effect on production parameters and methane emissions of cows during their 1st lactation period. The rumen microbiota was determined by the 16S rRNA gene, 18S rRNA gene, and ITS1 amplicon sequencing. Animal weight gain and rumen fermentation parameters were monitored from 2 to 12 months of age. The weight gain was not affected by treatment, but butyrate proportion was higher in T-group in month 3 (p = 0.04). Apart from archaea (p = 0.084), the richness of bacteria (p < 0.0001) and ciliate protozoa increased until month 7 (p = 0.004) and anaerobic fungi until month 11 (p = 0.005). The microbiota structure, measured as Bray-Curtis distances, continued to develop until months 3, 6, 7, and 10, in archaea, ciliate protozoa, bacteria, and anaerobic fungi, respectively (for all: p = 0.001). Treatment or age × treatment interaction had a significant (p < 0.05) effect on 18 bacterial, 2 archaeal, and 6 ciliate protozoan taxonomic groups, with differences occurring mostly before month 4 in bacteria, and month 3 in archaea and ciliate protozoa. Treatment stimulated earlier maturation of prokaryote community in T-group before month 4 and earlier maturation of ciliate protozoa at month 2 (Random Forest: 0.75 month for bacteria and 1.5 month for protozoa). No treatment effect on the maturity of anaerobic fungi was observed. The milk production and quality, feed efficiency, and methane emissions were monitored during cow's 1st lactation. The T-group had lower variation in energy-corrected milk yield (p < 0.001), tended to differ in pattern of residual energy intake over time (p = 0.069), and had numerically lower somatic cell count throughout their 1st lactation period (p = 0.081), but no differences between the groups in methane emissions (g/d, g/kg DMI, or g/kg milk) were observed. Our results demonstrated that the orally administered microbial inoculant induced transient changes in early rumen microbiome maturation. In addition, the treatment may influence the later production performance, although the mechanisms that mediate these effects need to be further explored.

The Association between Blood Β-Hydroxybutyric Acid Concentration in the Second Week of Lactation and Reproduction Performance of Lithuanian Black and White Cows.

Hyperketonemia is a very common metabolic state in dairy cows, which result in lower milk production, impaired fertility, and increased frequency of other diseases. In this study, we aimed to determine the influence of season, parity, and milk yield of cows on beta-hydroxybutyrate (BHB) concentration in the second week of lactation (WK 2) and establish the relationship between BHB concentration in WK 2 and reproduction performance traits such as insemination rate and first insemination day of Lithuanian Black and White dairy cows. The study included clinically healthy Lithuanian Black and White cows (n = 692). Blood BHB concentration was measured using capillary blood samples collected after morning milking when cows were 7-10 DIM. The impact of WK 2 blood BHB concentration on the insemination rate and first insemination day were investigated. The effect of BHB was evaluated according to the season, parity, and milk yield per lactation (305 DIM). Significant differences were observed in BHB concentration in WK 2 due to season and parity, but no statistically significant differences were observed for milk yields (305 d). Increased blood BHB concentration in WK 2 negatively affected insemination rate (p < 0.001) and first insemination day (p < 0.001). The study findings indicate that BHB concentration in WK 2 depends on season and parity, while the milk yield is not associated with BHB concentration. High BHB concentration in WK 2 increases insemination rate and delays the first insemination day for high milk-yielding Lithuanian Black and White dairy cows.

Preservation characteristics and bacterial communities of crimped ensiled barley grains modulated by moisture content and additive application.

Information about the relationships between preservation characteristics and main bacterial communities of fermented feeds can guide decision making during feed preservation and silage additive development. The objective was to evaluate fermentation quality, aerobic stability, microbial quality and bacterial profile of crimped barley grains ensiled under three moisture contents (MC): 228 (low MC), 287 (medium MC) and 345 (high MC) g/kg fresh matter; and using four additive treatments: 1. Control (CONT), 2. Formic and propionic acid-based additive (FPA), 3. Inoculation with homofermentative and heterofermentative strains of lactic acid bacteria (LAB), and 4. Salt-based additive (SALT). There was a quadratic effect (p < 0.05) of incremental MC on pH where greater decline happened from low (5.81) to medium (4.83) MC than from medium to high (4.28) MC, while lactic acid concentration and aerobic stability increased in a linear manner (p < 0.05). Ammonia-N and acetic acid concentrations increased quadratically (p < 0.05) with increasing levels of MC. The effects of additives depended on MC so that improvements in preservation characteristics in response to LAB and SALT were observed at medium and high MC, while FPA was effective at all MC levels. A minor shift was observed in bacterial ecology from raw material towards low MC samples, with Erwiniaceae sp., Enterobacterales spp. and Pseudomonas dominating the fermentation. A major change occurred in medium and high MC materials, where Fructilactobacillus dominated the fermentation in CONT, FPA and SALT silages. LAB-treated silages at medium and high MC resulted in a distinguished pattern with dominance of Lentilactobacillus followed by Lactiplantibacillus. Most abundant communities in the samples, such as Fructilactobacillus, Erwiniaceae sp., Enterobacterales spp. and Pseudomonas, were correlated with several fermentation characteristics. Our results showed that crimped barley grains could be successfully ensiled under various MC and additive treatments. Low MC feeds had higher risk to be aerobically unstable while high MC resulted in more extensive fermentation, with potentially poor fermentation quality. The suitable additive depends on the raw material characteristics as LAB and SALT require relatively high MC to be effective, while FPA showed consistent improvements over all MC levels used in the current study. Awareness of the MC of grain prior to ensiling allows to identify the risks to preservation quality and provides information for choosing an effective additive.

Effects of Starch Level and a Mixture of Sunflower and Fish Oils on Nutrient Intake and Digestibility, Rumen Fermentation, and Ruminal Methane Emissions in Dairy Cows.

Four multiparous dairy cows were used in a 4 × 4 Latin square to examine how starch level and oil mixture impact dry matter (DM) intake and digestibility, milk yield and composition, rumen fermentation, ruminal methane (CH4) emissions, and microbial diversity. Experimental treatments comprised high (HS) or low (LS) levels of starch containing 0 or 30 g of a mixture of sunflower and fish oils (2:1 w/w) per kg diet DM (LSO and HSO, respectively). Intake of DM did not differ between cows fed LS and HS diets while oil supplementation reduced DM intake. Dietary treatments did not affect milk and energy corrected milk yields. There was a tendency to have a lower milk fat concentration due to HSO compared with other treatments. Both high starch level and oil supplementation increased digestibility of gross energy. Cows receiving HS diets had higher levels of total rumen VFA while acetate was lower than LS without any differences in rumen pH, or ruminal CH4 emissions. Although dietary oil supplementation had no impact on rumen fermentation, decreased CH4 emissions (g/day and g/kg milk) were observed with a concomitant increase in Anoplodinium-Diplodinium sp. and Epidinium sp. but a decrease in Christensenellaceae, Ruminococcus sp., Methanobrevibacter ruminantium and Mbb. gottschalkii clades.

Fresh Rumen Liquid Inoculant Enhances the Rumen Microbial Community Establishment in Pre-weaned Dairy Calves.

The development of the functional rumen in calves involves a complex interplay between the host and host-related microbiome. Attempts to modulate rumen microbial community establishment may therefore have an impact on weaning success, calf health, and animal performance later in life. In this experiment, we aimed to elucidate how rumen liquid inoculum from an adult cow, provided to calves during the pre-weaning period, influences the establishment of rumen bacterial, archaeal, fungal, and ciliate protozoan communities in monozygotic twin calves (n = 6 pairs). The calves were divided into treatment (T-group) and control (C-group) groups, where the T-group received fresh rumen liquid as an oral inoculum during a 2-8-week period. The C-group was not inoculated. The rumen microbial community composition was determined using bacterial and archaeal 16S ribosomal RNA (rRNA) gene, protozoal 18S rRNA gene, and fungal ITS1 region amplicon sequencing. Animal weight gain and feed intake were monitored throughout the experiment. The T-group tended to have a higher concentrate intake (Treatment: p < 0.08) and had a significantly higher weekly weight gain (Treatment: p < 0.05), but no significant difference in volatile fatty acid concentrations between the groups was observed. In the T-group, the inoculum stimulated the earlier establishment of mature rumen-related bacterial taxa, affecting significant differences between the groups until 6 weeks of age. The inoculum also increased the archaeal operational taxonomic unit (OTU) diversity (Treatment: p < 0.05) but did not affect the archaeal quantity. Archaeal communities differed significantly between groups until week 4 (p = 0.02). Due to the inoculum, ciliate protozoa were detected in the T-group in week 2, while the C-group remained defaunated until 6 weeks of age. In week 8, Eremoplastron dilobum was the dominant ciliate protozoa in the C-group and Isotricha sp. in the T-group, respectively. The Shannon diversity of rumen anaerobic fungi reduced with age (Week: p < 0.01), and community establishment was influenced by a change of diet and potential interaction with other rumen microorganisms. Our results indicate that an adult cow rumen liquid inoculum enhanced the maturation of bacterial and archaeal communities in pre-weaning calves' rumen, whereas its effect on eukaryotic communities was less clear and requires further investigation.

Compound- and context-dependent effects of antibiotics on greenhouse gas emissions from livestock.

The use of antibiotics in livestock production may trigger ecosystem disservices, including increased emissions of greenhouse gases. To evaluate this, we conducted two separate animal experiments, administering two widely used antibiotic compounds (benzylpenicillin and tetracycline) to dairy cows over a 4- or 5-day period locally and/or systemically. We then recorded enteric methane production, total gas production from dung decomposing under aerobic versus anaerobic conditions, prokaryotic community composition in rumen and dung, and accompanying changes in nutrient intake, rumen fermentation, and digestibility resulting from antibiotic administration. The focal antibiotics had no detectable effect on gas emissions from enteric fermentation or dung in aerobic conditions, while they decreased total gas production from anaerobic dung. Microbiome-level effects of benzylpenicillin proved markedly different from those previously recorded for tetracycline in dung, and did not differ by the mode of administration (local or systemic). Antibiotic effects on gas production differed substantially between dung maintained under aerobic versus anaerobic conditions and between compounds. These findings demonstrate compound- and context-dependent impacts of antibiotics on methane emissions and underlying processes, and highlight the need for a global synthesis of data on agricultural antibiotic use before understanding their climatic impacts.

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

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

Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future.

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

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

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

The ruminal microbiome associated with methane emissions from ruminant livestock.

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

Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism.

Methane emissions from ruminal fermentation contribute significantly to total anthropological greenhouse gas (GHG) emissions. New meta-omics technologies are beginning to revolutionise our understanding of the rumen microbial community structure, metabolic potential and metabolic activity. Here we explore these developments in relation to GHG emissions. Microbial rumen community analyses based on small subunit ribosomal RNA sequence analysis are not yet predictive of methane emissions from individual animals or treatments. Few metagenomics studies have been directly related to GHG emissions. In these studies, the main genes that differed in abundance between high and low methane emitters included archaeal genes involved in methanogenesis, with others that were not apparently related to methane metabolism. Unlike the taxonomic analysis up to now, the gene sets from metagenomes may have predictive value. Furthermore, metagenomic analysis predicts metabolic function better than only a taxonomic description, because different taxa share genes with the same function. Metatranscriptomics, the study of mRNA transcript abundance, should help to understand the dynamic of microbial activity rather than the gene abundance; to date, only one study has related the expression levels of methanogenic genes to methane emissions, where gene abundance failed to do so. Metaproteomics describes the proteins present in the ecosystem, and is therefore arguably a better indication of microbial metabolism. Both two-dimensional polyacrylamide gel electrophoresis and shotgun peptide sequencing methods have been used for ruminal analysis. In our unpublished studies, both methods showed an abundance of archaeal methanogenic enzymes, but neither was able to discriminate high and low emitters. Metabolomics can take several forms that appear to have predictive value for methane emissions; ruminal metabolites, milk fatty acid profiles, faecal long-chain alcohols and urinary metabolites have all shown promising results. Rumen microbial amino acid metabolism lies at the root of excessive nitrogen emissions from ruminants, yet only indirect inferences for nitrogen emissions can be drawn from meta-omics studies published so far. Annotation of meta-omics data depends on databases that are generally weak in rumen microbial entries. The Hungate 1000 project and Global Rumen Census initiatives are therefore essential to improve the interpretation of sequence/metabolic information.

Ruminal Infusions of Cobalt EDTA Modify Milk Fatty Acid Composition via Decreases in Fatty Acid Desaturation and Altered Gene Expression in the Mammary Gland of Lactating Cows.

BACKGROUND: Intravenous or ruminal infusion of lithium salt of cobalt EDTA (Co-EDTA) or cobalt-acetate alters milk fat composition in cattle, but the mechanisms involved are not known. OBJECTIVE: The present study evaluated the effect of ruminal Co-EDTA infusion on milk FA composition, mammary lipid metabolism, and mammary lipogenic gene expression. METHODS: For the experiment, 4 cows in midlactation and fitted with rumen cannulae were used in a 4 × 4 Latin square with 28-d periods. Co-EDTA was administered in the rumen to supply 0, 1.5, 3.0, or 4.5 g Co/d over an 18-d interval with a 10-d washout between experimental periods. Milk production was recorded daily, and milk FA composition was determined on alternate days. Mammary tissue was biopsied on day 16, and arteriovenous differences of circulating lipid fractions and FA uptake across the mammary gland were measured on day 18. RESULTS: Co-EDTA had no effect on intake, proportions of rumen volatile FA, or milk production but caused dose-dependent changes in milk FA composition. Alterations in milk fat composition were evident within 3 d of infusion and characterized by linear or quadratic decreases (P < 0.05) in FAs containing a cis-9 double bond, an increase in 4:0 and 16:0, and linear decreases in milk 8:0, 10:0, 12:0, and 14:0 concentrations. Co-EDTA progressively decreased (P < 0.05) the stearoyl-CoA desaturase (SCD)-catalyzed desaturation of FAs in the mammary gland by up to 72% but had no effect on mammary SCD1 mRNA or SCD protein abundance. Changes in milk FA composition were accompanied by altered expression of specific genes involved in de novo FA and triacylglycerol synthesis. CONCLUSION: Ruminal infusion of Co-EDTA alters milk FA composition in cattle via a mechanism that involves decreases in the desaturation of FAs synthesized de novo or extracted from blood and alterations in mammary lipogenic gene expression, without affecting milk fat yield.

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

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