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

Unravelling AMR dynamics in the rumenofaecobiome: Insights, challenges and implications for One Health

Antimicrobial resistance (AMR) is a critical global threat to human, animal and environmental health, exacerbated by horizontal gene transfer (HGT) via mobile genetic elements. This poses significant challenges that have a negative impact on the sustainability of the One Health approach, hindering its long-term viability and effectiveness in addressing the interconnectedness of global health. Recent studies on livestock animals, specifically ruminants, indicate that culturable ruminal bacteria harbour AMR genes with the potential for HGT. However, these studies have focused predominantly on using the faecobiome as a proxy to the rumen microbiome or using easily isolated and culturable bacteria, overlooking the unculturable population. These unculturable microbial groups could have a profound influence on the rumen resistome and AMR dynamics within livestock ecosystems, potentially holding critical insights for advanced understanding of AMR in One Health. In order to address this gap, this review of current research on the burden of AMR in livestock was undertaken, and it is proposed that combined study of the rumen microbiome and faecobiome, termed the 'rumenofaecobiome', should be performed to enhance understanding of the risks of AMR in ruminant livestock. This review discusses the complexities of the rumen microbiome and the risks of AMR transmission in this microbiome in a One Health context. AMR transmission dynamics and methodologies for assessing the risks of AMR in livestock are summarized, and future considerations for researching the impact of AMR in the rumen microbiome and the implications within the One Health framework are discussed.

Invited review: Interplay of rumen microbiome and the cattle host in modulating feed efficiency and methane emissions

Given that the majority of energy and protein supplied to cattle arises as a result of ruminal fermentation, the rumen microbiome plays a key role in determining host feed efficiency and methane (CH4) emissions. Some reports suggest that a less diverse rumen microbiome is associated with improved feed efficiency, whereas other studies suggest that microbial diversity does not differ between low- and high-efficiency cattle of the same breed, fed identical diets. Although reducing enteric CH4 emissions offers a dual benefit in terms of improved feed efficiency and a reduced environmental footprint, recent findings indicate that these outcomes are not always consistent in ruminants. The composition of the rumen microbiome is mainly determined by diet but is also influenced by host genetics and physiological parameters such as rumen volume, rate of passage, and rumination. Reduced microbial diversity may impair the ability of cattle to adapt to frequent changes in diet and the environment. Hydrogen exchange and capture are the energetic foundation of the rumen microbiome, and considerable resources have been invested in developing additives that redirect hydrogen flow toward alternative sinks and away from the reduction of CO2 to CH4. These additives reduce enteric CH4 emissions by 30% to 80%, yet the anticipated gains in feed efficiency remain inconsistent. Strategies to improve the feed efficiency of cattle production must consider the multifaceted interactions among the host, rumen microbiome, and diet to ensure the sustainable intensification of cattle production while maintaining the social license for milk and meat production.

Potential role of key rumen microbes in regulating host health and growth performance in Hu sheep

BACKGROUND

Average daily gain (ADG) is an important component affecting the profitability of sheep. However, research on the relationship between rumen microbes and sheep growth phenotype is still very lacking. Therefore, in this study, 16 Hu sheep were selected from a cohort of 318 sheep assigned to the same feeding and management conditions, and divided into high growth rate (HADG, n = 8) group and low growth rate (LADG, n = 8) group according to the extreme ADG value. Then, the differences in rumen microbes, rumen fermentation and animal immune parameters were further compared between groups to explore the potential role of rumen key microbes in regulating the health and growth performance of Hu sheep hosts.

RESULTS

The results showed that specific pathogenic bacteria associated with ADG, including Anaerotruncus, Sediminibacterium and Glaesserella, exhibited significant correlations with interleukin-6 (IL-6) and immunoglobulin G (IgG). These interactions disrupt immune homeostasis in the host, leading to a metabolic prioritization of energy resources toward immune responses, thereby impairing growth and development. Succinivibrio_dextrinosolvens was enriched in HADG sheep and exhibited a significant positive correlation with propionate levels. This promoted propionate production in the rumen, enhancing the metabolic activity of carbohydrate, amino acid and energy metabolism, ultimately contributing to higher ADG in sheep. Importantly, random forest analysis results showed that Succinivibrio_dextrinosolvens could classify sheep into HADG and LADG with a prediction accuracy of 81.2%. Additionally, we identified 34 bacteria belonged to connectors in the HADG co-occurrence network, including Alloprevotella, Phascolarctobacterium, Anaerovibrio, Butyricicoccus, Ruminococcaceae_noname, and Roseburia, etc., which play an important role in the degradation of carbohydrates and convert them into short-chain fatty acids (SCFAs), maintaining rumen health, and modulating inflammation.

CONCLUSIONS

In summary, key microbes in the rumen affect the overall healthy homeostasis and rumen fermentation of the host, leading to changes in energy utilization, which in turn affects the average daily gain of Hu sheep. Succinivibrio_dextrinosolvens is a promising biomarker for selecting high growth rate sheep in the future. This study provides a new method to manipulate rumen bacteria to improve growth performance in sheep.

Microbiome determinants of productivity in aquaculture of whiteleg shrimp

Aquaculture holds immense promise for addressing the food needs of our growing global population. Yet, a quantitative understanding of the factors that control its efficiency and productivity has remained elusive. In this study, we address this knowledge gap by focusing on the microbiome determinants of productivity, more specifically animal survival and growth, for one of the most predominant animal species in global aquaculture, whiteleg shrimp (Penaeus vannamei). Through analysis of the shrimp-associated microbiome from previous studies across Asia and Latin America, we established the presence of core phylogenetic groups, widely prevalent across aquaculture conditions in disparate geographic locations and including both pathogenic and beneficial microbes. Focusing on the early stages of growth (larval hatcheries), we showed that the composition of the microbiome alone can predict a remarkable fraction of the variation in shrimp larvae survival rates (ca. 50%). Taxa associated with high survival rates share recently acquired genes that appear to be specific to aquaculture conditions. These genes are involved in the biosynthesis of growth factors and protein degradation, underscoring the potential role of beneficial microorganisms in nutrient assimilation. By contrast, the predictability of the microbiome on the adult shrimp weight in grow-out farms is weaker (10%-20%), akin to observations in the context of livestock. In conclusion, our study unveils a novel avenue for predicting productivity in shrimp aquaculture based on microbiome analysis. This paves the way for targeted manipulation of the microbiome as a strategic approach to enhance aquaculture efficiency from the earliest developmental stages.

IMPORTANCE

Aquaculture is a rapidly growing industry essential for global food security, yet its productivity is often constrained by high mortality rates and inefficient growth. While the microbiome is known to influence host health and nutrient assimilation, its broader role in animal production remains poorly understood. Here, we take a data-driven approach to address this gap by systematically analyzing shrimp-associated microbiomes across hatcheries and farms. By integrating microbiome data with machine learning, we demonstrate that microbial communities are powerful predictors of key production outcomes, shaping shrimp survival and growth. Our findings suggest that the microbiome could serve as a diagnostic tool for assessing production conditions and optimizing management strategies. In addition, machine learning techniques offer a promising avenue for identifying beneficial microbes and developing targeted microbiome therapies to enhance aquaculture sustainability and efficiency.

Sequence-based genome-wide association study reveals host genomic regions and candidate genes influencing the fecal microbiota of Holstein cows

In recent decades, the digestive tract microbiota of livestock has been extensively studied, revealing associations with host phenotypes, including production- and health-related traits. The effect of host genetics on gut microbes has been documented in several species; however, in dairy cattle, the specific genomic regions that influence microbial communities remain relatively unexplored. This study aimed to conduct a sequence-based GWAS and a gene-based association study to identify the genomic regions and candidate genes affecting fecal microbiota diversity and composition in a population of 1,875 commercial Holstein cows. From the sequence-based GWAS conducted on 116 fecal microbiota taxonomic levels, 6 QTL were significantly associated with the abundances of Paeniclostridium, an unclassified genus from the Paludibacteraceae family, Sutterella, Turicibacter, and Akkermansia genera, as well as the associated family Akkermansiaceae. These QTL explained between 2.0% and 25.5% of the phenotypic variances of the taxa abundances. Conversely, no genomic variants were found significant for either the α- or the β-diversity of the fecal microbiota. A gene-based association study subsequently conducted on the sequence-based GWAS results revealed significant effects of 90 genes across the bovine genome, effecting the relative abundances of some fecal taxa. Many of these genes were located within the major histocompatibility complex and enriched in immune response pathways. By combining GWAS with gene-based association studies, we specifically identified an association between the ABO gene and the fecal abundance of Akkermansia and Akkermansiaceae. The study represents a significant step forward in understanding the genetic determinism of the complex interactions between the fecal microbiota and their host. It provides new insights into the biological mechanisms underlying host-microbiota interaction in dairy cattle and unveils strong associations between host genomic regions and fecal microbiota in a commercial population. This study holds promise for large-scale breeding strategies to shape the fecal microbiota in Holstein cows and benefit from the host-microbiota interactions.

Studies on the concerted interaction of microbes in the gastrointestinal tract of ruminants on lignocellulose and its degradation mechanism

The complex structure of lignocellulose, one of the most abundant renewable resources on earth, makes biodegradation challenging. Ruminant gastrointestinal microbiota achieves efficient lignocellulose degradation through a highly synergistic ecosystem, which provides an important research model for sustainable energy development and high value-added chemical production. This review systematically summarizes the key mechanisms of lignocellulose degradation by ruminant gastrointestinal microorganisms, focusing on the synergistic roles of rumen and hindgut (including cecum, colon, and rectum) microorganisms in cellulose, hemicellulose, and lignin degradation. The study focuses on the functional differentiation and cooperation patterns of bacteria, fungi and protozoa in lignocellulose decomposition, and summarizes the roles of carbohydrate-active enzymes (CAZymes) and their new discoveries under the histological techniques. In addition, this manuscript explores the potential application of gastrointestinal tract (GIT) microbial degradation mechanisms in improving the utilization of straw-based feeds. In the future, by revealing the mechanism of microbe-host synergy and integrating multi-omics technologies, the study of ruminant gastrointestinal microbial ecosystems will provide new solutions to promote the efficient utilization of lignocellulose and alleviate the global energy crisis.

Gut metagenomes reveal interactions between dietary restriction, ageing and the microbiome in genetically diverse mice

The gut microbiome changes with age and has been proposed to mediate the benefit of lifespan-extending interventions such as dietary restriction. However, the causes and consequences of microbiome ageing and the potential of such interventions remain unclear. Here we analysed 2,997 metagenomes collected longitudinally from 913 deeply phenotyped, genetically diverse mice to investigate interactions between the microbiome, ageing, dietary restriction (caloric restriction and fasting), host genetics and a range of health parameters. Among the numerous age-associated microbiome changes that we find in this cohort, increased microbiome uniqueness is the most consistent parameter across a second longitudinal mouse experiment that we performed on inbred mice and a compendium of 4,101 human metagenomes. Furthermore, cohousing experiments show that age-associated microbiome changes may be caused by an accumulation of stochastic environmental exposures (neutral theory) rather than by the influence of an ageing host (selection theory). Unexpectedly, the majority of taxonomic and functional microbiome features show small but significant heritability, and the amount of variation explained by host genetics is similar to ageing and dietary restriction. We also find that more intense dietary interventions lead to larger microbiome changes and that dietary restriction does not rejuvenate the microbiome. Lastly, we find that the microbiome is associated with multiple health parameters, including body composition, immune components and frailty, but not lifespan. Overall, this study sheds light on the factors influencing microbiome ageing and aspects of host physiology modulated by the microbiome.

The association of seasonal dietary shift with fecal metabolome and microbiota in the captive Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis)

The gut microbiota can act as a buffer against changes in energy and food availability and adapt plastically to fluctuations in the host's diet. However, it is unknown how changes in the gut microbiome with the seasons impact microbial metabolism and the accessibility of nutrients to hosts. The study utilized 16S rRNA and UHPLC-MS/MS approaches to examine seasonal fecal metabolome variations in the captive Yangtze finless porpoises (YFPs) to determine if these variations are linked to nutrient intake or gut microbiome composition changes. The YFPs were mostly fed a frozen and live fish diet, with different food intakes yearly. We found that gut microbial diversity remained constant, but community structure varied seasonally. Firmicutes and Cyanobacteria were higher in winter, Actinobacteria in spring and fall, and proteobacteria in summer. The genus Paeniclostridium was significantly higher in the spring season, Romboutsia and Clostridium_sensu_stricto_13 were significantly higher in the summer, while Terrisporobacter and Macrococcus were significantly higher in the fall group. The study reported that seasonal dietary variation significantly impacted the fecal metabolome by affecting the metabolism, including energy, amino acid, carbohydrate, and nucleotide metabolism of the captive YFP. Moreover, significant correlations between metabolome and microbiome were found, and these correlations may indicate that the captive YFP has adapted to cope with dietary variations and enhance energy acquisition. These findings improve our knowledge of the link between microbiota, diet, metabolites, and the physiology of the host and suggest that gut microbial populations may adapt continuously to changes in diet.

Functional analysis of Parabacteroides distasonis F4: a novel probiotic strain linked to calf growth and rumen fermentation

BACKGROUND

Rumen microorganisms are key regulators of ruminant growth and production performance. Identifying probiotic candidates through microbial culturomics presents a promising strategy for improving ruminant production performance. Our previous study identified significant differences in rumen microbial communities of Holstein calves with varying average daily gain (ADG). This study aims to identify a target strain based on the findings from multi-omics analysis and literature review, isolating and evaluating the target microbial strains from both the rumen and hindgut contents for their probiotic potential.

RESULTS

Parabacteroides distasonis, a strain closely associated with ADG, was successfully isolated from calf rumen content cultured with Fastidious Anaerobe Agar (FAA) medium and named Parabacteroides distasonis F4. Whole-genome sequencing and pan-genome analysis showed that P. distasonis F4 possesses a core functional potential for carbohydrate and amino acid metabolism, with the ability to produce propionate, acetate, and lactate. The results of targeted and untargeted metabolomics further validated the organic acid production and metabolic pathways of P. distasonis F4. An in vitro simulated rumen fermentation test showed that supplementation with P. distasonis F4 significantly altered rumen microbial community structure and increased the molar proportions of propionate and butyrate in the rumen. Furthermore, an in vivo study demonstrated that dietary supplementation with P. distasonis F4 significantly increased the ADG of pre-weaning calves.

CONCLUSIONS

This study represents the first isolation of P. distasonis F4 from rumen, highlighting its potential as a probiotic strain for improving rumen development and growth performance in ruminants.

Gut Microbiota of Ruminants and Monogastric Livestock: An Overview

The diversity and composition of the gut microbiota are widely recognized as fundamental factors influencing the well-being and productivity of domestic animals. Advancements in sequencing technologies have revolutionized studies in this research field, allowing for deeper insights into the composition and functionality of microbiota in livestock. Ruminants and monogastric animals exhibit distinct digestive systems and microbiota characteristics: ruminants rely on fermentation, while monogastrics use enzymatic digestion, and monogastric animals have simpler stomach structures, except for horses and rabbits, where both processes coexist. Understanding the gut microbiota's impact and composition in both animal types is essential for optimizing production efficiency and promoting animal health. Following this perspective, the present manuscript review aims to provide a comprehensive overview of the gut microbiota in ruminants (such as cattle, sheep, and goats) and monogastric animals (including horses, pigs, rabbits, and chickens).

Effects of Yeast Culture on Lamb Growth Performance, Rumen Microbiota, and Metabolites

The effects of incorporating yeast culture (YC) into pelleted feeds on sheep production and the potential impact on rumen microbial populations, microbial metabolism, and fermentation have not been extensively studied. This study aimed to evaluate the effect of YC on growth performance, rumen tissue development, rumen fermentation, and rumen microflora in sheep and to explore the potential microbial mechanisms involved. Fifty healthy 3-month-old male lambs of small-tailed Han sheep, with an average weight of 28.44 ± 0.63 kg, were randomly divided into five groups: control (0% YC), 3% YC, 6% YC, 9% YC, and 12% YC. The pre-feeding period lasted for 15 days, followed by an official feeding period of 60 days. On the last day of the formal feeding period, six lambs that exhibited the best growth performance were randomly selected from the control group and the 9% YC group. These sheep were slaughtered, then the rumen epithelial tissue and rumen contents were collected for the measurement of rumen fermentation, microbial populations, and metabolites. Compared to the control group, the YC-treated groups showed higher daily and final body weight gains, as well as increased levels of propionic acid, butyric acid, and total volatile fatty acids (p < 0.05). YC supplementation also enhanced rumen papilla length and width (p < 0.05). Additionally, YC increased the relative abundance of certain microbial species (p < 0.05). These results suggest that supplementing 9% YC in pelleted diets for small-tailed Han sheep may enhance growth performance and improve the rumen environment.

Response of rumen methane production and microbial community to different abatement strategies in yaks

BACKGROUND

Developing region-specific dietary strategies is crucial for mitigating methane (CH4) emissions from yaks. However, there is a lack of tailored emission reduction strategies for yak production in the Qinghai-Tibet Plateau region. This study utilizes an in vitro rumen fermentation technique (Based on the ANKOMRF gas production measurement system) to investigate the effects of different dietary interventions on CH4 production from regional yaks. The selected strategies-Sodium Nitrate solution, regional Medicago sativa L., and regional Helianthus tuberosus L.-were chosen for their potential to reduce CH4 production through various mechanisms: Sodium Nitrate as a methanogenesis inhibitor, Medicago sativa L. for its high nutritional value and its ability to modulate microbial fermentation, and Helianthus tuberosus L. due to its inulin content, which promotes beneficial microbial activity. These dietary interventions aim not only to reduce CH4 production but also to support rumen health and productivity. In addition, gas chromatography and microbial sequencing techniques were employed to identify the optimal emission reduction strategy for regional yaks and to elucidate the key factors influencing the efficacy of these strategies.

RESULTS

The results indicate that supplementing the confined feeding ration (FR group) with Sodium Nitrate (12 mmol/L, FRN group), Medicago sativa L. (25%, FRM group), and Helianthus tuberosus L. (3%, FRH group) all have the effect of reducing CH4 production from yak rumen. Among these interventions, the FRM group exhibits the most significant reduction, with a decrease in rumen CH4 production by 42.76% compared to the FR group. The dry matter digestibility, total volatile fatty acids (TVFA), propionate, and butyrate levels in all groups were higher than those in the FR group. However, only the FRM group reached a significant level (P < 0.01). The pH values were significantly lower than those in the FR group (P < 0.01) across all groups. Each group exhibited distinct clustering patterns in bacterial and archaeal communities compared to the FR group (P < 0.05). The α diversity of bacterial communities was significantly lower than that of the FR group (P < 0.01), while the α diversity of archaeal communities was significantly higher than that of the FR group (P < 0.01). Taxa such as Lachnospiraceae, Clostridium, Treponema, Methanomicrobiaceae, Methanosphaera, and Methanoplanus were enriched in the FR group.

CONCLUSIONS

CH4 production from yak rumen were significantly negatively correlated with substrate crude protein (CP) levels, fermentation fluid TVFA levels, α diversity of archaeal communities, and the relative abundance of Selenomonas and Megasphaera in bacterial communities (P < 0.01). Conversely, CH4 production were significantly positively correlated with the relative abundance of Methanoplanus in archaeal communities (P < 0.01). From the perspective of CH4 gas production, the ranking of emission reduction effectiveness for different mitigation strategies is as follows: FRM group > FRH group > FRN group.

Loss of Myostatin leads to low production of CH4 by altering rumen microbiota and metabolome in cattle

Myostatin (MSTN) is a protein that plays a crucial role in regulating skeletal muscle development. Despite the known benefits of MSTN mutant cattle for increasing beef production, their potential impact on CH4 emissions has not been quantified. The study comparing wild-type (WT) cattle to MSTN-knockout (MSTN-KO) cattle revealed that CH4 production was lower. Macrogenomic analysis revealed a significant decrease in rumen archaea, with reduced Richness indices (P = 0.036). The MSTN-KO cattle also showed altered archaea distribution and composition at different taxonomic levels. LEfSe results showed changes in 21 methanogenic archaea clades, with obligately hydrogen (H2)-dependent methylotrophs Candidatus Methanoplasma termitum species belonging to Methanomassiliicoccales order demonstrating the most significant decrease. Rumen metabolites revealed a decrease in the ratio of acetate to propionate, indicating a shift in rumen fermentation pattern towards propionate fermentation. Additionally, the changing trend of methanogenic archaea is consistent with the evolution of methanogens, and this is correlated with the higher levels of linoleic acid in the rumen of MSTN-KO cattle. Linoleic acid affects the utilization of H2 by methanogenic archaea, leading to a reduction in obligately H2-dependent methylotrophs. Our study suggests that MSTN-KO cattle have potential as an economically and ecologically benign breed for reducing methane emissions.

A comparative study of the composition of microorganisms and metabolites in different β-casein genetic types of dairy cows based on metagenomics and non-targeted metabolomics

β-Casein is the main component of cow's milk protein, with A1 and A2 β-casein being the most common. Of these, A1 β-casein hydrolysate produces BCM-7, which can cause lactose intolerance, while A2 β-casein milk is more gentle on the gut. However, there is limited research on the composition of rumen microbiota, metabolites, and host metabolites in different genotype cows using metagenomics and metabolomics. In this study, we used multi-omics analysis techniques to perform enrichment analysis of differential metabolites, identifying three key metabolic pathways in all three groups: Arachidonic acid metabolism and Tryptophan metabolism. The metabolites in these pathways exhibited unique metabolic characteristics within each group. We then used random forests and ROC to predict key metabolites in these pathways, identifying that the signature metabolites in the A2A2 group were predominantly anti-inflammatory substances, including 12-HETE, PGD2-4d, and Arachidonic Acid. The signature metabolites in the A1A2 group and A2A2 group were Indoleacetaldehyde. The AUC of these signature metabolites was greater than 0.85. Macrogenic linear discriminant analysis (LDA > 2.5) found that the microorganisms with greater contribution were concentrated in the A2A2 group. Compared with the other two groups, g_Bacteroides and g_Parabacteroides were mainly enriched in the A1A2 group. In group A2A2, g_Xanthomonas and g_Acetobacter are mainly enriched. Then, the key microorganisms in A1A2 group were identified by correlation analysis as g_Bacteroides and g_Parabacteroides. The key microorganisms in group A2A2 were g_Acetobacter, g_Xanthomonas and g_Mannheimia, which were consistent with the results of LEfSe analysis. These microorganisms mainly affect the degradation of fiber in the diet, host metabolism and the occurrence of inflammation. In conclusion, our results provide theoretical basis and data support for the study of dairy cows with different genotypes of β-casein, and help to determine the potential biological functions of different genotypes of casein in dairy products and their effects on human health.

Methane production related to microbiota in dairy cattle feces

Methane (CH4) emission from livestock feces, led by ruminants, shows a profound impact on global warming. Despite this, we have almost no information on the syntrophy of the intact microbiome metabolisms, from carbohydrates to the one-carbon units, covering multiple stages of ruminant development. In this study, syntrophic effects of polysaccharide degradation and acetate-producing bacteria, and methanogenic archaea were revealed through metagenome-assembled genomes from water saturated dairy cattle feces. Although CH4 is thought to be produced by archaea, more edges, nodes, and balanced interaction types revealed by network analysis provided a closed bacteria-archaea network. The CH4 production potential and pathways were further evaluated through dynamic, thermodynamic and 13C stable isotope analysis. The powerful CH4 production potential benefited from the metabolic flux: classical polysaccharides, soluble sugar (glucose, galactose, lactose), acetate, and CH4 produced via typical acetoclastic methanogenesis. In comparison, a cooperative model dominated by hydrogenotrophic methanogenic archaea presented a weak ability to generate CH4. Our findings comprehensively link carbon and CH4 metabolism paradigm to specific microbial lineages which are shaped related to developmental stages of the dairy cattle, directing influencing global warming from livestock and waste treatment.

Designing host-associated microbiomes using the consumer/resource model

A key step toward rational microbiome engineering is in silico sampling of realistic microbial communities that correspond to desired host phenotypes, and vice versa. This remains challenging due to a lack of generative models that simultaneously capture compositions of host-associated microbiomes and host phenotypes. To that end, we present a generative model based on the mechanistic consumer/resource (C/R) framework. In the model, variation in microbial ecosystem composition arises due to differences in the availability of effective resources (inferred latent variables), while species' resource preferences remain conserved. Simultaneously, the latent variables are used to model phenotypic states of hosts. In silico microbiomes generated by our model accurately reproduce universal and dataset-specific statistics of bacterial communities. The model allows us to address three salient questions in host-associated microbial ecologies: (i) which host phenotypes maximally constrain the composition of the host-associated microbiomes? (ii) how context-specific are phenotype/microbiome associations, and (iii) what are plausible microbiome compositions that correspond to desired host phenotypes? Our approach aids the analysis and design of microbial communities associated with host phenotypes of interest.

IMPORTANCE

Generative models are extremely popular in modern biology. They have been used to model the variation of protein sequences, entire genomes, and RNA sequencing profiles. Importantly, generative models have been used to extrapolate and interpolate to unobserved regimes of data to design biological systems with desired properties. For example, there has been a boom in machine-learning models aiding in the design of proteins with user-specified structures or functions. Host-associated microbiomes play important roles in animal health and disease, as well as the productivity and environmental footprint of livestock species. However, there are no generative models of host-associated microbiomes. One chief reason is that off-the-shelf machine-learning models are data hungry, and microbiome studies usually deal with large variability and small sample sizes. Moreover, microbiome compositions are heavily context dependent, with characteristics of the host and the abiotic environment leading to distinct patterns in host-microbiome associations. Consequently, off-the-shelf generative modeling has not been successfully applied to microbiomes.To address these challenges, we develop a generative model for host-associated microbiomes derived from the consumer/resource (C/R) framework. This derivation allows us to fit the model to readily available cross-sectional microbiome profile data. Using data from three animal hosts, we show that this mechanistic generative model has several salient features: the model identifies a latent space that represents variables that determine the growth and, therefore, relative abundances of microbial species. Probabilistic modeling of variation in this latent space allows us to generate realistic in silico microbial communities. The model can assign probabilities to microbiomes, thereby allowing us to discriminate between dissimilar ecosystems. Importantly, the model predictively captures host-associated microbiomes and the corresponding hosts' phenotypes, enabling the design of microbial communities associated with user-specified host characteristics.

Feed additives for methane mitigation: Modeling the impact of feed additives on enteric methane emission of ruminants-Approaches and recommendations

Over the past decade, there has been considerable attention on mitigating enteric methane (CH4) emissions from ruminants through the utilization of antimethanogenic feed additives (AMFA). Administered in small quantities, these additives demonstrate potential for substantial reductions of methanogenesis. Mathematical models play a crucial role in comprehending and predicting the quantitative impact of AMFA on enteric CH4 emissions across diverse diets and production systems. This study provides a comprehensive overview of methodologies for modeling the impact of AMFA on enteric CH4 emissions in ruminants, culminating in a set of recommendations for modeling approaches to quantify the impact of AMFA on CH4 emissions. Key considerations encompass the type of models employed (i.e., empirical models including meta-analyses, machine learning models, and mechanistic models), the modeling objectives, data availability, modeling synergies and trade-offs associated with using AMFA, and model applications for enhanced understanding, prediction, and integration into higher levels of aggregation. Based on an evaluation of these critical aspects, a set of recommendations is presented concerning modeling approaches for quantifying the impact of AMFA on CH4 emissions and in support of farm-level, national, regional, and global inventories for accounting greenhouse gas emissions in ruminant production systems.

The Holobiont concept in ruminant physiology - more of the same, or something new and meaningful to food quality, food security, and animal health?

The holobiont concept has emerged as an attempt to recognize and describe the myriad interactions and physiological signatures inherent to a host organism, as impacted by the microbial communities that colonize and/or co-inhabit the environment within which the host resides. The field acknowledges and draws upon principles from evolution, ecology, genetics, and biology, and in many respects has been "pushed" by the advent of high throughput DNA sequencing and, to a lesser extent, other "omics"-based technologies. Despite the explosion in data generation and analyses, much of our current understanding of the human and ruminant "holobiont" is based on compositional forms of data and thereby, restricted to describing host phenotypes via associative or correlative studies. So, where to from here? We will discuss some past findings arising from ruminant and human gut microbiota research and seek to evaluate the rationale, progress, and opportunities that might arise from the "holobiont" approach to the ruminant and human host. In particular, we will consider what is a "good" or "bad" host gastrointestinalmicrobiome in different scenarios, as well as potential avenues to sustain or alter the holobiont. While the holobiont approach might improve food quality, food security and animal health, these benefits will be most likely achieved via a judicious and pragmatic compromise in data generation, both in terms of its scale, as well as its generation in context with the "forgotten" knowledge of ruminant and human physiology.

The cow GUTBIOME CY study: investigating the composition of the cattle gut microbiome in health and infectious disease transmission in cyprus

BACKGROUND

Recent evidence suggests that the lower gut microbiome of ruminants presents roles in their health and environment, including the development of the mucosal immune system, milk production efficiency and quality and subsequent methane emissions. However, there are proportionately fewer studies on this complex microbial community in cattle and region-focus studies are non- existent.

METHODS

Herein, we present the research protocol of the GUTBIOME CY project pertaining to determine the composition of the lower gut microbiome in dairy cows situated in 37 farms across five districts of the island of Cyprus. Detailed questionnaires on animal husbandry and farming practices will be gathered from each farm. Faecal, milk (individual and bulk) and water samples will also be collected from cows and their offspring. Samples will be analysed using a combination of molecular biology and bioinformatics pipelines to define microbiome profiles and antimicrobial resistance (AMR). Information collected from the questionnaires will be used to test for associations between animal husbandry or farming practices and microbiome components and AMR.

DISCUSSION

Collected samples will establish the first dairy cattle biobank in the country for contributing substantially towards scientific advancements in microbiome research and providing insights to all stakeholders, tailored to the unique agricultural context of Cyprus.

Circadian Rhythm Enhances mTORC1/AMPK Pathway-Mediated Milk Fat Synthesis in Dairy Cows via the Microbial Metabolite Acetic Acid

Livestock may respond differently to circadian rhythms, leading to differences in the composition of the animal products. Nevertheless, the circadian effects on rumen microorganisms and animal products are poorly understood. In the study, it was found that dairy cows exhibited increased milk fat levels, decreased acetic acid concentrations in the rumen fluid, and elevated acetic acid levels in the blood during the night compared to those of the day. Correlational analyses suggested a high association between Succiniclasticum, Lactobacillus, Prevotellacene NK3B31_group, Muribaculaceae_unclassified, etc., which were significantly enriched in rumen fluid at night, and milk fat levels. The differential metabolite Vitamin B6, significantly elevated at night, promoted the translocation of acetic acid into the circulation by increasing the level of rumen epithelial MCT1 protein expression. In addition, we found that both acetic acid treatment time and dose modulated the expression of lipid metabolism transcription factors (PPARγ, PPARα, and SREBP1c) and downstream genes (FASN, SCD1, ACCα, and CPT1A). Additionally, the mTORC1 and AMPK pathways were responsible for the effects of acetic acid on transcription factors and genes involved in lipid metabolism. Differences in rumen microbial taxa were observed between the day and night. Microbial metabolite (acetic acid) was found to be absorbed into the bloodstream and entered the mammary gland at night at a significantly elevated level. This regulation impacted the expression of lipid metabolism-related transcription factors (PPARγ, PPARα, and SREBP1c), as well as downstream genes through the mTORC1 and AMPK signaling pathways, ultimately affecting milk fat synthesis. These findings provide a new perspective for the microbial regulation of milk synthesis.

Connecting the ruminant microbiome to climate change: insights from current ecological and evolutionary concepts

Ruminant livestock provide meat, milk, wool, and other products required for human subsistence. Within the digestive tract of ruminant animals, the rumen houses a complex and diverse microbial ecosystem. These microbes generate many of the nutrients that are needed by the host animal for maintenance and production. However, enteric methane (CH4) is also produced during the final stage of anaerobic digestion. Growing public concern for global climate change has driven the agriculture sector to enhance its investigation into CH4 mitigation. Many CH4 mitigation methods have been explored, with varying outcomes. With the advent of new sequencing technologies, the host-microbe interactions that mediate fermentation processes have been examined to enhance ruminant enteric CH4 mitigation strategies. In this review, we describe current knowledge of the factors driving ruminant microbial assembly, how this relates to functionality, and how CH4 mitigation approaches influence ecological and evolutionary gradients. Through the current literature, we elucidated that many ecological and evolutionary properties are working in tandem in the assembly of ruminant microbes and in the functionality of these microbes in methanogenesis. Additionally, we provide a conceptual framework for future research wherein ecological and evolutionary dynamics account for CH4 mitigation in ruminant microbial composition. Thus, preparation of future research should incorporate this framework to address the roles ecology and evolution have in anthropogenic climate change.

Estimates of microbiome heritability across hosts

Microbiomes contribute to variation in many plant and animal traits, suggesting that microbiome-mediated traits could evolve through selection on the host. However, for such evolution to occur, microbiomes must exhibit sufficient heritability to contribute to host adaptation. Previous work has attempted to estimate the heritability of a variety of microbiome attributes. Here we show that most published estimates are limited to vertebrate and plant hosts, but significant heritability of microbiome attributes has been frequently reported. This indicates that microbiomes could evolve in response to host-level selection, but studies across a wider range of hosts are necessary before general conclusions can be made. We suggest future studies focus on standardizing heritability measurements for the purpose of meta-analyses and investigate the role of the environment in contributing to heritable microbiome variation. This could have important implications for the use of microbiomes in conservation, agriculture and medicine.

Changes in Gut Microbiota in Peruvian Cattle Genetic Nucleus by Breed and Correlations with Beef Quality

This study evaluated the gut microbiota and meat quality traits in 11 healthy female cattle from the Huaral region of Peru, including 5 Angus, 3 Braunvieh, and 3 F1 Simmental × Braunvieh. All cattle were 18 months old and maintained on a consistent lifelong diet. Meat quality traits, including loin area, fat thickness, muscle depth, and marbling, were assessed in vivo using ultrasonography. Fecal samples were collected for microbiota analysis, and DNA was extracted for 16S and 18S rRNA sequencing to characterize bacterial, fungal, and protist communities. Significant correlations were observed between microbial genera and meat traits: Christensenellaceae R-7 and Alistipes were positively associated with marbling and muscle area, while Rikenellaceae RC9 showed a negative correlation with fat thickness. Among fungi, Candida positively correlated with marbling, while Trichosporon was negatively associated with muscle depth. For protists, Entodinium negatively correlated with fat thickness and marbling. Alpha diversity varied by breed, with Angus showing greater bacterial diversity, and beta diversity analyses indicated a strong breed influence on microbial composition. These findings suggest that microbial composition, shaped by breed and dietary consistency, could serve as an indicator of meat quality, offering insights into gut microbiota's role in optimizing cattle production.

Harnessing meta-omics to unveil and mitigate methane emissions in ruminants: Integrative approaches and future directions

Methane emissions from enteric fermentation present a dual challenge globally: they not only contribute significantly to atmospheric greenhouse gases but also represent a considerable energy loss for ruminant animals. Utilizing high-throughput omics technologies to analyze rumen microbiome samples (meta-omics, i.e., metagenomics, metatranscriptomics, metaproteomics, metabolomics) holds vast potential for uncovering the intricate interplay between diet, microbiota, and methane emissions in these animals. The primary obstacle is the effective integration of diverse meta-omic approaches and their broader application across different ruminant species. Genetic variability significantly impacts methane production in ruminants, suggesting that genomic selection could be a viable strategy to reduce emissions. While substantial research has been conducted on the microbiological aspects of methane production, there remains a critical need to delineate the specific genetic interactions between the host and its microbiome. Advancements in meta-omics technologies are poised to shed light on these interactions, enhancing our understanding of the genetic factors that govern methane output. This review explores the potential of meta-omics to accelerate genetic advancements that could lead to reduced methane emissions in ruminants. By employing a systems biology approach, the integration of various omics technologies allows for the identification of key genomic regions and genetic markers linked to methane production. These markers can then be leveraged in selective breeding programs to cultivate traits associated with lower emissions. Moreover, the review addresses current challenges in applying genomic selection for this purpose and discusses how omics technologies can overcome these obstacles. The systematic integration and analysis of diverse biological data provide deeper insights into the genetic underpinnings and overall biology of methane production traits in ruminants. Ultimately, this comprehensive approach not only aids in reducing the environmental impact of agriculture but also contributes to the sustainability and efficiency of livestock management.

Host genetic regulation of specific functional groups in the rumen microbiome of dairy cows: Implications for lactation trait

INTRODUCTION

Ruminants play a pivotal role in our society by transforming non-consumable substances from industrial by-products and plant fibers into valuable resources such as meat and milk. This remarkable conversion ability is primarily attributed to the rumen microbiota, which is influenced by various factors, including diet, climate, and geographical location. In recent years, increasing research has shown that host factors (breed, genetic variation, etc.) also play vital roles in shaping rumen microbial composition and function in cattle.

OBJECTIVE

This study aims to provide a theoretical basis and an opportunity for further investigating the regulation of lactation traits in dairy cows through host genetics and the interaction with the rumen microbiota.

METHOD

To investigate the interactions between host genotype, rumen microbiota, and animal phenotype, we curated and analyzed the dairy herd improvement data, single nucleotide polymorphisms (SNPs) genotypes, and 16S rumen microbiota data from 1,169 Holstein dairy cows. Heritability and microbiability estimation, along with genome-wide association studies, were performed to identify candidate microorganisms and host genetic loci.

RESULT

We identified thirty-one heritable taxa, whose functions were predominantly enriched in carbohydrate metabolism and energy metabolism. The genome-wide association study revealed that nine heritable bacteria were significantly associated with forty-three SNPs. Functional genes located within or near these SNPs were primarily associated with rumen epithelial development. Additionally, these nine heritable bacteria were primarily annotated as complex polysaccharide degraders and butyrate producers, such as Fibrobacter sp900143055 and Pseudoruminococcus massiliensis, which showed significant associations with milk yield and milk fat percentage. Compared to previous studies, we newly discovered the existence of a high heritability of Olsenella umbonate, Butyrivibrio hungatei, among others.

CONCLUSION

This study identified thirty-one heritable bacterial taxa in Holstein dairy cows' rumen microbiota, with nine showing significant associations with forty-three SNPs related to rumen epithelial development. The discovery of novel heritable species and their correlations with lactation traits provides valuable insights for future breeding strategies aimed at improving dairy cattle productivity through the manipulation of host genetics and rumen microbiota.

An integrated microbiome- and metabolome-genome-wide association study reveals the role of heritable ruminal microbial carbohydrate metabolism in lactation performance in Holstein dairy cows

BACKGROUND

Despite the growing number of studies investigating the connection between host genetics and the rumen microbiota, there remains a dearth of systematic research exploring the composition, function, and metabolic traits of highly heritable rumen microbiota influenced by host genetics. Furthermore, the impact of these highly heritable subsets on lactation performance in cows remains unknown. To address this gap, we collected and analyzed whole-genome resequencing data, rumen metagenomes, rumen metabolomes and short-chain fatty acids (SCFAs) content, and lactation performance phenotypes from a cohort of 304 dairy cows.

RESULTS

The results indicated that the proportions of highly heritable subsets (h2 ≥ 0.2) of the rumen microbial composition (55%), function (39% KEGG and 28% CAZy), and metabolites (18%) decreased sequentially. Moreover, the highly heritable microbes can increase energy-corrected milk (ECM) production by reducing the rumen acetate/propionate ratio, according to the structural equation model (SEM) analysis (CFI = 0.898). Furthermore, the highly heritable enzymes involved in the SCFA synthesis metabolic pathway can promote the synthesis of propionate and inhibit the acetate synthesis. Next, the same significant SNP variants were used to integrate information from genome-wide association studies (GWASs), microbiome-GWASs, metabolome-GWASs, and microbiome-wide association studies (mWASs). The identified single nucleotide polymorphisms (SNPs) of rs43470227 and rs43472732 on SLC30A9 (Zn2+ transport) (P < 0.05/nSNPs) can affect the abundance of rumen microbes such as Prevotella_sp., Prevotella_sp._E15-22, Prevotella_sp._E13-27, which have the oligosaccharide-degradation enzymes genes, including the GH10, GH13, GH43, GH95, and GH115 families. The identified SNPs of chr25:11,177 on 5s_rRNA (small ribosomal RNA) (P < 0.05/nSNPs) were linked to ECM, the abundance alteration of Pseudobutyrivibrio_sp. (a genus that was also showed to be linked to the ECM production via the mWASs analysis), GH24 (lysozyme), and 9,10,13-TriHOME (linoleic acid metabolism). Moreover, ECM, and the abundances of Pseudobutyrivibrio sp., GH24, and 9,10,13-TRIHOME were significantly greater in the GG genotype than in the AG genotype at chr25:11,177 (P < 0.05). By further the SEM analysis, GH24 was positively correlated with Pseudobutyrivibrio sp., which was positively correlated with 9,10,13-triHOME and subsequently positively correlated with ECM (CFI = 0.942).

CONCLUSION

Our comprehensive study revealed the distinct heritability patterns of rumen microbial composition, function, and metabolism. Additionally, we shed light on the influence of host SNP variants on the rumen microbes with carbohydrate metabolism and their subsequent effects on lactation performance. Collectively, these findings offer compelling evidence for the host-microbe interactions, wherein cows actively modulate their rumen microbiota through SNP variants to regulate their own lactation performance. Video Abstract.

Unraveling the genetic basis of methane emission in dairy cattle: a comprehensive exploration and breeding approach to lower methane emissions

Ruminant animals, such as dairy cattle, produce CH4, which contributes to global warming emissions and reduces dietary energy for the cows. While the carbon foot print of milk production varies based on production systems, milk yield and farm management practices, enteric fermentation, and manure management are major contributors togreenhouse gas emissions from dairy cattle. Recent emerging evidence has revealed the existence of genetic variation for CH4 emission traits among dairy cattle, suggests their potential inclusion in breeding goals and genetic selection programs. Advancements in high-throughput sequencing technologies and analytical techniques have enabled the identification of potential metabolic biomarkers, candidate genes, and SNPs linked to methane emissions. Indeed, this review critically examines our current understanding of carbon foot print in milk production, major emission sources, rumen microbial community and enteric fermentation, and the genetic architecture of methane emission traits in dairy cattle. It also emphasizes important implications for breeding strategies aimed at halting methane emissions through selective breeding, microbiome driven breeding, breeding for feed efficiency, and breeding by gene editing.

Effects of spent substrate of oyster mushroom (Pleurotus ostreatus) on ruminal fermentation, microbial community and growth performance in Hu sheep

Introduction

The study aimed to evaluate the effects of Pleurotus Spent Mushroom Substrate (P.SMS) on the rumen microbiota, encompassing bacteria and fungi, as well as their interactions in Hu sheep.

Methods

A total of forty-five 3-month-old Hu sheep were randomly assigned to five groups. Each group was fed diets in which whole-plant corn silage (WPCS) was substituted with P.SMS at varying levels: 0% (CON), 5% (PSMS5), 10% (PSMS10), 15% (PSMS15), or 20% (PSMS20).

Results

The results indicated that higher proportions of P.SMS during the experimental period might have a detrimental effect on feed utilization efficiency, kidney function, and blood oxygen-carrying capacity. Notably, moderate levels of P.SMS, specifically below 15%, were associated with improvements in rumen NH3-N levels and absorption capacity. The results indicated that (1) PSMS20 exhibited a significantly higher feed-to-gain ratio compared to CON (P < 0.05); (2) PSMS15 showed a significantly higher NH3-N content than CON, PSMS5, and PSMS20. Additionally, PSMS10 and PSMS20 had elevated concentrations of NH3-N compared to CON and PSMS5 (P < 0.05); (3) The length and width of rumen papillae were significantly greater in PSMS20 compared to CON and PSMS5 (P < 0.05); (4) Creatinine levels were significantly higher in PSMS20 than in CON, PSMS5, and PSMS10 (P < 0.05); (5) By the conclusion of the experiment, hemoglobin concentration in PSMS20 showed a significant increase compared to CON (P < 0.05). Furthermore, the addition of P.SMS influenced microorganisms at both the phylum and genus levels: (1) At the phylum level, the prevalence of Patescibacteria was significantly lower in PSMS20 compared to the other groups; (2) PSMS15 exhibited significantly higher relative abundances of Basidiomycota compared to CON and PSMS10, while PSMS20 also demonstrated significantly higher relative abundances compared to CON (P < 0.05); (3) At the genus level, the prevalence of Candidatus_Saccharimonas in PSMS20 was significantly lower than in PSMS5, PSMS10, and PSMS15. Conversely, the prevalence of Phanerochaete in PSMS15 was notably higher than in CON and PSMS10, and it was also significantly elevated in PSMS20 compared to CON (P < 0.05); (4) Correlation analysis indicated no significant correlation between changes in the structure of bacterial and fungal communities.

Discussion

Considering these findings, a high percentage of P.SMS negatively impacted feed utilization efficiency, blood oxygen carrying capacity, and kidney function, while a moderate percentage of P.SMS promotes rumen absorption capacity, indicating that feeding 10% P.SMS is optimal.

Maternal gastrointestinal microbiome shapes gut microbial function and resistome of newborns in a cow-to-calf model

BACKGROUND

The maternal gut microbiome is the direct and important source of early colonization and development of the neonatal gut microbiome. However, differences in unique and shared features between mothers with different physiological phenotypes and their newborns still lack exhaustive investigation. Here, using a cow-to-calf model, a comprehensive investigation was conducted to elucidate the pattern and characterization of microbial transfer from the maternal source to the offspring.

RESULTS

The microbiota in the rumen and feces of dairy cows were divided into two clusters via enterotype analysis. The cows from the enterotype distinguished by Prevotella in the rumen had better production performance, whereas no difference was observed in the cows classified by feces enterotype. Furthermore, through a pairwise combination of fecal and ruminal enterotypes, we screened a group of dairy cows with excellent phenotypes. The gastrointestinal microbiomes of cows with different phenotypes and their offspring differed significantly. The rumen was a more important microbial source for meconium than feces. Transmission of beneficial bacteria from mother to offspring was observed. Additionally, the meconium inherits advantageous metabolic functions of the rumen. The resistome features of the rumen, feces, and meconium were consistent, and resistome abundance from cows to calves showed an expanding trend. The interaction between antibiotic-resistance genes and mobile genetic elements from the rumen to meconium was the most remarkable. The diversity of core metabolites from cows to calves was stable and not affected by differences in phenotypes. However, the abundance of specific metabolites varied greatly.

CONCLUSIONS

Our study demonstrates the microbial taxa, metabolic function, and resistome characteristics of maternal and neonatal microbiomes, and reveals the potential vertical transmission of the microbiome from a cow-to-calf model. These findings provide new insights into the transgenerational transmission pattern of the microbiome. Video Abstract.

Parameter Estimation of Host Genomic and Gut Microbiota Contribution to Growth and Feed Efficiency Traits in Meat Rabbits

Rabbits can efficiently utilize plant fibers that are indigestible to humans, and hence may contribute to the alleviation of feed-food competition. Therefore, it is economically and ecologically important to genetically improve the growth performance and feed efficiency of meat rabbits. In this study, we combined pedigree, genomic, and gut microbiota data to estimate genetic and microbial parameters for nine growth and feed efficiency traits of 739 New Zealand White rabbits, including body weight (BW) at 35 (BW35), 70 (BW70), and 84 (BW84) days of age, and average daily gain (ADG), feed conversion ratio (FCR), and residual feed intake (RFI) within two age intervals of 35-70 days (ADG70, FCR70, and RFI70) and 35-84 days (ADG84, FCR84, and RFI84). Based on single-step genomic best linear unbiased prediction, three BW traits and two ADG traits had the high estimates (±standard error, SE) of heritability, ranging from 0.44 ± 0.13 of BW35 to 0.66 ± 0.08 of BW70. Moderate heritabilities were observed for RFI70 (0.22 ± 0.07) and RFI84 (0.29 ± 0.07), whereas the estimates did not significantly deviate from zero for the two FCR traits. There was moderate positive genetic correlation (±SE) between BW70 and ADG70 (0.579 ± 0.086), but BW70 did not correlate with RFI70. Based on microbial best linear unbiased prediction, the estimates of microbiability did not significantly deviate from zero for any trait. Based on the combined use of genomic and gut microbiota data, the parameters obtained in this study could help us to implement efficient breeding schemes in meat rabbits.

Integrating genome- and transcriptome-wide association studies to uncover the host-microbiome interactions in bovine rumen methanogenesis

The ruminal microbiota generates biogenic methane in ruminants. However, the role of host genetics in modifying ruminal microbiota-mediated methane emissions remains mysterious, which has severely hindered the emission control of this notorious greenhouse gas. Here, we uncover the host genetic basis of rumen microorganisms by genome- and transcriptome-wide association studies with matched genome, rumen transcriptome, and microbiome data from a cohort of 574 Holstein cattle. Heritability estimation revealed that approximately 70% of microbial taxa had significant heritability, but only 43 genetic variants with significant association with 22 microbial taxa were identified through a genome-wide association study (GWAS). In contrast, the transcriptome-wide association study (TWAS) of rumen microbiota detected 28,260 significant gene-microbe associations, involving 210 taxa and 4652 unique genes. On average, host genetic factors explained approximately 28% of the microbial abundance variance, while rumen gene expression explained 43%. In addition, we highlighted that TWAS exhibits a strong advantage in detecting gene expression and phenotypic trait associations in direct effector organs. For methanogenic archaea, only one significant signal was detected by GWAS, whereas the TWAS obtained 1703 significant associated host genes. By combining multiple correlation analyses based on these host TWAS genes, rumen microbiota, and volatile fatty acids, we observed that substrate hydrogen metabolism is an essential factor linking host-microbe interactions in methanogenesis. Overall, these findings provide valuable guidelines for mitigating methane emissions through genetic regulation and microbial management strategies in ruminants.

The fecal microbiota of Holstein cows is heritable and genetically correlated to dairy performances

The fecal microbiota of ruminants constitutes a diversified community that has been phenotypically associated with a variety of host phenotypes, such as production and health. To gain a better understanding of the complex and interconnected factors that drive the fecal bacterial community, we have aimed to estimate the genetic parameters of the diversity and composition of the fecal microbiota, including heritabilities, genetic correlations among taxa, and genetic correlations between fecal microbiota features and host phenotypes. To achieve this, we analyzed a large population of 1,875 Holstein cows originating from 144 French commercial herds and routinely recorded for production, somatic cell score, and fertility traits. Fecal samples were collected from the animals and subjected to 16S rRNA gene sequencing, with reads classified into Amplicon Sequence Variants (ASVs). The estimated α- and β-diversity indices (i.e., Observed Richness, Shannon index, Bray-Curtis and Jaccard dissimilarity matrices) and the abundances of ASVs, genera, families and phyla, normalized by centered-log ratio (CLR), were considered as phenotypes. Genetic parameters were calculated using either univariate or bivariate animal models. Heritabilities estimates, ranging from 0.08 to 0.31 for taxa abundances and β-diversity indices, highlight the influence of the host genetics on the composition of the fecal microbiota. Furthermore, genetic correlations estimated within the microbial community and between microbiota features and host traits reveal the complex networks linking all components of the fecal microbiota together and to their host, thus strengthening the holobiont concept. By estimating the heritabilities of microbiota-associated phenotypes, our study quantifies the impact of the host genetics on the fecal microbiota composition. In addition, genetic correlations between taxonomic groups and between taxa abundances and host performance suggest potential applications for selective breeding to improve host traits or promote a healthier microbiota.

Temporal stability of the rumen microbiome and its longitudinal associations with performance traits in beef cattle

The rumen microbiome is the focus of a growing body of research, mostly based on investigation of rumen fluid samples collected once from each animal. Exploring the temporal stability of rumen microbiome profiles is imperative, as it enables evaluating the reliability of findings obtained through single-timepoint sampling. We explored the temporal stability of rumen microbiomes considering taxonomic and functional aspects across the 7-month growing-finishing phase spanning 6 timepoints. We identified a temporally stable core microbiome, encompassing 515 microbial genera (e.g., Methanobacterium) and 417 microbial KEGG genes (e.g., K00856-adenosine kinase). The temporally stable core microbiome profiles collected from all timepoints were strongly associated with production traits with substantial economic and environmental impact (e.g., average daily gain, daily feed intake, and methane emissions); 515 microbial genera explained 45-83%, and 417 microbial genes explained 44-83% of their phenotypic variation. Microbiome profiles influenced by the bovine genome explained 54-87% of the genetic variation of bovine traits. Overall, our results provide evidence that the temporally stable core microbiome identified can accurately predict host performance traits at phenotypic and genetic level based on a single timepoint sample taken as early as 7 months prior to slaughter.

Rumen microbiota succession throughout the perinatal period and its association with postpartum production traits in dairy cows: A review

The transition period for dairy cows usually refers to the 3 weeks pre-calving to the 3 weeks post-calving. During this period, dairy cows undergo metabolic and physiological adaptations because of their susceptibility to metabolic and infectious diseases. Poor feeding management under these circumstances may adversely affect the health and subsequent production performance of the cows. Owing to long-term adaptation and evolution, the rumen has become a unique ecosystem inhabited by a complex microbial community closely associated with its natural host. Dietary components are metabolized by the rumen microbiota, and volatile fatty acids and microbial protein products can be used as precursor substances for synthesizing meat and milk components. The successful transition of perinatal dairy cows includes changes in diet, physiology, and the rumen microbiota. Rumen microbial profiles have been confirmed to be heritable and repairable; however, adverse circumstances affect rumen microbial composition, host digestion and metabolism, as well as postpartum production traits of dairy cows for a certain period. Preliminary evidence indicates a close relationship between the rumen microbiota and animal performance. Therefore, changes in rumen microbes during the transition period and the intrinsic links between the microbiota and host postpartum phenotypic traits need to be better understood to optimize production performance in ruminants.

Ruminal microbiome changes across lactation in primiparous Holstein cows with varying methane intensity: Heritability assessment

Methane is a potent greenhouse gas produced during the ruminal fermentation and is associated with a loss of feed energy. Therefore, efforts to reduce methane emissions have been ongoing in the last decades. Methane production is highly influenced by factors such as the ruminal microbiome and host genetics. Previous studies have proposed to use the ruminal microbiome to reduce long-term methane emissions, as ruminal microbiome composition is a moderately heritable trait and genetic improvement accumulates over time. Lactation stage is another important factor that might influence methane production, but potential associations with the ruminal microbiome have not been evaluated previously. This study sought to examine the changes in ruminal microbiome over the lactation period of primiparous Holstein cows differing in methane intensity (MI) and estimate the heritability of the abundance of relevant microorganisms. Ruminal content samples from 349 primiparous Holstein cows with 14 to 378 DIM were collected from May 2018 to June 2019. Methane intensity of each cow was calculated as methane concentration/milk yield. Up to 64 taxonomic features (TF) from 20 phyla had a significant differential abundance between cows with low and high MI early in lactation, 16 TF during mid lactation, and none late in lactation. Taxonomical features within the Firmicutes, Proteobacteria, Melainabacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria phyla were associated with low MI, whereas eukaryotic TF and those within the Euryarchaeota, Verrucomicrobia, Kiritimatiellaeota, and Lentisphaerae phyla were associated with high MI. Out of the 60 TF that were found to be differentially abundant between early and late lactation in cows with low MI, 56 TF were also significant when cows with low and high MI were compared in the first third of the lactation. In general, microbes associated with low MI were more abundant early in lactation (e.g., Acidaminococcus, Aeromonas, and Weimeria genera) and showed low to moderate heritabilities (0.03 to 0.33). These results suggest some potential to modulate the rumen microbiome composition through selective breeding for lower MI. Differences in the ruminal microbiome of cows with extreme MI levels likely result from variations in the ruminal physiology of these cows and were more noticeable early in lactation, probably due to important interactions between the host phenotype and environmental factors associated with that period. Our results suggest that the ruminal microbiome evaluated early in lactation may be more precise for MI difference, and hence, this should be considered to optimize sampling periods to establish a reference population in genomic selection scenarios.

Characterization of bovine vaginal microbiota using 16S rRNA sequencing: associations with host fertility, longevity, health, and production

Due to their potential impact on the host's phenotype, organ-specific microbiotas are receiving increasing attention in several animal species, including cattle. Specifically, the vaginal microbiota of ruminants is attracting growing interest, due to its predicted critical role on cows' reproductive functions in livestock contexts. Notably, fertility disorders represent a leading cause for culling, and additional research would help to fill relevant knowledge gaps. In the present study, we aimed to characterize the vaginal microbiota of a large cohort of 1171 female dairy cattle from 19 commercial herds in Northern France. Vaginal samples were collected using a swab and the composition of the microbiota was determined through 16S rRNA sequencing targeting the V3-V4 hypervariable regions. Initial analyses allowed us to define the core bacterial vaginal microbiota, comprising all the taxa observed in more than 90% of the animals. Consequently, four phyla, 16 families, 14 genera and a single amplicon sequence variant (ASV) met the criteria, suggesting a high diversity of bacterial vaginal microbiota within the studied population. This variability was partially attributed to various environmental factors such as the herd, sampling season, parity, and lactation stage. Next, we identified numerous significant associations between the diversity and composition of the vaginal microbiota and several traits related to host's production and reproduction performance, as well as reproductive tract health. Specifically, 169 genera were associated with at least one trait, with 69% of them significantly associated with multiple traits. Among these, the abundances of Negativibacillus and Ruminobacter were positively correlated with the cows' performances (i.e., longevity, production performances). Other genera showed mixed relationships with the phenotypes, such as Leptotrichia being overabundant in cows with improved fertility records and reproductive tract health, but also in cows with lower production levels. Overall, the numerous associations underscored the complex interactions between the vaginal microbiota and its host. Given the large number of samples collected from commercial farms and the diversity of the phenotypes considered, this study marks an initial step towards a better understanding of the intimate relationship between the vaginal microbiota and the dairy cow's phenotypes.

Designing host-associated microbiomes using the consumer/resource model

A key step towards rational microbiome engineering is in silico sampling of realistic microbial communities that correspond to desired host phenotypes, and vice versa. This remains challenging due to a lack of generative models that simultaneously capture compositions of host-associated microbiomes and host phenotypes. To that end, we present a generative model based on the mechanistic consumer/resource (C/R) framework. In the model, variation in microbial ecosystem composition arises due to differences in the availability of effective resources (inferred latent variables) while species' resource preferences remain conserved. The same latent variables are used to model phenotypic states of hosts. In silico microbiomes generated by our model accurately reproduce universal and dataset-specific statistics of bacterial communities. The model allows us to address three salient questions in host-associated microbial ecologies: (1) which host phenotypes maximally constrain the composition of the host-associated microbiomes? (2) how context-specific are phenotype/microbiome associations, and (3) what are plausible microbiome compositions that correspond to desired host phenotypes? Our approach aids the analysis and design of microbial communities associated with host phenotypes of interest.

Metagenomics-Metabolomics Exploration of Three-Way-Crossbreeding Effects on Rumen to Provide Basis for Crossbreeding Improvement of Sheep Microbiome and Metabolome of Sheep

The objective of this experiment was to explore the effects of three-way hybridization on rumen microbes and metabolites in sheep using rumen metagenomics and metabolomics. Healthy Hu and CAH (Charolais × Australian White × Hu) male lambs of similar birth weight and age were selected for short-term fattening after intensive weaning to collect rumen fluid for sequencing. Rumen metagenomics diversity showed that Hu and CAH sheep were significantly segregated at the species, KEGG-enzyme, and CAZy-family levels. Moreover, the CAH significantly increased the ACE and Chao1 indices. Further, correlation analysis of the abundance of the top 80 revealed that the microorganisms were interrelated at the species, KEGG-enzyme, and CAZy-family levels. Overall, the microbiome significantly affected metabolites of the top five pathways, with the strongest correlation found with succinic acid. Meanwhile, species-level microbial markers significantly affected rumen differential metabolites. In addition, rumen microbial markers in Hu sheep were overall positively correlated with down-regulated metabolites and negatively correlated with up-regulated metabolites. In contrast, rumen microbial markers in CAH lambs were overall negatively correlated with down-regulated metabolites and positively correlated with up-regulated metabolites. These results suggest that three-way crossbreeding significantly affects rumen microbial community and metabolite composition, and that significant interactions exist between rumen microbes and metabolites.

Rumen protozoa are a hub for diverse hydrogenotrophic functions

Ciliate protozoa are an integral part of the rumen microbial community involved in a variety of metabolic processes. These processes are thought to be in part the outcome of interactions with their associated prokaryotic community. For example, methane production is enhanced through interspecies hydrogen transfer between protozoa and archaea. We hypothesize that ciliate protozoa are host to a stable prokaryotic community dictated by specific functions they carry. Here, we modify the microbial community by varying the forage-to-concentrate ratios and show that, despite major changes in the prokaryotic community, several taxa remain stably associated with ciliate protozoa. By quantifying genes belonging to various known reduction pathways in the rumen, we find that the bacterial community associated with protozoa is enriched in genes belonging to hydrogen utilization pathways and that these genes correspond to the same taxonomic affiliations seen enriched in protozoa. Our results show that ciliate protozoa in the rumen may serve as a hub for various hydrogenotrophic functions and a better understanding of the processes driven by different protozoa may unveil the potential role of ciliates in shaping rumen metabolism.

Rodents consuming the same toxic diet harbor a unique functional core microbiome

Gut microbiota are intrinsic to an herbivorous lifestyle, but very little is known about how plant secondary compounds (PSCs), which are often toxic, influence these symbiotic partners. Here we interrogated the possibility of unique functional core microbiomes in populations of two species of woodrat (Neotoma lepida and bryanti) that have independently converged to feed on the same toxic diet (creosote bush; Larrea tridentata) and compared them to populations that do not feed on creosote bush. Leveraging this natural experiment, we collected samples across a large geographic region in the U.S. desert southwest from 20 populations (~ 150 individuals) with differential ingestion of creosote bush and analyzed three gut regions (foregut, cecum, hindgut) using16S sequencing and shotgun metagenomics. In each gut region sampled, we found a distinctive set of microbes in individuals feeding on creosote bush that were more abundant than other ASVs, enriched in creosote feeding woodrats, and occurred more frequently than would be predicted by chance. Creosote core members were from microbial families e.g., Eggerthellaceae, known to metabolize plant secondary compounds and three of the identified core KEGG orthologs (4-hydroxybenzoate decarboxylase, benzoyl-CoA reductase subunit B, and 2-pyrone-4, 6-dicarboxylate lactonase) coded for enzymes that play important roles in metabolism of plant secondary compounds. The results support the hypothesis that the ingestion of creosote bush sculpts the microbiome across all major gut regions to select for functional characteristics associated with the degradation of the PSCs in this unique diet.

The Alpine ibex (Capra ibex) gut microbiome, seasonal dynamics, and potential application in lignocellulose bioconversion

Aiming to shed light on the biology of wild ruminants, we investigated the gut microbiome seasonal dynamics of the Alpine ibex (Capra ibex) from the Central Italian Alps. Feces were collected in spring, summer, and autumn during non-invasive sampling campaigns. Samples were analyzed by 16S rRNA amplicon sequencing, shotgun metagenomics, as well as targeted and untargeted metabolomics. Our findings revealed season-specific compositional and functional profiles of the ibex gut microbiome that may allow the host to adapt to seasonal changes in available forage, by fine-tuning the holobiont catabolic layout to fully exploit the available food. Besides confirming the importance of the host-associated microbiome in providing the phenotypic plasticity needed to buffer dietary changes, we obtained species-level genome bins and identified minimal gut microbiome community modules of 11-14 interacting strains as a possible microbiome-based solution for the bioconversion of lignocellulose to high-value compounds, such as volatile fatty acids.

A Feeding Trial to Investigate Strategies to Mitigate the Impacts of Pimelea Poisoning in Australian Cattle

Pimelea poisoning of cattle causes distinct symptoms and frequently death, attributable to the toxin simplexin. Pimelea poisoning was induced via addition of ground Pimelea trichostachya plant to the daily feed in a three-month trial with Droughtmaster steers. The trial tested four potential mitigation treatments, namely, biochar, activated biochar, bentonite, and a bacterial inoculum, and incorporated negative and positive control groups. All treatments tested were unable to prevent the development of simplexin poisoning effects. However, steers consuming a bentonite adsorbent together with Pimelea showed lesser rates-of-decline for body weight (P < 0.05) and four hematological parameters (P < 0.02), compared to the positive control group fed Pimelea only. Microbiome analysis revealed that despite displaying poisoning symptoms, the rumen microbial populations of animals receiving Pimelea were very resilient, with dominant bacterial populations maintained over time. Unexpectedly, clinical edema developed in some animals up to 2 weeks after Pimelea dosing was ceased.

Bacillus siamensis Targeted Screening from Highly Colitis-Resistant Pigs Can Alleviate Ulcerative Colitis in Mice

Ulcerative colitis (UC) is often accompanied by intestinal inflammation and disruption of intestinal epithelial structures, which are closely associated with changes in the intestinal microbiota. We previously revealed that Min pigs, a native Chinese breed, are more resistant to dextran sulfate sodium (DSS)-induced colitis than commercial Yorkshire pigs. Characterizing the microbiota in Min pigs would allow identification of the core microbes that confer colitis resistance. By analyzing the microbiota linked to the disease course in Min and Yorkshire pigs, we observed that Bacillus spp. were enriched in Min pigs and positively correlated with pathogen resistance. Using targeted screening, we identified and validated Bacillus siamensis MZ16 from Min pigs as a bacterial species with biofilm formation ability, superior salt and pH tolerance, and antimicrobial characteristics. Subsequently, we administered B. siamensis MZ16 to conventional or microbiota-deficient BALB/c mice with DSS-induced colitis to assess its efficacy in alleviating colitis. B. siamensis MZ16 partially counteracted DSS-induced colitis in conventional mice, but it did not mitigate DSS-induced colitis in microbiota-deficient mice. Further analysis revealed that B. siamensis MZ16 administration improved intestinal ecology and integrity and immunological barrier function in mice. Compared to the DSS-treated mice, mice preadministered B. siamensis MZ16 exhibited improved relative abundance of potentially beneficial microbes (Lactobacillus, Bacillus, Christensenellaceae R7, Ruminococcus, Clostridium, and Eubacterium), reduced relative abundance of pathogenic microbes (Escherichia-Shigella), and maintained colonic OCLN and ZO-1 levels and IgA and SIgA levels. Furthermore, B. siamensis MZ16 reduced proinflammatory cytokine levels by reversing NF-κB and MAPK pathway activation in the DSS group. Overall, B. siamensis MZ16 from Min pigs had beneficial effects on a colitis mouse model by enhancing intestinal barrier functions and reducing inflammation in a gut microbiota-dependent manner.

Inter-kingdom communication and the sympoietic way of life

Organisms are now seen as holobionts, consortia of several species that interact metabolically such that they sustain and scaffold each other's existence and propagation. Sympoiesis, the development of the symbiotic relationships that form holobionts, is critical for our understanding the origins and maintenance of biodiversity. Rather than being the read-out of a single genome, development has been found to be sympoietic, based on multigenomic interactions between zygote-derived cells and symbiotic microbes. These symbiotic and sympoietic interactions are predicated on the ability of cells from different kingdoms of life (e.g., bacteria and animals) to communicate with one another and to have their chemical signals interpreted in a manner that facilitates development. Sympoiesis, the creation of an entity by the interactions of other entities, is commonly seen in embryogenesis (e.g., the creation of lenses and retinas through the interaction of brain and epidermal compartments). In holobiont sympoiesis, interactions between partners of different domains of life interact to form organs and biofilms, wherein each of these domains acts as the environment for the other. If evolution is forged by changes in development, and if symbionts are routinely involved in our development, then changes in sympoiesis can constitute an important factor in evolution.

Association of litter size with the ruminal microbiome structure and metabolomic profile in goats

The Yunshang black goat is a renowned mutton specialist breed mainly originating from China that has excellent breeding ability with varying litter sizes. Litter size is an important factor in the economics of goat farming. However, ruminal microbiome structure might be directly or indirectly regulated by pregnancy-associated factors, including litter sizes. Therefore, the current experiment aimed to evaluate the association of different litter sizes (low versus high) with ruminal microbiome structure by 16S rRNA gene sequencing and metabolomic profiling of Yunshang black does. A total of twenty does of the Yunshang Black breed, approximately aged between 3 and 4 years, were grouped (n = 10 goats/group) into low (D-l) and high (D-h) litter groups according to their litter size (the lower group has ≤ 2 kids/litter and the high group has ≧ 3 kids/litter, respectively). All goats were sacrificed, and collected ruminal fluid samples were subjected to 16S rRNA sequencing and LC-MS/MC Analysis for ruminal microbiome and metabolomic profiling respectively. According to PCoA analysis, the ruminal microbiota was not significantly changed by the litter sizes among the groups. The Firmicutes and Bacteroidetes were the most dominant phyla, with an abundance of 55.34% and 39.62%, respectively. However, Ruminococcaceae_UCG-009, Sediminispirochaeta, and Paraprevotella were significantly increased in the D-h group, whereas Ruminococcaceae_UCG-010 and Howardella were found to be significantly decreased in the D-l group. The metabolic profiling analysis revealed that litter size impacts metabolites as 29 and 50 metabolites in positive and negative ionic modes respectively had significant differences in their regulation. From them, 16 and 24 metabolites of the D-h group were significantly down-regulated in the positive ionic mode, while 26 metabolites were up-regulated in the negative ionic mode for the same group. The most vibrant identified metabolites, including methyl linoleate, acetylursolic acid, O-desmethyl venlafaxine glucuronide, melanostatin, and arginyl-hydroxyproline, are involved in multiple biochemical processes relevant to rumen roles. The identified differential metabolites were significantly enriched in 12 different pathways including protein digestion and absorption, glycerophospholipid metabolism, regulation of lipolysis in adipocytes, and the mTOR signaling pathway. Spearman's correlation coefficient analysis indicated that metabolites and microbial communities were tightly correlated and had significant differences between the D-l and D-h groups. Based on the results, the present study provides novel insights into the regulation mechanisms of the rumen microbiota and metabolomic profiles leading to different fertility in goats, which can give breeders some enlightenments to further improve the fertility of Yunshang Black goats.

Genetic architecture of heritable leaf microbes

Host-associated microbiomes are shaped by both their environment and host genetics, and often impact host performance. The scale of host genetic variation important to microbes is largely unknown yet fundamental to the community assembly of host-associated microbiomes, with implications for the eco-evolutionary dynamics of microbes and hosts. Using Ipomoea hederacea, ivyleaf morning glory, we generated matrilines differing in quantitative genetic variation and leaf shape, which is controlled by a single Mendelian locus. We then investigated the relative roles of Mendelian and quantitative genetic variation in structuring the leaf microbiome and how these two sources of genetic variation contributed to microbe heritability. We found that despite large effects of the environment, both Mendelian and quantitative genetic host variation contribute to microbe heritability and that the cumulative small effect genomic differences due to matriline explained as much or more microbial variation than a single large effect Mendelian locus. Furthermore, our results are the first to suggest that leaf shape itself contributes to variation in the abundances of some phyllosphere microbes.IMPORTANCEWe investigated how host genetic variation affects the assembly of Ipomoea hederacea's natural microbiome. We found that the genetic architecture of leaf-associated microbiomes involves both quantitative genetic variation and Mendelian traits, with similar contributions to microbe heritability. The existence of Mendelian and quantitative genetic variation for host-associated microbes means that plant evolution at the leaf shape locus or other quantitative genetic loci has the potential to shape microbial abundance and community composition.

Dietary supplementation of rumen native microbes improves lactation performance and feed efficiency in dairy cows

Objectives were to determine the effects of 2 dietary microbial additives supplemented to diets of Holstein cows on productive performance and feed efficiency. One-hundred and 17 Holstein cows were enrolled at 61 d (31 to 87 d) postpartum in a randomized complete block design experiment. Cows were blocked by parity group, as nulliparous or multiparous cows and, within parity, by pre-treatment energy-corrected milk yield. Within block, cows were randomly assigned to one of 3 treatments administered as top-dress for 140 d. Treatments consisted of either 100 g of corn meal containing no microbial additive (CON; 15 primiparous and 25 multiparous), 100 g of corn meal containing 5 g of a mixture of Clostridium beijerinckii and Pichia kudriavzevii (G1; 4 × 107 cfu of C. beijerinckii and 1 × 109 cfu of P. kudriavzevii; 14 primiparous and 24 multiparous), or 100 g of corn meal containing 5 g of a mixture of C. beijerinckii, P. kudriavzevii, Butyrivibrio fibrisolvens, and Ruminococcus bovis (G2; 4 × 107 cfu of C. beijerinckii, 1 × 109 cfu of P. kudriavzevii, 1 × 108 cfu of B. fibrisolvens, and 1 × 108 cfu of R. bovis; 15 primiparous and 24 multiparous). Intake of DM, milk yield, and BW were measured daily, whereas milk composition was analyzed at each milking 2 d a week, and body condition was scored twice weekly. Milk samples were collected on d 60 and 62 in the experiment and analyzed for individual fatty acids. The data were analyzed with mixed-effects models with orthogonal contrast to determine the impact of microbial additive (MA; CON vs. 1/2 G1 + 1/2 G2) and type of microbial additive (TMA; G1 vs. G2). Results are described in sequence as CON, G1, and G2. Intake of DM (22.2 vs. 22.4 vs. 22.4 kg/d), BW (685 vs. 685 vs. 685 kg) and the daily BW change (0.40 vs. 0.39 vs. 0.39 kg/d) did not differ among treatments; however, feeding MA tended to increase BCS (3.28 vs. 3.33 vs. 3.36). Supplementing MA increased yields of milk (39.9 vs. 41.3 vs. 41.5 kg/d), ECM (37.9 vs. 39.3 vs. 39.9 kg/d), fat (1.31 vs. 1.37 vs. 1.40 kg/d), total solids (4.59 vs. 4.75 vs. 4.79 kg/d), and ECM per kg of DMI (1.72 vs. 1.76 vs. 1.80 kg/kg). Furthermore, cows fed MA increased yields of pre-formed fatty acids in milk fat (>16C; 435 vs. 463 vs. 488 g/d), particularly unsaturated fatty acids (367 vs. 387 vs. 410 g/d), such as linoleic (C18:2 cis-9, cis-12; 30.9 vs. 33.5 vs. 35.4 g/d) and α-linolenic acids (C18:3 cis-9, cis-12, cis-15; 2.46 vs. 2.68 vs. 2.82 g/d) on d 60 and 62 in the experiment. Collectively, supplementing G1 and G2 improved productive performance of cows with no differences between the 2 MA.

Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis

Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism's collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs' gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions.

Characteristics of rumen microbiota and Prevotella isolates found in high propionate and low methane-producing dairy cows

Ruminal methane production is the main sink for metabolic hydrogen generated during rumen fermentation, and is a major contributor to greenhouse gas (GHG) emission. Individual ruminants exhibit varying methane production efficiency; therefore, understanding the microbial characteristics of low-methane-emitting animals could offer opportunities for mitigating enteric methane. Here, we investigated the association between rumen fermentation and rumen microbiota, focusing on methane production, and elucidated the physiological characteristics of bacteria found in low methane-producing cows. Thirteen Holstein cows in the late lactation stage were fed a corn silage-based total mixed ration (TMR), and feed digestion, milk production, rumen fermentation products, methane production, and rumen microbial composition were examined. Cows were classified into two ruminal fermentation groups using Principal component analysis: low and high methane-producing cows (36.9 vs. 43.2 L/DMI digested) with different ruminal short chain fatty acid ratio [(C2+C4)/C3] (3.54 vs. 5.03) and dry matter (DM) digestibility (67.7% vs. 65.3%). However, there were no significant differences in dry matter intake (DMI) and milk production between both groups. Additionally, there were differences in the abundance of OTUs assigned to uncultured Prevotella sp., Succinivibrio, and other 12 bacterial phylotypes between both groups. Specifically, a previously uncultured novel Prevotella sp. with lactate-producing phenotype was detected, with higher abundance in low methane-producing cows. These findings provide evidence that Prevotella may be associated with low methane and high propionate production. However, further research is required to improve the understanding of microbial relationships and metabolic processes involved in the mitigation of enteric methane.

Feeding Astragalus membranaceus Root Improves the Rumen Fermentation Rate in Housed Goats through the Alteration of the Rumen Community Composition

Although Astragalus membranaceus root (AMR) has been noted as an ingredient in ruminant feed, the impacts of AMR feeding on rumen fermentation and the microbial community structure within the rumen are yet to be evaluated. This study investigated the effects of AMR supplementation on rumen fermentation characteristics and microbial community structures in goats. In two sets of feeding experiments, four Japanese native goats were fed AMR (10 g/kg DM/day/head) for three weeks per experiment. The rumen fluid samples were analyzed using high-performance liquid chromatography for fermentation products and next-generation sequencing for microbial analysis. The rumen fluid samples in the second experiment were also subject to an in vitro anaerobic fermentation test. The results indicated a significant modification, with a higher volatile fatty acid (VFA) content in the rumen fluid of goats in the feeding period than before feeding (p < 0.01). The microbial analysis revealed a significant increase in community diversity (p < 0.05) following AMR feeding, and the rumen bacterial community increased in two families belonging to the order Oscillospirales in Firmicutes (p < 0.05). The phylum Verrucomicrobiota was observed to be significantly less abundant after AMR feeding than during the control period (p < 0.05). Notably, the linear discriminant analysis revealed that the families with largely unknown functions in the rumen (Oscillospiraceae, Rikenellaceae, Muribaculaceae, and vadinBB97) were the determinants of the community split between control and AMR feeding. Increased fermentation rate by AMR feeding was also supported by an in vitro culture experiment, which resulted in faster VFA production without affecting methane production in total gas production. The study demonstrated that AMR can significantly facilitate change in the bacterial community structure in the goat rumen involving a shift of the favoring fibrolytic bacteria towards VFA production. The long-term effects of AMR supplementation and its applicability across different ruminant species, with potential benefits for animal health and productivity, should be addressed.