Dynamic fecal microenvironment properties enable predictions and understanding of peripartum blood oxidative status and nonesterified fatty acids in dairy cows.

The transition period in dairy cows is a critical stage and peripartum oxidative status, negative energy balance (NEB), and inflammation are highly prevalent. Fecal microbial metabolism is closely associated with blood oxidative status and nonesterified fatty acids (NEFA) levels. Here, we investigated dynamic changes in total oxidative status markers and NEFA in blood, fecal microbiome, and metabolome of 30 dairy cows during transition (-21, -7, +7, +21 d relative to calving). Then the Bayesian network and 9 machine-learning algorithms were applied to dismantle their relationship. Our results show that the oxidative status indicator (OSI) of -21, -7, +7 d was higher than +21 d. The plasma concentration of NEFA peaked on +7 d. For fecal microenvironment, a decline in bacterial α diversity was observed at postpartum and in bacterial interactions at +7 d. Conversely, microbial metabolites involved in carbohydrate, lipid, and energy metabolism increased on +7 d. A correlation analysis revealed that 11 and 10 microbial metabolites contributed to OSI and NEFA variations, respectively (arc strength >0.5). The support vector machine (SVM) radial model showed the highest average predictive accuracy (100% and 88.9% in the test and external data sets) for OSI using 1 metabolite and 3 microbiota. The SVM radial model also showed the highest average diagnostic accuracy (100% and 91% in the test and external data sets) for NEFA with 2 metabolites and 3 microbiota. Our results reveal a relationship between variation in the fecal microenvironment and indicators of oxidative status, NEB, and inflammation, which provide a theoretical basis for the prevention and precise regulation of peripartum oxidative status and NEB.

Microbiota-host crosstalk in the newborn and adult rumen at single-cell resolution.

BACKGROUND: The rumen is the hallmark organ of ruminants, playing a vital role in their nutrition and providing products for humans. In newborn suckling ruminants milk bypasses the rumen, while in adults this first chamber of the forestomach has developed to become the principal site of microbial fermentation of plant fibers. With the advent of single-cell transcriptomics, it is now possible to study the underlying cell composition of rumen tissues and investigate how this relates the development of mutualistic symbiosis between the rumen and its epithelium-attached microbes. RESULTS: We constructed a comprehensive cell landscape of the rumen epithelium, based on single-cell RNA sequencing of 49,689 high-quality single cells from newborn and adult rumen tissues. Our single-cell analysis identified six immune cell subtypes and seventeen non-immune cell subtypes of the rumen. On performing cross-species analysis of orthologous genes expressed in epithelial cells of cattle rumen and the human stomach and skin, we observed that the species difference overrides any cross-species cell-type similarity. Comparing adult with newborn cattle samples, we found fewer epithelial cell subtypes and more abundant immune cells, dominated by T helper type 17 cells in the rumen tissue of adult cattle. In newborns, there were more fibroblasts and myofibroblasts, an IGFBP3+ epithelial cell subtype not seen in adults, while dendritic cells were the most prevalent immune cell subtype. Metabolism-related functions and the oxidation-reduction process were significantly upregulated in adult rumen epithelial cells. Using 16S rDNA sequencing, fluorescence in situ hybridization, and absolute quantitative real-time PCR, we found that epithelial Desulfovibrio was significantly enriched in the adult cattle. Integrating the microbiome and metabolome analysis of rumen tissues revealed a high co-occurrence probability of Desulfovibrio with pyridoxal in the adult cattle compared with newborn ones while the scRNA-seq data indicated a stronger ability of pyroxidal binding in the adult rumen epithelial cell subtypes. These findings indicate that Desulfovibrio and pyridoxal likely play important roles in maintaining redox balance in the adult rumen. CONCLUSIONS: Our integrated multi-omics analysis provides novel insights into rumen development and function and may facilitate the future precision improvement of rumen function and milk/meat production in cattle.

Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows.

MOTIVATION: Enhancing the utilization of human-inedible crop by-products by ruminants to produce high-quality milk for human consumption is an emerging global task. We performed a multi-omics-based study to decipher the regulatory biological processes of milk production when cows fed low-quality crop by-products with the aim to improve their utilization. RESULTS: Seven types of different high-throughput omics data were generated across three central organs [rumen, liver and mammary gland (MG)] and biofluids (rumen fluid and blood) that involved in milk production. The integrated multi-omics analysis including metabolomics, metagenomics and transcriptomics showed altered microbiome at compositional and functional levels, microbial metabolites in the rumen, down-regulated genes and associated functions in liver and MG. These changes simultaneously contributed to down-regulated three key metabolic nodes (propionate, glucose and amino acid) across these organs and biofluids that led to lowered milk yield and quality when cows consumed corn stover (CS). Hippuric acid was identified as a biomarker that led to low milk production in CS-fed cows, suggesting a future evaluation parameter related to the metabolic mechanism of low-quality forage utilization. This study unveils the milk production-related biological mechanism across different biofluids and tissues under a low-quality forage diet, which provides a novel understanding and potential improvement strategies for future crop by-products utilization and sustainable ruminant production. AVAILABILITY AND IMPLEMENTATION: The raw files of metagenomics, metabolomics, and transcriptomics data can be accessed at NCBI SRA (No. SRR5028206), EMBI-EBI (No. MTBLS411), and GEO (NO. GSE78524) databases respectively. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene co-expression and alternative splicing analysis of key metabolic tissues to unravel the regulatory signatures of fatty acid composition in cattle.

Increasing the healthy/unhealthy fatty acid (FA) ratio in meat is one of the urgent tasks required to address consumer concerns. However, the regulatory mechanisms ultimately resulting in FA profiles vary among animals and remain largely unknown. In this study, using ~1.2 Tb high-quality RNA-Seq-based transcriptomic data of 188 samples from four key metabolic tissues (rumen, liver, muscle, and backfat) together with the contents of 49 FAs in backfat, the molecular regulatory mechanisms of these tissues contributing to FA formation in cattle were explored. Using this large dataset, the alternative splicing (AS) events, one of the transcriptional regulatory mechanisms in four tissues were identified. The highly conserved and absent AS events were detected in rumen tissue, which may contribute to its functional differences compared with the other three tissues. In addition, the healthy/unhealthy FA ratio related AS events, differential expressed (DE) genes, co-expressed genes, and their functions in four tissues were analysed. Eight key genes were identified from the integrated analysis of DE, co-expressed, and AS genes between animals with high and low healthy/unhealthy FA ratios. This study provides an applicable pipeline for AS events based on comprehensive RNA-Seq analysis and improves our understanding of the regulatory mechanism of FAs in beef cattle.

Longitudinal blood transcriptomic analysis to identify molecular regulatory patterns of bovine respiratory disease in beef cattle.

Bovine respiratory disease (BRD) is the most common disease in beef cattle and leads to considerable economic losses in both beef and dairy cattle. It is important to uncover the molecular mechanisms underlying BRD and to identify biomarkers for early identification of BRD cattle in order to address its impact on production and welfare. In this study, a longitudinal transcriptomic analysis was conducted using blood samples collected from 24 beef cattle at three production stages in the feedlot: 1) arrival (Entry group); 2) when identified as sick (diagnosed as BRD) and separated for treatment (Pulled); 3) prior to marketing (Close-out, representing healthy animals). Expressed genes were significantly different in the same animal among Entry, Pulled and Close-out stages (false discovery rate (FDR) < 0.01 & |Fold Change| > 2). Beef steers at both Entry and Pulled stages presented obvious difference in GO terms (FDR < 0.05) and affected biological functions (FDR < 0.05 & |Z-score| > 2) when compared with animals at Close-out. However, no significant functional difference was observed between Entry and Pulled animals. The interferon signaling pathway showed the most significant difference between animals at Entry/Pulled and Close-out stages (P < .001 & |Z-score| > 2), suggesting the animals initiated antiviral responses at an early stage of infection. Six key genes including IFI6, IFIT3, ISG15, MX1, and OAS2 were identified as biomarkers to predict and recognize sick cattle at Entry. A gene module with 169 co-expressed genes obtained from WGCNA analysis was most positively correlated (R = 0.59, P = 6E-08) with sickness, which was regulated by 11 transcription factors. Our findings provide an initial understanding of the BRD infection process in the field and suggests a subset of novel marker genes for identifying BRD in cattle at an early stage of infection.

Landscape of multi-tissue global gene expression reveals the regulatory signatures of feed efficiency in beef cattle.

MOTIVATION: Feed efficiency is an important trait for sustainable beef production that is regulated by the complex biological process, but the mode of action behinds it has not been clearly defined. Here, we aimed to elucidate the regulatory mechanisms of this trait through studying the landscape of the genome-wide gene expression of rumen, liver, muscle and backfat tissues, the key ones involved in the energy metabolism. RESULTS: The transcriptome of 189 samples across four tissues from 48 beef steers with varied feed efficiency were generated using Illumina HiSeq4000. The analysis of global gene expression profiles of four tissues, functional analysis of tissue-shared and -unique genes, co-expressed network construction of tissue-shared genes, weighted correlations analysis between gene modules and feed efficiency-related traits in each tissue were performed. Among four tissues, the transcriptome of muscle tissue was distinctive from others, while those of rumen and backfat tissues were similar. The associations between co-expressed genes and feed efficiency related traits at single or all tissues level exhibited that the gene expression in the rumen, liver, muscle and backfat were the most correlated with feed conversion ratio, dry matter intake, average daily gain and residual feed intake, respectively. The 19 overlapped genes identified from the strongest module-trait relationships in four tissues are potential generic gene markers for feed efficiency. AVAILABILITY AND IMPLEMENTATION: The distribution of gene expression data can be accessed at https://www.cattleomics.com/transcriptome. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metabolomics Integrated with Transcriptomics Reveals a Subtle Liver Metabolic Risk in Dairy Cows Fed Different Crop By-products.

Ruminants make large contributions to sustainable agriculture by converting crop by-products into agricultural food. Multi-omics integrative analysis helps to uncover the underlying molecular mechanisms. The liver metabolome-transcriptome interface (LMTI) in dairy cows, including 3938 significant correlations (p < 0.01 and |ρ| > 0.6) among 772 genes, 306 metabolites, and 305 microRNAs, is first demonstrated. How different crop by-products, corn stover (CS) and rice straw (RS), affect the liver metabolic functions based on the LMTI is further analyzed. Compared to the CS-fed cows, 13 out of 24 metabolites have lower relative concentrations (variable importance projection > 1.0 and p < 0.05), and 51 out of 68 genes are downregulated in the RS group (p < 0.01 and fold change < -2). Integrated analysis of metabolomics and transcriptomics reveal that lipid metabolism is most enriched including 14 subpathways. The altered metabolites and genes revealed the enriched ketogenesis induced by the linoleic acid pathways (p = 0.017, topology value = 1), which is supported by blood and histomorphometric phenotypes. The above results indicate the foreseeable liver metabolic disorders when RS is fed to cows. These findings provide new insights into the liver metabolic mechanism and into crop by-products utilization using integrative omics technologies.

Lactation-related metabolic mechanism investigated based on mammary gland metabolomics and 4 biofluids' metabolomics relationships in dairy cows.

BACKGROUND: Lactation is extremely important for dairy cows; however, the understanding of the underlying metabolic mechanisms is very limited. This study was conducted to investigate the inherent metabolic patterns during lactation using the overall biofluid metabolomics and the metabolic differences from non-lactation periods, as determined using partial tissue-metabolomics. We analyzed the metabolomic profiles of four biofluids (rumen fluid, serum, milk and urine) and their relationships in six mid-lactation Holstein cows and compared their mammary gland (MG) metabolomic profiles with those of six non-lactating cows by using gas chromatography-time of flight/mass spectrometry. RESULTS: In total, 33 metabolites were shared among the four biofluids, and 274 metabolites were identified in the MG tissues. The sub-clusters of the hierarchical clustering analysis revealed that the rumen fluid and serum metabolomics profiles were grouped together and highly correlated but were separate from those for milk. Urine had the most different profile compared to the other three biofluids. Creatine was identified as the most different metabolite among the four biofluids (VIP = 1.537). Five metabolic pathways, including gluconeogenesis, pyruvate metabolism, the tricarboxylic acid cycle (TCA cycle), glycerolipid metabolism, and aspartate metabolism, showed the most functional enrichment among the four biofluids (false discovery rate < 0.05, fold enrichment >2). Clear discriminations were observed in the MG metabolomics profiles between the lactating and non-lactating cows, with 54 metabolites having a significantly higher abundance (P < 0.05, VIP > 1) in the lactation group. Lactobionic acid, citric acid, orotic acid and oxamide were extracted by the S-plot as potential biomarkers of the metabolic difference between lactation and non-lactation. The TCA cycle, glyoxylate and dicarboxylate metabolism, glutamate metabolism and glycine metabolism were determined to be pathways that were significantly impacted (P < 0.01, impact value >0.1) in the lactation group. Among them, the TCA cycle was the most up-regulated pathway (P < 0.0001), with 7 of the 10 related metabolites increased in the MG tissues of the lactating cows. CONCLUSIONS: The overall biofluid and MG tissue metabolic mechanisms in the lactating cows were interpreted in this study. Our findings are the first to provide an integrated insight and a better understanding of the metabolic mechanism of lactation, which is beneficial for developing regulated strategies to improve the metabolic status of lactating dairy cows.

Metabolomics of four biofluids from dairy cows: potential biomarkers for milk production and quality.

The fundamental understanding of the mechanisms regulating milk protein synthesis is limited. This study aimed to elucidate the metabolic mechanisms of milk production affected by forage quality through studying metabolites from four biofluids (rumen fluid, milk, serum, and urine) collected from 16 lactating cows fed alfalfa hay (AH, high-quality, n = 8) and corn stover (CS, low-quality, n = 8) using gas chromatography-time-of-flight/mass spectrometry. The cows fed AH exhibited higher milk yield (P < 0.01), milk protein yield (P = 0.04), and milk efficiency (P < 0.01) than those fed CS. A total of 165, 195, 218, and 156 metabolites were identified in the rumen fluid, milk, serum, and urine, respectively, while 29 metabolites were found in all four biofluids. In addition 55, 8, 28, and 31 metabolites in each biofluid were significantly different (VIP > 1 and P < 0.05) between the AH- and CS-fed animals. These metabolites were involved in glycine, serine, and threonine metabolism; tyrosine metabolism; and phenylalanine metabolism. Further integrated key metabolic pathway analysis showed that the AH-fed cows may have more comprehensive amino acid metabolisms, suggesting that these metabolite-associated pathways may serve as biomarkers for higher milk yield and better milk protein quality.

- Invited Review - Understanding the functionality of the rumen microbiota: searching for better opportunities for rumen microbial manipulation.

Rumen microbiota play a central role in the digestive process of ruminants. Their remarkable ability to break down complex plant fibers and proteins, converting them into essential organic compounds that provide animals with energy and nutrition. Research on rumen microbiota not only contributes to improving animal production performance and enhancing feed utilization efficiency but also holds the potential to reduce methane emissions and environmental impact. Nevertheless, studies on rumen microbiota face numerous challenges, including complexity, difficulties in cultivation, and obstacles in functional analysis. This review provides an overview of microbial species involved in the degradation of macromolecules, the fermentation processes, and methane production in the rumen, all based on cultivation methods. Additionally, the review introduces the applications, advantages, and limitations of emerging omics technologies such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics, in investigating the functionality of rumen microbiota. Finally, the article offers a forward-looking perspective on the new horizons and technologies in the field of rumen microbiota functional research. These emerging technologies, with continuous refinement and mutual complementation, have deepened our understanding of rumen microbiota functionality, thereby enabling effective manipulation of the rumen microbial community.

Single-cell transcriptomics across 2,534 microbial species reveals functional heterogeneity in the rumen microbiome.

Deciphering the activity of individual microbes within complex communities and environments remains a challenge. Here we describe the development of microbiome single-cell transcriptomics using droplet-based single-cell RNA sequencing and pangenome-based computational analysis to characterize the functional heterogeneity of the rumen microbiome. We generated a microbial genome database (the Bovine Gastro Microbial Genome Map) as a functional reference map for the construction of a single-cell transcriptomic atlas of the rumen microbiome. The atlas includes 174,531 microbial cells and 2,534 species, of which 172 are core active species grouped into 12 functional clusters. We detected single-cell-level functional roles, including a key role for Basfia succiniciproducens in the carbohydrate metabolic niche of the rumen microbiome. Furthermore, we explored functional heterogeneity and reveal metabolic niche trajectories driven by biofilm formation pathway genes within B. succiniciproducens. Our results provide a resource for studying the rumen microbiome and illustrate the diverse functions of individual microbial cells that drive their ecological niche stability or adaptation within the ecosystem.

The hindgut microbiome contributes to host oxidative stress in postpartum dairy cows by affecting glutathione synthesis process.

BACKGROUND: Dairy cows are susceptible to postpartum systemic oxidative stress (OS), which leads to significant production loss and metabolic disorders. The gut microbiota has been linked to host health and stress levels. However, to what extent the gut microbiota is associated with postpartum OS remains unknown. In this study, the contribution of the fecal microbiota to postpartum systemic OS and its underlying mechanisms were investigated by integrating 16S rRNA gene sequencing, metagenomics, and metabolomics in postpartum dairy cattle and by transplanting fecal microbiota from cattle to mice. RESULTS: A strong link was found between fecal microbial composition and postpartum OS, with an explainability of 43.1%. A total of 17 significantly differential bacterial genera and 19 species were identified between cows with high (HOS) and low OS (LOS). Among them, 9 genera and 16 species showed significant negative correlations with OS, and Marasmitruncus and Ruminococcus_sp._CAG:724 had the strongest correlations. The microbial functional analysis showed that the fecal microbial metabolism of glutamine, glutamate, glycine, and cysteine involved in glutathione synthesis was lower in HOS cows. Moreover, 58 significantly different metabolites were identified between HOS and LOS cows, and of these metabolites, 19 were produced from microbiota or cometabolism of microbiota and host. Furthermore, these microbial metabolites were enriched in the metabolism of glutamine, glutamate, glycine, and cysteine. The mice gavaged with HOS fecal microbiota had significantly higher OS and lower plasma glutathione peroxidase and glutathione content than those orally administered saline or LOS fecal microbiota. CONCLUSIONS: Integrated results suggest that the fecal microbiota is responsible for OS and that lower glutathione production plays a causative role in HOS. These findings provide novel insights into the mechanisms of postpartum OS and potential regulatory strategies to alleviate OS in dairy cows. Video Abstract.

Gut microbiome is linked to functions of peripheral immune cells in transition cows during excessive lipolysis.

BACKGROUND: Postpartum dairy cows experiencing excessive lipolysis are prone to severe immunosuppression. Despite the extensive understanding of the gut microbial regulation of host immunity and metabolism, its role during excessive lipolysis in cows is largely unknown. Herein, we investigated the potential links between the gut microbiome and postpartum immunosuppression in periparturient dairy cows with excessive lipolysis using single immune cell transcriptome, 16S amplicon sequencing, metagenomics, and targeted metabolomics. RESULTS: The use of single-cell RNA sequencing identified 26 clusters that were annotated to 10 different immune cell types. Enrichment of functions of these clusters revealed a downregulation of functions in immune cells isolated from a cow with excessive lipolysis compared to a cow with low/normal lipolysis. The results of metagenomic sequencing and targeted metabolome analysis together revealed that secondary bile acid (SBA) biosynthesis was significantly activated in the cows with excessive lipolysis. Moreover, the relative abundance of gut Bacteroides sp. OF04 - 15BH, Paraprevotella clara, Paraprevotella xylaniphila, and Treponema sp. JC4 was mainly associated with SBA synthesis. The use of an integrated analysis showed that the reduction of plasma glycolithocholic acid and taurolithocholic acid could contribute to the immunosuppression of monocytes (CD14+MON) during excessive lipolysis by decreasing the expression of GPBAR1. CONCLUSIONS: Our results suggest that alterations in the gut microbiota and their functions related to SBA synthesis suppressed the functions of monocytes during excessive lipolysis in transition dairy cows. Therefore, we concluded that altered microbial SBA synthesis during excessive lipolysis could lead to postpartum immunosuppression in transition cows. Video Abstract.

Age- and Microbiota-Dependent Cell Stemness Plasticity Revealed by Cattle Cell Landscape.

Newborn ruminants are considered functionally monogastric animals. The poor understanding of cellular differences between newborn and mature ruminants prevents the improvement of health and performance of domestic ruminants. Here, we performed the single-cell RNA sequencing on the rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon, rectum, liver, salivary gland, and mammary gland from newborn and adult cattle. A comprehensive single-cell transcriptomic atlas covering 235,941 high-quality single cells and 78 cell types was deciphered. A Cattle Cell Landscape database (http://cattlecelllandscape.zju.edu.cn) was established to elaborately display the data and facilitate effective annotation of cattle cell types and subtypes for the broad research community. By measuring stemness states of epithelial cells in each tissue type, we revealed that the epithelial cells from newborn forestomach (rumen, reticulum, and omasum) were more transcriptionally indistinct and stochastic compared with the adult stage, which was in contrast to those of abomasum and intestinal tissues. The rapid forestomach development during the early life of calves was driven by epithelial progenitor-like cells with high DNA repair activities and methylation. Moreover, in the forestomach tissues of newborn calves, the Megasphaera genus was involved in regulating the transcriptional plasticity of the epithelial progenitor-like cells by DNA methylation regulation. A novel cell type, the STOML3+ cell, was found to be newborn-specific. It apparently plays a crucial role in stemness maintenance of its own and cholangiocytes in the hepatic microenvironment. Our results reveal that the age- and microbiota-dependent cell stemness plasticity drives the postnatal functional maturity of ruminants.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle.

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Cross-tissue single-cell transcriptomic landscape reveals the key cell subtypes and their potential roles in the nutrient absorption and metabolism in dairy cattle.

Introduction: Dairy cattle are a vitally important ruminant in meeting the demands for high-quality animal protein production worldwide. The complicated biological process of converting human indigestible biomass into highly digestible and nutritious milk is orchestrated by various tissues. However, poorly understanding of the cellular composition and function of the key metabolic tissues hinders the improvement of health and performance of domestic ruminants. Objectives: The cellular heterogeneity, metabolic features, interactions across ten tissue types of lactating dairy cattle were studied at single-cell resolution in the current study. Methods: Unbiased single-cell RNA-sequencing and analysis were performed on the rumen, reticulum, omasum, abomasum, ileum, rectum, liver, salivary gland, mammary gland, and peripheral blood of lactating dairy cattle. Immunofluorescences and fluorescence in situ hybridization were performed to verify cell identity. Results: In this study, we constructed a single-cell landscape covering 88,013 high-quality (500 < genes < 4,000, UMI < 50, 000, and mitochondrial gene ratio < 40% or 15%) single cells and identified 55 major cell types in lactating dairy cattle. Our systematic survey of the gene expression profiles and metabolic features of epithelial cells related to nutrient transport revealed cell subtypes that have preferential absorption of different nutrients. Importantly, we found that T helper type 17 (Th17) cells (highly expressing CD4 and IL17A) were specifically enriched in the forestomach tissues and predominantly interacted with the epithelial cell subtypes with high potential uptake capacities of short-chain fatty acids through IL-17 signaling. Furthermore, the comparison between IL17RAhighIL17RChigh cells (epithelial cells with IL17RA and IL17RC expression levels both greater than 0.25) and other cells explained the importance of Th17 cells in regulating the epithelial cellular transcriptional response to nutrient transport in the forestomach. Conclusion: The findings enhance our understanding of the cellular biology of ruminants and open new avenues for improved animal production of dairy cattle.

Formation of Blood Neutrophil Extracellular Traps Increases the Mastitis Risk of Dairy Cows During the Transition Period.

The current study was conducted to analyze the functions of blood neutrophils in transition cows and their association with postpartum mastitis risk as indicated by somatic cell counts (SCCs) in milk. Seventy-six healthy Holstein dairy cows were monitored from Week 4 prepartum to Week 4 postpartum. Five dairy cows with low SCCs (38 ± 6.0 × 103/mL) and five with high SCCs (3,753 ± 570.0 × 103/mL) were selected based on milk SCCs during the first three weeks of lactation. At Week 1 pre- and postpartum, serum samples were obtained from each cow to measure neutrophil extracellular trap (NET)-related variables, and blood neutrophils were collected for transcriptome analysis by RNA sequencing. The serum concentration of NETs was significantly higher (P < 0.05) in cows with high SCCs than in cows with low SCCs (36.5 ± 2.92 vs. 18.4 ± 1.73 ng/mL). The transcriptomic analysis revealed that the transcriptome differences in neutrophils between high- and low-SCC cows were mainly in cell cycle-related pathways (42.6%), including the cell cycle, DNA damage, and chromosomal conformation, at Week 1 prepartum. The hub genes of these pathways were mainly involved in both the cell cycle and NETosis. These results indicated that the formation of NETs in the blood of transition dairy cows was different between cows with low and high SCCs, which may be used as a potential indicator for the prognosis of postpartum mastitis risk and management strategies of perinatal dairy cows.

An Age Effect of Rumen Microbiome in Dairy Buffaloes Revealed by Metagenomics.

Age is an important factor in shaping the gut microbiome. However, the age effect on the rumen microbial community for dairy buffaloes remains less explored. Using metagenomics, we examined the microbial composition and functions of rumen microbiota in dairy Murrah buffaloes of different ages: Y (1 year old), M (3−5 years old), E (6−8 years old), and O (>9 years old). We found that Bacteroidetes and Firmicutes were the predominant phyla, with Prevotella accounting for the highest abundance at the genus level. The proportion of Bacteroides and Methanobrevibacter significantly increased with age, while the abundance of genus Lactobacillus significantly decreased with age (LDA > 3, p < 0.05). Most differed COG and KEGG pathways were enriched in Y with carbohydrate metabolism, while older buffaloes enriched more functions of protein metabolism and the processing of replication and repair (LDA > 2, p < 0.05). Additionally, the functional contribution analysis revealed that the genera Prevotella and Lactobacillus of Y with more functions of CAZymes encoded genes of glycoside hydrolases and carbohydrate esterases for their roles of capable of metabolizing starch and sucrose-associated oligosaccharide enzyme, hemicellulase, and cellulase activities than the other three groups (LDA > 2, p < 0.05), thus affecting the 1-year-old dairy buffalo rumen carbohydrate metabolism. This study provides comprehensive dairy buffalo rumen metagenome data and assists in manipulating the rumen microbiome for improved dairy buffalo production.

Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle.

BACKGROUND: As the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics. RESULTS: Comparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%. CONCLUSIONS: The results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows. Video Abstract.

Breed dependent regulatory mechanisms of beneficial and non-beneficial fatty acid profiles in subcutaneous adipose tissue in cattle with divergent feed efficiency.

The current study aimed to determine whether breed and feed efficiency affect the molecular mechanisms regulating beneficial and non-beneficial fatty acid profiles in subcutaneous adipose tissue of beef steers. Fatty acid profiling and RNA-Seq based transcriptome analysis were performed on subcutaneous adipose tissues collected from beef steers with three divergent breeds (Angus, ANG, n = 47; Charolais, CHAR, n = 48; Kinsella Composite, KC, n = 48) and different residual feed intake (RFI, a measure of feed efficiency). The comparison of fatty acid profiles showed that KC had higher beneficial FAs compared to the other two breeds. Distinct FA profiles between H-RFIfat and L-RFIfat steers was more obvious for KC steers, where H-RFIfat steers tended to have higher proportion of healthy FAs and lower proportion of the unhealthy FAs. A higher number of differentially expressed (DE) genes were observed for KC steers, whereas ANG and CHAR steers had a lower number of DE genes between H- and L-RFIfat steers. The association analyses of the gene expressions and FA profiles showed that 10 FA metabolism-associated genes together with the one upstream regulator (SREBF1) were associated with the proportion of C18:2n-6, total n-6, PUFA and PUFA/SFA for KC steers but not the other two breeds. Subcutaneous adipose tissue FA profiles and healthy FA index differed in cattle with divergent feed efficiency and such variation was unique for the three examined cattle breeds. Key FA metabolism-associated genes together with SREBF1 which is the upstream regulator of a set of genes involved in lipid metabolism may be of importance for genetic selection of meat with higher healthy FA index in beef cattle.