Integrating uterine microbiome and metabolome to advance the understanding of the uterine environment in dairy cows with metritis

BACKGROUND

Metritis is a prevalent uterine disease that affects the welfare, fertility, and survival of dairy cows. The uterine microbiome from cows that develop metritis and those that remain healthy do not differ from calving until 2 days postpartum, after which there is a dysbiosis of the uterine microbiome characterized by a shift towards opportunistic pathogens such as Fusobacteriota and Bacteroidota. Whether these opportunistic pathogens proliferate and overtake the uterine commensals could be determined by the type of substrates present in the uterus. The objective of this study was to integrate uterine microbiome and metabolome data to advance the understanding of the uterine environment in dairy cows that develop metritis. Holstein cows (n = 104) had uterine fluid collected at calving and at the day of metritis diagnosis. Cows with metritis (n = 52) were paired with cows without metritis (n = 52) based on days after calving. First, the uterine microbiome and metabolome were evaluated individually, and then integrated using network analyses.

RESULTS

The uterine microbiome did not differ at calving but differed on the day of metritis diagnosis between cows with and without metritis. The uterine metabolome differed both at calving and on the day of metritis diagnosis between cows that did and did not develop metritis. Omics integration was performed between 6 significant bacteria genera and 153 significant metabolites on the day of metritis diagnosis. Integration was not performed at calving because there were no significant differences in the uterine microbiome. A total of 3 bacteria genera (i.e. Fusobacterium, Porphyromonas, and Bacteroides) were strongly correlated with 49 metabolites on the day of metritis diagnosis. Seven of the significant metabolites at calving were among the 49 metabolites strongly correlated with opportunistic pathogenic bacteria on the day of metritis diagnosis. The main metabolites have been associated with attenuation of biofilm formation by commensal bacteria, opportunistic pathogenic bacteria overgrowth, tissue damage and inflammation, immune evasion, and immune dysregulation.

CONCLUSIONS

The data integration presented herein helps advance the understanding of the uterine environment in dairy cows with metritis. The identified metabolites may provide a competitive advantage to the main uterine pathogens Fusobacterium, Porphyromonas and Bacteroides, and may be promising targets for future interventions aiming to reduce opportunistic pathogenic bacteria growth in the uterus.

Blood metabolomics and impacted cellular mechanisms during transition into lactation in dairy cows that develop metritis

The objective of this study was to identify metabolites associated with metritis and use them for identification of cellular mechanisms affected during transition into lactation. Holstein cows (n = 104) had blood collected in the prepartum period (d -14 ± 6 relative to calving), at calving (d 0), and at the day of metritis diagnosis (d 7 ± 2 after calving). Cows with reddish or brownish, watery, and fetid discharge were diagnosed with metritis (n = 52). Cows with metritis were paired with herdmates without metritis (n = 52) based on days in milk. The metabolome of plasma samples was evaluated using untargeted gas chromatography time-of-flight mass spectrometry. Univariate analyses included t-tests and fold change analyses. Metabolites with false discovery rate adjusted P ≤ 0.10 on t-tests were used for partial least squares discriminant analysis coupled with permutational analysis using 2,000 permutations. Metabolites with false discovery rate adjusted P ≤ 0.10 on t-tests were also used for enriched pathway analyses and identification of cellular processes. Cows that developed metritis had affected cellular processes associated with lower amino acid metabolism in the prepartum period, greater lipolysis, cell death, and oxidative stress at calving and at metritis diagnosis, and greater leukocyte activation at calving, but lower immune cell activation at metritis diagnosis. In summary, cows that developed metritis had plasma metabolomic changes associated with greater lipolysis, oxidative stress, and a dysregulated immune response which may predispose cows to metritis development.

Differences in uterine and serum metabolome associated with metritis in dairy cows

Objectives were to evaluate differences in the uterine and serum metabolomes associated with metritis in dairy cows. Vaginal discharge was evaluated using a Metricheck device (Simcro) at 5, 7, and 11 d in milk (DIM; herd 1) or 4, 6, 8, 10, and 12 DIM (herd 2). Cows with reddish or brownish, watery, and fetid discharge were diagnosed with metritis (n = 24). Cows with metritis were paired with herdmates without metritis (i.e., clear mucous vaginal discharge or clear lochia with ≤50% of pus) based on DIM and parity (n = 24). Day of metritis diagnosis was considered study d 0. All cows diagnosed with metritis received antimicrobial therapy. The metabolome of uterine lavage collected on d 0 and 5, and serum samples collected on d 0 were evaluated using untargeted gas chromatography time-of-flight mass spectrometry. Normalized data were subjected to multivariate canonical analysis of population using the MultBiplotR and MixOmics packages in R Studio. Univariate analyses including t-test, principal component analyses, partial least squares discriminant analyses, and pathway analyses were conducted using Metaboanalyst. The uterine metabolome differed between cows with and without metritis on d 0. Differences in the uterine metabolome associated with metritis on d 0 were related to the metabolism of butanoate, amino acids (i.e., glycine, serine, threonine, alanine, aspartate, and glutamate), glycolysis and gluconeogenesis, and the tricarboxylic acid cycle. No differences in the serum metabolome were observed between cows diagnosed with metritis and counterparts without metritis on d 0. Similarly, no differences in uterine metabolome were observed between cows with metritis and counterparts not diagnosed with metritis on d 5. These results indicate that the establishment of metritis in dairy cows is associated with local disturbances in amino acid, lipid, and carbohydrate metabolism in the uterus. The lack of differences in the uterine metabolome on d 5 indicates that processes implicated with the disease are reestablished by d 5 after diagnosis and treatment.

Metabolomics Reveals the Effects of High Dietary Energy Density on the Metabolism of Transition Angus Cows

Simple Summary

The increase in the metabolic demand and the dramatically decreased feed intake of cows around parturition often cause a negative energy balance status in cows, which can cause metabolic disorders. Before parturition, dry matter intake of cows starts to decline, and this decline is practically unavoidable. Therefore, increasing the energy density of the diet is extremely important. We used untargeted metabolomics to reveal the effect of high dietary energy density on body metabolism and explore whether it can alleviate negative energy balance. Our research shows that feeding a high-energy diet could significantly improve antioxidant capacity, maintain phosphatidylcholine homeostasis and reduce the negative energy balance of cows by regulating lipid mobilization, muscle mobilization, and protein turnover.

Abstract

The diet energy level plays a vital role in the energy balance of transition cows. We investigated the effects of high dietary energy density on body metabolism. Twenty multiparous Angus cows were randomly assigned to two treatment groups (10 cows/treatment), one receiving a high-energy (HE) diet (NEm = 1.67 Mcal/kg of DM) and the other administered a control (CON) diet (NEm = 1.53 Mcal/kg of DM). The results indicated that feeding a high-energy diet resulted in higher plasma glucose concentration and lower concentrations of plasma NEFA and BHBA on d 14 relative to calving in the HE-fed cows compared to the CON-fed ones. The postpartum plasma levels of T-AOC were lower in cows that received the CON diet than in cows in the HE group, while the concentration of malondialdehyde (MDA) showed an opposite trend. Among the 51 significantly different metabolites, the concentrations of most identified fatty acids decreased in HE cows. The concentrations of inosine, glutamine, and citric acid were higher in HE-fed cows than in CON-fed cows. Enrichment analysis revealed that linoleic acid metabolism, valine, leucine as well as isoleucine biosynthesis, and glycerophospholipid metabolism were significantly enriched in the two groups.

A Targeted Serum Metabolomics GC-MS Approach Identifies Predictive Blood Biomarkers for Retained Placenta in Holstein Dairy Cows

The retained placenta is a common pathology of dairy cows. It is associated with a significant drop in the dry matter intake, milk yield, and increased susceptibility of dairy cows to metritis, mastitis, and displaced abomasum. The objective of this study was to identify metabolic alterations that precede and are associated with the disease occurrence. Blood samples were collected from 100 dairy cows at −8 and −4 weeks prior to parturition and on the day of retained placenta, and only 16 healthy cows and 6 cows affected by retained placenta were selected to measure serum polar metabolites by a targeted gas chromatography–mass spectroscopy (GC-MS) metabolomics approach. A total of 27 metabolites were identified and quantified in the serum. There were 10, 18, and 17 metabolites identified as being significantly altered during the three time periods studied. However, only nine metabolites were identified as being shared among the three time periods including five amino acids (Asp, Glu, Ser, Thr, and Tyr), one sugar (myo-inositol), phosphoric acid, and urea. The identified metabolites can be used as predictive biomarkers for the risk of retained placenta in dairy cows and might help explain the metabolic processes that occur prior to the incidence of the disease and throw light on the pathomechanisms of the disease.

Serum metabolic fingerprinting of pre-lameness dairy cows by GC-MS reveals typical profiles that can identify susceptible cows

The objectives of this study were to identify metabolite fingerprints in the serum related to amino acid (AA), carbohydrate, and lipid metabolism in transition dairy cows at -8 and -4 wks prior to parturition, at +2 wks postpartum during lameness diagnosis as well as at +4 and +8 wks after parturition. All cases of lameness occurred at around +2 wks after parturition. Out of 100 dairy cows included in this nested case-control study only 6 pregnant multiparous (parity: 3.0 ± 0.6, Mean ± SEM) Holstein dairy cows with lameness only and 20 healthy control cows (CON) were selected for serum GC-MS metabolomics analysis. All cows selected were not injured mechanically and had similar parity (3.3 ± 0.6) and body condition score (BCS). A total of 29 metabolites were identified and quantified in the serum. Results showed that 18 and 15 metabolites differentiated pre-lame cows from CON ones at -8 and -4 wks prior to parturition. Ten metabolites were found altered at the week of lameness diagnosis. Of note: pre-lame cows were characterized by greater concentrations of several amino acids including Gly, Leu, Phe, Ser, Val, D-mannose, Myo-inositol, and phosphoric acid (PA) at -8 and -4 wks prior to lameness and at the week of lameness diagnosis. At +4 wks after parturition 11 metabolites were altered in lameness cows, and at +8 wks there were 13 metabolites that differentiated the two groups. The high accuracy of the top 6 metabolites at -8 wks prior to parturition or approximately 9-11 wks before lameness diagnosis (Glu, Orn, Phe, Ser, Val, and PA) and another 5 metabolites at -4 wks before parturition, or approximately 5-7 wks before lameness diagnosis (Leu, Orn, Phe, Ser, and D-mannose) suggest that those metabolites may serve as potential monitoring biomarkers of lameness prior to lameness diagnosis. Data also showed multiple alterations during the week of lameness as well as at +4 and +8 wks postpartum suggesting lame cows are not metabolically healthy several weeks after the incidence of lameness. SIGNIFICANCE: Lameness is one of the top three health issues of dairy cows in Canada that influences early culling of dairy cows. Despite a few efforts, there is scarcity of data regarding metabolic alterations that precede, associate, and follow lameness. We investigated whether alterations in the metabolite signatures prior, during, and after development of lameness can be used to screen cows for susceptibility to lameness, characterize lameness from the metabolic prospective, and predict the outcome of this economically important health issue of dairy cows. The results demonstrate typical metabotypes as shown by increased serum concentrations of Val, Gly, Ser, Leu, Phe, D-mannose, myo-inositol, and phosphoric acid at -8 and -4 wks prior to parturition (or -6 to -10 wks prior to occurrence of lameness) and at the week of lameness diagnosis.

DI/LC-MS/MS-Based Metabolome Analysis of Plasma Reveals the Effects of Sequestering Agents on the Metabolic Status of Dairy Cows Challenged with Aflatoxin B1

The study applied a targeted metabolomics approach that uses a direct injection and tandem mass spectrometry (DI–MS/MS) coupled with a liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based metabolomics of plasma to evaluate the effects of supplementing clay with or without Saccharomyces cerevisiae fermentation product (SCFP) on the metabolic status of dairy cows challenged with aflatoxin B₁. Eight healthy, lactating, multiparous Holstein cows in early lactation (64 ± 11 DIM) were randomly assigned to one of four treatments in a balanced 4 × 4 duplicated Latin square design with four 33 d periods. Treatments were control, toxin (T; 1725 µg aflatoxin B₁ (AFB₁)/head/day), T with clay (CL; 200 g/head/day), and CL with SCFP (YEA; 35 g of SCFP/head/day). Cows in T, CL, and YEA were dosed with aflatoxin B₁ (AFB₁) from days 26 to 30. The sequestering agents were top-dressed from day 1 to 33. On day 30 of each period, 15 mL of blood was taken from the coccygeal vessels and plasma samples were obtained from blood by centrifugation and analyzed for metabolites using a kit that combines DI–MS/MS with LC–MS/MS-based metabolomics. The data were analyzed using the GLIMMIX procedure of SAS. The model included the effects of treatment, period, and random effects of cow and square. Significance was declared at p ≤ 0.05. Biomarker profiles for aflatoxin ingestion in dairy cows fed no sequestering agents were determined using receiver–operator characteristic (ROC) curves, as calculated by the ROCCET web server. A total of 127 metabolites such as amino acids, biogenic amines, acylcarnitines, glycerophospholipids, and organic acids were quantified. Compared with the control, T decreased (p < 0.05) plasma concentrations of alanine, leucine, and arginine and tended to decrease that of citrulline. Treatment with CL had no effects on any of the metabolites relative to the control but increased (p ≤ 0.05) concentrations of alanine, leucine, arginine, and that of citrulline (p = 0.07) relative to T. Treatment with YEA resulted in greater (p ≤ 0.05) concentrations of aspartic acid and lysine relative to the control and the highest (p ≤ 0.05) plasma concentrations of alanine, valine, proline, threonine, leucine, isoleucine, glutamic acid, phenylalanine, and arginine compared with other treatments. The results of ROC analysis between C and T groups revealed that the combination of arginine, alanine, methylhistidine, and citrulline had sufficient specificity and sensitivity (area under the curve = 0.986) to be excellent potential biomarkers of aflatoxin ingestion in dairy cows fed no sequestering agents. This study confirmed the protective effects of sequestering agents in dairy cows challenged with aflatoxin B₁.

Invited review: Advances and challenges in application of feedomics to improve dairy cow production and health

Dairy cattle science has evolved greatly over the past century, contributing significantly to the improvement in milk production achieved today. However, a new approach is needed to meet the increasing demand for milk production and address the increased concerns about animal health and welfare. It is now easy to collect and access large and complex data sets consisting of molecular, physiological, and metabolic data as well as animal-level data (such as behavior). This provides new opportunities to better understand the mechanisms regulating cow performance. The recently proposed concept of feedomics could help achieve this goal by increasing our understanding of interactions between the different components or levels and their impact on animal production. Feedomics is an emerging field that integrates a range of omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, and metatranscriptomics) to provide these insights. In this way, we can identify the best strategies to improve overall animal productivity, product quality, welfare, and health. This approach can help research communities elucidate the complex interactions among nutrition, environment, management, animal genetics, metabolism, physiology, and the symbiotic microbiota. In this review, we summarize the outcomes of the most recent research on omics in dairy cows and highlight how an integrated feedomics approach could be applied in the future to improve dairy cow production and health. Specifically, we focus on 2 topics: (1) improving milk yield and milk quality, and (2) understanding metabolic physiology in transition dairy cows, which are 2 important challenges faced by the dairy industry worldwide.