GC-MS Metabolomics Identifies Metabolite Alterations That Precede Subclinical Mastitis in the Blood of Transition Dairy Cows

Overview of Bovine Mastitis: Application of Metabolomics in Screening Its Predictive and Diagnostic Biomarkers

Bovine mastitis is an inflammatory disease of the mammary glands, and its pathogenesis and diagnosis are complicated. Through qualitative and quantitative analysis of small-molecule metabolites, the metabolomics technique plays an important role in finding biomarkers and studying the metabolic mechanism of bovine mastitis. Therefore, this paper reviews the predictive and diagnostic biomarkers of bovine mastitis that have been identified using metabolomics techniques and that are present in samples such as milk, blood, urine, rumen fluid, feces, and mammary tissue. In addition, the metabolic pathways of mastitis-related biomarkers in milk and blood were analyzed; it was found that the tricarboxylic acid (TCA) cycle was the most significant (FDR = 0.0015767) pathway in milk fluid, and glyoxylate and dicarboxylate metabolism was the most significant (FDR = 0.0081994) pathway in blood. The purpose of this review is to provide useful information for the prediction and early diagnosis of bovine mastitis.

Influence of repeated mastitis on the milk production and metabolic status in the subsequent lactation period of dairy cattle

Recurrent mastitis poses a common challenge on dairy farms. While the impact of repeated mastitis within the same lactation has been investigated, the difference from one lactation to the next, particularly concerning the change of milk and blood metabolites, remains unclear. This study aimed to examine the difference in milk yield, milk composition, and metabolic status in the subsequent lactation between healthy and repeated mastitis in the previous lactation. The study population comprised 50 cows chosen from 400 cows, with 25 having no history of mastitis and 25 experiencing mastitis more than three times during the last lactation. Following dry-off and calving, all cows initiated a new lactation, during which no mastitis was diagnosed until the sample collection period. In the group exposed to repeated mastitis, a significant decrease in milk fat levels was observed in the subsequent lactation, while no change was observed in milk somatic cell count (SCC). Milk collected from cows that had experienced repeated mastitis in the previous lactation exhibited significant increases in the levels of free amino acids, namely valine, proline, and alanine. However, no difference in plasma levels of these amino acids was noted. These results indicate that individuals exposed to repeated mastitis have persistent milk quality changes even after dry-off. Biomarker analysis suggested that the milk valine and proline showed a moderate biomarker potential on Kappa coefficients to characterize cows that have experienced repeated mastitis. Furthermore, the results of biomarker combinations for valine and proline provided the highest specificity (100 %), positive likelihood ratio (infinity), and substantial biomarker potential on kappa coefficients (0.68). These findings significantly enhance our understanding of the pathobiology and etiology of recurrent mastitis and provide a biomarker to characterize cows that have experienced repeated mastitis in the past.

Identifying Predictive Biomarkers of Subclinical Mastitis in Dairy Cows through Urinary Metabotyping

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings.

Serum metabolome differences associated with subclinical intramammary infection caused by Streptococcus agalactiae and Prototheca spp. in multiparous dairy cows

Mastitis is one of the most significant diseases in dairy cows and causes several economic losses. Somatic cell count (SCC) is often used as an indirect diagnostic tool for mastitis, especially for subclinical mastitis (SCM) where no symptoms or signs can be detected. Streptococcus agalactiae is one of the main causes of contagious mastitis, and Prototheca spp. is an alga-inducing environmental mastitis that is not always correlated with increased milk SCC. The aim of this study was to evaluate the changes in the metabolomic profile of blood in relation to subclinical intramammary infection (IMI) in dairy cows. In addition, differences resulting from the etiologic agent causing mastitis were also considered. Forty Holstein-Friesian dairy cows in mid and late lactation were enrolled in this cross-sectional design study. Based on the bacteriological examination of milk, the animals were divided into 3 groups: group CTR (control group; n = 16), group A (affected by SCM with IMI caused by Strep. agalactiae; n = 17), and group P (affected by SCM with IMI caused by Prototheca spp.; n = 7). Blood samples from the jugular vein were collected in tubes containing clot activator; the serum aliquot was stored until metabolomic analysis by 1H-nuclear magnetic resonance spectroscopy. Statistical analysis was conducted by fitting a linear model with the group as the fixed effect and SCC as the covariate. Forty-two metabolites were identified, and among them 10 were significantly different among groups. Groups A and P showed greater levels of His and lactose and lower levels of acetate, Asn, and dimethylamine compared with group CTR. Group A showed high levels of Val, and group P showed high levels of Cit and methylguanidine, as well as lower levels of 3-hydroxybutyrate, acetone, allantoin, carnitine, citrate, and ethanol. These metabolites were related to ruminal fermentations, energy metabolism, urea synthesis and metabolism, immune and inflammatory response, and mammary gland permeability. These results suggest systemic involvement with subclinical IMI and that the metabolic profile of animals with SCM undergoes changes related to the etiological agent of mastitis.

Metabolomics-a powerful tool in livestock research

Advancements in the Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) along with recent developments in omics sciences have resulted in a better understanding of molecular mechanisms and pathways associated with the physio-pathological state of the animal. Metabolomics is a post-genomics tool that deals with small molecular metabolites in a given set of time which provides clear information about the status of an organism. Recently many researchers mainly focus their research on metabolomics studies due to its valuable information in the various fields of livestock management and precision dairying. The main aim of the present review is to provide an insight into the current research output from different sources and application of metabolomics in various areas of livestock including nutri-metabolomics, disease diagnosis advancements, reproductive disorders, pharmaco-metabolomics, genomics studies, and dairy production studies. The present review would be helpful in understanding the metabolomics methodologies and use of livestock metabolomics in various areas in a brief way.

Changes in Uterine Metabolome Associated with Metritis Development and Cure in Lactating Holstein Cows

The objective of this study was to identify alterations in the vaginal discharge (VD) metabolome and potential biomarkers to predict metritis development and a cure in dairy cows. This prospective cohort study was conducted on two dairies located in CA and TX. Vaginal discharge was evaluated and collected using the Metricheck® device. Cows were examined for metritis at 4, 7, and 9 days in milk (DIM). Cows with a fetid, watery, and reddish-brown uterine discharge were classified as having metritis and randomized to receive ceftiofur (n = 10) or remain untreated (n = 7). A cure was defined as the absence of a fetid, watery, reddish-brown uterine discharge at 14 d after enrollment. Vaginal discharge samples were collected from 86 cows within 6 h after parturition, at 4 and 7 DIM, at metritis diagnosis, and at 4 and 7 days after metritis diagnosis. Cows with metritis (MET; n = 17) were paired with counterparts without metritis (HTH) of a similar DIM and parity (n = 34). The uterine metabolome was evaluated using untargeted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Metabolomic data were analyzed using the MetaboAnalyst 5.0. Data were log-transformed and auto-scaled for normalization. Univariate analyses, including the fold-change, were performed to identify the metabolites linked to metritis development and its cure and principal component analysis and partial least squares discriminant analysis were performed to explain metabolite variance between animals developing or not developing metritis and being cured or not being cured of metritis. Comparing HTH with MET cows at calving, 12 metabolites were upregulated, and one was downregulated. At four and seven DIM, 51 and 74 metabolites, respectively, were altered between MET and HTH cows. After metritis development, three and five metabolites were upregulated in cows that were cured and in cows that received treatment and were cured, respectively. In all scenarios, the metabolites lignoceric, malic, and maleic acids, ornithine, and hypotaurine, which are associated with arginine/aminoacyl-tRNA biosynthesis and taurine/purine metabolism, were upregulated in HTH cows. Metritis was associated with changes in the uterine metabolome. Cows not being cured of metritis had changes in the uterus metabolome independent of receiving ceftiofur or remaining untreated. Metabolome analysis may be an important tool to understand the vaginal discharge changes during postpartum and the dynamics of metritis development and cures and help to identify biomarkers to predict metritis being cured.

Differential Responses of Physiological Parameters, Production Traits, and Blood Metabolic Profiling between First- and Second-Parity Holstein Cows in the Comparison of Spring versus Summer Seasons

Heat stress (HS) negatively influences cows' welfare and productivity. Therefore, a better understanding of the physiological and molecular mechanisms of HS responses from multiple parities is paramount for the development of effective management and breeding strategies. In comparison with first-parity cows in the spring (Spring-1), first-parity cows in the summer (Summer-1) had a significantly higher rectal temperature (RT), respiration rate (RR), drooling score (DS), and daily activity (DA), while lower (P < 0.05) daily rumination (DR), seven-day average milk yield (7AMY), milk yield on sampling day (MY_S), milk yield on test day (MY_T), and lactose percentage (LP) were observed. When comparing the spring (Spring-2) and summer (Summer-2) of the second-parity cows, significant differences were also found in RT, RR, DS, DA, and DR (P < 0.05), corresponding to similar trends with the first parity while having smaller changes. Moreover, significantly negative impacts on performance traits were only observed on fat percentage (FP) and LP. These results showed that there were different biological responses between first- and second-parity Holstein cows. Further, 18 and 17 metabolites were involved in the seasonal response of first- and second-parity cows, respectively. Nine differential metabolites were shared between the two parities, and pathway analyses suggested that cows had an inhibited tricarboxylic acid cycle, increased utilization of lipolysis, and a dysregulated gut microbiome during the summer. The metabolites identified exclusively for each parity highlighted the differences in microbial response and host amino acid metabolism between two parities in response to HS. Moreover, glucose, ethanol, and citrate were identified as potential biomarkers for distinguishing individuals between Spring-1 and Summer-1. Ethanol and acetone were better predictors for distinguishing individuals between Spring-2 and Summer-2. Taken together, the present study demonstrated the impact of naturally induced HS on physiological parameters, production traits, and the blood metabolome of Holstein cows. There are different biological responses and regulation mechanisms between first- and second-parity Holstein cows.

Comparison of ruminal microbiota, metabolomics, and milk performance between Montbéliarde×Holstein and Holstein cattle

Holstein cattle are well known for their high average milk yield but are more susceptible to disease and have lower fecundity than other breeds of cattle. The purpose of this study was to explore the relationship between ruminal metabolites and both milk performance and ruminal microbiota composition as a means of assessing the benefits of crossbreeding Montbéliarde and Holstein cattle. This experiment crossbred Holstein with Montbéliarde cattle, aimed to act as a reference for producing high-quality dairy products and improving the overall efficiency of dairy cattle breeding. Based on similar age, parity and lactation time, 46 cows were selected and divided into two groups (n  =  23 per group) for comparison experiment and fed the same formula: Montbéliarde×Holstein (MH, DIM  =  33.23  ±  5.61 d), Holstein (H, DIM  =  29.27  ±  4.23 d). Dairy herd improvement (DHI) data is an important basis for evaluating the genetic quality of bulls, understanding the quality level of milk, and improving feeding management. We collected the DHI data of these cows in the early lactation, middle lactation and late lactation period of 10  months. The results showed that the average milk production and protein content in Montbéliarde×Holstein were 1.76  kg (34.41  kg to 32.65  kg, p  >  0.05) and 0.1% (3.54 to 3.44%, p  <  0.05) higher than in Holstein cattle. Moreover, milk from Montbéliarde×Holstein cattle had lesser somatic cell score (1.66 to 2.02) than Holstein cattle (p  <  0.01). A total of 10 experimental cattle in early lactation were randomly selected in the two groups (Lactation time  =  92.70  ±  6.81), and ruminal fluid were collected by oral gastric tube. Using 16S rRNA microbial sequencing, we compared the ruminal microbiota composition and found that Montbéliarde×Holstein cattle had a lower abundance of Alphaproteobacteria (p  <  0.05) and higher abundance of Selenomonas than Holstein cattle (p  <  0.05). These bacteria play roles in protein degradation, nitrogen fixation and lactic acid degradation. The abundance of Succiniclasticum was also greater in Montbéliarde×Holstein cattle (p  =  0.053). Through ruminal metabolome analysis, we found that the levels of trans-ferulic acid, pyrrole-2-carboxylic acid, and quinaldic acid were significantly increased in Montbéliarde×Holstein cattle, while that of lathosterol was significantly decreased. The changes in the levels of these metabolites could confer improved antioxidant, anti-inflammatory, and antibacterial activities.

Effects of perinatal stress on the metabolites and lipids in plasma of dairy goats

Dairy goats experience metabolic stress during the peripartal period, and their ability to navigate this stage of lactation is related to the occurrence and development of metabolic diseases. Unlike dairy cows, there is a lack of comprehensive analysis of changes in the plasma profiles of peripartal dairy goats, particularly using high-throughput techniques. A subset of 9 clinically-healthy dairy goats were used from a cohort of 96 primiparous Guanzhong dairy goats (BCS, 2.75 ± 0.15). Blood samples were collected at seven time points around parturition (d 21, 14, 7 before parturition, the day of kidding, and d 7, 14, 21 postpartum), were analyzed using untargeted metabolomics and targeted lipidomics. The orthogonal partial least squares discriminant analysis model revealed a total of 31 differential metabolites including p-cresol sulfate, pyruvic acid, cholic acid, and oxoglutaric acid. The pathway enrichment analysis identified phenylalanine metabolism, aminoacyl-tRNA biosynthesis, and citrate cycle as the top three significantly-altered pathways. The Limma package identified a total of 123 differentially expressed lipids. Phosphatidylserine (PS), free fatty acids (FFA), and acylcarnitines (ACs) were significantly increased on the day of kidding, while diacylglycerols (DAG) and triacylglycerols (TAG) decreased. Ceramides (Cer) and lyso-phosphatidylinositols (LPI) were significantly increased during postpartum period, while PS, FFA, and ACs decreased postpartum and gradually returned to antepartum levels. Individual species of FFA and phosphatidylcholines (PC) were segregated based on the differences in the saturation and length of the carbon chain. Overall, this work generated the largest repository of the plasma lipidome and metabolome in dairy goats across the peripartal period, which contributed to our understanding of the multifaceted adaptations of transition dairy goats.

Impact of dry-off and lyophilized Aloe arborescens supplementation on plasma metabolome of dairy cows

Positive effects have been observed as a result of Aloe arborescens supplementation in the dry-off phase in dairy cows. Metabolomic approaches can provide additional information about animal physiology. Thus, we characterized plasma metabolome around dry-off in 12 cows supplemented (AL) or not (CTR) with 10 g/d of lyophilized A. arborescens with an untargeted metabolomic approach. Overall, 1658 mass features were annotated. Regardless of treatment, multivariate statistics discriminated samples taken before and after dry-off. Overall, 490 metabolites were different between late lactation and early dry period, of which 237 were shared between AL and CTR. The most discriminant compounds (pentosidine and luteolin 7-O-glucoside) were related to the more fibrous diet. Pathway analysis indicated that pyrimidine and glycerophospholipid metabolisms were down-accumulated, suggesting reduced rumen microbial activity and liver load. Samples from AL were discriminated from CTR either the day of dry-off or 7 days after. At dry-off, aloin and emodin were the most discriminant metabolites, indicating that Aloe's bioactive compounds were absorbed. Seven days later, 534 compounds were different between groups, and emodin was among the most impacted. Pathway analysis highlighted that glycerophospholipid, pyrimidine, and folate metabolisms were affected. These results might indicate that Aloe has positive effects on liver function and a modulatory effect on rumen fermentation.

Serum 1H nuclear magnetic resonance-based metabolomics of sole lesion development in Holstein cows

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.

Influence of Parturition on Rumen Bacteria and SCFAs in Holstein Cows Based on 16S rRNA Sequencing and Targeted Metabolomics

The rumen fluids from ten cows at Day 3~5 before calving and Day 0 after calving were collected to analyze the composition and quantity of bacterial communities and concentrations of SCFAs. The results showed that the relative abundances of unidentified Lachnospiraceae, Acetitomaculum, Methanobrevibacter, Olsenella, Syntrophococcus, Lachnospira, and Lactobacillus genera were significant increased (p < 0.05), while that of unidentified-Prevotellaceae was notably decreased after calving (p < 0.05). In addition, the concentrations of acetic acid, propionic acid, butyric acid, and caproic acid obviously decreased after calving (p < 0.01). Our findings show that parturition altered the rumen microbiota and their fermentation ability in dairy cows. This study defines a rumen bacteria and metabolic profile of SCFAs associated with parturition in dairy cows.

Metabolomic Analysis of Multiple Biological Specimens (Feces, Serum, and Urine) by 1H-NMR Spectroscopy from Dairy Cows with Clinical Mastitis

Due to huge economic losses to the dairy industry worldwide, mastitis can be considered as one of the most common diseases in dairy cows. This work aimed to study this disease by comparing multiple biological specimens (feces, serum, and urine) from individuals with or without clinical mastitis. This was performed by a single analytical platform, namely ¹H-NMR, through a multi-matrix strategy. Thanks to the high reproducibility of ¹H-NMR, we could characterize 120 molecules across dairy cow feces, serum, and urine. Among them, 23 molecules were in common across the three biofluids. By integrating the results of multi-matrix metabolomics, several pathways pertaining to energy metabolism and amino acid metabolism appeared to be affected by clinical mastitis. The present work wished to deepen the understanding of dairy cow mastitis in its clinical form. Simultaneous analysis of metabolome changes across several key biofluids could facilitate knowledge discovery and the reliable identification of potential biomarkers, which could be, in turn, used to shed light on the early diagnosis of dairy cow mastitis in its subclinical form.

Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers

Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.

Plasma Metabolomic Analysis Reveals the Relationship between Immune Function and Metabolic Changes in Holstein Peripartum Dairy Cows

Dairy cows undergo dynamic physiological changes from late gestation to early lactation, including metabolic changes and immune dysfunction. The aim of this study was to investigate the relationship between immune function and metabolic changes in peripartum dairy cows. Fifteen healthy Holstein dairy cows were enrolled 14 days prior to parturition, and plasma was collected on day −7, 0, 7, and 21 relative to calving. Plasma non-esterified fatty acids (NEFAs), glucose, β-hydroxybutyric acid (BHBA), immunoglobulin G (IgG), tumor necrosis factor alpha (TNF-α), and interleukin-2 levels were measured, and metabolic profiles were determined using ultra-high-performance liquid chromatography−quadrupole time-of-flight mass spectrometry. The data were analyzed using Tukey−Kramer adjustment for multiple comparisons, and multivariate and univariate statistical analyses were performed to screen for differential metabolites. The results showed that the concentrations of NEFAs, glucose, BHBA, and TNF-α in the plasma significantly increased and concentrations of IgG and interleukin-2 in plasma significantly decreased from −7 d to the calving day (p < 0.05). Additionally, the concentrations of glucose, IgG, and TNF-α significantly decreased from 0 to +7 d, and concentrations of NEFAs decreased significantly from +7 to +21 d (p < 0.05). The following six primary metabolic pathways were identified in all time point comparisons, and L-glutamate, linoleic acid, taurine, and L-tryptophan were involved in these major metabolic pathways. Correlation and pathway analyses indicated that a negative energy balance during the transition period adversely affects immune responses in cows, and L-tryptophan exerts immunomodulatory effects through the Trp-Kyn pathway, resulting in depletion of Trp and elevation of Kyn.

Metabolome profiling of plasma reveals different metabolic responses to acute cold challenge between Inner-Mongolia Sanhe and Holstein cattle

Low-temperature conditions influence cattle productivity and survivability. Understanding the metabolic regulations of specific cattle breeds and identifying potential biomarkers related to cold challenges are important for cattle management and optimization of genetic improvement programs. In this study, 28 Inner-Mongolia Sanhe and 22 Holstein heifers were exposed to -25°C for 1 h to evaluate the differences in metabolic mechanisms of thermoregulation. In response to this acute cold challenge, altered rectal temperature was only observed in Holstein cattle. Further metabolome analyses showed a greater baseline of glycolytic activity and mobilization of AA in Sanhe cattle during normal conditions. Both breeds responded to the acute cold challenge by altering their metabolism of volatile fatty acids and AA for gluconeogenesis, which resulted in increased glucose levels. Furthermore, Sanhe cattle mobilized the citric acid cycle activity, and creatine and creatine phosphate metabolism to supply energy, whereas Holstein cattle used greater AA metabolism for this purpose. Altogether, we found that propionate and methanol are potential biomarkers of acute cold challenge response in cattle. Our findings provide novel insights into the biological mechanisms of acute cold response and climatic resilience, and will be used as the basis when developing breeding tools for genetically selecting for improved cold adaptation in cattle.

Discrepancies among healthy, subclinical mastitic, and clinical mastitic cows in fecal microbiome and metabolome and serum metabolome

Mastitis is generally considered a local inflammatory disease caused by the invasion of exogenous pathogens and resulting in the dysbiosis of microbiota and metabolites in milk. However, the entero-mammary pathway theory may establish a possible link between some endogenous gut bacteria and the occurrence and development of mastitis. In the current study, we attempted to investigate differences in the gut microbiota profile and metabolite composition in gut and serum from healthy cows and those with subclinical mastitis and clinical mastitis. Compared with those of healthy cows, the microbial community diversities in the feces of cows with subclinical mastitis (SM) and clinical mastitis (CM) were lower. Lower abundance of Bifidobacterium, Romboutsia, Lachnospiraceae_NK3A20_group, Coprococcus, Prevotellaceae_UCG-003, Ruminococcus, and Alistipes, and higher abundance of the phylum Proteobacteria and the genera Escherichia-Shigella and Streptococcus were observed in CM cows. Klebsiella and Paeniclostridium were significantly enriched in the feces of SM cows. Several similarities were observed in feces and serum metabolites in mastitic cows. Higher levels of proinflammatory lipid products (20-trihydroxy-leukotriene-B4, 13,14-dihydro-15-keto-PGE₂, and 9,10-dihydroxylinoleic acids) and lower levels of metabolites involved in secondary bile acids (deoxycholic acid, 12-ketolithocholic acid), energy (citric acid and 3-hydroxyisovalerylcarnitine), and purine metabolism (uric acid and inosine) were identified in both SM and CM cows. In addition, elevated concentrations of IL-1β, IL-6, tumor necrosis factor-α and decreased concentrations of glutathione peroxidase and superoxide dismutase were detected in the serum of SM and CM cows. Higher serum concentrations of triglyceride and total cholesterol and lower concentrations of high-density lipoproteins in mastitic cows might be related to changes in the gut microbiota and metabolites. These findings suggested a significant difference in the profile of feces microbiota and metabolites in cows with different udder health status, which might increase our understanding of bovine mastitis.

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.

Identification of Serum-Predictive Biomarkers for Subclinical Mastitis in Dairy Cows and New Insights into the Pathobiology of the Disease

Targeted direct injection/liquid chromatography coupled to tandem mass spectrometry-based metabolomics was employed to identify metabolite alterations that could differentiate subclinical mastitis (SCM) from control (CON) dairy cows at -8, -4, disease diagnosis, +4 and +8 wks relative to parturition. We identified and measured 128 metabolites in the serum. Univariate analysis revealed significant alterations of serum metabolites at all five time points studied. By applying multivariate analyses including principle component analysis and partial least squares-discriminant analysis, some of the metabolites were found to have the strongest power for discriminating the SCM from CON cows. The top five metabolites with the greatest variable importance in projection values were selected as potential biomarkers for SCM. A set of five serum metabolites including lysine, ornithine, isoleucine, LysoPC a C17:0, and leucine at -8 wks and five other metabolites including lysine, leucine, isoleucine, kynurenine, and sphingomyelin (SM) C26:0 at -4 wks prepartum were determined as predictive biomarkers for SCM, which provided highly predictive capabilities with AUC (area under the curve) at 1.00. Five metabolites including lysine, leucine, isoleucine, kynurenine, and SM C26:1 in the serum were identified as diagnostic biomarkers for SCM with the AUC of 1.00. Moreover, we observed that distinct metabolic pathways were affected in SCM cows including lysine degradation, biotin, cysteine, methionine, and glutathione metabolism, valine, leucine, and isoleucine biosynthesis and degradation, and aminoacyl-tRNA biosynthesis prior to and during the occurrence of the disease. Results of this study showed that metabolomics analyses can be used to identify susceptible cows to SCM starting from -8 and -4 wks prepartum and that blood can be used to diagnose cows with SCM.

Blood Metabolomic Phenotyping of Dry Cows Could Predict the High Milk Somatic Cells in Early Lactation—Preliminary Results

Subclinical mastitis (SCM) is a very common disease of dairy cows. Currently, somatic cell count (SCC) is used for SCM diagnoses. There are no prognostic tests to detect which cows may develop SCM during the dry-off period. Therefore, the objectives of this study were to identify metabolic alterations in the serum of pre-SCM cows during the dry-off period, at −8 and −4 weeks before calving, through a targeted mass spectrometry (MS) assay. Fifteen cows, free of any disease, and 10 cows affected only by SCM postpartum served as controls (CON) and the SCM group, respectively. Results showed 59 and 47 metabolites that differentiated (p ≤ 0.05) CON and pre-SCM cows at –8 and −4 weeks prior to the expected date of parturition, respectively. Regression analysis indicated that a panel of four serum metabolites (AUC = 0.92, p < 0.001) at −8 weeks and another four metabolites (AUC = 0.92, p < 0.01) at −4 weeks prior to parturition might serve as predictive biomarkers for SCM. Early identification of susceptible cows can enable development of better preventive measurements ahead of disease occurrence.

Dietary Concentrate Supplementation Alters Serum Metabolic Profiles Related to Energy and Amino Acid Metabolism in Grazing Simmental Heifers

Supplementation plays a vital role in the growth performance of grazing heifers. We investigated the effects of maize-based concentrate supplementation on the serum metabolome in grazing heifers. Twenty-four 7-month-old heifers (211.65 ± 4.25 kg BW) were randomly divided into a supplement (SUP) group and a control (CON) group. The results indicated that concentrate supplementation increased the final body weight (BW) of grazing heifers, and the average daily gain (ADG) was 61.5% (P = 0.011) higher in the SUP group than in the CON group. Serum concentrations of total protein (TP), triglyceride (TG), and leptin were higher in the SUP group than in the CON group (p < 0.05). Supplementation increased serum metabolites and amino acids and markedly altered glucose, lipid, and protein metabolism, which contributed to the heifer growth. Furthermore, by multivariate analysis, 45 serum metabolites were identified as significantly different between the two groups. Enrichment analysis revealed that arginine biosynthesis and tryptophan metabolism as well as glycerophospholipid metabolism were significantly enriched between the two groups. We concluded that the growth potential of heifers could be improved by maize-based concentrate supplementation, and the main biological pathways affected were those related to energy and amino acid metabolism.

Effect of Heat Stress on Bovine Mammary Cellular Metabolites and Gene Transcription Related to Amino Acid Metabolism, Amino Acid Transportation and Mammalian Target of Rapamycin (mTOR) Signaling

Simple Summary

This study mainly employed metabolomics technology to determine changes of intracellular metabolite concentrations related to milk protein synthesis induced by heat stress (HS) in bovine mammary epithelial cells. HS was associated with significant differences in intracellular amino acid metabolism resulting in an increase in the intracellular amino acid concentrations. Moreover, HS promoted amino acid transportation and the activity of the mammalian target of rapamycin (mTOR) signaling pathway, which plays an important role as a central regulator of cell metabolism, growth, proliferation and survival. Greater expression of the alpha-S2-casein gene (CSN1S2) was also observed during HS. Overall, our study indicated that bovine mammary epithelial cells may have the ability to resist HS damage and continue milk protein synthesis partly through enhanced intracellular amino acid absorption and metabolism and by activating the mTOR signaling pathway during HS.

Abstract

Heat stress (HS) is one of the most serious factors to negatively affect the lactation performance of dairy cows. Bovine mammary epithelial cells are important for lactation. It was demonstrated that HS decreases the lactation performance of dairy cows, partly through altering gene expression within bovine mammary epithelial tissue. However, the cellular metabolism mechanisms under HS remains largely unknown. The objective of this study was to determine whether HS induced changes in intracellular metabolites and gene transcription related to amino acid metabolism, amino acid transportation and the mTOR signaling pathway. Immortalized bovine mammary epithelial cell lines (MAC-T cells, n = 5 replicates/treatment) were incubated for 12 h at 37 °C (Control group) and 42 °C (HS group). Relative to the control group, HS led to a greater mRNA expression of heat shock protein genes HSF1, HSPB8, HSPA5, HSP90AB1 and HSPA1A. Compared with the control group, metabolomics using liquid chromatography tandem–mass spectrometry identified 417 differential metabolites with p < 0.05 and a variable importance in projection (VIP) score >1.0 in the HS group. HS resulted in significant changes to the intracellular amino acid metabolism of glutathione, phenylalanine, tyrosine, tryptophan, valine, leucine, isoleucine, arginine, proline, cysteine, methionine, alanine, aspartate and glutamate. HS led to a greater mRNA expression of the amino acid transporter genes SLC43A1, SLC38A9, SLC36A1, and SLC3A2 but a lower mRNA expression of SLC7A5 and SLC38A2. Additionally, HS influenced the expression of genes associated with the mTOR signaling pathway and significantly upregulated the mRNA expression of mTOR, AKT, RHEB, eIF4E and eEF2K but decreased the mRNA expression of TSC1, TSC2 and eEF2 relative to the control group. Compared with the control group, HS also led to greater mRNA expression of the CSN1S2 gene. Overall, our study indicates that bovine mammary epithelial cells may have the ability to resist HS damage and continue milk protein synthesis partly through enhanced intracellular amino acid absorption and metabolism and by activating the mTOR signaling pathway during HS.

Nuclear magnetic resonance spectroscopy to investigate the association between milk metabolites and udder quarter health status in dairy cows

Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

Application of Metabolomics in Diagnosis of Cow Mastitis: A Review

Cow mastitis, with high incidence rate and complex cause of disease, is one of the main diseases that affect the development of dairy industry in the world. Clinical mastitis and subclinical mastitis caused by Staphylococcus aureus, Escherichia coli, Streptococcus, and other pathogens have a huge potential safety hazard to food safety and the rapid development of animal husbandry. The economic loss caused by cow mastitis is billions of dollars every year in the world. In recent years, the omics technology has been widely used in animal husbandry with the continuous breakthrough of sequencing technology and the continuous reduction of sequencing cost. For dairy cow mastitis, the traditional diagnostic technique, such as histopathological screening, somatic cell count, milk pH test, milk conductivity test, enzyme activity test, and infrared thermography, are difficult to fully and comprehensively clarify its pathogenesis due to their own limitations. Metabolomics technology is an important part of system biology, which can simultaneously analyze all low molecular weight metabolites such as amino acids, lipids, carbohydrates under the action of complex factors including internal and external environment and in a specific physiological period accurately and efficiently, and then clarify the related metabolic pathways. Metabolomics, as the most downstream of gene expression, can amplify the small changes of gene and protein expression at the level of metabolites, which can more fully reflect the cell function. The application of metabolomics technology in cow mastitis can analyze the hetero metabolites, identify the related biomarkers, and reveal the physiological and pathological changes of cow mammary gland, so as to provide valuable reference for the prediction, diagnosis, and treatment of mastitis. The research progress of metabolomics technology in cow mastitis in recent years was reviewed, in order to provide guidance for the development of cow health and dairy industry safety in this manuscript.

Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review

Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods.

MILK LIPIDS AND SUBCLINICAL MASTITIS

This article deals with the process of obtaining quality raw milk by analyzing its lipid composition. The lipid composition of raw milk depends on many factors, among which, first of all, is the species, the composition of the diet and the physiological state of the breast. In recent years, a large amount of data has accumulated on the fluctuations of certain lipid parameters of milk depending on the type, age, lactation, diet, time of year, exercise, animal husbandry technology, physiological state of the lactating organism in general and breast status in particular. Factors of regulation of fatty acid composition of raw milk: genetically determined parameters of quality and safety; fatty acid composition of the diet; synthesis of fatty acids by microorganisms of the digestive tract; synthesis of fatty acids in the breast; physiological state of the breast. The milk of each species of productive animals has its own specific lipid profile and is used in the formulation of certain dairy products to obtain the planned technological and nutritional parameters. Diagnosis of productive animals for subclinical mastitis involves the use of auxiliary (thermometry, thermography, electrical conductivity) and laboratory research methods: counting the number of somatic cells; use of specialized tests; microbiological studies of milk; biochemical studies of milk. The biochemical component in the diagnosis of subclinical forms of mastitis is underestimated. An increase in body temperature implies an increase in the intensity of heat release during the oxidation of substrates, sometimes due to a decrease in the intensity of synthesis of energy-intensive compounds. There are simply no other sources of energy in the body. The situation is the same with certain parts of the metabolism, which are aimed at the development of protective reactions to the etiological factor aimed at the defeat of the breast. That is why the biochemical composition of breast secretions in the absence of clinical signs of mastitis undergoes biochemical changes and the task of scientists is to develop mechanisms for clear tracking of such changes, identification of animals with subclinical forms of mastitis and effective treatment.

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.

Monitoring the Transition Period in Dairy Cows through 1H NMR-Based Untargeted Metabolomics

The metabolic alterations associated with the increase in milk production make the transition period critical to the health of dairy cows, usually leading to a higher incidence of disease in periparturient animals. In this manuscript, we describe the use of NMR-based untargeted metabolomics to follow how these changes impact the serum metabolome in a group of 28 transition dairy cows with no initial clinical diseases. Principal component analysis (PCA) of serum 1H NMR data from four weeks before calving to 8 weeks after parturition allowed us to clearly identify four stages during the transition period. Pairwise comparisons using orthogonal partial least square discriminant analysis (OPLS-DA) and univariate data analysis led to the identification of 18 metabolites that varied significantly through these stages. Species such as acetate, betaine, and creatine are observed early after calving, while other markers of metabolic stress, including acetone, β-hydroxybutyrate (BHB), and choline, accumulate significantly at the height of milk production. Furthermore, marked variations in the levels of lactate, allantoin, alanine, and other amino acids reveal the activation of different gluconeogenic pathways following parturition. Concomitant with a return to homeostasis, a gradual normalization of the serum metabolome occurs 8 weeks after calving. Correlations of metabolite levels with dietary and metabolic adaptations based on animal parity could also be identified. Overall, these results show that NMR-based chemometric methods are ideally suited to monitor manifestations of metabolic diseases throughout the transition period and to assess the impact of nutritional management schemes on the metabolism of dairy cows.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Short-chain fatty acids can improve lipid and glucose metabolism independently of the pig gut microbiota

BACKGROUND

Previous studies have shown that exogenous short-chain fatty acids (SCFAs) introduction attenuated the body fat deposition in conventional mice and pigs. However, limited studies have evaluated the effects of exogenously introduced SCFAs on the lipid and glucose metabolism independently of the gut microbiota. This study was to investigate the effects of exogenous introduction of SCFAs on the lipid and glucose metabolism in a germ-free (GF) pig model.

METHODS

Twelve hysterectomy-derived newborn pigs were reared in six sterile isolators. All pigs were hand-fed with sterile milk powder for 21 d, then the sterile feed was introduced to pigs for another 21 d. In the second 21-d period, six pigs were orally administrated with 25 mL/kg sterile saline per day and considered as the GF group, while the other six pigs were orally administrated with 25 mL/kg SCFAs mixture (acetic, propionic, and butyric acids, 45, 15, and 11 mmol/L, respectively) per day and regarded as FA group.

RESULTS

Orally administrated with SCFAs tended to increase the adiponectin concentration in serum, enhance the CPT-1 activity in longissimus dorsi, and upregulate the ANGPTL4 mRNA expression level in colon (P < 0.10). Meanwhile, the mRNA abundances of ACC, FAS, and SREBP-1C in liver and CD36 in longissimus dorsi of the FA group were decreased (P < 0.05) compared with those in the GF group. Besides, the mRNA expression of PGC-1α in liver and LPL in longissimus dorsi tended to (P < 0.10) upregulate and downregulate respectively in the FA group. Moreover, oral administration of SCFAs tended to increase the protein level of GPR43 (P < 0.10) and decrease the protein level of ACC (P < 0.10) in liver. Also, oral administration of SCFAs upregulated the p-AMPK/AMPK ratio and the mRNA expressions of GLUT-2 and GYS2 in liver (P < 0.05). In addition, the metabolic pathway associated with the biosynthesis of unsaturated fatty acids was most significantly promoted (P < 0.05) by oral administration of SCFAs.

CONCLUSIONS

Exogenous introduction of SCFAs might attenuate the fat deposition and to some extent improve the glucose control in the pig model, which occurred independently of the gut microbiota.

Metabolomic and Proteomic Profiles Associated With Ketosis in Dairy Cows

Ketosis is a common metabolic disease in dairy cows during early lactation. However, information about the metabolomic and proteomic profiles associated with the incidence and progression of ketosis is still limited. In this study, an integrated metabolomics and proteomics approach was performed on blood serum sampled from cows diagnosed with clinical ketosis (case, ≥ 2.60 mmol/L plasma β-hydroxybutyrate; BHBA) and healthy controls (control, < 1.0 mmol/L BHBA). Samples were taken 2 weeks before parturition and 2 weeks after parturition from 19 animals (nine cases, 10 controls). All serum samples (n = 38) were subjected to Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomic analysis, and 20 samples underwent Data-Independent Acquisition (DIA) LC-MS based proteomic analysis. A total of 97 metabolites and 540 proteins were successfully identified, and multivariate analysis revealed significant differences in both metabolomic and proteomic profiles between cases and controls. We investigated clinical ketosis-associated metabolomic and proteomic changes using statistical analyses. Correlation analysis of statistically significant metabolites and proteins showed 78 strong correlations (correlation coefficient, R ≥ 0.7) between 38 metabolites and 25 proteins, which were then mapped to pathways using IMPaLA. Results showed that ketosis altered a wide range of metabolic pathways, such as metabolism, metabolism of proteins, gene expression and post-translational protein modification, vitamin metabolism, signaling, and disease related pathways. Findings presented here are relevant for identifying molecular targets for ketosis and biomarkers for ketosis detection during the transition period.

Metabolomics in the study of spontaneous animal diseases

Using analytical chemistry techniques such as nuclear magnetic resonance (NMR) spectroscopy and liquid or gas chromatography-mass spectrometry (LC/GC-MS), metabolomics allows detection of most endogenous and exogenous metabolites in a biological sample. Metabolomics has a wide range of applications, and has been employed in nutrition science, toxicology, environmental studies, and systems biology. Metabolomics is particularly useful in biomedical science, and has been used for diagnostic laboratory testing, identifying targets for drug development, and monitoring drug metabolism, mode of action, and toxicity. Despite its immense potential, metabolomics remains underutilized in the study of spontaneous animal diseases. Our aim was to comprehensively review the existing literature on the use of metabolomics in spontaneous veterinary diseases. Three databases were used to find journal articles that applied metabolomics in veterinary medicine. A screening process was then conducted to eliminate references that did not meet the eligibility criteria; only primary research studies investigating spontaneous animal disease were included; 38 studies met the inclusion criteria. The main techniques used were NMR and MS. All studies detected metabolite alterations in diseased animals compared with non-diseased animals. Metabolomics was mainly used to study diseases of the digestive, reproductive, and musculoskeletal systems. Inflammatory conditions made up the largest proportion of studies when articles were categorized by disease process. Following a comprehensive analysis of the literature on metabolomics in spontaneous veterinary diseases, we concluded that metabolomics, although in its early stages in veterinary research, is a promising tool regarding diagnosis, biomarker discovery, and in uncovering new insights into disease pathophysiology.

The Bovine Metabolome

From an animal health perspective, relatively little is known about the typical or healthy ranges of concentrations for many metabolites in bovine biofluids and tissues. Here, we describe the results of a comprehensive, quantitative metabolomic characterization of six bovine biofluids and tissues, including serum, ruminal fluid, liver, Longissimus thoracis (LT) muscle, semimembranosus (SM) muscle, and testis tissues. Using nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography–tandem mass spectrometry (LC–MS/MS), and inductively coupled plasma–mass spectrometry (ICP–MS), we were able to identify and quantify more than 145 metabolites in each of these biofluids/tissues. Combining these results with previous work done by our team on other bovine biofluids, as well as previously published literature values for other bovine tissues and biofluids, we were able to generate quantitative reference concentration data for 2100 unique metabolites across five different bovine biofluids and seven different tissues. These experimental data were combined with computer-aided, genome-scale metabolite inference techniques to add another 48,628 unique metabolites that are biochemically expected to be in bovine tissues or biofluids. Altogether, 51,801 unique metabolites were identified in this study. Detailed information on these 51,801 unique metabolites has been placed in a publicly available database called the Bovine Metabolome Database.

Urinary metabolomics fingerprinting around parturition identifies metabolites that differentiate lame dairy cows from healthy ones

Lameness is a very important disorder of periparturient dairy cows with implications on milk production and composition as well as with consequences on reproductive performance. The aetiology of lameness is not clear although there have been various hypotheses suggested over the years. The objective of this study was to metabotype the urine of dairy cows prior to, during and after the onset of lameness by evaluating at weeks -8, -4 pre-calving, the week of lameness diagnosis, and +4 and +8 weeks post-calving. We used a metabolomics approach to analyse urine samples collected from dairy cows around calving (6 cows with lameness v. 20 healthy control cows). A total of 153 metabolites were identified and quantified using an in-house MS library and classified into 6 groups including: 11 amino acids (AAs), 39 acylcarnitines (ACs), 3 biogenic amines (BAs), 84 glycerophospholipids, 15 sphingolipids and hexose. A total of 23, 36, 40, 23 and 49 metabolites were observed to be significantly different between the lame and healthy cows at -8 and -4 weeks pre-calving, week of lameness diagnosis as well as at +4 and +8 weeks post-calving, respectively. It should be noted that most of the identified metabolites were elevated; however, a few of them were also lower in lame cows. Overall, ACs and glycerophospholipids, specifically phosphatidylcholines (PCs), were the metabolite groups displaying the strongest differences in the urine of pre-lame and lame cows. Lysophosphatidylcholines (LysoPCs), although to a lesser extent than PCs, were altered at all time points. Alterations in urinary AA concentrations were also observed during the current study for four time points. During the pre-calving period, there was an observed elevation of arginine (-8 week), tyrosine (-8 week) and aspartate (-4 week), as well as a depression of urinary glutamate (-4 weeks). In the current study, it was additionally observed that concentrations of several sphingomyelins and one BA were altered in pre-lame and lame cows. Symmetric dimethylarginine was elevated at both -8 weeks pre-calving and the week of lameness diagnosis. Data showed that urinary fingerprinting might be a reliable methodology to be used in the future to differentiate lame cows from healthy ones.

Milk Metabotyping Identifies Metabolite Alterations in the Whole Raw Milk of Dairy Cows with Lameness

The objective of this study was to evaluate whether whole raw milk originating from Holstein dairy cows affected by lameness alters its composition. A total of 20 healthy control cows and 6 cows diagnosed with lameness were selected out of 100 sampled cows in a nested case control study at 2 weeks postpartum, and whole raw milk samples were collected and analyzed with direct inject/liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance. In total, 168 metabolites were identified and quantified using an in-house mass spectrometry library. A total of 35 of the identified metabolites decreased versus control cows. Only two metabolites (i.e., sn-glycero-3-phosphocholine and phosphatidylethanolamine ae C42:1) were increased in the milk of lame cows. In conclusion, milk metabotyping of lame cows revealed significant changes in multiple milk components, including amino acids, lipids, and biogenic amines. Most of the milk compounds identified as altered were lowered, suggesting deflection of nutrients from the mammary gland to the host needs for healing lameness-associated pathological processes.

Clinical Ketosis-Associated Alteration of Gene Expression in Holstein Cows

Ketosis is one of the most prevalent transition metabolic disorders in dairy cows, and has been intrinsically influenced by both genetic and nutritional factors. However, altered gene expression with respective to dairy cow ketosis has not been addressed yet, especially at the genome-wide level. In this study, we recruited nine Holsteins diagnosed with clinical ketosis and ten healthy controls, for which whole blood samples were collected at both prepartum and postpartum. Four groups of blood samples were defined: from cows with ketosis at prepartum (PCK, N = 9) and postpartum (CK, N = 9), respectively, and controls at prepartum (PHC, N = 10) and postpartum (HC, N = 10). RNA-Seq approach was used for investigating gene expression, by which a total of 27,233 genes were quantified with four billion high-quality reads. Subsequently, we revealed 75 and four differentially expressed genes (DEGs) between sick and control cows at postpartum and prepartum, respectively, which indicated that sick and control cows had similar gene expression patterns at prepartum. Meanwhile, there were 95 DEGs between postpartum and prepartum for sick cows, which showed depressed changes of gene expression during this transition period in comparison with healthy cows (428 DEGs). Functional analyses revealed the associated DEGs with ketosis were mainly involved in biological stress response, ion homeostasis, AA metabolism, energy signaling, and disease related pathways. Finally, we proposed that the expression level of STX1A would be potentially used as a new biomarker because it was the only gene that was highly expressed in sick cows at both prepartum and postpartum. These results could significantly help us to understand the underlying molecular mechanisms for incidence and progression of ketosis in dairy cows.

Technological interventions and advances in the diagnosis of intramammary infections in animals with emphasis on bovine population-a review

Mastitis, an inflammation of the udder, is a challenging problem in dairy animals accounting for high economic losses. Disease complexity, degree of economic losses and increasing importance of the dairy industries along with public health concerns envisages devising appropriate diagnostics of mastitis, which can offer rapid, accurate and confirmatory diagnosis. The various diagnostic tests of mastitis have been divided into general or phenotypic and specific or genotypic tests. General or phenotypic tests are those that identify general alterations, which are not specific to any pathogen. Genotypic tests are specific, hence confirmatory for diagnosis of mastitis and include specific culture, polymerase chain reaction (PCR) and its various versions (e.g. qRT-PCR), loop-mediated isothermal amplification, lateral flow assays, nucleotide sequencing, matrix-assisted laser desorption ionization time-of-flight mass spectrometry, and other molecular diagnostic methods. However, for highly specific and confirmatory diagnosis, pure cultures still provide raw materials for more sophisticated diagnostic technological interventions like PCR and nucleotide sequencing. Diagnostic ability of like infra-red thermography (IRT) has been shown to be similar to California mastitis test and also differentiates clinical mastitis from subclinical mastitis cases. As such, IRT can become a convenient and portable diagnostic tool. Of note, magnetic nanoparticles-based colorimetric biosensor assay was developed by using for instance proteolytic activity of plasmin or anti-S. aureus antibody. Last but not least, microRNAs have been suggested to be potential biomarkers for diagnosing bovine mastitis. This review summarizes the various diagnostic tests available for detection of mastitis including diagnosis through general and specific technological interventions and advances.

Mass-spec-based urinary metabotyping around parturition identifies screening biomarkers for subclinical mastitis in dairy cows

The objective of this study was to determine urinary metabotypes of dairy cows prior to, during, and after diagnosis of subclinical mastitis (SCM). Twenty controls (CON) and 6 cows with SCM were included in the study. DI/LC-MS/MS was used to measure 186 metabolites in the urine at -8 and - 4 wks prepartum, disease diagnosis, and at +4 and + 8 wks postpartum. Results showed a total of 24 and 27 metabolites that differentiated SCM and CON cows at -8 and - 4 wks, respectively, with 5 top metabolites having an accuracy to predict SCM of 1.0, for both time point. Altered metabolites included several acylcarnitines (ACs), phosphatidylcholines (PCs), amino acids (AAs), and biogenic amines (BAs). During SCM diagnosis week there were a total of 22 metabolites that differentiated the SCM and CON cows including 13 ACs, 5 AAs, hexose, and phosphatidylethanolamine ae C44:3. The top 5 metabolites Symmetric dimethylarginine (SDMA), methylglutarylcarnitine, dodecanoylcarnitine, phosphatidylethanolamine ae C42:1, and phosphatidylethanolamine ae C42:0 showed an AUC of 1.0. Metabolite alterations continued at +4 and + 8 wks postpartum with 13 (9 ACs, 3 glycerophospholipids, and 1 BA) and 28 metabolites (14 ACs, 2 glycerophospholipids, hexose, 8 AAs, and 2 BAs) that differentiated the two groups, respectively. The top 5 most important metabolites, for both time points, showed AUCs of 1.0. Results of this study showed that typical urinary metabotypes preceded SCM event starting from -8 and - 4 wks prepartum. Metabotypes typical of SCM continued to be present during the week of SCM and at +4 and + 8 wks postpartum. These data show that the urine of dairy cows can be used with very high accuracy for screening dairy cows for susceptibility to SCM prior to entering into the dry off period and a potential new pen-side test can help dairy producers and veterinarians to make selective treatments.

Hepatic metabolomics and transcriptomics to study susceptibility to ketosis in response to prepartal nutritional management

Background

Ketosis in dairy cows is associated with body fat mobilization during the peripartal period. Sub-clinical and clinical ketosis arise more frequently in cows that are overfed energy during the entire dry (last 50 to 45 days prior to parturition) or close-up period (last ~ 28 days prepartum).

Methods

A retrospective analysis was performed on 12 cows from a larger cohort that were fed a higher-energy diet [1.54 Mcal/kg of dry matter (DM); 35.9% of DM corn silage and 13% of DM ground corn] during the close-up dry period, of which 6 did not develop clinical ketosis (OVE, 0.83 mmol/L plasma hydroxybutyrate; BHB) and 6 were diagnosed with clinical ketosis (KET, 1.4 mmol/L BHB) during the first week postpartum. A whole-transcriptome bovine microarray (Agilent Technologies) and metabolomics (GC-MS, LC-MS; Metabolon® Inc.) were used to perform transcript and metabolite profiling of liver tissue harvested at − 10 days relative to parturition which allowed to establish potential associations between prepartal transcriptome/metabolome profiles and susceptibility to clinical ketosis postpartum.

Results

Cows in KET had greater (P = 0.01) overall body weight between − 2 and 1 week around parturition, but similar body condition score than OVE. Although dry matter intake (DMI) did not differ prepartum, KET cows had lower (P < 0.01) DMI and similar milk yield as OVE cows during the first week postpartum. Transcriptome analysis revealed a total of 3065 differentially expressed genes (DEG; P ≤ 0.05) in KET. Metabolomics identified 15 out of 313 total biochemical compounds significantly affected (P ≤ 0.10) in KET. Among those, greater concentrations (P ≤ 0.06, + 2.3-fold) of glycochenodeoxycholate in KET cows also have been detected in humans developing non-alcoholic fatty liver disease. Bioinformatics analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database and the DEG revealed that, among the top 20 most-impacted metabolic pathway categories in KET, 65% were overall downregulated. Those included ‘Metabolism of cofactors and vitamins’, ‘Biosynthesis of other secondary metabolites’, ‘Lipid’, ‘Carbohydrate’, and ‘Glycan biosynthesis and metabolism’. The lower relative concentration of glucose-6-phosphate and marked downregulation of fructose-1,6-bisphosphatase 2 and pyruvate dehydrogenase kinase 4 support a strong impairment in gluconeogenesis in prepartal liver of cows developing KET postpartum. Among the top 20 most-impacted non-metabolic pathways, 85% were downregulated. Pathways such as ‘mTOR signalling’ and ‘Insulin signalling’ were among those. ‘Ribosome’, ‘Nucleotide excision repair’, and ‘Adherens junctions’ were the only upregulated pathways in cows with KET.

Conclusions

The combined data analyses revealed more extensive alterations of the prepartal liver transcriptome than metabolome in cows overfed energy and developing ketosis postpartum. The causative link between these tissue-level adaptations and onset of clinical ketosis needs to be studied further.

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.

Gestational Diabetes Mellitus Changes the Metabolomes of Human Colostrum, Transition Milk and Mature Milk

BACKGROUND Gestational diabetes mellitus (GDM) is a pregnancy complication that is diagnosed by the novel onset of abnormal glucose intolerance. Our study aimed to investigate the changes in human breast milk metabolome over the first month of lactation and how GDM affects milk metabolome. MATERIAL AND METHODS Colostrum, transition milk, and mature milk samples from women with normal uncomplicated pregnancies (n=94) and women with GDM-complicated pregnancies (n=90) were subjected to metabolomic profiling by the use of gas chromatography-mass spectrometry (GC-MS). RESULTS For the uncomplicated pregnancies, there were 59 metabolites that significantly differed among colostrum, transition milk, and mature milk samples, while 58 metabolites differed in colostrum, transition milk, and mature milk samples from the GDM pregnancies. There were 28 metabolites that were found to be significantly different between women with normal pregnancies and women with GDM pregnancies among colostrum, transition milk, and mature milk samples. CONCLUSIONS The metabolic profile of human milk is dynamic throughout the first months of lactation. High levels of amino acids in colostrum and high levels of saturated fatty acids and unsaturated fatty acids in mature milk, which may be critical for neonatal development in the first month of life, were features of both normal and GDM pregnancies.

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.

Plasma metabolite changes in dairy cows during parturition identified using untargeted metabolomics

The metabolic responses of cows undergo substantial changes during the transition from late pregnancy to early lactation. However, the molecular mechanisms associated with these changes in physiological metabolism have not been clearly elucidated. The objective of this study was to investigate metabolic changes in transition cows from the perspective of plasma metabolites. Plasma samples collected from 24 multiparous dairy cows on approximately d 21 prepartum and immediately postpartum were analyzed using ultra-high-performance liquid chromatography/time-of-flight mass spectrometry in positive and negative ion modes. In conjunction with multidimensional statistical methods (principal component analysis and orthogonal partial least squares discriminant analysis), differences in plasma metabolites were identified using the t-test and fold change analysis. Sixty-seven differential metabolites were identified consisting of AA, lipids, saccharides, and nucleotides. The levels of 32 plasma metabolites were significantly higher and those of 35 metabolites significantly lower after parturition than on d 21 prepartum. Pathway analysis indicated that the metabolites that increased from late pregnancy to early lactation were primarily involved in lipid metabolism and energy metabolism, whereas decreased metabolites were related to AA metabolism.

Metabolite Markers for Characterizing Sasang Constitution Type through GC-MS and 1H NMR-Based Metabolomics Study

Sasang constitutional medicine classifies human beings into four types based on their physical and psychological characteristics. Despite its potential value in achieving personalized medicine, the diagnosis of sasang constitution (SC) type is complex and subjective. In this study, gas chromatography–mass spectrometry and ¹H nuclear magnetic resonance–based metabolic analyses were conducted to find maker metabolites in serum and urine according to different SC types. Although some samples were overlapped on orthogonal projection to latent structure discriminant analysis score plots, serum samples showed separation between different SC types. Levels of lactate, glutamate, triglyceride, and fatty acids in serum and glycolic acid in urine of Tae-Eum type were higher than those of So-Eum and So-Yang type. Fatty acids, triglyceride, and lactate levels were found to be metabolites related to body mass index, indicating that marker metabolites for the diagnosis of SC type could be associated with obese. However, Tae-Eum type showed higher lactate levels in serum than So-Yang type for both normal weight and overweight groups, suggesting that the contents of serum lactate might be dependent on the SC type regardless of body weight. These results suggest that metabolomics analysis could be used to determine SC type.

Plasma metabolomic profiles differ at the time of artificial insemination based on pregnancy outcome, in Bos taurus beef heifers

Infertility remains the most prevalent reason for cattle being removed from production environments. We utilized metabolomic profiling to identify metabolites in the blood plasma that may be useful in identifying infertile heifers at the time of artificial insemination (AI). Prior to AI, phenotypic parameters including body condition, weight, and reproductive organ measurements were collected. These were determined not effective at differentiating between fertile and infertile heifers. Analysis of the resulting metabolomic profiles revealed 15 metabolites at significantly different levels (T-test P ≤ 0.05), with seven metabolites having a greater than 2-fold difference (T-test P ≤ 0.05, fold change ≥2, ROC-AUC ≥ 0.80) between infertile and fertile heifers. We further characterized the utility of using the levels of these metabolites in the blood plasma to discriminate between fertile and infertile heifers. Finally, we investigated the potential role inflammation may play by comparing the expression of inflammatory cytokines in the white blood cells of infertile heifers to that of fertile heifers. We found significantly higher expression in infertile heifers of the proinflammatory markers tumor necrosis factor alpha (TNFα), interleukin 6 (IL6), and the C-X-C motif chemokine 5 (CXCL5). Our work offers potentially valuable information regarding the diagnosis of fertility problems in heifers undergoing AI.

LC-MS/MS-Based Metabolome Analysis of Biochemical Pathways Altered by Food Limitation in Larvae of Ivory Shell, Babylonia areolata

Ivory shell, Babylonia areolata, is one of the commercially important mariculture species in China and South East Asia. Survival varies in the artificial hatching and larval rearing of B. areolata. Food deprivation may be involved in rearing mortality, and so, a better understanding of how larvae respond and adjust to starvation is needed. In this study, the metabolite profiles of newly hatched larvae with yolk (I), larvae with yolk exhaustion (II), larvae suffering 24 h starvation after yolk exhaustion (III), and larvae fed with exogenous nutrients after yolk exhaustion (IV) were analyzed by LC-MS/MS. Principal component and cluster analyses revealed differential abundance of metabolite profiles across groups. When compared to metabolite levels of the I group, significantly up-regulated metabolites included polyunsaturated fatty acids, phospholipids, nucleotide, amino acids, and their derivatives were found in the II group, indicating that organisms relied predominantly on glycerophospolipid metabolism and protein-based catabolism for energy production during this stage. During starvation after yolk exhaustion, the levels of all energy related metabolites were significantly reduced, but an increase in products of purine and pyrimidine metabolism indicated an insufficient energy supply and an increase in cellular disintegration. Larvae fed exogenous nutrients can have significantly improved metabolism compared to starved larvae. These findings suggest that metabolomics, using LC-MS/MS, can be used to assess the physiological status and food-affected metabolic changes affecting B. areolata larvae.

Metabolomics Profiling of Serum and Urine in Three Beef Cattle Breeds Revealed Different Levels of Tolerance to Heat Stress

This study was to determine differences in the global metabolic profiles of serum and urine of Xuanhan yellow cattle, Simmental crossbred cattle (Simmental × Xuanhan yellow cattle), and cattle-yaks (Jersey × Maiwa yak) under heat stress (temperature-humidity index remained above 80 for 1 week). A total of 55 different metabolites associated with the three breeds were identified in the serum and urine samples by gas chromatography-mass spectrometry. The metabolic adaptations to heat stress are heterogeneous. Cattle-yaks mobilize a greater amount of body protein to release glucogenic amino acids to supply energy, whereas the tricarboxylic acid cycle is inhibited. Simmental crossbred cattle mobilize a greater amount of body fat to use free fatty acids as an energy source. In comparison with Simmental crossbred cattle and cattle-yaks, Xuanhan yellow cattle have higher glycolytic activity and possess a stronger antioxidant defense system and are, in conclusion, more adapted to hot and humid environments.