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.

Early-Life Exposure to Lipopolysaccharide Induces Persistent Changes in Gene Expression Profiles in the Liver and Spleen of Female FVB/N Mice.

The objective of this study was to investigate how subcutaneous (sc) lipopolysaccharide (LPS) administration affects the gene expression profiles of insulin signaling as well as innate and adaptive immunity genes in mouse livers and spleens. FVB/N female mice were randomly assigned to one of two treatment groups at 5 weeks of age: (1) a six-week subcutaneous injection of saline at 11 µL/h (control-CON), or (2) a six-week subcutaneous injection of LPS from Escherichia coli 0111:B4 at 0.1 µg/g body weight at 11 µL/h. At 106 weeks (i.e., 742 days) after the last treatment, mice were euthanized. Following euthanasia, liver and spleen samples were collected, snap frozen, and stored at -80 °C until gene expression profiling. LPS upregulated nine genes in the liver, according to the findings (Pparg, Frs3, Kras, Raf1, Gsk3b, Rras2, Hk2, Pik3r2, and Myd88). With a 4.18-fold increase over the CON group, Pparg was the most up-regulated gene in the liver. Based on the annotation cluster analysis, LPS treatment upregulated liver genes which are involved in pathways associated with hepatic steatosis, B- and T-cell receptor signaling, chemokine signaling, as well as other types of cancers such as endometrial cancer, prostate cancer, and colorectal cancer. LPS increased the spleen expression of Ccl11, Ccl25, Il6, Cxcl5, Pparg, Tlr4, Nos2, Cxcl11, Il1a, Ccl17, and Fcgr3, all of which are involved in innate and adaptive immune responses and the regulation of cytokine production. Furthermore, functional analysis revealed that cytokine-cytokine receptor interaction and chemokine signaling pathways were the most enriched in LPS-treated mice spleen tissue. Our findings support the notion that early-life LPS exposure can result in long-term changes in gene expression profiling in the liver and spleen tissues of FVB/N female mice.

Association of High Somatic Cell Counts Prior to Dry off to the Incidence of Periparturient Diseases in Holstein Dairy Cows.

Intramammary infections (mastitis) of dairy cows, along with other periparturient diseases, have become problematic within the dairy industry as they lead to loss of milk production. The main objective of this study was to determine whether elevated somatic cell counts (SCC) in cows prior to drying off are related to the incidence of other periparturient diseases. Additionally, we determined whether milk composition and milk yield are affected by a high SCC prior to drying off. Somatic cell counts of milk samples were determined prior to dry off (n = 140) and were used to classify cows in the study as high (>200,000 cells/mL) or low (<200,000 cells/mL) SCC. The composition of milk was analyzed before drying off and at 1 and 2 weeks after calving. The results showed that an elevated SCC before drying off was related to the incidence of ketosis. Cows with a high SCC at drying off also showed an increased likelihood of retained placenta, metritis, and lameness postpartum; however, it was not statistically significant. Milk lactose was lower in cows with high SCC, whereas protein content was lower after parturition. Milk production was lower for cows with pre-drying elevated SCC, particularly for cows with retained placenta, ketosis, and mastitis. In conclusion, cows with pre-drying elevated SCC were more likely to develop disease after parturition and produce less milk and with lower lactose and protein content.

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.

Combination of mouse prion protein with detoxified lipopolysaccharide triggers colon genes related to inflammatory, antibacterial, and apoptotic responses.

Previously we observed that bacterial lipopolysaccharide (LPS) was able to instantly convert recombinant murine prion protein (moPrP) from an alpha-helical to a beta-sheet enriched state. The objectives of this study were to evaluate the effects of a single in vitro administration of recombinant moPrP alone or combined with detoxified lipopolysaccharide (D-LPS) on innate immunity and antibacterial gene expression in the colon of male FVB/N mice, under an Ussing chamber system. Results showed that moPrP alone affected the expression of genes related to both toll-like receptor (TLR)- and nod-like receptor (NLR)-signaling as well as pro- and anti-inflammatory responses. moPrP induced a strong antibacterial response with Slpi mRNA over expression (> 9-fold). Combination of moPrP with D-LPS on the mucosal side of the colon induced genes associated with TLR-signaling, apoptosis, and a very strong antibacterial response (> 35-fold Slpi expression). Administration of moPrP on the mucosal side and D-LPS on the serosal side triggered expression of 12 genes related to TLR signaling, apoptosis, and antibacterial responses, as illustrated by overexpression of Slpi by >30-fold. The over expression of Slpi mRNA was further reaffirmed by ELISA and when moPrP was added to the mucosal side and D-LPS on the serosal side, an increased Slpi protein was observed. Application of combined moPrP and D-LPS on the mucosal side significantly increased the Slpi protein. Results of this study demonstrated that moPrP alone or combined with D-LPS affected the expression of various genes related to inflammation, antibacterial, and apoptotic responses.

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.

Mice Treated Subcutaneously with Mouse LPS-Converted PrPres or LPS Alone Showed Brain Gene Expression Profiles Characteristic of Prion Disease.

Previously, we showed that bacterial lipopolysaccharide (LPS) converts mouse PrPC protein to a beta-rich isoform (moPrPres) resistant to proteinase K. In this study, we aimed to test if the LPS-converted PrPres is infectious and alters the expression of genes related to prion pathology in brains of terminally sick mice. Ninety female FVB/N mice at 5 weeks of age were randomly assigned to 6 groups treated subcutaneously (sc) for 6 weeks either with: (1) Saline (CTR); (2) LPS from Escherichia coli 0111:B4 (LPS), (3) one-time sc administration of de novo generated mouse recombinant prion protein (moPrP; 29-232) rich in beta-sheet by incubation with LPS (moPrPres), (4) LPS plus one-time sc injection of moPrPres, (5) one-time sc injection of brain homogenate from Rocky Mountain Lab (RLM) scrapie strain, and (6) LPS plus one-time sc injection of RML. Results showed that all treatments altered the expression of various genes related to prion disease and neuroinflammation starting at 11 weeks post-infection and more profoundly at the terminal stage. In conclusion, sc administration of de novo generated moPrPres, LPS, and a combination of moPrPres with LPS were able to alter the expression of multiple genes typical of prion pathology and inflammation.

A Multi-Platform Metabolomics Approach Identifies Urinary Metabolite Signatures That Differentiate Ketotic From Healthy Dairy Cows.

Ketosis and subclinical ketosis are widespread among dairy cows especially after calving. Etiopathology of ketosis has been related to negative energy balance. The objective of this study was to investigate metabolite fingerprints in the urine of pre-ketotic, ketotic, and post-ketotic cows to identify potential metabolite alterations that can be used in the future to identify susceptible cows for ketosis and metabolic pathways involved in the development of disease. In this study, NMR, DI/LC-MS/MS, and GC-MS-based metabolomics were used to analyze urine samples from 6 cows diagnosed with ketosis and 20 healthy control (CON) cows at -8 and -4 weeks prepartum, the week (+1 to +3) of ketosis diagnosis, and at +4 and +8 weeks after parturition. Univariate and multivariate analyses were used to screen metabolite panels that can identify cows at their pre-ketotic stage. A total of 54, 42, 48, 16, and 31 differential metabolites between the ketotic and CON cows were identified at -8 and -4 weeks prepartum, ketosis week, and at +4, and +8 weeks postpartum, respectively. Variable importance in projection (VIP) plots ranked the most significant differential metabolites, which differentiated ketotic cows from the CON ones. Additionally, several metabolic pathways that are related to ketosis were identified. Moreover, two promising metabolite panels were identified which clearly separated ketotic from CON cows with excellent level of sensitivity and specificity. Overall, multiple urinary metabolite alterations were identified in pre-ketotic, ketotic, and post-ketotic cows. The metabolite panels identified need to be validated in the future in a larger cohort of animals.

Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones.

INTRODUCTION: Although much is known about lameness application of metabolomics technologies to better understanding its etiology and pathogenesis is of utmost interest. OBJECTIVES: The objective of this study was to investigate serum metabolite alterations in pre-lame, lame and post-lame dairy cows in order to identify potential screening serum metabolite biomarkers for lameness and better understand its pathobiology. METHODS: A combination of direct injection and tandem mass spectrometry (DI-MS/MS) with a reverse-phase liquid chromatography and tandem mass spectrometry (LC-MS/MS) analysis was performed in the serum of six cases of lameness and 20 healthy control cows (CON) at - 8 and - 4 weeks prepartum, at lameness diagnosis week, and at + 4 and + 8 weeks postpartum. RESULTS: Data indicated that pre-lame, lame, and post-lame cows experienced altered concentrations of multiple metabolites. It is interesting to note that throughout the 16-weeks of the study, 7 serum metabolites [e.g., diacyl-phosphatidylcholine (PC aa) C30:0, phosphatidylcholine acyl-alkyl (PC ae) C40:2, sphingomyelin (SM) (OH) C14:1, SM C18:0, isoleucine (Ile), leucine (Leu), and lysine (Lys)] differentiated CON cows from the lame ones. Furthermore, 4 metabolic pathways (i.e., Lys degradation, biotin metabolism, tryptophan (Trp) metabolism, and valine [(Val)-Leu-Ile degradation) were altered in cows with lameness during the onset and progression of the disease. CONCLUSION: Multiple metabolite and pathway alterations were identified in the serum of pre-lame, lame, and post-lame cows that through light into the pathobiology of the disease and that can be used as potential biomarker sets that can predict the risk of lameness in dairy cows.

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.

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.

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.

Mineral Elements in the Raw Milk of Several Dairy Farms in the Province of Alberta.

The objective of this study was to determine the concentrations of 20 minerals in the whole raw milk from Holstein dairy cows in the province of Alberta, Canada. A total of 156 milk samples were collected from 26 dairy farms (n = 6 per farm) and analyzed with inductively coupled plasma mass spectrometry (ICP-MS) for five macrominerals (Ca, Mg, P, K, and Na), ten microminerals (Bo, Co, Cu, Fe, Mn, Mo, Ru, Se, St, and Zn), and five heavy metals (Al, As, Cd, Cr, and Pb). Calculated means were compared with their recommended daily intakes (RDIs) or minimal risk levels (MRLs) obtained from several food safety agencies and with data obtained from a world meta-analytical study we conducted previously. Results of the present study showed differences in the concentrations of multiple minerals between the Alberta farms involved and world averages (WA) and within Alberta farms. Concentrations of macrominerals, including Ca, Mg, P, K, and Na, in the raw milk were greater in Alberta dairy farms than the WA (p < 00.5; except Ca). Of note, concentrations of Ca showed the highest variability among Alberta farms, with 11 farms having lower milk Ca than WA. The other macrominerals were higher than WA in more than 88% of Alberta farms. Data demonstrated that concentrations of microminerals, including Co, Cu, Fe, Mn, and Mo, in Alberta raw milk were lower compared with WA (p < 0.05). Selenium was the only element in raw milk that was found to have higher concentrations in all farms in Alberta vs. WA. High variability was observed for B, Sr, and Zn, which were lower in multiple locations around the province. Concentrations of heavy metals in the Alberta raw milk, including Al, As, Cd, and Pb, were lower than WA, whereas concentrations of Cr were higher. Most importantly, all heavy metals were below their respective MRLs in all analyzed samples. Overall, data from this study showed that raw milk from Holstein dairy cows in Alberta has concentrations of most mineral elements below their MRLs and some of them different from WA. Of note, although concentrations of Se and Zn in the raw milk were higher in Alberta compared with WA, their concentrations were still below their respective MRLs.

Chemical Composition of Commercial Cow's Milk.

Bovine milk is a nutritionally rich, chemically complex biofluid consisting of hundreds of different components. While the chemical composition of cow's milk has been studied for decades, much of this information is fragmentary and very dated. In an effort to consolidate and update this information, we have applied modern, quantitative metabolomics techniques along with computer-aided literature mining to obtain the most comprehensive and up-to-date characterization of the chemical constituents in commercial cow's milk. Using nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography-mass spectrometry (LC-MS), and inductively coupled plasma-mass spectrometry (ICP-MS), we were able to identify and quantify 296 bovine milk metabolites or metabolite species (corresponding to 1447 unique structures) from a variety of commercial milk samples. Through our literature analysis, we also found another 676 metabolites or metabolite species (corresponding to 908 unique structures). Detailed information regarding all 2355 of the identified chemicals in bovine milk have been made freely available through a Web-accessible database called the Milk Composition Database or MCDB ( http://www.mcdb.ca/ ).

Minerals and Heavy Metals in the Whole Raw Milk of Dairy Cows from Different Management Systems and Countries of Origin: A Meta-Analytical Study.

The objective of this meta-analytical study was to investigate selected macrominerals, microminerals, and toxic heavy metals in the bovine whole-raw-milk (WRM) samples of published data. An analytical data set was constructed from 72 different studies from 37 countries with two types of production systems: a conventional production system (CPS) and an organic production system (OPS) compared with commercially available or retail-store-available milk (COM). Results of the meta-analytical study showed differences in the concentrations of macrominerals. Concentrations of Ca, Mg, K, and P were greater in the CPS samples, whereas Na was greater in the COM samples ( P < 0.05). Data also demonstrated that concentrations of microminerals like Cu, I, Fe, Mn, Se, and Zn in the organic WRM were lower ( P < 0.05) compared with the milk from CPS. The highest concentration of Ni was reported for COM ( P < 0.05); however, this value was below the minimum-risk level (MRL). Concentrations of heavy metals like As and Ni were greater in CPS milk than those in organic milk ( P < 0.05). In addition, there were greater concentrations of Cd and Pb in the WRM from CPS versus that from the organic farms. Concentration of Al was lowest in the OPS milk versus Al in the CPS which was 6.5-fold greater than in organic milk. The amount of Hg was below the MRL of 0.01 µmol/L for all production systems. A high variability was observed in the published data regarding the country of origin. Raw milk originating from Europe and North America was characterized by concentrations of macro- and microminerals below the MRLs as compared with that from specific countries, which had some minerals above the MRLs. For example, concentrations of Pb were above the MRL in the milk samples from Brazil, Croatia, Egypt, Mexico, Nigeria, Palestine, Romania, Serbia, and Turkey. Moreover, data from this study indicate that organic dairy farms are characterized by lower concentrations of toxic heavy metals in the WRM compared with those from CPS dairy farms.

Reprint of Milk fever in dairy cows is preceded by activation of innate immunity and alterations in carbohydrate metabolism prior to disease occurrence.

The objective of this study was to search for potential alterations in innate immunity reactants and carbohydrate and lipid metabolism in the blood of transition dairy cows before, during, and after clinical occurrence of milk fever (MF) and identify potential predictive biomarkers of disease. One hundred pregnant multiparous Holstein dairy cows were involved in the study starting from -8wks before the expected day of parturition until +8wks postpartum as part of a large retrospective longitudinal study. Health status, DMI, milk yield, and milk composition were monitored during the whole experimental period. Six healthy cows (CON) and 6 cows that showed clinical signs of MF were selected for blood analyses. Serum concentrations of lactate, non-esterified fatty acids (NEFA), ß-hydroxybutyric acid (BHBA), interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor (TNF), haptoglobin (Hp), and serum amyloid A (SAA) were determined. Results indicated that concentrations of serum lactate, IL-6, TNF, SAA, and Hp were greater in cows with MF than those in the CON group at different time points. Moreover, serum lactate, TNF, SAA, and Hp were greater in cows with MF starting at -8 and -4wks prior to parturition. Both principal component analysis (PCA) and partial least squares - discriminant analysis (PLS-DA) showed separated clusters between MF and CON cows at -8, -4, and disease diagnosis weeks. Overall DMI and milk production were lower in MF-affected cows. Additionally milk fat and fat:protein ratio were greater in MF. In conclusion, cows affected by MF showed alterations in some of the innate immunity reactants and metabolites related to carbohydrate metabolism several weeks prior to appearance of clinical signs of MF. Variable importance in projection plots demonstrated that TNF and SAA in the serum were the strongest discriminators between MF cows and CON ones, which might be useful as predictive biomarkers of the disease.

Milk fever in dairy cows is preceded by activation of innate immunity and alterations in carbohydrate metabolism prior to disease occurrence.

The objective of this study was to search for potential alterations in innate immunity reactants and carbohydrate and lipid metabolism in the blood of transition dairy cows before, during, and after clinical occurrence of milk fever (MF) and identify potential predictive biomarkers of disease. One hundred pregnant multiparous Holstein dairy cows were involved in the study starting from -8wks before the expected day of parturition until +8wks postpartum as part of a large retrospective longitudinal study. Health status, DMI, milk yield, and milk composition were monitored during the whole experimental period. Six healthy cows (CON) and 6 cows that showed clinical signs of MF were selected for blood analyses. Serum concentrations of lactate, non-esterified fatty acids (NEFA), ß-hydroxybutyric acid (BHBA), interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor (TNF), haptoglobin (Hp), and serum amyloid A (SAA) were determined. Results indicated that concentrations of serum lactate, IL-6, TNF, SAA, and Hp were greater in cows with MF than those in the CON group at different time points. Moreover, serum lactate, TNF, SAA, and Hp were greater in cows with MF starting at -8 and -4wks prior to parturition. Both principal component analysis (PCA) and partial least squares - discriminant analysis (PLS-DA) showed separated clusters between MF and CON cows at -8, -4, and disease diagnosis weeks. Overall DMI and milk production were lower in MF-affected cows. Additionally milk fat and fat:protein ratio were greater in MF. In conclusion, cows affected by MF showed alterations in some of the innate immunity reactants and metabolites related to carbohydrate metabolism several weeks prior to appearance of clinical signs of MF. Variable importance in projection plots demonstrated that TNF and SAA in the serum were the strongest discriminators between MF cows and CON ones, which might be useful as predictive biomarkers of the disease.

DI/LC-MS/MS-Based Metabolic Profiling for Identification of Early Predictive Serum Biomarkers of Metritis in Transition Dairy Cows.

The objectives of this study were to evaluate alterations of metabolites in the blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected from both healthy and metritic cows during -8, -4, disease diagnosis, +4, and +8 wks relative to parturition. Results indicated that cows with metritis experienced altered concentrations of serum amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the entire experimental period. Moreover, two sets of predictive biomarker models and one set of diagnostic biomarker models for metritis were developed, and all of them showed high sensitivity and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for metritis in transition dairy cows.

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

The objectives of this study were to determine alterations in the serum metabolites related to amino acid (AA), carbohydrate, and lipid metabolism in transition dairy cows before diagnosis of subclinical mastitis (SCM), during, and after diagnosis of disease. A subclinical mastitis case was determined as a cow having somatic cell count (SCC) > 200 000/mL of milk for two or more consecutive reports. Blood samples were collected from 100 Holstein dairy cows at five time points at -8 and -4 weeks before parturition, at the week of SCM diagnosis, and +4 and +8 weeks after parturition. Twenty healthy control cows (CON) and six cows that were diagnosed with SCM were selected for serum analysis with GC-MS. At -8 weeks a total of 13 metabolites were significantly altered in SCM cows. In addition, at the week of SCM diagnosis 17 metabolites were altered in these cows. Four weeks after parturition 10 metabolites were altered in SCM cows and at +8 weeks 11 metabolites were found to be different between the two groups. Valine (Val), serine (Ser), tyrosine (Tyr), and phenylalanine (Phe) had very good predictive abilities for SCM and could be used at -8 weeks and -4 weeks before calving. Combination of Val, isoleucine (Ile), Ser, and proline (Pro) can be used as diagnostic biomarkers of SCM during early stages of lactation at +4 to +8 weeks after parturition. In conclusion, SCM is preceded and followed by alteration in AA metabolism.

Dairy cows affected by ketosis show alterations in innate immunity and lipid and carbohydrate metabolism during the dry off period and postpartum.

The objective of this investigation was to search for alterations in blood variables related to innate immunity and carbohydrate and lipid metabolism during the transition period in cows affected by ketosis. One hundred multiparous Holstein dairy cows were involved in the study. Blood samples were collected at -8, -4, week of disease diagnosis (+1 to +3weeks), and +4weeks relative to parturition from 6 healthy cows (CON) and 6 cows with ketosis and were analyzed for serum variables. Results showed that cows with ketosis had greater concentrations of serum ß-hydroxybutyric acid (BHBA), interleukin (IL)-6, tumor necrosis factor (TNF), serum amyloid A (SAA), and lactate in comparison with the CON animals. Serum concentrations of BHBA, IL-6, TNF, and lactate were greater starting at -8 and -4weeks prior to parturition in cows with ketosis vs those of CON group. Cows with ketosis also had lower DMI and milk production vs CON cows. Milk fat also was lower in ketotic cows at diagnosis of disease. Cows affected by ketosis showed an activated innate immunity and altered carbohydrate and lipid metabolism several weeks prior to diagnosis of disease. Serum IL-6 and lactate were the strongest discriminators between ketosis cows and CON ones before the occurrence of ketosis, which might be useful as predictive biomarkers of the disease state.