Ketone bodies in milk and blood of dairy cows: relationship between concentrations and utilization for detection of subclinical ketosis

The association between time-series milk β-hydroxybutyrate dynamics and early reproductive performance of dairy cows

The DeLaval Herd Navigator is an on-farm sensor system that measures on a frequent basis milk progesterone (P4) and β-hydroxybutyrate (BHB) in individual cows to closely monitor reproductive performance and energy balance. This information provides the opportunity to investigate the dynamics of BHB measured in milk (mBHB) and study the association between mBHB and early reproductive performance. The objectives of the study were (1) to describe mBHB dynamics within the first 20 d in milk (DIM), and (2) to evaluate the association between mBHB dynamics and early reproductive performance at cow-level. Two-year time-series data from 4,133 dairy cows in 38 Dutch dairy farms were available for analysis. Data included information on mBHB, daily milk yield and the indicators of early reproductive performance, days from calving to resumption of cyclicity, days from calving to first estrus, and days from calving to first insemination. The following mBHB dynamic parameters were defined based on the first 20 DIM for each individual cow: average mBHB (AvgBHB), DIM when mBHB was for the first time ≥80 μmol/L (OnsetKeto), the total number of consecutive days a cow had mBHB concentration ≥80 μmol/L, and the number of measurements mBHB concentration was ≥80 μmol/L. Three Cox proportional hazard regression models with random herd effect were developed to evaluate the association between cow level mBHB dynamics and days from calving to resumption of cyclicity, first estrus, and first insemination. Results showed that the mean AvgBHB within 20 DIM among all cows was 73 μmol/L. The mean OnsetKeto within 20 DIM, was 8 DIM. Among all cows having hyperketolactia, 55.8% (1,350/2,419) had OnsetKeto in the first week of lactation. In total, 41.5% (1,714/4,133) of the cows did not have OnsetKeto in the first 20 DIM. An early onset of hyperketolactia was associated with delayed fertility events. Cows with higher AvgBHB have a prolonged time interval from calving to resumption of cyclicity and first estrus. Information on mBHB dynamics and the association with early reproductive performance provides insights that might be helpful to improve reproductive performance of individual dairy cows.

The Most Important Metabolic Diseases in Dairy Cattle during the Transition Period

This review paper provides an in-depth analysis of three critical metabolic diseases affecting dairy cattle such as subacute ruminal acidosis (SARA), ketosis, and hypocalcemia. SARA represents a disorder of ruminal fermentation that is characterized by extended periods of depressed ruminal pH below 5.5-5.6. In the long term, dairy herds experiencing SARA usually exhibit secondary signs of the disease, such as episodes of laminitis, weight loss and poor body condition despite adequate energy intake, and unexplained abscesses usually 3-6 months after an episode of SARA. Depressed milk-fat content is commonly used as a diagnostic tool for SARA. A normal milk-fat test in Holstein dairy cows is >4%, so a milk-fat test of <3% can indicate SARA. However, bulk tank testing of milk fat is inappropriate to diagnose SARA at the herd level, so when >4 cows out of 12 and <60 days in milk are suspected to have SARA it can be considered that the herd has a problem. The rapid or abrupt introduction of fresh cows to high-concentrate diets is the most common cause of SARA. Changes in ruminal bacterial populations when exposed to higher concentrate rations require at least about 3 weeks, and it is recommended that concentrate levels increase by no more than 400 g/day during this period to avoid SARA. Ketosis, a prevalent metabolic disorder in dairy cattle, is scrutinized with a focus on its etiological factors and the physiological changes leading to elevated ketone bodies. In total mix ration-fed herds, an increased risk of mastitis and reduced fertility are usually the first clinical signs of ketosis. All dairy cows in early lactation are at risk of ketosis, with most cases occurring in the first 2-4 weeks of lactation. Cows with a body condition score ≥3.75 on a 5-point scale at calving are at a greater risk of ketosis than those with lower body condition scores. The determination of serum or whole blood acetone, acetoacetate, beta-hydroxybutyrate (BHB) concentration, non-esterified fatty acids (NEFA), and liver biopsies is considered the best way to detect and monitor subclinical ketosis, while urine or milk cowside tests can also be used in on-farm monitoring programs. Concentrations >1.0 mmol/L or 1.4 mmol/L blood or serum BHB are considered diagnostic of subclinical ketosis. The standard threshold used for blood is 1.2 mmol/L, which corresponds to thresholds of 100 mcmol/L for milk and 15 mg/dL for urine. Oral administration of propylene glycol (250-400 g, every 24 h for 3-5 days) is the standard and most efficacious treatment, as well as additional therapy with bolus glucose treatment. Hypocalcemia is a disease of adult dairy cows in which acute hypocalcemia causes acute to peracute, afebrile, flaccid paralysis that occurs most commonly at or soon after parturition. Dairy cows are at considerable risk for hypocalcemia at the onset of lactation, when daily calcium excretion suddenly increases from about 10 g to 30 g per day. Cows with hypocalcemia have a more profound decrease in blood calcium concentration-typically below 5.5 mg/dL. The prevention of parturient paresis has been historically approached by feeding cows low-calcium diets during the dry period. Negative calcium balance triggers calcium mobilization before calving and better equips the cow to respond to the massive calcium needs at the onset of lactation. Calcium intake must be limited to <20 g per day for calcium restriction to be effective. The most practical and proven method for monitoring hypocalcemia is by feeding cows an acidogenic diet for ~3 weeks before calving. Throughout the review, emphasis is placed on the importance of early diagnosis and proactive management strategies to mitigate the impact of these metabolic diseases on dairy cattle health and productivity. The comprehensive nature of this paper aims to serve as a valuable resource for veterinarians, researchers, and dairy farmers seeking a deeper understanding of these prevalent metabolic disorders in dairy cattle.

Prediction of key milk biomarkers in dairy cows through milk mid-infrared spectra and international collaborations

At the individual cow level, suboptimum fertility, mastitis, negative energy balance, and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were (1) to assess the potential of milk mid-infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6 phosphate [glucose-6P], free glucose), ketosis (β-hydroxybutyrate [BHB] and acetone), mastitis (N-acetyl-β-d-glucosaminidase activity [NAGase] and lactate dehydrogenase), and fertility (progesterone); (2) to test alternative methodologies to partial least squares (PLS) regression to better account for the specific asymmetric distribution of the biomarkers; and (3) to create robust models by merging large datasets from 5 international or national projects. Benefiting from this international collaboration, the dataset comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents, whereas the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. Partial least squares regression was used as the reference basis, and compared with a random modification of distribution associated with PLS (random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS), and support vector machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low versus high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation dataset. The remaining 80% of herds were used as the calibration dataset. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose, and lactate dehydrogenase (coefficient of determination in external herd validation [R2v] = 0.48, 0.58, 0.28, and 0.24, respectively). For other molecules, PLS-random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase, and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15, respectively). Hence, PLS and SVM based on the entire dataset provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis, and mastitis in dairy cows, which in turn have major influences on their fertility and survival.

Association between hyperketolactia and production in early-lactating dairy cows

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and β-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014-2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6-8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation.

Differentiating between metabolic health statuses in Simmental cows and describing related milk fatty acids and relevant associated factors

The aim of this observational study was to examine differences in milk fatty acid (FA) concentrations for different metabolic health statuses and for associated factors-specifically to examine with which FA concentrations an increased risk for developing a poor metabolic adaptation syndrome (PMAS) was associated. During weekly visits over 51 wk, blood samples were collected from cows between 5 and 50 days in milk. The farmer collected corresponding milk samples from all voluntary milkings. The analysis was performed on n = 2,432 samples from n = 553 Simmental cows. The observations were assigned to five different cow types (healthy, clever, athletic, hyperketonemic, and PMAS, representing five metabolic health statuses), based on the thresholds of 0.7 mmol/L, 1.2 mmol/L, and 1.4 for the concentrations of β-hydroxybutyrate and nonesterified fatty acids and for the milk fat-to-protein ratio, respectively. Linear regression models using the predictor variables cow type, parity, week of lactation, and milk yield as fixed effects were developed using a stepwise forward selection to test for significant associations of predictor variables regarding FA concentrations in milk. There was a significant interaction term found between PMAS cows and parity compared to healthy cows for C18:1 (P < 0.001) and for C18:0 (P < 0.01). It revealed higher concentrations for PMAS in primiparous and multiparous cows compared to healthy cows, the slope being steeper for primiparous cows. Further, an interaction term was found between PMAS cows and milk yield compared to healthy cows and milk yield for C16:0 (P < 0.05), revealing a steeper slope for the decrease of C16:0 concentrations with increasing milk yield for PMAS compared to healthy cows. The significant associations and interaction terms between cow type, parity, week of lactation, and milk yield as predictor variables and C16:0, C18:0, and C18:1 concentrations suggest excellent opportunities for cow herd health screening during the early postpartum period.

Multi-omics analysis reveals that the metabolite profile of raw milk is associated with dairy cows' health status

The metabolic status of dairy cows directly influences the nutritional quality and flavor of raw milk. A comprehensive comparison of non-volatile metabolites and volatile compounds in raw milk from healthy and subclinical ketosis (SCK) cows was performed using LC-MS, GC-FID, and HS-SPME/GC-MS. SCK can significantly alter the profiles of water-soluble non-volatile metabolites, lipids, and volatile compounds of raw milk. Compared with healthy cows, milk from SCK cows had higher contents of tyrosine, leucine, isoleucine, galactose-1-phosphate, carnitine, citrate, phosphatidylethanolamine species, acetone, 2-butanone, hexanal, dimethyl disulfide and lower content of creatinine, taurine, choline, α-ketoglutaric acid, fumarate, triglyceride species, ethyl butanoate, ethyl acetate, and heptanal. The percentage of polyunsaturated fatty acids in milk was lowered in SCK cows. Our results suggest that SCK can change milk metabolite profiles, disrupt the lipid composition of milk fat globule membrane, decrease the nutritional value, and increase the volatile compounds associated with off-flavors in milk.

Prediction of metabolic status of dairy cows in early lactation using milk fatty acids and test-day variables

Early lactation metabolic imbalance is an important physiological change affecting the health, production, and reproduction of dairy cows. The aims of this study were (1) to evaluate the potential of test-day (TD) variables with or without milk fatty acids (FA) content to classify metabolically imbalanced cows and (2) to evaluate the robustness of the metabolic classification with external data. A data set was compiled from 3 experiments containing plasma β-hydroxybutyrate, nonesterified FA, glucose, insulin-like growth factor-I, FA proportions in milk fat, and TD variables collected from 244 lactations in wk 2 after calving. Based on the plasma metabolites, 3 metabolic clusters were identified using fuzzy c-means clustering and the probabilistic membership value of each cow to the 3 clusters was determined. Comparing the mean concentration of the plasma metabolites, the clusters were differentiated into metabolically imbalanced, moderately impacted, and balanced. Following this, the 2 metabolic status groups identified were imbalanced cows (n = 42), which were separated from what we refer to as "others" (n = 202) based on the membership value of each cow for the imbalanced cluster using a threshold of 0.5. The following 2 FA data sets were composed: (1) FA (groups) having high prediction accuracy by Fourier-transform infrared spectroscopy and, thus, have practical significance, and (2) FA (groups) formerly identified as associated with metabolic changes in early lactation. Metabolic status prediction models were built using FA alone or combined with TD variables as predictors of metabolic groups. Comparison was made among models and external evaluations were performed using an independent data set of 115 lactations. The area under the receiver operating characteristics curve of the models was between 75 and 91%, indicating their moderate to high accuracy as a diagnostic test for metabolic imbalance. The addition of FA groups to the TD models enhanced the accuracy of the models. Models with FA and TD variables showed high sensitivities (80-88%). Specificities of these models (73-79%) were also moderate and acceptable. The accuracy of the FA models on the external data set was high (area under the receiver operating characteristics curve between 76 and 84). The persistently good performance of models with Fourier-transform infrared spectroscopy-quantifiable FA on the external data set showed their robustness and potential for routine screening of metabolically imbalanced cows in early lactation.

Integrating on-farm and genomic information improves the predictive ability of milk infrared prediction of blood indicators of metabolic disorders in dairy cows

BACKGROUND

Blood metabolic profiles can be used to assess metabolic disorders and to evaluate the health status of dairy cows. Given that these analyses are time-consuming, expensive, and stressful for the cows, there has been increased interest in Fourier transform infrared (FTIR) spectroscopy of milk samples as a rapid, cost-effective alternative for predicting metabolic disturbances. The integration of FTIR data with other layers of information such as genomic and on-farm data (days in milk (DIM) and parity) has been proposed to further enhance the predictive ability of statistical methods. Here, we developed a phenotype prediction approach for a panel of blood metabolites based on a combination of milk FTIR data, on-farm data, and genomic information recorded on 1150 Holstein cows, using BayesB and gradient boosting machine (GBM) models, with tenfold, batch-out and herd-out cross-validation (CV) scenarios.

RESULTS

The predictive ability of these approaches was measured by the coefficient of determination (R²). The results show that, compared to the model that includes only FTIR data, integration of both on-farm (DIM and parity) and genomic information with FTIR data improves the R² for blood metabolites across the three CV scenarios, especially with the herd-out CV: R² values ranged from 5.9 to 17.8% for BayesB, from 8.2 to 16.9% for GBM with the tenfold random CV, from 3.8 to 13.5% for BayesB and from 8.6 to 17.5% for GBM with the batch-out CV, and from 8.4 to 23.0% for BayesB and from 8.1 to 23.8% for GBM with the herd-out CV. Overall, with the model that includes the three sources of data, GBM was more accurate than BayesB with accuracies across the CV scenarios increasing by 7.1% for energy-related metabolites, 10.7% for liver function/hepatic damage, 9.6% for oxidative stress, 6.1% for inflammation/innate immunity, and 11.4% for mineral indicators.

CONCLUSIONS

Our results show that, compared to using only milk FTIR data, a model integrating milk FTIR spectra with on-farm and genomic information improves the prediction of blood metabolic traits in Holstein cattle and that GBM is more accurate in predicting blood metabolites than BayesB, especially for the batch-out CV and herd-out CV scenarios.

African Elephant Milk Short Saccharide and Metabolite Composition and Their Changes over Lactation

Elephant milk composition is unique, as are its changes over lactation. Presented here is the milk non-dedicated metabolite composition of three African elephants. Their lactation times are overlapping and span day one to thirty months. Metabolites were identified and quantified by ¹H nuclear magnetic resonance spectroscopy. Lactose and short oligosaccharides are a large component of the metabolites, with lacto-N-difucohexaose I as the major oligosaccharide. These were followed by metabolites of lipids, amino acids, and the citric acid cycle. The content of lactose, lacto-N-difucohexaose I, 2'-fucosyllactose, and some unidentified oligosaccharides decrease over lactation, while that of difucosyllactose and other unidentified ones increase. The high content of glutamate, as a glucogenic amino acid, supported the uprated synthesis of saccharides by the milk gland cells. The content of succinate and choline increase over lactation, indicating higher energy expenditure and phospholipid synthesis during later lactation.

Heritable and Nonheritable Rumen Bacteria Are Associated with Different Characters of Lactation Performance of Dairy Cows

Recent studies have reported that some rumen microbes are heritable. However, it is necessary to clarify the functions and specific contributions of the heritable rumen microbes to cattle phenotypes (microbiability) in comparison with those that are nonheritable. This study aimed to identify the distribution and predicted functions of heritable and nonheritable bacterial taxa at species level in the rumen of dairy cows and their respective contributions to energy-corrected milk yield, protein content and yield, and fat content and yield in milk. Thirty-two heritable and 674 nonheritable bacterial taxa were identified at species level, and the functional analysis revealed that predicted microbial functions for both groups were mainly enriched for energy, amino acid, and ribonucleotide metabolism. The mean microbiability (to reflect a single taxon's contribution) of heritable bacteria was found to range from 0.16% to 0.33% for the different milk traits, whereas the range for nonheritable bacteria was 0.03% to 0.06%. These findings suggest a strong contribution by host genetics in shaping the rumen microbiota, which contribute significantly to milk production traits. Therefore, there is an opportunity to further improve milk production traits through attention to host genetics and the interaction with the rumen microbiota. IMPORTANCE Rumen bacteria produce volatile fatty acids which exert a far-reaching influence on hepatic metabolism, mammary gland metabolism, and animal production. In the current study, 32 heritable and 674 nonheritable bacterial taxa at species level were identified, and shown to have different microbiability (overall community contribution) and mean microbiability (the average of a single taxon's contribution) for lactation performance. The predicted functions of heritable and nonheritable bacterial taxa also differed, suggesting that targeted nutritional and genetic breeding approaches could be used to manipulate them to improve dairy cow performance.

An investigation of blood, milk, and urine test patterns for the diagnosis of ketosis in dairy cows in early lactation

Ketosis in dairy cattle is primarily diagnosed based on the concentrations of ketone bodies in the blood, milk, or urine. Cow-side tests using these fluids are available for rapid detection of elevated concentrations of ketone bodies. Although these tests have been extensively validated, the performance of different tests has not been compared over time. Our objectives were to investigate the relationship between point-of-care diagnostic tests measuring the concentrations of β-hydroxybutyrate (BHB) in blood (BT; Precision Xtra, Abbott Laboratories), BHB in milk (MT; Keto-Test, Elanco), and acetoacetate (AcAc) in urine (UT; Ketostix, Bayer Corporation) through cases of ketosis. Holstein cows (n = 148) were screened daily for hyperketonemia (HYK; blood BHB ≥1.2 mmol/L) from 3 to 16 d in milk (DIM); moreover, milk and urine samples were collected concomitantly and tested for ketones (ketosis thresholds: 100 µmol/L milk BHB and 5 mg/dL urine AcAc). Of the animals screened (n = 148), 74% were diagnosed with HYK. When diagnosed with HYK, cows were treated with propylene glycol orally once daily for 5 d. After the day of diagnosis (d 0), hyperketonemic cows were retested with BT, MT, and UT for 3 d (d 1, 2, and 3). We assessed the diagnostic test performance and time to ketosis (survival analyses and Cox proportional hazards models) of MT and UT compared with BT. Considering all paired samples (before and after diagnosis of HYK), MT had 61% sensitivity and 91% specificity, whereas the UT had 77% sensitivity and 94% specificity compared with BT. The specificity of MT and UT increased from d 0 to d 1, decreased on d 2, and increased on d 3. The median time to diagnosis of ketosis in blood was 5 DIM (95% CI 5 to 7 DIM); moreover, MT and UT had 2 d greater median time to diagnosis of ketosis compared with the BT [7 DIM (6 to 11 d); and 7 DIM (6 to 13 d), respectively]. We concluded that the UT is a more sensitive predictor of blood BHB concentration than the MT. The UT and MT tests diagnosed ketotic cows approximately 2 d later than the BT. The possible consequences of delay in detection of ketosis in milk and urine should be investigated.

Effects of higher plasma growth hormone levels on subclinical ketosis in postpartum Holstein cows

Ketosis is a major metabolic disorder that can lead to huge economic losses in postpartum dairy cows by influencing milk production and reproduction performance. Therefore, it is very important to understand the characteristics and significance of plasma GH levels and dynamic changes in postpartum dairy cows for finding pathogenesis of subclinical ketosis (SK). The present study aimed to determine the role of growth hormone (GH) from the onset of SK to the fifth week postpartum and to explain the variations in GH, and metabolic markers namely, β-hydroxybutyric acid (BHBA), non-esterified fatty acid (NEFA) and glucose (GLU) at early and later SK stages in postpartum Holstein cows. A 5-wk test and an intraday 12-h test were conducted in postpartum Holstein cows. Both tests were carried out every three hours from 10:00–22:00 for 7–14 days postpartum (12-h test: n = 16) to determine plasma concentrations of GH, BHBA, NEFA and GLU. The 5-wk test results showed that GH, BHBA and NEFA concentrations were significantly higher in the SK group during the five-weeks postpartum (p < 0.01); GLU concentration was significantly lower in the SK group (p < 0.01). Intraday 12-h test results revealed that the feeding time affected the plasma concentrations of GH, BHBA, NEFA and GLU. After 1-h of feeding time, GH concentrations decreased, while BHBA, NEFA and GLU concentrations increased. After 4-h of feeding time GH, BHBA and NEFA had the highest plasma concentrations, and GLU the lowest. In both experiments, GH was positively correlated with BHBA, NEFA, and negatively correlated with GLU. It can be suggested that GH has a potential role in development and aetiology of subclinical ketosis.

Comparison of two diagnostic methods through blood and urine sample analyses for the detection of ketosis in cattle

Background and Aim:

Several Ecuadorian farms use human test strips (cheaper than veterinary strips) to diagnose bovine ketosis; however, their reliability is unknown. This study aimed to determine the confidence level of human strips for the detection of ketosis in bovines by comparing two diagnostic methods for ketosis: one used in bovines (gold standard) to analyze blood samples and the other used in humans to analyze urine samples.

Materials and Methods:

The study was conducted on an Ecuadorian farm using 50 animals, ten from each of five categories: heifers, 4 months pregnant (4MP), 15 days prepartum (15DPRE), 15 days postpartum (15DPOST), and 42 days postpartum (42DPOST). Blood samples were collected through coccygeal venipuncture and urine samples were collected during spontaneous urination. BHBCheck™ assay was used to measure b-hydroxybutyrate (BHB) in the blood, whereas Combur10Test^® was used to measure acetoacetate (AcAc) in urine for the determination of ketosis.

Results:

BHB was detected in all animals. Based on a ketosis cutoff point of 0.8-1.2 mmol/L, 13 animals from the 15DPOST and 42DPOST categories had ketosis; AcAc was detected in the urine from nine animals originated from the two same categories. Metabolites, either BHB or AcAc, were not detected in heifers, 4MP, or 15DPRE individuals. Finally, the BHBCheck™ assay had better efficiency in detecting ketosis in animals (p<0.05) than the Combur10Test^®.

Conclusion:

Combur10Test^® urine strips reached 92% reliability for the detection of ketosis in dairy cattle, compared to BHBCheck™ assays.

Comparison of raw cow milk microbiota in two milking systems: a field study

This study investigated the effect of different milking systems on the milk composition and microbial community of raw milk in a commercial dairy farm. Raw milk samples from conventional milking system (CMS) and automatic milking system (AMS) were collected and the microbiota on each was assessed by 16S rRNA gene sequencing. Results showed that the acetone (P = 0.031) and β-hydroxybutyrate (P≤0.001) levels in the raw milk of the AMS group were increased compared with the CMS group. Principal component analysis, unweighted and weighted principal coordinates analysis, and heat map of microbial community composition in the raw milk showed a clear separation between two groups. AMS increased the abundance of the genera Acinetobacter (FDR = 0.004) and Staphylococcus (FDR = 0.004) in the raw milk compared with the CMS group. In contrast, the abundance of the genera Pseudomonas (FDR = 0.028), Lactococcus (FDR = 0.015), Sphingobacterium (FDR = 0.004), Brevundimonas (FDR = 0.005), and Chryseobacterium (FDR = 0.042) in the raw milk was reduced in the AMS group compared with the CMS group. The abundance of the genera Acinetobacter and Staphylococcus in the raw milk was positively correlated with the β-hydroxybutyrate, acetone, free fatty acid, citric acid, and urea nitrogen levels. Furthermore, the abundance of the genus Acinetobacter in the raw milk was negatively correlated with the somatic cell counts. The study demonstrates that the introduction of AMS in the dairy farm can regulate microbiota composition in the raw milk and this modification may exert an effect on reducing the somatic cell counts in the raw milk.

Activation of Transcription Factor EB Is Associated With Adipose Tissue Lipolysis in Dairy Cows With Subclinical Ketosis

Excessive lipid mobilization for adipose tissue caused by severe negative energy balance is the pathological basis for subclinical ketosis (SCK) in dairy cows. In non-ruminants, transcription factor EB (TFEB) was reported to play a role in the regulation of lipid catabolism, but its role in the control of lipolysis in the bovine is unknown. The present study aimed to determine whether the enhanced TFEB transcriptional activity contributes to lipolysis of adipose tissue in SCK cows, and to explore the possibility of establishing a therapeutic strategy by using TFEB as a target to control lipolysis. Thirty cows with similar lactation number (median = 3, range = 2–4) and days in milk (median = 6 d, range = 3–9) were selected into a healthy control (n = 15) and SCK (n = 15) group, and used for subcutaneous adipose tissue biopsies and blood sampling. Adipocytes from healthy Holstein calves were used as a model for in vitro studies involving treatment with 10 μM isoproterenol (ISO) for 0, 1, 2 and 3 h, 250 nM of the TFEB activator Torin1 for 3 h, or used for transfection with TFEB small interfering RNA for 48 h followed by treatment with 10 μM ISO for 3 h. Compared with healthy cows, adipose tissue in SCK cows showed increased lipolysis accompanied by enhanced TFEB transcriptional activity. In vitro, ISO and Torin1 treatment increased lipolysis and enhanced TFEB transcriptional activity in calf adipocytes. However, knockdown of TFEB attenuated ISO-induced lipolysis in adipocytes. Overall, these findings indicated that enhanced transcriptional activity of TFEB may contribute to lipolysis of adipose tissue in dairy cows with SCK. The regulation of TFEB activity may be an effective therapeutic strategy for controlling overt lipolysis in ketotic cows.

Effect of Negative Energy Balance on Plasma Metabolites, Minerals, Hormones, Cytokines and Ovarian Follicular Growth Rate in Holstein Dairy Cows

Introduction

The aim of this study was to evaluate the effect of negative energy balance (NEB) on the final growth of the dominant ovarian follicle in Holstein cows.

Material and Methods

Cows at 14 to 21 d postpartum from an intensive dairy farm were randomly selected and allocated into a positive energy balance group (PEB, with β-hydroxybutyric acid (BHBA) level < 1.2 mmol/L, n = 15) and an NEB group (BHBA > 1.2 mmol/L, n = 15). Plasma samples were collected at 21, 50 and 55 d postpartum to assess the concentrations of energy metabolites, minerals, hormones and cytokines. Ovaries were examined by transrectal ultrasound on days 50 and 55 (120 hours later) to evaluate the diameter of the largest follicle.

Results

Compared with PEB cows, there were a more severe body condition loss and a lower milk yield in NEB cows (P < 0.05) and these had greater concentrations of plasma BHBA, non-esterified fatty acids, triglycerides, urea nitrogen, growth hormone, interleukin 6, and fibroblast growth factor 21 and lesser concentrations of plasma glucose, total cholesterol, insulin, insulin-like growth factor 1, insulin-like growth factor binding protein 3, leptin, brain-derived neurotrophic factor and angiopoietin-like protein 8 on d 21 (P < 0.05), while plasma minerals were not affected by energy status (P > 0.05). These changes persisted until the end of the study period (50–55 days postpartum) resulting in a lower follicular growth rate for cows in the NEB than the PEB group.

Conclusion

These observations indicate that follicular growth rate is associated with measurable changes in energy metabolite, hormone and cytokine concentrations caused by early postpartum NEB.

Acetoacetate is a trigger of NLRP3 inflammasome activation in bovine peripheral blood mononuclear cells

Repeat breeding, which is non-pregnancy following three or more breeding attempts, is a serious reproductive disorder in cattle. In the present study, metabolomic profiling was used to identify metabolites in the blood plasma of repeat breeder cows (RBCs) and non-RBCs. Metabolomic analysis showed that acetoacetate (AcAc), a ketone body, was detected in RBCs, but not in non-RBCs. In contrast, β-hydroxybutyrate (BHB) was at similar levels in both RBCs and non-RBCs. We hypothesized that an imbalance of AcAc and BHB induces abnormal inflammatory conditions, especially the NLRP3 inflammasome, which regulates sterile inflammation to control interleukin (IL)-1β secretion, and may be associated with repeat breeding in cattle. To investigate this hypothesis, blood samples were collected from both non-RBCs and RBCs on day 7 of the estrous cycle. The mRNA expression of IL1B in peripheral blood mononuclear cells (PBMCs) was observed to be higher in RBCs than in non-RBCs. To test the effects of AcAc and BHB on inflammatory responses, blood samples were collected from healthy cows and PBMCs were isolated. PBMCs were treated with AcAc and BHB to investigate the activation of the NLRP3 inflammasome (complex of NLRP3, ASC, and caspase-1) and IL-1β secretion. AcAc treatment resulted in higher protein and/or mRNA expression of NLRP3 and IL-1β in PBMCs. Moreover, AcAc increased the co-localization of NLRP3 and ASC and stimulated caspase-1 activation, indicating the formation of the platform of the NLRP3 inflammasome. Addition of specific NLRP3 inhibitor, MCC950, suppressed AcAc stimulation-induced IL-1β secretion. Contrary to the effects of AcAc, BHB treatment suppressed the activation of NLRP3 inflammasome and IL-1β secretion in response to AcAc and typical NLRP3 inflammasome triggers. These findings demonstrate that AcAc can potentially trigger NLRP3 inflammasome activation, resulting in IL-1β secretion, and that these inflammatory responses are suppressed by BHB in bovine PBMCs. In addition, the imbalance between AcAc and BHB with higher levels of IL-1β may be associated with repeat breeding in cattle.

Effects of intravenous butaphosphan and cyanocobalamin to late pregnant ewes on the metabolic indices around parturition and weight gain of their lambs after birth

Background

Management and control of metabolic disorders in sheep around parturition is important. and various researchers have suggested different managerial solutions. Butaphosphan and cyanocobalamin are widely used for curing metabolic disorders resulting from poor nutrition, inadequate management or diseases.

Objectives

It was hypothesised that butaphosphan and cyanocobalamin could improve the metabolism of ewes around parturition.

Methods

Twenty‐eight clinically healthy 3‐year‐old pregnant Afshari ewes from 21 days before parturition were enrolled into four equal groups: control (Ctrl), B+C1, B+C2 and B+C3. The Ctrl group only received intravenous normal saline and B+C1, B+C2 and B+C3 ewes, respectively, received an intravenous combination of 10% butaphosphan and 0.005% cyanocobalamin at 2, 4 and 6 ml/ewe, on Days 19–21, 10–12 and 1–3 before parturition. Blood samples were taken from all the ewes on Days 21, 12 and 3 before lambing at parturition day and on days 3, 12 and 21 after parturition. A body condition score of all the ewes was assessed at blood sampling days, and lambs born from the ewes were weighed at birth and every 2 weeks up to 3 months. Serum concentrations of glucose, cortisol, non‐esterified fatty acids, beta‐hydroxy butyric acid, triglyceride, cholesterol, high‐, low‐ and very‐low‐density lipoproteins, aspartate aminotransferase and alanine aminotransferase were measured.

Results

This drug combination decreased circulating glucose, cortisol, lipid profile and hepatic enzymes via dose‐dependent manner, 6 ml of this drug compound/ewe was more potent than 4 and 2 ml/ewe. The lambs’ weight from mothers receiving 6 ml of this combination was significantly higher than those of the others.

Conclusions

It may be suggested that the intravenous administration of 6 ml/ewe of this combination for 3 consecutive days in three states before parturition had prophylactic effects on metabolic disorders of ewes and enhanced the lambs weight gain after birth.

Milk metabolites and fatty acids as noninvasive biomarkers of metabolic status and energy balance in early-lactation cows

The objective was to study the effects of week of lactation (WOL) and experimental nutrient restriction on concentrations of selected milk metabolites and fatty acids (FA), and assess their potential as biomarkers of energy status in early-lactation cows. To study WOL effects, 17 multiparous Holstein cows were phenotyped from calving until 7 WOL while allowed ad libitum intake of a lactation diet. Further, to study the effects of nutrient restriction, 8 of these cows received a diet containing 48% straw (high-straw) for 4 d starting at 24 ± 3 days in milk (mean ± SD), and 8 cows maintained on the lactation diet were sampled to serve as controls. Blood and milk samples were collected weekly for the WOL data set, and daily from d -1 to 3 of nutrient restriction (or control) for the nutritional challenge data set. Milk β-hydroxybutyrate (BHB), isocitrate, glucose, glucose-6-phosphate (glucose-6P), galactose, glutamate, creatinine, uric acid, and N-acetyl-β-d-glucosaminidase activity (NAGase) were analyzed in p.m. and a.m. samples, and milk FA were analyzed in pooled p.m. and a.m. samples. Average energy balance (EB) per day ranged from -27 MJ/d to neutral when cows received the lactation total mixed ration, and from -109 to -87 ± 7 MJ/d for high-straw (least squares means ± standard error of the mean). Plasma nonesterified FA concentration was 1.67 ± 0.13 mM and BHB was 2.96 ± 0.39 mM on the d 3 of high-straw (least squares means ± standard error of the mean). Milk concentrations of BHB, glucose, glucose-6P, glutamate, and uric acid differed significantly between p.m. and a.m. milkings. Milk isocitrate, glucose-6P, creatinine, and NAGase decreased, whereas milk glucose and galactose increased with WOL. Changes in milk BHB, isocitrate, glucose, glucose-6P, and creatinine were concordant during early lactation and in response to nutrient restriction. Milk galactose and NAGase were modulated by WOL only, whereas glutamate and uric acid concentrations responded to nutrient restriction only. The high-straw increased milk concentrations of FA potentially mobilized from adipose tissue (e.g., C18:0 and cis-9 C18:1 and sum of odd- and branched-chain FA (OBCFA) with carbon chain greater than 16; ∑ OBCFA >C16), and decreased concentrations of FA synthesized de novo by the mammary gland (e.g., sum of FA with 6 to 15 carbons; ∑ C6:0 to C15:0). Similar observations were made during early lactation. Plasma nonesterified FA concentrations had the best single linear regression with EB (R² = 0.62). Milk isocitrate, Σ C6:0 to C15:0. and cis-9 C18:1 had the best single linear regressions with EB (R² ≥ 0.44). Milk BHB, isocitrate, galactose, glutamate, and creatinine explained up to 64% of the EB variation observed in the current study using multiple linear regression. Milk concentrations of ∑ C6:0 to C15:0, C18:0, cis-9 C18:1, and ∑ OBCFA >C16 presented some of the best correlations and regressions with other indicators of metabolic status, lipomobilization, and EB, and their responses were concordant during early lactation and during experimental nutrient restriction. Metabolites and FA secreted in milk may serve as noninvasive indicators of metabolic status and EB of early-lactation cows.

Analytical Methodology for a Metabolome Atlas of Goat's Plasma, Milk and Feces Using 1H-NMR and UHPLC-HRMS

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These studies in metabolomics often consider a single type of sample using a single analytical platform (nuclear magnetic resonance or mass spectrometry). Only few studies with multi-platform approaches are also used with a single or a multi type of sample, but they mainly consider dairy cows’ metabolome although dairy goats present similar diseases, that it could be interesting to detect early to preserve animal health and milk production. This study aims to create a metabolic atlas of goat plasma, milk and feces, based on healthy animals. Our study describes a standard operating procedure for three goat matrices: blood plasma, milk, and feces using multiple platforms (NMR (¹H), UHPLC (RP)-MS and UHPLC (HILIC)-MS) that follows a unique sample preparation procedure for each sample type to be analyzed on multi-platforms basis. Our method was evaluated for its robustness and allowed a better characterization of goat metabolic profile in healthy conditions.

Characterization of ketolactia in dairy cows during early lactation

Fourier transform infrared spectroscopy (FTIR) allows for the determination of milk acetone (mACE) and β-hydroxybutyrate (mBHB) concentrations, providing a potential herd monitoring tool for hyperketolactia, defined as elevated milk ketone bodies. The study aim was to characterize mACE and mBHB concentration dynamics during early lactation in Polish Holstein-Friesian cows. Milk samples (n = 3,867,390) were collected within 6 to 60 days in milk (DIM) over a 4-yr period (April 1, 2013 to March 31, 2017) from approximately 21,300 dairy herds (average 38.7 cows/herd). Fixed effects of parity, DIM, and their interaction on mACE and mBHB concentrations were determined using a mixed model with a herd-year-season fixed effect and random cow effect. Published hyperketolactic mACE (≥0.15 mmol/L) and mBHB (≥0.10 mmol/L) threshold concentrations were used to classify study milk samples into ketolactia groups of normal (mACE <0.15 mmol/L and mBHB <0.10 mmol/L) and hyperketolactic (HYKL; either mACE ≥0.15 mmol/L or mBHB ≥0.10 mmol/L). Additionally, HYKL samples were categorized into subpopulations as having elevated mBHB and mACE (HYKL_ACEBHB, mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L), only elevated mBHB (HYKL_BHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), or only elevated mACE (HYKL_ACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L). Effects of parity, DIM, ketolactia group or subpopulation, and their interactions on mACE and mBHB concentrations were also determined using the mixed model that included ketolactia group or subpopulation as an independent variable. Across all data, mACE and mBHB concentrations were influenced by effects of parity, DIM, and their interaction as well as parity, DIM, ketolactia group or subpopulation, and their interactions. For all samples, mACE and mBHB concentrations decreased with increasing DIM, with mACE concentration declining more rapidly compared with mBHB. In the data set, 68% and 32% of all samples were defined as normal or HYKL, respectively. Among HYKL samples, mACE was elevated soon after calving and declined over time. In contrast, mBHB started lower after calving and increased reaching peak concentrations around 30 DIM, and then decreased. Within HYKL samples, 50.8, 41.3, and 7.9% were categorized as HYKL_ACEBHB, HYKL_BHB, and HYKL_ACE respectively. Between 6 and 21 DIM, 11.3% of HYKL were classified as HYKL_ACE. Primiparous cows had greater (14.8%) HYKL_ACE samples in this time period. In conclusion, this study has characterized mACE and mBHB concentrations during early lactation and determined effects of parity, DIM, and their interaction. Using published criteria interpreting mACE and mBHB concentrations, it was intriguing to identify a unique population of samples having elevated mACE without mBHB in early lactation, especially in primiparous cows. Further research is needed to determine if this sample population represents an unhealthy metabolic status that adversely affects cow health and performance.

Indicators of full value feeding rations for dairy cows

This article presents the results of the level of feeding and the health status of dairy cows in a commercial dairy farm on the content of the main components in milk (fat, protein, urea). The aim of the research was to study the milk productivity and composition of milk of cows, to analyze the level of feeding and the content of basic nutrients in the diet of the farm. The farm breeds purebred Holstein cattle with a high genetic potential for productivity. The milking herd was formed in 2009 on the basis of 600 heads of Holstein-Friesian heifers imported from Hungary, as well as 65 heads of Holsteinized heifers of Ukrainian selection from Ukraine in 2015. Today the livestock numbers about 1,500 head of cattle, of which there are about 900 breeders. On the territory of the farm there are: 3 cowsheds for keeping cows, an insemination room, a milking parlor with a parallel installation of the Delaval company, in which 48 cows are milked for one milking, the ABK, where the manager's office, livestock technician, accounting is located, and a mini-hotel with dining room and lounges. Dairy bases are equipped with auto-drinkers, ventilation, plumbing, electric lighting, manure removal mechanisms, and a milking installation. The object of the research was Holstein cows in the amount of 483 heads of Aina Dairy Farm LLP. The studies were carried out according to generally accepted zootechnical methods using modern equipment for conducting analyzes and interstate and state standards. The research results showed that the milk productivity of cows averaged 19.5 kg per day, the fat content 4.3%, the protein 3.9%, the number of somatic cells 230.5 thousand units / ml, urea 45.3 mg / 100 ml respectively. Analyzing the level of urea in milk can suggest a high crude protein content in the diet. The ration of feeding dairy cows on the farm is concentrate-silage-haylage and there is an excess of dry matter by 16.2%, crude protein by 9.8%, starch by 29.4%, respectively.

Abomasal infusion of corn starch and β-hydroxybutyrate in early-lactation Holstein-Friesian dairy cows to induce hindgut and metabolic acidosis

The objectives of this study were to induce hindgut and metabolic acidosis via abomasal infusion of corn starch and β-hydroxybutyrate (BHB), respectively, and to determine the effects of these physiological states in early-lactation dairy cows. In a 6 × 6 Latin square design, 6 rumen-fistulated Holstein-Friesian dairy cows (66 ± 18 d in milk) were subjected to 5 d of continuous abomasal infusion treatments followed by 2 d of rest. The abomasal infusion treatments followed a 3 × 2 factorial design, with 3 levels of corn starch and 2 levels of BHB. The infusions were water as control, 1.5 kg of corn starch/d, 3.0 kg of corn starch/d, 8.0 mol BHB/d, 1.5 kg of corn starch/d + 8.0 mol BHB/d, or 3.0 kg of corn starch/d + 8.0 mol BHB/d. A total mixed ration consisting of 35.0% grass silage, 37.4% corn silage, and 27.6% concentrate (on a dry matter basis) was fed at 90% of ad libitum intake of individual cows. The experiment was conducted in climate respiration chambers to facilitate determination of energy and N balance. Fecal pH decreased with each level of corn starch infused into the abomasum and was 6.49, 6.00, and 5.15 with 0.0, 1.5, and 3.0 kg of corn starch/d, respectively, suggesting that hindgut acidosis was induced with corn starch infusion. No systemic inflammatory response was observed and the permeability of the intestine or hindgut epithelium was not affected by the more acidic conditions. This induced hindgut acidosis was associated with decreased digestibility of nutrients, except for crude fat and NDF, which were not affected. Induced hindgut acidosis did not affect milk production and composition and energy balance, but increased milk N efficiency. Abomasal infusion of BHB resulted in a compensated metabolic acidosis, which was characterized by a clear disturbance of acid-base status (i.e., decreased blood total CO₂, HCO₃, and base excess, and a tendency for decreased urinary pH), whereas blood pH remained within a physiologically normal range. Abomasal infusion of BHB resulted in increased concentrations of BHB in milk and plasma, but both remained well below the critical threshold values for subclinical ketosis. Induced compensated metabolic acidosis, as a result of abomasally infused BHB, increased energy retained as body fat, did not affect milk production and composition or inflammatory response, but increased intestinal permeability.

Engineered acetoacetate-inducible whole-cell biosensors based on the AtoSC two-component system

Whole-cell biosensors hold potential in a variety of industrial, medical, and environmental applications. These biosensors can be constructed through the repurposing of bacterial sensing mechanisms, including the common two-component system (TCS). Here we report on the construction of a range of novel biosensors that are sensitive to acetoacetate, a molecule that plays a number of roles in human health and biology. These biosensors are based on the AtoSC TCS. An ordinary differential equation model to describe the action of the AtoSC TCS was developed and sensitivity analysis of this model used to help inform biosensor design. The final collection of biosensors constructed displayed a range of switching behaviours at physiologically relevant acetoacetate concentrations and can operate in several Escherichia coli host strains. It is envisaged that these biosensor strains will offer an alternative to currently available commercial strip tests and, in future, may be adopted for more complex in vivo or industrial monitoring applications.

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.

Ketone bodies - causes and effects of their increased presence in cows' body fluids: A review

Ketosis is the most common metabolic disease in high-performance dairy cows during the first 6-8 weeks of lactation. Its main symptoms include an excessive amount of so-called ketone bodies in a cow's body fluids. Ketone bodies consist of β-hydroxybutyric acid (βHBA), acetoacetic acid, and acetone. βHBA is the main component with its share of the total volume of ketone bodies in the blood of about 70%. Clinical symptoms of ketosis in cows include loss of appetite, preference for forage to concentrated feed, and acetone odor in their mouth and urine. Those symptoms are accompanied by a production drop, an increase of concurrent illness (mastitis, metritis, and displaced abomasum), and poor reproductive performance. One of the ketosis characteristic effects is an increase in the level of fat in milk (>5%), while protein levels decrease (<2.9%). In the case of subclinical ketosis (SCK), the fat-protein ratio in milk is increased to above 1.4:1. The current consensus for SCK is to consider a cutoff point of βHBA to be at least 1.2 mmol/L in blood plasma. Ketosis prevention is based on keeping perinatal cows in good condition, that is, with around 3.5 points in the five-point body condition scoring, carefully balancing food doses during the first 2 months of lactation with the correct energy-protein ratio. Glucose precursor products should be administered orally, in particular to at-risk herds. Ketosis occurs in 7-14% on average of the total number of cows in a herd. In general, data on the prevalence of SCK vary considerably, depending on their source. Moreover, the problem is mostly observed in poorly-fed animals with high milk production potential. The objectives of this review are to reveal the current situation of ketosis prevalence, the possibility of diagnosis, consequences in dairy cows and to provide some recommendations for ketosis treatment and prevention.

Exploration of metabolite profiles in the biofluids of dairy cows by proton nuclear magnetic resonance analysis

Studies that screen for metabolites produced in ruminants are actively underway. We aimed to evaluate the metabolic profiles of five biofluids (ruminal fluid, serum, milk, urine, and feces) in dairy cow by using proton nuclear magnetic resonance (1H-NMR) and provide a list of metabolites in each biofluid for the benefit of future research. We analyzed the metabolites in five biofluids from lactating cows using proton nuclear magnetic resonance imaging; 96, 73, 88, 118, and 128 metabolites were identified in the five biofluids, respectively. In addition, 8, 6, 9, and 17 metabolites were unique to ruminal fluid, serum, milk, and urine, respectively. The metabolites present at high concentrations were: acetate, propionate, and butyrate in ruminal fluid; lactate, glucose, and acetate in serum; and lactose, guanidoacetate, and glucitol in milk. In addition, the following metabolites were present at high concentrations: hippurate, urea, and trimethylamine N-oxide in urine and acetate, propionate, and butyrate in feces. The score plots of the principal component analysis did not show clear distinctions among the five biofluid samples. The purpose of this study was to verify the ability of our metabolomics approaches to identify metabolites in the biofluids of dairy cows.

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.

Effects of a Multicomponent Herbal Extract on the Course of Subclinical Ketosis in Dairy Cows - a Blinded Placebo-controlled Field-study

A blinded placebo-controlled multi-center on-farm trial was conducted in dairy cows with subclinical ketosis to investigate effects of a multicomponent herbal extract. Blood ketone levels were measured weekly in early lactating cows from 16 Swiss herds. Cows were subclassified based on their initial blood-β-hydroxybutyrate levels (≥ 1.0 [KET-low, 84 cows] and > 1.2 mmol/L [KET-high, 39 cows]) and randomly distributed to 3 groups treated orally with herbal extract containing Camellia sinensis, Cichcorium intybus, Gentiana lutea, Glycyrrhiza glabra, Taraxacum officinale, Trigonella foenum-graecum, and Zingiber officinale, sodium propionate, or placebo twice a day for 5 days. Milk yield, milk acetone, blood-β-hydroxybutyrate, glucose, nonesterified fatty acids, gamma-glutamyl transferase, and glutamate dehydrogenase were analyzed over 2 wk. Linear mixed effect models were used for data analysis. No effects were found for nonesterifed fatty acids, gamma-glutamyl transferase, and glucose. Significantly higher glutamate dehydrogenase (29.71 U/L) values were found in herbal extract-treated animals compared to sodium propionate on day 7 (22.33 U/L). By trend, higher blood-β-hydroxybutyrate levels (1.36 mmol/L) were found in the placebo group of KET-high-cows on day 14 compared to the sodium propionate group (0.91 mmol/L). Milk yields of all treatment groups increased. Milking time and treatment showed a significant interaction for milk acetone: sodium propionate led to an immediate decrease, whereas herbal extracts resulted in a milk acetone decrease from day 7 on, reaching significantly lower milk acetone on day 14 (3.17 mg/L) when compared to placebo (4.89 mg/L). In conclusion, herbal extracts and sodium propionate are both likely to improve subclinical ketosis in dairy cows, however, by different modes of action.

Metabolic alterations in dairy cows with subclinical ketosis after treatment with carboxymethyl chitosan-loaded, reduced glutathione nanoparticles

Background

Subclinical ketosis (SCK) causes economic losses in the dairy industry because it reduces the milk production and reproductive performance of cows.

Hypothesis/Objectives

To evaluate whether carboxymethyl chitosan‐loaded reduced glutathione (CMC‐rGSH) nanoparticles can alleviate the incidence or degree of SCK in a herd.

Animals

Holstein dairy cows 21 days postpartum (n = 15).

Methods

The trial uses a prospective study. Five cows with serum β‐hydroxybutyric acid (BHBA) ≥1.20 mmol/L and aspartate aminotransferase (AST) <100 IU/L were assigned to group T1, 5 cows with BHBA ≥1.20 mmol/L and AST >100 IU/L to group T2, and 5 cows with BHBA <1.00 mmol/L and AST <100 IU/L to group C. Carboxymethyl chitosan‐loaded reduced glutathione (0.012 mg/kg body weight per cow) was administered to cows in T1 and T2 once daily via jugular vein for 6 days after diagnosis. Serum from all groups were collected 1 day before administration, then on days 1, 3, 5, 7, 10, and 15 after administration to determine the changes in biochemical index and ¹H‐NMR.

Results

The difference in liver function or energy metabolism indices in T1, T2, and C disappeared at day 7 and day 10 after the administration (P > .05). Valine, lactate, alanine, lysine, creatinine, glucose, tyrosine, phenylalanine, formate, and oxalacetic acid levels, and decrease in isoleucine, leucine, proline, acetate, trimethylamine N‐oxide, glycine, and BHBA levels were greater (P < .05) at day 7 than day 0 for cows in T2.

Conclusions and Clinical Importance

Carboxymethyl chitosan‐loaded reduced glutathione treatment might alleviate SCK by enhancing gluconeogenesis and reducing ketogenesis in amino acids.

Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows

Ketosis is a metabolic disorder of increasing importance in high-yielding dairy cows, but accurate population-wide binary health trait recording is difficult to implement. Against this background, proper Gaussian indicator traits, which can be routinely measured in milk, are needed. Consequently, we focused on the ketone bodies acetone and β-hydroxybutyrate (BHB), measured via Fourier-transform infrared spectroscopy (FTIR) in milk. In the present study, 62,568 Holstein cows from large-scale German co-operator herds were phenotyped for clinical ketosis (KET) according to a veterinarian diagnosis key. A sub-sample of 16,861 cows additionally had first test-day observations for FTIR acetone and BHB. Associations between FTIR acetone and BHB with KET and with test-day traits were studied phenotypically and quantitative genetically. Furthermore, we estimated SNP marker effects for acetone and BHB (application of genome-wide association studies) based on 40,828 SNP markers from 4,384 genotyped cows, and studied potential candidate genes influencing body fat mobilization. Generalized linear mixed models were applied to infer the influence of binary KET on Gaussian-distributed acetone and BHB (definition of an identity link function), and vice versa, such as the influence of acetone and BHB on KET (definition of a logit link function). Additionally, linear models were applied to study associations between BHB, acetone and test-day traits (milk yield, fat percentage, protein percentage, fat-to-protein ratio and somatic cell score) from the first test-day after calving. An increasing KET incidence was statistically significant associated with increasing FTIR acetone and BHB milk concentrations. Acetone and BHB concentrations were positively associated with fat percentage, fat-to-protein ratio and somatic cell score. Bivariate linear animal models were applied to estimate genetic (co)variance components for KET, acetone, BHB and test-day traits within parities 1 to 3, and considering all parities simultaneously in repeatability models. Pedigree-based heritabilities were quite small (i.e., in the range from 0.01 in parity 3 to 0.07 in parity 1 for acetone, and from 0.03-0.04 for BHB). Heritabilites from repeatability models were 0.05 for acetone, and 0.03 for BHB. Genetic correlations between acetone and BHB were moderate to large within parities and considering all parities simultaneously (0.69-0.98). Genetic correlations between acetone and BHB with KET from different parities ranged from 0.71 to 0.99. Genetic correlations between acetone across parities, and between BHB across parities, ranged from 0.55 to 0.66. Genetic correlations between KET, acetone, and BHB with fat-to-protein ratio and with fat percentage were large and positive, but negative with milk yield. In genome-wide association studies, we identified SNP on BTA 4, 10, 11, and 29 significantly influencing acetone, and on BTA 1 and 16 significantly influencing BHB. The identified potential candidate genes NRXN3, ACOXL, BCL2L11, HIBADH, KCNJ1, and PRG4 are involved in lipid and glucose metabolism pathways.

Nuclear Magnetic Resonance-Based Metabolomic Comparison of Breast Milk and Organic and Traditional Formula Milk Brands for Infants and Toddlers

In recent years, new formula milk (FM) products based on milk from farms that strictly adhere to the "organic farming" practices became available. However, little is known about the differences in nutritional profile of these organic formulae with respect to traditional ones. We comprehensively evaluated the metabolite profiles of FM with nuclear magnetic resonance (NMR)-based metabolomic analysis. Five commercial brands of organic and nonorganic formula liquid milk for infants (0-12 months) and toddlers (1-3 years) were analyzed, together with human milk (HM) samples. Proton NMR (¹H NMR) spectroscopy mapped molecular characteristics of FM linked to different production techniques, and identified differences between FM and HM samples. We performed a metabolic fingerprint analysis using multivariate and univariate statistical techniques. A clear distinction is found among different commercial brands of the FM samples. In addition, several differences in metabolomic profiles of FM have been found in comparison with HM for the first time. Notably, it was possible to identify, both in the formulations for toddlers and for infants, metabolites that vary in concentration between the formulae produced with milk obtained according to organic farming techniques, and those produced using nonorganic milk. In particular, organic and nonorganic formulations are differentiated by the levels of glucose, methionine, o-phosphocholine, butyrate, hippurate, creatine, and dimethyl sulfone. Importantly, the HM appeared to differ from both organic and nonorganic brands in a context of metabolites. These findings inform efforts to design FM in ways that closely mimic HM, and guide research to differentiate organic and traditional FM.

Economic value of information from an alert system on physiological imbalance in fresh cows

Physiological imbalance is an abnormal physiological condition that cannot be directly observed but is assumed to precede subclinical and clinical diseases in the beginning of lactation. Alert systems to detect the physiological imbalance in a cow using Fourier transform mid-infrared spectroscopy in milk have been developed. The objective of this study was to estimate the value of information provided from such system with different indicator accuracies, herd prevalence and prices. A decision tree was created to model the probabilities of detection and associated costs of test outcome, intervention and occurrence of disease. We assumed that the negative effect of physiological imbalance was the development of subclinical ketosis and that this negative effect was prevented by drenching the cows with propylene glycol for 5 days. We simulated the economic impact of subclinical ketosis mediated through physiological imbalance to be $194 per case. The results showed that if the alert system was highly accurate (Se = 0.99/Sp = 0.99), and the prevalence of physiological imbalance was 30 %, the value of information provided from the system is $19 per cow-year. In case the prevalence is 5 % or 50 %, the value of information is $3 and $13, respectively. These estimates for the value do not cover the capital costs and operational costs of the alert system. This study furthermore clearly demonstrated that in order to estimate the value of information correctly, it is important to consider that drenching all cows and not drenching any of the cows are the two relevant alternative options in the absence of the alert system. In conclusion, the decision tree and sensitivity analysis developed in this study show that final economic results are highly variable to the prevalence of physiological imbalance and highest at an intermediate prevalence. Other relevant factors are the costs associated with drenching and the cost associated with treating false positives and not treating false negatives. In addition, this study highlights the benefits of simulation to pinpoint where additional information is needed to further quantify the economic value and required accuracy of an indication-based intervention system.

Mid-infrared spectroscopic analysis of raw milk to predict the blood nonesterified fatty acid concentrations in dairy cows

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations <0.6 mmol/L with a root mean square error of prediction of <0.143 mmol/L. However, for blood plasma with >1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R² values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for negative energy status, indicated by detrimental morning blood plasma NEFA levels (>0.6 mmol/L), could be identified with a sensitivity and specificity of, respectively, 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens an opportunity for regular metabolic screening and improved resilience phenotyping.

Predicting physiological imbalance in Holstein dairy cows by three different sets of milk biomarkers

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and "intermediate cows" with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1-50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R²_cv) and root mean squared error (RMSE_cv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R²_cv = 0.40 (95 % CI: 0.29-0.50) at 14 DIM and 0.35 (0.23-0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R²_cv = 0.28 (0.24-0.33) vs 0.21 (0.18-0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95 % CI: 0.39-0.68) to 0.65 (0.55-0.75) for MME and 0.51 (0.37-0.65) to 0.68 (0.53-0.81) for FT-MIR. R²_cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted.

Relationship Between Content of Ketone Bodies in Milk and Milk Freezing Point of Polish Holstein-Friesian Cows in Early Lactation

The objective of this study was to determine the relationship between milk β-hydroxybutyrate (BHB), acetone (ACE) as well as parity and lactation stage and milk freezing point (MFP) in Polish Holstein-Friesian cows in early lactation. Additionally, we studied the relationship between milk ketone bodies and daily milk yield (DMY), fat (MF) and protein (MP) content in milk. The data obtained from the Polish Federation of Cattle Breeders and Dairy Farmers, comprised 749,894 test day milk samples, collected between 6 and 60 days in milk (DIM) from 521,049 lactations of 514,066 cows. Milk BHB and ACE were determined using the Fourier transform infrared (FTIR) technology. Four classes of parities were created: first, second, third, and fourth to seventh and two classes of lactation stage: 5–21 and 22–60 DIM. BHB was grouped into five classes: ≤0.05, 0.06–0.10, 0.11–0.20, 0.21–0.50 and >0.50 mmol/L, and ACE was also classified into five classes: ≤0.05, 0.06–0.10, 0.11–0.15, 0.16–0.30 and >0.30 mmol/L. Data on MFP, DMY, and MF and MP content were analyzed using the MIXED procedure of SAS and a linear model in which effects of parity, lactation stage, BHB and ACE classes were included, together with interactions between lactation stage and BHB classes, parity and BHB classes, lactation stage and ACE classes, and parity and ACE classes. The differences among parity, lactation stages, BHB and ACE classes in MFP, DMY, MF and MP were highly significant. There was a clear tendency for decreasing of MFP with increasing of BHB. Such a trend did not occur in case of ACE. DMY and MP decreased and MF increased with increasing BHB or ACE. In conclusion, since MFP can be measured relatively easily and is well related to milk BHB content, it may be used in the prediction of diagnostic models of ketosis based on milk composition.

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.

Symposium review: Big data, big predictions: Utilizing milk Fourier-transform infrared and genomics to improve hyperketonemia management

Negative animal health and performance outcomes are associated with disease incidences that can be labor-intensive, costly, and cumbersome for many farms. Amelioration of unfavorable outcomes through early detection and treatment of disease has emphasized the value of improving health monitoring. Although the value is recognized, detecting hyperketonemia (HYK) is still difficult for many farms to do practically and efficiently. Increasing data streams available to farms presents opportunities to use data to better monitor cow and herd health; however, challenges remain with regard to validating, integrating, and interpreting data. During the transition to lactation period, useful data are presented in the form of milk production and composition, milk Fourier-transform infrared (FTIR) wavelength absorbance, cow management records, and genomics, which have been employed to monitor postpartum onset of HYK. Attempts to predict postpartum HYK from test-day milk and performance variables incorporated into multiple linear regression models have demonstrated sufficient accuracy to monitor monthly herd prevalence; however, they lacked the sensitivity and specificity for individual cow diagnostics. Subsequent artificial neural network prediction models employing FTIR data and milk composition variables achieved 83 and 81% sensitivity and specificity for individual cow diagnostics. Although these results fail to reach the diagnostic goals of 90%, they are achieved without individual cow blood samples, which may justify acceptance of lower performance. The caveat is that these models depend on milk analysis, which is traditionally done every 4 weeks. This infrequent sampling allows for a single diagnostic sample for about half of the fresh cows. Benefits to farms are greatly improved if postpartum cows can be milk-tested weekly. Additionally, this allows for close monitoring of somatic cell count and may open the door for use of other herd health monitoring tools. Future improvements in these models may be achievable by maximizing sensitivity at the expense of specificity and may be most economical in disorders for which the cost of treatment is less than that of mistreating (e.g., HYK). Genomic predictions for HYK may be improved by incorporating genome-wide associated SNP and further utilized for precision management of HYK risk groups. Development and validation of HYK prediction models may provide producers with individual cow and herd-level management tools.

Diagnosis of Bovine Respiratory Disease in feedlot cattle using blood 1H NMR metabolomics

Current diagnosis methods for Bovine Respiratory Disease (BRD) in feedlots have a low diagnostic accuracy. The current study aimed to search for blood biomarkers of BRD using ¹H NMR metabolomics and determine their accuracy in diagnosing BRD. Animals with visual signs of BRD (n = 149) and visually healthy (non-BRD; n = 148) were sampled for blood metabolomics analysis. Lung lesions indicative of BRD were scored at slaughter. Non-targeted ¹H NMR metabolomics was used to develop predictive algorithms for disease classification using classification and regression trees. In the absence of a gold standard for BRD diagnosis, six reference diagnosis methods were used to define an animal as BRD or non-BRD. Sensitivity (Se) and specificity (Sp) were used to estimate diagnostic accuracy (Acc). Blood metabolomics demonstrated a high accuracy at diagnosing BRD when using visual signs of BRD (Acc = 0.85), however was less accurate at diagnosing BRD using rectal temperature (Acc = 0.65), lung auscultation score (Acc = 0.61) and lung lesions at slaughter as reference diagnosis methods (Acc = 0.71). Phenylalanine, lactate, hydroxybutyrate, tyrosine, citrate and leucine were identified as metabolites of importance in classifying animals as BRD or non-BRD. The blood metabolome classified BRD and non-BRD animals with high accuracy and shows potential for use as a BRD diagnosis tool.

Metabolomic Profile of Oviductal Extracellular Vesicles across the Estrous Cycle in Cattle

Oviductal extracellular vesicles (oEVs) have been proposed as key modulators of gamete/embryo maternal interactions. The aim of this study was to examine the metabolite content of oEVs and its regulation across the estrous cycle in cattle. Oviductal EVs were isolated from bovine oviducts ipsilateral and contralateral to ovulation at four stages of the estrous cycle (post-ovulatory stage, early and late luteal phases, and pre-ovulatory stage). The metabolomic profiling of EVs was performed by proton nuclear magnetic resonance spectroscopy (NMR). NMR identified 22 metabolites in oEVs, among which 15 were quantified. Lactate, myoinositol, and glycine were the most abundant metabolites throughout the estrous cycle. The side relative to ovulation had no effect on the oEVs' metabolite concentrations. However, levels of glucose-1-phosphate and maltose were greatly affected by the cycle stage, showing up to 100-fold higher levels at the luteal phase than at the peri-ovulatory phases. In contrast, levels of methionine were significantly higher at peri-ovulatory phases than at the late-luteal phase. Quantitative enrichment analyses of oEV-metabolites across the cycle evidenced several significantly regulated metabolic pathways related to sucrose, glucose, and lactose metabolism. This study provides the first metabolomic characterization of oEVs, increasing our understanding of the potential role of oEVs in promoting fertilization and early embryo development.

The relationship between plasma β-hydroxybutyric acid and conjugated linoleic acid in milk as a biomarker for early diagnosis of ketosis in postpartum Polish Holstein-Friesian cows

Background

The aim of this study was to investigate the association between plasma β-hydroxybutyric acid (BHBA) and conjugated linoleic acid in postpartum Polish Holstein-Friesian (PHF) cows. The experiment was carried out at an experimental dairy farm, where a herd of approximately 350 cows was kept. Samples were taken at six time points: between days 5–7, 8–14, 15–21, 22–28, 29–35, and 36–42, resulting in 510 samples of both milk and blood. The cows involved in the experiment were divided into two groups – ketotic and healthy – by taking into account general health symptoms, blood serum BHBA, and non-esterified fatty acids (NEFA) concentration at 5–7 days postpartum.

Results

In the first week of lactation, at 5–7 day in milk (DIM), the study showed a 53% lower level of C18:2 cis-9 trans-11 (CLA9) and an 80% lower level of C18:2 trans-10 cis-12 (CLA10) in cows with diagnosed ketosis compared to healthy cows. In the second week of lactation (8–14 DIM), a 34% lower level of CLA9 and a 54% lower level of CLA10 was found in the group of cows with BHBA levels > 1.2 mmol/L. Additionally, Pearson correlation analysis showed significant negative correlation between BHBA x CLA9 and BHBA x CLA10 in the first week of lactation: − 0.732and − 0.821, respectively.

Conclusion

The study shows that that both CLA9 and CLA10 can be used as markers for the early diagnosis of elevated blood levels of BHBA in postpartum Polish Holstein-Friesian cows.

Beta-hydroxybutyrate in milk as screening test for subclinical ketosis in dairy cows

Ketosis is a very frequent metabolic disease in dairy cows, resulting in lower milk production, impaired fertility and increased frequency of other diseases. The course of the disease is often subclinical, so early detection is very important. The aim of the study was to investigate the relation between the concentration of beta-hydroxybutyrate in blood and milk and to determine the cut-off value in milk for detection of subclinical ketosis. The study included 94 cows, which were in the first third of lactation. Beta-hydroxybutyrate (BHB) concentrations were measured in blood and milk serum using a biochemical analyser. The average concentration of BHB in the blood serum samples was 1.14 mmol/L while in the milk it was about ten times lower at 0.117 mmol/L. A statistically significant positive correlation between the concentration of BHB in blood and milk (r=0.705, p<0.001) was found. In cows with BHB in blood below 2.0 mmol/L a stronger correlation between blood and milk BHB was established (r=0.658, p<0.001) than in cows with blood BHB above 2.0 mmol/L (r=-0.292, p=0.206). Therefore, BHB in milk is a very suitable indicator in the diagnosis of subclinical ketosis as there is a good correlation between BHB in the blood and milk of cows with subclinical ketosis. The cut-off concentration of BHB in milk set at ≥0.080 mmol/L (AUC=0.91±0.03; p<0.001) is a significant indicator for subclinical ketosis in dairy cows. The sensitivity of the test was 94% and specificity 74%. Beta-hydroxybutyrate in milk is a good indicator of subclinical ketosis in dairy cows and can be measured accurately with a biochemical analyser.

Hyperketolactia occurrence before or after artificial insemination is associated with a decreased pregnancy per artificial insemination in dairy cows

The reproductive parameters of dairy cattle have continuously declined worldwide over the last 50 years. Nutritional imbalances are identified as risk factors for this decrease of reproductive performance. The present paper aims to quantify the decrease in the pregnancy per artificial insemination (P/AI) in the case of high milk ketones before and after AI. A total of 388,731 test-day from the Brittany Milk Recording Program in France from 226,429 cow-lactations were provided for this trial. For each test-day, information about lactation characteristics, date of AI, date of the following calving, and acetone and β-hydroxybutyrate (BHB) values were included. Ketones were predicted by Fourier transform mid-infrared spectroscopy using MilkoScan Foss analyzers (Foss, Hillerød, Denmark). Many thresholds were evaluated to define cows with hyperketolactia. Hyperketolactia statuses were then categorized into 1 of 4 possible classes according to the milk ketone dynamics for each AI and each threshold of acetone or BHB values (low-low, high-low, low-high, and high-high) within 20 d before and after AI. Similarly, the dynamics of udder health were characterized by changes in somatic cell counts measured at the same test day as ketone bodies. A logistic regression with a Poisson correction was performed to explain the relationship of P/AI with milk ketones and somatic cell count dynamics. Predicted acetone and BHB ranged from -0.51 to 4.92 mM (mean = 0.08 mM, SD = 0.10 mM) and -0.62 to 5.85 mM (mean = 0.07 mM, SD = 0.1 mM), respectively. Hyperketolactia defined by high acetone levels before AI was not associated with decreased P/AI, but high acetone levels after AI were associated with a >10% reduction in P/AI for all thresholds >0.10 mM. Hyperketolactia, defined by high BHB values before, after, or before and after AI, was associated with a 6 to 14% reduction in P/AI compared with cows with low BHB values. These associations are lower than those reported in previous trials in which blood ketones were used. High ketones in advanced lactation are likely to be the result of various primary disorders (secondary ketosis). Because the present work demonstrated that this situation is considered a risk factor for deteriorated reproductive performance, we suggest that high ketones in early and advanced lactation should be of interest to farm advisors.

Effects of feeding management on disease incidence and blood metabolites in dairy herds in Iwate Prefecture, Japan

The objective of the present study was to identify the effect of feeding management on disease incidence and blood metabolite levels in dairy herds in Iwate Prefecture, Japan. A generalized linear model approach was used to identify the risk factors for ketosis and displaced abomasum (DA) in dairy herds (n=30), and metabolic profile test (MPT) results were compared to verify the involvement of the factors. Consequently, the proportion of corn silage (CS) with ≥30% of dry matter (DM) fed to cows during the lactation period was confirmed as the most reliable risk factor for ketosis, while no risk factor was identified for DA. Meanwhile, the incidence rates of ketosis and DA were significantly (P<0.05) higher in the herds that were fed CS (n=20) than in those fed a non-CS diet (n=10). When the MPT results of the herds fed with CS containing ≥30% of DM (HCS group, n=4; 76 cows), with CS containing <30% of DM (LCS group, n=14; 285 cows), and a non-CS diet (NCS group, n=12; 236 cows) were compared, the HCS group showed higher beta-hydroxybutyric and lower blood urea nitrogen concentrations for until 49 days after parturition. Overall, feeding cows with CS diets containing over 30% of DM might increase their risk of developing negative energy and protein balances, thereby resulting in increasing incidences of ketosis in the Iwate Prefecture.

Nutritional and performance viability of cactus Opuntia-based diets added to concentrate levels for Girolando lactating dairy cows

Objective

The aim of this research was to evaluate the effect of different concentrate levels in diets based on cactus Opuntia Stricta (Haw.) Haw cladodes on the performance of lactating Girolando cows.

Methods

The experiment involved 10 Girolando multiparous dairy cows at 512.6 kg of body weight (BW) and producing 13.2 kg milk/d, allocated into two 5×5 Latin squares. The experimental treatments consisted of control diet composed by cactus Nopalea cochenillifera. Salm-Dyck. cladodes (Nopalea), forage sorghum silage and concentrate at 20% on dry matter (DM) basis, and four concentrate levels diets (20%, 24%, 28%, and 32%) plus cactus Opuntia stricta (Haw.) Haw. cladodes (Opuntia) and forage sorghum silage.

Results

Regarding cows fed control diet, the nutrients intake were greater than for cows fed with cactus Opuntia and concentrate. Regarding concentrate levels, intakes of DM, organic matter (OM), crude protein (CP), non-fiber carbohydrates (NFC), and total digestible nutrients of cows increased linearly. Organic matter, CP, and NDF digestibilities were similar in between to control diet and cactus Opuntia-based diets. The digestibility of NFC increased linearly when the concentrate was inserted. The N balance was the same for control diet and cactus Opuntia-based diets, irrespective the concentrate levels.

Conclusion

For cows producing 14 kg/d with 3.5% of fat, it is recommended 32% of concentrate to be included in cactus Opuntia-based diets, and the increase in concentrate level promotes a linear increase in milk yield.