Review: Metabolic challenges in lactating dairy cows and their assessment via established and novel indicators in milk

Attomolar-sensitive milk fever sensor using 3D-printed multiplex sensing structures

The diagnosis of milk fever or hypocalcemia in lactating cows has a significant economic impact on the dairy industry. It is challenging to identify asymptomatic subclinical hypocalcemia (SCH) in transition dairy cows. Monitoring subclinical hypocalcemia in milk samples can expedite treatment and improve the health, productivity, and welfare of dairy cows. In this study, an attomolar-sensitive sensor is developed using extrusion-based 3D-printed sensing structures to detect the ratio of ionized calcium to phosphate levels in milk samples. The unique geometries of the lateral structure of 3D-printed sensors, along with the wrinkled surfaces, provide a limit of detection down to the attomole (138 aM) concentration of the target analyte. The calcium-to-phosphate ratio in milk samples not only provides early disease indications but also enables on-site testing. This highly selective test is validated using real milk and blood samples, and the results are compared with those of commercial meters. This fast response (~10 s) low-cost sensor opens a promising tool for the farm-side diagnostic of dairy cows that can promote best practice management of dairy cows.

Phenotypic variation of dairy cows' hematic metabolites and feasibility of non-invasive monitoring of the metabolic status in the transition period

Introduction

The incidence of metabolic diseases tends to be highest during the transition period (±3 weeks around parturition) in dairy cows due to physiological changes and the onset of lactation. Although blood profile testing allows for the monitoring of nutritional and metabolic status, conducting extensive analyses in the herd is costly and stressful for cows due to invasive procedures. Therefore, mid-infrared spectroscopy (MIR) could be seen as a valid alternative.

Methods

In the present study, we used laboratory-determined reference blood data and milk spectra of 349 Holstein cows to (i) identify the non-genetic factors affecting the variability of major blood traits in healthy cows and, subsequently, (ii) test the predictive ability of milk MIR. Cows belonged to 14 Italian commercial farms and were sampled once between 5 and 38 days in milk. For β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), cholesterol, glucose, urea, total protein, albumin, globulin, minerals, aspartate aminotransferase, gamma-glutamyl transferase, creatine kinase, total bilirubin, and cortisol, the effects of parity, days in milk, and season were investigated using a linear model.

Results and discussion

The results indicate that all fixed effects significantly affected the hematic concentration of most of the traits. Regarding MIR, the most predictable traits were BHB, NEFA, and urea, with coefficients of determination equal to 0.57, 0.62, and 0.89, respectively. These values suggest that MIR predictions of BHB and NEFA are not sufficiently accurate for precise and punctual determination of the hematic concentration, however, still the spectrum of the milk can be exploited to identify cows at risk of negative energy balance and subclinical ketosis. Finally, the predictions can be useful for herd screening, decision-making, and genetic evaluation.

Detection of Mycobacterium avium subsp. paratuberculosis in Australian Cattle and Sheep by Analysing Volatile Organic Compounds in Faeces

Paratuberculosis is a debilitating disease of ruminants that causes significant economic loss in both cattle and sheep. Early detection of the disease is crucial to controlling the disease; however, current diagnostic tests lack sensitivity. This study evaluated the potential for volatile organic compounds (VOCs) detected by gas chromatography and an electronic nose (eNose) for use as diagnostic tools to differentiate between Map-infected and non-infected cattle and sheep. Solid-phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) was used to quantify VOCs from the headspace of faecal samples (cattle and sheep), and partial least squares-discriminant analysis (PLS-DA) was used to determine the suitability as a diagnostic tool. Both the cattle and sheep models had high specificity and sensitivity, 98.1% and 92.3%, respectively, in cattle, and both were 100% in sheep. The eNose was also able to discriminate between Map-infected and non-infected sheep and cattle with 88.9% specificity and 100% sensitivity in sheep and 100% specificity and sensitivity in cattle. This is the first time that VOC analysis by eNose and GCMS has been used for identification of Map in cattle and sheep faeces. GCMS also allowed the identification of putative disease biomarkers, and the eNose diagnostic capability suggests it is a promising tool for point-of-care diagnosis for Map detection on farms.

Developmental programming of production and reproduction in dairy cows: V. Association of the main and interactive effects of maternal level of milk production and milk fat to protein ratio with offspring's birth weight, survival, and productive and reproductive performance from birth to the first lactation period

Level of dam milk production (DMP) and dam milk fat to protein ratio (DFPR), as an indicator of metabolic status in dairy cows, have been identified to be associated with productive and reproductive performance of the offspring. Yet whether the interaction of DMP by DFPR can be associated with performance of the offspring have not been studied to our knowledge. Therefore, the present study was conducted to investigate the association of the main and interactive effects of DMP and DFPR with offspring's birth weight, survival, milk yield and fertility. To this end, data of birth weight, culling rate, milk yield and reproductive variables of offspring born to lactating dams (n = 14,582) and data associated with DMP and DFPR during 305-day lactation were retrieved. Afterwards, offspring were classified in three categories of DMP, including DMP1 (dams with <10.00 × 103 kg of 305-day milk production), DMP2 (dams with ≥10.00 × 103 kg and <14.00 × 103 kg of 305-day milk production), DMP3 (dams with ≥14.00 × 103 kg of 305-day milk production), and three categories of DFPR, including DFPR1 (offspring born to dams with <1.00 FPR), DFPR2 (offspring born to dams with ≥1.00 and < 1.40 FPR) and DFPR3 (offspring born to dams with ≥1.40 FPR). Statistical analysis revealed no association of the interaction effect of DMP by DFPR with investigated variables in the offspring (P > 0.05). However, the main effect of DMP was positively associated with milk yield, but negatively associated with survival, age at first insemination and conception during nulliparity, and transgenerational improvement in milk yield in the offspring (P < 0.05). Moreover, the main effect of DFPR was positively associated with birth weight, survival and first service conception rate during nulliparity, but negatively associated with metabolic status and reproductive performance during primiparity in the offspring (P < 0.05). In conclusion, the present study did not find any interaction effect of DMP by DFPR on productive and reproductive variables in the offspring. This finding implicates the association of DMP with milk production in the offspring was regardless of DFPR. Moreover, this finding implies the association of DFPR with postpartum metabolic status and reproductive performance in the offspring was regardless of DMP.

Patterns of variation and relationships among fat, protein, and milk yield of individual dairy cattle in a Thai multibreed population

This study systematically examines the patterns of milk yield (MY, kg), fat (FAT, %), and protein (PROT, %) in a diverse population of Thai multibreed dairy cattle, considering the tropical environment's impact on lactating cows. Using a dataset of 47,205 monthly test-day records from 4,440 first-lactation cows across 446 farms, we analyze variations and interrelationships through mathematical averaging and introduce the fat-to-protein ratio (FPR) to assess acidosis (FPR < 1.1) and ketosis (FPR > 1.5) risks during lactation. Pearson correlation analysis elucidated trait associations. The findings, aligned with established lactation norms, indicate peak production at 297 days in milk (DIM) for FAT (4.08%; SD = 0.96%), PROT (3.43%; SD = 0.47%), and 52 DIM for MY (18.09 kg; SD = 4.91 kg). Nadirs are observed at 72 DIM for FAT (3.27%; SD = 0.74%), 47 DIM for PROT (2.86%; SD = 0.36%), and 299 DIM for MY (9.05 kg; SD = 2.95 kg). FPR variations highlight acidosis (46.48%), normal (43.66%), and ketosis (9.86%), especially during early lactation (100 DIM). Significant negative correlations emerge between MY, FAT, and PROT (P < 0.05), while a positive correlation is identified between FAT and PROT (P < 0.01), with robust correlations during early lactation. This study contributes to understanding tailored nutritional strategies for dairy cows' holistic health and sustainability in tropical environments, guiding efficient production practices and mitigating health-related productivity impediments.

Milk component ratios and their associations with energy balance indicators and serum calcium concentration in early-lactation spring-calving pasture-based dairy cows

Indirect assessment of metabolic status using milk samples provides a non-invasive and objective tool for cow-level health monitoring. Milk fat-to-protein ratio (FPR) has been commonly evaluated as an indirect measure for negative energy balance (EB) in confined dairy cows. However, milk component ratios have not been explored for their association with pasture-based cows' metabolic status. The objectives of this observational study were to 1) describe milk component ratios from 0 to 45 d postpartum, 2) evaluate the associations between milk component ratios [FPR, fat-to-lactose (FLR), protein-to-lactose (PLR)] and indicators of EB (serum β-hydroxybutyrate (BHB) concentration at 5-45 d postpartum and body condition score (BCS) change during the transition period), and 3) evaluate the associations between milk component ratios and serum Ca concentration 0-4 d postpartum in spring-calving dairy cows from pasture-based commercial farms. Milk component ratios were determined on samples collected before AM or PM milkings from 548 cows at 0-45 d postpartum (n = 970). Serum BHB and Ca determinations were performed in blood samples collected at the time of milk sample collection at 5-45 d postpartum (n = 918) and 0-4 d postpartum (n = 50), respectively; and BCS change was calculated using BCS assigned between 29 d prepartum and 45 d postpartum (n = 851). Cows' calving date, parity (1st, 2nd-3rd or ≥ 4th) and breed (Holstein-Friesian or dairy crossbred) information was obtained from the farm records. Data was analyzed by multiple linear regression. Average milk FPR, FLR and PLR were 0.70, 0.53 and 0.72, respectively. Milk FPR linearly increased while milk FLR linearly decreased postpartum both at a rate of 0.004 units per day; milk PLR decreased 0.05 units per day for the first 30 d postpartum and moderately increased afterward. Milk FPR and FLR were 0.71 and 0.52 units lower before AM than PM milking, respectively; while milk PLR was similar before AM and PM milking. Milk FPR and FLR were 0.07 to 0.10 units higher for 2nd-3rd compared with 1st and ≥ 4th parity cows. Milk PLR was 0.03 units greater for ≥ 4th compared with 2nd-3rd and 1st parity cows. Further, crossbred cows had 0.07, 0.08 and 0.03 higher milk FPR, FLR and PLR than Holstein-Friesian cows, respectively. Moderate to high P-values along with moderate to small estimated slopes and wide 95% confidence intervals were observed for the associations between milk component ratios and indicators of EB. A positive linear association was observed between milk FPR and serum Ca concentration within 4 d postpartum; milk FPR increased 0.31 units per each mmol/L increase in serum Ca concentration. Cows with low serum Ca concentration within 4 d postpartum had 0.27 units lower milk FPR compared with cows at or above the threshold (2.12 mmol/L), and tended to have 0.15 units lower milk FPR compared with cows at or above the threshold (2.00 mmol/L). In conclusion, further research is needed to reach conclusions on the association between milk component ratios determined before milking and EB indicators. The potential of milk FPR for monitoring blood Ca status warrants further investigation in early-lactation pasture-based dairy cows.

Milk components as potential indicators of energy status in early lactation Holstein dairy cows from two farms

Negative energy balance (NEB) is a serious problem in most dairy cows. It occurs most frequently after calving, when cows are unable to consume sufficient DM to meet their energy requirements during early lactation. During NEB, the breakdown of fat stores releases non-esterified fatty acids (NEFAs) into the bloodstream. High blood concentrations of NEFAs cause health problems such as ketosis, fatty liver syndrome, and enhanced susceptibility to infections. These issues may substantially increase premature culling from the herd. Serum NEFA concentrations are often used as a direct marker of energy metabolism. However, because the direct measurement of serum NEFAs is difficult under commercial conditions, alternative indicators, such as milk components, have been increasingly investigated for their use in estimating energy balance. The objectives of this study were to (1) evaluate the relationships between serum NEFA concentrations and selected milk components in cows from two farms during the first 5 weeks of lactation, and to (2) develop a model valid for both herds for predicting serum NEFA concentrations using milk components. A total of 121 lactating Holstein cows from two different farms were included in the experiment. Blood samples were collected for NEFA analysis on days 7 (± 3), 14 (± 3), 21 (± 3), and 35 (± 3) after calving. Composite milk samples were collected during afternoon milking on the same days as blood sampling. Concentrations of fat, protein, lactose, and milk fatty acids (FAs) were determined using Fourier-transform IR spectroscopy analysis. The strongest correlations (r > 0.43) were recorded between serum NEFAs and milk long-chain FAs, monounsaturated FAs, C18:0, and C18:1 within each farm and for both farms combined. Two prediction models for serum log(NEFA) using milk components as predictors were developed by stepwise regression. The prediction model with the best fit (R2 = 0.52) included days in milk, fat-to-protein ratio, and C18:1, C18:12 and C14:0 expressed as g/100 g of milk fat. An essential finding is that, despite different concentrations of NEFAs, and of most milk components observed in the evaluated herds, there were no significant interactions between farm and any of the FAs, so the same regression coefficients could be used for the prediction models in both farms. Validation of these findings in a greater number of herds would allow for the use of milk FAs to identify energy-imbalanced cows in herds under different farm conditions.

Genetic analysis of milk citrate predicted by milk mid-infrared spectra of Holstein cows in early lactation

Milk citrate is regarded as an early biomarker of negative energy balance in dairy cows during early lactation and serves as a suitable candidate phenotype for genomic selection due to its wide availability across a large number of cows through milk mid-infrared spectra prediction. However, its genetic background is not well known. Therefore, the objectives of this study were to (1) analyze the genetic parameters of milk citrate; (2) identify genomic regions associated with milk citrate; and (3) analyze the functional annotation of candidate genes and quantitative trait loci (QTL) related to milk citrate in Walloon Holstein cows. In total, 134,517 test-day milk-citrate phenotypes (mmol/L) collected within the first 50 d in milk on 52,198 Holstein cows were used. These milk-citrate phenotypes, predicted by milk mid-infrared spectra, were divided into 3 traits according to the first (citrate1), second (citrate2), and third to fifth parity (citrate3+). Genomic information for 566,170 SNPs was available for 4,479 animals. A multiple-trait repeatability model was used to estimate genetic parameters. A single-step GWAS was used to identify candidate genes for citrate and post-GWAS analysis was done to investigate the relationship and function of the identified candidate genes. The heritabilities estimated for citrate1, citrate2, and citrate3+ were 0.40, 0.37, and 0.35, respectively. The genetic correlations among the 3 traits ranged from 0.98 to 0.99. The genomic correlations among the 3 traits were also close to 1.00 across the genomic regions (1 Mb) in the whole genome, which means that citrate can be considered as a single trait in the first 5 parities. In total, 603 significant SNPs located on 3 genomic regions (chromosome 7, 68.569-68.575 Mb; chromosome 14, 0.15-1.90 Mb; and chromosome 20, 54.00-64.28 Mb), were identified to be associated with milk citrate. We identified 89 candidate genes including GPT, ANKH, PPP1R16A, and 32 QTL reported in the literature related to the identified significant SNPs. These identified QTL were mainly reported associated with milk fatty acids and metabolic diseases in dairy cows. This study suggests that milk citrate in Holstein cows is highly heritable and has the potential to be used as an early proxy for the negative energy balance of Holstein cows in a breeding objective.

Developmental programming of production and reproduction in dairy cows: IV. Association of maternal milk fat and protein percentage and milk fat to protein ratio with offspring's birth weight, survival, productive and reproductive performance and AMH concentration from birth to the first lactation period

Although the association of maternal milk production with developmental programming of offspring has been investigated, there is limited information available on the relationship of maternal milk components with productive and reproductive performance of the offspring. Therefore, the present study was conducted to analyze the association of maternal milk fat and protein percentage and milk fat to protein ratio with birth weight, survival, productive and reproductive performance and AMH concentration in the offspring. In study I, data of birth weight, milk yield and reproductive variables of offspring born to lactating dams (n = 14,582) and data associated with average maternal milk fat percentage (MFP), protein percentage (MPP) and fat to protein ratio (MFPR) during 305-day lactation were retrieved. Afterwards, offspring were classified in various categories of MFP, MPP and MFPR. In study II, blood samples (n = 339) were collected from offspring in various categories of MFP, MPP and MFPR for measurement of serum AMH. Maternal milk fat percentage was positively associated with birth weight and average percentage of milk fat (APMF) and protein (APMP) and milk fat to protein ratio (FPR) during the first lactation, but negatively associated with culling rate during nulliparity in the offspring (P < 0.05). Maternal milk protein percentage was positively associated with birth weight, APMF, APMP, FPR and culling rate, but negatively associated with milk yield and fertility in the offspring (P < 0.05). Maternal FPR was positively associated with APMF and FPR, but negatively associated with culling rate, APMP and fertility in the offspring (P < 0.05). However, concentration of AMH in the offspring was not associated with MFP, MPP and MFPR (P > 0.05). In conclusion, the present study revealed that maternal milk fat and protein percentage and their ratio were associated with birth weight, survival, production and reproduction of the offspring. Yet it was a preliminary research and further studies are required to elucidate the mechanisms underlying these associations.

Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models

BACKGROUND

Metabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation. Hence, we evaluated the genomic prediction of serum biomarkers levels for metabolic distress in 1353 Holsteins genotyped with the 100K single nucleotide polymorphism (SNP) chip assay. The GS was evaluated using parametric models best linear unbiased prediction (GBLUP), Bayesian B (BayesB), elastic net (ENET), and nonparametric models, gradient boosting machine (GBM) and stacking ensemble (Stack), which combines ENET and GBM approaches.

RESULTS

The results show that the Stack approach outperformed other methods with a relative difference (RD), calculated as an increment in prediction accuracy, of approximately 18.0% compared to GBLUP, 12.6% compared to BayesB, 8.7% compared to ENET, and 4.4% compared to GBM. The highest RD in prediction accuracy between other models with respect to GBLUP was observed for haptoglobin (hapto) from 17.7% for BayesB to 41.2% for Stack; for Zn from 9.8% (BayesB) to 29.3% (Stack); for ceruloplasmin (CuCp) from 9.3% (BayesB) to 27.9% (Stack); for ferric reducing antioxidant power (FRAP) from 8.0% (BayesB) to 40.0% (Stack); and for total protein (PROTt) from 5.7% (BayesB) to 22.9% (Stack). Using a subset of top SNPs (1.5k) selected from the GBM approach improved the accuracy for GBLUP from 1.8 to 76.5%. However, for the other models reductions in prediction accuracy of 4.8% for ENET (average of 10 traits), 5.9% for GBM (average of 21 traits), and 6.6% for Stack (average of 16 traits) were observed.

CONCLUSIONS

Our results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.

Combined Metabolomics and Biochemical Analyses of Serum and Milk Revealed Parity-Related Metabolic Differences in Sanhe Dairy Cattle

The production performance of dairy cattle is closely related to their metabolic state. This study aims to provide a comprehensive understanding of the production performance and metabolic features of Sanhe dairy cattle across different parities, with a specific focus on evaluating variations in milk traits and metabolites in both milk and serum. Sanhe dairy cattle from parities 1 to 4 (S1, n = 10; S2, n = 9; S3, n = 10; and S4, n = 10) at mid-lactation were maintained under the same feeding and management conditions. The milk traits, hydrolyzed milk amino acid levels, serum biochemical parameters, and serum free amino acid levels of the Sanhe dairy cattle were determined. Multiparous Sanhe dairy cattle (S2, S3, and S4) had a greater milk protein content, lower milk lactose content, and lower solids-not-fat content than primiparous Sanhe dairy cattle (S1). Moreover, S1 had a higher ratio of essential to total amino acids (EAAs/TAAs) in both the serum and milk. The serum biochemical results showed the lower glucose and total protein levels in S1 cattle were associated with milk quality. Furthermore, ultra-high-resolution high-performance liquid chromatography with tandem MS analysis (UPLC-MS/MS) identified 86 and 105 differential metabolites in the serum and milk, respectively, and these were mainly involved in amino acid, carbohydrate, and lipid metabolism. S1 and S2/S3/S4 had significantly different metabolic patterns in the serum and milk, and more vitamin B-related metabolites were significantly higher identified in S1 than in multiparous cattle. Among 36 shared differential metabolites in the serum and milk, 10 and 7 metabolites were significantly and strongly correlated with differential physiological indices, respectively. The differential metabolites identified were enriched in key metabolic pathways, illustrating the metabolic characteristics of the serum and milk from Sanhe dairy cattle of different parities. L-phenylalanine, dehydroepiandrosterone, and linoleic acid in the milk and N-acetylornithine in the serum could be used as potential marker metabolites to distinguish between Sanhe dairy cattle with parities of 1-4. In addition, a metabolic map of the serum and milk from the three aspects of carbohydrates, amino acids, and lipids was created for the further analysis and exploration of their relationships. These results reveal significant variations in milk traits and metabolites across different parities of Sanhe dairy cattle, highlighting the influence of parity on the metabolic profiles and production performance. Tailored nutritional strategies based on parity-specific metabolic profiles are recommended to optimize milk production and quality in Sanhe cattle.

Observational study on the associations between milk yield, composition, and coagulation properties with blood biomarkers of health in Holstein cows

The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits). All milk traits (i.e., production, composition, and technological traits) were analyzed according to a linear mixed model that included the days in milk, the parity order, and the blood metabolites (tested one at a time) as fixed effects and the herd and date of sampling as random effects. Our findings revealed that milk yield and daily milk energy output were positively and linearly associated with total cholesterol, nonesterified fatty acids, urea, aspartate aminotransferase, γ-glutamyl transferase, total bilirubin, albumin, and ferric-reducing antioxidant power, whereas they were negatively associated with glucose, creatinine, alkaline phosphatase, total reactive oxygen metabolites, and proinflammatory proteins (ceruloplasmin, haptoglobin, and myeloperoxidase). Regarding composition traits, the protein percentage was negatively associated with nonesterified fatty acids and β-hydroxybutyrate (BHB), while the fat percentage was positively associated with BHB, and negatively associated with paraoxonase. Moreover, we found that the lactose percentage increased with increasing cholesterol and albumin and decreased with increasing ceruloplasmin, haptoglobin, and myeloperoxidase. Milk urea increased with an increase in cholesterol, blood urea, nonesterified fatty acids, and BHB, and decreased with an increase in proinflammatory proteins. Finally, no association was found between the blood metabolites and milk coagulation properties and curd-firming traits. In conclusion, this study showed that variations in blood metabolites had strong associations with milk productivity traits, the lactose percentage, and milk urea, but no relationships with technological traits of milk. Specifically, increasing levels of proinflammatory and oxidative stress metabolites, such as ceruloplasmin, haptoglobin, myeloperoxidase, and total reactive oxygen metabolites, were shown to be associated with reductions in milk yield, daily milk energy output, lactose percentage, and milk urea. These results highlight the close connection between the metabolic and innate immunity status and production performance. This connection is not limited to specific clinical diseases or to the transition phase but manifests throughout the entire lactation. These outcomes emphasize the importance of identifying cows with subacute inflammatory and oxidative stress as a means of reducing metabolic impairments and avoiding milk fluctuations.

Metabolic Changes in Serum and Milk of Holstein Cows in Their First to Fourth Parity Revealed by Biochemical Analysis and Untargeted Metabolomics

The performance of dairy cows is closely tied to the metabolic state, and this performance varies depending on the number of times the cows have given birth. However, there is still a lack of research on the relationship between the metabolic state of Holstein cows and the performance of lactation across multiple parities. In this study, biochemical analyses and metabolomics studies were performed on the serum and milk from Holstein cows of parities 1-4 (H1, N = 10; H2, N = 7; H3, N = 9; H4, N = 9) in mid-lactation (DIM of 141 ± 4 days) to investigate the link between performance and metabolic changes. The results of the milk quality analysis showed that the lactose levels were highest in H1 (p = 0.036). The total protein content in the serum increased with increasing parity (p = 0.013). Additionally, the lipase activity was found to be lowest in H1 (p = 0.022). There was no difference in the composition of the hydrolyzed amino acids in the milk among H1 to H4. However, the free amino acids histidine and glutamate in the serum were lowest in H1 and highest in H3 (p < 0.001), while glycine was higher in H4 (p = 0.031). The metabolomics analysis revealed that 53 and 118 differential metabolites were identified in the milk and serum, respectively. The differential metabolites in the cows' milk were classified into seven categories based on KEGG. Most of the differential metabolites in the cows' milk were found to be more abundant in H1, and these metabolites were enriched in two impact pathways. The differential metabolites in the serum could be classified into nine categories and enriched in six metabolic pathways. A total of six shared metabolites were identified in the serum and milk, among which cholesterol and citric acid were closely related to amino acid metabolism in the serum. These findings indicate a significant influence of blood metabolites on the energy and amino acid metabolism during the milk production process in the Holstein cows across 1-4 lactations, and that an in-depth understanding of the metabolic changes that occur in Holstein cows during different lactations is essential for precision farming, and that it is worthwhile to further investigate these key metabolites that have an impact through controlled experiments.

Milk as an indicator of dietary imbalance

BACKGROUND

Milk provides a readily available diagnostic fluid collected daily or more frequently on an individual animal or herd basis. Milk, as an aggregated sample in bulk tank milk (BTM) represents the status of a herd instead of a single animal. In this review, we examine the potential for milk to predict risks to efficient production, reproductive success, and health on the individual cow and herd level.

FINDINGS

For many conditions related to disorders of metabolism including hyperlipdaemia and ketonaemia, improved individual cow milk testing may allow a temporally useful detection of metabolic disorder that can target intervention. However, the extension of these tests to the BTM is made more difficult by the tight temporal clustering of disorder to early lactation and the consequent mixing of cows at even moderately different stages of lactation. Integrating herd recording demographic information with Fourier-transformed mid-infrared spectra (FT-MIR) can provide tests that are useful to identify cows with metabolic disorders. The interpretation of BTM urea and protein content provides useful indications of herd nutrition. These may provide indicators that encourage further investigations of nutritional influences on herd fertility but are unlikely to provide strong diagnostic value. The fat-to-protein ratio has a high specificity, but poor sensitivity for detection of fibre insufficiency and acidosis on an individual cow basis. Selenium, zinc, β-carotene, and vitamin E status of the herd can be determined using BTM.

CONCLUSIONS

There appears to be increasing potential for the use of milk as a diagnostic fluid as more in-parlour tests become available for individual cows. However, the BTM appears to have under-utilised potential for herd monitoring.

In-Line Registered Milk Fat-to-Protein Ratio for the Assessment of Metabolic Status in Dairy Cows

This study endeavors to ascertain alterations in the in-line registered milk fat-to-protein ratio as a potential indicator for evaluating the metabolic status of dairy cows. Over the study period, farm visits occurred biweekly on consistent days, during which milk composition (specifically fat and protein) was measured using a BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania). Clinical examinations were performed at the same time as the farm visits. Blood was drawn into anticoagulant-free evacuated tubes to measure the activities of GGT and AST and albumin concentrations. NEFA levels were assessed using a wet chemistry analyzer. Using the MediSense and FreeStyle Optium H systems, blood samples from the ear were used to measure the levels of BHBA and glucose in plasma. Daily blood samples were collected for BHBA concentration assessment. All samples were procured during the clinical evaluations. The cows were categorized into distinct groups: subclinical ketosis (SCK; n = 62), exhibiting elevated milk F/P ratios without concurrent clinical signs of other post-calving diseases; subclinical acidosis (SCA; n = 14), characterized by low F/P ratios (<1.2), severe diarrhea, and nondigestive food remnants in feces, while being free of other post-calving ailments; and a healthy group (H; n = 20), comprising cows with no clinical indications of illness and an average milk F/P ratio of 1.2. The milk fat-to-protein ratios were notably higher in SCK cows, averaging 1.66 (±0.29; p < 0.01), compared to SCA cows (0.93 ± 0.1; p < 0.01) and healthy cows (1.22). A 36% increase in milk fat-to-protein ratio was observed in SCK cows, while SCA cows displayed a 23.77% decrease. Significant differences emerged in AST activity, with SCA cows presenting a 26.66% elevation (p < 0.05) compared to healthy cows. Moreover, SCK cows exhibited a 40.38% higher NEFA concentration (p < 0.001). A positive correlation was identified between blood BHBA and NEFA levels (r = 0.321, p < 0.01), as well as a negative association between BHBA and glucose concentrations (r = -0.330, p < 0.01). Notably, AST displayed a robust positive correlation with GGT (r = 0.623, p < 0.01). In light of these findings, this study posits that milk fat-to-protein ratio comparisons could serve as a non-invasive indicator of metabolic health in cows. The connections between milk characteristics and blood biochemical markers of lipolysis and ketogenesis suggest that these markers can be used to check the metabolic status of dairy cows on a regular basis.

Invited Review: Increasing Milk Yield and Negative Energy Balance: A Gordian Knot for Dairy Cows?

The continued increase in milk production during the last century has not been accompanied by an adequate dry matter intake (DMI) by cows, which therefore experience a negative energy balance (NEB). NEB is low and of minor importance at low milk yield (MY), such as for the nutrition of one calf, and under these circumstances is considered "natural". MY and low DMI around parturition are correlated and are the reason for the genetic correlation between increasing MY and increasing NEB up to 2000 MJ or more for 2-3 months postpartum in high-genetic-merit dairy cows. The extension and duration of NEB in high-producing cows cannot be judged as "natural" and are compensated by the mobilization of nutrients, particularly of fat. The released non-esterified fatty acids (NEFAs) overwhelm the metabolic capacity of the cow and lead to the ectopic deposition of NEFAs as triglycerides (TGs) in the liver. The subsequent lipidosis and the concomitant hampered liver functions cause subclinical and clinical ketosis, both of which are associated with "production diseases", including oxidative and endoplasmatic stress, inflammation and immunosuppression. These metabolic alterations are regulated by homeorhesis, with the priority of the physiological function of milk production. The prioritization of one function, namely, milk yield, possibly results in restrictions in other physiological (health) functions under conditions of limited resources (NEB). The hormonal framework for this metabolic environment is the high concentration of growth hormone (GH), the low concentration of insulin in connection with GH-dependent insulin resistance and the low concentration of IGF-1, the so-called GH-IGF-1 axis. The fine tuning of the GH-IGF-1 axis is uncoupled because the expression of the growth hormone receptor (GHR-1A) in the liver is reduced with increasing MY. The uncoupled GH-IGF-1 axis is a serious impairment for the GH-dependent stimulation of gluconeogenesis in the liver with continued increased lipolysis in fat tissue. It facilitates the pathogenesis of lipidosis with ketosis and, secondarily, "production diseases". Unfortunately, MY is still increasing at inadequate DMI with increasing NEB and elevated NEFA and beta-hydroxybutyric acid concentrations under conditions of low glucose, thereby adding health risks. The high incidences of diseases and of early culling and mortality in dairy cows are well documented and cause severe economic problems with a waste of resources and a challenge to the environment. Moreover, the growing public concerns about such production conditions in agriculture can no longer be ignored.

Prediction of detailed blood metabolic profile using milk infrared spectra and machine learning methods in dairy cattle

The adoption of preventive management decisions is crucial to dealing with metabolic impairments in dairy cattle. Various serum metabolites are known to be useful indicators of the health status of cows. In this study, we used milk Fourier-transform mid-infrared (FTIR) spectra and various machine learning (ML) algorithms to develop prediction equations for a panel of 29 blood metabolites, including those related to energy metabolism, liver function/hepatic damage, oxidative stress, inflammation/innate immunity, and minerals. For most traits, the data set comprised observations from 1,204 Holstein-Friesian dairy cows belonging to 5 herds. An exception was represented by β-hydroxybutyrate prediction, which contained observations from 2,701 multibreed cows pertaining to 33 herds. The best predictive model was developed using an automatic ML algorithm that tested various methods, including elastic net, distributed random forest, gradient boosting machine, artificial neural network, and stacking ensemble. These ML predictions were compared with partial least squares regression, the most commonly used method for FTIR prediction of blood traits. Performance of each model was evaluated using 2 cross-validation (CV) scenarios: 5-fold random (CV_r) and herd-out (CV_h). We also tested the best model's ability to classify values precisely in the 2 extreme tails, namely, the 25th (Q25) and 75th (Q75) percentiles (true-positive prediction scenario). Compared with partial least squares regression, ML algorithms achieved more accurate performance. Specifically, elastic net increased the R² value from 5% to 75% for CV_r and 2% to 139% for CV_h, whereas the stacking ensemble increased the R² value from 4% to 70% for CV_r and 4% to 150% for CV_h. Considering the best model, with the CV_r scenario, good prediction accuracies were obtained for glucose (R² = 0.81), urea (R² = 0.73), albumin (R² = 0.75), total reactive oxygen metabolites (R² = 0.79), total thiol groups (R² = 0.76), ceruloplasmin (R² = 0.74), total proteins (R² = 0.81), globulins (R² = 0.87), and Na (R² = 0.72). Good prediction accuracy in classifying extreme values was achieved for glucose (Q25 = 70.8%, Q75 = 69.9%), albumin (Q25 = 72.3%), total reactive oxygen metabolites (Q25 = 75.1%, Q75 = 74%), thiol groups (Q75 = 70.4%), total proteins (Q25 = 72.4%, Q75 = 77.2.%), globulins (Q25 = 74.8%, Q75 = 81.5%), and haptoglobin (Q75 = 74.4%). In conclusion, our study shows that FTIR spectra can be used to predict blood metabolites with relatively good accuracy, depending on trait, and are a promising tool for large-scale monitoring.

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.

Metabolic Profiling in Ruminant Diagnostics

A herd-based approach and interpretative perspective is necessary in using metabolic profile testing in contrast to individual animal disease diagnostics. Metabolic profile testing requires formulating a question to be answered, followed by the appropriate selection of animals for testing. A range of blood analytes and nutrients can be determined with newer biomarkers being developed. Sample collection and handling and herd-based reference criteria adjusted to time relative to parturition are critical for interpretation. The objective of this article is to review the concepts and practical applications of metabolic profile testing in ruminants.

Methane Emission and Metabolic Status in Peak Lactating Dairy Cows and Their Assessment Via Methane Concentration Profile

Ruminant husbandry contributes to global methane (CH4) emissions and beside its negative impact on the environment, enteric CH4 emissions cause a loss of gross energy intake in cows. The study is aimed to estimate CH4 emission and metabolic status in dairy cows via the methane concentration profile as a tool for analyzing the CH4 production pattern. The study included eighteen cows whose enteric CH4 emission was measured during three consecutive days in three periods: 2 hours before (P1), 2–4 hours (P2) and 6–8 hours (P3) after the morning feeding. Based on CH4 enteric emissions, cows were divided into two groups (n=6, respectively): HM (average CH4 concentration: 5430.08 ± 365.92 ppm) and LM (average CH4 concentration: 1351.85 ± 205.20 ppm). Following CH4 measurement, on day 3, venous blood was sampled to determine the indicators of the metabolic status. HM cows had significantly higher average CH4 concentrations, maximum and average CH4 peak amplitude than LM cows in all measuring periods (P1-P3), while the number of CH4 peaks tended to be higher in HM than in LM cows in P2. There were no differences in the maximum and average CH4 peak width and average distance among two CH4 peaks between examined groups of cows. HM cows had significantly higher total protein concentrations and significantly lower total bilirubin and NEFA concentrations than LM cows. In conclusion, HM cows have a greater number of eructations and release more CH4 per eructation than LM cows, hence the differences in metabolic status are most likely related to the differences in their liver function.

Glucose-6-Phosphate Dehydrogenase Activity in Milk May Serve as a Non-Invasive Metabolic Biomarker of Energy Balance in Postpartum Dairy Cows

Negative energy balance (EB) postpartum is associated with adverse outcomes in dairy cows; therefore, non-invasive biomarkers to measure EB are of particular interest. We determined whether specific metabolites, oxidative stress indicators, enzyme activity, and fatty acid (FA) profiles in milk can serve as indicators of negative EB. Forty-two multiparous Holstein dairy cows were divided at calving into 2 groups: one was milked 3 times daily and the other, twice a day for the first 30 d in milk (DIM). Cows were classified retrospectively as being in either negative EB (NEB, n = 19; the mean EB during the first 21 DIM were less than the overall median of -2.8 Mcal/d), or in positive EB (PEB, n = 21; the mean EB was ≥-2.8 Mcal/d). The daily milk yield, feed intake, and body weight were recorded individually. Blood samples were analyzed for metabolites and stress biomarkers. Milk samples were taken twice weekly from 5 to 45 DIM to analyze the milk solids, the FA profile, glucose, glucose-6-P (G6P), G6P-dehydrogenase (G6PDH) activity, malic and lactic acids, malondialdehyde (MDA), and oxygen radical antioxidant capacity (ORAC). The NEB cows produced 10.5% more milk, and consumed 7.6% less dry matter than the PEB cows. The plasma glucose concentration was greater and β-hydroxybutyrate was lower in the PEB vs. the NEB cows. The average concentrations of milk glucose, G6P, malic and lactic acids, and MDA did not differ between groups; however, the G6PDH activity was higher and ORAC tended to be higher in the milk of NEB vs. the PEB cows. The correlation between milk G6PDH activity and EB was significant (r = -0.39). The percentages of oleic acid and total unsaturated FA in milk were higher for the NEB vs. the PEB cows. These findings indicate that G6PDH activity in milk is associated with NEB and that it can serve as a non-invasive candidate biomarker of NEB in postpartum cows, that should be validated in future studies.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

Changes in plasma fatty acids profile in hyperketonemic ewes during early lactation: a preliminary study

The transition from late pregnancy to early lactation is characterized by marked changes in energy balance of dairy ruminants. The mobilization of adipose tissue led to an increase in plasma non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). The aim of this study was to analyze the total plasma fatty acids of healthy and hyperketonemic dairy ewes in early lactation through gas chromatography (GC) to evaluate metabolic alterations. An observational study was used with a cross-sectional experimental design. Forty-six Sarda dairy ewes were enrolled in the immediate post-partum (7 ± 3 days in milk) and divided into two groups according to serum BHB concentration: non-hyperketonemic group (n = 28; BHB < 0.86 mmol/L) and hyperketonemic group (n = 18; BHB ≥ 0.86 mmol/L). A two-way ANOVA included the effect of group and parity was used to evaluate differences in fatty acids (FA) concentrations. A total of 34 plasma FA was assessed using GC. 12 out of 34 FA showed a significant different between groups and 3 out of 34 were tended to significance. Only NEFA concentration and stearic acid were influenced by parity. The results may suggest possible links with lipid metabolism, inflammatory and immune responses in hyperketonemic group. In conclusion, GC represents a useful tool in the study of hyperketonemia and primiparous dairy ewes might show a greater risk to develop this condition.

Alterations in the Milk Metabolome of Dairy Cows Supplemented with Different Levels of Calcium Propionate in Early Lactation

This study aimed to investigate the effects of dietary supplementation with different levels of calcium propionate on the lactation performance, blood energy metabolite parameters, and milk metabolites of dairy cows in early lactation. Thirty-two multiparous Holstein cows were randomly divided into 4 groups, which were orally drenched with 0, 200, 350, and 500 g/d calcium propionate per cow supplemented to a basal diet for 5 weeks from calving. The milk and blood of the dairy cows were sampled and measured every week. The milk samples from the last week were used for the metabolomic analysis via liquid chromatography–mass spectrometry (LC-MS). The results showed that the calcium propionate supplementation quadratically increased the dry matter intake, energy-corrected milk yield, and 4% fat-corrected milk yield; linearly reduced the milk protein and milk lactose concentrations; and quadratically decreased the somatic cell count in the milk. With the increase in calcium propionate, the serum glucose content showed a linear increase, while the serum insulin content showed a quadratic increase. The diets supplemented with calcium propionate quadratically decreased the β-hydroxybutyric acid and linearly decreased the non-esterified fatty acid content in the serum. The metabolomic analysis revealed that eighteen different metabolites were identified in the milk samples of the dairy cows supplemented with calcium propionate at 350 g/d, which decreased the abundance of genistein and uridine 5-monophosphate and increased the abundance of adenosine, uracil, protoporphyrin IX, and sphingomyelin (d 18:1/18:0) compared with the control group. The milk metabolic analysis indicated that the calcium propionate effectively improved the milk synthesis and alleviated the mobilization of adipose tissue and bone calcium. In summary, the calcium propionate could improve the lactation performance and energy status and promote the milk metabolic profile of dairy cows in early lactation. Calcium propionate (350 g/d) is a well-recommended supplement for dairy cows for alleviating negative energy balance and hypocalcemia in early lactation.

Dietary supplementation with calcium propionate could beneficially alter rectal microbial composition of early lactation dairy cows

Dietary supplementation with calcium propionate can effectively alleviate negative energy balance and hypocalcemia of dairy cows in early lactation. The objective of this study was to investigate the effects of calcium propionate feeding levels on the immune function, liver function, and fecal microbial composition of dairy cows in early lactation. Thirty-two multiparous Holstein cows were randomly assigned to four treatments after calving. Treatments were a basal diet plus 0, 200, 350, and 500 g calcium propionate per cow per day throughout a 5-week trial period. Cows were milked three times a day, and blood was sampled to measure immune function and liver function on d 7, 21, and 35. The rectal contents were sampled and collected on d 35 to analyze the microbial composition using 16S rRNA gene sequencing. The results indicated that increasing amounts of calcium propionate did not affected the serum concentrations of total protein, IgG, IgM, and calcium, but the concentrations of albumin and IgA changed quadratically. With the increase of calcium propionate, the activity of serum alanine transaminase and aspartate aminotransferase increased linearly, in contrast, the activity of alkaline phosphatase decreased linearly. Moreover, dietary supplementation with increasing levels of calcium propionate tended to quadratically decrease the relative abundance of Firmicutes while quadratically increased the abundance of Bacteroidetes, and consequently linearly decreased the Firmicutes/Bacteroidetes ratio in the rectal microbiota. Additionally, the supplementation of calcium propionate increased the relative abundances of Ruminococcaceae_UCG-005 and Prevotellaceae_UCG-004 linearly, and Ruminococcaceae_UCG-014 quadratically, but decreased the relative abundances of Lachnospiraceae_NK3A20_group and Family_XIII_AD3011_group quadratically. Compared with the CON group, the calcium propionate supplementation significantly decreased the relative abundance of Acetitomaculum but increased the abundances of Rikenellaceae_RC9_gut_group and Alistipes. In summary, these results suggested that the supplementation of calcium propionate to dairy cows in early lactation could beneficially alter the rectal microbiota.

Oilseed Supplementation Improves Milk Composition and Fatty Acid Profile of Cow Milk: A Meta-Analysis and Meta-Regression

Oilseed supplementation is a strategy to improve milk production and milk composition in dairy cows; however, the response to this approach is inconsistent. Thus, the aim of this study was to evaluate the effect of oilseed supplementation on milk production and milk composition in dairy cows via a meta-analysis and meta-regression. A comprehensive and structured search was performed using the following electronic databases: Google Scholar, Primo-UAEH and PubMed. The response variables were: milk yield (MY), atherogenic index (AI), Σ omega-3 PUFA, Σ omega-6 PUFA, fat, protein, lactose, linoleic acid (LA), linolenic acid (LNA), oleic acid (OA), vaccenic acid (VA), conjugated linoleic acid (CLA), unsaturated fatty acid (UFA) and saturated fatty acid (SFA) contents. The explanatory variables were breed, lactation stage (first, second, and third), oilseed type (linseed, soybean, rapeseed, cottonseed, and sunflower), way (whole, extruded, ground, and roasted), dietary inclusion level, difference of the LA, LNA, OA, forage and NDF of supplemented and control rations, washout period and experimental design. A meta-analysis was performed with the “meta” package of the statistical program R. A meta-regression analysis was applied to explore the sources of heretogeneity. The inclusion of oilseeds in dairy cow rations had a positive effect on CLA (+0.27 g 100 g−1 fatty acids (FA); p < 0.0001), VA (+1.03 g 100 g−1 FA; p < 0.0001), OA (+3.44 g 100 g−1 FA; p < 0.0001), LNA (+0.28 g 100 g−1 FA; p < 0.0001) and UFA (+8.32 g 100 g−1 FA; p < 0.0001), and negative effects on AI (−1.01; p < 0.0001), SFA (−6.51; p < 0.0001), fat milk (−0.11%; p < 0.001) and protein milk (−0.04%; p < 0.007). Fat content was affected by animal breed, lactation stage, type and processing of oilseed and dietary NDF and LA contents. CLA, LA, OA and UFA, desirable FA milk components, were affected by type, processing, and the intake of oilseed; additionally, the concentrations of CLA and VA are affected by washout and design. Oilseed supplementation in dairy cow rations has a positive effect on desirable milk components for human consumption. However, animal response to oilseed supplementation depends on explanatory variables related to experimental design, animal characteristics and the type of oilseed.

In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle

Precision livestock farming technologies are used to monitor animal health and welfare parameters continuously and in real time in order to optimize nutrition and productivity and to detect health issues at an early stage. The possibility of predicting blood metabolites from milk samples obtained during routine milking by means of infrared spectroscopy has become increasingly attractive. We developed, for the first time, prediction equations for a set of blood metabolites using diverse machine learning methods and milk near-infrared spectra collected by the AfiLab instrument. Our dataset was obtained from 385 Holstein Friesian dairy cows. Stacking ensemble and multi-layer feedforward artificial neural network outperformed the other machine learning methods tested, with a reduction in the root mean square error of between 3 and 6% in most blood parameters. We obtained moderate correlations (r) between the observed and predicted phenotypes for γ-glutamyl transferase (r = 0.58), alkaline phosphatase (0.54), haptoglobin (0.66), globulins (0.61), total reactive oxygen metabolites (0.60) and thiol groups (0.57). The AfiLab instrument has strong potential but may not yet be ready to predict the metabolic stress of dairy cows in practice. Further research is needed to find out methods that allow an improvement in accuracy of prediction equations.

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.

Variability of bovine conceptus-related volumes in early pregnancy measured with transrectal three-dimensional ultrasonography

Up until now, bovine fetometry has been entirely based on 2-dimensional ultrasonography. Fetal size is estimated by several linear measurements such as crown-rump length (CRL). However, the advent of 3-dimensional ultrasonography (3D-US) provides in vivo access to the volumes of the fetus and its amniotic sac. The objective of this preliminary observational study was to determine the variability of conceptus-related volumes using transrectal 3D-US in dairy cows and to identify factors affecting them. Furthermore, relationships between the gained measurements and calf birth weight were investigated. In total, 315 Simmental and Holstein-Friesian dairy cows were transrectally examined at d 42 after breeding using a portable ultrasound device (Voluson I, GE Healthcare). Gestational volumes including fetal volume (FV) and amniotic sac volume (ASV) were determined with the software tool VOCAL (Virtual Organ Computer-Aided Analysis, GE Healthcare), whereas amniotic fluid volume (AFV) values were derived from the subtraction of FV from ASV. The CRL was determined by means of 3-dimensional data. The mean values and standard deviations for FV, ASV, AFV, and CRL were 1.47 ± 0.25 cm³, 5.86 ± 1.22 cm³, 4.38 ± 1.02 cm³, and 2.38 ± 0.18 cm, respectively. All gestational volumes and CRL values were affected by breed. In Simmental cattle, larger concepti were observed compared with pregnancies derived from Holstein-Friesian animals. Parity affected only ASV and AFV, with heifers showing greater values than lactating cows. The CRL was positively associated with milk protein content. It was not possible to predict calf weight at birth by using FV, ASV, or AFV; however, tendencies were found for ASV and AFV. The present study was the first to adopt 3D-US volumetry to assess early pregnancy development in dairy cattle. Our results showed that this method could be used successfully to identify minor variations in conceptus growth.

Differentiation of Subclinical Ketosis and Liver Function Test Indices in Adipose Tissues Associated With Hyperketonemia in Postpartum Dairy Cattle

Past studies suggested that during early lactation and the transition period, higher plasma growth hormone (GH) levels in subclinical ketosis (SCK) might involve the initiation of body adipose tissues mobilization, resulting in metabolic disorders in ruminants particularly hyperketonemia. The upregulated GH mRNA expression in adipose tissue may take part in the adipolysis process in SCK-affected cows that paves a way for study further. This study aimed to characterize the plasma levels of GH, β-hydroxybutyrate acid (BHBA) and non-esterified fatty acid (NEFA) and glucose (GLu) in ketotic cows and healthy control (CON) cows; to measure the liver function test (LFT) indices in ketotic and healthy CON cows, and finally the quantitative real-time PCR (qRT-PCR) assay of candidate genes expressed in adipose tissues of ketotic and healthy CON cows during 0 to 7 week postpartum. Three experiments were conducted. Experiment-1 involved 21 Holstein cows weighing 500–600 kg with 2–5 parities. Results showed that GH, BHBA, and NEFA levels in ketotic cows were significantly higher and the GLu level significantly lower. Pearson's correlation analysis revealed a significant positive correlation of GH with BHBA, NEFA, and GLu in ketotic and healthy CON cows. In experiment-2, dynamic monitoring of LFT indices namely, alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyl transpeptidase (GGT), total bilirubin (TBIL), direct bilirubin (DBIL), total protein (TP), albumin (ALB), globulin (GLOB) and albumin/globulin (A/G) were examined. The TBIL, DBIL, and GGT indices were significantly higher in ketotic cows and TP was significantly lower. In experiment-3, mRNA expression levels of GHR and peroxisome-proliferator-activated receptor alpha (PPARα) genes in adipose tissue were significantly upregulated in ketotic cows. However, the mRNA expression of insulin-like growth factor-I (IGF-1), insulin-like growth factor-I receptor (IGF-1R), and sterol regulatory element-binding protein-1c (SREBP-1c) genes in adipose tissue were downregulated in ketotic cows. Our study concluded that during postpartum, higher plasma GH levels in SCK cows might involve the initiation of body adipose tissue mobilization, resulting in hyperketonemia.

Differences of the Plasma Total Lipid Fraction from Pre-Foaling to Post-Foaling Period in Donkeys

Simple Summary

An association between increased metabolic demands and reduced dry matter intake is observed from late gestation to early lactation in donkeys. Furthermore, little is known about the nutritional and energy requirements of this period in animals. Changes in energy metabolism make donkeys more susceptible to metabolic diseases such as hyperlipemia, which is characterized by the mobilization of fatty acids from adipose tissue. A better knowledge of this period could improve animal husbandry, well-being, and health. The aim of this study was to analyze the plasma total lipid fraction, to highlight metabolic changes from the pre-foaling to post-foaling periods, using the gas chromatography technique. Our findings reveal a greater risk of metabolic disease in late gestation to early lactation in donkeys.

Abstract

The period from late gestation to early lactation is characterized by changes in energy metabolism. The aim of the current study was to analyze the plasma total lipid fraction using gas chromatography (GC) analysis, in order to highlight metabolic changes from the pre-foaling to post-foaling periods. Eleven pluriparous dairy jennies (mean age of 11.88 ± 3.79 years) belonging to the Amiata donkey breed were enrolled. Blood sampling was performed at 15 days before foaling (T0), and 15 (T1), 30 (T2), 60 (T3), and 90 (T4) days after foaling, for biochemical and GC analysis. A total of 37 fatty acids were identified in plasma samples: 4 medium chain (MCFA), 24 long chain (LCFA), and 9 very-long chain (VLCFA) fatty acids. Among them, 20 fatty acids changed significantly, and two fatty acid showed a trend toward significance. Furthermore, the LCFA, saturated, unsaturated, monounsaturated, and polyunsaturated ω-3 fatty acids changed significantly during the study period. The main alterations were between T0 and the other time points and appeared to be related to lipid metabolism, cellular structure and function, and inflammatory and immune responses. Our findings reveal greater energy requirements at the end of gestation compared to early lactation in donkeys.

Major Nutritional Metabolic Alterations Influencing the Reproductive System of Postpartum Dairy Cows

Early successful conception of postpartum dairy cows is crucial in determining the optimum reproductive efficiency and profitability in modern dairy farming. Due to the inherent high production potential of modern dairy cows, the extra stress burden of peri-parturient events, and associated endocrine and metabolic changes causes negative energy balance (NEBAL) in postpartum cows. The occurrence of NEBAL is associated with excessive fat mobilization in the form of non-esterified fatty acids (NEFAs). The phenomenon of NEFA mobilization furthers with occurrence of ketosis and fatty liver in postpartum dairy cows. High NEFAs and ketones are negatively associated with health and reproductive processes. An additional burden of hypocalcemia, ruminal acidosis, and high protein metabolism in postpartum cows presents further consequences for health and reproductive performance of postpartum dairy cows. This review intends to comprehend these major nutritional metabolic alterations, their mechanisms of influence on the reproduction process, and relevant mitigation strategies.

Metabogenomic analysis to functionally annotate the regulatory role of long non-coding RNAs in the liver of cows with different nutrient partitioning phenotype

Long non-coding RNAs (lncRNAs) hold gene regulatory potential, but require substantial further functional annotation in livestock. Applying two metabogenomic approaches by combining transcriptomic and metabolomic analyses, we aimed to identify lncRNAs with potential regulatory function for divergent nutrient partitioning of lactating crossbred cows and to establish metabogenomic interaction networks comprising metabolites, genes and lncRNAs. Through correlation analysis of lncRNA expression with transcriptomic and metabolomic data, we unraveled lncRNAs that have a putative regulatory role in energy and lipid metabolism, the urea and tricarboxylic acid cycles, and gluconeogenesis. Especially FGF21, which correlated with a plentitude of differentially expressed genes, differentially abundant metabolites, as well as lncRNAs, suggested itself as a key metabolic regulator. Notably, lncRNAs in close physical proximity to coding-genes as well as lncRNAs with natural antisense transcripts appear to perform a fine-tuning function in gene expression involved in metabolic pathways associated with different nutrient partitioning phenotypes.

Revisiting the Relationships between Fat-to-Protein Ratio in Milk and Energy Balance in Dairy Cows of Different Parities, and at Different Stages of Lactation

Simple Summary

Data from 840 Holstein-Friesian cows (1321 lactations) were used to evaluate trends in fat-to-protein ratios in milk (FPR), and the use of FPR as an indicator of energy balance (EB). The fat-to-protein ratio was negatively related to EB, and this relationship became more negative with increased parity. Regression slopes describing linear relationships between FPR and EB differed over time, although trends were inconsistent. Similarly, ‘High’ FPR scores in milk (≥1.5) were consistently associated with a greater negative energy balance, milk yields, body weight loss, and plasma non-esterified fatty acid concentrations; however, their relationships with dry matter intake did not follow a clear trend. Although FPR can provide an indication of EB at a herd level, this analysis suggests that FPR cannot accurately predict the EB of individual cows.

Abstract

A statistical re-assessment of aggregated individual cow data was conducted to examine trends in fat-to-protein ratio in milk (FPR), and relationships between FPR and energy balance (EB, MJ of ME/day) in Holstein-Friesian dairy cows of different parities, and at different stages of lactation. The data were collected from 27 long-term production trials conducted between 1996 and 2016 at the Agri-Food and Biosciences Institute (AFBI) in Hillsborough, Northern Ireland. In total, 1321 lactations (1 to 20 weeks in milk; WIM), derived from 840 individual cows fed mainly grass silage-based diets, were included in the analysis. The energy balance was calculated daily and then averaged weekly for statistical analyses. Data were further split in 4 wk. intervals, namely, 1–4, 5–8, 9–12, 13–16, and 17–20 WIM, and both partial correlations and linear regressions (mixed models) established between the mean FPR and EB during these periods. Three FPR score categories (‘Low’ FPR, <1.0; ‘Normal’ FPR, 1.0–1.5; ‘High’ FPR, >1.5) were adopted and the performance and EB indicators within each category were compared. As expected, multiparous cows experienced a greater negative EB compared to primiparous cows, due to their higher milk production relative to DMI. Relatively minor differences in milk fat and protein content resulted in large differences in FPR curves. Second lactation cows displayed the lowest weekly FPR, and this trend was aligned with smaller BW losses and lower concentrations of non-esterified fatty acids (NEFA) until at least 8 WIM. Partial correlations between FPR and EB were negative, and ‘greatest’ in early lactation (1–4 WIM; r = −0.38 on average), and gradually decreased as lactation progressed across all parities (17–20 WIM; r = −0.14 on average). With increasing parity, daily EB values tended to become more negative per unit of FPR. In primiparous cows, regression slopes between FPR and EB differed between 1–4 and 5–8 WIM (−54.6 vs. −47.5 MJ of ME/day), while differences in second lactation cows tended towards significance (−57.2 vs. −64.4 MJ of ME/day). Irrespective of the lactation number, after 9–12 WIM, there was a consistent trend for the slope of the linear relationships between FPR and EB to decrease as lactation progressed, with this likely reflecting the decreasing milk nutrient demands of the growing calf. The incidence of ‘High’ FPR scores was greatest during 1–4 WIM, and decreased as lactation progressed. ‘High’ FPR scores were associated with increased energy-corrected milk (ECM) yields across all parities and stages of lactation, and with smaller BW gains and increasing concentrations (log transformed) of blood metabolites (non-esterified fatty acid, NEFA; beta-hydroxybutyrate, BHB) until 8 WIM. Results from the present study highlight the strong relationships between FPR in milk, physiological changes, and EB profiles during early lactation. However, while FPR can provide an indication of EB at a herd level, the large cow-to-cow variation indicates that FPR cannot be used as a robust indicator of EB at an individual cow level.

Nuclear factor erythroid 2-related factor 2 protects bovine mammary epithelial cells against free fatty acid-induced mitochondrial dysfunction in vitro

Bovine mammary epithelial cells undergo an increase in metabolic rate, mitochondrial dysfunction, and oxidative stress after calving. Nuclear factor erythroid 2-related factor 2 (NFE2L2), a master regulator of cellular redox homeostasis, plays crucial roles in the regulation of mitochondrial function. The objective of this study was to investigate the role of NFE2L2 on mitochondrial function in bovine mammary epithelial cells under hyperlipidemic conditions. Three experiments were conducted as follows: (1) the immortalized bovine mammary epithelial cell line MAC-T was treated with various concentrations of free fatty acids (FFA; 0, 0.6, 1.2, or 2.4 mM) for 24 h to induce stress; (2) MAC-T cells were transfected with small interfering RNA targeting NFE2L2 (si-NFE2L2) and scrambled nontarget negative control (si-Control) for 48 h; and (3) MAC-T cells were pretreated with 10 μM sulforaphane (SFN), an activator of NFE2L2, for 24 h followed by treatment with 1.2 mM FFA for an additional 24 h. Results indicated that exogenous FFA challenge induced linear and quadratic increases in concentrations of mitochondrial reactive oxygen species (ROS). Compared with 0 mM FFA, mitochondrial membrane potential, mRNA abundance of oxidative phosphorylation complexes (CO I-V), protein abundance of nuclear respiratory factor 1 (NRF1), peroxisome proliferator-activated receptor γ coactivator 1 α (PGC-1α), mitochondrial transcription factor A (TFAM), and NFE2L2 along with the contents of ATP, mitochondrial DNA (mtDNA), and total mitochondria were greater in the MAC-T challenged with 0.6 mM FFA group, but lower in the 1.2 and 2.4 mM FFA cultures. Knockdown of NFE2L2 via small interfering RNA led to greater mitochondrial ROS content and lower mitochondrial membrane potential along with contents of ATP, mtDNA, and total mitochondria. The SFN pretreatment upregulated protein abundance of NFE2L2 and attenuated the downregulation of NFE2L2 induced by FFA. Pretreatment with SFN attenuated the downregulation induced by FFA of PGC-1α, NRF1, and TFAM protein abundance along with contents of mtDNA and total mitochondria. Furthermore, SFN pretreatment attenuated the upregulation of mitochondrial ROS content, the downregulation of mitochondrial membrane potential, and the decreases in ATP, mtDNA, and mitochondrial content induced by FFA. Overall, data indicated that FFA inhibit NFE2L2, resulting in mitochondrial dysfunction and ROS production in bovine mammary epithelial cells. Thus, NFE2L2 may be a promising therapeutic target against metabolic challenge-driven mitochondrial dysfunction and oxidative stress in bovine mammary epithelial cells.

Different Protein Sources in the Maternal Diet of the Rat during Gestation and Lactation Affect Milk Composition and Male Offspring Development during Adulthood

Protein sources in maternal diet are important for mammary gland differentiation and milk protein; however, few studies have examined the metabolic and cellular adaptations of mothers based on protein source diets during pregnancy and lactation, and leptin concentration in offspring. We evaluated metabolic parameters and maternal key organs and milk components in mothers at the end of lactation, who were fed different sources of proteins. In postnatal day 110 and 250, we studied development parameters and leptin in male offspring. Female rats received a Vegetal (V) or Animal (A) diet during pregnancy and lactation. After weaning, male offspring ate V diet until postnatal day 250, which yielded two groups: Vv and Av. Milk dry, protein and fat were analyzed. Maternal metabolic parameters, leptin, and liver, adipose tissue and mammary gland histological analyses were studied. Body weight, food intake and leptin were analyzed in offspring at two ages. Adipose tissue weight and cells size and liver fat, mammary gland apoptosis, weight, milk protein and leptin were higher in A vs V. Maternal liver and milk dry were lower in A vs V. All offspring parameters were higher in Av vs Vv at postnatal day 110; however, at postnatal day 250, leptin was higher in Av vs Vv. Maternal serum and milk leptin had a positive correlation with offspring serum leptin at both ages. Consumption of animal protein-based diets by mothers during developmental periods affects specific maternal organs and changes milk composition during lactation, leading to a hyperleptinemic phenotype in male offsprings.

The Whole and the Parts—A New Perspective on Production Diseases and Economic Sustainability in Dairy Farming

The levels of production diseases (PD) and the cow replacement rate are high in dairy farming. They indicate excessive production demands on the cow and a poor state of animal welfare. This is the subject of increasing public debate. The purpose of this study was to assess the effect of production diseases on the economic sustainability of dairy farms. The contributions of individual culled cows to the farm’s economic performance were calculated, based on milk recording and accounting data from 32 farms in Germany. Cows were identified as ‘profit cows’ when they reached their individual ‘break-even point’. Data from milk recordings (yield and indicators for PD) were used to cluster farms by means of a principal component and a cluster analysis. The analysis revealed five clusters of farms. The average proportion of profit cows was 57.5%, 55.6%, 44.1%, 29.4% and 19.5%. Clusters characterized by a high proportion of cows with metabolic problems and high culling and mortality rates had lower proportions of profit cows, somewhat irrespective of the average milk-yield per cow. Changing the perception of PD from considering it as collateral damage to a threat to the farms’ economic viability might foster change processes to reduce production diseases.

Invited Review: Ketosis Diagnosis and Monitoring in High-Producing Dairy Cows

This work reviews the current impact and manifestation of ketosis (hyperketonemia) in dairy cattle, emphasizing the practical use of laboratory methods, field tests, and milk data to monitoring this disease. Ketosis is a major issue in high-producing cows, easily reaching a prevalence of 20% during early postpartum when the negative energy balance is well established. Its economic losses, mainly related to decreasing milk yield, fertility, and treatment costs, have been estimated up to €250 per case of ketosis/year, which can double if associated diseases are considered. A deep relationship between subclinical or clinical ketosis and negative energy balance and related production diseases can be observed mainly in the first two months postpartum. Fourier transform infrared spectrometry methods gradually take place in laboratory routine to evaluates body ketones (e.g., beta-hydroxybutyrate) and probably will accurately substitute cowside blood and milk tests at a farm in avenir. Fat to protein ratio and urea in milk are largely evaluated each month in dairy farms indicating animals at risk of hyperketonemia. At preventive levels, other than periodical evaluation of body condition score and controlling modifiable or identifying non-modifiable risk factors, the ruminatory activity assessment during the peripartum seems to be a valuable tool at farms. We conclude that a technological advance progressively takes place to mitigate the effects of these metabolic diseases, which challenge the high-yielding cows.

Milk Fatty Acids Composition Changes According to β-Hydroxybutyrate Concentrations in Ewes during Early Lactation

Simple Summary

Ketosis can occur during the last six weeks of gestation and continue to the early weeks of lactation due to an increase in energy requirement. This condition can cause substantial economic issues because of the decrease in production, the cost of medical management, the loss of the mothers and the lambs. A better knowledge of this disorder and its early diagnosis could make treatment more effective and optimize productivity. The aims of this study were to understand the metabolic status of the early-lactating ewes and to identify biomarkers for precocious diagnosis of subclinical ketosis using gas chromatographic technique. Different relationships were found between milk fatty acids and metabolic status of the ewes. Furthermore, 8 potential biomarkers were determined.

Abstract

Ketosis is a metabolic disease of pregnant and lactating ewes linked to a negative energy balance which can cause different economic losses. The aims of this study were to understand the metabolic status of the early-lactating ewes and to identify biomarkers for early diagnosis of subclinical ketosis. Forty-six Sarda ewes were selected in the immediate post-partum for the collection of the biological samples. A blood sample from the jugular vein was used to determine β-Hydroxybutyrate (BHB) concentrations. Animals were divided into two groups: BHB 0 or healthy group (n = 28) with BHB concentration < 0.86 mmol/L; and BHB 1 or subclinical ketosis (n = 18) with a BHB concentration ≥ 0.86 mmol/L. Ten mL of pool milk were collected at the morning milking for the analyses. The concentration of 34 milk fatty acids was evaluated using gas chromatography. Two biochemical parameters and 11 milk fatty acids of the total lipid fraction presented a p-value ≤ 0.05. The study revealed different relationships with tricarboxylic acid cycle, blood flows, immune and nervous systems, cell functions, inflammatory response, and oxidative stress status. Eight parameters were significant for the receiver operating characteristic (ROC) analysis with an area under the curve greater than 0.70.

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces, Alveolar Gas, and Stable Air

Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC-MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4-5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.

Milk Beta-Hydroxybutyrate and Fat to Protein Ratio Patterns during the First Five Months of Lactation in Holstein Dairy Cows Presenting Treated Left Displaced Abomasum and Other Post-Partum Diseases

Simple Summary

This study aimed to evaluate the 5-month pattern (averaged days in milk; DIM1 to 5) of milk beta-hydroxybutyrate (BHB) concentration and fat to protein content (F:P) ratio patterns from Holstein cows presenting postpartum diseases which have been treated. Cows presenting left displaced abomasum (LDA) and concomitant diseases within the first three months had higher concentrations of BHB than the control group (cows without diseases) in the first, but not in the second month postpartum. The F:P ratio had a similar evolution pattern also for DIM2. Animals with LDA were four to six times more likely to have a F:P ratio ≥ 1.29 than the control group during DIM1 and DIM2, respectively. Moderate and high correlations were also observed between the F:P ratio and BHB in DIM1 and DIM2, respectively. We concluded that animals suffering from LDA within the first three months postpartum have a significantly higher concentration of BHB and F:P ratio in milk than cows without postpartum diseases during the first two months. The treated cows with LDA quickly recovered normal levels, up to DIM3. The F:P ratio is a viable and economic indicator, mainly between the first two months postpartum, to estimate BHB concentration and energy balance in cows presenting LDA and in recovery.

Abstract

The main objective of the present study was to evaluate the beta-hydroxybutyrate (BHB) and fat to protein content (F:P) ratio patterns in the milk of Holstein cows with postpartum diseases throughout the first five months of lactation. This prospective study was performed at Vestjyske Dyrlaeger ApS (Nørre Nebel, Denmark). The milk fat, protein, and BHB were evaluated in the Danish Eurofins laboratory according to the monthly averaged days in milk (DIM1 to 5). According to clinical records, five groups were formed: A (control group; cows without diseases; n = 32), B (cows with left displaced abomasum -LDA- and concomitant diseases; n = 25); C (cows with other diseases up to DIM3; n = 13); D (cows with foot disorders up to DIM3; n = 26); and E (cows with disease manifestations in DIM4 and DIM5; n = 26). All the sick cows were treated after diagnosis, and laparoscopy was performed on cows with LDA. In group B, a higher concentration of BHB (0.18 ± 0.02 mmol/L; p < 0.001) was observed than in the control group (0.07 ± 0.02 mmol/L; p < 0.001) in DIM1, presenting an odds ratio (OR) = 8.9. In all groups, BHB decreased to 0.03–0.05 mmol/L (p < 0.05) since DIM3. The F:P ratio was higher in group B (1.77 ± 0.07) than in group A (1.32 ± 0.06; p < 0.05) in DIM1. A similar profile is observed in DIM2. It was observed that animals in group B were four to six times more likely to have a F:P ratio ≥1.29 during DIM1 (OR = 4.0; 95% CI:1.3–14.4; p = 0.01) and DIM2 (OR = 5.9; 95% CI %:1.9–21.9; p < 0.01), than cows in group A. There were also moderate and high correlations between the F:P ratio and the BHB for DIM1 (r = 0.57; r² = 0.33; RSD = 0.09; p < 0.001) and DIM2 (r = 0.78; r² = 0.60; RSD = 0.07; p < 0.001), respectively. We concluded that animals affected by LDA in the postpartum period have a higher concentration of BHB in milk in DIM1 and all treated animals quickly recover BHB levels up to DIM3. The F:P ratio is a viable and economic indicator, mainly in DIM1 and DIM2, to estimate BHB concentration and energy balance in cows with LDA and other postpartum diseases.

Transcription factor EB (TFEB)-mediated autophagy protects bovine mammary epithelial cells against H2O2-induced oxidative damage in vitro

Background

Bovine mammary epithelial cells after calving undergo serious metabolic challenges and oxidative stress both of which could compromise autophagy. Transcription factor EB (TFEB)-mediated autophagy is an important cytoprotective mechanism against oxidative stress. However, effects of TFEB-mediated autophagy on the oxidative stress of bovine mammary epithelial cells remain unknown. Therefore, the main aim of the study was to investigate the role of TFEB-mediated autophagy in bovine mammary epithelial cells experiencing oxidative stress.

Results

H₂O₂ challenge of the bovine mammary epithelial cell MAC-T increased protein abundance of LC3-II, increased number of autophagosomes and autolysosomes while decreased protein abundance of p62. Inhibition of autophagy via bafilomycin A1 aggravated H₂O₂-induced reactive oxygen species (ROS) accumulation and apoptosis in MAC-T cells. Furthermore, H₂O₂ treatment triggered the translocation of TFEB into the nucleus. Knockdown of TFEB by siRNA reversed the effect of H₂O₂ on protein abundance of LC3-II and p62 as well as the number of autophagosomes and autolysosomes. Overexpression of TFEB activated autophagy and attenuated H₂O₂-induced ROS accumulation. Furthermore, TFEB overexpression attenuated H₂O₂-induced apoptosis by downregulating the caspase apoptotic pathway.

Conclusions

Our results indicate that activation of TFEB mediated autophagy alleviates H₂O₂-induced oxidative damage by reducing ROS accumulation and inhibiting caspase-dependent apoptosis.

Relationships between energy balance during early lactation and cow performance, blood metabolites, and fertility: A meta-analysis of individual cow data

This study was designed to contribute to the understanding of the relationships between energy balance (EB) in early lactation [4 to 21 d in milk (DIM)] and fertility traits [interval to start of luteal activity (SLA), interval to first observed heat (FOH), and conception to first artificial insemination (AI)], and their associated relationships with cow performance and blood metabolites between 4 to 150 DIM. Individual cow data (488 primiparous and 1,020 multiparous lactations) from 27 experiments was analyzed. Data on cow performance, EB (on a metabolizable energy basis), and fertility traits were available for all cows, whereas milk progesterone data (to determine SLA) and periodic blood metabolite data were available for 1,042 and 1,055 lactations, respectively. Data from primiparous and multiparous cows were analyzed separately, with the data sets for the 2 parity groups divided into quartiles (Q1-Q4) according to the average EB during 4 to 21 DIM (EB range for Q1 to Q4: primiparous, -120 to -49, -49 to -24, -24 to -3, and -3 to 92 MJ/d, respectively: multiparous, -191 to -79, -79 to -48, -48 to -22, and -22 to 93 MJ/d, respectively). Differences between EB quartiles for production and fertility traits were compared. In early lactation (4 to 21 DIM), moving from Q1 to Q4 mean DMI and metabolizable energy intake increased whereas mean ECM decreased. During the same period, moving from Q1 to Q4 milk fat content, milk fat-to-protein ratio, and plasma nonesterified fatty acid and β-hydroxybutyrate concentrations decreased, whereas milk protein content and plasma glucose concentrations increased in both primiparous and multiparous cows. When examined over the entire experimental period (4 to 150 DIM), many of the trends in intakes and milk production remained, although the magnitude of the difference between quartiles was much reduced, whereas milk fat content did not differ between quartiles in primiparous cows. The percentage of cows with FOH before 42 DIM increased from Q1 to Q4 (from 46 to 72% in primiparous cows, and from 41 to 58% in multiparous cows). Interval from calving to SLA and to FOH decreased with increasing EB during 4 to 21 DIM, with these occurring 9.8 and 10.2 d earlier, respectively, in Q4 compared with Q1 (primiparous cows), and 7.4 and 5.9 d earlier, respectively, in Q4 compared with Q1 (multiparous cows). For each 10 MJ/d decrease in mean EB during 4 to 21 DIM, FOH was delayed by 1.2 and 0.8 d in primiparous and multiparous cows, respectively. However, neither days to first AI nor the percentage of cows that conceived to first AI were affected by daily EB during 4 to 21 DIM in either primiparous or multiparous cows, and this is likely to reflect a return to a less metabolically stressed status at the time of AI. These results demonstrate that interval from calving to SLA and to FOH were reduced with increasing EB in early lactation, whereas early lactation EB had no effect on conception to the first service.

Oxidative stress, NF-κB signaling, NLRP3 inflammasome, and caspase apoptotic pathways are activated in mammary gland of ketotic Holstein cows

Ketosis is a serious metabolic disorder characterized by systemic and hepatic oxidative stress, inflammation, and apoptosis, as well as reduced milk yield. Because of the paucity of data on mammary responses during ketosis, the aim of this study was to evaluate alterations in oxidative stress, NF-κB signaling, NLRP3 inflammasome, and caspase apoptotic pathways in mammary gland of dairy cows with ketosis. Blood, mammary gland tissue, and milk samples were collected from healthy cows [Control, blood concentration of β-hydroxybutyrate (BHB) <0.6 mM, n = 10] and cows with subclinical ketosis (SCK, blood concentration of BHB >1.2 mM and <3 mM, n = 10) or clinical ketosis (CK, blood concentration of BHB >3 mM, n = 10) at median 8 d in milk (range = 6-12). Compared with Control, serum concentration of glucose was lower (3.91 vs. 2.86 or 2.12 mM) in cows with SCK or CK, whereas concentrations of fatty acids (0.25 vs. 0.57 or 1.09 mM) and BHB (0.42 vs. 1.81 or 3.85 mM) were greater. Compared with Control, the percentage of milk fat was greater in cows with SCK or CK. In contrast, the percentage of milk protein was lower in cows with SCK or CK. We detected no differences in milk lactose content across groups. Compared with Control, activities of glutathione peroxidase, superoxide dismutase, and catalase were lower in mammary gland tissue of cows with SCK or CK. In contrast, concentrations of hydrogen peroxide and malondialdehyde were greater in cows with SCK or CK. Compared with Control, mRNA abundances of TNFA, IL6, and IL1B were greater in mammary tissues of cows with SCK or CK. In addition, activity of IKKβ and the ratio of phosphorylated inhibitor of κBα to IκBα, and of phosphorylated NF-κB p65 to NF-κB p65, were also greater in mammary tissues of cows with SCK or CK. Subclinical or clinical ketosis also led to greater activity of caspase 1 and protein abundance of caspase 1, NLRP3, Bax, caspase 3, and caspase 9. In contrast, abundance of the antiapoptotic protein was lower in SCK or CK cows. The data indicate that the mammary gland of SKC or CK cows undergoes severe oxidative stress, inflammation, and cell death.

Gain and loss of subcutaneous and abdominal adipose tissue depot mass of German Holstein dairy cows with different body conditions during the transition period

Subcutaneous adipose tissue (SCAT) and abdominal adipose tissue (AAT) depots are mobilized during the fresh cow period (FCP) and early lactation period (ELP) to counteract the negative energy balance (NEB). Earlier studies suggested that fat depots contribute differently to lipomobilization and may vary in functionality. Differences between the adipose depots might influence the development of metabolic disorders. Thus, the gain and loss of subcutaneous and abdominal adipose depot masses in Holstein cows with lower and higher body condition (mean body condition scores: 3.48 and 3.87, respectively) were compared in the period from d -42 to d 70 relative to parturition in this study. Animals of the 2 experimental groups represented adequately conditioned and overconditioned cows. Estimated depot mass (eDM) of SCAT, AAT, retroperitoneal, omental, and mesenteric adipose depots of 31 pluriparous German Holstein cows were determined via ultrasonography at d -42, 7, 28, and 70 relative to parturition. The cows were grouped according to the eDM of SCAT on d -42 [low body condition (LBC) group: n = 16, mean eDM 8.6 kg; high body condition (HBC) group: n = 15, mean eDM 15.6 kg]. Average daily change (prepartum gain and postpartum loss) in depot masses during dry period (DP; from d -42 to d 7), FCP (d 7 to d 28), and ELP (d 28 to d 70) were calculated and daily dry matter intake and lactation performance recorded. Cows of this study stored about 2 to 3 times more fat in AAT than in SCAT depots. After parturition, on average more adipose tissue mass was lost from the AAT than the SCAT depot (0.23 kg/d vs. 0.14 kg/d). Cows with high compared with low body condition had similar gains in AAT (0.33 kg/d) and SCAT (0.14 kg/d) masses during the DP but mobilized significantly more adipose tissue mass from both depots after calving (AAT, HBC vs. LBC: 0.30 vs. 0.17 kg/d; SCAT, HBC vs. LBC: 0.19 vs. 0.10 kg/d). Correlation analysis indicated a functional disparity between AAT and SCAT. In the case of AAT (R² = 0.36), the higher the gain in adipose mass during DP, the higher the loss in FCP, but this was not the case for SCAT. During FCP, a greater NEB resulted in greater loss of mass from SCAT (R² = 0.18). In turn, greater mobilization of SCAT mass led to a higher calculated feed efficiency (R² = 0.18). However, AAT showed no such correlations. On the other hand, during ELP, loss of both SCAT and AAT mass correlated positively with feed efficiency (R² = 0.35 and 0.33, respectively). The results indicate that feed efficiency may not be an adequate criterion for performance evaluation in cows during NEB. Greater knowledge of functional disparities between AAT and SCAT depots may improve our understanding of excessive lipomobilization and its consequences for metabolic health and performance of dairy cows during the transition period.

Ovarian function and the establishment and maintenance of pregnancy in dairy cows with and without evidence of postpartum uterine disease

Uterine disease early postpartum reduces fertility during the breeding period. One potential mechanism involves the reduced functional capacity of the uterus to support pregnancy. A second potential mechanism involves damage to ovarian follicles associated with systemic inflammation. We categorized lactating Holstein cows into healthy (n = 63) and diseased (n = 39) uterus groups based on the percentage of polymorphonuclear neutrophils in the uterine lumen during the second and third month postpartum and evaluated the functionality of their ovaries and their capacity to establish and maintain pregnancy. Cows were enrolled in a timed artificial insemination protocol (Presynch Ovsynch) so that the first artificial insemination was approximately 75 d postpartum. Ovarian follicles and corpora lutea were counted and measured using transrectal ultrasound, ovulatory responses were assessed, and luteal phase progesterone concentrations were measured. Pregnancy was detected on d 18, 20, 22, 25, 32, and 45 through chemical (d 18 to 25) or ultrasonographic methods (d 32 and 45). The percentage of cows ovulating during the Presynch period; the number, diameter, and ovulatory capacity of follicles during the Ovsynch period; and plasma progesterone concentrations following ovulation were similar for healthy and diseased cows. The initial period of pregnancy establishment (d 18 to 22) appeared to be unaffected by disease because a similar percentage of healthy and diseased cows were pregnant during this period. Embryonic loss occurred in both healthy and diseased cows after d 22. Based on a relatively small number of pregnancies (n = 30 healthy and n = 17 diseased), the cumulative embryonic loss after d 22 was greater in diseased compared with healthy cows. In short, uterine disease as defined in this study did not affect cyclicity, ovarian follicular growth, or plasma progesterone concentrations. Percentages of healthy and diseased cows that were pregnant were similar from d 18 to 22 after artificial insemination. Greater embryonic loss was observed after d 22 in diseased compared with healthy cows, but this observation was based on a small number of pregnancies and should be studied further in larger trials with greater statistical power.

Metabolic profile according to the parity and stage of lactation of high-performance Holstein-Friesian cows

Objective

The aim of the study was to determine the effect of parity and the stage of lactation on the metabolic profile of cows based on the basic chemical milk components and the blood parameters.

Methods

The study material consisted of high-yielding Holstein-Friesian cows. In total, 473 cows were examined. According to the parity, cows were divided into four groups: primiparous (P), and multiparous in the second (M2), in the third (M3), and in subsequent lactations (M4). The feeding of cows was based on total mixed ration (TMR) ad libitum. Milk and blood samples were collected individually from each cow three times per standard lactation period.

Results

Greater exacerbation of changes in the dynamics of the blood plasma parameters examined was proved for multiparous cows. The highest value of β-hydroxybutyrate acid (0.946 mmol/L) was found for multiparous cows from group M3 at the beginning of lactation. However, it was still in the normal range. The results showed aspartate aminotransferase, and gamma-glutamyl transferase (GGT) activities in dairy cows during lactation had significant variations taking in to account stage of lactation. The highest activity of GGT was found in the group of the oldest cows and measured from 26.36 U/L at the beginning of lactation to 48.75 U/L at the end of the lactation period.

Conclusion

The time-related changes in the concentrations of the biochemical parameters described differ markedly among lactating cows, though the housing conditions on the research dairy farm are highly standardised. This indicates that the ability to cope with metabolic stress is mainly affected by the individual predispositions of cows and feed nutrient supply in different stage of lactation. Especially, the feed nutrient supply (in net energy for lactation), which was the best in TMR 1 in comparison TMR 3.