Association of residual feed intake with peripartal ruminal microbiome and milk fatty acid composition during early lactation in Holstein dairy cows.

Residual feed intake (RFI) is a moderately heritable trait of feed efficiency in dairy cows. The main objective of the present study was to assess potential differences in the ruminal microbiome, milk fatty acid (FA) composition, and plasma concentrations of glucose, nonesterified fatty acids (NEFA), and ß-hydroxybutyrate between the most (M-EFF) and the least efficient (L-EFF) dairy cows during early lactation. Forty-seven multiparous Holstein dairy cows with daily ad libitum access to a total mixed ration from 30 d before calving to 30 d in milk were used. Cows were retrospectively classified into M-EFF (i.e., low RFI, n = 29) and L-EFF (high RFI, n = 18) based on a linear regression model. Ruminal digesta and milk samples were collected from each cow at 15 and 30 d in milk for microbiome analysis using 16S rRNA gene sequencing. Microbiome sequencing data were analyzed with the QIIME 2 platform (http://qiime.org/), whereas the microbiome statistical analyses and visual explorations were performed using the web-based MicrobiomeAnalyst platform. Milk FA composition was measured via gas chromatography-mass spectrometry. The statistical model used in SAS 9.4 (SAS Institute Inc.) included RFI, time, and their interactions as fixed effects. The cor() function in R programming was used to determine Pearson correlations between relative abundance of significant bacteria and milk FA. Overall, daily milk yield did not differ due to RFI and averaged 42 ± 1.6 kg for L-EFF and 43 ± 1.3 kg for M-EFF cows. However, M-EFF cows had lower overall dry matter intake (14.9 ± 0.5 kg/d) compared with L-EFF cows (19.2 ± 0.6 kg/d). No incidence of clinical disease was recorded for cows in the study. Compared with L-EFF, overall glucose concentration was lower, whereas NEFA and ß-hydroxybutyrate concentrations were greater in M-EFF cows. Ruminal digesta from both RFI groups had similar bacterial composition, but differed in the relative abundance of some bacteria. Compared with L-EFF, M-EFF cows had greater relative abundance of Lachnospiraceae, Lachnoclostridium, Papillibacter, Desulfovibrio, Sphaerochaeta, Acetobacter, and Histophilus. In contrast, relative abundance of Bifidobacterium, Ruminiclostridium, Prevotellaceae, and Erysipelotrichaceae bacterium was lower in M-EFF cows. Compared with L-EFF, M-EFF cows had greater proportions of long-chain monounsaturated FA, including 16:1 trans-9, 16:1 cis-9, 17:1 trans-10, 17:1 cis-10, 18:1 cis-9, 18:1 cis-11, whereas proportions of medium-chain saturated and 16:0 were lower in M-EFF. Acetate-producing bacteria (Sphaerochaeta and Acetobacter) were positively and significantly correlated (r ≥ 0.24) with concentrations of 16:1 cis-9 and 17:1 cis-10, whereas Prevotellaceae was significantly and negatively correlated (r = -0.25) with these FA. Butyrate-producing bacterium (Papillibacter) had a significant negative correlation (r = -0.27) with concentration of 15:0. Overall, data suggested that feed-efficient cows have unique profiles of ruminal microbiota, some of which are correlated with concentrations of milk FA during early lactation.

Genome-wide association study and functional analyses for clinical and subclinical ketosis in Holstein cattle.

Ketosis is one of the most frequent metabolic diseases in high-yielding dairy cows and is characterized by high concentrations of ketone bodies in blood, urine, and milk, causing high economic losses. The search for polymorphic genes, whose alleles have different effects on resistance to developing the disease, is of extreme importance to help select less susceptible animals. The aims of this study were to identify genomic regions associated with clinical and subclinical ketosis (ß-hydroxybutyrate concentration) in North American Holstein dairy cattle and to investigate these regions to identify candidate genes and metabolic pathways associated with these traits. To achieve this, a GWAS was performed for 4 traits: clinical ketosis lactation 1, clinical ketosis lactation 2 to 5, subclinical ketosis lactation 1, and subclinical ketosis lactation 2 to 5. The estimated breeding values from 77,277 cows and 7,704 bulls were deregressed and used as pseudophenotypes in the GWAS. The top-20 genomic regions explaining the largest proportion of the genetic variance were investigated for putative genes associated with the traits through functional analyses. Regions of interest were identified on chromosomes 2, 5, and 6 for clinical ketosis lactation 1; 3, 6, and 7 for clinical ketosis lactation 2 to 5; 1, 2, and 12 for subclinical ketosis lactation 1; and 20, 11, and 25 for subclinical ketosis lactation 2 to 5. The highlighted genes potentially related to clinical and subclinical ketosis included ACAT2 and IGF1. Enrichment analysis of the list of candidate genes for clinical and subclinical ketosis showed molecular functions and biological processes involved in fatty acid metabolism, lipid metabolism, and inflammatory response in dairy cattle. Several genomic regions and SNPs related to susceptibility to ketosis in dairy cattle that were previously described in other studies were confirmed. The novel genomic regions identified in this study aid to characterize the most important genes and pathways that explain the susceptibility to clinical and subclinical ketosis in dairy cattle.

Validation of a Gas Chromatography-Mass Spectrometry Method for the Measurement of the Redox State Metabolic Ratios Lactate/Pyruvate and ß-Hydroxybutyrate/Acetoacetate in Biological Samples.

The metabolic ratios lactate/pyruvate and ß-hydroxybutyrate/acetoacetate are considered valuable tools to evaluate the in vivo redox cellular state by estimating the free NAD+/NADH in cytoplasm and mitochondria, respectively. The aim of the current study was to validate a gas-chromatography mass spectrometry method for simultaneous determination of the four metabolites in plasma and liver tissue. The procedure included an o-phenylenediamine microwave-assisted derivatization, followed by liquid-liquid extraction with ethyl acetate and silylation with bis(trimethylsilyl)trifluoroacetamide:trimethylchlorosilane 99:1. The calibration curves presented acceptable linearity, with a limit of quantification of 0.001 mM for pyruvate, ß-hydroxybutyrate and acetoacetate and of 0.01 mM for lactate. The intra-day and inter-day accuracy and precision were within the European Medicines Agency's Guideline specifications. No significant differences were observed in the slope coefficient of three-point standard metabolite-spiked curves in plasma or liver and water, and acceptable recoveries were obtained in the metabolite-spiked samples. Applicability of the method was tested in precision-cut liver rat slices and also in HepG2 cells incubated under different experimental conditions challenging the redox state. In conclusion, the validated method presented good sensitivity, specificity and reproducibility in the quantification of lactate/pyruvate and ß-hydroxybutyrate/acetate metabolites and may be useful in the evaluation of in vivo redox states.

Up-converting phosphor technology-based lateral flow assay for quantitative detection of ß-hydroxybutyrate in biological samples.

In the present study, a novel up-converting phosphor technology-based lateral flow (UPT-LF) assay was developed as a point of care testing method for the rapid and quantitative detection of ß-Hydroxybutyrate (BHB) in milk and serum samples. BHB is one of the most important serum molecular markers not only in ketosis but also for other metabolic disorders in bovines. The developed UPT-LF assay has high sensitivity compared with existing kits in the market for BHB quantification. The detection limit of UPT-BHB- LF assay, with a coefficient of variation (CV) < 10% was 0.01 mM, which is lower than the clinical diagnosis cutoff value of serum BHB (1 mM); while 0.1 mM is the standard level of BHB in milk samples. The relatively good stability and reproducibility of UPT-LF assay with CV<10% results for both serum and milk samples at various storage temperatures demonstrates the superiority of this method and therefore it could be used as a point of care method for the quantitative detection of BHB in the biological samples for veterinary applications. The claimed performance of this assay along with a shorter detection time makes it a viable point-of-care method for the quantitative detection of BHB in the biological samples of veterinary applications.

Comparison of the beta-hydroxybutyrate, glucose, and lactate concentrations derived from postmortem proton magnetic resonance spectroscopy and biochemical analysis for the diagnosis of fatal metabolic disorders.

PURPOSE: The detection and quantification of metabolites relevant for the diagnosis of fatal metabolic disorders by proton magnetic resonance spectroscopy (1H-MRS) was recently demonstrated. This prospective study aimed to compare the concentrations of beta-hydroxybutyrate (BHB), glucose (GLC), and lactate (LAC) derived from both biochemical analyses and 1H-MRS for the diagnosis of fatal metabolic disorders. METHODS: In total, 20 cases with suspected fatal metabolic disorders were included in the study. For the agreement based on thresholds, the concentrations of BHB and GLC in the vitreous humor (VH) from the right vitreous and in cerebrospinal fluid (CSF) from the right lateral ventricle were derived from 1H-MRS and biochemical analyses. The predefined thresholds for pathological elevations were 2.5 mmol/l for BHB and 10 mmol/l for GLC based on the literature. In addition, concentrations of the same metabolites in white matter (WM) tissue from the corona radiata of the right hemisphere were analyzed experimentally using both methods. To enable the biochemical analysis, a dialysate of WM tissue was produced. For all three regions, the LAC concentration was determined by both methods. RESULTS: The conclusive agreement based on thresholds was almost perfect between both methods with only one disagreement in a total of 70 comparisons due to the interference of a ferromagnetic dental brace. The differences in the concentrations between both methods showed high standard deviations. Confidence intervals of the bias not including 0 were found in CSF-GLC (- 3.1 mmol/l), WM-GLC (1.1 mmol/l), and WM-LAC (- 6.5 mmol/l). CONCLUSION: Despite a considerable total error attributable to both methods, MRS derives the same forensic conclusions as conventional biochemical analyses. An adaptation of the protocol to reduce the detected errors and more data are needed for the long-term validation of MRS for the diagnosis of fatal metabolic disorders. The production of WM dialysates cannot be recommended due to high glycolytic loss.

Short communication: Effects of electrochemically activated drinking water on bovine milk production and composition, including chlorate, perchlorate, and fatty acid profile.

The objective of this study was to assess the effects of electrochemically activated drinking water (ECW) on milk chlorate, milk perchlorate, milk iodine, milk composition, milk fatty acid profile, and overall performance of dairy cows. Ten Red Danish cows in mid-lactation (203 ± 31 d in milk; average ± SD) were chosen from these 2 groups for intensive sampling. The treated group drank water with 4 ppm of ECW (29 mg/L of chlorate of Neuthox, Danish Clean Water A/S, Sønderborg, Denmark). The treatment lasted 60 consecutive days, with milk and water sampling on d 0, 30, and 60. Additionally, milk samples from both the control group and treated group were taken on d 90 to assess if any carry-over effect was present. Interactions between period and milk yield and somatic cell for the full group and period and milk fat content and milk urea nitrogen in the selected animals occurred. Milk yield was not significantly affected by treatments. Milk fat, milk fatty acid profile, chlorate, perchlorate, and iodine contents were not significantly different between treatments. Milk urea increased, whereas ß-hydroxybutyrate and somatic cell count decreased significantly in the treated groups. Results showed that at a dosing of 4 ppm of ECW, both chlorate and perchlorate concentrations in milk (<0.002 mg/kg) were low, and no deleterious effects on milk production or milk chemical composition were observed. These data can be of use when assessing the effects of ECW on milk and milk powder chlorate and perchlorate levels and provide a context for assessing the potential for influencing human health under the conditions prevailing on a commercial dairy farm.

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

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

Predictive ability of host genetics and rumen microbiome for subclinical ketosis.

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and ß-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.

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

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

Only few benefits from propylene glycol drench in early lactation for cows identified as physiologically imbalanced based on milk spectra analyses.

The main objective of this study was to test the efficiency of a management system combining metabolic clustering of cows based on Fourier-transform mid-infrared (FT-MIR) spectra of milk and targeted treatment of metabolically imbalanced cows with propylene glycol drench. We hypothesized that cows identified in a metabolically imbalanced status during early lactation were associated with subsequent impaired health, reproduction, and production, and that treatment with propylene glycol treatment would improve health, reproduction, and production relatively more in these cows than in control cows. We completed a prospective, randomized controlled trial with 356 early-lactation cows in 2 private dairy herds in Denmark from December 2017 to April 2018. Milk samples of cows were collected before treatment, from 4 to 9 d in milk, and after treatment, from 22 to 27 d in milk. Milk samples were analyzed using FT-MIR spectroscopy. We also measured 4 milk metabolites (ß-hydroxybutyrate, isocitrate, malate, and glutamate) and fat and protein contents. Based on FT-MIR spectra and cluster analyses, cows were clustered into groups of metabolically imbalanced and healthy cows. Within each group, cows were allocated randomly to treatment with propylene glycol (500 mL for 5 d) or no treatment. We analyzed the effect of the treatment on cow-level variables: metabolic cluster, milk metabolites, fat and protein contents, and fat-to-protein ratio at a milk sampling after the treatment. Furthermore, we analyzed daily milk yield, calving to first service interval, and disease occurrence. Results showed only a few effects of propylene glycol treatment and few interactions between treatment and metabolic clusters. We found no significant main effects of propylene glycol treatment in any of these analyses. A negative effect of the imbalanced metabolic cluster was found for the outcome of calving to first service interval for multiparous cows. In conclusion, we found a longer calving to first service interval in metabolically imbalanced cows, but we were not able to demonstrate overall benefits from the applied detection of cows in imbalanced metabolic status in early lactation and follow-up by treatment with propylene glycol.

Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and ß-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows.

Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood ß-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.

ß-Hydroxybutyrate dehydrogenase decorated MXene nanosheets for the amperometric determination of ß-hydroxybutyrate.

MXene nanosheets of type Ti3C2Tx were modified with ß-hydroxybutyrate dehydrogenase and then used as a biosensor for amperometric sensing of ß-hydroxybutyrate. The MXene and the nanocomposite were characterized by X-ray photoelectron spectroscopy, field-emission scanning electron microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The MXene has a layered structure and proved to be an excellent immobilization matrix providing good compatibility with the enzyme ß-hydroxybutyrate dehydrogenase. The MXene-based biosensor, best operated at a potential of - 0.35 V (vs. Ag/AgCl), displays a wide linear range (0.36 to 17.9 mM), a sensitivity of 0.480 µA mM-1 cm-2, and a low detection limit (45 µM). The biosensor was successfully applied to the determination of ß-hydroxybutyrate in (spiked) real serum samples. Graphical abstract Schematic representation of the synthesis and decoration of Mxene 2D sheets with ß-hydroxybutyrate dehydrogenase for the amperometric determination of ß-hydroxybutyric acid.

The role of the acyl-CoA thioesterase "YciA" in the production of (R)-3-hydroxybutyrate by recombinant Escherichia coli.

Biotechnologically produced (R)-3-hydroxybutyrate is an interesting pre-cursor for antibiotics, vitamins, and other molecules benefitting from enantioselective production. An often-employed pathway for (R)-3-hydroxybutyrate production in recombinant E. coli consists of three-steps: (1) condensation of two acetyl-CoA molecules to acetoacetyl-CoA, (2) reduction of acetoacetyl-CoA to (R)-3-hydroxybutyrate-CoA, and (3) hydrolysis of (R)-3-hydroxybutyrate-CoA to (R)-3-hydroxybutyrate by thioesterase. Whereas for the first two steps, many proven heterologous candidate genes exist, the role of either endogenous or heterologous thioesterases is less defined. This study investigates the contribution of four native thioesterases (TesA, TesB, YciA, and FadM) to (R)-3-hydroxybutyrate production by engineered E. coli AF1000 containing a thiolase and reductase from Halomonas boliviensis. Deletion of yciA decreased the (R)-3-hydroxybutyrate yield by 43%, whereas deletion of tesB and fadM resulted in only minor decreases. Overexpression of yciA resulted in doubling of (R)-3-hydroxybutyrate titer, productivity, and yield in batch cultures. Together with overexpression of glucose-6-phosphate dehydrogenase, this resulted in a 2.7-fold increase in the final (R)-3-hydroxybutyrate concentration in batch cultivations and in a final (R)-3-hydroxybutyrate titer of 14.3 g L-1 in fed-batch cultures. The positive impact of yciA overexpression in this study, which is opposite to previous results where thioesterase was preceded by enzymes originating from different hosts or where (S)-3-hydroxybutyryl-CoA was the substrate, shows the importance of evaluating thioesterases within a specific pathway and in strains and cultivation conditions able to achieve significant product titers. While directly relevant for (R)-3-hydroxybutyrate production, these findings also contribute to pathway improvement or decreased by-product formation for other acyl-CoA-derived products.

Prediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers.

The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and ß-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immunogamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbalanced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the "balanced" group (n = 43) and were compared with cows in what was referred to as the "other balanced" group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the "imbalanced" group (n = 19) and compared with cows in what was referred to as the "other imbalanced" group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids and BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-ß-d-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, parity, milk yield features) were used to create predictive models for the metabolic clusters. Accuracy for prediction of balanced (80%) and imbalanced (88%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows.

Postruminal infusion of calcium gluconate increases milk fat production and alters fecal volatile fatty acid profile in lactating dairy cows.

Gluconic acid is a carboxylic acid naturally occurring in plants and honey. In nonruminant animals, gluconic acid has been shown to increase gastrointestinal butyrate concentrations and improve growth performance, but a ruminant application remains undescribed. This experiment examined the effects of postruminal calcium gluconate (CaG) on milk production, fecal volatile fatty acid concentrations, and plasma metabolite concentrations in lactating dairy cows. Six rumen cannulated multiparous Holstein cows (60 ± 6 d in milk) were randomly assigned to 6 treatment sequences within a 6 × 6 Latin square design in which each experimental period consisted of 5 d of continuous postruminal infusion followed by a 2 d wash-out period. Test treatments included a negative control (CON; 0.90% NaCl wt/vol), positive control (Na-butyrate, 135 g/d), and 4 doses of CaG (44, 93, 140, and 187 g/d). Cows received a total mixed ration (31% corn silage, 28% alfalfa silage, 5% hay, 36% concentrate) with dry matter intake fixed (25.3 ± 1.7 kg/d) throughout the experiment. On d 5 of each infusion period, samples of milk, feces, and blood were collected from each animal. Calcium gluconate treatments increased milk fat concentration, and a tendency was observed for increased milk fat yield and energy-corrected milk yield above levels achieved by CON, with maximal treatment responses of 4.43% (CON 3.81%), 2.089 kg/d (CON 1.760 kg/d), and 51.8 kg/d (CON 47.1 kg/d), respectively. Concentrations of iso-butyric acid in feces were greater in cows infused with CaG (13.3 µmol/g) treatments compared with CON (9.7 µmol/g). Arterial concentrations of glucose and nonesterified fatty acids were lower (glucose: CaG 2.98 mmol/L, CON 3.29 mmol/L and nonesterified fatty acids: CaG 0.130 mmol/L vs. 0.148 mmol/L) and ß-hydroxybutyrate higher (CaG 1.703 vs. CON 0.812) in cows infused with CaG than CON. Together, these results suggest that postruminal infusion of CaG may alter metabolic mechanisms to support a milk fat production response.

Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early-lactation Holstein and Jersey cows.

Although cowside testing strategies for diagnosing hyperketonemia (HYK) are available, many are labor intensive and costly, and some lack sufficient accuracy. Predicting milk ketone bodies by Fourier transform infrared spectrometry during routine milk sampling may offer a more practical monitoring strategy. The objectives of this study were to (1) develop linear and logistic regression models using all available test-day milk and performance variables for predicting HYK and (2) compare prediction methods (Fourier transform infrared milk ketone bodies, linear regression models, and logistic regression models) to determine which is the most predictive of HYK. Given the data available, a secondary objective was to evaluate differences in test-day milk and performance variables (continuous measurements) between Holsteins and Jerseys and between cows with or without HYK within breed. Blood samples were collected on the same day as milk sampling from 658 Holstein and 468 Jersey cows between 5 and 20 d in milk (DIM). Diagnosis of HYK was at a serum ß-hydroxybutyrate (BHB) concentration ≥1.2 mmol/L. Concentrations of milk BHB and acetone were predicted by Fourier transform infrared spectrometry (Foss Analytical, Hillerød, Denmark). Thresholds of milk BHB and acetone were tested for diagnostic accuracy, and logistic models were built from continuous variables to predict HYK in primiparous and multiparous cows within breed. Linear models were constructed from continuous variables for primiparous and multiparous cows within breed that were 5 to 11 DIM or 12 to 20 DIM. Milk ketone body thresholds diagnosed HYK with 64.0 to 92.9% accuracy in Holsteins and 59.1 to 86.6% accuracy in Jerseys. Logistic models predicted HYK with 82.6 to 97.3% accuracy. Internally cross-validated multiple linear regression models diagnosed HYK of Holstein cows with 97.8% accuracy for primiparous and 83.3% accuracy for multiparous cows. Accuracy of Jersey models was 81.3% in primiparous and 83.4% in multiparous cows. These results suggest that predicting serum BHB from continuous test-day milk and performance variables could serve as a valuable diagnostic tool for monitoring HYK in Holstein and Jersey herds.

ß-Hydroxybutyrate elevation as a compensatory response against oxidative stress in cardiomyocytes.

Recent studies have shown that the ketone body ß-hydroxybutyrate (ßOHB) acts not only as a carrier of energy but also as a signaling molecule that has a role in diverse cellular functions. Circulating levels of ketone bodies have been previously reported to be increased in patients with congestive heart failure (HF). In this study, we investigated regulatory mechanism and pathophysiological role of ßOHB in HF. First, we revealed that ßOHB level was elevated in failing hearts, but not in blood, using pressure-overloaded mice. We also measured cellular ßOHB levels in both cardiomyocytes and non-cardiomyocytes stimulated with or without H2O2 and revealed that increased myocardial ßOHB was derived from cardiomyocytes but not non-cardiomyocytes under pathological states. Next, we sought to elucidate the mechanisms of myocardial ßOHB elevation and its implication under pathological states. The gene and protein expression levels of CoA transferase (SCOT), a key enzyme involved in ketone body oxidation, was decreased in failing hearts. In cardiomyocytes, H2O2 stimulation caused ßOHB accumulation concomitantly with SCOT downregulation, implying that the accumulation of myocardial ßOHB occurs because of the decline in its utilization. Finally, we checked the effects of ßOHB on cardiomyocytes under oxidative stress. We found that ßOHB induced FOXO3a, an oxidative stress resistance gene, and its target enzyme, SOD2 and catalase. Consequently, ßOHB attenuated reactive oxygen species production and alleviated apoptosis induced by oxidative stress. It has been reported that hyperadrenergic state in HF boost lipolysis and result in elevation of circulating free fatty acids, which can lead hepatic ketogenesis for energy metabolism alteration. The present findings suggest that the accumulation of ßOHB also occurs as a compensatory response against oxidative stress in failing hearts.

Prevalence of ketosis, ketonuria, and ketoacidosis during liberal glycemic control in critically ill patients with diabetes: an observational study.

BACKGROUND: It is uncertain whether liberal glucose control in critically ill diabetic patients leads to increased ketone production and ketoacidosis. Therefore, we aimed to assess the prevalence of ketosis, ketonuria and ketoacidosis in critically ill diabetic patients treated in accordance with a liberal glycemic control protocol. METHODS: We performed a prospective observational cohort study of 60 critically ill diabetic patients with blood and/or urine ketone bodies tested in ICU. All patients were treated according to a liberal glucose protocol targeting a blood glucose level (BGL) between 10 and 14 mmol/l in a single tertiary intensive care unit in Australia. We measured quantitative bedside blood 3-beta-hydroxybutyrate (ß-OHB) and semi-quantitative urine ketones on ICU admission and daily during ICU stay, for a maximum of 10 consecutive days. RESULTS: Median blood ß-OHB level on admission was 0.3 (0.1, 0.8) mmol/l. Ketoacidosis was rare (3 %), but some level of ketosis (ß-OHB ≥0.6 mmol/l) was found in 38 patients (63 %) early during their ICU stay. However, there was no significant difference in prevalence or severity of ketonemia and ketonuria among patients with BGL above (permissive hyperglycemia) or below 10 mmol/l. On multivariable linear regression analysis there was no association between blood ketone levels and BGL, HbA1c, lactate levels, hematocrit, catecholamine infusion or APACHE III score. In contrast, blood ketone levels tended to be higher after cardiopulmonary bypass surgery (P = 0.06). CONCLUSIONS: Liberal glycemic control in critically ill diabetic patients does not appear to be associated with a high prevalence of ketoacidosis or ketonemia. Moreover, ketosis is typically present on admission and resolves rapidly. Finally, cardiopulmonary bypass surgery may be an important trigger of ketone body production. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ( ACTRN12615000216516 ; trial registration date 5 March 2015).

Development of Fourier transform mid-infrared calibrations to predict acetone, ß-hydroxybutyrate, and citrate contents in bovine milk through a European dairy network.

To manage negative energy balance and ketosis in dairy farms, rapid and cost-effective detection is needed. Among the milk biomarkers that could be useful for this purpose, acetone and ß-hydroxybutyrate (BHB) have been proved as molecules of interest regarding ketosis and citrate was recently identified as an early indicator of negative energy balance. Because Fourier transform mid-infrared spectrometry can provide rapid and cost-effective predictions of milk composition, the objective of this study was to evaluate the ability of this technology to predict these biomarkers in milk. Milk samples were collected in commercial and experimental farms in Luxembourg, France, and Germany. Acetone, BHB, and citrate contents were determined by flow injection analysis. Milk mid-infrared spectra were recorded and standardized for all samples. After edits, a total of 548 samples were used in the calibration and validation data sets for acetone, 558 for BHB, and 506 for citrate. Acetone content ranged from 0.020 to 3.355mmol/L with an average of 0.103mmol/L; BHB content ranged from 0.045 to 1.596mmol/L with an average of 0.215mmol/L; and citrate content ranged from 3.88 to 16.12mmol/L with an average of 9.04mmol/L. Acetone and BHB contents were log-transformed and a part of the samples with low values was randomly excluded to approach a normal distribution. The 3 edited data sets were then randomly divided into a calibration data set (3/4 of the samples) and a validation data set (1/4 of the samples). Prediction equations were developed using partial least square regression. The coefficient of determination (R(2)) of cross-validation was 0.73 for acetone, 0.71 for BHB, and 0.90 for citrate with root mean square error of 0.248, 0.109, and 0.70mmol/L, respectively. Finally, the external validation was performed and R(2) obtained were 0.67 for acetone, 0.63 for BHB, and 0.86 for citrate, with respective root mean square error of validation of 0.196, 0.083, and 0.76mmol/L. Although the practical usefulness of the equations developed should be further verified with other field data, results from this study demonstrated the potential of Fourier transform mid-infrared spectrometry to predict citrate content with good accuracy and to supply indicative contents of BHB and acetone in milk, thereby providing rapid and cost-effective tools to manage ketosis and negative energy balance in dairy farms.

Effect of postpartum propylene glycol allocation to over-conditioned Holstein cows on concentrations of milk metabolites.

The objective of the study was to investigate the effect of propylene glycol (PG) allocation on concentrations of milk metabolites with potential use as indicators of glucogenic status in high yielding postpartum dairy cows. At time of calving, nine ruminally cannulated Holstein cows were randomly assigned to ruminal dosing of 500 g/d tap water (CON, n = 4) or 500 g/d PG (PPG, n = 5). The PG was given with the morning feeding week 1-4 postpartum (treatment period) and cows were further followed during week 5-8 postpartum (follow-up period). All cows were fed the same postpartum diet. Milk samples were obtained at each milking (3 times/d) in the treatment period, and at morning milking during the follow-up period. Weekly blood samples were obtained from -4 to +8 weeks relative to calving and daily blood samples from -7 until +7 d relative to calving. The main effect of PG allocation was an increased glucogenic status, e.g. visualised by a prompt marked increase in blood fructosamine. During the treatment period, milk concentration of free glucose tended to be greater, whereas milk concentrations of isocitrate and BHBA were lower for PPG compared with CON. It is proposed that the ratio between free glucose and isocitrate in milk may be a potential biomarker for glucogenic status in the vulnerable early postpartum period. We will pursue this issue in the future.