Discovery of different metabotypes in overconditioned dairy cows by means of machine learning.

Using data from targeted metabolomics in serum in combination with machine learning (ML) approaches, we aimed at (1) identifying divergent metabotypes in overconditioned cows and at (2) exploring how metabotypes are associated with lactation performance, blood metabolites, and hormones. In a previously established animal model, 38 pregnant multiparous Holstein cows were assigned to 2 groups that were fed differently to reach either high (HBCS) or normal (NBCS) body condition score (BCS) and backfat thickness (BFT) until dryoff at -49 d before calving [NBCS: BCS < 3.5 (3.02 ± 0.24) and BFT < 1.2 cm (0.92 ± 0.21), mean ± SD; HBCS: BCS > 3.75 (3.82 ± 0.33) and BFT > 1.4 cm (2.36 ± 0.35)]. Cows were then fed the same diets during the dry period and the subsequent lactation, and maintained the differences in BFT and BCS throughout the study. Blood samples were collected weekly from 7 wk antepartum (ap) to 12 wk postpartum (pp) to assess serum concentrations of metabolites (by targeted metabolomics and by classical analyses) and metabolic hormones. Metabolic clustering by applying 4 supervised ML-based classifiers [sequential minimal optimization (SMO), random forest (RF), alternating decision tree (ADTree), and naïve Bayes-updatable (NB)] on the changes (d 21 pp minus d 49 ap) in concentrations of 170 serum metabolites resulted in 4 distinct metabolic clusters: HBCS predicted HBCS (HBCS-PH, n = 13), HBCS predicted NBCS (HBCS-PN, n = 6), NBCS predicted NBCS (NBCS-PN, n = 15), and NBCS predicted HBCS (NBCS-PH, n = 4). The accuracies of SMO, RF, ADTree, and NB classifiers were >70%. Because the number of NBCS-PH cows was low, we did not consider this group for further comparisons. Dry matter intake (kg/d and percentage of body weight) and energy intake were greater in HBCS-PN than in HBCS-PH in early lactation, and HBCS-PN also reached a positive energy balance earlier than did HBCS-PH. Milk yield was not different between groups, but milk protein percentage was greater in HBCS-PN than in HBCS-PH cows. The circulating concentrations of fatty acids (FA) increased during early lactation in both groups, but HBCS-PN cows had lower concentrations of ß-hydroxybutyrate, indicating lower ketogenesis compared with HBCS-PH cows. The concentrations of insulin, insulin-like growth factor 1, leptin, adiponectin, haptoglobin, glucose, and revised quantitative insulin sensitivity check index did not differ between the groups, whereas serum concentrations of glycerophospholipids were lower before calving in HBCS-PH than in HBCS-PN cows. Glycine was the only amino acid that had higher concentration after calving in HBCS-PH than in HBCS-PN cows. The circulating concentrations of some short- (C2, C3, and C4) and long-chain (C12, C16:0, C18:0, and C18:1) acylcarnitines on d 21 pp were greater in HBCS-PH than in HBCS-PN cows, indicating incomplete FA oxidation. In conclusion, the use of ML approaches involving data from targeted metabolomics in serum is a promising method for differentiating divergent metabotypes from apparently similar BCS phenotypes. Further investigations, using larger numbers of cows and farms, are warranted for confirmation of this finding.

Alterations of the acylcarnitine profiles in blood serum and in muscle from periparturient cows with normal or elevated body condition.

The objective of the current study was to characterize muscle and blood serum acylcarnitine (AcylCN) profiles and to determine the mRNA abundance of muscle carnitine acyltransferases in periparturient dairy cows with high (HBCS) and normal body condition (NBCS). Fifteen weeks antepartum, 38 pregnant multiparous Holstein cows were assigned to 2 groups that were fed differently to reach the targeted BCS and backfat thickness (BFT) until dry-off at -49 d before calving (HBCS: BCS >3.75 and BFT >1.4 cm; NBCS: <3.5 and <1.2 cm). Thereafter, both groups were fed identical diets. Blood samples and biopsies from the semitendinosus muscle were collected on d -49, 3, 21, and 84 relative to calving. Actual BCS at d -49 were 3.02 ± 0.24 and 3.82 ± 0.33 (mean ± SD) for NBCS and HBCS, respectively. In both groups, serum profiles showed marked changes during the periparturient period, with decreasing concentrations of free carnitine and increasing concentrations of long-chain AcylCN. Compared with NBCS, HBCS had greater serum long-chain AcylCN in early lactation, which may point to an insufficient adaptation of their metabolism in response to the metabolic load of fatty acids around parturition. The muscle concentrations of C5-, C9-, C18:1-, and C18:2-AcylCN were lower and those of C14:2-AcylCN were greater in HBCS than in NBCS cows. The mRNA abundance of carnitine palmitoyltransferase (CPT)1, muscle isoform (CPT1b) and CPT2 increased from d -49 to early lactation (d 3, d 21), followed by a decline to nearly antepartum values by d 84; this change was not affected by group. In conclusion, over-conditioning around calving seems to be associated with mitochondrial overload, which can result in incomplete fatty acid oxidation in dairy cows.

Profiling of circulating microRNA and pathway analysis in normal- versus over-conditioned dairy cows during the dry period and early lactation.

The objective of this study was to determine the circulating microRNA (miRNA) profile in over-conditioned (HBCS) versus normal-conditioned (NBCS) dairy cows in combination with pathway enrichment analyses during the transition period. Thirty-eight multiparous Holstein cows were selected 15 wk before anticipated calving date based on their current and previous body condition scores (BCS) for forming either a HBCS group (n = 19) or a NBCS group (n = 19). They were fed different diets during late lactation to reach the targeted differences in BCS and backfat thickness until dry-off. A subset of 15 animals per group was selected based on their circulating concentrations of nonesterified fatty acids (on d 14 postpartum) and ß-hydroxybutyrate (on d 21 postpartum), representing the greater or the lower extreme values within their BCS group. Blood serum obtained at d -49 and 21 relative to parturition (3 pools with 5 cows per each group and time point) were used to identify miRNA that were differentially expressed (DE) between groups or time points using miRNA sequencing. No DE-miRNA were discovered between NBCS versus HBCS. Comparing pooled samples from d -49 and d 21 resulted in 7 DE-miRNA in the NBCS group, of which 5 miRNA were downregulated and 2 miRNA were overexpressed on d 21 versus -49. The abundance of 5 of these DE-miRNA was validated in all individual samples via quantitative PCR and extended to additional time points (d -7, 3, 84). Group differences were observed for miR-148a, miR-122 as well as miR-455-5p, and most DE-miRNA (miR-148a, miR-122, miR-30a, miR-450b, miR-455-5p) were downregulated directly after calving. Subsequently, the DE-miRNA was used for bioinformatics analysis to identify putative target genes and the most enriched biological pathways. The most significantly enriched pathways of DE-miRNA were associated with cell cycle and insulin signaling as well as glucose and lipid metabolism. Overall, we found little differences in circulating miRNA in HBCS versus NBCS cows around calving.

Plasma proteomic profiling and pathway analysis of normal and overconditioned dairy cows during the transition from late pregnancy to early lactation.

This study applied a quantitative proteomics approach along with bioinformatics analyses to investigate changes in the plasma proteome of normal and overconditioned dairy cows during the transition period. Fifteen weeks before their anticipated calving date, 38 multiparous Holstein cows were selected based on their current and previous body condition scores (BCS) and allocated to either a high or a normal BCS group (19 cows each). They received different diets until dry-off to reach targeted differences in BCS and back fat thickness (BFT) until dry-off. At dry-off, normal BCS cows had a BCS <3.5 (minimum, 2.75) and BFT <1.2 cm (minimum, 0.58), and the high BCS cows had a BCS >3.75 (maximum, 4.50) and BFT >1.4 cm (maximum, 2.90). The proteomics study used a subset of 5 animals from each group. These cows were selected based on their circulating concentrations of fatty acids (FA) on d 14 postpartum and ß-hydroxybutyrate (BHB) on d 21 postpartum, representing the greater or the lower extreme values within their BCS group, respectively. The high BCS subset (HE-HBCS) had 4.50 < BCS > 3.75, FA = 1.17 ± 0.46 mmol/L, and BHB = 2.15 ± 0.42 mmol/L (means ± SD), and the low BCS subset (LE-NBCS) had 3.50 < BCS > 2.75, FA = 0.51 ± 0.28 mmol/L, and BHB = 0.84 ± 0.17 mmol/L. Plasma samples from d -49, +7, and +21 relative to parturition were used for proteome profiling by applying the quantitative tandem mass tags (TMT) approach. Nondepleted plasma samples were subjected to reduction and digestion and then labeled with TMT 10plex reagents. High-resolution liquid chromatography-tandem mass spectrometry analysis of TMT-labeled peptides was carried out, and the acquired spectra were analyzed for protein identification and quantification. In total, 254 quantifiable proteins (criteria: 2 unique peptides and 5% false discovery rate) were identified in the plasma samples. From these, 24 differentially abundant proteins (14 more abundant, 10 less abundant) were observed in the LE-NBCS cows compared with the HE-HBCS cows during the transition period. Plasma α-2-macroglobulins were more abundant in HE-HBCS versus LE-NBCS cows at d +7 and +21. Gene Ontology enrichment analyses of differentially abundant proteins revealed that the acute inflammatory response, regulation of complement activation, protein activation cascade, and regulation of humoral immune response were the most enriched terms in the LE-NBCS group compared with the HE-HBCS group. In addition, we identified 24 differentially abundant proteins (16 in the LE-NBCS group, and 8 in the HE-HBCS group) during the transition period. The complement components C1q and C5 were less abundant, while C3 and C3d were more abundant in LE-NBCS compared with HE-HBCS cows. Overall, overconditioning around calving was associated with alterations in protein pathways related to acute inflammatory response and regulation of complement and coagulation cascades in transition cows.

Metabolomics meets machine learning: Longitudinal metabolite profiling in serum of normal versus overconditioned cows and pathway analysis.

This study aimed to investigate the differences in the metabolic profiles in serum of dairy cows that were normal or overconditioned when dried off for elucidating the pathophysiological reasons for the increased health disturbances commonly associated with overconditioning. Fifteen weeks antepartum, 38 multiparous Holstein cows were allocated to either a high body condition (HBCS; n = 19) group or a normal body condition (NBCS; n = 19) group and were fed different diets until dry-off to amplify the difference. The groups were also stratified for comparable milk yields (NBCS: 10,361 ± 302 kg; HBCS: 10,315 ± 437 kg; mean ± standard deviation). At dry-off, the cows in the NBCS group (parity: 2.42 ± 1.84; body weight: 665 ± 64 kg) had a body condition score (BCS) <3.5 and backfat thickness (BFT) <1.2 cm, whereas the HBCS cows (parity: 3.37 ± 1.67; body weight: 720 ± 57 kg) had BCS >3.75 and BFT >1.4 cm. During the dry period and the subsequent lactation, both groups were fed identical diets but maintained the BCS and BFT differences. A targeted metabolomics (AbsoluteIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria) approach was performed in serum samples collected on d -49, +3, +21, and +84 relative to calving for identifying and quantifying up to 188 metabolites from 6 different compound classes (acylcarnitines, AA, biogenic amines, glycerophospholipids, sphingolipids, and hexoses). The concentrations of 170 metabolites were above the limit of detection and could thus be used in this study. We used various machine learning (ML) algorithms (e.g., sequential minimal optimization, random forest, alternating decision tree, and naïve Bayes-updatable) to analyze the metabolome data sets. The performance of each algorithm was evaluated by a leave-one-out cross-validation method. The accuracy of classification by the ML algorithms was lowest on d 3 compared with the other time points. Various ML methods (partial least squares discriminant analysis, random forest, information gain ranking) were then performed to identify those metabolites that were contributing most significantly to discriminating the groups. On d 21 after parturition, 12 metabolites (acetylcarnitine, hexadecanoyl-carnitine, hydroxyhexadecenoyl-carnitine, octadecanoyl-carnitine, octadecenoyl-carnitine, hydroxybutyryl-carnitine, glycine, leucine, phosphatidylcholine-diacyl-C40:3, trans-4-hydroxyproline, carnosine, and creatinine) were identified in this way. Pathway enrichment analysis showed that branched-chain AA degradation (before calving) and mitochondrial ß-oxidation of long-chain fatty acids along with fatty acid metabolism, purine metabolism, and alanine metabolism (after calving) were significantly enriched in HBCS compared with NBCS cows. Our results deepen the insights into the phenotype related to overconditioning from the preceding lactation and the pathophysiological sequelae such as increased lipolysis and ketogenesis and decreased feed intake.

Enzymatic production of lactulose and epilactose in milk.

The enzymatic production of lactulose was described recently through conversion of lactose by a thermophilic cellobiose 2-epimerase from Caldicellulosiruptor saccharolyticus (CsCE). In the current study, we examined the application of CsCE for lactulose and epilactose production in milk (1.5% fat). The bioconversions were carried out in stirred reaction vessels at 2 different temperatures (50 and 8°C) at a scale of 25 mL volume. At 50°C, 2 highly different CsCE amounts were investigated for the time course of formation of lactulose and epilactose. The conversion of milk lactose (initial lactose content of 48.5 ± 2.1 g/L) resulted in a final yield of 57.7% (28.0 g/L) lactulose and 15.5% (7.49 g/L) epilactose in the case of the approximately 9.5-fold higher CsCE amount (39.5 µkat epilactose, 50°C) after 24 h. Another enzymatic lactose conversion was carried out at low 8°C, an industrially relevant temperature for milk processing. Although the CsCE originated from a thermophilic microorganism, it was still applicable at 8°C. This enzymatic lactose conversion resulted in 56.7% (27.5 g/L) lactulose and 13.6% (6.57 g/L) epilactose from initial milk lactose after 72 h. The time courses of lactose conversion by CsCE suggested that first epilactose formed and afterward lactulose via epilactose. To the best of our knowledge, this is the first time that an enzyme has produced lactulose directly in milk in situ at industrially relevant temperatures.

Muscle metabolome and adipose tissue mRNA expression of lipid metabolism-related genes in over-conditioned dairy cows differing in serum-metabotype.

Over-conditioned dairy cows, classified by body condition score (BCS) and backfat thickness (BFT) are less able to metabolically adapt to the rapidly increasing milk yield after parturition. Based on serum metabolome and cluster analyses, high BCS cows (HBCS) could be classified into metabotypes that are more similar to normal (NBCS) cows, i.e., HBCS predicted normal (HBCS-PN) than the HBCS predicted high (HBCS-PH) cows-similar to the concept of obese but metabolically healthy humans. Our objective was to compare muscle metabolome and mRNA abundance of genes related to lipogenesis and lipolysis in adipose tissue between HBCS-PH (n = 13), HBCS-PN (n = 6), and NBCS-PN (n = 15). Tail-head subcutaneous fat was biopsied on d -49, 3, 21, and 84 relative to parturition. Potential differences in the oxidative capacity of skeletal muscle were assessed by targeted metabolomics in M. semitendinosus from d 21. Besides characteristic changes with time, differences in the mRNA abundance were limited to lipogenesis-related genes on d -49 (HBCS-PH > HBCS-PN). The HBCS-PH had more than two-fold higher muscle concentrations of short (C2, C4-OH, C6-OH) and long-chain acylcarnitines (C16, C18, and C18:1) than HBCS-PN, indicating a greater oxidative capacity for fatty acids (and utilization of ketones) in muscle of HBCS-PN than HBCS-PH cows.