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.

Biodiversity and antibiotic resistance profile provide new evidence for a different origin of enterococci in bovine raw milk and feces.

Enterococci are widely distributed in dairy sector. They are commensals of the gastrointestinal tract of animals, thus, via fecal contamination, could reach raw milk and dairy products. The aims of this study were: 1) to investigate the enterococcal diversity in cow feces and milk samples and 2) to evaluate the antibiotic resistance (AR) of dairy-related enterococci and their ability to transfer resistance genes. E. faecalis (59.9%), E. faecium (18.6%) and E. lactis (12.4%) were prevalent in milk, while E. faecium (84.2%) and E. hirae (15.0%) were dominant in bovine feces. RAPD-PCR highlighted a high number of Enterococcus biotypes (45 from milk and 37 from feces) and none of the milk strains exhibited genetic profiles similar to those of feces biotypes. A high percentage of enterococci isolated from milk (71%) were identified as multidrug resistant and resistance against streptomycin and tetracycline were widespread among milk strains while enterococci from feces were commonly resistant to linezolid and quinupristin/dalfopristin. Only E. faecalis strains were able to transfer horizontally the tetM gene to Lb. delbrueckii subsp. lactis. Our results indicated that Enterococcus biotypes from milk and bovine feces belong to different community and the ability of these microorganisms to transfer AR genes is strain-dependent.

Residual feed intake is related to metabolic and inflammatory response during the preweaning period in Italian Simmental calves.

Residual Feed Intake (RFI) is defined as the difference between measured and predicted intake. Understanding its biological regulators could benefit farm profit margins. The most-efficient animals (M-Eff) have observed intake smaller than predicted resulting in negative RFI, whereas the least-efficient (L-Eff) animals have positive RFI. Hence, this observational study aimed at retrospectively comparing the blood immunometabolic profile in calves with divergent RFI during the preweaning period. Twenty-two Italian Simmental calves were monitored from birth through 60 d of age. Calves received 3 L of colostrum from their respective dams. From 2 to 53 d of age, calves were fed a milk replacer twice daily, whereas from 54 to 60 d (i.e., weaning) calves were stepped down to only one meal in the morning. Calves had ad libitum access to concentrate and intakes were recorded daily. The measurement of BW and blood samples were performed at 0, 1, 7, 14, 21, 28, 35, 45, 54, and 60 d of age. Calves were ranked and categorized as M-Eff or L-Eff according to the median RFI value. Median RFI was -0.06 and 0.04 kg of DMI/d for M-Eff and L-Eff, respectively. No evidence for group differences was noted for colostrum and plasma IgG concentrations. Although growth rate was not different, as expected, (0.67 kg/d [95% CI = 0.57-0.76] for both L-Eff and M-Eff) throughout the entire preweaning period (0-60 d), starter intake was greater in L-Eff compared with M-Eff calves (+36%). Overall, M-Eff calves had a greater gain-to-feed ratio compared with L-Eff calves (+16%). Plasma ceruloplasmin, myeloperoxidase, and reactive oxygen metabolites concentrations were greater in L-Eff compared with M-Eff calves. Compared with L-Eff, M-Eff calves had an overall greater plasma concentration of globulin, and γ-glutamyl transferase (indicating a better colostrum uptake) and Zn at 1 d. Retinol and urea were overall greater in L-Eff. The improved efficiency in nutrient utilization observed in M-Eff was paired with a lower grade of oxidative stress and systemic inflammation. L-Eff may have had greater energy expenditure to support the activation of the immune system.

Feeding spent hemp biomass to lactating dairy cows: Effects on performance, milk components and quality, blood parameters, and nitrogen metabolism.

The legalization of industrial hemp by the 2018 Farm Bill in the United States has driven a sharp increase in its cultivation, including for cannabinoid extraction. Spent hemp biomass (SHB), produced from the extraction of cannabinoids, can potentially be used as feed for dairy cows; however, it is still illegal to do so in the United States, according to the US Food and Drug Administration Center for Veterinary Medicine, due to the presence of cannabinoids and the lack of data on the effect on animals. To assess the safety of this byproduct as feed for dairy cows, late-lactation Jersey cows (245 ± 37 d in milk; 483 ± 38 kg body weight; 10 multiparous and 8 primiparous) received a basal total mixed ration (TMR) diet plus 13% alfalfa pellet (CON) or 13% pelleted SHB for 4 wk (intervention period [IP]) followed by 4 wk of withdrawal period (WP), where all cows received only the basal TMR during WP. The dry matter intake (DMI), body weight, body condition score, milk yield, milk components, and fatty acid profile, blood parameters, N metabolism, methane emission, and activity were measured. Results indicated that feeding SHB decreased DMI mainly due to the low palatability of the SHB pellet, as the cows consumed only 7.4% of the total TMR with 13.0% SHB pellet offered in the ration. However, milk yield was not affected during the IP and was higher than CON during the WP, leading to higher milk yield/DMI. Milk components were not affected, except for a tendency in decreased fat percentage. Milk fat produced by cows fed SHB had a higher proportion of oleate and bacteria-derived fatty acids than CON. The activity of the cows was not affected, except for a shorter overall lying time in SHB versus CON cows during the IP. Blood parameters related to immune function were not affected. Compared with CON, cows fed SHB had a lower cholesterol concentration during the whole experiment and higher ß-hydroxybutyric acid during the WP, while a likely low-grade inflammation during the IP was indicated by higher ceruloplasmin and reactive oxidative metabolites. Other parameters related to liver health and inflammatory response were unaffected, except for a tendency for higher activity of alkaline phosphatase during IP and a lower activity of gamma-glutamyl transferase during WP in the SHB group versus CON. The bilirubin concentration was increased in cows fed SHB, suggesting a possible decrease in the clearance ability of the liver. Digestibility of the dry matter and protein and methane emission were not affected by feeding SHB. The urea, purine derivatives, and creatinine concentration in urine was unaffected, but cows fed SHB had higher N use efficiency and lower urine volume. Altogether, our data revealed a relatively low palatability of SHB affecting DMI with minimal biological effects, except for a likely low-grade inflammation, a higher N use efficiency, and a possible decrease in liver clearance. Overall, the data support the use of SHB as a safe feed ingredient for lactating dairy cows.

Expression of hepatic genes involved in bile acid metabolism in dairy cows with fatty liver.

Bile acids are cholesterol-derived molecules that are primarily produced in the liver. In nonruminants with fatty liver, overproduction of bile acids is associated with liver injury. During the transition period, fatty liver is a metabolic disorder that can affect up to 50% of high-producing dairy cows. The purpose of this study was to provide a comprehensive evaluation on hepatic bile acid metabolism in dairy cows with fatty liver by assessing expression changes of genes involved in bile acid synthesis, export and uptake. The serum activities of aspartate aminotransferase, alanine aminotransferase and glutamate dehydrogenase and concentration of total bile acids were all greater, whereas serum concentration of total cholesterol was lower in cows with fatty liver than in healthy cows. Content of total bile acids was higher but total cholesterol was slightly lower in liver tissues from fatty liver cows than from healthy cows. The hepatic mRNA abundance of cholesterol 7a-hydroxylase (CYP7A1), hydroxy-delta-5-steroid dehydrogenase, 3 ß- and steroid delta-isomerase 7 (HSD3B7) and sterol 12α-hydroxylase (CYP8B1), enzymes involved in the classic pathway of bile acid synthesis, was higher in fatty liver cows than in healthy cows. Compared with healthy cows, the hepatic mRNA abundance of alternative bile acid synthesis pathway-related genes sterol 27-hydroxylase (CYP27A1) and oxysterol 7α-hydroxylase (CYP7B1) did not differ in cows with fatty liver. The protein and mRNA abundance of bile acid transporter bile salt efflux pump (BSEP) were lower in the liver of dairy cow with fatty liver. Compared with healthy cows, the hepatic mRNA abundance of bile acid transporters solute carrier family 51 subunit α (SLC51A), ATP binding cassette subfamily C member 1 (ABCC1) and 3 (ABCC3) was greater in cows with fatty liver, whereas the solute carrier family 51 subunit ß (SLC51B) did not differ. The expression of genes involved in bile acid uptake, including solute carrier family 10 member 1 (NTCP), solute carrier organic anion transporter family member 1A2 (SLCO1A2) and 2B1 (SLCO2B1) was upregulated in dairy cows with fatty liver. Furthermore, the hepatic protein and mRNA abundance of bile acid metabolism regulators farnesoid X receptor (FXR) and small heterodimer partner (SHP) were lower in cows with fatty liver than in healthy cows. Overall, these data suggest that inhibition of FXR signaling pathway may lead to the increased bile acid synthesis and uptake and decreased secretion of bile acids from hepatocytes to the bile, which elevates hepatic bile acids content in dairy cows with fatty liver. As the hepatotoxicity of bile acids has been demonstrated on nonruminant hepatocytes, it is likely that the liver injury is induced by increased hepatic bile acids content in dairy cows with fatty liver.

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.

Associations between the detailed milk mineral profile, milk composition, and metabolic status in Holstein cows.

The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e., protein, fat, and lactose percentages), and their associations with the cows' metabolic status indicators were explored. The metabolic status indicators (MET) that we used were blood energy-protein metabolites [nonesterified fatty acids, ß-hydroxybutyrate (BHB), glucose, cholesterol, creatinine, and urea], and liver ultrasound measurements (predicted triacylglycerol liver content, portal vein area, portal vein diameter and liver depth). Milk and blood samples, and ultrasound measurements were taken from 295 Holstein cows belonging to 2 herds and in the first 120 d in milk (DIM). Milk mineral contents were determined by ICP-OES; these were considered the response variable and analyzed through a mixed model which included DIM, parity, milk yield, and MET as fixed effects, and the herd/date as a random effect. The MET traits were divided in tertiles. The results showed that milk protein was positively associated with body condition score (BCS) and glucose, and negatively associated with BHB blood content; milk fat was positively associated with BHB content; milk lactose was positively associated with BCS; and Ca, P, K and S were the minerals with the greatest number of associations with the cows' energy indicators, particularly BCS, predicted triacylglycerol liver content, glucose, BHB and urea. We conclude that the protein, fat, lactose, and mineral contents of milk partially reflect the metabolic adaptation of cows during lactation and within 120 DIM. Variations in the milk mineral profile were consistent with changes in the major milk constituents and the metabolic status of cows.

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 ß-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 (CVr) and herd-out (CVh). 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 CVr and 2% to 139% for CVh, whereas the stacking ensemble increased the R2 value from 4% to 70% for CVr and 4% to 150% for CVh. Considering the best model, with the CVr 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.

Drying-off dairy cows without antibiotic therapy and orally supplemented with lyophilized Aloe arborescens: effects on rumen activity, immunometabolic profile, and milk yield.

The drying-off is a stressful stage of the lactation cycle of dairy cows that deeply affects cows' metabolism, inflammatory status, and immune system. The promising effects observed during the transition period resulting from supplementation with Aloe arborescens Mill. suggest its potential utility during this phase. A group of 23 Holstein dairy cows with somatic cell count (SCC) less than 200 × 103 cells/ml and without intramammary infections were enroled in the study. Cows were divided into two groups: one orally receiving 10 g/day of A. arborescens Mill. lyophilized powder (AL; 11 cows) between -7 and 7 days from dry-off (DFD), and a control group (CTR; 12 cows). From -14 to 7 DFD and 7 and 28 days from calving, the body condition score and rectal temperature were determined, and rumen fluid, feces, milk, and blood samples were collected. Daily rumination times and milk yield were recorded. Data were analyzed through repeated measures mixed models. Compared to the CTR group, AL cows tended to show reduced production of volatile fatty acids in the rumen with acetate proportion that tended to be higher and valerate proportion that was lower. Moreover, Aloe supplementation caused a reduction in fecal dry matter. At the end of drying-off, AL cows presented better liver function, as suggested by higher paraoxonase plasma concentrations at 7 DFD, higher glucose, and lower urea, but showed increased reactive oxygen metabolites. Aloe supplementation at dry-off ameliorated inflammatory status after calving (lower haptoglobin and ceruloplasmin levels), and improved milk yield in the first weeks of subsequent lactation, without influencing milk composition, SCC, and incidence of intramammary infections. These results confirmed the positive effects of Aloe administration on liver function in dairy cows but indicate the need for further studies investigating the effects of Aloe on rumen fermentation profile and oxidative status.

Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle.

Cheese-making traits in dairy cattle are important to the dairy industry but are difficult to measure at the individual level because there are limitations on collecting phenotypic information. Mid-infrared spectroscopy has its advantages, but it can only be used during monthly milk recordings. Recently, in-line devices for real-time analysis of milk quality have been developed. The AfiLab recording system (Afimilk) offers significant benefits as phenotypes can be collected from each cow at each milking session. The objective of this study was to assess the potential of integrating AfiLab real-time milk analyzer measures with the stacking ensemble learning technique using heterogeneous base learners for the in-line daily monitoring of cheese-making traits in Holstein cattle with a view to developing a precision livestock farming system for monitoring the technological quality of milk. Data and samples for wet-laboratory analyses were collected from 499 Holstein cows belonging to 2 farms where the AfiLab system was installed. The traits of concern were 9 milk coagulation traits [3 milk coagulation properties (MCP), and 6 curd firming traits (CFt)], and 7 cheese-making traits [3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits]. The near-infrared AfiLab spectral data and on-farm information (days in milk and parity) were used to assess the predictive ability of different statistical methods [elastic net (EN), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), and artificial neural network (ANN)] across different cross-validation scenarios. These statistical methods were considered the base learners, which were then combined in a stacking ensemble learning. Results indicate that including information on the cows (days in milk and parity) in the AfiLab infrared prediction increased its accuracy by 10.3% for traditional MCP, 13.8% for curd firming, 9.8% for CY, and 11.2% for REC traits compared with those obtained from near-infrared AfiLab alone. The statistical approaches exhibited high prediction accuracies (R2) averaged across the cross-validation scenarios for traditional MCP (0.58 for ANN, 0.55 for EN and GBM, 0.52 for XGBoost, and 0.62 for stacking ensemble), CFt (0.55 for ANN, 0.54 for EN and GBM, 0.53 for XGBoost, and 0.61 for stacking ensemble), and similar R2 averages for CY and REC (0.55 for ANN, 0.54 for EN and GBM, 0.53 for XGBoost, and 0.61 for stacking ensemble). The ANN approach was more accurate than the other base learners (EN, GBM, and XGBoost) and improved accuracy across cross-validation scenarios on average by 7% for traditional MCP, 5% for CFt, 8% for CY, and 7% for REC. The stacking ensemble method improved prediction accuracy by 3% to 31% for traditional MCP, 2% to 26% for CFt, 1% to 38% for CY traits, and 2% to 27% for REC traits compared with the base learners. The prediction accuracies of the different approaches evaluated tended to decrease from the 10-fold cross-validation to the independent validation scenario, although there was a smaller reduction in prediction accuracy with the stacking ensemble learning technique across all the cross-validation scenarios. Our results show that combining in-line on-farm information with stacking ensemble machine learning represents an effective alternative for obtaining robust daily predictions of milk cheese-making traits.

Unique adaptations in neonatal hepatic transcriptome, nutrient signaling, and one-carbon metabolism in response to feeding ethyl cellulose rumen-protected methionine during late-gestation in Holstein cows.

BACKGROUND: Methionine (Met) supply during late-pregnancy enhances fetal development in utero and leads to greater rates of growth during the neonatal period. Due to its central role in coordinating nutrient and one-carbon metabolism along with immune responses of the newborn, the liver could be a key target of the programming effects induced by dietary methyl donors such as Met. To address this hypothesis, liver biopsies from 4-day old calves (n = 6/group) born to Holstein cows fed a control or the control plus ethyl-cellulose rumen-protected Met for the last 28 days prepartum were used for DNA methylation, transcriptome, metabolome, proteome, and one-carbon metabolism enzyme activities. RESULTS: Although greater withers and hip height at birth in Met calves indicated better development in utero, there were no differences in plasma systemic physiological indicators. RNA-seq along with bioinformatics and transcription factor regulator analyses revealed broad alterations in 'Glucose metabolism', 'Lipid metabolism, 'Glutathione', and 'Immune System' metabolism due to enhanced maternal Met supply. Greater insulin sensitivity assessed via proteomics, and efficiency of transsulfuration pathway activity suggested beneficial effects on nutrient metabolism and metabolic-related stress. Maternal Met supply contributed to greater phosphatidylcholine synthesis in calf liver, with a role in very low density lipoprotein secretion as a mechanism to balance metabolic fates of fatty acids arising from the diet or adipose-depot lipolysis. Despite a lack of effect on hepatic amino acid (AA) transport, a reduction in metabolism of essential AA within the liver indicated an AA 'sparing effect' induced by maternal Met. CONCLUSIONS: Despite greater global DNA methylation, maternal Met supply resulted in distinct alterations of hepatic transcriptome, proteome, and metabolome profiles after birth. Data underscored an effect on maintenance of calf hepatic Met homeostasis, glutathione, phosphatidylcholine and taurine synthesis along with greater efficiency of nutrient metabolism and immune responses. Transcription regulators such as FOXO1, PPARG, E2F1, and CREB1 appeared central in the coordination of effects induced by maternal Met. Overall, maternal Met supply induced better immunometabolic status of the newborn liver, conferring the calf a physiologic advantage during a period of metabolic stress and suboptimal immunocompetence.

Comparison of metabolic, oxidative and inflammatory status of Simmental × Holstein crossbred with parental breeds during the peripartal and early lactation periods.

The aim of the research reported in this paper was to evaluate plasma concentrations of energy, oxidative and inflammatory biomarkers of Simmental (sire) × Holstein (dam) crossbred cows, in comparison with the two parental breeds during the peripartal and early lactation periods and to estimate the effects of heterosis for these traits. Thirty-three animals, managed under the same conditions, 8 Simmental (SI), 9 Holstein (HO) and 16 crossbred (CR) cows were enrolled in this study. Glucose, non-esterified fatty acids (NEFA), ß-hydroxybutyrate (BHB), total bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), creatine kinase (CK), total protein, albumin, creatinine and urea were determined in blood sampled at six different time points (30 ± 3 and 15 ± 3 d before the expected calving date, at calving and 15, 30 and 60 d after calving). Furthermore, derived reactive oxygen metabolites (d-ROMs), biological antioxidant potential (BAP), interleukin-6 (IL-6), haptoglobin (Hp) and serum amyloid A protein (SAA) were determined to evaluate inflammatory and oxidative status. Results showed that the CR group had significantly lower average values of glucose and NEFA when compared to HO group; signifcantly lower values of urea than SI group and significantly higher values of creatinine than HO. Furthermore, CR cows showed the lowest average value of d-ROMs with respect to SI and HO parental breeds. Finally, the average value of haptoglobin was significantly lower in CR and HO groups, when compared to SI group. As for the heterosis we found the highest (positive) percentage for CK (98%) and BAP (47%) and the lowest (negative) percentage for OSi (-75%) and d-ROMs (-39%). A negative percentage was also found for the glucose (-11%) and NEFA (-20%) toward the Simmental parental breed. Our results suggest a different response among the three genetic groups during the peripartal and early lactation periods. In particular, CR and SI cows seem more adaptable regarding energy metabolism and oxidative status. Heterosis led to a positive effect on those parameters in Simmental (sire) × Holstein (dam) crossbred cows F1 population (50% Simmental and 50% Holstein).

Evaluation of circulating leukocyte transcriptome and its relationship with immune function and blood markers in dairy cows during the transition period.

Dairy cows during the transition period are faced with important physiological changes which include a dysfunctional immune system and an increased inflammatory state. New data are necessary to understand the key factors involved in the immune system regulation. Six dairy cows were sampled during transition period to investigate the leukocyte transcriptome changes and its relationship with blood biomarkers. Blood samples were collected at - 20 ± 2, - 3 ± 1, 3, and 7 days from parturition (DFP). Leukocyte transcriptome was analyzed by deep sequencing technology (Hiseq1000 Illumina, USA). Plasma was analyzed for metabolic biomarkers. Differentially expressed genes (DEG) were used to run an enrichment analysis through the Dynamic Impact Approach (DIA). Considering - 20 DFP as references time, the main KEGG impacted pathways were activated before calving (- 3 DFP) and were connected to lipid metabolism, lipid transport in plasma, and phagosome. The greatest differences were found after parturition with 281 DEG (179 upregulated and 102 downregulated). The activated pathways were mainly related to immunity and endocrine aspects, while metabolic pathways related to lipid and amino acid metabolism were inhibited. Plasma BHBA had a substantial inhibitory impact on KEGG pathways related to DNA replication and cell cycle, while plasma IL-1ß had an inhibitory impact on fatty acid elongation in mitochondria and an activated impact in several pathways related to cellular energy metabolism. Overall, this study confirmed that many changes in lipid metabolism and immune competence of the circulating leukocytes occurred in dairy cow around calving. Interestingly, BHBA and IL-1ß connected with the transcriptome.

Systems for evaluation of welfare on dairy farms.

Animal welfare is an essential component of dairy production and several systems exist to evaluate the welfare of dairy cows. Here, we review and compare three well-known systems that operate at farm level from around the world (FARM, Welfare Quality®, and The Code of Welfare) and discuss their advantages and limitations. Despite having some commonalities, the programs evaluate different elements. We also briefly review an emerging system (Integrated Diagnostic Welfare System) that might address some of the shortcomings of the existing systems, especially the possibility of automating the evaluation of animal well-being and identifying any cause of poor welfare. None of the aforementioned systems has been fully validated for their ability to assess animal welfare using independent measurements. The future holds increased attention around the well-being of dairy cows and increased use of sensing technologies. There is an urgent need for dairy welfare evaluation systems that are scientifically validated, holistic, and that can take advantage of the use of sensing technologies to continuously monitor animal welfare.

Differential effects of coconut versus soy oil on gut microbiota composition and predicted metabolic function in adult mice.

BACKGROUND: Animal studies show that high fat (HF) diet-induced gut microbiota contributes to the development of obesity. Oil composition of high-fat diet affects metabolic inflammation differently with deleterious effects by saturated fat. The aim of the present study was to examine the diversity and metabolic capacity of the cecal bacterial community in C57BL/6 N mice administered two different diets, enriched respectively with coconut oil (HFC, high in saturated fat) or soy oil (HFS, high in polyunsaturated fat). The relative impact of each hypercaloric diet was evaluated after 2 and 8 weeks of feeding, and compared with that of a low-fat, control diet (LF). RESULTS: The HFC diet induced the same body weight gain and fat storage as the HFS diet, but produced higher plasma cholesterol levels after 8 weeks of treatment. At the same time point, the cecal microbiota of HFC diet-fed mice was characterized by an increased relative abundance of Allobaculum, Anaerofustis, F16, Lactobacillus reuteri and Deltaproteobacteria, and a decreased relative abundance of Akkermansia muciniphila compared to HFS mice. Comparison of cecal microbiota of high-fat fed mice versus control mice indicated major changes that were shared between the HFC and the HFS diet, including the increase in Lactobacillus plantarum, Lutispora, and Syntrophomonas, while some other shifts were specifically associated to either coconut or soy oil. Prediction of bacterial gene functions showed that the cecal microbiota of HFC mice was depleted of pathways involved in fatty acid metabolism, amino acid metabolism, xenobiotic degradation and metabolism of terpenoids and polyketides compared to mice on HFS diet. Correlation analysis revealed remarkable relationships between compositional changes in the cecal microbiota and alterations in the metabolic and transcriptomic phenotypes of high-fat fed mice. CONCLUSIONS: The study highlights significant differences in cecal microbiota composition and predictive functions of mice consuming a diet enriched in coconut vs soy oil. The correlations established between specific bacterial taxa and various traits linked to host lipid metabolism and energy storage give insights into the role and functioning of the gut microbiota that may contribute to diet-induced metabolic disorders.

Dietary supplement of conjugated linoleic acids or polyunsaturated fatty acids suppressed the mobilization of body fat reserves in dairy cows at early lactation through different pathways.

To investigate the metabolic changes in the adipose tissue (AT) of dairy cows under milk fat depression (MFD), 30 cows were randomly allocated to a control diet, a conjugated linoleic acid (CLA)-supplemented diet, or a high-starch diet supplemented with a mixture of sunflower and fish oil (2:1; as HSO diet) from 1 to 112 d in milk. Performance of animals, milk yield, milk composition, energy balance, and blood metabolites were measured during lactation. Quantitative PCR analyses were conducted on the AT samples collected at wk 3 and 15 of lactation. The CLA and HSO diets considerably depressed milk fat yield and milk fat content at both wk 3 and 15 in the absence of significant changes in milk protein and lactose contents. In addition, the HSO diet lowered milk yield at wk 15 and decreased dry matter intake of cows from wk 3 to 15. Compared with the control, both CLA and HSO groups showed reduced body weight loss, improved energy balance, and decreased plasma concentrations of nonesterified fatty acids and ß-hydroxybutyrate at early lactation. The gene expression analyses reflected suppressed lipolysis in AT of the CLA and HSO groups compared with the control at wk 3, as suggested by the downregulation of hormone-sensitive lipase and fatty acid binding protein 4 and the upregulation of perilipin 2. In addition, the HSO diet promoted lipogenesis in AT at wk 15 through the upregulation of 1-acylglycerol-3-phosphate O-acyltransferase 2, mitochondrial glycerol-3-phosphate acyltransferase, perilipin 2, and peroxisome proliferator-activated receptor γ. The CLA diet likely regulated insulin sensitivity in AT as it upregulated the transcription of various genes involved in insulin signaling, inflammatory responses, and ceramide metabolism, including protein kinase B2, nuclear factor κ B1, toll-like receptor 4, caveolin 1, serine palmitoyltransferase long chain base subunit 1, and N-acylsphingosine amidohydrolase 1. In contrast, the HSO diet resulted in little or no change in the pathways relevant to insulin sensitivity. In conclusion, the CLA and HSO diets induced a shift in energy partitioning toward AT instead of mammary gland during lactation through the regulation of different pathways.

Effect of consuming endophyte-infected fescue seed on transcript abundance in the mammary gland of lactating and dry cows, as assessed by RNA sequencing.

Ergot alkaloids in endophyte-infected grasses inhibit prolactin secretion and reduce milk production in lactating cows. However, we previously showed that prepartum consumption of infected seed throughout the dry period did not inhibit subsequent milk production and prior exposure to bromocriptine (ergot peptide) actually increased production in the next lactation. To identify changes in the transcriptome and molecular pathways mediating the mammary gland's response to ergot alkaloids in the diet, RNA sequencing (RNA-seq) was performed on mammary tissues obtained from 22 multiparous Holstein cows exposed to 1 of 3 treatments. Starting at 90 ± 4 d prepartum, cows were fed endophyte-free fescue seed (control; CON), endophyte-free fescue seed plus 3×/wk subcutaneous injections of bromocriptine (BROMO; 0.1 mg/kg of BW), or endophyte-infected fescue seed (INF) as 10% of the diet. Cows were dried off 60 ± 2 d prepartum. Mammary biopsies from 4 (BROMO, INF) or 5 (CON) cows/treatment at each of the 3 phases were obtained: 7 d before dry off during the initial lactation (L1), mid-dry period (D), and 10 d postpartum (L2). Although tissue from the same cow was preferentially used at 3 phases (L1, D, L2), tissue from additional cows were used to as necessary to provide RNA of sufficient quality. Individual samples were used to generate individual RNA-seq libraries. Normalized reads of the RNA-seq data were organized into technical and biological replicates before processing with the RSEM software package. Each lactation phase was processed separately and genes that differed between any of 3 treatments were identified. A large proportion of genes differentially expressed in at least 1 treatment (n = 866) were found to be similarly expressed in BROMO and INF treatments, but differentially expressed from CON (n = 575, total for 3 phases). Of genes differentially expressed compared with CON, 104 genes were common to the L1 and L2 phases. Consistent with the production findings, networks most affected by treatments in L1 and L2 included lipid metabolism, small molecule biochemistry, and molecular transport, whereas networks related more to developmental and cellular functions and maintenance were evident during D phase. Similar patterns of expression in BROMO and INF during late and early lactation suggest involvement of similar cell signaling pathways or mechanisms of action for BROMO and INF and the importance of prolactin messaging pathways.

Assessment of the main plasma parameters included in a metabolic profile of dairy cow based on Fourier Transform mid-infrared spectroscopy: preliminary results.

BACKGROUND: Although a metabolic profile represents a valid tool utilized in dairy herds to determine abnormalities in blood chemistry related to an increased risk of production diseases, there are no studies on application of Fourier Transform mid-infrared (FT-MIR) spectroscopy. This study assesses the potential application of FT-MIR to analyze the main blood biochemical parameters included in the metabolic profile of dairy cows. Infrared transmission spectra were acquired for 35 plasma samples (two replicates on each sample) of Italian Friesian dairy cows (14 primiparous and 21 pluriparous), all without clinical events, and at different stages of lactation, although mainly in the transition phase. Each sample was also analyzed independently using accepted reference clinical chemical methods and these results were used as calibrating values to perform predictive models by PLS method using cross validation. RESULTS: Measured blood parameters concentrations were all within the reference ranges reported for healthy dairy cows. The number of extracted factors with the PLS procedure for each prediction model ranged between 3 and 7. The coefficient of determination (R(2)) of the prediction models ranged between 0.1 to values close to 1. R(2) values greater than 0.9 were observed for the prediction models of total cholesterol, total protein, globulin, and albumin; values between 0.75 and 0.9 were observed for urea, NEFA, and total bilirubin, while values of R(2) lower than 0.6 were observed for all minerals and for enzyme activity. The range error ratio (RER) and prediction to deviation (RPD) ranged from 5.1 to 43.8 and from 1 to 13.8 for RER and RPD, respectively. Values of RPD greater than 5 were observed for total cholesterol, total protein, albumin, and globulin. RPD ranged between 2 and 5 for the prediction models of urea, NEFA, and total bilirubin, while RPD and RER were low for minerals and enzyme activities. CONCLUSIONS: Although the results of this study require further validation, the use of FT-MIR spectroscopy was possible and provides fairly accurate measurement of various parameters of great importance in the evaluation of the metabolic and inflammatory status in dairy cows.

Consumption of endophyte-infected fescue seed during the dry period does not decrease milk production in the following lactation.

Ergot alkaloids in endophyte-infected grasses inhibit prolactin (PRL) secretion and may reduce milk production of cows consuming these grasses. We investigated the effects of consuming endophyte-infected fescue seed during late lactation and the dry period on mammary growth, differentiation, and milk production. Twenty-four multiparous Holstein cows were randomly assigned to 3 treatment groups. Starting at 90±4 d prepartum, cows were fed endophyte-free fescue seed (control; CON), endophyte-free fescue seed plus 3×/wk subcutaneous injections of bromocriptine (0.1mg/kg of body weight, positive control; BROMO), or endophyte-infected fescue seed (INF) as 10% of the diet on an as fed basis. Although milk yield of groups did not differ before treatment, at dry off (-60 d prepartum) INF and BROMO cows produced less milk than CON. Throughout the treatment period, basal concentrations of PRL and the prepartum increase in plasma PRL were reduced in INF and BROMO cows compared with CON cows. Three weeks after the end of treatment, circulating concentrations of PRL were equivalent across groups. In the subsequent lactation milk yield was not decreased; in fact, BROMO cows exhibited a 9% increase in milk yield relative to CON. Evaluation of mammary tissue during the dry period and the subsequent lactation, by quantitative histology and immunohistochemical analysis of proliferation markers and putative mammary stem or progenitor cell markers, indicated that feeding endophyte-infected fescue seed did not significantly affect mammary growth and development. Feeding endophyte-infected grasses during the dry period may permit effective utilization of feed resources without compromising milk production in the next lactation.

Stress and inflammatory gene networks in bovine liver are altered by plane of dietary energy during late pregnancy.

The prepartal dietary energy level is tightly correlated with the degree of tissue mobilization that the animal experiences around parturition (giving birth). To better understand the link between the dry period dietary energy management and the inflammatory status around parturition, 12 multiparous Holstein cows were fed for the entire dry period either a high-wheat straw/lower-energy diet to supply at least 100% of the calculated net energy for lactation (NEL) (control, CON) or a higher-energy diet to supply >140% of NEL (overfed, OVE). The blood was sampled throughout the transition period for biomarker analyses. Liver tissue samples were taken on days -14, 7, 14, and 30 relative to parturition for triacylglycerol (TAG) composition and gene expression analysis. Fifty genes involved in inflammation, endoplasmic reticulum (ER), and oxidative stress, and cell cycle and growth were evaluated. Although blood biomarkers did not reveal signs of a greater inflammatory status compared with OVE, CON cows had a greater activation of the intrahepatic unfolded protein response prepartum. However, postpartum mRNA profiling indicated that the OVE group experienced a mild but sustained level of ER stress, with higher oxidative stress and impairment of antioxidant mechanisms. After parturition, inflammation-related genes were upregulated in OVE cows compared with CON. However, CON cows experienced a gradual increase in expression of key inflammatory transcription regulators up to 30 days postpartum which agreed with the lower plasma albumin and cholesterol, suggesting an inflammatory state. Data underscored that ER stress is not necessarily linked with inflammation during the peripartal period. Gene expression data also suggest that prepartum overnutrition could have negative effects on normal cell cycle activity. Overall, allowing cows to overconsume energy prepartum increased the hepatic pro-inflammatory response prepartum and up to the point of parturition. Subsequently, cows fed the lower-energy diet experienced a gradual increase in the inflammatory response. The lack of differences between groups in voluntary feed intake and lactation capacity suggests that nutritional management prepartum triggers different mechanisms that affect ER and oxidative stress along with inflammation. Although no clinical disorders were detected, these alterations expose animals to the development of immuno-metabolic disorders.