Molecular signatures of longissimus dorsi differ between dairy cattle based on prepartum muscle reserves and branched-chain volatile fatty acid supplementation.

Dairy cattle with high (HM) versus low muscle (LM) reserves exhibit distinct temporal changes in longissimus dorsi muscle depth (LDD) in late gestation. Branched-chain volatile fatty acids (BCVFA) supplementation increased blood glucose levels. We hypothesized that differences in HM and LM reflect distinct muscle metabolism and BCVFA supplementation altered metabolic pathways. At 42 d before expected calving (BEC) Holstein dairy cows were enrolled in a 2 x 2 factorial study of diet and muscle reserves, by assigning to control (CON) or BCVFA supplemented diets and LDD of HM (>4.6 cm) or LM (≤4.6 cm) groups: HM-CON (n=13), HM-BCVFA (n=10), LM-CON (n=9), and LM-BCVFA (n=9). Longisumus dorsi was biopsied at 21 d BEC, total RNA isolated and protein coding gene expression measured with RNA-seq. Between HM and LM 713 genes were differentially expressed and 481 between BCVFA and CON (P<0.05). Transcriptional signatures indicated differential distribution of Type II fibers between groups, with MYH1 greater in LM and MYH2 greater in HM cattle (P<0.05). Signatures of LM cattle relative to HM indicated greater activation of autophagy, ubiquitin-proteasome, and Ca2+-calpain pathways. HM cattle displayed greater expression of genes that encode extracellular matrix proteins and factors that regulate their proteolysis and turnover. BCVFA modified transcriptomes by increasing expression of genes that regulate fatty acid degradation and flux of carbons into the TCA cycle as acetyl CoA. Molecular signatures support distinct metabolic strategies between LM and HM cattle, and that BCVFA supplementation increased substrates for energy generation.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle.

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems have increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in a xyz plan, which can then be used to derive udder conformation traits. AMS generate a large amount of per milking visit data for individual cows, which contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multi-trait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 single nucleotide polymorphisms. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (±standard error, SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (±SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between the FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection sub-indexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

Graduate Student Literature Review: Social and feeding behavior of group-housed dairy calves in automated milk feeding systems.

Automated milk feeders (AMF) allow farmers to raise calves in groups while generating individual records on milk consumption, drinking speed, and frequency of visits. Calves raised in groups benefit from social interaction, which facilitates learning and adapting to novelty. However, calves in large groups (>12 calves/feeder) experience a higher risk of disease transmission and competition than those housed individually or in smaller groups. Therefore, if group size, grouping strategy, and disease detection are not optimal, the health and performance of calves can be compromised. The objectives of this narrative literature review, from publications available as of February 2023, are to (1) describe the use of AMF in group housing systems for calves and the associated feeding behavior variables they automatically collect, (2) linking feeding behavior collected from AMF to disease risk in calves, (3) describe research on social behavior in AMF systems, and (4) introduce social networks as a promising tool for the study of social behavior and disease transmission in group-housed AMF-fed calves. Existing research suggests that feeding behavior measures from AMF can assist in detecting bovine respiratory disease and enteric disease, which are common causes of morbidity and mortality for preweaning dairy heifers. Automated milk feeder records show reduced milk intake, drinking speed, or frequency of visits when calves are sick. However, discrepancies exist among published research about the sensitivity of feeding behavior measures as indicators of sickness, likely due to differences in feeding plans and disease-detection protocols. Therefore, considering the influence of milk allowance, group density, and individual variation on the analysis of AMF data is essential to derive meaningful information used to inform management decisions. Research using dynamic social networks derived from precision data show potential for the use of social network analysis to understand disease transmission and the effect of disease on social behavior of group-housed calves.

Machine learning methods for genomic prediction of cow behavioral traits measured by automatic milking systems in North American Holstein cattle.

Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction methods and deep learning algorithms for genomic prediction of milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows measured by automatic milking systems (milking robots). A total of 1,993,509 daily records from 4,511 genotyped Holstein cows were collected by 36 milking robot stations. After quality control, 57,600 SNPs were available for the analyses. Four genomic prediction methods were considered: Bayesian least absolute shrinkage and selection operator (LASSO), multiple layer perceptron (MLP), convolutional neural network (CNN), and GBLUP. We implemented the first 3 methods using the Keras and TensorFlow libraries in Python (v.3.9) but the GBLUP method was implemented using the BLUPF90+ family programs. The accuracy of genomic prediction (mean square error) for MREF and MFAIL was 0.34 (0.08) and 0.27 (0.08) based on LASSO, 0.36 (0.09) and 0.32 (0.09) for MLP, 0.37 (0.08) and 0.30 (0.09) for CNN, and 0.35 (0.09) and 0.31(0.09) based on GBLUP, respectively. Additionally, we observed a lower reranking of top selected individuals based on the MLP versus CNN methods compared with the other approaches for both MREF and MFAIL. Although the deep learning methods showed slightly higher accuracies than GBLUP, the results may not be sufficient to justify their use over traditional methods due to their higher computational demand and the difficulty of performing genomic prediction for nongenotyped individuals using deep learning procedures. Overall, this study provides insights into the potential feasibility of using deep learning methods to enhance genomic prediction accuracy for behavioral traits in livestock. Further research is needed to determine their practical applicability to large dairy cattle breeding programs.

Unraveling the genomic background of resilience based on variability in milk yield and milk production levels in North American Holstein cattle through genome-wide association study and Mendelian randomization analyses.

Breeding more resilient animals will benefit the dairy cattle industry in the long term, especially as global climate changes become more severe. Previous studies have reported genetic parameters for various milk yield-based resilience indicators, but the underlying genomic background of these traits remain unknown. In this study, we conducted GWAS of 62,029 SNPs with 4 milk yield-based resilience indicators, including the weighted occurrence frequency (wfPert) and accumulated milk losses (dPert) of milk yield perturbations, and log-transformed variance (LnVar) and lag-1 autocorrelation (rauto) of daily yield residuals. These variables were previously derived from 5.6 million daily milk yield records from 21,350 lactations (parities 1-3) of 11,787 North American Holstein cows. The average daily milk yield (ADMY) throughout lactation was also included to compare the shared genetic background of resilience indicators with milk yield. The differential genetic background of these indicators was first revealed by the significant genomic regions identified and significantly enriched biological pathways of positional candidate genes, which confirmed the genetic difference among resilience indicators. Interestingly, the functional analyses of candidate genes suggested that the regulation of intestinal homeostasis is most likely affecting resilience derived based on variability in milk yield. Based on Mendelian randomization analyses of multiple instrumental SNPs, we further found an unfavorable causal association of ADMY with LnVar. In conclusion, the resilience indicators evaluated are genetically different traits, and there are causal associations of milk yield with some of the resilience indicators evaluated. In addition to providing biological insights into the molecular regulation mechanisms of resilience derived based on variability in milk yield, this study also indicates the need for developing selection indexes combining multiple indicator traits and taking into account their genetic relationship for breeding more resilient dairy cattle.

Genetic parameters for calf feeding traits derived from automated milk feeding machines and number of bovine respiratory disease treatments in North American Holstein calves.

Precision livestock farming technologies, such as automatic milk feeding machines, have increased the availability of on-farm data collected from dairy operations. We analyzed feeding records from automatic milk feeding machines to evaluate the genetic background of milk feeding traits and bovine respiratory disease (BRD) in North American Holstein calves. Data from 10,076 preweaning female Holstein calves were collected daily over a period of 6 yr (3 yr included per-visit data), and daily milk consumption (DMC), per-visit milk consumption (PVMC), daily sum of drinking duration (DSDD), drinking duration per-visit, daily number of rewarded visits (DNRV), and total number of visits per day were recorded over a 60-d preweaning period. Additional traits were derived from these variables, including total consumption and duration variance (TCV and TDV), feeding interval, drinking speed (DS), and preweaning stayability. A single BRD-related trait was evaluated, which was the number of times a calf was treated for BRD (NTT). The NTT was determined by counting the number of BRD incidences before 60 d of age. All traits were analyzed using single-step genomic BLUP mixed-model equations and fitting either repeatability or random regression models in the BLUPF90+ suite of programs. A total of 10,076 calves with phenotypic records and genotypic information for 57,019 SNP after the quality control were included in the analyses. Feeding traits had low heritability estimates based on repeatability models (0.006 ± 0.0009 to 0.08 ± 0.004). However, total variance traits using an animal model had greater heritabilities of 0.21 ± 0.023 and 0.23 ± 0.024, for TCV and TDV, respectively. The heritability estimates increased with the repeatability model when using only the first 32 d preweaning (e.g., PVMC = 0.040 ± 0.003, DMC = 0.090 ± 0.009, DSDD = 0.100 ± 0.005, DS = 0.150 ± 0.007, DNRV = 0.020 ± 0.002). When fitting random regression models (RRM) using the full dataset (60-d period), greater heritability estimates were obtained (e.g., PVMC = 0.070 [range: 0.020, 0.110], DMC = 0.460 [range: 0.050, 0.680], DSDD = 0.180 [range: 0.010, 0.340], DS = 0.19 [range: 0.070, 0.430], DNRV = 0.120 [range: 0.030, 0.450]) for the majority of the traits, suggesting that RRM capture more genetic variability than the repeatability model with better fit being found for RRM. Moderate negative genetic correlations of -0.59 between DMC and NTT were observed, suggesting that automatic milk feeding machines records have the potential to be used for genetically improving disease resilience in Holstein calves. The results from this study provide key insights of the genetic background of early in-life traits in dairy cattle, which can be used for selecting animals with improved health outcomes and performance.

Dynamics of the nasopharyngeal microbiome of apparently healthy calves and those with clinical symptoms of bovine respiratory disease from disease diagnosis to recovery.

Introduction: Bovine respiratory disease (BRD) is a multifactorial disease complex in which bacteria in the upper respiratory tract play an important role in disease development. Previous studies have related the presence of four BRD-pathobionts (Mycoplasma bovis, Histophilus somni, Pasteurella multocida, and Mannheimia haemolytica) in the upper respiratory tract to BRD incidence and mortalities in the dairy and beef cattle industry, but these studies typically only use one time point to compare the abundance of BRD-pathobionts between apparently healthy and BRD-affected cattle. The objective of this study was to characterize the longitudinal development of the nasopharyngeal (NP) microbiome from apparently healthy calves, and in calves with clinical signs of BRD, the microbiota dynamics from disease diagnosis to recovery. Methods: Deep nasopharyngeal swabs were taken from all calves immediately after transport (day 0). If a calf was diagnosed with BRD (n = 10), it was sampled, treated with florfenicol or tulathromycin, and sampled again 1, 5, and 10 days after antibiotic administration. Otherwise, healthy calves (n = 20) were sampled again on days 7 and 14. Bacterial community analysis was performed through 16S rRNA gene amplicon sequencing. Results: The NP microbiome of the healthy animals remained consistent throughout the study, regardless of time. The NP microbiota beta diversity and community composition was affected by tulathromycin or florfenicol administration. Even though BRD-pathobionts were identified by 16S rRNA gene sequencing in BRD-affected animals, no difference was observed in their relative abundance between the BRD-affected and apparently healthy animals. The abundance of BRD-pathobionts was not predictive of disease development while the relative abundance of BRD pathobionts was unique to each BRD-affected calf. Interestingly, at the end of the study period, the genera Mycoplasma was the most abundant genus in the healthy group, while Lactobacillus was the most abundant genus in the animals that recovered from BRD. Discussion: This study highlights that injected antibiotics seem to improve the NP microbiome composition (higher abundance of Lactobacillus and lower abundance of Mycoplasma), and that the relative abundance of BRD-pathobionts differs between individual calves but is not strongly predictive of BRD clinical signs, indicating that additional factors are likely important in the clinical progression of BRD.

Environmental and biological factors that influence feeding behavior of Holstein calves in automated milk feeding systems.

Automated milk feeders (AMF) used for dairy calves continuously provide individual feeding behavior measurements. The objective of this retrospective cohort study was to evaluate the association between temperature-humidity index (THI), birth weight, and dam parity characteristics on feeding behavior (i.e., milk consumption and drinking speed). Historical data sets generated from a single commercial dairy farm, where healthy (not treated for bovine respiratory disease, enteric disease, or injury) Holstein calves were fed up to 24 L/d of milk, were used for the analysis. A total of 5,312 female Holstein calves born between August 2015 and August 2021 (mean birth weight ± standard deviation: 40.7 ± 4.7 kg) on a commercial dairy farm were fed up to 24 L/d of nonsaleable milk for the first 32 d. For the analyses, feeding behavior data from the AMF system were combined with demographic data from the farm management software, and weather records from the closest public weather station (7 km away). Linear mixed models used to analyze daily milk consumption and drinking speed included THI, birth weight, dam parity, and feeding day as fixed effects, and feeder and calf within feeder as random effects. These models explained 57% of the total variation in milk consumption and 48% of the variation in drinking speed. Calves born from primiparous cows had the lowest milk consumption and the greatest drinking speed in comparison to calves born from multiparous cows. Calves with heavier birth weights had higher milk consumption and faster drinking speed than lighter calves. Drinking speed was negatively associated with THI. Including data derived from individual calves and their environmental conditions in data sets exploring feeding behavior from AMF would control for variation and improve the predictive models for performance assessment.

l-Glutamine supplementation reduces gastrointestinal permeability and biomarkers of physiological stress in preweaning Holstein heifer calves.

l-Glutamine supplementation improves gastrointestinal and immune function in dairy calves during controlled immune and stress challenges. However, it is unknown whether supplementing milk replacer (MR) with l-glutamine improves preweaning dairy calf health and welfare under production conditions. Therefore, the study objective was to evaluate the effects of supplementing MR with l-glutamine on gastrointestinal permeability, immune function, growth performance, postabsorptive metabolic biomarkers, and physiological stress response in preweaning dairy calves. In 3 repetitions, Holstein heifer calves (n = 30; 1.5 ± 0.5 d old; 37.1 ± 0.86 kg body weight) were blocked by serum total protein, body weight, and age, and provided MR (3.8 L/calf per d; 24% CP, 17% fat, 12.5% solids) supplemented with l-glutamine (GLN; 10g/kg MR powder; n = 5 calves/repetition) or nonsupplemented (NSMR; n = 5 calves/repetition). Calves were individually housed with ad libitum starter grain and water access until weaning (56.4 ± 0.5 d old). At 1 and 6 wk of age, urinary catheters were placed, and calves were orally dosed with 1 L of chromium (Cr)-EDTA. Urine samples were collected over a 24-h period for Cr output analysis as an in vivo biomarker of gastrointestinal permeability. Blood was collected on study d 1, 5, 7, 14, 21, 42, and 56 to measure white blood cell counts, cortisol, insulin, glucose, nonesterified fatty acids, serum amyloid A, haptoglobin, and neutrophil: lymphocytes. Two study intervals were used in the statistical analyses, representing greater (P1; wk 1-3) and reduced (P2; wk 4-8) enteric disease susceptibility. Data were analyzed using PROC GLIMMIX in SAS 9.4 (SAS Institute Inc.) with calf as the experimental unit. Overall, total urinary Cr output was reduced in GLN versus NSMR calves. Total Cr output was reduced at 1 wk of age in GLN versus NSMR calves, but no differences were detected at 6 wk of age. Neutrophil:lymphocyte was decreased both overall and during P2 in GLN versus NSMR calves, and neutrophil counts tended to be reduced in GLN versus NSMR calves during P2. No MR treatment differences were detected for average daily feed intake, average daily gain, body measurements, postabsorptive metabolic biomarkers, disease scores, and therapeutic treatments between GLN and NSMR calves. In summary, l-glutamine supplementation reduced gastrointestinal permeability and biomarkers of physiological stress in preweaning Holstein heifer calves.

Relationship between body temperature and behavior of nonpregnant early-lactation dairy cows.

Animal behavior and management factors that influence behavior affect physiology and lactation performance. Circadian rhythms of core body temperature are a primary output of the master clock; however, core body temperature in early-lactation dairy cows showed poor fit to 24-h rhythms. We hypothesized that eating behavior was related to daily body temperature oscillations. The objectives of this study were to determine if oscillations in daily behaviors, specifically feeding behavior, were related to body temperature. The behavior of 11 Holstein cows (34 ± 14 d in milk; mean ± standard deviation) housed in a freestall barn was recorded every 10 min for a 48-h period. Simultaneously, data loggers (iButtons; iButtonLink Technology) recorded the body temperature of cows with the same sampling frequency. The mean temperature of all cows showed a better fit to a 2-component cosinor (R2 = 0.54) than to a single cosinor model (R2 = 0.26). Logistic regression showed that the probability (Pr) of a cow experiencing an increase in body temperature (increment, I) given that she was milking [Pr(I|milking) = 0.94] was higher than for ruminating [Pr(I|ruminating) = 0.69], lying [Pr(I|lying) = 0.66], feeding [Pr(I|feeding) = 0.16], standing [Pr(I|standing) = 0.54], and mounting [Pr(I|mounting) = 0.62]. The main limitations of this study are the length of the observation period and the sample size. Longer observation windows on core body temperature would allow to isolate the noise and the signal and identify patterns with more clarity. Oscillations in body temperature were not associated with feeding. However, findings indicate that milking, activity associated with walking to the parlor, or the temperature in the parlor may affect secondary rhythms of daily body temperature.

Genomic-based genetic parameters for resilience across lactations in North American Holstein cattle based on variability in daily milk yield records.

Considering the increasing challenges imposed by climate change and the need to improve animal welfare, breeding more resilient animals capable of better coping with environmental disturbances is of paramount importance. In dairy cattle, resilience can be evaluated by measuring the longitudinal occurrences of abnormal daily milk yield throughout lactation. Aiming to estimate genetic parameters for dairy cattle resilience, we collected 5,643,193 daily milk yield records on automatic milking systems (milking robots) and milking parlors across 21,350 lactations 1 to 3 of 11,787 North American Holstein cows. All cows were genotyped with 62,029 SNPs. After determining the best fitting models for each of the 3 lactations, daily milk yield residuals were used to derive 4 resilience indicators: weighted occurrence frequency of yield perturbations (wfPert), accumulated milk losses of yield perturbations (dPert), and log-transformed variance (LnVar) and lag-1 autocorrelation (rauto) of daily yield residuals. The indicator LnVar presented the highest heritability estimates (±standard error), ranging from 0.13 ± 0.01 in lactation 1 to 0.15 ± 0.02 in lactation 2; the other 3 indicators had relatively lower heritabilities across the 3 lactations (0.01-0.06). Based on bivariate analyses of each resilience indicator across lactations, stronger genetic correlations were observed between lactations 2 and 3 (0.88-0.96) than between lactations 1 and 2 or 3 (0.34-0.88) for dPert, LnVar, and rauto. For the pairwise comparisons of different resilience indicators within each lactation, dPert had the strongest genetic correlations with wfPert (0.64) and rauto (0.53) in lactation 1, whereas the correlations in lactations 2 and 3 were more variable and showed relatively high standard errors. The genetic correlation results indicated that different resilience indicators across lactations might capture additional biological mechanisms and should be considered as different traits in genetic evaluations. We also observed favorable genetic correlations of these resilience indicators with longevity and Net Merit index, but further biological validation of these resilience indicators is needed. In conclusion, this study provided genetic parameter estimates for different resilience indicators derived from daily milk yields across the first 3 lactations in Holstein cattle, which will be useful when potentially incorporating these traits in dairy cattle breeding schemes.

Genomic-based genetic parameters for milkability traits derived from automatic milking systems in North American Holstein cattle.

The number of dairy farms adopting automatic milking systems (AMS) has considerably increased around the world aiming to reduce labor costs, improve cow welfare, increase overall performance, and generate a large amount of daily data, including production, behavior, health, and milk quality records. In this context, this study aimed to (1) estimate genomic-based variance components for milkability traits derived from AMS in North American Holstein cattle based on random regression models; and (2) derive and estimate genetic parameters for novel behavioral indicators based on AMS-derived data. A total of 1,752,713 daily records collected using 36 milking robot stations and 70,958 test-day records from 4,118 genotyped Holstein cows were used in this study. A total of 57,600 SNP remained after quality control. The daily-measured traits evaluated were milk yield (MY, kg), somatic cell score (SCS, score unit), milk electrical conductivity (EC, mS), milking efficiency (ME, kg/min), average milk flow rate (FR, kg/min), maximum milk flow rate (FRM, kg/min), milking time (MT, min), milking failures (MFAIL), and milking refusals (MREF). Variance components and genetic parameters for MY, SCS, ME, FR, FRM, MT, and EC were estimated using the AIREMLF90 software under a random regression model fitting a third-order Legendre orthogonal polynomial. A threshold Bayesian model using the THRGIBBS1F90 software was used for genetically evaluating MFAIL and MREF. The daily heritability estimates across days in milk (DIM) ranged from 0.07 to 0.28 for MY, 0.02 to 0.08 for SCS, 0.38 to 0.49 for EC, 0.45 to 0.56 for ME, 0.43 to 0.52 for FR, 0.47 to 0.58 for FRM, and 0.22 to 0.28 for MT. The estimates of heritability (± SD) for MFAIL and MREF were 0.02 ± 0.01 and 0.09 ± 0.01, respectively. Slight differences in the genetic correlations were observed across DIM for each trait. Strong and positive genetic correlations were observed among ME, FR, and FRM, with estimates ranging from 0.94 to 0.99. Also, moderate to high and negative genetic correlations (ranging from -0.48 to -0.86) were observed between MT and other traits such as SCS, ME, FR, and FRM. The genetic correlation (± SD) between MFAIL and MREF was 0.25 ± 0.02, indicating that both traits are influenced by different sets of genes. High and negative genetic correlations were observed between MFAIL and FR (-0.58 ± 0.02) and MFAIL and FRM (-0.56 ± 0.02), indicating that cows with more MFAIL are those with lower FR. The use of random regression models is a useful alternative for genetically evaluating AMS-derived traits measured throughout the lactation. All the milkability traits evaluated in this study are heritable and have demonstrated selective potential, suggesting that their use in dairy cattle breeding programs can improve dairy production efficiency in AMS.

Effects of feeding Saccharomyces cerevisiae fermentation postbiotic on the fecal microbial community of Holstein dairy calves.

BACKGROUND: The livestock industry is striving to identify antibiotic alternatives to reduce the need to use antibiotics. Postbiotics, such as Saccharomyces cerevisiae fermentation product (SCFP), have been studied and proposed as potential non-antibiotic growth promoters due to their effects on animal growth and the rumen microbiome; however, little is known of their effects on the hind-gut microbiome during the early life of calves. The objective of this study was to measure the effect of in-feed SCFP on the fecal microbiome of Holstein bull calves through 4 months of age. Calves (n = 60) were separated into two treatments: CON (no SCFP added) or SCFP (SmartCare®, Diamond V, Cedar Rapids, IA, in milk replacer and NutriTek®, Diamond V, Cedar Rapids, IA, incorporated into feed), and were blocked by body weight and serum total protein. Fecal samples were collected on d 0, 28, 56, 84, and 112 of the study to characterize the fecal microbiome community. Data were analyzed as a completely randomized block design with repeated measures when applicable. A random-forest regression method was implemented to more fully understand community succession in the calf fecal microbiome of the two treatment groups. RESULTS: Richness and evenness of the fecal microbiota increased over time (P < 0.001), and SCFP calves tended to increase the evenness of the community (P = 0.06). Based on random-forest regression, calf age as predicted by microbiome composition was significantly correlated with the calf physiological age (R2 = 0.927, P < 1 × 10-15). Twenty-two "age-discriminatory" ASVs (amplicon sequence variants) were identified in the fecal microbiome that were shared between the two treatment groups. Of these, 6 ASVs (Dorea-ASV308, Lachnospiraceae-ASV288, Oscillospira-ASV311, Roseburia-ASV228, Ruminococcaceae-ASV89 and Ruminoccocaceae-ASV13) in the SCFP group reached their highest abundance in the third month, but they reached their highest abundance in the fourth month in the CON group. All other shared ASVs reached their highest abundance at the same timepoint in both treatment groups. CONCLUSIONS: Supplementation of SCFP altered the abundance dynamics of age discriminatory ASVs, suggesting a faster maturation of some members of the fecal microbiota in SCFP calves compared to CON calves. These results demonstrate the value of analyzing microbial community succession as a continuous variable to identify the effects of a dietary treatment.

Effect of medium-chain fatty acids on growth, health, and immune response of dairy calves.

It is necessary for the dairy industry to reduce calf morbidity and mortality, and the reliance on antibiotics to treat sick calves, to address the growing concern regarding antibiotic resistant bacteria. The primary objective of this study was to evaluate the effect that feeding dairy calves medium-chain fatty acids (MCFA) has on growth performance and health, and the secondary objective was to evaluate the effect of MCFA on energy status around weaning and the adaptive immune response following a vaccine challenge. Thirty-three Holstein bull calves (5 ± 1.6 d of age) were randomly assigned to 1 of 2 treatments. Control (CON) calves were fed milk replacer with no C8:0 or C10:0 oil added and MCFA calves were fed milk replacer with 0.5% of a combination of C8:0 or C10:0 oil added. Body weight and average daily gain were measured weekly. Feed efficiency (gain/feed) and the change in body condition score, hip width, hip height, heart girth, and paunch girth were calculated for the duration of the study. Fecal scores were recorded daily and all medical treatments were documented for the duration of the trial. On d 42, 49, and 56 of the study, a serum sample was collected from each calf and used to measure nonesterified fatty acids, ß-hydroxybutyric acid, insulin, and glucose concentrations to evaluate energy status around weaning. A subset of 11 calves per treatment were enrolled in a vaccine challenge. At 21 ± 1.9 d of age (mean ± standard deviation) calves were vaccinated intramuscularly with 1 mL of endotoxin-free ovalbumin (OVA) mixed with aluminum hydroxide adjuvant. At 42 d of age (±1.9 d), blood samples were collected and used to analyze OVA-specific IgG1 and IgG2, and calves were vaccinated a second time. At 56 d of age (±1.9 d), blood samples were collected to analyze IgG1 and IgG2 as well as IFN-γ and IL-4 secreted from peripheral blood mononuclear cells (PBMC) treated with OVA or phytohemagglutinin. Data were analyzed as a completely randomized design with repeated measures when applicable. A tendency for greater daily fecal score was observed for MCFA calves compared with CON. At d 42 of the study, nonesterified fatty acid concentrations were greater in CON calves compared with MCFA. At 42 and 56 d of age, anti-OVA IgG1 concentrations for CON and MCFA calves were greater than prevaccination samples. This study suggests that feeding MCFA to calves affects the energy status of calves around weaning and vaccinating dairy calves with ovalbumin combined with an aluminum hydroxide adjuvant is an effective way to evaluate the adaptive immune responses.

Technical Note: A procedure to place urinary catheters in 1- and 6-week-old preweaned Holstein heifer calves for the in vivo evaluation of intestinal permeability.

Oral administration of indigestible markers and subsequent urine collection is a useful method to determine in vivo gastrointestinal tract (GIT) permeability in cattle for research purposes. However, urine sampling techniques often rely on total waste collection, which reduces the ability to perform more frequent sampling and obtain accurate volumes and sterile samples. An alternative is urethral catheterization, though the feasibility of this technique has not been thoroughly tested in preweaned Holstein heifer calves. The study objective was to develop a urethral catheter placement procedure in preweaned Holstein heifer calves for continuous and accurate urine collection to evaluate GIT permeability using an indigestible marker. Fifteen Holstein heifer calves had catheters placed at approximately 1 wk (8.0 ± 1.5 d) and 6 wk (40.0 ± 1.5 d) of age. During the procedure, calves were individually housed and restrained. The vulva was sterilized and then a sterile, lubricated speculum was inserted into the vagina. A sterile 0.09 cm diameter guidewire was guided into a lubricated, sterile 10 French Foley catheter. The catheter was inserted at approximately 5 through 7 cm into the urethral opening, guided into the bladder, and the catheter balloon was filled with 10 mL of water. The guidewire was removed, and urine flow confirmed correct placement before a 4-L urinary drainage bag was attached to the catheter. After catheterization (24 h), 1 L of chromium (Cr)-ethylenediaminetetraacetic acid was orally dosed to the calves. Calf health observations were made six times over a 48-h period, and any occurrence of vaginal discharge, tissue discharge in catheter, bleeding, inflammation, or abnormal urine was considered a localized reaction. The proportion of localized reactions for each age group was determined using Microsoft Excel, and the total Cr output was analyzed using PROC GLIMMIX. Localized reactions occurred for 20.0% of the 1-wk-old calves and 13.3% of the 6-wk-old calves. In the first 4 h, urine was collected every 15 min, and there were no overall Cr output differences (P = 0.38; 10.28 ± 3.21 mg Cr) when comparing 1- and 6-wk-old calves. However, 1-wk-old calves tended (P = 0.08) to have greater overall Cr output at 480 min (19.2%) and 1,440 min (41.9%) when compared with 6-wk-old calves. In summary, urinary catheterization is a viable urinary collection method for the determination of in vivo GIT permeability in preweaned Holstein heifer calves.

Neonatal calves are highly susceptible to enteric disease during their first few weeks of life, and enteric disease is the leading cause of preweaning morbidity and mortality. A consequence of enteric disease is greater gastrointestinal tract (GIT) permeability in neonatal calves, which is also influenced by reduced intestinal maturity and environmental factors. Therefore, an accurate and precise method of evaluating GIT permeability in neonatal calves is necessary to develop appropriate treatment and mitigation strategies. The oral administration of indigestible markers and measurement of their presence in urine is an accepted method to determine the total GIT permeability in mature heifers. However, current urine collection methods in preweaned heifer calves may not be reliable. Therefore, the study objective was to develop a urinary catheterization method to collect urine accurately and precisely for the in vivo determination of GIT permeability in 1- and 6-wk-old Holstein heifer calves. It was determined that the urinary catheterization procedure and collection system developed in this study were viable and could be applied when evaluating GIT permeability in preweaned Holstein heifer calves using orally dosed indigestible markers.

Identification of bovine respiratory disease through the nasal microbiome.

BACKGROUND: Bovine respiratory disease (BRD) is an ongoing health and economic challenge in the dairy and beef cattle industries. Multiple risk factors make an animal susceptible to BRD. The presence of Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis in lung tissues have been associated with BRD mortalities, but they are also commonly present in the upper respiratory tract of healthy animals. This study aims to compare the cattle nasal microbiome (diversity, composition and community interaction) and the abundance of BRD pathogens (by qPCR) in the nasal microbiome of Holstein steers that are apparently healthy (Healthy group, n = 75) or with BRD clinical signs (BRD group, n = 58). We then used random forest models based on nasal microbial community and qPCR results to classify healthy and BRD-affected animals and determined the agreement with the visual clinical signs. Additionally, co-occurring species pairs were identified in visually BRD or healthy animal groups. RESULTS: Cattle in the BRD group had lower alpha diversity than pen-mates in the healthy group. Amplicon sequence variants (ASVs) from Trueperella pyogenes, Bibersteinia and Mycoplasma spp. were increased in relative abundance in the BRD group, while ASVs from Mycoplasma bovirhinis and Clostridium sensu stricto were increased in the healthy group. Prevalence of H. somni (98%) and P. multocida (97%) was high regardless of BRD clinical signs whereas M. haemolytica (81 and 61%, respectively) and M. bovis (74 and 51%, respectively) were more prevalent in the BRD group than the healthy group. In the BRD group, the abundance of M. haemolytica and M. bovis was increased, while H. somni abundance was decreased. Visual observation of clinical signs agreed with classification by the nasal microbial community (misclassification rate of 32%) and qPCR results (misclassification rate 34%). Co-occurrence analysis demonstrated that the nasal microbiome of BRD-affected cattle presented fewer bacterial associations than healthy cattle. CONCLUSIONS: This study offers insight into the prevalence and abundance of BRD pathogens and the differences in the nasal microbiome between healthy and BRD animals. This suggests that nasal bacterial communities provide a potential platform for future studies and potential pen-side diagnostic testing.

Effect of circadian system disruption on the concentration and daily oscillations of cortisol, progesterone, melatonin, serotonin, growth hormone, and core body temperature in periparturient dairy cattle.

Metabolic, circadian, sleep, and reproductive systems are integrated and reciprocally regulated, but the understanding of the mechanism is limited. To study this integrated regulation, the circadian timing system was disrupted by exposing late pregnant nonlactating (dry) cows to chronic shifts in the light-dark phase, and rhythms of body temperature and circulating cortisol (CORT), progesterone (P4), serotonin (5HT), melatonin (MEL), and growth hormone (GH) concentrations were measured. Specifically, across 2 identical studies (1 and 2), at 35 d before expected calving (BEC) multiparous cows were assigned to control (CON; n = 24) and exposed to 16 h light and 8 h dark or phase shift (PS; n = 24) treatments and exposed to 6-h light-dark phase shifts every 3 d until parturition. All cows were exposed to control lighting after calving. Blood samples were collected in the first study at 0600 h on d 35 BEC, d 21 BEC, and 2 d before calving, and d 0, 2, 9, 15, and 22 postpartum (PP). A subset of cows (n = 6/group) in study 1 was blood sampled every 4 h over 48 h beginning on d 23 BEC, 9 BEC, and 5 PP. Body temperature was measured every 30 min (n = 8-16/treatment) for 48 h at 23 BEC and 9 BEC in both studies; and at 14 PP and 60 PP only in study 2. Treatment did not affect levels of CORT, GH, or P4 at 0600 h, but overall level of 5HT was lower and MEL higher in PS cows across days sampled. A 2-component versus single-component cosinor model better described [>coefficient of determination (R2);

Effects of feeding Saccharomyces cerevisiae fermentation products on the health of Holstein dairy calves following a lipopolysaccharide challenge.

Before weaning, dairy calves are at high risk for illness, especially respiratory and digestive diseases, which reduces average daily gain, age at first calving, and first-lactation milk production. Although these illnesses are commonly treated with antibiotics, efforts are being made to reduce antibiotic use, due to concerns about antibiotic-resistant bacteria. The objective was to evaluate the effects of Saccharomyces cerevisiae fermentation products (SCFP) on the immune status of calves, following a lipopolysaccharide (LPS) challenge administered just before weaning. Thirty Holstein bull calves were blocked based on initial body weight and then assigned to 1 of 2 study treatments. The control group (CON) was fed a 24% crude protein:17% fat milk replacer (MR) and calf starter with no SCFP added. The SCFP treatment was fed the same 24% crude protein:17% fat MR with 1 g/d of SmartCare (Diamond V) and calf starter with 0.8% NutriTek (Diamond V). SmartCare and NutriTek are both produced from anaerobic fermentation of S. cerevisiae. Calves were offered 2.84 L (12.5% solids) of MR twice daily at 0630 and 1630 h through d 51; from d 52 to 56, calves were fed MR once daily at 0630 h; and calves were weaned on d 57. Calves also received ad libitum access to a texturized calf starter and water. On d 50, a subset of calves (n = 20, 10 calves per treatment) were enrolled in an LPS challenge. At -1.5, -0.5, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 5, 6, 7, 8, and 24 h relative to dosing with LPS, 20 mL of blood was collected, and rectal temperature and respiration rate were measured for each calf. Blood serum samples were analyzed for interleukin 6, TNF-α (tumor necrosis factor-α), interferon-gamma, haptoglobin, serum amyloid-A, fibrinogen, nonesterified fatty acid, cortisol, and glucose. This study observed increased concentrations of TNF-α at 1 h and 1.5 h and glucose at 0.5 h after dosing with LPS in SCFP calves compared with CON. Calves supplemented with SCFP also had an increase in respiration rate 0.5 h after dosing with LPS and reduced feed intake the day of the challenge compared with CON calves. These results suggest that dairy calves supplemented with SCFP exhibit an increased acute immune response, as observed by increased TNF-α, glucose, and respiration rate immediately after dosing with LPS, compared with CON calves.

Transcriptome analysis reveals disruption of circadian rhythms in late gestation dairy cows may increase risk for fatty liver and reduced mammary remodeling.

Circadian disruption increased insulin resistance and decreased mammary development in late gestation, nonlactating (dry) cows. The objective was to measure the effect of circadian disruption on transcriptomes of the liver and mammary gland. At 35 days before expected calving (BEC), multiparous dry cows were assigned to either control (CON) or phase-shifted treatments (PS). CON was exposed to 16-h light and 8-h dark. PS was exposed to 16-h light to 8-h dark, but phase of the light-dark cycle was shifted 6 h every 3 days. On day 21 BEC, liver and mammary were biopsied. RNA was isolated (n = 6 CON, n = 6 PS per tissue), and libraries were prepared and sequenced using paired-end reads. Reads mapping to bovine genome averaged 27 ± 2 million and aligned to 14,222 protein-coding genes in liver and 15,480 in mammary analysis. In the liver, 834 genes, and in the mammary gland, 862 genes were different (nominal P < 0.05) between PS and CON. In the liver, genes upregulated in PS functioned in cholesterol biosynthesis, endoplasmic reticulum stress, wound healing, and inflammation. Genes downregulated in liver function in cholesterol efflux. In the mammary gland, genes upregulated functioned in mRNA processing and transcription and downregulated genes encoded extracellular matrix proteins and proteases, cathepsins and lysosomal proteases, lipid transporters, and regulated oxidative phosphorylation. Increased cholesterol synthesis and decreased efflux suggest that circadian disruption potentially increases the risk of fatty liver in cows. Decreased remodeling and lipid transport in mammary may decrease milk production capacity during lactation.

Relative Late Gestational Muscle and Adipose Thickness Reflect the Amount of Mobilization of These Tissues in Periparturient Dairy Cattle.

Due to insufficient dry matter intake and heightened nutrient requirements in early lactation, periparturient dairy cows mobilize adipose and muscle tissues to bridge energy and amino acid gaps, respectively. Our objective was to evaluate the relationship between the relative muscle thickness of late pregnant cows and their early lactation performance. At 35 d before expected calving (BEC), longissimus dorsi muscle thickness (LDT) was measured in forty-one multiparous Holstein cows via ultrasound. Tissue mobilization was evaluated via ultrasound images of LDT and backfat thickness (BFT) at 21 and 7 d BEC as well as at 0, 10, 30, and 60 DIM. Plasma concentrations of 3-methylhistidine (3-MH), creatinine (CRE), non-esterified fatty acids (NEFA), and ß-hydroxybutyrate (BHB) were evaluated weekly. Milk yield and milk component data were collected through 60 DIM. Cattle were assigned post hoc to high-muscle (HM; n = 20; LDT > 4.49 cm) or low-muscle (LM; n = 21; ≤4.37 cm) groups, with mean LDT at 35 d BEC greater in HM (5.05 ± 0.49) than in LM (3.52 ± 0.65) animals. Between 35 and 21 d BEC, LM cows gained LDT, whereas HM cows gained BFT. HM cows mobilized more muscle from 21 d BEC to 30 DIM, as reflected by a greater loss of LDT, greater 3-MH concentrations (532 vs. 438 ± 30 ng/mL), and a greater 3-MH:CRE ratio (0.164 vs. 0.131 ± 0.008) in the first three weeks postpartum. The LDT and BFT at 21 d BEC were related to the amount of respective tissue mobilized through 30 DIM (R2 = 0.37 and 0.88, respectively). Although calves born to HM cattle were larger (45.2 vs. 41.8 ± 0.7 kg), HM cows produced less milk (38.8 vs. 41.6 ± 0.8 kg/d) with a tendency towards higher fat content (4.33 vs. 4.05 ± 0.12%), likely related to the mobilization of more backfat from 0 to 60 DIM (1.78 vs. 0.68 ± 0.34 mm), compared to LM cattle. These findings suggest that a cow's metabolic status, as measured by LDT and BFT prepartum, may influence the metabolic strategy the animal uses to meet energy and amino acid requirements in late gestation and early lactation.