The objective of this study was to identify alterations in the vaginal discharge (VD) metabolome and potential biomarkers to predict metritis development and a cure in dairy cows. This prospective cohort study was conducted on two dairies located in CA and TX. Vaginal discharge was evaluated and collected using the Metricheck^® device. Cows were examined for metritis at 4, 7, and 9 days in milk (DIM). Cows with a fetid, watery, and reddish-brown uterine discharge were classified as having metritis and randomized to receive ceftiofur (n = 10) or remain untreated (n = 7). A cure was defined as the absence of a fetid, watery, reddish-brown uterine discharge at 14 d after enrollment. Vaginal discharge samples were collected from 86 cows within 6 h after parturition, at 4 and 7 DIM, at metritis diagnosis, and at 4 and 7 days after metritis diagnosis. Cows with metritis (MET; n = 17) were paired with counterparts without metritis (HTH) of a similar DIM and parity (n = 34). The uterine metabolome was evaluated using untargeted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Metabolomic data were analyzed using the MetaboAnalyst 5.0. Data were log-transformed and auto-scaled for normalization. Univariate analyses, including the fold-change, were performed to identify the metabolites linked to metritis development and its cure and principal component analysis and partial least squares discriminant analysis were performed to explain metabolite variance between animals developing or not developing metritis and being cured or not being cured of metritis. Comparing HTH with MET cows at calving, 12 metabolites were upregulated, and one was downregulated. At four and seven DIM, 51 and 74 metabolites, respectively, were altered between MET and HTH cows. After metritis development, three and five metabolites were upregulated in cows that were cured and in cows that received treatment and were cured, respectively. In all scenarios, the metabolites lignoceric, malic, and maleic acids, ornithine, and hypotaurine, which are associated with arginine/aminoacyl-tRNA biosynthesis and taurine/purine metabolism, were upregulated in HTH cows. Metritis was associated with changes in the uterine metabolome. Cows not being cured of metritis had changes in the uterus metabolome independent of receiving ceftiofur or remaining untreated. Metabolome analysis may be an important tool to understand the vaginal discharge changes during postpartum and the dynamics of metritis development and cures and help to identify biomarkers to predict metritis being cured.

Bovine respiratory disease (BRD) remains a costly challenge to the dairy industry, as the bacterial complex involved in BRD has shown decreased susceptibility to antimicrobials, exacerbating its effects on animal health, productivity, and recovery. In human medicine, cumulative antimicrobial susceptibility testing (CAST) is used to generate antibiograms that support empirical decision-making for antimicrobial treatment. The goal of this study was to evaluate a CAST framework for BRD in dairy cattle and factors of relevance when analyzing and reporting antibiogram data for on-farm treatment decisions. For this purpose, a repeated cross-sectional study was conducted using criteria adapted from the Clinical Laboratory Standards Institute for the collection, analysis, and presentation of CAST data. From 3 dairy farms in California, calves, heifers, and cows were sampled using deep nasopharyngeal swabs for culture and antimicrobial susceptibility testing for Pasteurella multocida and Mannheimia haemolytica. Antimicrobial susceptibility testing was performed using the minimum inhibitory concentration approach for 12 antimicrobial drugs of relevance to dairy cattle. The variability in the odds of nonsusceptible isolates was evaluated for effects of age group, farm, and season using a logistic regression model in SAS. The antimicrobial susceptibility of co-occurring P. multocida and M. haemolytica isolates were evaluated using Pearson chi-squared and Cohen's kappa in SAS. Overall, P. multocida isolates were mostly nonsusceptible to tetracycline (74%) and spectinomycin (46%), whereas M. haemolytica isolates were frequently nonsusceptible to penicillin (43%) and tetracycline (34%). There were increased odds of nonsusceptible isolates across farms and age groups, with calves and heifers showing a higher number of nonsusceptible isolates than cows. For P. multocida, isolates nonsusceptible to tetracycline and spectinomycin were affected by age group, with calves showing greater odds of nonsusceptibility to antimicrobials. The farm effect was significantly associated with P. multocida nonsusceptible to all antimicrobials but penicillin, suggesting individual farm management practices may heavily affect profiles of nonsusceptible BRD bacteria. Similarly, nonsusceptible M. haemolytica was consistently associated with farm for macrolides and tetracyclines and with age, with heifers showing the greatest odds of being nonsusceptible when compared with cows. Season did not affect the nonsusceptibility of either pathogen, suggesting that either California seasonal patterns or other factors, such as farm practices and animal management, play a more prominent role in the change of susceptibility profile. Overall, these findings highlight the potential effects of farm and age when interpreting data from CAST reports for BRD, where these and other factors should be considered when analyzing and presenting antibiogram reports.

Effective isolation of bacterial pathogens for bovine respiratory disease (BRD) is a critical step for accurate diagnosis of the agent associated with this disease on the dairy. Limited information is available on factors associated with herd-level bacterial pathogen recovery for BRD clinical cases, which are important data to help identify strategies to support the successful collection of a minimum number of each organism over time to generate cumulative antibiogram susceptibility testing reports. Our objective was to evaluate factors associated with the recovery of common pathobionts (Pasteurella multocida and Mannheimia haemolytica) in BRD clinical cases from preweaning calves, heifers, and cows at 3 California dairy farms over 2 yr. A second objective was to test the predictability of isolating these organisms in BRD clinical cases using the factors evaluated in the first objective utilizing machine learning (ML). During monthly herd visits, deep nasopharyngeal samples were collected from calves, heifers, and cows diagnosed with BRD over 2 yr. Samples were cultured in aerobic conditions, and pathogens were isolated through colony morphology and validated with MALDI-TOF MS. Evaluation of factors influencing bacterial recovery was initially tested for independence, followed by a logistic regression model and a stepwise logistic feature selection in SAS, and ML classifiers with leave-one-out cross-validation in Python packages. For our study, samples were collected from a total of 301 BRD clinical cases: 152 samples with a culture-positive for P. multocida, 63 samples with a culture-positive for M. haemolytica, and 3 samples with a culture-positive for Histophilus somni. For factors associated with the culture-positive of P. multocida in BRD clinical cases, an interaction between age and season was identified, where cows had overall lower odds of being culture-positive independently of the season when compared with calves in the spring and summer and heifers in the fall and winter. For factors associated with the culture-positive of M. haemolytica in BRD clinical cases, an interaction was also observed between age and season, but the farm further played a role in the odds of being culture-positive, with one farm having considerably greater odds than the remaining ones. Machine learning models with cross-validation showed a weak ability to distinguish positive from negative cases when using age, season, and farm for all scenarios according to F1-scores and receiver operating characteristic analysis. Differences in predictive abilities, factor importance, and the still limited number of predictors in these ML analyses further indicate a potential for building more robust future models once datasets are expanded and more robust algorithms are considered. Overall, correctly identifying factors that may be associated with the prevalence of BRD pathogens and, therefore, recovery of these pathogens is critical for the development of antibiogram programs for evaluation of the antimicrobial susceptibility of BRD pathogens.

Multidrug-resistant (MDR) bovine respiratory pathogens can significantly decrease treatment success and have an effect on dairy farm productivity. Although antibiograms have emerged as a tool to support empirical decision making for disease treatment, the prevalence of MDR isolates on a farm can have a negative effect on the selection of the best antibiotic treatment using antibiogram data. This study aimed to characterize the MDR profile of Pasteurella multocida and Mannheimia haemolytica isolates from the deep nasopharyngeal swabs of calves, heifers, and cows diagnosed with bovine respiratory disease (BRD) over 2 yr. For this purpose, animals were sampled in a repeated cross-sectional study from 3 large dairy farms in Northern California. From this study, a total of 146 P. multocida and 63 of M. haemolytica isolates were isolated and tested for antimicrobial susceptibility. Our results showed that, overall, a small fraction of the animals in the study had MDR P. multocida (15%) and M. haemolytica (17%). The prevalence of MDR P. multocida isolates was comparable between calves (14%), heifers (19%), and cows (12%), whereas MDR M. haemolytica was most prevalent in heifers (40%) followed by calves (4%). No MDR M. haemolytica was detected in the isolates from cows. Farm effect had the most significant association with MDR BRD pathogens, with 1 farm accounting for 94% of all MDR isolates of the study, while season had a minor association with MDR. The most common antimicrobial resistance drug classes across MDR pathogens were macrolides, phenicols, quinolones, and tetracyclines. Prevalence of resistant isolates to tetracyclines represented the greatest disparity between the 2 BRD pathogens evaluated, with P. multocida isolates having a higher percentage of resistance (71.8%) when compared with M. haemolytica (22.2%). In conclusion, there was a low prevalence of MDR in both P. multocida and M. haemolytica in the study, but farm management and the age of the animals increased the odds of MDR prevalence. These factors should be considered when generating antibiogram reports for BRD treatment to account for the potential prevalence of MDR isolates.