The impact of kit, environment, and sampling contamination on the observed microbiome of bovine milk.

In low-microbial biomass samples such as bovine milk, contaminants can outnumber endogenous bacteria. Because of this, milk microbiome research suffers from a critical knowledge gap, namely, does non-mastitis bovine milk contain a native microbiome? In this study, we sampled external and internal mammary epithelia and stripped and cisternal milk and used numerous negative controls, including air and sampling controls and extraction and library preparation blanks, to identify the potential sources of contamination. Two algorithms were used to mathematically remove contaminants and track the potential movement of microbes among samples. Results suggest that the majority (i.e., >75%) of sequence data generated from bovine milk and mammary epithelium samples represents contaminating DNA. Contaminants in milk samples were primarily sourced from DNA extraction kits and the internal and external skin of the teat, while teat canal and apex samples were mainly contaminated during the sampling process. After decontamination, the milk microbiome displayed a more dispersed, less diverse, and compositionally distinct bacterial profile compared with epithelial samples. Similar microbial compositions were observed between cisternal and stripped milk samples, as well as between teat apex and canal samples. Staphylococcus and Acinetobacter were the predominant genera detected in milk sample sequences, and bacterial culture showed growth of Staphylococcus and Corynebacterium spp. in 50% (7/14) of stripped milk samples and growth of Staphylococcus spp. in 7% (1/14) of cisternal milk samples. Our study suggests that microbiome data generated from milk samples obtained from clinically healthy bovine udders may be heavily biased by contaminants that enter the sample during sample collection and processing workflows.IMPORTANCEObtaining a non-contaminated sample of bovine milk is challenging due to the nature of the sampling environment and the route by which milk is typically extracted from the mammary gland. Furthermore, the very low bacterial biomass of bovine milk exacerbates the impacts of contaminant sequences in downstream analyses, which can lead to severe biases. Our finding showed that bovine milk contains very low bacterial biomass and each contamination event (including sampling procedure and DNA extraction process) introduces bacteria and/or DNA fragments that easily outnumber the native bacterial cells. This finding has important implications for our ability to draw robust conclusions from milk microbiome data, especially if the data have not been subjected to rigorous decontamination procedures. Based on these findings, we strongly urge researchers to include numerous negative controls into their sampling and sample processing workflows and to utilize several complementary methods for identifying potential contaminants within the resulting sequence data. These measures will improve the accuracy, reliability, reproducibility, and interpretability of milk microbiome data and research.

Exploring associations between the teat apex metagenome and Staphylococcus aureus intramammary infections in primiparous cows under organic directives.

The primary objective of this study was to identify associations between the prepartum teat apex microbiome and the presence of Staphylococcus aureus intramammary infections (IMI) in primiparous cows during the first 5 weeks after calving. We performed a case-control study using shotgun metagenomics of the teat apex and culture-based milk data collected longitudinally from 710 primiparous cows on five organic dairy farms. Cases had higher odds of having S. aureus metagenomic DNA on the teat apex prior to parturition compared to controls (OR = 38.9, 95% CI: 14.84-102.21). Differential abundance analysis confirmed this association, with cases having a 23.8 higher log fold change (LFC) in the abundance of S. aureus in their samples compared to controls. Of the most prevalent microorganisms in controls, those associated with a lower risk of post-calving S. aureus IMI included Microbacterium phage Min 1 (OR = 0.37, 95% CI: 0.25-0.53), Corynebacterium efficiens (OR = 0.53, 95% CI: 0.30-0.94), Kocuria polaris (OR = 0.54, 95% CI: 0.35-0.82), Micrococcus terreus (OR = 0.64, 95% CI: 0.44-0.93), and Dietzia alimentaria (OR = 0.45, 95% CI: 0.26-0.75). Genes encoding for Microcin B17 AMPs were the most prevalent on the teat apex of cases and controls (99.7% in both groups). The predicted abundance of genes encoding for Microcin B17 was also higher in cases compared to controls (LFC 0.26). IMPORTANCE: Intramammary infections (IMI) caused by Staphylococcus aureus remain an important problem for the dairy industry. The microbiome on the external skin of the teat apex may play a role in mitigating S. aureus IMI risk, in particular the production of antimicrobial peptides (AMPs) by commensal microbes. However, current studies of the teat apex microbiome utilize a 16S approach, which precludes the detection of genomic features such as genes that encode for AMPs. Therefore, further research using a shotgun metagenomic approach is needed to understand what role prepartum teat apex microbiome dynamics play in IMI risk.

Randomized clinical trial evaluating the effects of administering acidogenic boluses at dry-off on udder health, milk yield, and herd removal.

Acidogenic boluses can mitigate potential negative effects of high milk yield at dry-off on udder health. This randomized controlled trial aimed to investigate the effect of administering acidogenic boluses at dry-off on dry period intramammary infection (IMI) dynamics and on milk production parameters, somatic cell count linear score (LSCC), clinical mastitis (CM), and herd removal in the next lactation. A total of 901 cows from 3 dairy farms were randomly allocated to a control (CON, n = 458; no administration of acidogenic boluses at dry-off) or treatment group (TRT, n = 443; administration of 2 acidogenic boluses at dry-off). Quarter milk samples were collected at dry-off and after calving and submitted for bacteriological milk culture. The effects of treatment on the presence of quarter-level postpartum IMI, cure of existing IMI, and acquisition of new IMI, and on the prevalence of cow-level high LSCC (LSCC ≥4) in the first 30 days in milk (DIM) were analyzed using mixed effects logistic regression. Mixed linear regression was used to analyze cow-level milk production parameters (i.e., milk yield, fat corrected milk, fat and protein yield, and LSCC) in the first 90 DIM and until 300 DIM. For CM and herd removal, Cox proportional hazard regression models were used. In addition to treatment group, lactation group at dry-off, presence of high LSCC in the last test-day, average milk yield in the week before dry-off, presence of CM in the lactation of enrollment, and biologically relevant interactions were offered in all models. There was no evidence of a difference in IMI dynamics or in milk, fat corrected milk, protein or fat yields in the subsequent lactation between groups. The TRT group had a lower LSCC in the first 2 mo postpartum compared with the CON group (2.58 ± 0.3 vs. 2.92 ± 0.3 and 2.42 ± 0.3 vs. 2.81 ± 0.3, for first and second month postpartum). The prevalence of high LSCC in the first 30 DIM was 9.1% lower in the TRT compared with the CON group (16.3% vs. 25.5%; risk difference: -9.2; 95% confidence interval [CI]: -15.8, -2.5). Cows in the TRT group exhibited reduced hazards of CM in the subsequent lactation compared with cows in the CON group (hazard ratio: 0.75; 95% CI: 0.63, 0.89) as well as a reduced hazard of herd removal (hazard ratio: 0.82, 95% CI: 0.77, 0.88). The administration of acidogenic boluses as a component of dry-off management is a promising approach to maintain good udder health and reduce the hazard of CM and herd removal during the subsequent lactation.

Metabolic-digestive clinical disorders of lactating dairy cows were associated with alterations of rumination, physical activity, and lying behavior monitored by an ear-attached sensor.

The objective of this observational cohort study was to characterize the pattern of rumination time (RT), physical activity (PA), and lying time (LT) monitored by an automated health monitoring system, based on an ear-attached sensor, immediately before, during, and after clinical diagnosis (CD) of metabolic-digestive disorders. Sensor data were collected from 820 lactating Holstein cows monitored daily from calving up to 21 DIM for detection of health disorders (HD). Cows were grouped retrospectively in the no-clinical health disorder group (NCHD; n = 616) if no HD were diagnosed, or the metabolic-digestive group (METB-DIG; n = 58) if diagnosed with clinical ketosis or indigestion only. Cows with another clinical health disorder within -7 to +7 d of CD of displaced abomasum, clinical ketosis, or indigestion were included in the metabolic-digestive plus one group (METB-DIG+1; n = 25). Daily RT, PA, and LT, and absolute and relative changes within -7 to +7 d of CD were analyzed with linear mixed models with or without repeated measures. Rumination time and PA were smaller, and LT was greater for the METB-DIG and METB-DIG+1 group than for cows in the NCHD group for most days from -7 to +7 d of CD of HD. In general, daily RT, PA, and LT differences were larger between the METB-DIG+1 and NCHD groups than between the METB-DIG and NCHD groups. In most cases, RT and PA decreased to a nadir and LT increased to a peak immediately before or after CD of HD, with a return to levels similar to the NCHD group within 7 d of CD. Absolute values and relative changes from 5 d before CD to the day of the nadir for RT and PA or peak for LT were different for cows in the METB-DIG and METB-DIG+1 group than for the NCHD group. For PA, the METB-DIG+1 group had greater changes than the METB-DIG group. For cows affected by metabolic-digestive disorders, RT, PA, and LT on the day of CD and resolution of clinical signs were different than for cows in the NCHD group, but an increase in RT and PA or a decrease in LT was observed from the day of CD to the day of resolution of clinical signs. We conclude that dairy cows diagnosed with metabolic-digestive disorders including displaced abomasum, clinical ketosis, and indigestion presented substantial alterations in the pattern of RT, PA, and LT captured by an ear-attached sensor. Thus, automated health monitoring systems based on ear-attached sensors might be used as an aid for identifying cows with metabolic-digestive disorders. Moreover, RT, PA, and LT changes after CD might be positive indicators of recovery from metabolic-digestive disorders.

Metritis and clinical mastitis events in lactating dairy cows were associated with altered patterns of rumination, physical activity, and lying behavior monitored by an ear-attached sensor.

Understanding changes in parameters recorded by automated health monitoring systems based on ear-attached sensors on the days immediately before and after diagnosis of metritis and clinical mastitis can help develop dairy cow health monitoring strategies. The objective of this observational cohort study was to characterize rumination time, physical activity, and lying time monitored by an ear-attached sensor before, during, and after clinical diagnosis (CD) of metritis and clinical mastitis. Lactating Holsteins monitored daily for 21 d in milk for detection of health disorders were retrospectively included in the no clinical health disorder group (NCHD; n = 616) if no disorders were diagnosed. Cows were included in the metritis (MET; n = 69) or clinical mastitis (MAST; n = 36) group if diagnosed only with nonsevere metritis (watery, reddish, and fetid uterine discharge with or without pyrexia) or nonsevere clinical mastitis (visibly abnormal milk secretion with or without signs of udder inflammation, with no pyrexia and no systemic signs of disease), respectively. Cows diagnosed with severe metritis (signs of metritis plus systemic signs of disease) or severe clinical mastitis (signs of mastitis plus pyrexia and systemic signs of disease), and cows diagnosed with nonsevere metritis or clinical mastitis plus another disorder within -7 to +7 d of CD of metritis or clinical mastitis diagnosis, were included in the metritis plus (MET+; n = 25) or the clinical mastitis plus (MAST+; n = 15) group, respectively. Cows were fitted with an ear-attached accelerometer to measure rumination time, physical activity, and lying time. Mean daily values, mean value absolute change, and relative change for the mean daily value from 3 or 5 d before CD to the nadir for cows with metritis and clinical mastitis, respectively, were analyzed with linear mixed models with or without repeated measures. Rumination time and physical activity were lesser, and lying time was greater for the MET and MET+ groups than for the NCHD group for most days from -4 to +7 d of CD of metritis. Generally, daily rumination time, physical activity, and lying time differences were greater and more prolonged between the MET+ and NCHD than between the MET and NCHD groups. Similarly, cows in the MAST and MAST+ groups had lesser rumination time and physical activity than cows in the NCHD group for several days before diagnosis. Lying time was greater for the MAST+ than the NCHD group on d -1 and 0 relative to CD. Absolute values and relative changes from 3 d before CD to the day of the nadir for rumination time and physical activity, or peak for lying time, were different for cows in the MET and MET+ groups than for the NCHD group. Similar results were observed for the MAST and MAST+ groups compared with the NCHD group. For cows with metritis, either an increase in rumination time and physical activity or a decrease in lying time was observed from the day of CD to resolution of clinical signs, but no changes were observed for the NCHD. Cows with clinical mastitis and the NCHD group had different rumination times, physical activity, and lying times on the day of CD and resolution of clinical signs, but cows with clinical mastitis had no significant changes from the day of CD to resolution of clinical signs. We conclude that cows affected by metritis and clinical mastitis presented substantial alterations of the patterns of rumination time, physical activity, and lying time captured by an ear-attached sensor. Thus, automated health monitoring systems based on ear-attached sensors might be used as an aid for identifying cows with metritis and clinical mastitis. Moreover, behavioral parameter changes after CD might be good indicators of resolution of clinical signs of metritis but not mastitis.