Different cellular and molecular responses of Bovine milk phagocytes to persistent and transient strains of Streptococcus uberis causing mastitis.

Streptococcus uberis is frequently isolated from milk collected from dairy cows with mastitis. According to the host's immunity, bacterial virulence, and their interaction, infection with some strains can induce persistent subclinical inflammation, while infection with others induces severe inflammation and transient mastitis. This study compared the inflammatory response of milk-isolated white blood cells (mWBCs) to persistent and transient S. uberis strains. Quarter milk samples were collected aseptically for bacterial culture from all lactating cows once a week over a 10-week period. A transient and noncapsular strain with a 1-week intramammary infection duration was selected from this herd, while a persistent and capsular S. uberis strain with an intramammary infection longer than 2 months from our previous study was selected based on an identical pulse field gel electrophoresis pattern during the IMI episode. Cellular and molecular responses of mWBCs were tested, and the data were analyzed using repeated analysis of variance. The results showed a higher response in migration, reactive oxygen species generation, and bacterial killing when cells were stimulated with transient S. uberis. In contrast, the persistent strain led to increased neutrophil extracellular trap release. This study also highlighted several important molecular aspects of mWBCs. Gene expression analyses by real-time RT-PCR revealed a significant elevation in the expression of Toll-like receptors (TLR-1, TLR-2, TLR-6) and proinflammatory cytokines (tumor necrosis factor-alpha or TNF-α) with the transient strain. Additionally, Streptococcus uberis capsule formation might contribute to the capability of these strains to induce different immune responses. Altogether, these results focus on the immune function of activated mWBCs which demonstrate that a transient strain can elicit a stronger local immune response and, subsequently, lead to rapid recovery from mastitis.

Evaluation of factors associated with bulk milk somatic cell count and total plate count in Indonesian smallholder dairy farms.

Increasing milk quality in smallholder dairy farms will result in a greater quantity of milk being delivered to milk collection centers, an increased milk price for farmers and consequently an improved farmers' livelihood. However, little research on milk quality has been performed on smallholder farms in Southeast Asia. The objective of this study was to identify risk factors associated with somatic cell count (SCC) and total plate count (TPC) in Indonesian smallholder dairy farms. One dairy cooperative in West Java, Indonesia was selected based on its willingness to participate. All 119 member farmers in the cooperative, clustered in six groups, were interviewed and a bulk milk sample from all farms was collected in April 2022. Risk factors associated with dairy farms' SCC and TPC were investigated using multivariable population-averaged generalized estimating equations (GEE) models. The mean geometric SCC and TPC from these farms were 529,665 cells/mL of milk and 474,492 cfu/mL of milk, respectively. Five risk factors including manure removal frequency, receiving mastitis treatment training, washing the udder using soap, number of workers, and ownership of the pasture area were associated with SCC. Two risk factors, manure removal frequency and dairy income contribution, were associated with TPC. These findings can therefore be used as a starting point to improve udder health and milk quality in Indonesia and other countries where smallholder farmers play a significant role in milk production.

Smallholder milk-quality awareness in Indonesian dairy farms.

In most low- and middle-income countries, milk is produced by smallholders, thereby contributing to the livelihood of their households. With the increasing importance of milk production in these countries, it is essential that milk quality is of a high level to ensure a safe product for consumers. It is, however, unclear whether smallholder dairy farmers are aware of the quality of their milk. The aim of this cross-sectional study was to gain insight on Indonesian smallholder dairy farmer awareness of milk quality parameters and to identify factors associated with the total plate count (TPC) and somatic cell count (SCC). A stratified sampling method was used to select smallholder farms in 4 districts in West Java, Indonesia, that were interviewed between August and September 2017. Factors putatively associated with awareness of TPC were investigated with multinomial regression models, whereas a Firth-type logistic regression was applied to identify factors associated with SCC awareness. Of the total 600 farmers surveyed, 264 (44%), 109 (18%), 170 (28%), 111 (19%), and 23 (4%) farmers were aware of TPC, total solid, fat content, milk density, and SCC, respectively, but did not know its value. Those that were conceptually aware of these quality parameters were generally unaware of their value. Furthermore, this study revealed that the following variables were significantly associated with dairy farmers' awareness of TPC: cooperative to which the farmer belonged, distance to neighboring dairy farmer, technology adoption index, TPC as the most important quality factor for the buyer, milk production information from cooperatives, and cow health information from veterinarians. Similarly, cooperative, dairy business experience, and milk quality test adoption were significantly associated with dairy farmers' awareness of SCC. Cooperative was the only variable that was significant in both final statistical models. This indicates that cooperatives play an important role in increasing farmer awareness of milk quality parameters in these smallholder dairies. This may be valid for other regions in the world also where milk production is dominated by smallholder dairy farmers.

Effects of pathogen-specific clinical mastitis occurrence in the first 100 days of lactation 1 on future mastitis occurrence in Holstein dairy cows: An observational study.

The objective of this observational study was to estimate effects of clinical mastitis (CM) cases caused by different pathogens (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth) occurring in the first 100 d in lactation 1, of a dairy cow on the future rate of occurrence of different types of CM during a cow's full lifetime. The outcomes were occurrence of Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth, after the first 100 d of lactation 1, until a cow's removal through death or sale in that or a subsequent lactation. Data, including information on CM cases, milk production, and event dates (including death or sale dates), were collected from 14,440 cows in 5 New York State Holstein herds from January 2004 until February 2014. Generalized linear mixed models with a Poisson distribution and log link function were fit for each pathogen. The individual cow was the unit of analysis. Escherichia coli was a predictor of future occurrence of E. coli, Klebsiella spp., and CM cases with no growth. Early-occurring Klebsiella spp. was a predictor of future cases of Klebsiella spp. Cases with no growth were predictors of future occurrence of Staphylococcus spp., E. coli, Klebsiella spp., and cases with no growth. Thus, E. coli and cases with no growth occurring early in lactation 1 appear to be consistent risk factors for future cases of CM, whether cases with the same pathogen or a different pathogen. In this study, farm effects on later pathogen occurrence differed somewhat, so treatment protocol and culling strategy may play a role in the findings. Nevertheless, the findings may help farmers in managing young cows with CM in early productive life, especially those with E. coli or cases with no growth, in that they may be more susceptible to future CM cases in their later productive life, thus meriting closer attention.

Association of pathogen-specific clinical mastitis in the first 100 days of first lactation with productive lifetime: An observational study comparing competing risks models for death and sale with the Cox model.

The objective of this observational study was to study the association between clinical mastitis (CM) (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., cases with other treated or other not treated organisms, CM without growth) occurring in a dairy cow's first 100 days (d) of her first lactation and her total productive lifetime, ending in death or sale (for slaughter). Data were collected from 24,831 cows in 5 New York Holstein herds from 2004 to 2014. Two analytical approaches were compared. First, removals (death, sale) were treated as competing events in separate survival analyses, in proportional subdistribution hazards models. In one, death was coded as the event of interest and sale as the competing event; in another, sale was the event of interest and death the competing event. Second, traditional survival analysis (Cox proportional hazards) was conducted. In all models, the time variable was number of days from date of first calving until event (death or sale) date; if the cow was alive at study end, she was censored. Models were stratified by herd. Ten percent of cows died; 48.4 % were sold. In the competing risks analysis, E. coli and CM without growth were associated with death; the former with an increased hazard rate of death, the latter with a lower one. Streptococcus spp., Staph. aureus, Klebsiella spp., cases with other treated or untreated organisms, and CM without growth were associated with higher hazard rates of sale. The Cox proportional hazards model's hazard rates were higher than those in the competing risks model in which death was the event of interest, and resembled those in the model in which sale was the event of interest. Four additional Cox models, omitting dead or sold cows, or censoring each, were also fitted; hazard ratios were similar to the above models. Proportional subdistribution hazards models were appropriate due to competing risks (death, sale); they produce less-biased estimates. A study limitation is that while proportional subdistribution hazards models were appropriate, they have the illogical feature of keeping subjects at risk for the event of interest even after experiencing the competing event. This is, however, necessary in estimating cumulative incidence functions. Another limitation concerns pathogen variability among study farms, implying that CM decisions are farm-specific. Misclassification of 'dead' vs. 'sold' cows was also possible. Nevertheless, the findings may help in optimizing management of cows contracting specific types of CM early in productive lifetime.

Pegbovigrastim treatment resulted in an economic benefit in a large randomized clinical trial in grazing dairy cows.

This randomized controlled trial on 4 commercial grazing dairy farms investigated whether pegbovigrastim (PEG) treatment affected partial net return as calculated from milk revenues and costs for feed, medical treatments [clinical mastitis, uterine disease, and other diseases (i.e., any medical treatment that was not intended for clinical mastitis or uterine disease)], inseminations, and culling during a full lactation in grazing dairy cows. We also explored the effect of potential interactions of PEG treatment with parity, prepartum body condition score, and prepartum nonesterified fatty acids concentration on partial net return, milk revenues, and the costs mentioned above. Holstein cows were randomly assigned to 1 of the 2 following trial arms: a first PEG dose 9.4 ± 0.3 (mean ± standard error) days before the calving date and a second dose within 24 hours after calving (PEG: primiparous = 342; multiparous = 697) compared with untreated controls (control: primiparous = 391; multiparous = 723). The effect of PEG treatment on the outcomes of interest expressed per year was tested using general linear mixed models. Results are presented as least squares means ± standard error. Overall, PEG treatment increased the partial net return, resulting in an economic benefit per cow per year of $210 ± 100. The cost of treatment of clinical mastitis was lower for PEG treated cows compared with control cows ($9 ± 3). The largest nonsignificant difference was seen for the cost of culling; additionally, PEG treatment numerically reduced the cost of culling by $145 ± 77.

Predicting Positive ELISA Results in Dairy Herds with a Preferred Status in a Paratuberculosis Control Program.

Dairy herds participating in the Dutch milk quality assurance program for paratuberculosis are assigned a herd status on the basis of herd examinations by ELISA of individual serum or milk samples, followed by an optional confirmatory fecal PCR. Test-negative herds are assigned Status A; the surveillance of these herds consists of biennial herd examinations. Farmers falsely believing that their Status A herds are Map-free may inadvertently refrain from preventive measures. Therefore, we aimed to develop a predictive model to alert Status A farmers at increased risk of future positive ELISA results. Using data of 8566 dairy herds with Status A in January 2016, two logistic regression models were built, with the probabilities of ≥1 or ≥2 positive samples from January 2017-June 2019 as dependent variables, and province, soil type, herd size, proportion of cattle born elsewhere, time since previous positive ELISA results, and the 95th percentile of the S/P ratios in 2015-2016, as explanatory variables. As internal validation, both models were applied to predict positive ELISA results from January 2019-June 2021, in 8026 herds with Status A in January 2019. The model predicting ≥1 positive sample had an area under the receiver operating characteristics curve of 0.76 (95% CI: 0.75, 0.77). At a cut-off predicted probability πc = 0.40, 25% of Status A herds would be alerted with positive and negative predictive values of 0.52 and 0.83, respectively. The model predicting ≥2 positive samples had lower positive, but higher negative, predictive values. This study indicates that discrimination of Status A herds with high and low risks of future positive ELISA results is feasible. This might stimulate farmers with the highest risks to take additional measures to control any undetected Map infections.

Effect of pegbovigrastim on fertility and culling in grazing dairy cows and its association with prepartum nonesterified fatty acids.

This randomized controlled trial on 4 commercial grazing dairy farms investigated whether treatment with pegbovigrastim (PEG) affected fertility and culling as measured during the full lactation. We also explored the effect of potential interactions of PEG treatment with parity, prepartum body condition score, prepartum nonesterified fatty acid concentration (pre-NEFA), and early-lactation clinical disease on these outcomes. Holstein cows were randomly assigned to 1 of 2 trial arms: a first PEG dose approximately 7 d before the expected calving date and a second dose within 24 h after calving (PEG: primiparous = 342; multiparous = 697) compared with untreated controls (control: primiparous = 391; multiparous = 723). Cox's proportional hazards regression models were used to analyze rate of first insemination, rate of pregnancy [within 150 and 305 d in milk (DIM)], and hazard of culling. Additional analyses were performed on data that were stratified by parity group and pre-NEFA class (low ≤0.3; high >0.3 mM). In high pre-NEFA cows, PEG treatment increased the rate of first insemination [hazard ratio (HR) = 1.15]. Early-lactation clinical mastitis (CM) and uterine disease (UD: retained placenta, metritis, or both) were associated with a reduced rate of pregnancy within 150 DIM (HR = 0.49 and 0.78, respectively). Pegbovigrastim treatment in high pre-NEFA cows with CM and UD increased the rate of pregnancy within 150 DIM (HR = 1.75 and 1.46, respectively). In high pre-NEFA cows, PEG treatment resulted in a lower hazard of culling (HR = 0.79). No treatment effect was detected in low pre-NEFA cows. This study shows that the effect of PEG treatment on fertility and culling interacts with pre-NEFA. In high pre-NEFA cows, PEG treatment increased the rate of first insemination, counteracted the negative association of early-lactation CM and UD with the rate of pregnancy, and decreased the hazard of culling.

Effect of pegbovigrastim on clinical mastitis and uterine disease during a full lactation in grazing dairy cows.

In this randomized controlled trial on four commercial grazing dairy farms, we investigated whether pegbovigrastim (PEG) treatment affects clinical mastitis (CM) and uterine disease (i.e. retained placenta (RP), metritis and endometritis) occurrence during a full lactation. The association of prepartum body condition score and prepartum non-esterified fatty acid (NEFA) concentration with disease occurrence was also evaluated. Holstein cows were randomly assigned to one of two treatments: first PEG dose approximately 7 d before the expected calving date and a second dose within 24 h after calving (PEG) compared to untreated controls (Control). In total, 2,153 animals were included in the study: 733 primiparous cows (Control = 391, PEG = 342) and 1420 multiparous cows (Control = 723, PEG = 697). Treatment effects were evaluated with generalized linear mixed models and Cox's proportional hazard models. Treatment with PEG reduced the occurrence of a first case of CM during the first 30 days in milk (DIM) by 24.6% and reduced the hazard of a first case and the rate of total cases of CM during the full lactation. All PEG treatment effects were independent of parity. Prepartum body condition score interacted with PEG treatment: in over-conditioned cows, PEG reduced the occurrence of a first case of CM during the first 30 DIM by 49.5%. The hazard analysis of a first case of CM during the full lactation suggested that the preventive effect of PEG disappeared with increasing DIM. Treatment with PEG did not affect the occurrence of RP or metritis. Pegbovigrastim treated cows with metritis subsequently showed a reduced occurrence of endometritis compared to control cows with metritis. Pegbovigrastim reduces the occurrence of CM particularly in cows at risk of elevated lipid mobilization, and PEG ameliorates the uterine healing process in cows that experienced metritis.

Who infects whom?-Reconstructing infection chains of Mycobacterium avium ssp. paratuberculosis in an endemically infected dairy herd by use of genomic data.

Recent evidence of circulation of multiple strains within herds and mixed infections of cows marks the beginning of a rethink of our knowledge on Mycobacterium avium ssp. paratuberculosis (MAP) epidemiology. Strain typing opens new ways to investigate MAP transmission. This work presents a method for reconstructing infection chains in a setting of endemic Johne's disease on a well-managed dairy farm. By linking genomic data with demographic field data, strain-specific differences in spreading patterns could be quantified for a densely sampled dairy herd. Mixed infections of dairy cows with MAP are common, and some strains spread more successfully. Infected cows remain susceptible for co-infections with other MAP genotypes. The model suggested that cows acquired infection from 1-4 other cows and spread infection to 0-17 individuals. Reconstructed infection chains supported the hypothesis that high shedding animals that started to shed at an early age and showed a progressive infection pattern represented a greater risk for spreading MAP. Transmission of more than one genotype between animals was recorded. In this farm with a good MAP control management program, adult-to-adult contact was proposed as the most important transmission route to explain the reconstructed networks. For each isolate, at least one more likely ancestor could be inferred. Our study results help to capture underlying transmission processes and to understand the challenges of tracing MAP spread within a herd. Only the combination of precise longitudinal field data and bacterial strain type information made it possible to trace infection in such detail.

Increase in white blood cell counts by pegbovigrastim in primiparous and multiparous grazing dairy cows and the interaction with prepartum body condition score and non-esterified fatty acids concentration.

The objective of this study was to determine if parity affected the effect of pegbovigrastim (PEG) treatment on white blood cell (WBC) counts in grazing dairy cows. Additionally, the association of prepartum body condition score (BCS) and non-esterified fatty acid (Pre-NEFA) concentration with WBC counts was investigated. The effect of early-lactation disease was included in the statistical analysis. A randomized controlled trial on four commercial grazing dairy farms was performed. Holstein primiparous (Control = 87, PEG = 89) and multiparous (Control = 181, PEG = 184) cows were randomly assigned to one of two treatments: first PEG dose 8 ± 5 (mean ± SD) days before the expected calving date and a second dose within 24 h after calving (PEG) compared to untreated controls (Control). Treatment effects were evaluated with mixed linear regression models. Treatment with PEG increased WBC, neutrophil, lymphocyte and monocyte counts at 6 ± 1 (mean ± SD) days in milk. Parity, BCS and their interactions with treatment were not associated with WBC counts. In control cows, Pre-NEFA concentration was associated with reduced WBC, neutrophil and lymphocyte counts and tended to be associated with reduced monocyte counts. Pegbovigrastim treatment reversed the negative association of Pre-NEFA concentration with neutrophil and monocyte counts and tended to reverse the negative association of Pre-NEFA concentration with WBC counts. In the PEG treated group, cows diagnosed with retained placenta or metritis showed lower neutrophil counts when compared to PEG treated cows without these clinical diseases. These data confirm that PEG treatment increases WBC, neutrophil, lymphocyte and monocyte counts in grazing dairy cows and that this effect is independent of parity. Pegbovigrastim treatment reversed the negative association of Pre-NEFA concentration with neutrophil and monocyte counts, and tended to reverse the negative association of Pre-NEFA concentration with WBC counts.

Characterizing infectious disease progression through discrete states using hidden Markov models.

Infectious disease management relies on accurate characterization of disease progression so that transmission can be prevented. Slowly progressing infectious diseases can be difficult to characterize because of a latency period between the time an individual is infected and when they show clinical signs of disease. The introduction of Mycobacterium avium ssp. paratuberculosis (MAP), the cause of Johne's disease, onto a dairy farm could be undetected by farmers for years before any animal shows clinical signs of disease. In this time period infected animals may shed thousands of colony forming units. Parameterizing trajectories through disease states from infection to clinical disease can help farmers to develop control programs based on targeting individual disease state, potentially reducing both transmission and production losses due to disease. We suspect that there are two distinct progression pathways; one where animals progress to a high-shedding disease state, and another where animals maintain a low-level of shedding without clinical disease. We fit continuous-time hidden Markov models to multi-year longitudinal fecal sampling data from three US dairy farms, and estimated model parameters using a modified Baum-Welch expectation maximization algorithm. Using posterior decoding, we observed two distinct shedding patterns: cows that had observations associated with a high-shedding disease state, and cows that did not. This model framework can be employed prospectively to determine which cows are likely to progress to clinical disease and may be applied to characterize disease progression of other slowly progressing infectious diseases.

Dynamics of somatic cell count patterns as a proxy for transmission of mastitis pathogens.

Management of udder health is particularly focused on preventing new infections. Data from the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) may be used in forecasting to improve decision support for improved udder health management. It provides online cell counts (OCC) as a proxy for somatic cell counts from every milking at the cow level. However, these values are typically too insensitive and nonspecific to indicate subclinical intramammary infection (IMI). Our aim was to describe and evaluate use of dynamic transmission models to forecast subclinical IMI episodes using milk cultures or changes in OCC patterns over time. The latter was expressed by an elevated mastitis risk variable. Data were obtained from the dairy herd of the Norwegian University of Life Sciences (Oslo, Norway). In total, 173 cows were sampled monthly for bacteriological milk culture during a 17-mo study period and 5,330 quarter milk samples were cultured. Mastitis pathogens identified were assigned to 1 of 2 groups, Pat 1 or Pat 2. Pathogens from which a high cell count would be expected during a subclinical IMI episode were assigned to the Pat 1 group. Pathogens not in the Pat 1 group were assigned to the Pat 2 group. Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae were the most common Pat 1 pathogens. Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus were the most common Pat 2 pathogens. The OCC were successfully recorded from 82,182 of 96,542 milkings. The current study included 324 subclinical IMI episodes. None of the mastitis pathogens demonstrated a basic reproduction number (R0) >1. Patterns of OCC change related to an episode of Pat 1 subclinical IMI at specificity levels of 80, 90, and 95% at sensitivity levels of 69, 59, and 48% respectively, demonstrated an R0 >1. An existing infection was significant for transmission for several Pat 2 pathogens, but only for Staphylococcus aureus and Staphylococcus epidermidis among Pat 1 pathogens. Dynamic transmission models showed that patterns of OCC change related to an episode of Pat 1 subclinical IMI were significantly related to the same pattern occurring in susceptible cows at specificity levels of 80, 90, and 99% at sensitivity levels of 69, 48, and 8%, respectively. We conclude that changes in herd prevalence of subclinical IMI can be predicted using dynamic transmission models based on patterns of OCC change. Choice of specificity level depends on management goals and tolerance for false-positive alerts.

The detection of intramammary infections using online somatic cell counts.

Timely and accurate identification of cows with intramammary infections is essential for optimal udder health management. Various sensor systems have been developed to provide udder health information that can be used as a decision support tool for the farmer. Among these sensors, the DeLaval Online Cell Counter (DeLaval, Tumba, Sweden) provides somatic cell counts from every milking at cow level. Our aim was to describe and evaluate diagnostic sensor properties of these online cell counts (OCC) for detecting an intramammary infection, defined as an episode of subclinical mastitis or a new case of clinical mastitis. The predictive abilities of a single OCC value, rolling averages of OCC values, and an elevated mastitis risk (EMR) variable were compared for their accuracy in identifying cows with episodes of subclinical mastitis or new cases of clinical mastitis. Detection of subclinical mastitis episodes by OCC was performed in 2 separate groups of different mastitis pathogens, Pat 1 and Pat 2, categorized by their known ability to increase somatic cell count. The data for this study were obtained in a field trial conducted in the dairy herd of the Norwegian University of Life Sciences. Altogether, 173 cows were sampled at least once during a 17-mo study period. The total number of quarter milk cultures was 5,330. The most common Pat 1 pathogens were Staphylococcus epidermidis, Staphylococcus aureus, and Streptococcus dysgalactiae. The most common Pat 2 pathogens were Corynebacterium bovis, Staphylococcus chromogenes, and Staphylococcus haemolyticus. The OCC were successfully recorded from 82,182 of 96,542 milkings during the study period. For episodes of subclinical mastitis the rolling 7-d average OCC and the EMR approach performed better than a single OCC value for detection of Pat 1 subclinical mastitis episodes. The EMR approach outperformed the OCC approaches for detection of Pat 2 subclinical mastitis episodes. For the 2 pathogen groups, the sensitivity of detection of subclinical mastitis episodes was 69% (Pat 1) and 31% (Pat 2), respectively, at a predefined specificity of 80% (EMR). All 3 approaches were equally good at detecting new cases of clinical mastitis, with an optimum sensitivity of 80% and specificity of 90% (single OCC value).

Elucidating Transmission Patterns of Endemic Mycobacterium avium subsp. paratuberculosis Using Molecular Epidemiology.

Mycobacterial diseases are persistent and characterized by lengthy latent periods. Thus, epidemiological models require careful delineation of transmission routes. Understanding transmission routes will improve the quality and success of control programs. We aimed to study the infection dynamics of Mycobacterium avium subsp. paratuberculosis (MAP), the causal agent of ruminant Johne's disease, and to distinguish within-host mutation from individual transmission events in a longitudinally MAP-defined dairy herd in upstate New York. To this end, semi-annual fecal samples were obtained from a single dairy herd over the course of seven years, in addition to tissue samples from a selection of culled animals. All samples were cultured for MAP, and multi-locus short-sequence repeat (MLSSR) typing was used to determine MAP SSR types. We concluded from these precise MAP infection data that, when the tissue burden remains low, the majority of MAP infections are not detectable by routine fecal culture but will be identified when tissue culture is performed after slaughter. Additionally, we determined that in this herd vertical infection played only a minor role in MAP transmission. By means of extensive and precise longitudinal data from a single dairy herd, we have come to new insights regarding MAP co-infections and within-host evolution.

A data-driven individual-based model of infectious disease in livestock operation: A validation study for paratuberculosis.

Chronic livestock diseases cause large financial loss and affect animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform the farmer's decisions, but even successful control programmes do by no means assure elimination. Mathematical models provide opportunities to test different control and elimination options rather than implementing them in real herds, but these models require robust parameter estimation and validation. Fitting these models to data is a difficult task due to heterogeneities in livestock processes. In this paper, we develop an infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and causes significant economic losses to the dairy industry. These economic effects are particularly important motivations in the control and elimination of MAP. In this framework, an individual-based model (IBM) of a dairy herd was built and MAP infection dynamics was integrated. Once the model produced realistic dynamics of MAP infection, we implemented an evaluation method by fitting it to data from three dairy herds from the Northeast region of the US. The model fitting exercises used least-squares and parameter space searching methods to obtain the best-fitted values of selected parameters. The best set of parameters were used to model the effect of interventions. The results show that the presented model can complement real herd statistics where the intervention strategies suggest a reduction in MAP prevalence without elimination. Overall, this research not only provides a complete model for MAP infection dynamics in a dairy herd but also offers a method for estimating parameters by fitting IBM models.

Transmission dynamics of intramammary infections caused by Corynebacterium species.

The development of reliable models for transmission of intramammary infections (IMI) is the subject of extensive research. Such models are useful to enhance the identification and understanding of factors that affect pathogen-specific IMI dynamics. Longitudinal transmission models are valuable for predicting infection outbreak risks, quantifying the effectiveness of response tactics, and performing response planning. In this work, we focused on modeling Corynebacterium spp. by using a compartmental model. Previous investigations have considered modeling the transmission dynamics of several bacterial pathogens, but not Corynebacterium spp. We established a Corynebacterium spp. Susceptible-Infectious-Susceptible (SIS) model. We simulated the model numerically by using parameters that we estimated by a generalized linear model approach, using month of study as the time variable. The data, from which the parameters of the model were estimated, were obtained in a field trial conducted in 2 US dairy herds. Altogether, 786 cows were sampled at least once during the 13-mo study period. The total number of quarter milk cultures and cases of IMI caused by Corynebacterium spp. were 11,744 and 556, respectively, in farm A; the corresponding figures for farm B were 11,804 and 179. Our modeling study included only transmission from persistent IMI caused by Corynebacterium spp. within the lactation pens. The rate of new infections was significantly related to preexisting IMI in both farms, underscoring the importance of preexisting Corynebacterium spp. IMI for the transmission of Corynebacterium spp. within lactation pens. The estimated basic reproduction numbers (R0) in the 2 farms were 1.18 and 0.98, respectively. The nonsignificant disparity in R0 was associated with significant differences in cure rates between farms.

Normal milk microbiome is reestablished following experimental infection with Escherichia coli independent of intramammary antibiotic treatment with a third-generation cephalosporin in bovines.

BACKGROUND: The use of antimicrobials in food animals and the emergence of antimicrobial resistance are global concerns. Ceftiofur is the only third-generation cephalosporin labeled for veterinary use in the USA, and it is the drug of choice in the majority of dairy farms for the treatment of mastitis. Here, we use next-generation sequencing to describe longitudinal changes that occur in the milk microbiome before, during, and after infection and treatment with ceftiofur. Twelve animals were intramammary challenged with Escherichia coli in one quarter and randomly allocated to receive intramammary treatment with ceftiofur (5d) or untreated controls. Serial samples were collected from -72 to 216 h relative to challenge from the challenged quarter, an ipsilateral quarter assigned to the same treatment group, and from a third quarter that did not undergo intervention. RESULTS: Infection with E. coli dramatically impacted microbial diversity. Ceftiofur significantly decreased LogCFUs but had no significant effect on the milk microbiome, rate of pathogen clearance, or somatic cell count. At the end of the study, the microbial profile of infected quarters was indistinguishable from pre-challenge samples in both treated and untreated animals. Intramammary infusion with ceftiofur did not alter the healthy milk (i.e., milk devoid of clots or serous appearance and collected from a mammary gland that shows no clinical signs of mastitis) microbiome. CONCLUSIONS: Our results indicate that the mammary gland harbors a resilient microbiome, capable of reestablishing itself after experimental infection with E. coli independent of antimicrobial treatment.

The value of pathogen information in treating clinical mastitis.

The objective of this study was to determine the economic value of obtaining timely and more accurate clinical mastitis (CM) test results for optimal treatment of cows. Typically CM is first identified when the farmer observes recognisable outward signs. Further information of whether the pathogen causing CM is Gram-positive, Gram-negative or other (including no growth) can be determined by using on-farm culture methods. The most detailed level of information for mastitis diagnostics is obtainable by sending milk samples for culture to an external laboratory. Knowing the exact pathogen permits the treatment method to be specifically targeted to the causation pathogen, resulting in less discarded milk. The disadvantages are the additional waiting time to receive test results, which delays treating cows, and the cost of the culture test. Net returns per year (NR) for various levels of information were estimated using a dynamic programming model. The Value of Information (VOI) was then calculated as the difference in NR using a specific level of information as compared to more detailed information on the CM causative agent. The highest VOI was observed where the farmer assumed the pathogen causing CM was the one with the highest incidence in the herd and no pathogen specific CM information was obtained. The VOI of pathogen specific information, compared with non-optimal treatment of Staphylococcus aureus where recurrence and spread occurred due to lack of treatment efficacy, was $20.43 when the same incorrect treatment was applied to recurrent cases, and $30.52 when recurrent cases were assumed to be the next highest incidence pathogen and treated accordingly. This indicates that negative consequences associated with choosing the wrong CM treatment can make additional information cost-effective if pathogen identification is assessed at the generic information level and if the pathogen can spread to other cows if not treated appropriately.

Longitudinal metagenomic profiling of bovine milk to assess the impact of intramammary treatment using a third-generation cephalosporin.

Antimicrobial usage in food animals has a direct impact on human health, and approximately 80% of the antibiotics prescribed in the dairy industry are used to treat bovine mastitis. Here we provide a longitudinal description of the changes in the microbiome of milk that are associated with mastitis and antimicrobial therapy. Next-generation sequencing, 16 S rRNA gene quantitative real-time PCR, and aerobic culturing were applied to assess the effect of disease and antibiotic therapy on the milk microbiome. Cows diagnosed with clinical mastitis associated with Gram-negative pathogens or negative aerobic culture were randomly allocated into 5 days of Ceftiofur intramammary treatment or remained as untreated controls. Serial milk samples were collected from the affected quarter and the ipsilateral healthy quarter of the same animal. Milk from the mastitic quarter had a higher bacterial load and reduced microbial diversity compared to healthy milk. Resolution of the disease was accompanied by increases in diversity indexes and a decrease in pathogen relative abundance. Escherichia coli-associated mastitic milk samples had a remarkably distinct bacterial profile, dominated by Enterobacteriaceae, when compared to healthy milk. However, no differences were observed in culture-negative mastitis samples when compared to healthy milk. Antimicrobial treatment had no significant effect on clinical cure, bacteriological cure, pathogen clearance rate or bacterial load.