Detection and Quantification of Seven Major Serogroups of Shiga Toxin-Producing Escherichia coli on Hides of Cull Dairy, Cull Beef, and Fed Beef Cattle at Slaughter†.

Dehiding during beef cattle processing can introduce fecal contaminants, including Shiga toxin-producing Escherichia coli (STEC), from hides onto carcass surfaces, creating the potential for contaminated beef. Fecal shedding of major STEC serogroups (O26, O45, O103, O111, O121, O145, and O157; STEC-7) may differ among cattle populations, yet no study has been conducted to isolate STEC-7 on hides of multiple cattle types on the same production days at the same processing plant. Our objective was to estimate and compare prevalence and concentrations of STEC-7 on hides of cull dairy, cull beef, and fed beef cattle from the same date and processing plant. Overall, 1,500 cattle hides were sponge sampled from cull dairy ( n = 500), cull beef ( n = 500) and fed beef cattle ( n = 500) over 10 processing days. To determine prevalence, samples were subjected to an immunomagnetic separation culture method, and presumptive STEC isolates were tested by PCR for serogroup and major virulence genes. A spiral plate method was used to enumerate STEC-7 from hide samples. Data were analyzed with linear mixed models. All STEC-7 serogroups except O121 were detected and quantified on cattle hides in this study population. Slightly more fed beef hides (77 of 500; 15.4%) and cull beef hides (76 of 500; 15.2%) were positive for at least one STEC-7 strain compared with cull dairy hides (57 of 500; 11.4%), but cattle type was not significantly associated ( P = 0.19) with STEC-7 prevalence. Fed beef hides had a significantly higher prevalence ( P < 0.05) of STEC O103, O145, and O157 serogroups than did either of the other cattle types. The highest proportions of quantifiable samples were for STEC O145 (32 of 1,500 samples; 2.1%) and O157 (31 of 1,500 samples; 2.1%) serogroups, with the majority of concentrations at 3 to 5 and 2 to 4 log CFU/100 cm2 of hide, respectively. Results indicate that hide contamination with some major STEC serogroups differs significantly among cattle types at harvest, even within the same day and location.

Role of the stress-associated chemicals norepinephrine, epinephrine and substance P in dispersal of Mannheimia haemolytica from biofilms.

Bovine respiratory disease (BRD) is a major problem for the cattle industry that is triggered by various environmental stressors, pathogens and host responses. Mannheimia hemolytica, an important bacterial component of BRD, are present within the nasopharayngeal region of normal calves as commensal biofilm communities. However, following stress there are changes in the nasopharyngeal microenvironment that triggers the transition of the commensal M. haemolytica into a pulmonary pathogen. The factors responsible for this transition in- vivo are unknown. In this study we developed an in-vitro biofilm model and investigated the effect of three stress- related compounds: norepinephrine (NE), epinephrine (E), and substance P (SP) on M. haemolytica biofilms. Biofilm formation was demonstrated for 3 bovine nasal isolates of M. haemolytica by growing them in basal culture media, basal media with additional glucose, and basal media with a reduced pH. Increased glucose enhanced biofilm biomass for 2/3 isolates, but acidic media did not increase biofilm biomass when compared to biofilm biomass in basal media. When the biofilm was exposed to NE, E and SP, there was a dispersal of the biofilm which was most effective with E, followed by NE, and SP being the least effective. Using high - throughput scanning electron microscopy and confocal-imaging we confirmed our experimental data that treatment with NE, E and SP cause dispersion of M.haemolytica from biofilms.

Implementing structural equation models to observational data from feedlot production systems.

The objective of this study was to illustrate the implementation of a mixed-model-based structural equation modeling (SEM) approach to observational data in the context of feedlot production systems. Different from traditional multiple-trait models, SEMs allow assessment of potential causal interrelationships between outcomes and can effectively discriminate between direct and indirect effects. For illustration, we focused on feedlot performance and its relationship to health outcomes related to Bovine Respiratory Disease (BRD), which accounts for approximately 75% of morbidity and 50-80% of deaths in feedlots. Our data consisted of 1430 lots representing 178,983 cattle from 9 feedlot operations located across the US Great Plains. We explored functional links between arrival weight (AW; i = 1), BRD-related treatment costs (Trt$; as a proxy for health; i = 2) and average daily weight gain (ADG; as an indicator of productive performance i = 3), accounting for the fixed effect of sex and correlation patterns due to the clustering of lots within feedlots. We proposed competing plausible causal models based on expert knowledge. The best fitting model selected for inference supported direct effects of AW on ADG as well as indirect effects of AW on ADG mediated by Trt$. Direct effects from outcome i' to outcome i are quantified by the structural coefficient λii', such that every unit increase in kg/head of AW had a direct effect of increasing ADG by approximately (estimate ±â€¯standard error) λˆ31=0.002±0.0001 kg/head/day and also a direct effect of reducing Trt$ by an estimated λˆ21=$0.08±0.006 USD per head. In addition, every $1 USD spent on Trt$ directly decreased ADG by an estimated λˆ32=0.004±0.0006 kg/head/day. From these estimates, we show how to compute the indirect, Trt$-mediated, effect of AW on ADG, as well as the overall effect of AW on ADG, including both direct and indirect effects. We further compared estimates of SEM-based effects with those obtained from standard linear regression mixed models and demonstrated the additional advantage of explicitly distinguishing direct and indirect components of an overall regression effect using SEMs. Understanding the direct and indirect mechanisms of interplay between health and performance outcomes may provide valuable insight into production systems.

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.

Evidence of no protection for a recurrent case of pathogen specific clinical mastitis from a previous case.

The objective of this study was to determine whether the occurrence of a previous case of pathogen-specific clinical mastitis (CM) protects Holstein dairy cows against a recurrent case. Pathogens studied were Escherichia coli, Staphylococcus aureus, Staphylococcus spp., Streptococcus spp., Klebsiella spp., and Trueperella pyogenes. A total of 40 864 lactations (17,265 primiparous and 23,599 multiparous) from 19 835 cows from 5 large, high milk producing New York State dairy herds were analysed. We estimated the effects of parity, calving diseases, milk yield, current season and number of CM cases in the previous lactation on the risk of a first CM case using generalised linear mixed models with a log link and Poisson error distribution. The aforementioned risk factors and the occurrence of previous cases of pathogen-specific CM within the current lactation were evaluated as risks for second and third cases of pathogen-specific CM. Cows with more CM cases in the previous lactation were at greater risk of pathogen-specific CM in the current lactation. Multiparous cows were at greater risk of a second CM case if they had suffered from a first CM case that was caused by the same pathogen as the second case. In contrast, a second CM case generally put cows at greater risk of a third case, irrespective of whether the third case was caused by the same or a different pathogen. Our results showed that a previous case of pathogen specific CM does not generally protect against a recurrent case.