Optimization of Epidemiologic Interventions: Evaluation of Spatial and Non-Spatial Methods That Identify Johne’s Disease-Infected Subpopulations Targeted for Intervention

The potential costs and/or benefits associated with two epidemiological methods were compared. Using the same epidemiologic dataset (74 Israeli dairy herds tested for bovine paratuberculosis of which 57 farms were regarded to be infected, and 619 non-tested herds), the efficacy associated with the identification of the target population where control or preventive measures could be applied was evaluated by: 1) A method that applied geographical information systems (GIS), spatial statistics, network analysis (infective spatial links or ISL); and 2) A method that only partially applied spatial techniques. Based on the herd size of tested and non-tested farms, the geographical area of influence of each infected farm was estimated. Using the Euclidean distance between tested farms (distances between 2701 farm pairs), the ISL method calculated two measures of spatial connectivity: the number of links/farm and the ISL index. These measures are analogous to the number of roads connecting a city (links/farm) and the width of a road (index). The more links and/or the greater the average index ( width ), the greater the chances of an infected farm to disseminate an infection (especially to neighboring farms). While not reaching statistical significance, positive indices of Moran\u27s I test for some spatial lags prompted the additional investigation of a subset of 547 farm pairs. This subset included 33 farm pairs (16 individual farms) which displayed \u3e 2 links/farm, and ISL indices \u3e7.5 times greater than average (high ISL farms). Regarding as cost the number of infected cows selected to receive an intervention, and as benefit the number of susceptible cows within the area of influence of an infected farm, hypothetical interventions implemented on the 16 high ISL farms yielded 39 % greater benefits and occupied a territory 9.5% smaller than decisions based on the 16 farms showing the highest prevalence. The analysis on spatial infective connectivity may lead to earlier, farm-specific and more beneficial, decisions than methods based only on outcomes (later data), such as prevalence

Protein Kinase G Induces an Immune Response in Cows Exposed to Mycobacterium avium Subsp. paratuberculosis

To establish infection, pathogens secrete virulence factors, such as protein kinases and phosphatases, to modulate the signal transduction pathways used by host cells to initiate immune response. The protein MAP3893c is annotated in the genome sequence of Mycobacterium avium subspecies paratuberculosis (MAP), the causative agent of Johne’s disease, as the serine/threonine protein kinase G (PknG). In this work, we report that PknG is a functional kinase that is secreted within macrophages at early stages of infection. The antigen is able to induce an immune response from cattle exposed to MAP in the form of interferon gamma production after stimulation of whole blood with PknG. These findings suggest that PknG may contribute to the pathogenesis of MAP by phosphorylating macrophage signalling and/or adaptor molecules as observed with other pathogenic mycobacterial species

Novel Cell Preservation Technique to Extend Bovine In Vitro White Blood Cell Viability.

Although cell-mediated immunity based diagnostics can be integral assays for early detection of various diseases of dairy cows, processing of blood samples for these tests is time-sensitive, often within 24 hours of collection, to maintain white blood cell viability. Therefore, to improve utility and practicality of such assays, the objective of this study was to assess the use of a novel white blood cell preservation technology in whole bovine blood. Blood samples from ten healthy cows were each divided into an unpreserved control sample and a test sample preserved with commercially-available cell transport medium. Samples were maintained at room temperature and stimulated with the mitogens pokeweed and concanavalinA, as well as with interleukin-12 p40. Stimulation was completed on days 1, 5, and 8 post-sampling. Viability of white blood cells was assessed through interferon gamma production determined with a commercial enzyme linked immunosorbent assay. In addition, mononuclear cell viability was assessed with propidium iodide flow cytometry. Greater interferon gamma production was observed on days 5 and 8 post-collection in preserved samples, with both pokeweed and concanavalinA stimulating positive interferon gamma production on day 5 post-collection. A greater proportion of the amount of interferon gamma produced on day 1 continued to be produced on days 5 and 8 post-collection with concanavalinA stimulation (with or without interleukin 12) as compared to pokeweed stimulation. Additionally, viable mononuclear cells were still present at eight days post-collection, with a higher mean proportion detected at days 5 and 8 in all stimulated preserved samples. This practical and simple method to extend in vitro white blood cell viability could benefit the efficient utilization of cell-based blood tests in ruminants

Predicted average proportion of mononuclear cell viability (with 95% confidence intervals) over time (days).

<p>Predicted results are shown for whole blood samples, either unpreserved or preserved with a transport medium (SCSR-T, NonInvasive Technologies), that were collected from ten healthy cows.</p

Propidium iodide flow cytometric analysis of viable and nonviable cells in preserved and unpreserved samples.

<p>Results from day 8 of the sampling period are shown for whole blood samples, either preserved (panel a.) with a transport medium (TM; SCSR-T, NonInvasive Technologies) or unpreserved (panel b.), that were collected from ten healthy cows. Arrows identify areas representing viable and nonviable cells, with the percentage of cells measured labelled per quadrant. Representative samples shown were samples stimulated with interleukin-12 p40 potentiated concanavalinA (ConA+IL-12).</p

Means, model estimates, and <i>P</i>-values for predictors of interest, predictor interactions, and variances for random effects.

<p>^a Estimates for treatments presented as a range of means over time.</p><p>^b Estimates for treatments in unpreserved samples.</p><p>^c Estimates for treatments in preserved samples.</p><p>^d Proportion of total unexplained variance.</p><p>^e<i>P</i>-value for complete treatment factor.</p><p>Means, model estimates, and <i>P</i>-values for predictors of interest, predictor interactions, and variances for random effects.</p

Feedback-based, system-level properties of vertebrate-microbial interactions

Background: Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. Methods: To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. Results: In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. Conclusions: More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling