Evolutionary genomic and bacteria GWAS analysis of Mycobacterium avium subsp. paratuberculosis and dairy cattle Johne's disease phenotypes.

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle. The Regional Dairy Quality Management Alliance (RDQMA) project is a multistate research program involving MAP isolates taken from three intensively studied commercial dairy farms in the northeastern United States, which emphasized longitudinal data collection of both MAP isolates and animal health in three regional dairy herds for a period of about 7 years. This paper reports the results of a pan-GWAS analysis involving 318 MAP isolates and dairy cow Johne's disease phenotypes, taken from these three farms. Based on our highly curated accessory gene count the pan-GWAS analysis identified several MAP genes associated with bovine Johne's disease phenotypes scored from these three farms, with some of the genes having functions suggestive of possible cause/effect relationships to these phenotypes. This paper reports a pan-genomic comparative analysis between MAP and Mycobacterium tuberculosis, assessing functional Gene Ontology category enrichments between these taxa. Finally, we also provide a population genomic perspective on the effectiveness of herd isolation, involving closed dairy farms, in preventing MAP inter-farm cross infection on a micro-geographic scale.IMPORTANCE Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle, and enormous economic consequences for the dairy industry. Understanding which genes in this bacterium are correlated with key disease phenotypes can lead to functional experiments targeting these genes and ultimately lead to improved control strategies. This study represents a rare example of a prolonged longitudinal study of dairy cattle where the disease was measured and the bacteria were isolated from the same cows. The genome sequences of over 300 MAP isolates were analyzed for genes that were correlated with a wide range of Johne's disease phenotypes. A number of genes were identified that were significantly associated with several aspects of the disease and suggestive of further experimental follow-up.

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.

Machine learning to further improve the decision which boar ejaculates to process into artificial insemination doses.

Current artificial insemination (AI) laboratory practices assess semen quality of each boar ejaculate to decide which ones to process into AI doses. This decision is aided with two, world-wide used, motility parameters that come available through computer assisted semen analysis (CASA). This decision process, however, still results in AI doses with variable and sometimes suboptimal fertility outcomes (e.g., small litter size). The hypothesis was that the decision which ejaculates to process into AI doses can be improved by adding more data from CASA systems, and data from other sources, in combination with a data-driven model. Available data consisted of ejaculates that passed the initial decision, and thus, were processed into AI doses and used to inseminate sows. Data were divided into a training set (6793 records) and a validation set (1191 records) for model development, and an independent test set (1434 records) for performance assessment. Gradient Boosting Machine (GBM) models were developed to predict four fertility phenotypes of interest (gestation length, total number born, number born alive, and number of stillborn piglets). Each fertility phenotype was considered as a numeric and as a binary outcome parameter, totaling to eight different fertility phenotypes. Data used to further improve the decision process originated from four sources: 1) CASA information, 2) boar ejaculate information, 3) breeding value estimations, and 4) weather information. These data were used to create seven prediction sets, where each new set added parameters to the ones included in the previous set. The GBM models predicted fertility phenotypes with low correlations (for numeric phenotypes) and area under the curve values (for binary phenotypes) on the test data. Hence, results demonstrated that a combination of more data and GBM did not enable further improvement of the AI dose quality checks, resulting in the rejection of our hypothesis. However, our study revealed parameters affecting boar ejaculate fertility which were not used in today's decision process. These parameters (listed in the top 10 in at least four GBM models) included one parameter associated with boar ejaculate information, two with breeding value estimations, five with CASA information, and one with weather information. These parameters, therefore, should be further investigated for their potential value when assessing the quality of boar ejaculates in daily routine AI doses processing.

Mycobacterium caprae Infection of Red Deer in Western Austria-Optimized Use of Pathology Data to Infer Infection Dynamics.

Austria is officially bovine tuberculosis (TB) free, but during the last decade the west of the country experienced sporadic TB cases in cattle. Free-ranging red deer are known to be the maintenance host of Mycobacterium (M.) caprae in certain areas in Austria, where cattle can become infected on alpine pastures shared with deer. The epidemiology of TB in deer in alpine regions is still poorly understood. To inform decisions on efficient interventions against TB in deer, a method is needed to better capture the infection dynamics on population level. A total of 4,521 free-ranging red deer from Austria's most western Federal state Vorarlberg were TB-tested between 2009 and 2018. M. caprae was confirmed in samples from 257 animals. Based on descriptions of TB-like lesions, TB positive animals were categorized with a newly developed lesion score called "Patho Score." Analyses using this Patho Score allowed us to distinguish between endemic, epidemic and sporadic TB situations and revealed different roles of subgroups of infected deer in infection dynamics. Overall, deer in poor condition, deer of older age and stags were the subgroups that were significantly more often TB positive (p = 0.02 or smaller for all subgroups). Deer in poor condition (p < 0.001) and stags (p = 0.04) also showed more often advanced lesions, indicating their role in mycobacterial spread. TB was never detected in fawns, while hinds were the subgroup that showed the fewest advanced lesions. Analysis of outbreaks of TB and lesion development in yearlings provided some evidence for the role of winter feeding as a source for increased infection transmission. Sporadic cases in TB-free areas appear to precede outbreaks in these areas. These currently TB-free areas should receive particular attention in sampling schemes to be able to detect early spreading of the infection. The Patho Score is a quick, easy-to-apply and reproducible tool that provides new insights on the epidemiology of TB in deer at population level and is flexible enough to relate heterogeneous wildlife monitoring data collected following different sampling plans. This lesion score was used for systematic assessment of infection dynamics of mycobacterial infections.

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.

Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period.

African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10-60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1-2 infected premises per outbreak (95% IQR: 1-4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as "super-spreaders"; Germany and Poland as "super-receivers". In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection.

[Acceptance of alternative disease control strategies in the European Union]. / Die Akzeptanz alternativer Seuchenbekämpfungsstrategien in der Europäischen Union.

The European Commission intends to change its animal disease control strategy following the slogan "Prevention is better than cure". Vaccination and diagnostics should play a major role in emergency situations. A policy paper regarding the use of vaccines has been discussed with all Member States and the main aspects were evaluated in a questionnaire. In principle, the majority of Member States are in favour of a future strategy in which vaccination is replacing culling. However, questions regarding the pathogen freedom and the trade of vaccinated animals and animal products from vaccinated animals still remain open.