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Background Bovine paratuberculosis, or Johne’s disease (JD), is a contagious and incurable disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). It has adverse effects on animal welfare and is very difficult to control, leading to serious economic consequences. An important line of defense to this disease is host genetic resistance to MAP, which, when it will be more fully understood, could be improved through selective breeding. Using a large dataset of Holstein cows (161,253 animals including 56,766 cows with ELISA serological phenotypes and 12,431 animals with genotypes), we applied a single-step single nucleotide polymorphism (SNP) best linear unbiased prediction approach to investigate the genetic determinism underlying resistance to this disease (heritability estimate and identification of relevant genomic regions) and estimated genetic trends, reliability, and relative risk factors associated with genomic predictions. Results Resistance to JD was moderately heritable (0.14) and 16 genomic regions were detected that accounted for at least 0.05% of the breeding values variance (GV) in resistance to JD, and were located on chromosomes 1, 3, 5, 6, 7, 19, 20, 21, 23, 25, and 27, with the highest percentage of variance explained by regions on chromosomes 23 (0.36% GV), 5 (0.22% GV), 1 (0.14% GV), and 3 (0.13% GV). When estimated for the whole chromosomes, the autosomes with the largest overall contributions were chromosomes 3 (5.3% GV), 10 (4.8%), 23 (4.7%), 1 (3.6%), 7 (3.4%), 5 (2.9%), 12 (2.5%), 11 (2.2%), and 13 (2%). We estimated a slightly favorable genetic trend in resistance to JD over the last two decades, which can be explained by a low positive genetic correlation between resistance to JD and total merit index (+ 0.06). Finally, in a validation population of 907 cows, relatively reliable genomic predictions (reliability = 0.55) were obtained, which allowed the identification of cows at high risk of infection. Conclusions This study provides new insights into the genetic determinism of resistance to JD and shows that this trait can be predicted from SNP genotypes. It has led to the implementation of a single-step genomic evaluation that should rapidly become an effective tool for controlling paratuberculosis on French Holstein farms.

AbstractBackgroundBovine paratuberculosis is a contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), with adverse effects on animal welfare and serious economic consequences. Published results on host genetic resistance to MAP are inconsistent, mainly because of difficulties in characterizing the infection status of cows. The objectives of this study were to identify quantitative trait loci (QTL) for resistance to MAP in Holstein and Normande cows with an accurately defined status for MAP.ResultsFrom MAP-infected herds, cows without clinical signs of disease were subjected to at least four repeated serum ELISA and fecal PCR tests over time to determine both infected and non-infected statuses. Clinical cases were confirmed using PCR. Only cows that had concordant results for all tests were included in further analyses. Positive and control cows were matched within herd according to their birth date to ensure a same level of exposure to MAP. Cows with accurate phenotypes, i.e. unaffected (control) or affected (clinical or non-clinical cases), were genotyped with the Illumina BovineSNP50 BeadChip. Genotypes were imputed to whole-genome sequences using the 1000 Bull Genomes reference population (run6). A genome-wide association study (GWAS) of MAP status of 1644 Holstein and 649 Normande cows, using either two (controls versus cases) or three classes of phenotype (controls, non-clinical and clinical cases), revealed three regions, on Bos taurus (BTA) chromosomes 12, 13, and 23, presenting significant effects in Holstein cows, while only one of those was identified in Normande cows (BTA23). The most significant effect was found on BTA13, in a short 8.5-kb region. Conditional analyses revealed that only one causal variant may be responsible for the effects observed on each chromosome with the ABCC4 (BTA12), CBFA2T2 (BTA13), and IER3 (BTA23) genes as good functional candidates.ConclusionsA sequence-based GWAS on cows for which resistance to MAP was accurately defined, was able to identify candidate variants located in genes that were functionally related to resistance to MAP; these explained up to 28% of the genetic variance of the trait. These results are very encouraging for efforts towards implementation of a breeding strategy aimed at improving resistance to paratuberculosis in Holstein cows.

Paratuberculosis, a gastrointestinal disease caused by Mycobacterium avium subsp. paratuberculosis (Map), can lead to severe economic losses in dairy cattle farms. Current measures are aimed at controlling prevalence in infected herds, but are not fully effective. Our objective was to determine the most effective control measures to prevent an increase in adult prevalence in infected herds. We developed a new individual-based model coupling population and infection dynamics. Animals are characterized by their age (6 groups) and health state (6 states). The model accounted for all transmission routes and two control measures used in the field, namely reduced calf exposure to adult faeces and test-and-cull. We defined three herd statuses (low, moderate, and high) based on realistic prevalence ranges observed in French dairy cattle herds. We showed that the most relevant control measures depend on prevalence. Calf management and test-and-cull both were required to maximize the probability of stabilizing herd status. A reduced calf exposure was confirmed to be the most influential measure, followed by test frequency and the proportion of infected animals that were detected and culled. Culling of detected high shedders could be delayed for up to 3 months without impacting prevalence. Management of low prevalence herds is a priority since the probability of status stabilization is high after implementing prioritized measures. On the contrary, an increase in prevalence was particularly difficult to prevent in moderate prevalence herds, and was only feasible in high prevalence herds if the level of control was high.

Limited data are available regarding animal-based biomarkers over time as outcomes of biosecurity in pig farms. The aim of this study was to gain an insight into the biosecurity implementation in a convenience sample of 15 swine herds, and to describe potential biomarkers of interest; inputs from a systematic evaluation of biosecurity implementation were used to develop tailor-made biosecurity protocols monitored over a 12-month period. The farms’ implementation was then described, and animal-based biomarkers were explored as output parameters. A significative biosecurity improvement was observed at the end of the study (p = 0.047), in particular in the professional zone (p = 0.012). Four clusters of farms were identified for their progress on biosecurity implementation by means of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA): 4/15 farms improved their biosecurity only in the professional zone, 8/15 showed scarce/null improvement of total biosecurity, 2/15 worsened their biosecurity, and 1/15 greatly improved biosecurity. The farm biosecurity profiles showing an improvement included farms with a reduction in lung lesions and scars at slaughter at the end of the study. The results suggest that a systematic evaluation of biosecurity is a useful approach to formulate tailor-made biosecurity plans and monitor their implementation; biomarkers might bring insight into the outcomes of biosecurity.

Following the emergence of the Bluetongue virus serotype 8 (BTV-8) in France in 2006, a surveillance system (both passive and active) was implemented to detect and follow precociously the progression of the epizootic wave. This system did not allow a precise estimation of the extent of the epizootic. Infection by BTV-8 is associated with a decrease of fertility. The objective of this study was to evaluate whether a decrease in fertility can be used to evidence the under-reporting of cases during an epizootic and to quantify to what extent non-reported cases contribute to the total burden of the epizootic. The cow fertility in herds in the outbreak area (reported or not) was monitored around the date of clinical signs. A geostatistical interpolation method was used to estimate a date of clinical signs for non-reported herds. This interpolation was based on the spatiotemporal dynamic of confirmed case herds reported in 2007. Decreases in fertility were evidenced for both types of herds around the date of clinical signs. In non-reported herds, the decrease fertility was large (60% of the effect in reported herds), suggesting that some of these herds have been infected by the virus during 2007. Production losses in non-reported infected herds could thus contribute to an important part of the total burden of the epizootic. Overall, results indicate that performance data can be used to evidence the under-reporting during an epizootic. This approach could be generalized to pathogens that affect cattle's performance, including zoonotic agents such as Coxiella burnetii or Rift Valley fever virus.

Paratuberculosis is a worldwide disease causing production losses in dairy cattle herds. Variability of cattle response to exposure to Mycobacterium avium subsp. paratuberculosis (Map) has been highlighted. Such individual variability could influence Map spread at larger scale. Cattle resistance to paratuberculosis has been shown to be heritable, suggesting genetic selection could enhance disease control. Our objective was to identify which phenotypic traits characterising the individual course of infection influence Map spread in a dairy cattle herd. We used a stochastic mechanistic model. Resistance consisted in the ability to prevent infection and the ability to cope with infection. We assessed the effect of varying (alone and combined) fourteen phenotypic traits characterising the infection course. We calculated four model outputs 25 years after Map introduction in a naïve herd: cumulative incidence, infection persistence, and prevalence of infected and affected animals. A cluster analysis identified influential phenotypes of cattle resistance. An ANOVA quantified the contribution of traits to model output variance. Four phenotypic traits strongly influenced Map spread: the decay in susceptibility with age (the most effective), the quantity of Map shed in faeces by high shedders, the incubation period duration, and the required infectious dose. Interactions contributed up to 12% of output variance, highlighting the expected added-value of improving several traits simultaneously. Combinations of the four most influential traits decreased incidence to less than one newly infected animal per year in most scenarios. Future genetic selection should aim at improving simultaneously the most influential traits to reduce Map spread in cattle populations.

Antimicrobial residues may pose harmful effects on the health of consumers. At the same time, an adequate quality of drinking water for animals is one of the important element to ensure animal welfare and food without antibacterials. The presented study is aimed at estimating the residue levels of antibacterial compounds, such as penicillins, cephalosporin, macrolides, tetracyclines, quinolones, sulphonamides, aminoglycosides, diaminopirymidines, pleuromutilines and lincosamides in meat and on-farm drinking water samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS), as a part of a surveillance system on pig and broiler farms within the project Healthy Livestock. A total of 870 samples of muscle from pig and broiler, as well as 229 water samples were analysed for antibiotic residues. Samples were collected from farms in EU countries in two steps, before and after implementation of a tailor-made health plan. In muscle samples, the detected concentrations of doxycycline in the post-intervention step (15.9–70.8 µg/kg) were lower than concentrations in the pre-intervention step (20.6–100 µg/kg). In water samples, doxycycline in an average concentration of 119 µg/L in the pre- and 23.1 µg/L in the post-intervention step, as well as enrofloxacin at concentrations of 170 µg/L in the pre- and 1.72 µg/L in the post-intervention step were quantified. Amoxicillin was only present before intervention. The obtained results confirm the effectiveness of the intervention actions. The concentrations of antibiotics in muscles and water were lower after implementation of a health plan on the farms.

Two vector borne diseases, caused by the Bluetongue and Schmallenberg viruses respectively, have emerged in the European ruminant populations since 2006. Several diseases are transmitted by the same vectors and could emerge in the future. Syndromic surveillance, which consists in the routine monitoring of indicators for the detection of adverse health events, may allow an early detection. Milk yield is routinely measured in a large proportion of dairy herds and could be incorporated as an indicator in a surveillance system. However, few studies have evaluated continuous indicators for syndromic surveillance. The aim of this study was to develop a framework for the quantification of both disease characteristics and model predictive abilities that are important for a continuous indicator to be sensitive, timely and specific for the detection of a vector-borne disease emergence. Emergences with a range of spread characteristics and effects on milk production were simulated. Milk yields collected monthly in 48 713 French dairy herds were used to simulate 576 disease emergence scenarios. First, the effect of disease characteristics on the sensitivity and timeliness of detection were assessed: Spatio-temporal clusters of low milk production were detected with a scan statistic using the difference between observed and simulated milk yields as input. In a second step, the system specificity was evaluated by running the scan statistic on the difference between observed and predicted milk yields, in the absence of simulated emergence. The timeliness of detection depended mostly on how easily the disease spread between and within herds. The time and location of the emergence or adding random noise to the simulated effects had a limited impact on the timeliness of detection. The main limitation of the system was the low specificity i.e. the high number of clusters detected from the difference between observed and predicted productions, in the absence of disease.

Bovine neonatal pancytopenia (BNP), a high fatality condition causing haemorrhages in calves aged less than 4 weeks, was first reported in 2007 in Germany and subsequently observed at low incidence in other European countries and New Zealand. A multi-country matched case-control study was conducted in 2011 to identify calf-level risk factors for BNP. 405 BNP cases were recruited from 330 farms in Belgium, France, Germany and the Netherlands by laboratory confirmation of farmer-reported cases. Up to four calves of similar age from the same farm were selected as controls (1154 calves). Risk factor data were collected by questionnaire. Multivariable modelling using conditional logistic regression indicated that PregSure (R) BVD (PregSure, Pfizer Animal Health) vaccination of the dam was strongly associated with BNP cases (adjusted matched Odds Ratio - amOR 17.8 first lactation dams; 95% confidence interval - ci 2.4, 134.4; p = 0.005), and second or more lactation PregSure-vaccinated dams were more likely to have a case than first lactation vaccinated dams (amOR 2.2 second lactation; ci 1.1, 4.3; p = 0.024; amOR 5.3 third or more lactation; ci 2.9, 9.8; p = < 0.001). Feeding colostrum from other cows was strongly associated with BNP if the dam was not PregSure-vaccinated (amOR 30.5; ci 2.1, 440.5; p = 0.012), but the effect was less if the dam was PregSure-vaccinated (amOR 2.1; ci 1.1, 4.0; p = 0.024). Feeding exclusively dam's milk was a higher risk than other types of milk (amOR 3.4; ci 1.6, 7.5; p = 0.002). The population attributable fractions were 0.84 (ci 0.68, 0.92) for PregSure vaccination, 0.13 (ci 0.06, 0.19) for feeding other cows' colostrum, and 0.15 (ci 0.08, 0.22) for feeding dam's milk. No other calf-level factors were identified, suggesting that there are other important factors that are outside the scope of this study, such as genetics, which explain why BNP develops in some PregSure-colostrum-exposed calves but not in others.