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Abstract Background Since 2002, active surveillance programmes have detected numerous atypical scrapie (AS) and classical scrapie cases (CS) in French sheep with almost all the PrP genotypes. The aim of this study was 1) to quantify the genetic risk of AS in French sheep and to compare it with the risk of CS, 2) to quantify the risk of AS associated with the increase of the ARR allele frequency as a result of the current genetic breeding programme against CS. Methods We obtained genotypes at codons 136, 141, 154 and 171 of the PRNP gene for representative samples of 248 AS and 245 CS cases. We used a random sample of 3,317 scrapie negative animals genotyped at codons 136, 154 and 171 and we made inferences on the position 141 by multiple imputations, using external data. To estimate the risk associated with PrP genotypes, we fitted multivariate logistic regression models and we estimated the prevalence of AS for the different genotypes. Then, we used the risk of AS estimated for the ALRR-ALRR genotype to analyse the risk of detecting an AS case in a flock homogenous for this genotype. Results Genotypes most at risk for AS were those including an AFRQ or ALHQ allele while genotypes including a VLRQ allele were less commonly associated with AS. Compared to ALRQ-ALRQ, the ALRR-ALRR genotype was significantly at risk for AS and was very significantly protective for CS. The prevalence of AS among ALRR-ALRR animals was 0.6‰ and was not different from the prevalence in the general population. Conclusion In conclusion, further selection of ALRR-ALRR animals will not result in an overall increase of AS prevalence in the French sheep population although this genotype is clearly susceptible to AS. However the probability of detecting AS cases in flocks participating in genetic breeding programme against CS should be considered.

Abstract Background Ticks transmit pathogens of medical and veterinary importance and are an increasing threat to human and animal health. Assessing disease risk and developing new control strategies requires identifying members of the tick-borne microbiota as well as their temporal dynamics and interactions. Methods Using high-throughput sequencing, we studied the Ixodes ricinus microbiota and its temporal dynamics. 371 nymphs were monthly collected during three consecutive years in a peri-urban forest. After a Poisson lognormal model was adjusted to our data set, a principal component analysis, sparse network reconstruction, and differential analysis allowed us to assess seasonal and monthly variability of I. ricinus microbiota and interactions within this community. Results Around 75% of the detected sequences belonged to five genera known to be maternally inherited bacteria in arthropods and to potentially circulate in ticks: Candidatus Midichloria, Rickettsia, Spiroplasma, Arsenophonus and Wolbachia. The structure of the I. ricinus microbiota varied over time with interannual recurrence and seemed to be mainly driven by OTUs commonly found in the environment. Total network analysis revealed a majority of positive partial correlations. We identified strong relationships between OTUs belonging to Wolbachia and Arsenophonus, evidence for the presence of the parasitoid wasp Ixodiphagus hookeri in ticks. Other associations were observed between the tick symbiont Candidatus Midichloria and pathogens belonging to Rickettsia. Finally, more specific network analyses were performed on TBP-infected samples and suggested that the presence of pathogens belonging to the genera Borrelia, Anaplasma and Rickettsia may disrupt microbial interactions in I. ricinus. Conclusions We identified the I. ricinus microbiota and documented marked shifts in tick microbiota dynamics over time. Statistically, we showed strong relationships between the presence of specific pathogens and the structure of the I. ricinus microbiota. We detected close links between some tick symbionts and the potential presence of either pathogenic Rickettsia or a parasitoid in ticks. These new findings pave the way for the development of new strategies for the control of ticks and tick-borne diseases. Video abstract.

Abstract ELISA methods are the diagnostic tools recommended for the serological diagnosis of Coxiella burnetii infection in ruminants but their respective diagnostic performances are difficult to assess because of the absence of a gold standard. This study focused on three commercial ELISA tests with the following objectives (1) assess their sensitivity and specificity in sheep, goats and cattle, (2) assess the between- and within-herd seroprevalence distribution in these species, accounting for diagnostic errors, and (3) estimate optimal sample sizes considering sensitivity and specificity at herd level. We comparatively tested 1413 cattle, 1474 goat and 1432 sheep serum samples collected in France. We analyzed the cross-classified test results with a hierarchical zero-inflated beta-binomial latent class model considering each herd as a population and conditional dependence as a fixed effect. Potential biases and coverage probabilities of the model were assessed by simulation. Conditional dependence for truly seropositive animals was high in all species for two of the three ELISA methods. Specificity estimates were high, ranging from 94.8% [92.1; 97.8] to 99.2% [98.5; 99.7], whereas sensitivity estimates were generally low, ranging from 39.3 [30.7; 47.0] to 90.5% [83.3; 93.8]. Between- and within-herd seroprevalence estimates varied greatly among geographic areas and herds. Overall, goats showed higher within-herd seroprevalence levels than sheep and cattle. The optimal sample size maximizing both herd sensitivity and herd specificity varied from 3 to at least 20 animals depending on the test and ruminant species. This study provides better interpretation of three widely used commercial ELISA tests and will make it possible to optimize their implementation in future studies. The methodology developed may likewise be applied to other human or animal diseases.

Abstract Milk production in dairy cow udders is a complex and dynamic physiological process that has resisted explanatory modelling thus far. The current standard model, Wood’s model, is empirical in nature, represents yield in daily terms, and was published in 1967. Here, we have developed a dynamic and integrated explanatory model that describes milk yield at the scale of the milking session. Our approach allowed us to formally represent and mathematically relate biological features of known relevance while accounting for stochasticity and conditional elements in the form of explicit hypotheses, which could then be tested and validated using real-life data. Using an explanatory mathematical and biological model to explore a physiological process and pinpoint potential problems (i.e., “problem finding”), it is possible to filter out unimportant variables that can be ignored, retaining only those essential to generating the most realistic model possible. Such modelling efforts are multidisciplinary by necessity. It is also helpful downstream because model results can be compared with observed data, via parameter estimation using maximum likelihood and statistical testing using model residuals. The process in its entirety yields a coherent, robust, and thus repeatable, model.

The role of microbial interactions in defining the properties of microbiota is a topic of key interest in microbial ecology. Microbiota contain hundreds to thousands of operational taxonomic units (OTUs), most of them rare. This feature of community structure can lead to methodological difficulties: simulations have shown that methods for detecting pairwise associations between OTUs, which presumably reflect interactions, yield problematic results. The performance of association detection tools is impaired when there is a high proportion of zeros in OTU tables. Our goal was to understand the impact of OTU rarity on the detection of associations. We explored the utility of common statistics for testing associations; the sensitivity of alternative association measures; and the performance of network inference tools. We found that a large proportion of pairwise associations, especially negative associations, cannot be reliably tested. This constraint could hamper the identification of candidate biological agents that could be used to control rare pathogens. Identifying testable associations could serve as an objective method for filtering datasets in lieu of current empirical approaches. This trimming strategy could significantly reduce the computational time needed to infer networks and network inference quality. Different possibilities for improving the analysis of associations within microbiota are discussed.

Abstract Most parasites co-occur with other parasites, although the importance of such multiparasitism has only recently been recognised. Co-infections may result when hosts are independently infected by different parasites at the same time or when interactions among parasite species facilitate co-occurrence. Such interactions can have important repercussions on human or animal health because they can alter host susceptibility, infection duration, transmission risks, and clinical symptoms. These interactions may be synergistic or antagonistic and thus produce diverse effects in infected humans and animals. Interactions among parasites strongly influence parasite dynamics and therefore play a major role in structuring parasite populations (both within and among hosts) as well as host populations. However, several methodological challenges remain when it comes to detecting parasite interactions. The goal of this review is to summarise current knowledge on the causes and consequences of multiparasitism and to discuss the different methods and tools that researchers have developed to study the factors that lead to multiparasitism. It also identifies new research directions to pursue.

Human leptospirosis is a zoonotic and potentially fatal disease that has increasingly been reported in both developing and developed countries, including France. However, our understanding of the basic aspects of the epidemiology of this disease, including the source of Leptospira serogroup Australis infections in humans and domestic animals, remains incomplete. We investigated the genetic diversity of Leptospira in 28 species of wildlife other than rats using variable number tandem repeat (VNTR) and multispacer sequence typing (MST). The DNA of pathogenic Leptospira was detected in the kidney tissues of 201 individuals out of 3,738 tested individuals. A wide diversity, including 50 VNTR profiles and 8 MST profiles, was observed. Hedgehogs and mustelid species had the highest risk of being infected (logistic regression, OR = 66.8, CI95% = 30.9-144 and OR = 16.7, CI95% = 8.7-31.8, respectively). Almost all genetic profiles obtained from the hedgehogs were related to Leptospira interrogans Australis, suggesting the latter as a host-adapted bacterium, whereas mustelid species were infected by various genotypes, suggesting their interaction with Leptospira was different. By providing an inventory of the circulating strains of Leptospira and by pointing to hedgehogs as a potential reservoir of L. interrogans Australis, our study advances current knowledge on Leptospira animal carriers, and this information could serve to enhance epidemiological investigations in the future.

Le présent article a pour objectif de discuter de la faisabilité et de l’intérêt que représenterait le suivi d’un indicateur indirect de survenue des avortements élaboré à partir des données d’insémination artificielle, le taux d’avortements précoces, afin d’identifier l’impact d’un évènement abortif, de manière rétrospective ou prospective. Deux études sont présentées pour illustrer le propos, ayant eu pour objet d’estimer, par l’analyse des variations du taux d’avortements précoces, l’impact de l’épizootie de fièvre catarrhale ovine due au sérotype 8 (FCO-8), qui a émergé en France en 2006, puis s’est diffusée dans une large partie du territoire métropolitain en 2007 et 2008. La première étude souligne qu’une analyse des variations temporelles du taux d’avortements précoces à l’échelle du département a permis d’identifier a posteriori l’impact de la FCO-8 sur la survenue d’avortements en élevages de bovins. La seconde étude indique qu’une analyse prospective hebdomadaire des variations temporelles du taux d’avortements précoces aurait permis d’identifier l’impact de la FCO-8 dans un département dans un délai médian de 12 semaines suivant son introduction. Considérant ces résultats, il apparaît pertinent de réfléchir à la mise en place d’une surveillance intégrée des avortements en élevage de bovins, qui reposerait sur deux volets : la déclaration obligatoire des avortements (sous la forme du dispositif actuel en version révisée) et un outil de surveillance syndromique (qui devrait être mis en place à une échelle infra-départementale, en particulier pour améliorer les délais de détection).

Lyme borreliosis, one of the most frequently contracted zoonotic diseases in the Northern Hemisphere, is caused by bacteria belonging to different genetic groups within the Borrelia burgdorferi species complex, which are transmitted by ticks among various wildlife reservoirs, such as small mammals and birds. These features make the Borrelia burgdorferi species complex an attractive biological model that can be used to study the diversification and the epidemiology of endemic bacterial pathogens. We investigated the potential of population genomic approaches to study these processes. Sixty-three strains belonging to three species within the Borrelia burgdorferi complex were isolated from questing ticks in Alsace (France), a region where Lyme disease is highly endemic. We first aimed to characterize the degree of genetic isolation among the species sampled. Phylogenetic and coalescent-based analyses revealed clear delineations: there was a ∼50 fold difference between intra-specific and inter-specific recombination rates. We then investigated whether the population genomic data contained information of epidemiological relevance. In phylogenies inferred using most of the genome, conspecific strains did not cluster in clades. These results raise questions about the relevance of different strategies when investigating pathogen epidemiology. For instance, here, both classical analytic approaches and phylodynamic simulations suggested that population sizes and migration rates were higher in B. garinii populations, which are normally associated with birds, than in B. burgdorferi s.s. populations. The phylogenetic analyses of the infection-related ospC gene and its flanking region provided additional support for this finding. Traces of recombination among the B. burgdorferi s.s. lineages and lineages associated with small mammals were found, suggesting that they shared the same hosts. Altogether, these results provide baseline evidence that can be used to formulate hypotheses regarding the host range of B. burgdorferi lineages based on population genomic data.

BackgroundIn natural populations, individuals are infected more often by several pathogens than by just one. In such a context, pathogens can interact. This interaction could modify the probability of infection by subsequent pathogens. Identifying when pathogen associations correspond to biological interactions is a challenge in cross-sectional studies where the sequence of infection cannot be demonstrated.Methodology/principal findingsHere we modelled the probability of an individual being infected by one and then another pathogen, using a probabilistic model and maximum likelihood statistics. Our model was developed to apply to cross-sectional data, vector-borne and persistent pathogens, and to take into account confounding factors. Our modelling approach was more powerful than the commonly used Chi-square test of independence. Our model was applied to detect potential interaction between Borrelia afzelii and Bartonella spp. that infected a bank vole population at 11% and 57% respectively. No interaction was identified.Conclusions/significanceThe modelling approach we proposed is powerful and can identify the direction of potential interaction. Such an approach can be adapted to other types of pathogens, such as non-persistents. The model can be used to identify when co-occurrence patterns correspond to pathogen interactions, which will contribute to understanding how organism communities are assembled and structured. In the long term, the model's capacity to better identify pathogen interactions will improve understanding of infectious risk.

Abstract: In ecology and epidemiology, exploratory field studies based on multivariate statistical models commonly are used to identify factors that are associated with a phenomenon. The challenge is to evaluate whether these factors are indeed correlated to the phenomenon or if the statistical significance results from fortuitous association or type 1 statistical error (probability of rejecting a null hypothesis when it is true). This is particularly the case when the phenomenon is linked to environmental factors that usually are more or less correlated to each other and when the phenomenon is itself highly variable. The abundance of Ixodes ricinus ticks, a major disease vector in Europe, is highly variable and depends on environmental conditions that define suitable habitat and host presence. Our objective was to identify reproducible factors in space and time that influenced the abundance of questing I. ricinus nymphs. We sampled questing nymphs in pastures in 4 settings, i.e. during 3 periods (2003, 2004, and 2006) in one region, and during one period (2006) in another region, both regions located in Central France. The same data collection, data selection, and model analysis using negative binomial distribution were applied independently in the 4 data sets to identify ‘reproducible’ factors, i.e. explanatory factors that were significant in different time periods and spaces. The 3 most reproducible factors suggested that woodland type vegetation and woodland vicinity constantly favoured nymph abundance on pastures. In addition, the presence of fruit trees was significantly associated with nymph abundance in one region. The other factors were not reproducible. The study confirmed the status of key factors for nymph abundance while avoiding having to redefine the statistical model to model the different sampling conditions. It also shows the difficulty to identify factors with general significance acting on a very variable phenomenon, based on a study made one year in one region. Relevant study design should consider appropriate repetitions based on the range of values of the studied factors. Furthermore, discussion of the results is essential to identify factors that have a general significance. [Copyright &y& Elsevier]

The tick Ixodes ricinus is widely distributed across Europe and is responsible for the transmission of several pathogens to humans and animals. In this study, we used a knowledge-based method to map variations in habitat suitability for I. ricinus ticks throughout continental France and Corsica. The multi-criteria decision analysis (MCDA) integrated four major biotic and abiotic factors known to influence tick populations: climate, land cover, altitude and the density of wild ungulates. For each factor, habitat suitability index (HSI) values were attributed to different locations based on knowledge regarding its impact on tick populations. For the MCDA, two methods of factor combination were tested, additive and multiplicative, both which were evaluated at the spatial scales of departments and local municipalities. The resulting habitat suitability maps (resolution=100x100 m) revealed that conditions are suitable for I. ricinus over most of France and Corsica. Particularly suitable habitats were located in central, north-eastern and south-western France, while less-suitable habitats were found in the Mediterranean and mountainous regions. To validate the approach, the HSI scores were compared to field data of I. ricinus nymph abundance. Regardless of scale, the correlation between abundance indicator and HSI score was stronger for the additive than for the multiplicative approach. Overall, this study demonstrates the value of MCDA for estimating habitat suitability maps for I. ricinus abundance, which could be especially useful in highlighting areas of the tick’s distribution where preventive measures should be prioritised.

Brown rats are one of the most widespread urban species worldwide. Despite the nuisances they induce and their potential role as a zoonotic reservoir, knowledge on urban rat populations remains scarce. The main purpose of this study was to characterize an urban brown rat population from Chanteraines park (Hauts-de-Seine, France), with regards to haematology, population genetics, immunogenic diversity, resistance to anticoagulant rodenticides, and community of parasites. Haematological parameters were measured. Population genetics was investigated using 13 unlinked microsatellite loci. Immunogenic diversity was assessed for Mhc-Drb. Frequency of the Y139F mutation (conferring resistance to rodenticides) and two linked microsatellites were studied, concurrently with the presence of anticoagulant residues in the liver. Combination of microscopy and molecular methods were used to investigate the occurrence of 25 parasites. Statistical approaches were used to explore multiple parasite relationships and model parasite occurrence. Eighty-six rats were caught. The first haematological data for a wild urban R. norvegicus population was reported. Genetic results suggested high genetic diversity and connectivity between Chanteraines rats and surrounding population(s). We found a high prevalence (55.8%) of the mutation Y139F and presence of rodenticide residues in 47.7% of the sampled individuals. The parasite species richness was high (16). Seven potential zoonotic pathogens were identified, together with a surprisingly high diversity of Leptospira species (4). Chanteraines rat population is not closed, allowing gene flow and making eradication programs challenging, particularly because rodenticide resistance is highly prevalent. Parasitological results showed that co-infection is more a rule than an exception. Furthermore, the presence of several potential zoonotic pathogens, of which four Leptospira species, in this urban rat population raised its role in the maintenance and spread of these pathogens. Our findings should stimulate future discussions about the development of a long-term rat-control management program in Chanteraines urban park.

INTRODUCTION:Ticks are the most common arthropod vectors of both human and animal diseases in Europe, and the Ixodes ricinus tick species is able to transmit a large number of bacteria, viruses and parasites. Ticks may also be co-infected with several pathogens, with a subsequent high likelihood of co-transmission to humans or animals. However few data exist regarding co-infection prevalences, and these studies only focus on certain well-known pathogens. In addition to pathogens, ticks also carry symbionts that may play important roles in tick biology, and could interfere with pathogen maintenance and transmission. In this study we evaluated the prevalence of 38 pathogens and four symbionts and their co-infection levels as well as possible interactions between pathogens, or between pathogens and symbionts. METHODOLOGY/PRINCIPAL FINDINGS:A total of 267 Ixodes ricinus female specimens were collected in the French Ardennes and analyzed by high-throughput real-time PCR for the presence of 37 pathogens (bacteria and parasites), by rRT-PCR to detect the presence of Tick-Borne encephalitis virus (TBEV) and by nested PCR to detect four symbionts. Possible multipartite interactions between pathogens, or between pathogens and symbionts were statistically evaluated. Among the infected ticks, 45% were co-infected, and carried up to five different pathogens. When adding symbiont prevalences, all ticks were infected by at least one microorganism, and up to eight microorganisms were identified in the same tick. When considering possible interactions between pathogens, the results suggested a strong association between Borrelia garinii and B. afzelii, whereas there were no significant interactions between symbionts and pathogens. CONCLUSION/SIGNIFICANCE:Our study reveals high pathogen co-infection rates in ticks, raising questions about possible co-transmission of these agents to humans or animals, and their consequences to human and animal health. We also demonstrated high prevalence rates of symbionts co-existing with pathogens, opening new avenues of enquiry regarding their effects on pathogen transmission and vector competence.

Q fever is a worldwide zoonosis caused by Coxiella burnetii. Domestic ruminants are considered to be the main reservoir. Sheep, in particular, may frequently cause outbreaks in humans. Because within-flock circulation data are essential to implementing optimal management strategies, we performed a follow-up study of a naturally infected flock of dairy sheep. We aimed to (i) describe C. burnetii shedding dynamics by sampling vaginal mucus, feces, and milk, (ii) assess circulating strain diversity, and (iii) quantify barn environmental contamination. For 8 months, we sampled vaginal mucus and feces every 3 weeks from aborting and nonaborting ewes (n = 11 and n = 26, respectively); for lactating females, milk was obtained as well. We also sampled vaginal mucus from nine ewe lambs. Dust and air samples were collected every 3 and 6 weeks, respectively. All samples were screened using real-time PCR, and strongly positive samples were further analyzed using quantitative PCR. Vaginal and fecal samples with sufficient bacterial burdens were then genotyped by multiple-locus variable-number tandem-repeat analysis (MLVA) using 17 markers. C. burnetii burdens were higher in vaginal mucus and feces than in milk, and they peaked in the first 3 weeks postabortion or postpartum. Primiparous females and aborting females tended to shed C. burnetii longer and have higher bacterial burdens than nonaborting and multiparous females. Six genotype clusters were identified; they were independent of abortion status, and within-individual genotype diversity was observed. C. burnetii was also detected in air and dust samples. Further studies should determine whether the within-flock circulation dynamics observed here are generalizable. [ABSTRACT FROM AUTHOR]