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Durand, Jonas

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Durand, Jonas
Affiliation principale
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https://libra.unine.ch/handle/123456789/616

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  • Publication
    Métadonnées seulement
  • Publication
    Accès libre
    Cross-immunity and community structure of a multiple-strain pathogen in the tick vector
    (2015-11)
    Durand, Jonas 
    ;
    Jacquet, Maxime 
    ;
    Paillard, Lye 
    ;
    Rais, Olivier 
    ;
    Gern, Lise 
    ;
    Voordouw, Maarten 
    Many vector-borne pathogens consist of multiple strains that circulate in both the vertebrate host and the arthropod vector. Characterization of the community of pathogen strains in the arthropod vector is therefore important for understanding the epidemiology of mixed vector-borne infections. Borrelia afzelii and B. garinii are two species of tick-borne bacteria that cause Lyme disease in humans. These two sympatric pathogens use the same tick, Ixodes ricinus, but are adapted to different classes of vertebrate hosts. Both Borrelia species consist of multiple strains that are classified using the highly polymorphic ospC gene. Vertebrate cross-immunity against the OspC antigen is predicted to structure the community of multiple-strain Borrelia pathogens. Borrelia isolates were cultured from field-collected I. ricinus ticks over a period spanning 11 years. The Borrelia species of each isolate was identified using a reverse line blot (RLB) assay. Deep sequencing was used to characterize the ospC communities of 190 B. afzelii isolates and 193 B. garinii isolates. Infections with multiple ospC strains were common in ticks, but vertebrate cross-immunity did not influence the strain structure in the tick vector. The pattern of genetic variation at the ospC locus suggested that vertebrate cross-immunity exerts strong selection against intermediately divergent ospC alleles. Deep sequencing found that more than 50% of our isolates contained exotic ospC alleles derived from other Borrelia species. Two alternative explanations for these exotic ospC alleles are cryptic coinfections that were not detected by the RLB assay or horizontal transfer of the ospC gene between Borrelia species.
  • Publication
    Métadonnées seulement
    Genetic variation in transmission success of the Lyme borreliosis pathogen Borrelia afzelii
    (2015)
    Tonetti, Nicolas 
    ;
    Voordouw, Maarten 
    ;
    Durand, Jonas 
    ;
    Monnier, Séverine
    ;
    Gern, Lise 
    The vector-to-host and host-to-vector transmission steps are the two critical events that define the life cycle of any vector-borne pathogen. We expect negative genetic correlations between these two transmission phenotypes, if parasite genotypes specialized at invading the vector are less effective at infecting the vertebrate host and vice versa. We used the tick-borne bacterium Borrelia afzelii, a causative agent of Lyme borreliosis in Europe, to test whether genetic trade-offs exist between tick-to-host, systemic (host-to-tick), and a third mode of co-feeding (tick-to-tick) transmission. We worked with six strains of B. afzelii that were differentiated according to their ospC gene. We compared the three components of transmission among the B. afzelii strains using laboratory rodents as the vertebrate host and a laboratory colony of Ixodes ricinus as the tick vector. We used next generation matrix models to combine these transmission components into a single estimate of the reproductive number (R0) for each B. afzelii strain. We also tested whether these strain-specific estimates of R0 were correlated with the strain-specific frequencies in the field. We found significant genetic variation in the three transmission components among the B. afzelii strains. This is the first study to document genetic variation in co-feeding transmission for any tick-borne pathogen. We found no evidence of trade-offs as the three pairwise correlations of the transmission rates were all positive. The R0 values from our laboratory study explained 45% of the variation in the frequencies of the B. afzelii ospC strains in the field. Our study suggests that laboratory estimates of pathogen fitness can predict the distribution of pathogen strains in nature.