Susceptibility to infection with Borrelia afzelii and TLR2 polymorphism in a wild reservoir host

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Susceptibility to infection with Borrelia afzelii and TLR2 polymorphism in a wild reservoir host © The Author(s) 2019 Published version Gomez-Chamorro, Andrea; Battilotti, Florian; Cayol, Claire; Mappes, Tapio; Koskela, Esa; Boulanger, Nathalie; Genné, Dolores; Sarr, Anouk; Voordouw, Maarten Jeroen Gomez-Chamorro, A., Battilotti, F., Cayol, C., Mappes, T., Koskela, E., Boulanger, N., Genné, D., Sarr, A., & Voordouw, M. J. (2019). Susceptibility to infection with Borrelia afzelii and TLR2 polymorphism in a wild reservoir host. Scientific Reports, 9, Article 6711. https://doi.org/10.1038/s41598-019-43160-3 2019 1 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports susceptibility to infection with Borrelia afzelii and TLR2 polymorphism in a wild reservoir host Andrea Gomez-Chamorro 1, Florian Battilotti1, Claire Cayol 2, tapio Mappes 2, esa Koskela 2, Nathalie Boulanger3, Dolores Genné 1, Anouk sarr1 & Maarten Jeroen Voordouw 1,4 the study of polymorphic immune genes in host populations is critical for understanding genetic variation in susceptibility to pathogens. Controlled infection experiments are necessary to separate variation in the probability of exposure from genetic variation in susceptibility to infection, but such experiments are rare for wild vertebrate reservoir hosts and their zoonotic pathogens. the bank vole (Myodes glareolus) is an important reservoir host of Borrelia afzelii, a tick-borne spirochete that causes Lyme disease. Bank vole populations are polymorphic for Toll-like receptor 2 (TLR2), an innate immune receptor that recognizes bacterial lipoproteins. To test whether the TLR2 polymorphism influences variation in the susceptibility to infection with B. afzelii, we challenged pathogen-free, lab-born individuals of known TLR2 genotype with B. afzelii-infected ticks. We measured the spirochete load in tissues of the bank voles. the susceptibility to infection with B. afzelii following an infected tick bite was very high (95%) and did not differ between TLR2 genotypes. The TLR2 polymorphism also had no effect on the spirochete abundance in the tissues of the bank voles. Under the laboratory conditions of our study, we did not find that the TLR2 polymorphism in bank voles influenced variation in the susceptibility to B. afzelii infection. The Toll-like receptors (TLRs) are an important family of pathogen recognition receptors (PRRs) that are found in all vertebrates1. These receptors of the innate immune system play a critical role in the recognition of pathogen-associated molecular patterns (PAMPs). PAMPs are highly conserved molecules that are essential for the pathogen’s existence such as the cell wall components of bacteria. To date, 12 to 15 different TLR genes have been discovered in humans and mice, and each TLR receptor recognizes a distinct set of PAMPs2. For example, TLR4 recognizes lipopolysaccharides (LPS), whereas TLR5 recognizes the bacterial flagellin protein2,3. The recognition of pathogens by the TLR receptors is a critical step in the activation of the adaptive immune system in the vertebrate host4. Recent reviews have described numerous polymorphisms in the different TLRs and their associations with susceptibility or resistance to different infectious diseases4,5. The toll-like receptor 2 (TLR2) recognizes a wide variety of PAMPs including peptidoglycan, zymosan, and lipoproteins3. TLR2 can also dimerize with TLR1 and TLR6 to recognize additional PAMPs6. TLR2 plays an important role in recognizing the lipoproteins of the spirochete bacteria of the Borrelia burgdorferi sensu lato (sl) genospecies complex, which includes the causative agents of Lyme borreliosis in humans7,8. Functional studies have shown that TLR2-knockout mice have much higher loads of B. burgdorferi sensu stricto (ss) in their tissues than immunocompetent control mice7,9. Furthermore, population genetic studies have found associations between genetic polymorphisms at the TLR2 locus and resistance to B. burgdorferi sl pathogens in humans and wild rodents10–14. 1institut de Biologie, Université de neuchâtel, neuchâtel, Switzerland. 2Department of Biological and environmental Science, University of Jyväskylä, Jyväskylä, finland. 3facultés de Médecine et de Pharmacie, Université de Strasbourg, Strasbourg, france. 4Department of Veterinary Microbiology, Western college of Veterinary Medicine, University of Saskatchewan, Saskatoon, canada. correspondence and requests for materials should be addressed to M.J.V. (email: maarten.[email protected]) Received: 26 February 2018 Accepted: 17 April 2019 Published: xx xx xxxx opeN 2 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ Lyme borreliosis is the most common vector-borne disease in the northern hemisphere15. In Europe, Borrelia afzelii is the most important etiological agent of Lyme borreliosis and is transmitted by the hard tick Ixodes ricinus16,17. The main reservoir hosts of B. afzelii include small mammals such as mice (Apodemus species) and the bank vole (Myodes glareolus). Experimental infections have shown that B. afzelii establishes chronic infections in its rodent reservoir hosts that can last for months or even years18–20. Larval ticks acquire spirochetes after feeding on an infected reservoir host, as there is no vertical transmission21,22. Blood-engorged larvae subsequently moult into nymphs that infect the reservoir hosts the following year15. In areas with high tick densities, wild rodents are repeatedly bitten by nymphs and exposed to B. burgdorferi sl pathogens23,24. Long-term field studies in Sweden have shown that a quarter of all wild rodents were infected with B. afzelii25. Thus, B. afzelii is an important pathogen in wild rodent populations that could exert strong selection on the host immune system13,14,26. The bank vole (M. glareolus) is an important wild reservoir host for B. afzelii and for immature Ixodes ticks17,23,27. Genetic studies on the TLR2 locus in this species found three different clusters of alleles: C1, C2, and C313,28. A field study in Sweden found that individuals with the C1C1, C1C2, and C2C2 genotype had the highest (48.6%), intermediate (30.6%), and lowest (17.9%) prevalence of B. afzelii13. Thus, the C1 and C2 alleles appear to confer susceptibility and resistance, respectively, to B. afzelii in bank voles. The C3 allele was rare in this population and its phenotype with respect to B. afzelii infection was not investigated. A recent study of the TLR2 polymorphism in bank vole populations across 19 countries in Europe found a strong positive correlation between the frequency of the C2 resistance allele and the case load of human Lyme borreliosis26. This study suggests that B. afzelii is driving the evolution of the C2 resistance allele in European bank vole populations26. Nevertheless, it remains to be conclusively demonstrated that the TLR2 polymorphism in bank voles causes variation in susceptibility to B. afzelii in this important reservoir host. To date, all the work on the TLR2 polymorphism and B. afzelii infection in bank voles has been correlative in nature13,14,26. Experimental infections are needed to further confirm whether the TLR2 polymorphism in this species influences variation in susceptibility to infection with B. afzelii. The two aims of this study were to determine whether the TLR2 polymorphism in wild bank voles influences variation in the probability of infection with B. afzelii (hereafter referred to as host susceptibility) and variation in B. afzelii spirochete abundance in host tissues (hereafter referred to as host spirochete load). To test this hypothesis, we challenged Borrelia-free, lab-born bank voles of known TLR2 genotype with B. afzelii via tick bite. The TLR2 gene could influence the prevalence of B. afzelii by different mechanisms such as preventing systemic infection and/or spirochete clearance following infection. We expected that compared to the C1C1 genotype, the C2C2 genotype would be less likely to develop a systemic infection following infestation with B. afzelii-infected nymphs. We also expected that the C2C2 genotype would have a lower spirochete load in the tissues than the C1C1 genotype. The importance of the C3 allele was assessed for the first time in this study. Materials and Methods General experimental design. The present study consists of two separate infection experiments: the first experiment was conducted in the summer of 2015 using bank voles from a Swiss colony, whereas the second experiment was conducted in the summer of 2016 using bank voles from a Finnish colony. In these infection experiments, the Swiss and Finnish bank voles of known TLR2 genotype were challenged via tick bite with different isolates of B. afzelii, respectively. The Swiss bank vole colony contained the C1 susceptible allele and the C3 allele, for which the B. afzelii infection phenotype was unknown. The Finnish bank vole colony contained the C1 susceptible allele, the C2 resistance allele, and the C3 allele. ethics statement and animal experimentation permits. All the experiments were performed following the Swiss and Finnish legislation on animal experimentation. For the infection experiment conducted in Switzerland, the commission that is part of the ‘Service de la Consommation et des Affaires Vétérinaires (SCAV)’ of the canton of Vaud, Switzerland evaluated and approved the ethics of this part of the study. The SCAV of the canton of Neuchâtel, Switzerland issued the animal experimentation permit (NE2/2014). The infection experiment conducted in Finland was carried out under the permits of the Finnish Animal Experiment Board (ESAVI/3834/04.10.03/2011, ESAVI/7256/04.10.07/2014 and ESAVI/3457/04.10.07/2015). Breeding of the bank voles in the laboratory. The Swiss and Finnish colonies of bank voles were established by trapping bank voles near Neuchâtel, Switzerland and Jyväskylä, Finland, respectively (section1 in the electronic supplementary material (ESM)). TLR2 genotyping found that the Swiss bank voles carried the C1 and C3 alleles (n = 36 animals; frequencies were 42.2% and and 57.8%, respectively), but not the C2 putative resistance allele (section2 in the ESM). For the Swiss infection experiment, male and female bank voles of known TLR2 genotype were crossed to maximize the number of homozygous C1C1 and C3C3 offspring. A sample of the Finnish colony (n = 48 animals) revealed that the frequencies of the TLR2 allele were as follows: 88.5% C1, 4.2% C2, and 7.3% C3. For the Finnish infection experiment, bank voles were bred to maximize the number of homozygous C1C1, C2C2 and C3C3 offspring. All lab-born offspring were genotyped with respect to their TLR2 locus. TLR2 genotyping of the bank voles is described in section2 in the ESM. strains of B. afzelii. Our original intention was to challenge the Swiss and Finnish bank voles with ticks carrying a single Swiss strain (NE4049) and a single Finnish strain (Fin-Jyv-A3) of B. afzelii, respectively. We chose these two strains because our previous work had shown that they are competent at establishing infection in laboratory mice29–32. Due to a combination of experimental error and time constraints, we used nymphs that were co-infected with two strains of B. afzelii. The Swiss bank voles were challenged with nymphs co-infected with a local Swiss strain (NE4049) and a foreign Austrian strain (E61). The Finnish bank voles were challenged with nymphs that were co-infected with a local Finnish strain (Fin-Jyv-A3) and a foreign Swiss strain (NE4049). The 3 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ origin and genetics of these B. afzelii strains is described in section3 in the ESM. We used a strain-specific qPCR to confirm that the local strain of B. afzelii had established infection in the bank voles (section3 in the ESM). Infectious challenge of bank voles with B. afzelii-infected nymphal ticks. All animals were Borrelia-free, lab-born individuals and were in the adult stage (older than 2 months) at the time of the challenge with B. afzelii-infected nymphs. For the Swiss infection experiment, 50 animals were challenged with B. afzelii-infected nymphs and the TLR2 genotypes were as follows: 17 C1C1 (12 females, 5 males), 15 C1C3 (7 females, 8 males), and 18 C3C3 (8 females, 10 males). For the Finnish infection experiment, 50 animals were challenged and theirTLR2 genotypes were as follows: 11 C1C1 (4 females, 7 males), 8 C1C2 (4 females, 4 males), 12 C2C2 (4 females, 8 males), 1 C2C3 (1 male), 8 C1C3 (4 females, 4 males), and 10 C3C3 (6 females, 4 males). In the field, rodents are rarely infested with more than one I. ricinus nymph at a time13,23,24,33. To simulate the natural conditions while also ensuring a good probability of infectious challenge, each animal was infested with 3 randomly selected nymphs. The creation of the experimentally infected nymphs is described in section3 in the ESM. The percentage of B. afzelii-infected nymphs was >90% for both the Swiss and Finnish infection experiments. The nymphs were placed in a neoprene capsule that had been glued to the shaved backs of the bankvoles. During this procedure, animals were anesthetized with a mixture of xylazine, ketamine and PBS (1:2:9; 5 µl per gram of bankvole). The purpose of the capsule is to prevent the bank vole from grooming off and killing the attached nymphs. The animals were fitted with an Elizabethan collar to prevent them from removing the capsules. The capsules were checked on a daily basis over a period of 7 days, and detached engorged nymphs were collected from the capsule and frozen at −20 °C. At 49 days post-infection, the animals were sacrificed using CO2 asphyxiation. Our previous work had shown that this is enough time for B. afzelii to disseminate to all of the organs20,29,30. For each animal, a tissue biopsy was taken from the ear and the dorsal skin from the site of the tick bite using a 2 mm forceps-type punch. The bladder and ankle joints were aseptically dissected29. These internal tissues are typically used to demonstrate that B. burgdorferi sl has disseminated andestablished a systemic infection9,34–38. To determine the infection status of the bank voles, these four tissue samples were tested for B. afzelii using qPCR (see below). Borrelia afzelii infection status of the engorged nymphs and the bank voles. We extracted the DNA from engorged nymphs and bank vole tissue samples and used qPCR targeting the flagellin gene to estimate the spirochete load (for details, see section3 in the ESM). For the bank vole tissue samples, we used the DNA concentration of the DNA extraction to standardize the spirochete load as the number of spirochetes per mg of host DNA (for details, see section3 in the ESM). statistical analyses. General approach. The three response variables included the number of engorged nymphs collected from each bank vole, the infection status of the bank vole (infected, uninfected) and the spirochete load of B. afzelii in the bank vole tissues. These three response variables were analysed using generalized linear models (GLMs) with binomial errors, GLMs with binomial errors, and linear mixed effects models (LMEMs) with normal errors, respectively. The fixed effects included experiment (2 levels: Swiss, Finnish), sex (2 levels: female, male), organ (4 levels: bladder, ear, joint, dorsal skin), and TLR2 genotype. TLR2 genotype was coded in eight different ways that corresponded to different assumptions about the effects of the TLR2 alleles (Table1). Experiment and TLR2 could not be includedin the same model because of partial or complete redundancy between these factors(i.e. the C2 allele only occurs in the Finnish experiment). We thereforeused model selection Name Type of variable # of genotypes Identity of genotypes # of alleles Identity of alleles Geno1 Categorical 6 C1C1, C2C2, C3C3, C1C2, C1C3, C2C3 NA NA Geno2 Categorical 3 C2C2, C2Cx, CxCx; (Cx = C1 = C3) NA NA Geno3 Categorical 3 C1C1, C1Cy, CyCy; (Cy = C2 = C3) NA NA Geno4 Categorical 3 C3C3, C2Cz, CzCz; (Cz = C1 = C2) NA NA Geno5 1 Covariate NA NA 2# of C2 alleles; (C1 = C3) Geno6 1 Covariate NA NA 2# of C1 alleles; (C2 = C3) Geno7 1 Covariate NA NA 2# of C3 alleles; (C1 = C2) Geno8 3 Covariates NA NA 3# of C1, C2, and C3 alleles Table 1. The eight different ways in which TLR2 genotype was modelled are shown. TLR2 genotype was either modelled as a categorical factor where each TLR2 genotype was a different category or as a covariate that counted the number of TLR2 alleles. We reduced the number of genotypes or alleles by setting pairs of alleles or genotypes as equivalent. For example, for Geno2, we assumed that the C1 and C3 alleles are equivalent so that there are only 3 distinct genotypes: C2C2, C2Cx, CxCx, where Cx = C1 = C3. Combining similar genotypes (or alleles) increases the sample size for the remaining genotype categories and thereby increases the power of the statistical test. 4 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ based on the Akaike Information Criterion (AIC) to determine the best model; the advantage of this approach is that it allows us to compare non-nested models. We used the model weights to calculate the % support for each of the fixed effects. We used model averaging to obtain robust parameter estimates and 95% confidence intervals (95% CI) for the fixed effects. A fixed effect is significant when its model-averaged 95% CI does not overlap 0. We used R version 3.4.3 to analyse the data. The GLMs and LMEMs were run using the glm() function in the base package and the lmer() function in the lme4 package, respectively. Model selection and calculation of model-averaged parameter estimates were run using the model.sel() and the model.avg() functions in the MuMIn package. Number of engorged nymphs per bank vole. Each bank vole was infested with 3 nymphs, and the number of engorged nymphs collected from each bank vole was therefore a binomial responsevariable that ranged from 0/3 to 3/3. To test whether the 100 bank voles were exposed to the same infectious challenge, we analysed two response variables: the number of engorged nymphs that were collected per bank vole and the number of engorged B. afzelii-infected nymphs that were collected per bank vole. These two response variables were modelled using GLMs with binomial errors. The fixed factors were experiment, sex, and the eight different ways to code TLR2 genotype. Each vole occurred only once in the analysis so it was not necessary to include bank vole ID as a random effect. TLR2 genotype and infection status of the bank voles. Bank vole infection status is a binomial variable (uninfected, infected) that was modelled using GLMs with binomial errors. The fixed effects were number of B. afzelii-infected nymphs (0, 1, 2, 3), experiment, sex, and the eight different ways to code TLR2 genotype. As there was no variation in infection status among the four organs, we did not include this factor in the analysis. Each bankvole occurred only once in the analysis so it was not necessary to include bank vole ID as a random effect. The analysis was performed for all the bank voles (n = 100) and for the subset of bank voles that had been successfully challenged with B. afzelii-infected nymphs (n = 88). B. afzelii spirochete load of the bank vole tissue samples. The statistical analysis of the B. afzelii spirochete load in the tissue samples was restricted to the subset of infected bank voles (n = 84). For each tissue sample, the geometric mean spirochete load (in 3 μl of DNA template) was calculated for the three replicate qPCRruns. The tissue spirochete loads were standardized to mg of DNA (by dividing by the DNA concentration). This variable was log10-transformed to normalize the residuals. The log10-transformed tissue spirochete loads were modelled using LMEMs with normal errors. The fixed factors were experiment, sex, organ, and the eight different ways to code TLR2 genotype. Organs sampled from the same bank vole are not independent and bank vole identity was therefore modelled as a random factor. Results The C1, C2, and C3 allele clusters encode different TLR2 proteins. The TLR2 gene sequences of the animals in the experimental infection formed three clearly separated clusters that coded for three different protein variants: cluster 1 (C1), cluster 2 (C2) and cluster 3 (C3); these three clusters were the same as the ones described by Tschirren et al.13. The C1 and C2 clusters, C1 and C3 clusters, and C2 and C3 clusters were separated by a genetic distance of 12, 15, and 15 nucleotide differences, respectively, which corresponded to a protein distance of 7, 7, and 4 amino acids, respectively (Fig.S1). A protein model of TLR2 had previously shown that the variants encoded by the C1 and C2 alleles would differ in at least one amino acid in the binding site that is believed to be critical for ligand binding13. We therefore expected that these three variants of theTLR2 protein would differ in their ability to recognize the lipoproteins of B. afzelii and therefore to protect the bank vole against infection via tick bite. Definition of a successful infectious challenge. We collected at least 1 engorged B. afzelii-infected nymph from 83 of the 100 bank voles (TablesS01 and S02 in the ESM). There were 17 bank voles for which we did not recover any engorged B. afzelii-infected nymphs (TablesS01 and S02 in the ESM). Five of these 17 individuals became infected with B. afzelii proving that they had been exposed to an infected nymph (which we failed to recover). Hence, we have proof that 88 of the 100 bank voles were successfully challenged in this study (83 + 5 = 88). The 12 remaining individuals for which there was no proof of an infectious challenge (no infected engorged nymphs, bank voles are uninfected) all came from the Swiss experiment. Number of engorged nymphs per bank vole. For the 50 Swiss bank voles, we collected 84 engorged nymphs (mean = 2.00, range = 0–3 engorged nymphsper bank vole), of which 52 were infected with B. afzelii (mean = 1.24, range = 0–3 engorged infected nymphsper bank vole). For the 50 Finnish bank voles, we collected 131 engorged nymphs (mean = 2.72, range = 2–3 engorged nymphs per bank vole), of which 96 were infected with B. afzelii (mean = 1.92, range = 0–3 engorged infected nymphsper bank vole). For the model selection analysis of the number of engorged nymphs per bank vole, the top 3 models had 99.999% of the support; the remaining 26 models had <0.001% of the support (Table2 and TableS07 in the ESM). The support for individual factors was as follows: experiment (99.999%), sex (32.4%), and TLR2 genotype (<0.001% for 24 models). The model-averaged parameter estimates found that significantly more engorged nymphs were collected per bank vole in the Finnish experiment (TableS08 in the ESM) compared to the Swiss experiment. The results were similar for the number of engorged B. afzelii-infected nymphs and when the analyses were done on the subset of 88 bank voles that had been successfully challenged. These analyses show that the infectious challenge was the same for all TLR2 genotypes. 5 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ Infection status of the bank voles. A bank vole was defined as being infected if it tested positive for B. afzelii for at least one of four organs: (1) bladder, (2) ear, (3) joint, and (4) dorsal skin. There was no ambiguity about the infection status of the 100 bank voles: 84 tested positive for all four organs and 16 tested negative for all four organs. The susceptibility of a host to a pathogen is the probability of acquiring an infection following exposure. In our study, the susceptibility of bank voles to infection with B. afzelii was 95.5% (84 infected/ 88 total; 95% CI = 88.1–98.5%) and was therefore very high. Infection was higher in the Finnish experiment (100.0% = 50/50) than the Swiss experiment (68.0% = 34/50). When the analysis was restricted to the subset of 88 bank voles that had been successfully challenged, infection in the Finnish experiment (100.0% = 50/50) and Swiss experiment (89.5% = 34/38) were similar. Bank vole infection status was initially modelled using GLMs with binomial errors (TableS09 in the ESM). However, due to the lack of variation in infection status (most bankvoles were infected), the standard errors (SE) estimated by the glm() function had very low precision (i.e., SE was ~1000 times bigger than the parameter estimate; TableS10 in the ESM). To avoid this problem with parameter estimation, we re-analysed the data using linear models with normal errors. For the model selection analysis of the linear models of infection status of 100 bank voles, the top 6 models had 99.9% of the support; the remaining 111 models had 0.1% of the support (Table3 and TableS11 in the ESM). The support for individual factors was as follows: number of infected nymphs (>99.9%), experiment (>99.9%), sex (55.6%), and TLR2 genotype (<0.001% for 98 models). The model-averaged parameter estimates found that infection increased significantly with the number of engorged infected nymphs per bank vole and that infection was significantly higher in the Finnish experiment compared to the Swiss experiment (TableS12 in the ESM). We do not present the model selection analysis for the subset of 88 bank voles that had been successfully challenged because there was no variation in infection status (84 infected/ 88 total). We compared the susceptibility of bank voles to infection with B. afzelii between our study and the study by Tschirren et al.13 (for details, see section4 in the ESM). For the study by Tschirren et al.13, the probability of encountering an infected tick in the field was not known, but by setting this probability to a maximum (100%) or a minimum (48.7%), we were able to estimate the susceptibility of each TLR2 genotype. This comparison found that the susceptibility was significantly different between the two studies (Fig.1). Model Model structure df logLik AICc Delta Weight (%) model003 nymphs.engorged~E 2−109.353 222.831 0.000 67.575 model002 nymphs.engorged~E + S 3−109.316 224.881 2.051 24.235 model001 nymphs.engorged~E + S + E:S 4−109.315 227.051 4.221 8.189 model010 nymphs.engorged~geno2 3 −121.250 248.751 25.920 0.000 model022 nymphs.engorged~geno5 2 −122.638 249.399 26.569 0.000 Table 2. Model selection table is shown for the generalized linear models (with binomial errors) of the number of engorged nymphs per bank vole (nymphs.engorged). The analysis was done on the entire data set of 100 bank voles. Of the 29 models, the top 5 models are shown; the top 3 models have 99.999% of the support. TableS09 in the ESM shows all 29 models. The fixed factors are experiment (E), sex (S), and TLR2 genotype. TLR2 genotype was modelled in 8 different ways (geno1, geno2, geno3, geno4, geno5, geno6, geno7, and geno8). For each model, the model structure, modeldegrees of freedom (df), log likelihood, corrected AIC value (AICc), difference in AICc from the top model (Delta), and the support (Weight) expressed as a percentare shown. Model Model structure df logLik AICc Delta Weight (%) model011 infection~E + N + E:N 5−12.287 35.212 0.000 44.374 model007 infection~E + S + N + E:N 6−11.802 36.507 1.295 23.226 model005 infection~E + S + N + E:N + S:N 7−11.164 37.546 2.334 13.817 model003 infection~E + S + N + E:S + E:N 7−11.317 37.851 2.639 11.862 model002 infection ~E + S + N + E:S + E:N + S:N 8−11.032 39.646 4.434 4.835 model001 infection~E + S + N + E:S + E:N + S:N + E:S:N 9−10.826 41.651 6.439 1.774 model014 infection~E + N 4−21.428 51.277 16.065 0.014 model606 infection~geno6 + S + N + geno6:S 6−19.780 52.463 17.251 0.008 model009 infection ~E + X + N 5−20.939 52.517 17.305 0.008 model008 infection ~E + X + N + S:N 6−19.871 52.645 17.433 0.007 Table 3. Model selection table is shown for the linear models of bank vole infection status (infection). The analysis was done on the entire data set of 100 bank voles. Of the 117 models, the top 10 models are shown; the top 6 models have 99.9% of the support. TableS11 in the ESM shows all 117 models. The fixed factors are number of engorged B. afzelii-infected nymphs (N), experiment (E), sex (S), and TLR2 genotype. TLR2 genotype is modelled in 7 different ways (geno1, geno2, geno3, geno4, geno5, geno6, and geno7). For each model, the model structure, modeldegrees of freedom (df), log likelihood, corrected AIC value (AICc), difference in AICc from the top model (Delta), and the support (Weight) expressed as a percentare shown. 6 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ B. afzelii spirochete load of the bank vole tissue samples. For each organ, the repeatability of the log10-transformed tissue spirochete loads was high (range = 71–75%; section5 in the ESM). For the Swiss bank voles, the mean spirochete load per mg of DNA was lowest in the bladder (540 spirochetes per mg of DNA; Table 4), 4.2 times higher in the ear, 5.1 times higher in the dorsal skin, and 8.4 times higher in the ankle joint (Fig.2; Table4). For the Finnish bank voles, the mean spirochete load per mg of DNA was lowest in the bladder (1339 spirochetes per mg of DNA; Table4), 9.4 times higher in the dorsal skin, 10.9 times higher in the ankle joint, and 15.2 times higher in the ear (Fig.2; Table4). Averaged across the four organs, the tissue spirochete loads in the Finnish bank voles were 4.2 times higher than the Swiss bank voles (Fig.2; Table4). For the model selection analysis of tissue spirochete load per mg of DNA, the top 5 models had 99.4% of the support; the remaining 112 models had 0.6% of the support (Table5 and TableS13 in the ESM). The support for individual factors was as follows: experiment (99.99%), sex (11.4%), organ (100.0%), and TLR2 genotype (<0.001% for 98 models). The model-averaged parameter estimates found that the ear, joints, and ventral skin had significantly higher spirochete loads than the bladder (Fig.2; TableS14 in the ESM). The Finnish bank voles had significantly higher spirochete loads in their tissues than the Swiss bank voles (Fig.2; TableS14 in the ESM). Finally, the interaction between experiment and organ was significant because the difference in ear tissue spirochete load between Finnish and Swiss bank voles was higher than the difference for the other tissues (Fig.2; TableS14 in the ESM). Strain-specific qPCR to determine infection success of the local strain. For the sample of infected Swiss bank voles, 88.2% (30/34) were infected with the local strain of B. afzelii (strain NE4049). For the sample of infected Finnish bank voles, 98.0% (49/50) were infected with the local strain of B. afzelii (strain Fin-Jyv-A3). Thus, 94.0% (79/84) of the bank voles became infected with their local (and intended) strain of B. afzelii following the infectious challenge. C1C1 C1C2 C2C2 Susceptibility to B. afzelii (%) 0 20 40 60 80 100 Field1 Field2 Lab Figure 1. The susceptibility of the three bank vole TLR2 genotypes (C1C1, C1C2, and C2C2) to infection with B. afzelii is compared between our lab study (Lab) and the field study by Tschirren et al.13 (Field1, Field2). The field study by Tschirren et al.13 assumed that the exposure rates were identical for the three TLR2 genotypes and that bank voles do not clear the infection. Using these assumptions, the prevalence of infection can be separated into the probability of exposure and the susceptibility to infection following an infectious challenge. The Field1 estimates of susceptibility are based on the unrealistic assumption that 100% of the bank voles were exposed to an infected tick. The Field2 estimates of susceptibility are based on the assumption that 48.6% of the bank voles were exposed to an infected tick, which maximizes the susceptibility of the C1C1 genotype to 100.0%(for details, see section 4 in the ESM). Model Model structure df logLik AICc Delta Weight (%) lm.model1014 log10(spiro.per.mg.DNA)~E + O 7−408.954 832.250 0.000 76.959 lm.model1011 log10(spiro.per.mg.DNA)~E + O + E:O 10 −407.676 836.029 3.779 11.632 lm.model1009 log10(spiro.per.mg.DNA)~E + S + O 8−410.178 836.796 4.547 7.925 lm.model1006 log10(spiro.per.mg.DNA)~E + S + O + E:S 9−410.639 839.830 7.580 1.739 lm.model1007 log10(spiro.per.mg.DNA)~E + S + O + E:O 11 −408.900 840.614 8.364 1.175 lm.model1003 log10(spiro.per.mg.DNA)~E + S + O + E:S + E:O 12 −409.361 843.688 11.438 0.253 lm.model1008 log10(spiro.per.mg.DNA)~E + S + O + S:O 11 −410.562 843.939 11.689 0.223 lm.model1004 log10(spiro.per.mg.DNA)~E + S + O + E:S + S:O 12 −411.023 847.012 14.762 0.048 lm.model1005 log10(spiro.per.mg.DNA)~E + S + O + E:O + S:O 14 −409.259 847.826 15.576 0.032 lm.model1002 log10(spiro.per.mg.DNA)~E + S + O + E:S + E:O + S:O 15 −409.720 850.939 18.690 0.007 Table 5. Model selection table is shown for the linear mixed effects models of the B. afzelii spirochete load in bank vole tissues(spiro.per.mg.DNA). Spirochete load is standardized per mg of DNA and was log10transformed to normalize the residuals (log10(spiro.per.mg.DNA)). The analysis was done on the subset of 84 bank voles infected with B. afzelii. Of the 117 models, the top 10 models are shown; the top 5 models have 99.4% of the support. TableS12 in the ESM shows all 117 models. The fixed factors are experiment (E), organ (O), sex (S), and TLR2 genotype. TLR2 genotype is modelled in 7 different ways (geno1, geno2, geno3, geno4, geno5, geno6, and geno7). For each model, the model structure, modeldegrees of freedom (df), log likelihood, corrected AIC value (AICc), difference in AICc from the top model (Delta), and the support (Weight) expressed as a percentare shown. 7 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ Swiss Finnish 0 1 2 3 4 5 6 Bladder log10(Spirochetes per mg of DNA+1) Swiss Finnish 0 1 2 3 4 5 6 Ear log10(Spirochetes per mg of DNA+1) Swiss Finnish 0 1 2 3 4 5 6 Ankle joint log10(Spirochetes per mg of DNA+1) Swiss Finnish 0 1 2 3 4 5 6 Ventral skin log10(Spirochetes per mg of DNA+1) Figure 2. Organ and experiment had a significant effect on the tissue spirochete load of B. afzelii in the bank voles. The spirochete loads were standardized per mg of DNA and then log10-transformed. For the Finnish bank voles, the tissue spirochete loads were higher compared to the Swiss bank voles. The rank order of the organ spirochete loads (from lowest to highest) depended on the experiment: bladder, ear, ventral skin, ankle joint for the Swiss bank voles and bladder, ventral skin, ankle joint, ear for the Finnish bank voles. Shown are the medians (black line), the 25th and 75th percentiles (edges of the box), the minimum and maximum values (whiskers), and the outliers (circles). Experiment Organ Mean LL UL Switzerland Bladder 540 286 1017 Switzerland Ear 2283 1211 4303 Switzerland Joint 4531 2404 8541 Switzerland Skin 2768 1469 5218 Finland Bladder 1339 794 2259 Finland Ear 20300 12036 34240 Finland Joint 14533 8616 24512 Finland Skin 12587 7463 21230 Table 4. Mean tissue spirochete loads in the bank voles are shown for each organ in both the Swiss and Finnish infection experiments. Bank vole organs were dissected at 49 days post-infection. The tissue spirochete load was standardized per mg of DNA (units are spirochetes per mg of DNA). Shown are the means, and the lower limits (LL) and upper limits (UL) of the 95% confidence interval. 8 Scientific RepoRts | (2019) 9:6711 | https://doi.org/10.1038/s41598-019-43160-3 www.nature.com/scientificreports www.nature.com/scientificreports/ Discussion In this study, we standardized exposure to infected ticks and tested whether a genetic polymorphism at the TLR2 locus in the bank vole explained variation in susceptibility to B. afzelii, a common and important tick-borne pathogen. Most studies on the role of TLR2 polymorphisms in the susceptibility to B. burgdorferi sl pathogens have been association studies in humans and wild rodents4,13,14,26,39,40. To our knowledge, there are no experimental infection studies showing that a TLR2 polymorphism influences variation in susceptibility to infection with B. burgdorferi sl. Under the laboratory conditions of our study, ~100% of all bank voles become infected following exposure to B. afzelii-infected ticks. Thus, our study found no evidence that bank voles with different TLR2 genotypes (C1C1, C2C2, C3C3) differed in their susceptibility to infection with B. afzelii. One limitation of this study was the small sample size for the C2C2 genotypes (n = 12), which limits our power to detect differences in susceptibility to B. afzelii infection between the susceptible (C1C1) and resistant (C2C2) genotypes. The prevalence of B. afzelii infection in our study (95.5%) was 2.5 times higher than the field study by Tschirren et al. (37.5%)13 as shown in Fig.1. This discrepancy is due to differences in the risk of exposure between the two studies. In our study, the risk of exposure was 100.0% for the subset of 88 bank voles that had been successfully challenged (by definition). In the field study by Tschirren et al.13, the risk of exposure was unknown, but was assumed to be identical for the three TLR2 genotypes. Under this assumption and after minimizing the risk of exposure (subject to the assumption that bank voles cannot clear their infection), the susceptibility of the resistant C2C2 TLR2 genotype remained significantly lower in the study by Tschirren et al.13 compared to our study (Fig.1). Why did we not find the expected differences in susceptibility to infection with B. afzelii between the TLR2 genotypes? One explanation for the different infection prevalences in the field study by Tschirren et al.13 is that the three TLR2 genotypes differed in their risk of exposure to B. afzelii-infected nymphs. Fine-scale spatial studies have shown that the density of infected nymphs (DIN) and the risk of exposure can vary dramatically over very small distances41. If by chance, families of bank voles carrying the C2 allele live in areas of the sampling grid that have a low DIN compared to families of bank voles carrying the C1 allele, then observed differences in infection prevalence would be caused by these spatial differences in the risk of exposure and not by differences in susceptibility between the TLR2 genotypes. Differences in exposure can also explain why the prevalence of B. afzelii infection was 2.5 times higher in our lab study compared to the field study by Tschirren et al.13. A second explanation involves grooming, which is an important behaviour that protects vertebrate hosts against ectoparasites such as ticks42. Previous studies have shown that the probability of nymph-to-host transmission of B. burgdorferi sl pathogens increases with the duration of attachment of the nymphal tick to the vertebrate host43,44. In nature, the normal grooming behaviour of the vertebrate host is a significant cause of tick mortality that would reduce the risk of pathogen transmission following nymphal attachment42,45. In the present study, we prevented the bank voles from grooming off the nymphs by fitting them with a collar and by placing the nymphs in a protective capsule. If C2C2 individuals have a more effective grooming response than C1C1 individuals, they would be less likely to become infected with B. afzelii following the attachment of an infected nymph. The link between the immune system and grooming behaviour is not so far-fetched because the former has itch-generation mechanisms (e.g. release of histamine by mast cells) that would stimulate the latter46. The absence of the grooming defence mechanism can also explain why the prevalence of B. afzelii infection was 2.5 times higher in our lab study compared to the field study by Tschirren et al.13. A third explanation involves acquired immunity, which can influence susceptibility to infection with B. afzelii. We have recently shown that infected female bank voles can transmit maternal antibodies to their offspring that protect against infection with B. afzelii47–49. Bank voles can also develop acquired immunity against I. ricinus ticks50, and this anti-tick immunity protects against infection with B. burgdorferi sl51–53. Thus variation in maternal antibodies and/or anti-tick immunity in wild bank vole populations will influence variation in susceptibility to infection with B. burgdorferi sl. In our study, the bank voles did not have any antibodies to either B. afzelii or to I. ricinus ticks at the time of the infectious challenge (i.e. they were completey naive). In contrast, field studies can not control for this variation in acquired immunity13,14,26. The absence of maternal antibodies or anti-tick immunity can also explain why the prevalence of B. afzelii infection was 2.5 times higher in our lab study compared to the field study by Tschirren et al.13 A fourth explanation involves the ability of bank voles to clear B. afzelii. The consensus is that rodent reservoir hosts cannot clear B. burgdorferi sl18–20,23,27,54. In our study, there was no evidence of clearance at 49 days post-infection, as the four tissues in the 84 infected bank voles were all positive for B. afzelii. However, we recently found clearance of spirochetes from ear tissues in bank voles that had been experimentally infected with B. afzelii strain NE404948. Bank voles that had cleared the infection from their ear tissues still had very high spirochete loads in other tissues (bladder, heart, dorsal skin, ventral skin)48. This study suggests that ear tissue biopsies might underestimate the infection status of bank voles in the field48. In most field studies, the infection status of the bank voles is determined by taking ear tissue biopsies13,14,26. Thus, another explanation for the difference in prevalence of B. afzelii infection between the two studies, is that we determined infection status by testing for spirochetes in multiple internal organs. A fifth explanation is that our laboratory environment was so stressful that it overwhelmed the variation in susceptibility to infection between the TLR2 genotypes. Physiological stress can suppress the host immune system and increase susceptibility to infection with pathogens55–58. Although we cannot rule out the stress-immunosuppression explanation, we believe that it is unlikely for the following reasons. First, there is a long history in Lyme disease research of performing experimental infections with wild animals in the lab, and this work has successfully determined the susceptibility of many vertebrate hosts to various B. burgdorferi sl pathogens18,19,59–65. Second, as mentioned previously, using the same experimental conditions described in the present study, female bank voles infected with B. afzelii transmitted antibodies to their offspring, which protected the offspring against infected ticks47–49. The creation of antibodies in the mothers and their ability to block infection