NGS population genetics analyses reveal divergent evolution of a Lyme Borreliosis agent in Europe and Asia.

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Original article

NGS population genetics analyses reveal divergent evolution of a Lyme Borreliosis agent in Europe and Asia Fanny Gatzmann a , Dirk Metzler a , Stefan Krebs b , Helmut Blum b , Andreas Sing c , Ai Takano d,e , Hiroki Kawabata e,f , Volker Fingerle c , Gabriele Margos c,∗,1 , Noémie S. Becker a,1 a

LMU Munich, Department Biology II, Großhaderner Str. 2, 82152 Munich, Germany Gene Center Munich, Lafuga, LMU Munich, Feodor-Lynen-Strasse 25, 81377 Munich, Germany c Bayerisches Landesamt für Gesundheits- und Lebensmittelsicherheit (LGL), Veterinärstraße 2, 85764 Oberschleißheim, Germany d Department of Veterinary Medicine, Joint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, Yamaguchi 753-8515, Japan e Department of Bacteriology-I, National Institute of Infectious Diseases, Tokyo 162-8640, Japan f United Graduate School of Agricultural Science and Veterinary Science, Gifu University, Gifu, 501-1193, Japan b

a r t i c l e

i n f o

Article history: Received 24 July 2014 Received in revised form 17 February 2015 Accepted 18 February 2015 Available online xxx Keywords: Borrelia bavariensis Ixodes ricinus Ixodes persulcatus Lyme disease Population genetics Evolution

a b s t r a c t Borrelia bavariensis is a recently described agent of Lyme disease within the B. burgdorferi sensu lato species complex and exhibits a strong capacity for human pathogenicity. B. bavariensis strains are widely distributed in Eurasia spanning the distribution range of the tick vectors Ixodes persulcatus and I. ricinus. It has been suggested that B. bavariensis forms two populations, one of which arose through vector adaptation and geographic expansion. We have performed phylogenetic and population genetic analyses with next-generation sequencing data of 26 strains of B. bavariensis targeting the main linear chromosome and two plasmids (lp54, cp26). A very low number of single nucleotide polymorphisms (SNPs) was found in the European population and a deep branching pattern between European and Asian B. bavariensis was observed in all phylogenies. The results confirm the population structure of B. bavariensis and strongly support the hypothesis of clonal expansion of the European population of B. bavariensis. In addition, signals of positive selection identified in the populations further support the hypothesis that the European population of B. bavariensis likely underwent vector adaptation in its recent evolutionary history. Identified genes represent promising candidates for experimental vector adaptation studies. Thus, this species forms a very good model to study vector adaptation, which is known to play an important role in the geographic distribution of B. burgdorferi. Analysis of well known virulence determinants that are attributed to severity of clinical manifestation in B. burgdorferi s.s. revealed no variation within the European population of B. bavariensis, underlining the importance of including various Borrelia species into investigations that aim to understand the pathogenesis of Lyme disease agents. © 2015 Elsevier GmbH. All rights reserved.

Introduction

Abbreviations: NGS, next generation sequencing; SNP, single nucleotide polymorphism; LB, Lyme Borreliosis; EM, erythema migrans; dN/dS, ratio of nonsynonymous to synonymous SNPs; FDR, false discovery rate. ∗ Corresponding author. Tel.: +49 913168085883. E-mail addresses: [email protected] (F. Gatzmann), [email protected] (D. Metzler), [email protected] (S. Krebs), [email protected] (H. Blum), [email protected] (A. Sing), [email protected] (A. Takano), [email protected] (H. Kawabata), volker.fi[email protected] (V. Fingerle), [email protected] (G. Margos), [email protected] (N.S. Becker). 1 These authors contributed equally to this work.

Lyme Borreliosis (LB, also called Lyme disease) is caused by several species of the Borrelia burgdorferi sensu lato complex including B. burgdorferi sensu stricto (s.s.), B. afzelii, B. spielmanii, B. garinii and B. bavariensis. Often termed a multi-systemic disease, LB can manifest itself with varying symptoms in different patients, ranging from the skin condition erythema migrans (EM) to more severe conditions including arthritis, neurological manifestations (neuroborreliosis) or lymphocytoma (Stanek et al., 2011; Stanek and Strle, 2009). It has been suggested that symptoms caused by the different species vary in their manifestations, for example B. afzelii was mainly associated with

http://dx.doi.org/10.1016/j.ttbdis.2015.02.008 1877-959X/© 2015 Elsevier GmbH. All rights reserved.

Please cite this article in press as: Gatzmann, F., et al., NGS population genetics analyses reveal divergent evolution of a Lyme Borreliosis agent in Europe and Asia. Ticks Tick-borne Dis. (2015), http://dx.doi.org/10.1016/j.ttbdis.2015.02.008

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skin manifestations while B. garinii and B. bavariensis have been associated with neuroborreliosis (Stanek et al., 2011). However, there are cases that deviate from this principle and cases of neuroborreliosis or EM have been reported for all LB causing Borrelia species, albeit these may occur at different frequencies. The question of what determines the pathogenicity of LB spirochetes remains of continuous scientific and medical interest. Information on the geographic distribution of the different species causing LB is important for epidemiological and public health purposes. LB is a zoonosis, the spirochetes are being maintained in natural transmission cycles between tick vectors and animal reservoir hosts. Bridge vectors that are known to transmit Borrelia to humans are Ixodes ricinus in Europe, Ixodes persulcatus in Eastern Europe and Asia, Ixodes scapularis and Ixodes pacificus in North America (Kurtenbach et al., 2006). The spatial distribution of Borrelia species is not uniform, and it has been suggested that host and vector adaptation contribute to the geographic pattern of species distribution (Korenberg et al., 2002; Margos et al., 2012; Miyamoto and Masuzawa, 2002). The species B. bavariensis was previously categorized as one serotype of the B. garinii group and was raised to species level only recently (Margos et al., 2009, 2013). This species is distributed in Eurasia (Margos et al., 2013; Mukhacheva and Kovalev, 2013; Scholz et al., 2013; Takano et al., 2011) and is transmitted by rodents (Hu et al., 2001; Huegli et al., 2002), whereas B. garinii utilizes birds as reservoir hosts (Dubska et al., 2009; Hanincova et al., 2003; Taragel’ova et al., 2008). The evolution of these species, and in particular how it switched from one host type to the other, is still unknown. European B. bavariensis were described to have very low genetic diversity (Marconi et al., 1999; Margos et al., 2013), whereas the Asian strains show more diversity (Mukhacheva and Kovalev, 2013; Scholz et al., 2013; Takano et al., 2011). In previous studies, strains now constituting the species B. bavariensis were termed NT29 and NT29-like in Eastern Europe and Asia, while European-type B. bavariensis were referred to as ospA type 4. Field studies have shown that Asian-type (NT29-like) B. bavariensis are exclusively found in, and transmitted by, I. persulcatus (Geller et al., 2013; Korenberg et al., 2002; Masuzawa et al., 2005). In Estonia, in a zone of overlap of I. persulcatus and I. ricinus populations, 28% of I. persulcatus were found to be infected with NT29-like strains while not a single infection of I. ricinus with NT29 strains was found (Geller et al., 2013). Similar results were found in other geographic regions of I. ricinus and I. persulcatus sympatry – only NT29-like strains have ever been found in I. persulcatus (Masuzawa et al., 2005). In contrast, the European B. bavariensis (ospA-type 4) are exclusively found I. ricinus (Fingerle et al., 2008; Geller et al., 2013; Skuballa et al., 2007), occasionally co-infecting ticks together with B. afzelii or B. burgdorferi s.s. (Fingerle et al., 2008). This situation has led to the hypothesis that B. bavariensis is divided into two populations: a genetically homogeneous European population (suggesting spread of a single strain) and a genetically heterogeneous Asian population (Margos et al., 2013). The strain collection of the German National Reference Centre contains a number of B. bavariensis strains isolated from patients with EM, but equally often from patients with neuroborreliosis (Wilske et al., 1996). In this study, we describe for the first time the fine-scale phylogeny and evolution of B. bavariensis using next-generation sequencing (NGS) whole genome data from eight Japanese and 18 European isolates from ticks as well as patients showing signs of neuroborreliosis and patients with EM. Our results highlight regions of the genome that might have been under selection in the evolution of B. bavariensis and that may be involved in pathogenicity or vector adaptation of Borrelia species.

Materials and methods Samples We analyzed 26 strains of B. bavariensis isolated from humans with LB (neuroborreliosis, EM or arthritis) or tick tissues. 18 strains were sampled in Europe (Austria, Denmark, Germany, Netherlands and Slovenia) and eight strains came from Japan. As an outgroup we also sequenced two samples from the sister species B. garinii from Germany and Japan. Information on the samples can be found in Table S1.

Sequencing and data processing ´ Borrelia cultures grown under standard conditions (RuzicSabljic´ and Strle, 2004) were used for DNA extraction via a Maxwell® 16 (Promega, Germany). Following DNA quantification, libraries were prepared according to Nextera DNA sample preparation guide (NexteraXT, Illumina, San Diego, USA). The samples were diluted to 1–50 ng/␮l concentration and “tagmented” by simultaneously fragmenting DNA using transposomes and adding adapters. After tagmentation samples having adapters on both ends underwent five PCR cycles to amplify the product and to add index primers. The resulting libraries were then validated using Agilent 2100 Bioanalyser (DNA 1500 chip, Agilent, Santa Clara, USA). Sequencing was performed on an Illumina MiSeq platform that produced paired-end reads of 250 bp (Gen Centre, Lafuga, LMU Munich; Source BioScience, Cambridge, UK). Some low quality samples were repeated on an Illumina HiSeq platform producing 100 bp long paired-end reads (Source BioScience). We thus had either HiSeq or MiSeq paired-end reads for each sample. Mean median coverage was 194.2 (minimum coverage 39.9 for sample PRof and maximum coverage 1535.17 for sample PWin). Read filtering, de novo assembly with two assemblers (Li et al., 2010; Zerbino and Birney, 2008), alignment to the chromosome and plasmids cp26 and lp54 of reference sequence PBi (GenBank accession number NC 006156.1) (Glöckner et al., 2004) and SNP calling were performed using the Galaxy (Blankenberg et al., 2010; Giardine et al., 2005; Goecks et al., 2010) platform maintained at LMU Genzentrum. See supplementary material and methods for detailed analyses. The workflow used in Galaxy (Blankenberg et al., 2010; Giardine et al., 2005; Goecks et al., 2010) and our python v2.7.3 (Lutz, 2009) scripts for pileup (Li et al., 2009) conversion to FASTA are available upon request. Data were missing for two European strains (PNi and PBN) for the plasmid lp54 due to low quality. In the chromosomal phylogenetic reconstruction presented in Fig. S1, we included two samples listed in GenBank (Benson et al., 2013) as B. garinii strains from Russia (BgVir GenBank accession number NC 017717.1 (Brenner et al., 2012)) and China (NMJW1 GenBank accession number NC 018747.1 (Jiang et al., 2012)), and which we suspected to be B. bavariensis due to their association with rodents (and not birds as B. garinii). Each sequence was aligned independently to PBi reference sequence (Glöckner et al., 2004) using kalign v2.04 (Lassmann and Sonnhammer, 2005) with default settings.

Nucleotide diversity We estimated the nucleotide diversity ␲ (Nei, 1987) using the R package pegas v0.5 (Paradis, 2010) separately for the chromosome, plasmid cp26 and lp54 (Table 1) and for individual genes from the reference sequence for B. bavariensis (PBi (Glöckner et al., 2004)). We recorded the 5% most extreme genes in the Japanese population as loci potentially under specific evolutive constraints and show


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Table 1 Nucleotide diversity () (Nei, 1987) and neutrality indices (Fu and Li, 1993; Tajima, 1989) estimated using R package ape (Paradis et al., 2004) on the chromosome and plasmids cp26 and lp54 for the European (EU) and Japanese (JA) B. bavariensis populations. Pop

Segment

Samples

Tajima’s D

D*

F*

D

F

EU EU EU JA JA JA

chr cp26 lp54 chr cp26 lp54

18 18 16 8 8 8

1.08 × 10−4 1.62 × 10−4 1.82 × 10−4 9.13 × 10−3 1.47 × 10−2 3.47 × 10−2

−1.5 −2.07** −0.74 −1.12 −0.73 −0.53

−0.49 −1.19 −0.2 −1.6 −1.41 −0.68

−0.59 −1.27 −0.3 −1.49 −1.2 −0.3

0.62 0.87 0.38 −1.17 −1.1 −0.14

0.29 0.34 0.16 −1.29 −1.08 0.1

Significance thresholds: **[0.05;0.01[.

them in Table S2. Values for the European population were so low that we could not identify regions with specific high or low values. Detection of demographic evolution We performed, on each population separately, five tests of detection of departure from neutral evolution: Tajima’s D (Tajima, 1989), Fu and Li’s D, D*, F and F* (Fu and Li, 1993) using R package ape v3.1.2 (Paradis et al., 2004). For the two tests requiring an outgroup (F and D (Fu and Li, 1993)), data from one of our two B. garinii strains (European or Japanese strain respectively) were used. Table 1 presents the value of these statistics. Recombination The four-gamete condition introduced by Hudson and Kaplan (1985) detects recombining sites under an infinite-sites model. Considering two polymorphic sites in a population, mutation alone can produce only three allele combinations (haplotypes). If four are observed, we say that the four-gamete condition is violated, and either recombination or double-mutation must have occurred. As an infinite-sites model does not apply to our data, these violation signals are thus ambiguous and should only be interpreted as evidence of recombination if they cannot be explained by few back mutations or double hits. We applied the four-gamete condition on the Japanese population only, as the diversity was too low in the European population. The ordered list of segregating sites was divided into blocks containing the same number of sites (12 for the chromosome and plasmid lp54 and 6 for plasmid cp26). We then tested if more than three allele combinations were present when comparing a pair of SNPs belonging to two different blocks (the SNP pair received a score of 1 or 0 accordingly) and averaged the scores over SNP pairs to compute the score value for one pair of blocks. Genes showing extremely high four-gamete scores in the Japanese population are shown in Table S3. The PhiTest implemented in the software SplitsTree4 (version 4.1.3.1 (Huson and Bryant, 2006) was also used to test for recombination in the Japanese population of B. bavariensis. Details are given in Supplemental Methods, Table S4 and Figs. S2–S4. Reconstructing phylogenies We used a Bayesian software for evolutionary inference, BEAST v1.7.5 (Drummond and Rambaut, 2007), to reconstruct phylogenies for our dataset, including two B. garinii identified as outgroup by the programme. We reconstructed trees for the chromosome and the two plasmids independently. The chosen priors for all parameters of this Bayesian analysis can be found in supplementary methods. In addition, we also reconstructed, using the same method but for the main chromosome only, a phylogeny including two samples that had previously been classified as B. garinii samples (see Sequencing and data processing). This phylogeny is shown in Fig. S1. In addition, we also used the software ClonalFrame1.1 (Didelot and Falush, 2007) to reconstruct the phylogeny and estimate ratios

of recombination to mutation rate and of external to internal branch lengths (to detect expansion) that are presented in Table S5. The software was launched with default parameters on the whole chromosome sequence and independently on each one of the two plasmids. The default chain length was 100,000 iterations (including 50,000 burn-in) and three independent runs showed high convergence for all parameters for the main chromosome and for plasmid cp26 (all convergence ratios below 1.1). However for plasmid lp54, convergence was very low even when increasing the chain length. In Table S5, we present the results obtained for one run of a total length of 1,000,000 iterations (including 500,000 iterations of burn-in) but convergence was still low for this plasmid with similar runs. The trees reconstructed using ClonalFrame (Didelot and Falush, 2007) were very similar to those obtained with BEAST (Drummond and Rambaut, 2007) for the chromosome and plasmid cp26 (data not shown). However, the lp54 ClonalFrame trees were more different, but, as no satisfying values of convergence between runs could be obtained, these phylogenies cannot be considered as reliable (data not shown). Detection of selection We used the codeML tool from PAML v4.8 (Yang, 2007) for detection of selection using ratios of non-synonymous to synonymous SNPs (dN/dS) for 649 genes of the reference sequence PBi (Glöckner et al., 2004) showing at least 30 SNPs in our sample and with no more than 20% missing data. CodeML (Yang, 2007) allows testing for departure from neutrality on the global phylogeny and on a particular branch of interest (see supplementary methods for more details). We used a likelihood-ratio test between a model where the dN/dS ratio on the branch under study (branch leading to the European or Japanese population) was fixed to 1, and a model allowing this rate to be greater than 1 (positive selection), and corrected the p values using false discovery rate (FDR) correction. Results We produced whole-genome NGS data for 26 strains from two populations of the Lyme Borreliosis agent B. bavariensis and aligned them to the chromosome and plasmids cp26 and lp54 of the reference sequence PBi (Glöckner et al., 2004) (see information on the samples in Table S1). The nucleotide diversity per site (␲) is a measure of genetic variation within populations. We estimated ␲ (Innan et al., 1999; Nei, 1987) in each population (Table 1) and found that the diversity was very high in the Japanese population compared to the European population, as expected if the European B. bavariensis emerged through a recent founder event. Indeed, ␲ for the chromosome was only 1.01 × 10−4 in the European population while it reached 9.13 × 10−3 in the Japanese population. Nucleotide diversity varied across the genome and was as high as 0.0347 for the Japanese plasmid lp54. We also estimated ␲ in each gene from the reference sequence PBi (Glöckner et al., 2004) and show in Table S2 the 2.5% most conserved and most diverse genes for the Japanese




population (diversity was so low in the European population that no regions with specifically high or low values could be detected). Some genes were found to be highly conserved, including the region spanning from 505 to 509.7 kb on the chromosome, which contains a cluster of genes encoding ribosomal proteins. This result was not surprising since such proteins are probably under strong negative selection, which remains to be confirmed. The ospC gene (BGB18), which has already been shown to be highly diverse in several Borrelia populations (Barbour and Travinsky, 2010; Wang et al., 1999), had the highest nucleotide diversity on plasmid cp26 (0.107) in the Japanese population. The dbpA gene (BGA21) has also been repeatedly reported to be diverse and, while it shows a large diversity in the Japanese isolates (0.196), it is fully conserved in the European population. We computed several statistics to detect departure from neutral evolution: Tajima’s D (Tajima, 1989), Fu and Li’s D, D*, F and F* (Fu and Li, 1993), on the main chromosome and on each of the two plasmids in each of the two populations (Table 1). All but one value of these statistics for the Japanese population were negative, which could be the signal of a population expansion. For the European population the intraspecific statistics (Tajima’s D, D* and F*) showed negative values and statistics requiring an outgroup to identify the ancestral state (F and D) showed positive values. This pattern could be due to the influence of the sequences used as an outgroup as a Japanese B. garinii strain was used for the Japanese B. bavariensis statistics and a European B. garinii for the European B. bavariensis statistics. The only marginally significant value, however, was Tajima’s D for cp26 in the European B. bavariensis (p = 0.039 without multiple-testing correction). However, the phylogenies reconstructed using ClonalFrame (Didelot and Falush, 2007) showed a significant signal of expansion for the chromosome and plasmid cp26, as detected by the external to internal ratio test (see Table S5). We inferred recombination, that is lateral gene transfer, by applying the four-gamete condition (Hudson and Kaplan, 1985) and the PhiTest implemented in SplitsTree4 (Huson and Bryant, 2006) (see Materials and methods). The four-gamete test was applied over blocks of 12 SNPs for the chromosome and plasmid lp54 and of 6 SNPs for cp26 for the Japanese population. The mean block score was 0.148 for the chromosome, 0.058 for lp54, and 0.239 for cp26, where low numbers indicate low recombination. Regions showing the highest 2.5% probability of recombination (see Table S3) include two genes which were previously reported as undergoing recombination in various Borrelia species, ospC (BGB18) and dbpA (BGA21). Other regions with high recombination have not been described before, as for example a chromosomal region spanning from 502.7 to 504.3 kb, containing several ribosomal proteins that might have been acquired by recombination during the evolution of the Japanese B. bavariensis. The Phi test detected statistically significant evidence for recombination for the chromosome (p = 0.0) and in plasmid cp26 (p = 5.475E−11) but not for plasmid lp54 (p = 0.9408) (see Figs. S2–S4). Similar results were obtained when strain HT59 was used as an outgroup (chromosome p = 0.0; cp26 p = 2.564E−12; lp54 p = 0.1582). In addition, the ratio of recombination to substitution rates estimated by ClonaFrame (Didelot and Falush, 2007) was lower than one in each segment, indicating that mutation remained the leading force of evolution. Recombination seemed to be more important in the chromosome as compared to both plasmids (ratio 0.222 for the chromosome and 0.048 and 0.040 for plasmids cp26 and lp54, respectively; see Table S5). We reconstructed phylogenies using a Bayesian software for evolutionary inference, BEAST v1.7.5 (Drummond and Rambaut, 2007), for the complete sequence data and for sequence data excluding regions with high indication of recombination. The phylogenies reconstructed with or without potentially recombining regions were extremely similar, so we show here only

the phylogenies using all regions for the chromosome and each plasmid (Fig. 1). The trees were rooted using two B. garinii samples (PFr and HT59) as outgroup. B. garinii and B. bavariensis strains form distinct cluster in the tree, as do the European and Japanese B. bavariensis. The European samples show a high homogeneity despite their geographic distances, while the Japanese population is far more structured. We also included two GenBank sequences, which are listed as B. garinii strains from Russia (BgVir) and China (NMJW1) (Brenner et al., 2012; Jiang et al., 2012), and which we suspected to be B. bavariensis due to their association with rodents (and not birds as expected for ‘true’ B. garinii). Indeed, as shown in Fig. S1, these two samples cluster within the Japanese B. bavariensis clade in our phylogeny. We therefore suggest they should be classified as B. bavariensis. This phylogeny, however, shows some differences with respect to the trees reconstructed without the two GenBank samples: the European B. bavariensis are shown as a sub-sample of the Japanese group. This shows that including more samples from other Eurasian regions might help us to understand how and from where the European population evolved. We used codeML from PAML v4.8 (Yang, 2007) to detect selection along the branch leading to the Japanese population and the branch leading to the European population. We included all genes present in the PBi reference (Glöckner et al., 2004) that showed at least 30 SNPs in our samples (649 genes in total) (see Table 2). The dN/dS of the global phylogeny, as estimated using model 0 (see Materials and methods), was 1, indicating positive selection, along the branches leading to the European and the Japanese populations (see Materials and methods). Eleven genes on the European branch and two genes on the Japanese branch were identified, but only one of the two genes identified in the Japanese population remained significant after FDR correction for multiple testing. We show in Table 2 this gene (confirmed to be under positive selection) as well as the 12 other genes that can be seen as candidates for positive selection. Discussion We produced NGS data for the Lyme disease agent B. bavariensis and focused our analyses on the main linear chromosome and two plasmids, cp26 and lp54. The data confirmed the species status for B. bavariensis, which differs clearly from the sister species B. garinii. The population genetics analyses conducted here showed two populations with very distinct evolutionary histories: a European population with a very low genetic diversity compared to a structured Asian population represented by strains from Japan. We identified loci as candidates for selection and found again that the two B. bavariensis populations differed. Comparison of the B. bavariensis populations Our nucleotide diversity and phylogenetic analyses do confirm the species status of B. bavariensis (Margos et al., 2013, 2009), and that it consists of two populations: a diverse Asian population and a genetically homogeneous European population. The observed difference in genetic heterogeneity cannot be attributed to different geographic scales of sample origin. The samples from Europe originated from Denmark, The Netherlands, Germany and Slovenia, a geographic region that is larger than the geographic region of origin of Japanese samples (Hokkaido and Honshu islands), and, although the European region is not divided into islands, it contains many other geographical barriers (mountains, rivers . . .) that may affect the heterogeneity of B. bavariensis. In addition, BgVir (Brenner




5

Fig. 1. Phylogenies reconstructed by BEAST (Drummond and Rambaut, 2007) for the sample containing Japanese (black circles) and European (dark grey squares) B. bavariensis for the chromosome (a), plasmid cp26 (b) and lp54 (c). The trees were rooted using two B. garinii samples (light grey). Numbers on the deep nodes indicate posterior probabilities among 9000 trees sampled from the iteration chain (the first 1000 trees were erased as burn-in). No posterior probabilities are shown within the European block due to lack of space. The scale bars are expressed in units of substitution per site. Table 2 Genes identified as candidates for positive selection using codeML from PAML v4.8 (Yang, 2007). Pop

Segment

Gene ID

Sites

ω

Function

EU EU EU EU EU EU EU EU EU EU EU JA JA

chr chr chr chr chr chr chr chr chr lp54 lp54 lp54 lp54

BG0142 BG0275 BG0298 BG0327 BG0359 BG0368 BG0706 BG0748 BG0827a BGA04 BGA37 BGA03 BGA65

65 43 50 148 82 125 61 36 191 89 72 78 180

29.8 41.5 41.5 175.9 22.9 6.9 25.8 39.2 48.8 49.0 15.2 999.0 437.7**

mtrC, membrane fusion protein flhB, flagellar biosynthesis protein hslU, ATP-dependent protease Hypothetical protein ctp, carboxyl-terminal protease clpA, ATP-dependent Clp protease, subunit A 3-hydroxy-3-methylglutaryl-CoA ylxH-3, minD-related ATP-binding protein infB, translation initiation factor IF-2 Antigen, S1 Hypothetical protein Antigen, S2 Antigen, P35, putative

Notes: Sites: number of SNP identified in the gene. ω: dN/dS ratio on the focal branch (branch leading to the European or Japanese population). Significance thresholds after FDR correction: **[0.01;0.005[. a Gene with an extreme high four-gamete score for recombination (Table S3).




et al., 2012) and NMJW1 (Jiang et al., 2012), two strains previously reported as B. garinii, respectively from Russia and China in Genbank (Benson et al., 2013) clustered with the Asian B. bavariensis in the phylogeny (Fig. S1) and can therefore be considered members of the species B. bavariensis. It seems unlikely that the genetic homogeneity of European B. bavariensis stems from the fact that there are fewer horizontal transfers than in other Borrelia species due to low prevalence. Other Borrelia species with low prevalence or a focal distribution in Europe, e.g. B. spielmanii or B. lusitaniae, showed genetic heterogeneity when analyzed with MLST while B. bavariensis did not. The very low diversity and short branches in the phylogeny of the European population suggests a recent founding event that has been suggested to be linked to the switch to the European vector I. ricinus. The species split in the phylogenies (between B. bavariensis and B. garinii) could be due to host adaptation (rodents vs. birds), while the population split within B. bavariensis could be caused by adaptation to different tick vectors. We did not detect any bottleneck signal using neutrality indices in the European population. However, the very low diversity in the sample drastically reduced the power of our analyses. The European samples analyzed here all come from patient tissues, and it may therefore be possible that the population within ticks is more diverse. However, no tick isolate is available for NGS from the European population, and MLST data suggest that B. bavariensis in European ticks is equally clonal. In fact, MLST alleles genotyped from tick strains are identical to those found in patients (Rieger et al., own unpublished data). Due to the lack of knowledge on the mutation rate in Borrelia, we were not able to date the species or population split. We still hypothesize that the founding of the European population is recent, as there is very little diversity within this population despite its wide distribution in Europe (from Denmark to Slovenia). Support for the hypothesis of vector adaptation We identified several loci under potential positive selection in each one of the populations under study. No gene was found to be selected in both populations which is in line with the hypothesis that the selective pressures changed when B. bavariensis switched to a different vector. Indeed, several of the potentially selected genes in European strains have been previously shown to be linked to fitness in the vector in studies performed in B. burgdorferi s.s. No reports are available for B. garinii or B. bavariensis, but our results indicate that the genes playing a role in vector association may be essentially the same as in B. burgdorferi s.s. For example, gene flhB (BG0275) has been shown to be up-regulated under conditions that simulate vector conditions (Ojaimi et al., 2002), and it was one of the identified candidates for positive selection in the European population. Another of these genes was the BGA04 antigen S1, and the homologue in B. burgdorferi s.s. (BBA05) has been shown to be upregulated in feeding nymphal ticks (Xu et al., 2010). This gene could thus have been a target of positive selection during the vector shift. The gene BG0827, coding for the translation initiation factor IF-2, was also one of the candidates for positive selection in the European B. bavariensis, and it was found in the region with the highest four-gamete score for recombination (Hudson and Kaplan, 1985) in the Japanese population (Table S3). IF-2 is a GTPase that plays a role in the assembly of ribosomes and promotes binding of the initiator tRNA to the ribosome (Laursen et al., 2005). However, it had been reported that the orthologous gene in B. burgdorferi s.s. (BB-0801) contains tandem repeats (Mongodin et al., 2013), which may have been challenging for proper assembly of the short sequence reads. Indeed, the region containing repeats was not well mapped, but we identified two non-synonymous positions in an adjacent well mapped region of the gene, where the European samples differed from the Japanese and B. garinii strains. Further investigations are needed to investigate the significance of this with respect to vector

adaptation. The mechanism(s) underlying the adaptation to a new vector in Borrelia is not known, as the present study is the first one to explore the evolution of a population that recently switched to a new vector. The genes identified here are thus very promising candidates for understanding the complex relationship between the bacteria and its vector, through functional analysis. Several lines of evidence support the notion that OspA is an important molecule for vector transmission of Borrelia. Firstly, ospA has been shown to be expressed and up-regulated during the vector phase of the life cycle of Borrelia, while it is down-regulated before transmission to the reservoir host (Schwan and Piesman, 2000). A molecule expressed by the tick vector termed TROSPA may act as receptor for ospA (Pal et al., 2004). Although, in our study, ospA was not one of the molecules that appeared to be under positive selection in European B. bavariensis strains, it is noteworthy that all European B. bavariensis strains express the exact same ospA molecule (ospA type 4) that has not been found in Japanese B. bavariensis or B. garinii. Indeed, Japanese B. bavariensis had between 32 and 86 differences (i.e. SNPs) in the ospA sequence with respect to the European B. bavariensis. The significance of this finding requires further investigations. As an example, the role of ospA in vector adaptation could be investigated by replacement and transmission studies. However, genetic manipulation – although common in B. burgdorferi s.s. – has not been established for B. bavariensis, and appropriate tools need to be developed and tested.

Human pathogenicity factors differ between Borrelia species Infection with Borrelia can cause various symptoms in humans including a skin condition termed EM or more severe conditions such as arthritis or neuroborreliosis. B. bavariensis itself can cause each of these symptoms. Since Borrelia do neither produce toxins nor possess known pathogenicity islands, it is unknown whether there is a bacterial genetic basis for the different symptoms seen in patients. Studies in the United States have suggested a relationship between B. burgdorferi s.s. genotype and invasiveness in human patients (Hanincova et al., 2013; Seinost et al., 1999; Wormser et al., 2008). Polymorphisms in the ospC and dbpA genes have been shown to be associated with pathogenicity. Here, we confirm that the ospC gene BGB18 has a high variability in the Japanese population ( = 0.11). The estimated nucleotide diversity (Nei, 1987) was also high in the European populations as compared to the rest of the genome (: 8.3 × 10−4 whereas estimated for the whole plasmid cp26 was 1.6 × 10−4 ) but was due to only one synonymous SNP. The dbpA gene BGA21 was also highly diverse in the Japanese population ( = 0.2) but it was fully conserved in European B. bavariensis. Thus, this shows that, unlike B. burgdorferi s.s., B. bavariensis can cause diverse forms of Lyme borreliosis (neuroborreliosis, arthritis, skin condition) without any non-synonymous variation of the ospC and dbpA loci. We thus hypothesize that the mechanisms underlying pathogenicity and invasiveness in patients were not conserved during the evolution of the various Borrelia species.

Conclusion The genome assemblies that we provide strongly support the notion that the European population of B. bavariensis has entered a new vector and spreads clonally over its distribution range. We also identified candidate genes for vector adaptation that should be investigated in further experimental studies. This study shows that including various Borrelia species is crucial to understand pathomechanisms of Lyme disease. The clonal evolution of the European population of B. bavariensis makes it an outstanding model for studies of pathogenicity and vector adaptation in Borrelia.




Acknowledgements The authors are grateful to Cecilia Hizo-Teufel and Sylvia Stockmeier for excellent technical assistance. The authors acknowledge the Bavarian Ministry for Health and Care (project nos. 14-42 and 12-45) and the Robert-Koch-Institute (project no. 07-36) for financial support. VF and GM are members of ESCMID STUDY GROUP FOR BORRELIA (ESGBOR).

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.ttbdis.2015.02.008.

References Barbour, A.G., Travinsky, B., 2010. Evolution and distribution of the ospC Gene, a transferable serotype determinant of Borrelia burgdorferi. MBio, 1. Benson, D.A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J., Sayers, E.W., 2013. GenBank. Nucleic Acids Res. 41, D36–D42, http://dx.doi.org/10.1093/nar/gks1195. Blankenberg, D., Von Kuster, G., Coraor, N., Ananda, G., Lazarus, R., Mangan, M., Nekrutenko, A., Taylor, J., 2010. Galaxy: a web-based genome analysis tool for experimentalists. Curr. Protoc. Mol. Biol., 10–19. Brenner, E.V., Kurilshikov, A.M., Stronin, O.V., Fomenko, N.V., 2012. Whole-genome sequencing of Borrelia garinii BgVir, isolated from Taiga ticks (Ixodes persulcatus). J. Bacteriol. 194, 5713, http://dx.doi.org/10.1128/JB.01360-12. Didelot, X., Falush, D., 2007. Inference of bacterial microevolution using multilocus sequence data. Genetics 175 (3), 1251–1266. Drummond, A.J., Rambaut, A., 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214, http://dx.doi.org/10.1186/1471-2148-7-214. Dubska, L., Literak, I., Kocianova, E., Taragelova, V., Sychra, O., 2009. Differential role of passerine birds in distribution of Borrelia spirochetes, based on data from ticks collected from birds during the postbreeding migration period in Central Europe. Appl. Environ. Microbiol. 75, 596–602. Fingerle, V., Schulte-Spechtel, U.C., Ruzic-Sabljic, E., Leonhard, S., Hofmann, H., Weber, K., Pfister, K., Strle, F., Wilske, B., 2008. Epidemiological aspects and molecular characterization of Borrelia burgdorferi s.l. from southern Germany with special respect to the new species Borrelia spielmanii sp. nov. Int. J. Med. Microbiol. 298, 279–290. Fu, Y.X., Li, W.H., 1993. Statistical tests of neutrality of mutations. Genetics 133, 693–709. Geller, J., Nazarova, L., Katargina, O., Golovljova, I., 2013. Borrelia burgdorferi sensu lato prevalence in tick populations in Estonia. Parasit. Vectors 6, 202, http://dx.doi.org/10.1186/1756-3305-6-202. Giardine, B., Riemer, C., Hardison, R.C., Burhans, R., Elnitski, L., Shah, P., Zhang, Y., Blankenberg, D., Albert, I., Taylor, J., Miller, W.C., Kent, W.J., Nekrutenko, A., 2005. Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 15, 1451–1455. Glöckner, G., Lehmann, R., Romualdi, A., Pradella, S., Schulte-Spechtel, U., Schilhabel, M., Wilske, B., Sühnel, J., Platzer, M., 2004. Comparative analysis of the Borrelia garinii genome. Nucleic Acids Res. 32, 6038–6046, http://dx.doi.org/10.1093/nar/gkh953. Goecks, J., Nekrutenko, A., Taylor, J., Team, T.G., 2010. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11, R86. Hanincova, K., Mukherjee, P., Ogden, N.H., Margos, G., Wormser, G.P., Reed, K.D., Meece, J.K., Vandermause, M.F., Schwartz, I., 2013. Multilocus sequence typing of Borrelia burgdorferi suggests existence of lineages with differential pathogenic properties in humans. PLOS ONE 8, e73066, http://dx.doi.org/10.1371/journal.pone.0073066. Hanincova, K., Taragelova, V., Koci, J., Schafer, S.M., Hails, R., Ullmann, A.J., Piesman, J., Labuda, M., Kurtenbach, K., 2003. Association of Borrelia garinii and B. valaisiana with songbirds in Slovakia. Appl. Environ. Microbiol. 69, 2825–2830. Hu, C.M., Wilske, B., Fingerle, V., Lobet, Y., Gern, L., 2001. Transmission of Borrelia garinii OspA serotype 4 to BALB/c mice by Ixodes ricinus ticks collected in the field. J. Clin. Microbiol. 39, 1169–1171. Hudson, R.R., Kaplan, N.L., 1985. Statistical properties of the number of recombination events in the history of a sample of DNA sequences. Genetics 111, 147–164. Huson, D.H., Bryant, D., 2006. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23 (2), 254–267. Huegli, D., Hu, C.M., Humair, P.F., Wilske, B., Gern, L., 2002. Apodemus species mice are reservoir hosts of Borrelia garinii OspA serotype 4 in Switzerland. J. Clin. Microbiol. 40, 4735–4737. Innan, H., Terauchi, R., Kahl, G., Tajima, F., 1999. A method for estimating nucleotide diversity from AFLP data. Genetics 151, 1157–1164. Jiang, B., Yao, H., Tong, Y., Yang, X., Huang, Y., Jiang, J., Cao, W., 2012. Genome sequence of Borrelia garinii strain NMJW1, isolated from China. J. Bacteriol. 194, 6660–6661, http://dx.doi.org/10.1128/JB.01844-12.

7

Korenberg, E.I., Gorelova, N.B., Kovalevskii, Y.V., 2002. Ecology of Borrelia burgdorferi sensu lato in Russia. In: Gray, J., Kahl, O., Lane, R.S., Stanek, G. (Eds.), Lyme Borreliosis: Biology, Epidemiology and Control. CABI Publishing, Wallingford. Kurtenbach, K., Hanincová, K., Tsao, J.I., Margos, G., Fish, D., Ogden, N.H., 2006. Fundamental processes in the evolutionary ecology of Lyme borreliosis. Nat. Rev. Microbiol. 4, 660–669. Lassmann, T., Sonnhammer, E.L.L., 2005. Kalign – an accurate and fast multiple sequence alignment algorithm. BMC Bioinformatics 6, 298, http://dx.doi.org/10.1186/1471-2105-6-298. Laursen, B.S., Sørensen, H.P., Mortensen, K.K., Sperling-Petersen, H.U., 2005. Initiation of protein synthesis in bacteria. Microbiol. Mol. Biol. Rev. 69, 101–123, http://dx.doi.org/10.1128/MMBR.69.1.101-123.2005. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., 2009. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079, http://dx.doi.org/10.1093/bioinformatics/btp352. Li, R., Zhu, H., Ruan, J., Qian, W., Fang, X., Shi, Z., Li, Y., Li, S., Shan, G., Kristiansen, K., Li, S., Yang, H., Wang, J., Wang, J., 2010. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res. 20, 265–272, http://dx.doi.org/10.1101/gr.097261.109. Lutz, M., 2009. Learning Python, 4th ed. O’Reilly Media. Marconi, R.T., Hohenberger, S., Jauris-Heipke, S., Schulte-Spechtel, U., LaVoie, C.P., Rossler, D., Wilske, B., 1999. Genetic analysis of Borrelia garinii OspA serotype 4 strains associated with neuroborreliosis: evidence for extensive genetic homogeneity. J. Clin. Microbiol. 37 (12), 3965–3970. Margos, G., Castillo-Ramírez, S., Hoen, A.G., 2012. Phylogeography of Lyme borreliosis-group spirochetes and methicillin-resistant Staphylococcus aureus. Parasitology 139, 1952–1965, http://dx.doi.org/10.1017/S0031182012000741. Margos, G., Vollmer, S.A., Cornet, M., Garnier, M., Fingerle, V., Wilske, B., Bormane, A., Vitorino, L., Collares-Pereira, M., Drancourt, M., Kurtenbach, K., 2009. A new Borrelia species defined by multilocus sequence analysis of housekeeping genes. Appl. Environ. Microbiol. 75, 5410–5416. Margos, G., Wilske, B., Sing, A., Hizo-Teufel, C., Cao, W.-C., Chu, C., Scholz, H., Straubinger, R.K., Fingerle, V., 2013. Borrelia bavariensis sp. nov. is widely distributed in Europe and Asia. Int. J. Syst. Evol. Microbiol. 63, 4284–4288. Masuzawa, T., Kharitonenkov, I.G., Kadosaka, T., Hashimoto, N., Kudeken, M., Takada, N., Kaneda, K., Imai, Y., 2005. Characterization of Borrelia burgdorferi sensu lato isolated in Moscow province-a sympatric region for Ixodes ricinus and Ixodes persulcatus. Int. J. Med. Microbiol. 294, 455–464. Miyamoto, K., Masuzawa, T., 2002. Ecology of Borrelia burgdorferi sensu lato in Japan and East Asia. In: Gray, J., Kahl, O., Lane, R.S., Stanek, G. (Eds.), Lyme Borreliosis: Biology, Epidemiology and Control. CABI Publishing, Wallingford, pp. 201–222. Mongodin, E.F., Casjens, S.R., Bruno, J.F., Xu, Y., Drabek, E.F., Riley, D.R., Cantarel, B.L., Pagan, P.E., Hernandez, Y.A., Vargas, L.C., Dunn, J.J., Schutzer, S.E., Fraser, C.M., Qiu, W.-G., Luft, B.J., 2013. Inter- and intra-specific pan-genomes of Borrelia burgdorferi sensu lato: genome stability and adaptive radiation. BMC Genomics 14, 693, http://dx.doi.org/10.1186/1471-2164-14-693. Mukhacheva, T.A., Kovalev, S.Y., 2013. Multilocus sequence analysis of Borrelia burgdorferi s.l. in Russia. Ticks Tick Borne Dis. 4, 275–279. Nei, M., 1987. Molecular Evolutionnary Genetics. Columbia Univ. Press, New York. Ojaimi, C., Brooks, C., Akins, D., Casjens, S., Rosa, P., Elias, A., Barbour, A., Jasinskas, A., Benach, J., Katonah, L., Radolf, J., Caimano, M., Skare, J., Swingle, K., Sims, S., Schwartz, I., 2002. Borrelia burgdorferi gene expression profiling with membrane-based arrays. Methods Enzymol. 358, 165–177. Pal, U., Li, X., Wang, T., Montgomery, R.R., Ramamoorthi, N., Desilva, A.M., Bao, F., Yang, X., Pypaert, M., Pradhan, D., Kantor, F.S., Telford, S., Anderson, J.F., Fikrig, E., 2004. TROSPA, an Ixodes scapularis receptor for Borrelia burgdorferi. Cell 119, 457–468, http://dx.doi.org/10.1016/j.cell.2004.10.027. Paradis, E., 2010. pegas: an R package for population genetics with an integrated-modular approach. Bioinformatics 26, 419–420, http://dx.doi.org/ 10.1093/bioinformatics/btp696. Paradis, E., Claude, J., Strimmer, K., 2004. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290. ´ ´ E., Strle, F., 2004. Comparison of growth of Borrelia afzelii, B. garinii, and Ruzic-Sablji c, B. burgdorferi sensu stricto in MKP and BSK-II medium. Int. J. Med. Microbiol. 294, 407–412, http://dx.doi.org/10.1016/j.ijmm.2004.08.002. Scholz, H.C., Margos, G., Derschum, H., Speck, S., Tserennorov, D., Erdenebat, N., Undraa, B., Enkhtuja, M., Battsetseg, J., Otgonchimeg, C., Otgonsuren, G., Nymadulam, B., Romer, A., Thomas, A., Essbauer, S., Wolfel, R., Kiefer, D., Zoller, L., Otgonbaatar, D., Fingerle, V., 2013. High prevalence of genetically diverse Borrelia bavariensis-like strains in Ixodes persulcatus from Selenge Aimag, Mongolia. Ticks Tick Borne Dis. 4, 89–92, http://dx.doi.org/10.1016/j.ttbdis.2012.08.004. Schwan, T.G., Piesman, J., 2000. Temporal changes in outer surface proteins A and C of the Lyme disease-associated spirochete. Borrelia burgdorferi, during the chain of infection in ticks and mice. J. Clin. Microbiol. 38, 382–388. Seinost, G., Dykhuizen, D.E., Dattwyler, R.J., Golde, W.T., Dunn, J.J., Wang, I.N., Wormser, G.P., Schriefer, M.E., Luft, B.J., 1999. Four clones of Borrelia burgdorferi sensu stricto cause invasive infection in humans. Infect. Immun. 67, 3518–3524. Skuballa, J., Oehme, R., Hartelt, K., Petney, T., Bucher, T., Kimmig, P., Taraschewski, H., 2007. European hedgehogs as hosts for Borrelia spp., Germany. Emerg. Infect. Dis. 13, 952–953. Stanek, G., Fingerle, V., Hunfeld, K.-P., Jaulhac, B., Kaiser, R., Krause, A., Kristoferitsch, W., O’Connell, S., Ornstein, K., Strle, F., Gray, J., 2011. Lyme borreliosis: clinical case definitions for diagnosis and management in Europe. Clin. Microbiol. Infect. 17, 69–79, http://dx.doi.org/10.1111/j.1469-0691.2010.03175.x.




Stanek, G., Strle, F., 2009. Lyme borreliosis: a European perspective on diagnosis and clinical management. Curr. Opin. Infect. Dis. 22, 450–454, http://dx.doi.org/10.1097/QCO.0b013e32832ee880. Tajima, F., 1989. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595. Takano, A., Nakao, M., Masuzawa, T., Takada, N., Yano, Y., Ishiguro, F., Fujita, H., Ito, T., Ma, X., Oikawa, Y., Kawamori, F., Kumagai, K., Mikami, T., Hanaoka, N., Ando, S., Honda, N., Taylor, K., Tsubota, T., Konnai, S., Watanabe, H., Ohnishi, M., Kawabata, H., 2011. Multilocus sequence typing implicates rodents as the main reservoir host of human-pathogenic Borrelia garinii in Japan. J. Clin. Microbiol. 49, 2035–2039. Taragel’ova, V., Koci, J., Hanincova, K., Kurtenbach, K., Derdakova, M., Ogden, N.H., Literak, I., Kocianova, E., Labuda, M., 2008. Blackbirds and song thrushes constitute a key reservoir of Borrelia garinii, the causative agent of borreliosis in Central Europe. Appl. Environ. Microbiol. 74, 1289–1293. Wang, I.N., Dykhuizen, D.E., Qiu, W., Dunn, J.J., Bosler, E.M., Luft, B.J., 1999. Genetic diversity of ospC in a local population of Borrelia burgdorferi sensu stricto. Genetics 151, 15–30.

Wilske, B., Busch, U., Eiffert, H., Fingerle, V., Pfister, H.W., Rossler, D., Preac-Mursic, V., 1996. Diversity of OspA and OspC among cerebrospinal fluid isolates of Borrelia burgdorferi sensu lato from patients with neuroborreliosis in Germany. Med. Microbiol. Immunol. 184, 195–201. Wormser, G.P., Brisson, D., Liveris, D., Hanincová, K., Sandigursky, S., Nowakowski, J., Nadelman, R.B., Ludin, S., Schwartz, I., 2008. Borrelia burgdorferi genotype predicts the capacity for hematogenous dissemination during early Lyme disease. J. Infect. Dis. 198, 1358–1364, http://dx.doi.org/10.1086/592279. Xu, H., He, M., Pang, X., Xu, Z.C., Piesman, J., Yang, X.F., 2010. Characterization of the highly regulated antigen BBA05 in the enzootic cycle of Borrelia burgdorferi. Infect. Immun. 78, 100–107, http://dx.doi.org/10.1128/IAI.01008-09. Yang, Z., 2007. PAML 4, phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591, http://dx.doi.org/10.1093/molbev/msm088. Zerbino, D.R., Birney, E., 2008. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821–829, http://dx.doi.org/10.1101/gr.074492.107.


Lyme borreliosis: relation of its causative agent to its vectors and hosts in North America and Europe.

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Evolution and population genomics of the Lyme borreliosis pathogen, Borrelia burgdorferi.

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