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A novel locus on mouse chromosome 7 that influences survival after infection with tick-borne encephalitis virus

BMC Neuroscience volume 19, Article number: 39 (2018) Cite this article

Abstract

Background

Tick-borne encephalitis (TBE) is the main tick-borne viral infection in Eurasia. Its manifestations range from inapparent infections and fevers with complete recovery to debilitating or fatal encephalitis. The basis of this heterogeneity is largely unknown, but part of this variation is likely due to host genetic. We have previously found that BALB/c mice exhibit intermediate susceptibility to the infection of TBE virus (TBEV), STS mice are highly resistant, whereas the recombinant congenic strain CcS-11, carrying 12.5% of the STS genome on the background of the BALB/c genome is even more susceptible than BALB/c. Importantly, mouse orthologs of human TBE controlling genes Oas1b, Cd209, Tlr3, Ccr5, Ifnl3 and Il10, are in CcS-11 localized on segments derived from the strain BALB/c, so they are identical in BALB/c and CcS-11. As they cannot be responsible for the phenotypic difference of the two strains, we searched for the responsible STS-derived gene-locus. Of course the STS-derived genes in CcS-11 may operate through regulating or epigenetically modifying these non-polymorphic genes of BALB/c origin.

Methods

To determine the location of the STS genes responsible for susceptibility of CcS-11, we analyzed survival of TBEV-infected F2 hybrids between BALB/c and CcS-11. CcS-11 carries STS-derived segments on eight chromosomes. These were genotyped in the F2 hybrid mice and their linkage with survival was tested by binary trait interval mapping. We have sequenced genomes of BALB/c and STS using next generation sequencing and performed bioinformatics analysis of the chromosomal segment exhibiting linkage with TBEV survival.

Results

Linkage analysis revealed a novel suggestive survival-controlling locus on chromosome 7 linked to marker D7Nds5 (44.2 Mb). Analysis of this locus for polymorphisms between BALB/c and STS that change RNA stability and genes’ functions led to detection of 9 potential candidate genes: Cd33, Klk1b22, Siglece, Klk1b16, Fut2, Grwd1, Abcc6, Otog, and Mkrn3. One of them, Cd33, carried a nonsense mutation in the STS strain.

Conclusions

The robust genetic system of recombinant congenic strains of mice enabled detection of a novel suggestive locus on chromosome 7. This locus contains 9 candidate genes, which will be focus of future studies not only in mice but also in humans.

Background

Tick-borne encephalitis (TBE) is the main tick-borne viral infection in Eurasia. It is prevalent across the entire continent from Japan to France [1]. The disease is caused by tick-borne encephalitis virus (TBEV), a flavivirus of the family Flaviviridae, which besides TBEV includes West Nile virus (WNV), dengue virus (DENV), Zika virus (ZIKV), yellow fever virus (YFV), Japanese encephalitis virus (JEV), and several other viruses causing extensive morbidity and mortality in humans. Ticks act as both the vector and reservoir for TBEV. The main hosts are small rodents, with humans being accidental hosts. In Europe and Russia between 5000 and 13,000 clinical cases of TBE are reported annually, with a large annual fluctuation [2]. The highest incidence of TBE is reported in western Siberia, in the Czech Republic, Estonia, Slovenia and Lithuania, but the prevalence of the disease is believed to be higher than actually reported [1, 2]. TBEV may produce a variety of clinical symptoms, from an asymptomatic disease to a fever and acute or chronic progressive encephalitis. The outcome of infection depends on the strain of virus [1], as well as on the genotype [3], sex and age of the host [4], and on the environmental and social factors [1]. Environmental and social factors influence also risk of infection.

Genetic influence on susceptibility to TBEV-induced disease has been analyzed by two main strategies: a hypothesis-independent phenotype-driven approach and a hypothesis-driven approach. Application of a genome-wide search (hypothesis-independent approach) in mouse led to identification of the gene Oas1 (2′-5′-oligoadenylate synthetase gene) [5, 6]. A stop codon in exon 4 of the gene Oas1b (a natural knockout) present in majority of mouse laboratory strains causes production of protein lacking 30% of the C terminal sequence [5]. This part of molecule seems to be critical for tetramerization required for OAS1B activity leading to degradation of viral RNA. Thus, this mutation makes majority of mouse laboratory strains susceptible to flaviviruses [6, 7]. Human ortholog to this gene (OAS1) also modifies susceptibility to other flaviviruses (WNV) [8, 9], whereas OAS2 and OAS3 localized in the same cluster on chromosome 12q24.2 influence response to TBEV [3]. The polymorphic sites associated in OAS2 and OAS3 with susceptibility to TBEV did not resulted in amino acid changes, thus mechanisms of susceptibility control is not known [3]. The hypothesis-driven approach has focused on genes that encode molecules indicated to be involved in antiviral response by mechanistic studies [9]. These candidate genes studies revealed that polymorphisms in CD209/DC-SIGN [10], CCR5 [11, 12], TLR3 [12, 13], IL10 [14] and IFNL3/IL28B [14] influence susceptibility to TBEV in humans.

Our previous study has shown that both after subcutaneous and intracerebral inoculation of European prototypic TBEV, BALB/c mice exhibited intermediate susceptibility to the infection, STS mice were highly resistant, whereas the strain CcS-11, which carries 12.5% of the STS genome on the background of the genome of the strain BALB/c [15], is even more susceptible than its two parents—BALB/c and STS [16]. Importantly, mouse orthologs of human TBEV controlling genes: Oas1b, Cd209, Tlr3, Ccr5, Il10 and Ifnl3 are in CcS-11 localized on segments derived from the strain BALB/c (Fig. 1), so they are identical in both BALB/c and CcS-11 and hence cannot be responsible for the phenotypic difference of the two strains. Therefore, the difference must be due to a presently unknown locus, which could be detected by a linkage study of a cross between BALB/c and CcS-11. Thus, we have generated a F2 intercross between BALB/c and CcS-11 and performed a linkage and bioinformatics analysis. These studies revealed a novel suggestive locus on mouse chromosome 7 containing 9 potential candidate genes.

Fig. 1
figure1

Genetic composition of the strain CcS-11. The regions of STS and BALB/c origin are represented as dark and white, respectively, the boundary regions of undetermined origin are shaded. Only the markers or SNPs defining the boundaries of STS-derived segment and markers that were tested for linkage (underlined) are shown. Genes Oas1b, Cd209, Tlr3, Ccr5, Ifnl3 and Il10, known to control susceptibility to TBEV are shown in green, potential candidate genes Cd33, Klk1b22, Siglece, Klk1b16, Fut2, Grwd1, Abcc6, Otog, and Mkrn3 detected in current study are shown in red

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Methods

Mice

417 female F2 offspring of an intercross between strains CcS-11 and BALB/c (mean and median age 9.5 and 9 weeks, respectively, at the time of infection) were produced at the Institute of Molecular Genetics AS CR. Mice were tested in three successive experimental groups at the Institute of Parasitology, AS CR. When used for these experiments, strain CcS-11 had undergone more than 90 generations of inbreeding. Experiments Nr. 1, 2, and 3 comprised 120, 121 and 176 F2 mice, respectively. Sterilized pellet diet and water were supplied ad libitum. The mice were housed in plastic cages with wood-chip bedding, situated in a specific pathogen-free room with a constant temperature of 22 °C and a relative humidity of 65%.

Virus infection and disease phenotype

Experiments were performed with European prototypic TBEV strain Neudoerfl (a generous gift from Professor F. X. Heinz, Medical University of Vienna). This strain was passaged five times in brains of suckling mice before the use in this study [16]. Mice were infected subcutaneously with 104 pfu of the virus.

Mice were scored for mortality for a period of 35 days post-infection (p.i.) with TBEV, as well as presence of ruffled fur and paresis in three independent successive experiments at the Institute of Parasitology AS CR.

Genotyping of F2 mice

DNA was isolated from tails using a standard proteinase procedure. The strain CcS-11 differs from BALB/c at STS-derived regions on eight chromosomes [17]. These differential regions were genotyped in the F2 hybrid mice between CcS-11 and BALB/c using 16 microsatellite markers (Generi Biotech, Hradec Králové, Czech Republic): D1Mit403, D3Mit45, D7Mit25, D7Nds5, D7Mit18, D7Nds1, D7Mit282, D7Mit259, D8Mit85, D10 Mit12, D10Mit46, D12Mit37, D16Mit73, D19Mit51, D19Mit60, D19Mit46 (Fig. 1) as described in [17].

Statistical analysis

Survival, ruffled fur and paresis were treated as binary phenotypes (death/survival; presence/absence of symptom), and binary trait interval mapping was performed [18, 19]. A permutation test [20] was used to assess significance. This takes account of the limited genetic difference between the strains BALB/c and CcS-11. On the basis of 10,000 permutation replicates, the 5% significance LOD threshold was 2.56; the 10% threshold was 2.23. The Pearson correlation coefficient between presence of death and paresis was computed by the program Statistica for Windows 12.0 (StatSoft, Inc., Tulsa, OK).

Detection of polymorphisms that change RNA stability and genes’ functions

We have sequenced the genomes of strains BALB/c and STS using next generation sequencing (NGS) system HiSeq 2500 (Illumina) (12× coverage). NGS data was preprocessed using software Trimmomatic [21] and overlapped paired reads were joined by software Flash [22]. Alignment—reference mouse sequence mm10 (build GRCm38)—was performed using BWA (Burrows-Wheeler Aligner) [23] program. Mapped reads were sorted and indexed, duplicated reads were marked. Segment covering peak of linkage on chromosome 7 from 36.2 to 74.5 Mb was inspected for polymorphisms between BALB/c and STS that change RNA stability and genes’ functions. Local realignment around indels, base recalibration and variants filtration were performed using software GATK (The Genome Analysis Toolkit) [24]. Variant annotation and effect prediction was performed by software SnpEff [25]. IGV (Integrated Genome Viewer) was used for visualization of results [26].

Results

Binary trait linkage analysis revealed a suggestive locus on chromosome 7 near D7Nds5 affecting the binary trait (death/survival) (LOD = 2.15), with a corresponding genome-scan-adjusted P value = 0.12 (Fig. 2a). The 1-LOD support interval spans from D7Mit25 to D7Nds1. The STS allele both in homozygotes and heterozygotes was associated with a higher death rate in each of the three separate experimental groups (Fig. 2b), and in the pooled data (Fig. 3a), so its presence in CcS-11 enhances even more the overall susceptibility determined by the BALB/c background. Ruffled fur was observed in only 8% of mice, so it was not suitable for statistical analysis. Paresis was less frequent than mortality (n = 60 vs. 102) and not all paretic mice died, but the two phenotypes were positively correlated (Pearson correlation 0.53). Moreover, frequency of paresis in the three D7Nds5 genotypes (Fig. 3b), although not significantly different, was biologically compatible with the survival data, because D7Nds5 CC homozygotes had the highest survival rate, and the lowest percentage of paresis.

Fig. 2
figure2

Genetic influence on susceptibility to TBEV in an F2 intercross between BALB/c and CcS-11. a LOD curves from binary trait interval mapping for death/survival. A dashed horizontal line is plotted at the 5% significance threshold, adjusting for the genome scan. b A plot of the death rate as a function of genotype at marker D7Nds5 and experiment, with 95% confidence intervals. C and S indicate the presence of BALB/c and STS allele, respectively. The S allele is associated with a higher death rate. The numbers of mice in the experiments 1, 2, and 3 were 120, 121 and 176, respectively

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Fig. 3
figure3

Differential survival (a) and incidence of paresis (b) of and in F2 hybrid mice carrying CC, CS and SS genotype at the marker D7Nds5 (n.s) after TBEV infection. Mice were infected subcutaneously with 104 pfu of the TBEV strain Neudoerfl and observed for lethality for 35 days

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We have sequenced genomes of BALB/c and STS and analyzed the segment covering peak of linkage on chromosome 7 from 36.2 to 74.5 Mb for polymorphisms between BALB/c and STS that change RNA stability and genes’ functions. This revealed 9 potential candidate genes: Cd33 (CD33 antigen), Klk1b22 (kallikrein 1-related peptidase b22), Siglece (sialic acid binding Ig-like lectin E), Klk1b16 (kallikrein 1-related peptidase b16), Fut2 (fucosyltransferase 2), Grwd1 (glutamate-rich WD repeat containing 1), Abcc6 (ATP-binding cassette, sub-family C (CFTR/MRP), member 6), Otog (otogelin), and Mkrn3 (makorin, ring finger protein, 3) (Table 1, Fig. 1).

Table 1 List of candidate genes in TBEV susceptibility locus
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One of these genes, Cd33, carried in the strain STS a nonsense mutation. Other changes in the strain STS in comparison with BALB/c (and the reference strain C57BL/6) represented single amino acids change in Siglec E, KLK1B22, KLK1B16, FUT2 and OTOG. The BALB/c strain had in comparison with STS (and the reference strain C57BL/6) deletion of two amino acids in GRWD1, insertion of four amino acids in MKRN3 and single amino acid change in and ABCC6 (Table 1).

Discussion

CD33 and Siglec E belong to family of CD33-related sialic-acid-binding immunoglobulin-like lectins (CD33rSiglecs). They are ITIM-containing inhibitory receptors, which are involved in regulation of inflammatory and immune responses [27]. Gene Cd33 carried in the strain STS a nonsense mutation (Table 1). Product of this gene is in mouse expressed on myeloid precursors and cells of myeloid origin [28] and on microglial cells [29]. It can inhibit response to amyloid plaques and its deletion leads to protection in the mouse model of Alzheimer disease (AD) [29] and in humans some CD33 genetic variants are associated with late-onset AD [30]; its potential role in pathology of TBEV might be associated with its regulatory role in inflammatory responses. Gene Siglece carried in the strain STS a single amino acid change. Siglec E is expressed on microglia and inhibits neurotoxicity triggered by neural debris [31], which might have protective role against damage induced by flaviviruses.

A single amino acid change was present in KLK1B22 and KLK1B16. Kallikreins are serine proteases that might both help to fight infection by activating complement system [32], as well as aggravate disease symptoms by releasing bradykinin, which causes alterations in vascular permeability [33]. Their role in defense against flaviviruses has not been described. Kallikrein-bradykinin system have been described to contribute to protection against Leishmania [34] and Trypanosoma cruzi [35] parasites in mice. Interestingly, on the mouse chromosome 7 were in the strain CcS-11 mapped loci Lmr21 and Tbbr3 that control susceptibility to L. major [36] and T. b. brucei [17], respectively. However, both loci are mapped on a long chromosomal segment, thus other gene(s) might be responsible for their effect.

FUT2 have been described to influence control of a wide range of pathogens such as noroviruses [37], rotaviruses [38], HIV [39], and Escherichia coli [40] in humans, and to Helicobacter pylori in mouse [41], but its role in resistance to flaviviruses is not known.

Makorin 1 induces degradation of WNV capsid which might protect host cells [42]. The E3 ligase domain responsible for MKRN1 effect is present also in MKRN3 [43]. Thus, gene Mkrn3 might have relationship to defense against flaviviruses. Similarly, possible role of Otog, Grwd1 and Abcc6 in resistance to TBEV remains to be elucidated.

Public database BioGPS shows that all the candidate genes are in uninfected mice expressed in tissues such as brain, spleen and liver (Table 2). Brain is the main target for the virus; however, during the extraneural phase of the infection, several tissues and organs in the body are infected, including spleen and liver [44]. Highest expression in these tissues exhibits Cd33 and Siglece with expression in microglia ten times higher than median value (> 10M), Cd33 and Klk1b22 are highly expressed in spleen (> 3M), > 10M expression of these two genes is also observed in bone marrow; Siglece is also highly expressed in bone (> 3M) and bone marrow macrophages (> 3M), whereas Cd33 is highly expressed in granulocytes (> 30M), plasmacytoid dendritic cells (> 30M), osteoclasts (> 30M), myeloid dendritic cells (> 10M), in spleen (> 3M), lymph nodes (> 3M), eyecup (> 3M), B cells in marginal zone (> 3M) and in FoxP+ T cells (> 3M). For both Klk1b22 and Klk1b16 is characteristic very high expression in salivary gland (> 1000M) and high expression in lacrimal gland (> 30M). Klk1b22 is also highly expressed in large intestine (> 30M), kidney (> 30M), pancreas (> 30M), testis (> 30M), stomach (> 10M), plasmacytoid dendritic cells (> 10M), small intestine (> 3M), spleen (> 3M) and CD8 + T cells (> 3M), whereas Klk1b16 is also highly expressed in pituitary (> 30M), kidney (> 3M), pancreas (> 3M) and testis (> 30M). Highest expression of Fut2 was observed in uterus (> 30M), and in stomach (> 10M), it was also highly expressed in large intestine (> 3M), prostate (> 3M) and in testis (> 3M). GRWD1 was described to play a role in ribosome biogenesis and during myeloid differentiation [45]. High expression level in hematopoietic stem cells (> 10M), mega erythrocyte progenitors (> 10M), granulocytes (> 10M), common myeloid progenitor (> 3M) supports this finding, but it is also expressed in several T cell subpopulations (> 3M), B cells in marginal zone (> 3M), as well as in lacrimal gland. Abcc6 is highly expressed in liver (≫ 30M) and in lens (> 10M) and Mrkn3 is highly expressed in retina (10M) and in olfactory bulb (> 3M). The expression data further support a potential role of detected candidate genes in defense against TBEV, but they must be in the future complemented with data describing gene expression after TBEV infection.

Table 2 Expression of potential candidate genes in organs and cells of uninfected mice
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We have found a susceptibility allele of a locus on chromosome 7 in the resistant strain STS. This apparent paradox is likely caused by the fact that most inbred mouse strains were produced without an intentional selective breeding for a specific quantitative phenotype (like susceptibility to specific infections). Therefore they inherited randomly from their non-inbred ancestors susceptible alleles at some loci and resistant alleles at others, so that their overall susceptibility phenotype depends on the relative number of both types of alleles. Such finding is not unique, as susceptibility alleles originating from resistant strains were found in susceptibility studies of other infectious diseases [17, 46, 47] and colon cancer [48]. Similarly, in different in vitro tests of immune responses a low-responder allele was identified in a high responding strain [49] or vice versa [50]. Another explanation might be presence of BALB/c allele interacting with STS allele on chromosome 7. Demonstration of such interaction would require further experiments. We have already observed interaction of STS and BALB/c alleles leading to extreme phenotypes in susceptibility to L. major [51] and L. tropica [47].

Conclusion

Mapping of TBEV controlling genes in mice is not easy due to presence of a strong TBEV controlling gene Oas1b, which is identical both in BALB/c and CcS-11, as well as in majority of laboratory mouse strains [6, 7] and masks effects of other controlling genes. Therefore using a powerful genetic system—recombinant congenic strains, we succeeded in mapping novel TBEV susceptibility locus on chromosome 7 and identified 9 potential candidate genes. Products of some of these genes have been described to participate in defense against flaviviruses, the role of the others is unknown. The genes detected here will be focus of future studies that will include characterization of candidate gene(s) products in BALB/c and CcS-11, introducing modification to candidate genes and study their influence on disease outcome in mouse, and study influence of polymorphisms in human orthologs of candidate genes on susceptibility to TBEV in humans.

List of abbreviations

Abcc6 (ATP-binding cassette, sub-family C (CFTR/MRP), member 6), mouse gene; ABCC6-human gene; ABCC6-protein (gene product); Ccr5: chemokine (C–C motif) receptor 5; Cd209: CD209 antigen; Cd33 (CD33 antigen); Fut2 (fucosyltransferase 2); Grwd1 (glutamate-rich WD repeat containing 1); Ifnl3: interferon lambda 3 (synonym Il28b); Il10: interleukin 10; Klk1b16 (kallikrein 1-related peptidase b16); Klk1b22 (kallikrein 1-related peptidase b22); Mkrn3 (makorin, ring finger protein, 3); Oas1b: 2′-5′-oligoadenylate synthetase gene; Otog (otogelin); pfu: Plaque-forming unit; RC: Recombinant congenic; s.c: Subcutaneous; Siglece (sialic acid binding Ig-like lectin E); TBE: Tick-borne encephalitis; TBEV: Tick-borne encephalitis virus; Tlr3: toll-like receptor 3.

According to current gene and protein nomenclature, mouse gene symbols are italicized, with only the first letter in upper-case (e.g. Cd33). Protein symbols are not italicized, and all letters are in upper-case (e.g. CD33). Human gene symbols are in upper-case and are italicized (e.g. CD33). Protein symbols are identical to their corresponding gene symbols except that they are not italicized (e.g. CD33).

References

  1. 1.

    Dobler G, Gniel D, Petermann R, Pfeffer M. Epidemiology and distribution of tick-borne encephalitis. Wien Med Wochenschr. 2012;162:230–8.

    Article  PubMed  Google Scholar 

  2. 2.

    Süss J. Tick-borne encephalitis 2010: epidemiology, risk areas, and virus strains in Europe and Asia—an overview. Ticks Tick Borne Dis. 2011;2:2–15.

    Article  PubMed  Google Scholar 

  3. 3.

    Barkhash AV, Perelygin AA, Babenko VN, Myasnikova NG, Pilipenko PI, Romaschenko AG, Voevoda MI, Brinton MA. Variability in the 2′-5′-oligoadenylate synthetase gene cluster is associated with human predisposition to tick-borne encephalitis virus-induced disease. J Infect Dis. 2010;202:1813–8.

    Article  PubMed  CAS  Google Scholar 

  4. 4.

    Rushton JO, Lecollinet S, Hubálek Z, Svobodová P, Lussy H, Nowotny N. Tick-borne encephalitis virus in horses, Austria. Emerg Infect Dis. 2011;19:635–7.

    Article  Google Scholar 

  5. 5.

    Perelygin AA, Scherbik SV, Zhulin IB, Stockman BM, Li Y, Brinton MA. Positional cloning of the murine flavivirus resistance gene. Proc Natl Acad Sci USA. 2002;99(14):9322–7.

    Article  PubMed  CAS  Google Scholar 

  6. 6.

    Mashimo T, Lucas M, Simon-Chazottes D, Frenkiel MP, Montagutelli X, Ceccaldi PE, Deubel V, Guenet JL, Despres P. A nonsense mutation in the gene encoding 2′-5′-oligoadenylate synthetase/L1 isoform is associated with West Nile virus susceptibility in laboratory mice. Proc Natl Acad Sci USA. 2002;99:11311–6.

    Article  PubMed  CAS  Google Scholar 

  7. 7.

    Darnell MB, Koprowski H, Lagerspetz K. Genetically determined resistance to infection with group B arboviruses. I. Distribution of the resistance gene among various mouse populations and characteristics of gene expression in vivo. J Infect Dis. 1974;129(3):240–7.

    Article  PubMed  CAS  Google Scholar 

  8. 8.

    Lim JK, Lisco A, McDermott DH, Huynh L, Ward JM, Johnson B, Johnson H, Pape J, Foster GA, Krysztof D, Follmann D, Stramer SL, Margolis LB, Murphy PM. Genetic variation in OAS1 is a risk factor for initial infection with West Nile virus in man. PLoS Pathog. 2009;5(2):e1000321.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. 9.

    Turtle L, Griffiths MJ, Solomon T. Encephalitis caused by flaviviruses. QJM. 2012;105:219–23.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. 10.

    Barkhash AV, Perelygin AA, Babenko VN, Brinton MA, Voevoda MI. Single nucleotide polymorphism in the promoter region of the CD209 gene is associated with human predisposition to severe forms of tick-borne encephalitis. Antivir Res. 2012;93:64–8.

    Article  PubMed  CAS  Google Scholar 

  11. 11.

    Kindberg E, Mickiene A, Ax C, Akerlind B, Vene S, Lindquist L, Lundkvist A, Svensson L. A deletion in the chemokine receptor 5 (CCR5) gene is associated with tickborne encephalitis. J Infect Dis. 2008;197:266–9.

    Article  PubMed  CAS  Google Scholar 

  12. 12.

    Barkhash AV, Voevoda MI, Romaschenko AG. Association of single nucleotide polymorphism rs3775291 in the coding region of the TLR3 gene with predisposition to tick-borne encephalitis in a Russian population. Antivir Res. 2013;99(2):136–8.

    Article  PubMed  CAS  Google Scholar 

  13. 13.

    Mickienė A, Pakalnienė J, Nordgren J, Carlsson B, Hagbom M, Svensson L, Lindquist L. Polymorphisms in chemokine receptor 5 and toll-like receptor 3 genes are risk factors for clinical tick-borne encephalitis in the Lithuanian population. PLoS ONE. 2014;9(9):e106798.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. 14.

    Barkhash AV, Babenko VN, Voevoda MI, Romaschenko AG. Association of IL28B and IL10 gene polymorphism with predisposition to tick-borne encephalitis in a Russian population. Ticks Tick Borne Dis. 2016;7(5):808–12.

    Article  PubMed  Google Scholar 

  15. 15.

    Démant P, Hart AA. Recombinant congenic strains–a new tool for analyzing genetic traits determined by more than one gene. Immunogenetics. 1986;24(6):416–22.

    Article  PubMed  Google Scholar 

  16. 16.

    Palus M, Vojtíšková J, Salát J, Kopecký J, Grubhoffer L, Lipoldová M, Demant P, Růžek D. Mice with different susceptibility to tick-borne encephalitis virus infection show selective neutralizing antibody response and inflammatory reaction in the central nervous system. J Neuroinflammation. 2013;10:77.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. 17.

    Šíma M, Havelková H, Quan L, Svobodová M, Jarošíková T, Vojtíšková J, Stassen AP, Demant P, Lipoldová M. Genetic control of resistance to Trypanosoma brucei brucei infection in mice. PLoS Negl Trop Dis. 2011;5:e1173.

    Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Xu S, Atchley WR. Mapping quantitative trait loci for complex binary diseases using line crosses. Genetics. 1996;143:1417–24.

    PubMed  PubMed Central  CAS  Google Scholar 

  19. 19.

    Broman KW. Mapping quantitative trait loci in the case of a spike in the phenotype distribution. Genetics. 2003;163(3):1169–75.

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Churchill GA, Doerge RW. Empirical threshold values for quantitative trait mapping. Genetics. 1994;138:963–71.

    PubMed  PubMed Central  CAS  Google Scholar 

  21. 21.

    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. 22.

    Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27(21):2957–63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. 23.

    Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics. 2010;26(5):589–95.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. 24.

    McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–303.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. 25.

    Cingolani P, Platts A, le Wang L, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012;6(2):80–92.

    Article  CAS  Google Scholar 

  26. 26.

    Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. 27.

    Macauley MS, Crocker PR, Paulson JC. Siglec-mediated regulation of immune cell function in disease. Nat Rev Immunol. 2014;14(10):653–66.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. 28.

    Brinkman-Van der Linden EC, Angata T, Reynolds SA, Powell LD, Hedrick SM, Varki A. CD33/Siglec-3 binding specificity, expression pattern, and consequences of gene deletion in mice. Mol Cell Biol. 2003;23(12):4199–206.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. 29.

    Griciuc A, Serrano-Pozo A, Parrado AR, Lesinski AN, Asselin CN, Mullin K, Hooli B, Choi SH, Hyman BT, Tanzi RE. Alzheimer’s disease risk gene CD33 inhibits microglial uptake of amyloid beta. Neuron. 2013;78(4):631–43.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. 30.

    Jiang T, Yu JT, Hu N, Tan MS, Zhu XC, Tan L. CD33 in Alzheimer’s disease. Mol Neurobiol. 2014;49(1):529–35.

    Article  PubMed  CAS  Google Scholar 

  31. 31.

    Claude J, Linnartz-Gerlach B, Kudin AP, Kunz WS, Neumann H. Microglial CD33-related Siglec-E inhibits neurotoxicity by preventing the phagocytosis-associated oxidative burst. J Neurosci. 2013;33(46):18270–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. 32.

    Kant Upadhyay R. Biomarkers in Japanese encephalitis: a review. Biomed Res Int. 2013;2013:591290.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. 33.

    Rust NM, Papa MP, Scovino AM, da Silva MM, Calzavara-Silva CE, Marques ET Jr, Peçanha LM, Scharfstein J, Arruda LB. Bradykinin enhances Sindbis virus infection in human brain microvascular endothelial cells. Virology. 2012;422(1):81–91.

    Article  PubMed  CAS  Google Scholar 

  34. 34.

    Nico D, Feijó DF, Maran N, Morrot A, Scharfstein J, Palatnik M, Palatnik-de-Sousa CB. Resistance to visceral leishmaniasis is severely compromised in mice deficient of bradykinin B2-receptors. Parasit Vectors. 2012;5:261.

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Monteiro AC, Schmitz V, Morrot A, de Arruda LB, Nagajyothi F, Granato A, Pesquero JB, Müller-Esterl W, Tanowitz HB, Scharfstein J. Bradykinin B2 Receptors of dendritic cells, acting as sensors of kinins proteolytically released by Trypanosoma cruzi, are critical for the development of protective type-1 responses. PLoS Pathog. 2007;3(11):e185.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. 36.

    Kurey I, Kobets T, Havelková H, Slapnicková M, Quan L, Trtková K, Grekov I, Svobodová M, Stassen AP, Hutson A, Demant P, Lipoldová M. Distinct genetic control of parasite elimination, dissemination, and disease after Leishmania major infection. Immunogenetics. 2009;61(9):619–33.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Lindesmith L, Moe C, Marionneau S, Ruvoen N, Jiang X, Lindblad L, Stewart P, LePendu J, Baric R. Human susceptibility and resistance to Norwalk virus infection. Nat Med. 2003;9(5):548–53.

    Article  PubMed  CAS  Google Scholar 

  38. 38.

    Payne DC, Currier RL, Staat MA, Sahni LC, Selvarangan R, Halasa NB, Englund JA, Weinberg GA, Boom JA, Szilagyi PG, Klein EJ, Chappell J, Harrison CJ, Davidson BS, Mijatovic-Rustempasic S, Moffatt MD, McNeal M, Wikswo M, Bowen MD, Morrow AL, Parashar UD. Epidemiologic association between FUT2 secretor status and severe rotavirus gastroenteritis in children in the United States. JAMA Pediatr. 2015;169(11):1040–5.

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Kindberg E, Hejdeman B, Bratt G, Wahren B, Lindblom B, Hinkula J, Svensson L. A nonsense mutation (428G → A) in the fucosyltransferase FUT2 gene affects the progression of HIV-1 infection. Aids. 2006;20(5):685–9.

    Article  PubMed  CAS  Google Scholar 

  40. 40.

    Mottram L, Wiklund G, Larson G, Qadri F, Svennerholm AM. FUT2 non-secretor status is associated with altered susceptibility to symptomatic enterotoxigenic Escherichia coli infection in Bangladeshis. Sci Rep. 2017;7(1):10649.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. 41.

    Magalhães A, Rossez Y, Robbe-Masselot C, Maes E, Gomes J, Shevtsova A, Bugaytsova J, Borén T, Reis CA. Muc5ac gastric mucin glycosylation is shaped by FUT2 activity and functionally impacts Helicobacter pylori binding. Sci Rep. 2016;6:25575.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. 42.

    Ko A, Lee EW, Yeh JY, Yang MR, Oh W, Moon JS, Song J. MKRN1 induces degradation of West Nile virus capsid protein by functioning as an E3 ligase. J Virol. 2010;84(1):426–36.

    Article  PubMed  CAS  Google Scholar 

  43. 43.

    http://www.informatics.jax.org/genes.shtml. Accessed 5 Sept 2017.

  44. 44.

    Hayasaka D, Aoki K, Morita K. Development of simple and rapid assay to detect viral RNA of tick-borne encephalitis virus by reverse transcription-loop-mediated isothermal amplification. Virol J. 2013;10:68.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. 45.

    Gratenstein K, Heggestad AD, Fortun J, Notterpek L, Pestov DG, Fletcher BS. The WD-repeat protein GRWD1: potential roles in myeloid differentiation and ribosome biogenesis. Genomics. 2005;85(6):762–73.

    Article  PubMed  CAS  Google Scholar 

  46. 46.

    Vladimirov V, Badalová J, Svobodová M, Havelková H, Hart AA, Blazková H, Demant P, Lipoldová M. Different genetic control of cutaneous and visceral disease after Leishmania major infection in mice. Infect Immun. 2003;71:2041–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. 47.

    Sohrabi Y, Havelková H, Kobets T, Šíma M, Volkova V, Grekov I, Jarošíková T, Kurey I, Vojtíšková J, Svobodová M, Demant P, Lipoldová M. Mapping the genes for susceptibility and response to Leishmania tropica in mouse. PLoS Negl Trop Dis. 2013;7(7):e2282.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. 48.

    van Wezel T, Stassen AP, Moen CJ, Hart AA, van der Valk MA, Demant P. Gene interaction and single gene effects in colon tumour susceptibility in mice. Nat Genet. 1996;14:468–70.

    Article  PubMed  Google Scholar 

  49. 49.

    Lipoldová M, Havelková H, Badalova J, Vojtísková J, Quan L, Krulova M, Sohrabi Y, Stassen AP, Demant P. Loci controlling lymphocyte production of interferon γ after alloantigen stimulation in vitro and their co-localization with genes controlling lymphocyte infiltration of tumors and tumor susceptibility. Cancer Immunol Immunother. 2010;59:203–13.

    Article  PubMed  CAS  Google Scholar 

  50. 50.

    Kosařová M, Havelková H, Krulová M, Demant P, Lipoldová M. The production of two Th2 cytokines, interleukin-4 and interleukin-10, is controlled independently by locus Cypr1 and by loci Cypr2 and Cypr3, respectively. Immunogenetics. 1999;49:134–41.

    Article  PubMed  Google Scholar 

  51. 51.

    Havelková H, Badalová J, Svobodová M, Vojtísková J, Kurey I, Vladimirov V, Demant P, Lipoldová M. Genetics of susceptibility to leishmaniasis in mice: four novel loci and functional heterogeneity of gene effects. Genes Immun. 2006;7(3):220–33.

    Article  PubMed  CAS  Google Scholar 

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Authors’ contributions

ML conceived and designed the research, analyzed the experiments, coordinated collaborations; and wrote the manuscript. MP, YS, MŠ, DR, VV, JV, LM, JS and MS performed the experiments and participated in the design of experiments and analysis of data. HS performed sequence analysis. KWB performed statistical analysis. HS and JV analyzed bioinformatics data. All authors read and approved the final manuscript.

Acknowledgements

We thank Dr. Peter Demant from the Department of Molecular and Cellular Biology of the Roswell Park Cancer Institute in Buffalo, New York, USA for useful discussion. We appreciate help of Mrs. Helena Havelková with preparation of figures.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The research had complied with all relevant European Union guidelines for work with animals and was in accordance with the Czech national law and guidelines on the use of experimental animals and protection of animals against cruelty (the Animal Welfare Act Number 246/1992 Coll.). The protocol was approved by the Committee on the Ethics of Animal Experiments of the Institute of Parasitology and of the Departmental Expert Committee for the Approval of Projects of Experiments on Animals of the Academy of Sciences of the Czech Republic (Permit Number: 165/2010).

Funding

This work was supported by the by the Czech Science Foundation [Grants 16-20054S, 14-30186S, 16-22346S], the Academy of Sciences of the Czech Republic [RVO 68378050], the Ministry of Education, Youth, and Sports of the Czech Republic, under the NPU I program [Grant LO1218], by Project “FIT” [Pharmacology, Immunotherapy, nanoToxicology], which was funded by the European Regional Development Fund, the Czech Technical University [SGS15/173/OHK4/2T/17] and by the United States National Institutes of Health [R01 GM074244, to KWB]. Y. Sohrabi and M. Šíma are PhD students of Faculty of Science, Charles University, Prague, Czech Republic, M. Slapničková is a PhD student of Faculty of Science, The University of South Bohemia, České Budějovice, Czech Republic, Lucie Mrázková is a PhD student of the Department of Natural Sciences, Faculty of Biomedical Engineering, Czech Technical University in Prague.

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Author notes

  1. Martin Palus and Yahya Sohrabi contributed equally to this work

Affiliations

  1. Institute of Parasitology, Biology Centre of the Czech Academy of Sciences, Branišovská 31, 37005, České Budějovice, Czech Republic

    Martin Palus & Daniel Růžek

  2. Department of Virology, Veterinary Research Institute, Hudcova 70, 62100, Brno, Czech Republic

    Martin Palus, Daniel Růžek & Jiří Salát

  3. Department of Molecular and Cellular Immunology, Institute of Molecular Genetics, Academy of Sciences of the Czech Republic, Vídeňská 1083, 14220, Prague, Czech Republic

    Yahya Sohrabi, Matyáš Šíma, Valeriya Volkova, Martina Slapničková, Jarmila Vojtíšková, Lucie Mrázková & Marie Lipoldová

  4. Department of Biostatistics and Medical Informatics, 6770 Medical Sciences Center, 1300 University Avenue, Madison, WI, 53706-1532, USA

    Karl W. Broman

  5. Department of Genomics and Bioinformatics, Institute of Molecular Genetics, Academy of Sciences of the Czech Republic, Vídeňská 1083, 14220, Prague, Czech Republic

    Hynek Strnad

  6. Department of Natural Sciences, Faculty of Biomedical Engineering, Czech Technical University in Prague, Sítná 3105, 272 01, Kladno, Czech Republic

    Lucie Mrázková & Marie Lipoldová

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  1. Martin Palus
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Corresponding author

Correspondence to Marie Lipoldová.

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Palus, M., Sohrabi, Y., Broman, K.W. et al. A novel locus on mouse chromosome 7 that influences survival after infection with tick-borne encephalitis virus. BMC Neurosci 19, 39 (2018). https://doi.org/10.1186/s12868-018-0438-8

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Keywords

  • Tick-borne encephalitis virus (TBEV)
  • Mouse model
  • Survival
  • Susceptibility locus
  • Chromosome 7
  • Candidate gene

BMC Neuroscience

ISSN: 1471-2202

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