https://orcid.org/0009-0004-1972-433X
Figures
Abstract
Background
Ticks are widely distributed throughout China and are the second most prevalent pathogen vectors in the world, following only mosquitoes. Tick bites can lead to Lyme disease, forest encephalitis, and other illnesses that may result in death under severe circumstances. Materials and methods: Ticks collected from March 2021 to May 2023 were pooled and used in metatranscriptomic analyses to gain insight into the diversity and distribution of tick-borne viruses in Inner Mongolia. Next-generation sequencing (NGS) outcomes were validated, and viral prevalence across distinct tick species was determined through the application of polymerase chain reaction (PCR) paired with Sanger sequencing.
Results
A total of 20 RNA viruses belonging to at least 8 families, including Chuviridae, Flaviviridae, Solemoviridae, Nairoviridae, Partitiviridae, Phenuiviridae, Rhabdoviridae, and Totiviridae, and to unclassified families were identified by NGS. Five of the identified RNA viruses (Nuomin virus, Yezo virus, tick-borne encephalitis virus, Alongshan virus, and Beiji nairovirus) are considered human pathogens. A potential human pathogen, Mukawa virus, was also among the identified viruses. Ixodes persulcatus carried a significantly greater number of viral species than did Dermacentor nuttalli, Hyalomma marginatum, and Haemaphysalis concinna. The prevalence of coinfection with multiple viruses differed in I. persulcatus from Hinggan League and Hulun Buir, and Beiji nairovirus was the codominant virus species.
Author summary
Ticks are important vectors of zoonotic diseases and play a major role in the circulation and transmission of such diseases. In this study, ticks collected from March 2021 to May 2023 were pooled and subjected to metatranscriptomic analysis to gain insight into the diversity and distribution of tick-borne viruses in Inner Mongolia. Among the identified RNA viruses, 6 are recognized as human pathogens or potential human pathogens; these are Nuomin virus, Yezo virus, tick-borne encephalitis virus, Alongshan virus, Beiji nairovirus, and Mukawa phlebovirus. This study revealed significant diversity among RNA viruses transported by ticks in Inner Mongolia as well as variations in their geographic distribution. To effectively detect alterations in pathogen distribution, ongoing surveillance is urgently needed.
Citation: Su S, Cui M-Y, Xing L-L, Gao R-J, Mu L, Hong M, et al. (2024) Metatranscriptomic analysis reveals the diversity of RNA viruses in ticks in Inner Mongolia, China. PLoS Negl Trop Dis 18(12): e0012706. https://doi.org/10.1371/journal.pntd.0012706
Editor: Michael W. Gaunt, Solena Ag, UNITED STATES OF AMERICA
Received: February 12, 2024; Accepted: November 18, 2024; Published: December 11, 2024
Copyright: © 2024 Su et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The sequence reads generated in this project can be found in the NCBI Short Read Archive under BioProject PRJNA1034810. The viral genome sequences were submitted to the GenBank database under the following accession numbers: OR454143–OR454165, OR723930–OR723967, OR737808–OR737844, OR744750–OR744818, OR754420–OR754428, OR756261–OR756270, OR785045–OR785055, and OR911899–OR911912.
Funding: This work received financial support from the Scientific Research Project of the Mongolian Medicine Collaborative Innovation Center of the Inner Mongolia Autonomous Region (No. MYYXTPY202206 to J-FY). Zhiyuan talent project of Inner Mongolia Medical University (No. ZY0201027 to J-FY). Health Science and Technology Plan of Inner Mongolia Autonomous Region in 2022 (No. 202201213 to J-FY and No. 202201167 to X-YS). Natural Science Foundation of Inner Mongolia Autonomous Region (No. 2022LHMS08004 to J-FY and No. 2020MS08057 to X-YS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Background
Ticks, considered the second most important vector of human disease worldwide, are the primary vectors of hundreds of disease-causing pathogens, including viruses, bacteria, protozoa, and helminths [1]. Their capacity to parasitize multiple hosts, their extensive geographical distribution, and their prolonged life cycles collectively support their pivotal role in the transmission of various diseases [2]. Several tick-borne viruses (TBVs) are associated with serious diseases in both humans and animals. Notable examples include tick-borne encephalitis virus (TBEV) [3], Nairobi sheep disease virus (NSDV) [4], Crimean-Congo haemorrhagic fever virus (CCHFV) [5,6] and severe fever with thrombocytopenia syndrome virus (SFTSV) [7]. In addition, several new viruses, such as Alongshan virus (ALSV), Songling virus (SGLV) [8], and Jingmen virus (JMTV), have emerged in the past decade [9]. Owing to the absence of effective vaccines and reliable clinical diagnostic measures, these diseases pose a constant threat to human health.
Most tick-borne viruses are RNA viruses [10]. The genomes of these viruses frequently undergo genetic mutations during replication, facilitating their spread to new habitats and hosts [11,12]. Next-generation sequencing (NGS) technology has been used extensively in tick virology research [13–16]. Recent studies using next-generation sequencing (NGS) have revealed hundreds of new tick-associated RNA viruses, greatly enhancing our understanding of the tick virome [15,17–21]. Several important culturable tick-borne viruses, such as Dadong virus [22] and Antu virus [23], have also been detected through NGS, highlighting the role of NGS in expanding the knowledge of tick virus diversity and disease transmission potential.
The Inner Mongolia region, which is long and narrow from east to west, covers an area of 1,183,000 square kilometres and contains highly diverse ecological environments. Prior investigations of tick-borne viruses in this region revealed the presence of several viruses that pose significant threats to human health, including ALSV, TBEV, SGLV and CCHFV [24]. More recently, research utilizing metatranscriptomic approaches has revealed the presence of additional tick-borne viruses, such as SZW tick virus (STV), Alxa tick phlebovirus (ATPV), and Alxa tick rhabdovirus (ATRV) [25]. These findings highlight the diversity and significance of tick-borne viruses in this area. Considering the vast expanse and the ecological complexity of Inner Mongolia, it is imperative to maintain extensive and ongoing surveillance of tick-borne viruses in the region.
In this study, we collected four tick species from three distinct ecosystems—forest, desert, and grassland—across nine sampling sites in Inner Mongolia. Metagenomic analyses and PCR were conducted to investigate the diversity of the RNA viruses carried by these ticks. Our research aims to enhance the understanding of RNA virus diversity in ticks within Inner Mongolia and to provide critical data to inform the prevention and control of tick-borne viral diseases in this area.
Materials and methods
Ethics statement
The collection of ticks from the body surfaces of cattle, sheep and goats in this study was verbally approved by the owners of the animals and was performed in strict accordance with the National Guidelines for Experimental Animal Welfare of China (2006–398). In addition, this study was reviewed and approved by the Medical Ethics Committee of Inner Mongolia Medical University (No. YKD202302084).
Sample collection and identification
From March 2021 to May 2023, ticks of the species Dermacentor nuttalli, Ixodes persulcatus, Hyalomma marginatum, and Haemaphysalis concinna were collected from nine locations across Hulun Buir, Hinggan League, and Bayan Nur in Inner Mongolia, China (Fig 1 and Table 1). Adult ticks collected from cattle, sheep and vegetation were grouped and pooled on the basis of species and sampling location (S1 Table). The developmental stage and the species of the collected animals were initially identified on the basis of morphological characteristics by trained experts via stereomicroscopy, followed by confirmation through molecular biological methods utilizing PCR assays of mitochondrial 16S ribosomal RNA [26]. The collected samples were transported to the laboratory in ventilated bottles at low temperatures, and the ticks were then stored at -80°C for RNA library construction and subsequent analysis.
The map was created using the ArcGIS software program. Map source: Xinliang Xu, Multiyear administrative division boundary data of Chinese cities and municipalities, Resource and Environmental Science Data Registration and Publication System (http://www.resdc.cn/DOI, DOI: 10.12078/2023010102).
RNA library construction and sequencing
Prior to nucleic acid extraction, each group of samples was thoroughly cleaned to eliminate potential impurities and pathogens present on their surfaces. After soaking in 75% ethanol (w/v) for 3 min, the ticks were washed three times with phosphate-buffered saline (PBS, pH = 7.4) and dried on clean filter paper. The samples in each group were ground in a mortar at a low temperature, maintained in liquid nitrogen and placed in a 1.5-ml centrifuge tube. Total RNA was extracted from the samples using a TransZol Up Plus RNA Kit (TransGen Biotech). The quality of the extracted RNA was determined using a 2100 Bioanalyzer (Agilent) and quantified via an ND-2000 (NanoDrop Technologies). High-quality RNA samples (OD260/280 = 1.8–2.2, OD260/230 ≥ 2.0) were used to construct a sequencing library.
Metatranscriptome libraries were prepared from 5 μg of total RNA according to the instructions provided with the RNA Sample Preparation Kit from Illumina (San Diego, CA). Briefly, rRNA was removed using rRNA Removal Kits (Epicenter) and fragmented in fragmentation buffer. cDNA synthesis, end repair, A-base addition and ligation of the Illumina-indexed adapters were performed according to Illumina’s protocol. The libraries were then size-selected for cDNA target fragments 200–300 bp in size by electrophoresis on 2% low-range ultra agarose, followed by PCR amplification using Phusion DNA polymerase (NEB) for 15 PCR cycles. Metatranscriptome sequencing was performed by Shanghai Biozeron Biotechnology Co., Ltd. (Shanghai, China). The samples were sequenced on an NGS platform using the Illumina NovaSeq 6000 in paired-end 150 bp (PE150) mode.
Read quality control and mapping
For each library, sequencing quality was assessed using FastQC v0.11.9 [27], followed by quality control using Trimmomatic 0.39 to remove adapters and low-quality sequences [28]. The clean reads were subsequently de novo assembled into contigs using Megahit v1.2.9 [29]. For the assembled genome, Diamond blastx was used to align the assembled contigs against the RdRp-scan 0.90 database to obtain information on RNA viruses, with parameters set to "more sensitive" and a threshold of 1E-5 [30]. Further confirmation of the obtained information was conducted through online BLASTn analysis. Unless otherwise specified, all parameters were set to their default values.
Phylogenetic analysis
To elucidate the evolutionary positions of the viruses found in ticks in Inner Mongolia, a phylogenetic analysis of the amino acid sequences of the viral RdRp proteins was performed. Reference sequences were downloaded from the NCBI database containing ICTV VMR MSL38 v3 virus classification information. For the virus sequences of interest, SeqProcessor v0.1.2 (https://pypi.org/project/seqprocessor/) was first used for sequence name modification, followed by multiple sequence alignment using MAFFT v7.450 software [31]. The phylogenetic trees were constructed using IQ-TREE v1.6.12 software [32], with the optimal substitution model selected by ModelFinder based on the Bayesian information criterion. Details regarding the best-fitting model are provided in the supplementary file (S1 File). The phylogenetic trees were visualized using Chiplot (www.chiplot.online) [33], with the roots determined by the midpoint method, providing an approximate overview of the relationships among the sequences.
cDNA preparation and PCR for virus screening
Viral RNA was extracted using a TransZol Up Plus RNA Kit (TransGen Biotech, China), and cDNA was synthesized using One-Step gDNA Removal and cDNA Synthesis SuperMix (TransGen Biotech, China). To verify the results of NGS and determine the percentage positivity of each species for viruses of interest, oligo7 was used to design specific primers for RT–PCR. cDNA amplification for virus screening was conducted via PCR using PCR Master Mix (Tiangen, China). The amplified PCR products were separated on 1.5% agarose gels and purified for Sanger sequencing using an agarose gel purification kit.
Statistical analysis
The viral infection rates of ticks were calculated using PooledInfRate software, version 4.0 (a Microsoft Office Excel Add-In designed by Brad J. Biggerstaff to compute prevalence estimates from pooled samples, Centers for Disease Control and Prevention, Fort Collins, CO, USA, 2024). The data were analysed using SPSS version 21.0. Differences in the percentage of infection rates of viruses in ticks were evaluated via Fisher’s exact test, with a significance threshold of p < 0.05.
Results
Tick collection and identification
A total of 1,168 adult ticks were collected and identified from Hulun Buir (n = 281), Bayan Nur (n = 270), and Hinggan League (n = 637); the collected ticks included 897 I. persulcatus, 122 D. nuttalli, 148 H. marginatum, and 21 H. concinna (Fig 1 and Table 1). We divided 130 sample pools into five groups according to species and geographical origin, each representing a unique tick species from a specific region: I. persulcatus from the Hinggan League region (library D), D. nuttalli from the Bayan Nur region (library B), H. marginatum from the Bayan Nur region (library E), H. concinna collected in Hulun Buir (library G) and I. persulcatus collected in Hulun Buir (library K).
Identification of RNA viruses
Five RNA libraries were constructed and sequenced, resulting in 71.1 gigabases (GB) of high-quality, clean data comprising 480 million nonribosomal RNA (non-rRNA) reads. De novo assembly of these data yielded 405 distinct viral sequences from approximately 980,000 viral reads, constituting 0.2% of the total non-rRNA reads. The percentage of viral reads ranged from 0.006% (library G) to 44.0% (library K) of the total nonhost (no host rate) reads. After further confirmation via online BLASTn analysis, the viral contigs were ultimately annotated to at least 8 viral families and 20 distinct viral species, as detailed in Table 2. Notably, 5 families of vertebrate-infecting viruses were identified, namely, Chuviridae, Flaviviridae, Nairoviridae, Phenuiviridae, and Rhabdoviridae. These families included 6 viruses potentially associated with human and livestock diseases, namely, Nuomin virus (NUMV), Yezo virus (YZV), TBEV, ALSV, Mukawa phlebovirus (MKWV), and Beiji nariovirus (BJNV).
In a comparative analysis of the five RNA libraries, library D presented the greatest diversity, with 13 detected viruses, followed by library K, with 11 viruses, and libraries B and E, each of which contained only 3 viruses (S2 Table). Library G contained only 2 viruses. Ten viruses were shared between libraries K and D; these represented several viral families: Chuviridae (Nuomin virus), Flaviviridae (tick-borne encephalitis virus, Alongshan virus), Nairoviridae (Beiji nairovirus), Phenuiviridae (Mukawa phlebovirus, Onega tick phlebovirus, Sara tick-borne phlebovirus), Rhabdoviridae (Tahe rhabdovirus 2, Tahe rhabdovirus 3) and Solemoviridae (Ixodes scapularis-associated virus 1).
Among the 20 viruses identified, 14 were harboured by I. persulcatus ticks, and 3 were carried by D. nuttalli ticks and H. marginatum ticks. H. concinna ticks carried the least variety of RNA viruses, with only 2 viruses detected. Notably, the majority of the viruses are species-specific.
Virus composition and evolution
In the phylogenetic tree constructed on the basis of the amino acid sequences of the viral RdRp proteins, the sequences representative of this study were clustered with the corresponding published viral sequences obtained from the NCBI database (Figs 2–4).
ML tree of representative viruses based on the RdRp genes. (A) ML tree of Bunyavirales viruses. (B) ML tree of viruses of Flaviviridae. (C) ML tree of viruses of Nairoviridae. The viruses newly identified in this study and previously identified viruses are shown in red and black, respectively. The best-fit amino acid substitution model for each phylogenetic tree was LG + F + R10 for Bunyavirales, LG + F + R7 for Flaviviridae, and LG + F + G4 for Nairoviridae.
ML tree of representative viruses based on the RdRp genes. (A) ML tree of Chuviridae viruses. (B) ML tree of Partitiviridae viruses. (C) ML tree of Phenuiviridae viruses (Fold clade 1 includes several members of the genus Phlebovirus. Fold clade 2 includes Phasivirus, Beidivirus, Hudivirus, Pidchovirus, Hudovirus, Tenuivirus, Mechlorovirus, and Horwuvirus. Fold clade 3 includes Goukovirus and Mobuvirus. Fold clade 4 includes Coguvirus, Laulavirus, Lentinuvirus, Entovirus, and Rubodvirus). The viruses newly identified in this study and previously identified viruses are shown in red and black, respectively. The best-fit amino acid substitution model for each phylogenetic tree was LG + I + G4 for Chuviridae, LG + F + I + G4 for Partitiviridae, and LG + F + R10 for Phenuiviridae.
ML tree of representative viruses based on the RdRp genes. (A) ML tree of Rhabdoviridae (Fold clade 1 includes Hapavirus, Arurhavirus, Curiovirus, Ephemerovirus, Tibrovirus, Vesiculovirus, Sprivivirus, Perhabdovirus, Siniperhavirus, Cetarhavirus, Scophrhavirus, Sigmaviris, Alphapaprhavirus, Ohlsrhavirus, Merhavirus, Caligrhavirus, Sunrhavirus, Sripuvirus, Tupavirus, Ledantevirus, and Thriprhavirus. Fold clade 2 includes Lyssavirus, Replylivirus, and Amplylivirus. Fold clade 3 includes Betanucleorhabdovirus, Dichorhavirus, Alphanucleorhabdovirus, Gammanucleorhabdovirus, Varicosavirus, Cytorhabdovirus, Alphahymrhavirus, Betanemrhavirus, Alphacrustrhavirus, Betaricinrhavirus, Aphadrosrhavirus, Betahymrhavirus, and Betanemrhavirus). (B) ML tree of Solemoviridae. (C) ML tree of Totiviridae. The viruses newly identified in this study and previously identified viruses are shown in red and black, respectively. The best-fit amino acid substitution model for each phylogenetic tree was LG + F + R10 for Rhabdoviridae, LG + F + R5 for Solemoviridae, and LG + F + I + G4 for Totiviridae.
Phylogenetic analysis of unclassified Bunyavirales sequences
The order Bunyavirales encompasses a diverse array of viruses, many of which are arthropod-borne and capable of causing significant disease in humans and animals, including the Crimean-Congo haemorrhagic fever virus (CCHFV), Hantavirus, and Rift Valley fever virus (RVFV) [34–36]. In this study, a contig belonging to Volzhskoe tick virus, an unclassified member of the Bunyavirales, was identified in H. marginatum ticks; the strain from which this contig was derived showed 87.3% nucleotide similarity to a previously identified strain of H. marginatum from Astrakhan, Russia, and it clustered in the same branch of the phylogenetic tree (Table 2 and Fig 2A).
Phylogenetic analysis of Flaviviridae sequences
The family Flaviviridae is extensive and includes numerous significant human pathogens [37,38]. Three viruses belonging to the Flaviviridae were identified in three tick species. These viruses include ALSV and TBEV, both of which are associated with human disease; they were found in I. persulcatus ticks from Hulun Buir and Hinggan League. The nucleotide identities of these viruses with other strains of I. persulcatus ranged from 98.0% to 99.6% for TBEV and from 95.8% to 99.5% for ALSV. Additionally, a Pestivirus-like virus, Bole tick virus 4, was detected in D. nuttalli and H. marginatum; it had nucleotide identities of 93.2%–97.5% with other Bole tick virus 4 strains. These sequences all clustered with published sequences (Table 2 and Fig 2B).
Phylogenetic analysis of Nairoviridae sequences
Members of the family Nairoviridae consist of three negative-sense, single-stranded RNA segments [39]. Orthonairovirus is a genus within the Nairoviridae. These viruses are found in arthropods and are transmitted to mammals by ticks [40]. BJNV and YZV were discovered in I. persulcatus ticks through NGS. BJNV sharing nucleotide identities of 98.4%–99.8% with other strains was detected in I. persulcatus from both Hulun Buir and Hinggan League. YZV was detected only in I. persulcatus ticks from Hulun Buir; it had nucleotide identities of 98.6%–99.0% with other strains (Table 2 and Fig 2C).
Phylogenetic analysis of Chuviridae sequences
The genus Mivirus belongs to the newly classified family Chuviridae, a recently recognized viral family within the order Jingchuvirales [41,42]. Two Mivirus viruses and one Nigecruvirus virus were identified in ticks by NGS. NUMV showing 99.8%–99.9% nucleotide identity with other strains was detected in I. persulcatus ticks from Hulun Buir and Hinggan League. Bole tick virus 3 was derived from only H. marginatum ticks; it showed 98.6% nucleotide similarity to strains isolated from Hyalomma asiaticum. Taiga tick nigecruvirus was obtained from I. persulcatus ticks from Hinggan League and presented 98.0% nucleotide identity with other strains (Table 2 and Fig 3A).
Phylogenetic analysis of Partitiviridae sequences
A Deltapartitivirus-like virus, Jilin partita-like virus 1, belonging to the family Partitiviridae was harvested from I. persulcatus ticks from Hinggan League and showed nucleotide identities of 99.7% with other strains (Table 2 and Fig 3B). The family Partitiviridae is known for its double-stranded RNA genomes and typically infects plants and fungi [43].
Phylogenetic analysis of Phenuiviridae sequences
The genus Phlebovirus belongs to the family Phenuiviridae; it infects mammals, including livestock and humans, and is transmitted by infected arthropods [44,45]. Three viruses belonging to the Phenuiviridae were found in I. persulcatus ticks: one Phlebovirus, MKWV, and two Ixoviruses, Onega tick phlebovirus and Sara tick phlebovirus. The nucleotide identities of these strains were 89.1%–98.8%, 99.6%–100.0%, and 99.6%–100.0%, respectively (Table 2 and Fig 3C).
Phylogenetic analysis of Rhabdoviridae sequences
The family Rhabdoviridae, a member of the order Mononegavirales, includes important pathogens that affect humans, livestock, fish, and agricultural crops [46]. Rhabdoviruses are found in invertebrates such as arthropods, some of which serve as hosts or vectors for transmission to other animals or plants [47]. We identified several viral contigs belonging to Rhabdoviridae; all were Alphanemrhavirus-like viruses. The strains included Tahe rhabdovirus 1 from H. concinna ticks, and Tahe rhabdovirus 2 and Tahe rhabdovirus 3 from I. persulcatus ticks from Hulun Buir and Hinggan League; the nucleotide identities of these viruses with other strains were 99.6%, 98.7%–99.2%, and 99.7–99.9%, respectively (Table 2 and Fig 4A).
Phylogenetic analysis of Solemoviridae sequences
Solemoviridae is a recently recognized family of plant-infecting viruses. Solemoviridae are transmitted abiotically via mechanical damage, via asexual reproduction or through soil or insects [48]. In this study, we identified several viral contigs belonging to the Solemoviridae. Xinjiang tick-associated virus 1 was identified in D. nuttalli ticks, and Ixodes scapularis-associated virus 1 and Jilin luteo-like virus 2 were discovered in I. persulcatus ticks. The nucleotide identities of these viruses with other strains were 98.9%, 98.5%–99.2%, and 98.9%, respectively (Table 2 and Fig 4B).
Phylogenetic analysis of Totiviridae sequences
The Totiviridae are double-stranded RNA viruses that commonly infect fungi and protozoa [49]. In this study, Totiviridae sp. showing 96.9%–98.6% nucleotide identity with previously discovered strains were detected in H. concinna (Table 2 and Fig 4C).
Statistical analysis of the virus detection results
In this study, important pathogenic viruses were identified in RNA libraries by NGS; each sample of collected ticks was further subjected to PCR combined with sequencing to identify the RNA viruses it carried and to analyse the distribution and prevalence of the viruses. The primers used for amplification are listed in S3 Table. The nucleotide sequences of the identified RNA viruses amplified via PCR have been submitted to NCBI (S4 Table).
A total of 20 viruses representing more than eight different families were confirmed to be present in the ticks collected in this study. RNA viruses were detected in 76 (58.5%) of the 130 tick pools that underwent molecular screening (Table 3). Thirteen viruses were detected in I. persulcatus collected in Hinggan League. Among these tick samples, Jilin partiti-like virus 1 had the lowest prevalence at 0.5% (3/26), whereas the emerging zoonotic pathogen BJNV had the highest prevalence at 7.7% (23/26). Other tick-borne viruses with potential relevance to human and livestock diseases included TBEV, ALSV, NUMV, and MKWV; the collected ticks were infected with these viruses at rates of 1.1% (6/26), 1.4% (7/26), 4.7% (17/26), and 1.7% (8/26), respectively.
The rates at which ticks were infected with viruses were calculated using the bias-corrected MLE method in PooledInfRate software, version 4.0; 95% confidence intervals (CIs) are presented in brackets.
Eight viruses, including five potentially pathogenic viruses, were detected in I. persulcatus from Hulun Buir. YZV had the lowest prevalence at 0.38% (1/14), followed by NUMV at 0.8% (2/14), ALSV at 1.3% (3/14), Sara tick phlebovirus at 0.4% (1/14), and BJNV, which had the highest prevalence at 8.7% (12/14).
Specimens of D. nuttalli and H. marginatum collected from Bayan Nur were found to carry three different viruses each. Both of these species were coinfected with Bole tick virus 4 at rates of 5.2% (6/30) and 17.4% (20/50), respectively. Volzhskoe tick virus and Bole tick virus 3 were detected in H. marginatum in China for the first time, with infection rates of 10.1% (14/50) and 1.4% (2/50), respectively. Xinjiang tick-associated virus 1 and Totiviridae sp. were detected only in D. nuttalli; the infection rate for each of these viruses was 0.8% (1/30).
A statistical comparison of the carriage rates of concurrently detected viruses in I. persulcatus from two different regions revealed significant disparities (Table 4). The prevalence of ALSV remained consistent across regions. However, substantial regional discrepancies were observed for Sara tick phlebovirus and Onega tick phlebovirus, both of which belong to the Phenuiviridae; these viruses exhibited notably greater prevalence in ticks collected from Hinggan League than in ticks collected from Hulun Buir. Additionally, BJNV, an Orthonairovirus from the Nairoviridae family, presented the highest prevalence among the cases of concurrent infection; it displayed a homogeneous distribution across the studied tick populations, indicating widespread prevalence. Conversely, significant disparities in the distributions of NUMV and Tahe rhabdovirus 3, which belong to the Chuviridae and Rhabdoviridae, respectively, were observed; these viruses were more prevalent in Hinggan League than in Hulun Buir.
Discussion
In this study, we delineated the diverse constellation of RNA viromes harboured by several tick species in Inner Mongolia, China. By utilizing high-throughput transcriptome sequencing, we identified a wide range of RNA viruses in I. persulcatus, D. nuttalli, H. marginatum, and H. concinna. The 20 distinct viral species represented at least 8 virus families, including Chuviridae, Flaviviridae, Solemoviridae, Nairoviridae, Partitiviridae, Phenuiviridae, Rhabdoviridae, and Totiviridae.
PCR validation reinforced the data obtained through NGS, unequivocally confirming the presence of a diverse array of viruses within the tick populations subjected to analysis. Among the detected viruses, NUMV [20], YZV [50], TBEV [51], ALSV [52], and BJNV [53] have been recognized as pathogens that are capable of infecting humans. These findings not only reaffirm the findings of previous studies of viromes in Northeast China [15,20,54] but also emphasize the widespread presence of RNA viruses in tick populations. Notably, ALSV has been detected in tick-bitten patients and in I. persulcatus in Inner Mongolia and Heilongjiang [52]. Additionally, viral RNA and virus-specific antibodies have been identified in sheep and cattle in Hulunbuir, northeastern Inner Mongolia [55]. The detection of ALSV in I. persulcatus ticks collected from Hinggan League and Hulun Buir, Inner Mongolia, further confirms previous findings. Tick-borne encephalitis (TBE) has been shown to be endemic in China, including the three mountainous areas of Heilongjiang, Jilin, Inner Mongolia, and Xinjiang [24,56]. Inner Mongolia, especially the forested and grassland environments of that region, plays a particularly important role in the transmission of tick-borne encephalitis virus (TBEV). These areas provide conditions that favour the survival and proliferation of ticks, facilitating the spread of TBEV. In this study, TBEV was detected in I. persulcatus ticks collected from the Hinggan League of Inner Mongolia. Liu et al. previously detected TBEV in northeastern China via metagenomic techniques [15]. However, the results of the current study suggest that the natural foci of TBEV in these regions may be more widespread than was previously believed. The current findings underscore the importance of ongoing surveillance for tick-borne viruses and the need for public health interventions. Phleboviruses infect mammals, including livestock and humans, and are transmitted by infected mosquitoes, phlebotomine sandflies, and ticks [57]. Studies have shown that Mukawa virus can replicate in mammalian cells, indicating that there is potential for its zoonotic transmission [58]. In this study, MKWV was detected in I. persulcatus ticks collected from two locations. Previous studies have detected these viruses in ticks of various classes in various regions, but the current study provides a more comprehensive understanding of the distribution of these viruses as well as of their prevalence in different tick species. Notably, the Volzhskoe tick virus, previously detected only in I. persulcatus ticks from northern China [20], is here reported for the first time to be present in H. marginatum ticks in China. Although the pathogenicity of this virus remains unknown, the findings suggest that the virus may have a broader geographical distribution than was previously suspected and that various tick species may act as vectors of the virus within China.
The utilization of PCR-based methods to detect viruses in tick populations has revealed significant differences in viral prevalence among tick species and in different geographical locations. In Hinggan League, I. persulcatus tick pools presented an exceptionally high prevalence of viral infection; 100% (26/26) of the collected tick pools tested positive for viruses. In Hulun Buir, the virus positivity rate in I. persulcatus tick pools was also high, reaching 92.9% (13/14). In contrast, in Bayan Nur, the virus infection rates in the D. nuttalli and H. marginatum tick pools were lower, 20.0% (6/30) and 60.0% (30/50), respectively. Notably, in Hulun Buir, only one H. concinna sample pool tested positive for viruses, yielding a virus detection rate of 10.0% (1/10). It is noteworthy that the elevated number of viruses detected in I. persulcatus may be attributed to the substantially larger sample size collected. Furthermore, I. persulcatus were gathered as free-living ticks from forest and shrub environments, in contrast to other species, which were collected directly from host animals. These findings reflect differences in the capacities of various tick species to serve as virus vectors. Consistent with previous studies, I. persulcatus ticks were found to carry the most diverse range of viruses [59].
The species-specific distribution of tick-borne viruses is further exemplified by the exclusive presence of certain viruses in particular tick hosts. Xinjiang tick-associated virus 1 and Totiviridae sp. were detected only in D. nuttalli ticks. Bole tick virus 3 and Volzhskoe tick viruses were uniquely identified in H. marginatum ticks, whereas Tahe rhabdovirus 1 was isolated exclusively from H. concinna. In contrast, I. persulcatus ticks were identified as hosts of 14 other distinct viruses, including 5 tick-borne viruses known to cause illness in humans as well as other potentially pathogenic viruses.
A statistical analysis of the prevalence of specific viruses in I. persulcatus ticks from two distinct regions revealed comparable rates of infection by ALSV and BJNV in the two regions. However, a marked discrepancy was observed in the prevalence of Sara tick phlebovirus, Onega tick phlebovirus, NUMV, and Tahe rhabdovirus 3, with ticks from Hinggan League demonstrating a significantly greater rate of infection with these viruses than ticks from Hulun Buir. The survival and reproduction of ticks, which are important vector organisms, are directly influenced by environmental conditions. Consequently, the distributions of tick species and the viruses they carry vary across different ecosystems. The Hinggan League area has a high density of forests that are predominantly coniferous and provide a stable habitat for ticks. The diverse forest vegetation and the humid environment of this region favour tick survival and reproduction. Additionally, the deciduous and humus layers of vegetation in the forest provide suitable habitats for ticks. In contrast, the Hulun Buir area is primarily a steppe ecosystem in which there is relatively sparse vegetation cover, especially during the dry season when the vegetation density is lowest. The open environment and greater temperature fluctuations in the grassland environment are less conducive to tick survival and reproduction than are conditions in the forest environment. Owing to their stable and diverse ecosystems, Hinggan League and Hulun Buir offer favourable habitat conditions for a diverse range of tick species and the viruses they carry. Conversely, the arid environment of Bayan Nur restricts the diversity of tick species and their viruses. The findings suggest that the ecological diversity of Inner Mongolia significantly affects the distribution of RNA viruses in ticks. In addition, changes in natural environmental conditions alter tick habitats and thereby impact the ecology of tick-borne viruses [60]. The ecological data gathered in this study will aid future research on virus transmission through advanced methods such as mathematical modelling and machine learning [61,62]. Notably, the prominent presence of BJNV, which emerged as the pathogen with the highest prevalence in ticks in Inner Mongolia, indicated a widespread distribution of this virus within the I. persulcatus populations of both regions. Since ticks cannot travel long distances, they are likely to acquire the viruses they harbour from local organisms with which they interact. This highlights both the potential for BJNV to pose a significant public health concern and the importance of ongoing surveillance for tick-borne pathogens.
In conclusion, this study utilized NGS to investigate the spectrum of viruses present in tick populations across various regions of Inner Mongolia. Validation of the NGS results was performed via PCR combined with Sanger sequencing; in this way, the prevalence of these viruses in various tick species was determined. The detection of these viruses not only underscores the diversity of RNA viruses carried by ticks in Inner Mongolia but also reveals the variations in their distributions in different regions and different tick hosts. However, it is important to acknowledge the limitations of this study. Some other causative viruses previously reported in Inner Mongolia, such as the severe fever with thrombocytopenia syndrome virus (SFTSV) [54] and SGLV [15], were not detected in this investigation. Our investigation may not encompass all tick species and geographical areas in Inner Mongolia and may have potentially overlooked certain viral hosts. Moreover, our understanding of the epidemiology of these viruses and their adaptability to hosts remains superficial. Future research should aim to broaden the sample range by including a greater diversity of tick species and geographical locations and by conducting more in-depth studies into the ecology and evolution of viruses carried by ticks.
Conclusions
The findings of this study revealed significant diversity among RNA viruses carried by ticks collected from various geographical regions in Inner Mongolia, China. To detect alterations in pathogen distribution effectively, ongoing surveillance is urgently needed. The changing natural environment is altering tick habitats, thereby affecting the distribution of the viruses they transmit. Our findings across different ecosystems and climates lay a foundation for research on predicting the spatiotemporal distribution and transmission of viruses.
Supporting information
S1 Table. Grouping and pooling information on the studied adult ticks.
https://doi.org/10.1371/journal.pntd.0012706.s001
(DOC)
S2 Table. Viruses identified from each library in the present study.
https://doi.org/10.1371/journal.pntd.0012706.s002
(DOC)
S3 Table. Primer sequences used in virus detection.
https://doi.org/10.1371/journal.pntd.0012706.s003
(DOC)
S4 Table. Accession numbers of viral sequences amplified by PCR.
https://doi.org/10.1371/journal.pntd.0012706.s004
(DOC)
S1 File. Data used in phylogenetic tree construction for each family, including aligned sequences, software logs, best-fit substitution models, and phylogenetic trees.
https://doi.org/10.1371/journal.pntd.0012706.s005
(ZIP)
Acknowledgments
We are very grateful to the Molecular Biology Research Center of Inner Mongolia Medical University for providing the experimental facilities used in this study.
References
- 1. de la Fuente J, Estrada-Pena A, Venzal JM, Kocan KM, Sonenshine DE. Overview: Ticks as vectors of pathogens that cause disease in humans and animals. Front Biosci. 2008;13:6938–46. Epub 2008/05/30. pmid:18508706.
- 2. Jongejan F, Uilenberg G. The global importance of ticks. Parasitology. 2004;129 Suppl:S3–14. Epub 2005/06/09. pmid:15938502.
- 3. Mansfield KL, Johnson N, Phipps LP, Stephenson JR, Fooks AR, Solomon T. Tick-borne encephalitis virus—a review of an emerging zoonosis. J Gen Virol. 2009;90(Pt 8):1781–94. Epub 2009/05/08. pmid:19420159.
- 4. Gong S, He B, Wang Z, Shang L, Wei F, Liu Q, et al. Nairobi sheep disease virus RNA in ixodid ticks, China, 2013. Emerg Infect Dis. 2015;21(4):718–20. Epub 2015/03/27. pmid:25811222; PubMed Central PMCID: PMC4378503.
- 5. Xia H, Li P, Yang J, Pan L, Zhao J, Wang Z, et al. Epidemiological survey of Crimean-Congo hemorrhagic fever virus in Yunnan, China, 2008. Int J Infect Dis. 2011;15(7):e459–63. Epub 2011/05/07. pmid:21546303.
- 6. Yen YC, Kong LX, Lee L, Zhang YQ, Li F, Cai BJ, et al. Characteristics of Crimean-Congo hemorrhagic fever virus (Xinjiang strain) in China. Am J Trop Med Hyg. 1985;34(6):1179–82. Epub 1985/11/01. pmid:2422968.
- 7. Zhang Y, Huang Y, Xu Y. Antiviral Treatment Options for Severe Fever with Thrombocytopenia Syndrome Infections. Infect Dis Ther. 2022;11(5):1805–19. Epub 2022/09/23. pmid:36136218; PubMed Central PMCID: PMC9510271.
- 8. Ma J, Lv XL, Zhang X, Han SZ, Wang ZD, Li L, et al. Identification of a new orthonairovirus associated with human febrile illness in China. Nat Med. 2021;27(3):434–9. Epub 2021/02/20. pmid:33603240.
- 9. Zhang X, Wang N, Wang Z, Liu Q. The discovery of segmented flaviviruses: implications for viral emergence. Curr Opin Virol. 2020;40:11–8. Epub 2020/03/29. pmid:32217446.
- 10. Kazimírová M, Thangamani S, Bartíková P, Hermance M, Holíková V, Štibrániová I, et al. Tick-Borne Viruses and Biological Processes at the Tick-Host-Virus Interface. Front Cell Infect Microbiol. 2017;7:339. Epub 2017/08/12. pmid:28798904; PubMed Central PMCID: PMC5526847.
- 11. Narasimhan S, Swei A, Abouneameh S, Pal U, Pedra JHF, Fikrig E. Grappling with the tick microbiome. Trends Parasitol. 2021;37(8):722–33. Epub 2021/05/09. pmid:33962878; PubMed Central PMCID: PMC8282638.
- 12. Moya A, Elena SF, Bracho A, Miralles R, Barrio E. The evolution of RNA viruses: A population genetics view. Proc Natl Acad Sci U S A. 2000;97(13):6967–73. Epub 2000/06/22. pmid:10860958; PubMed Central PMCID: PMC34371.
- 13. Pérez-Sautu U, Wiley MR, Prieto K, Chitty JA, Haddow AD, Sánchez-Lockhart M, et al. Novel viruses in hard ticks collected in the Republic of Korea unveiled by metagenomic high-throughput sequencing analysis. Ticks Tick Borne Dis. 2021;12(6):101820. Epub 2021/09/24. pmid:34555711.
- 14. Pettersson JH, Shi M, Bohlin J, Eldholm V, Brynildsrud OB, Paulsen KM, et al. Characterizing the virome of Ixodes ricinus ticks from northern Europe. Sci Rep. 2017;7(1):10870. Epub 2017/09/09. pmid:28883464; PubMed Central PMCID: PMC5589870.
- 15. Liu Z, Li L, Xu W, Yuan Y, Liang X, Zhang L, et al. Extensive diversity of RNA viruses in ticks revealed by metagenomics in northeastern China. PLoS Negl Trop Dis. 2022;16(12):e0011017. Epub 2022/12/22. pmid:36542659; PubMed Central PMCID: PMC9836300.
- 16. He T, Zhu C, Li Z, Ai L, Hu D, Wang C, et al. Virome analysis of ticks in Zhoushan Archipelago, China. J Vet Med Sci. 2022;84(6):847–54. Epub 2022/05/19. pmid:35584918; PubMed Central PMCID: PMC9246684.
- 17. Ni XB, Cui XM, Liu JY, Ye RZ, Wu YQ, Jiang JF, et al. Metavirome of 31 tick species provides a compendium of 1,801 RNA virus genomes. Nature microbiology. 2023;8(1):162–73. Epub 2023/01/06. pmid:36604510; PubMed Central PMCID: PMC9816062.
- 18. Wang R, Liu S, Sun H, Xu C, Wen Y, Wu X, et al. Metatranscriptomics Reveals the RNA Virome of Ixodes Persulcatus in the China-North Korea Border, 2017. Viruses. 2023;16(1). Epub 2024/01/23. pmid:38257762; PubMed Central PMCID: PMC10819109.
- 19. Hu G, Jiang F, Luo Q, Zong K, Dong L, Mei G, et al. Diversity Analysis of Tick-Borne Viruses from Hedgehogs and Hares in Qingdao, China. Microbiol Spectr. 2023:e0534022. Epub 2023/04/19. pmid:37074196.
- 20. Qin T, Shi M, Zhang M, Liu Z, Feng H, Sun Y. Diversity of RNA viruses of three dominant tick species in North China. Frontiers in veterinary science. 2022;9:1057977. Epub 2023/01/31. pmid:36713863; PubMed Central PMCID: PMC9880493.
- 21. Cai X, Cai X, Xu Y, Shao Y, Fu L, Men X, et al. Virome analysis of ticks and tick-borne viruses in Heilongjiang and Jilin Provinces, China. Virus Res. 2022;323:199006. Epub 2022/11/23. pmid:36414189.
- 22. Li F, Li J, Song J, Li D, Yin Q, Fu S, et al. Identification of a novel orthonairovirus from ticks and serological survey in animals near China-North korea border. Journal of medical virology. 2024;96(4):e29567. Epub 2024/03/28. pmid:38546093.
- 23. Li F, Li J, Song J, Yin Q, Nie K, Xu S, et al. Novel Orthonairovirus Isolated from Ticks near China-North Korea Border. Emerg Infect Dis. 2023;29(6):1254–7. Epub 2023/05/21. pmid:37209692; PubMed Central PMCID: PMC10202851.
- 24. Wu Y, Zhou Q, Mao M, Chen H, Qi R. Diversity of species and geographic distribution of tick-borne viruses in China. Front Microbiol. 2024;15:1309698. Epub 2024/03/13. pmid:38476950; PubMed Central PMCID: PMC10929907.
- 25. Teng AY, Che TL, Zhang AR, Zhang YY, Xu Q, Wang T, et al. Mapping the viruses belonging to the order Bunyavirales in China. Infect Dis Poverty. 2022;11(1):81. Epub 2022/07/08. pmid:35799306; PubMed Central PMCID: PMC9264531.
- 26. Black WCt, Piesman J. Phylogeny of hard- and soft-tick taxa (Acari: Ixodida) based on mitochondrial 16S rDNA sequences. Proc Natl Acad Sci U S A. 1994;91(21):10034–8. Epub 1994/10/11. pmid:7937832; PubMed Central PMCID: PMC44952.
- 27.
Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics, Babraham Institute, Cambridge, United Kingdom; 2010.
- 28. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. Epub 2014/04/04. pmid:24695404; PubMed Central PMCID: PMC4103590.
- 29. Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31(10):1674–6. Epub 2015/01/23. pmid:25609793.
- 30. Buchfink B, Reuter K, Drost H-GJNm. Sensitive protein alignments at tree-of-life scale using DIAMOND. 2021;18(4):366–8. pmid:33828273
- 31. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular biology and evolution. 2013;30(4):772–80. Epub 2013/01/19. pmid:23329690; PubMed Central PMCID: PMC3603318.
- 32. Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Molecular biology and evolution. 2015;32(1):268–74. Epub 2014/11/06. pmid:25371430; PubMed Central PMCID: PMC4271533.
- 33. Xie J, Chen Y, Cai G, Cai R, Hu Z, Wang H. Tree Visualization By One Table (tvBOT): a web application for visualizing, modifying and annotating phylogenetic trees. Nucleic acids research. 2023. Epub 2023/05/05. pmid:37144476.
- 34. Neriya Y, Kojima S, Sakiyama A, Kishimoto M, Iketani T, Watanabe T, et al. A comprehensive list of the Bunyavirales replication promoters reveals a unique promoter structure in Nairoviridae differing from other virus families. Sci Rep. 2022;12(1):13560. Epub 2022/08/10. pmid:35945265; PubMed Central PMCID: PMC9363447.
- 35. Monsalve-Arteaga L, Alonso-Sardón M, Muñoz Bellido JL, Vicente Santiago MB, Vieira Lista MC, López Abán J, et al. Seroprevalence of Crimean-Congo hemorrhagic fever in humans in the World Health Organization European region: A systematic review. PLoS Negl Trop Dis. 2020;14(3):e0008094. Epub 2020/03/03. pmid:32119682; PubMed Central PMCID: PMC7067482.
- 36. Paquette SJ, Simon AY, Xiii A, Kobinger GP, Shahhosseini N. Medically Significant Vector-Borne Viral Diseases in Iran. Microorganisms. 2023;11(12). Epub 2023/12/23. pmid:38138150; PubMed Central PMCID: PMC10745727.
- 37. Marceau CD, Puschnik AS, Majzoub K, Ooi YS, Brewer SM, Fuchs G, et al. Genetic dissection of Flaviviridae host factors through genome-scale CRISPR screens. Nature. 2016;535(7610):159–63. Epub 2016/07/08. pmid:27383987; PubMed Central PMCID: PMC4964798.
- 38. Simmonds P, Becher P, Bukh J, Gould EA, Meyers G, Monath T, et al. ICTV Virus Taxonomy Profile: Flaviviridae. J Gen Virol. 2017;98(1):2–3. Epub 2017/02/22. pmid:28218572; PubMed Central PMCID: PMC5370391.
- 39. Garrison AR, Alkhovsky Альховский Сергей Владимирович SV, Avšič-Županc T, Bente DA, Bergeron É, Burt F, et al. ICTV Virus Taxonomy Profile: Nairoviridae. J Gen Virol. 2020;101(8):798–9. Epub 2020/08/26. pmid:32840475; PubMed Central PMCID: PMC7641396.
- 40. Lasecka L, Baron MD. The molecular biology of nairoviruses, an emerging group of tick-borne arboviruses. Arch Virol. 2014;159(6):1249–65. Epub 2013/12/12. pmid:24327094; PubMed Central PMCID: PMC7087186.
- 41. Bratuleanu BE, Temmam S, Munier S, Chrétien D, Bigot T, van der Werf S, et al. Detection of Phenuiviridae, Chuviridae Members, and a Novel Quaranjavirus in Hard Ticks From Danube Delta. Front Vet Sci. 2022;9:863814. Epub 2022/05/03. pmid:35498749; PubMed Central PMCID: PMC9044029.
- 42. Kuhn JH, Dheilly NM, Junglen S, Paraskevopoulou S, Shi M, Di Paola N. ICTV Virus Taxonomy Profile: Jingchuvirales 2023. J Gen Virol. 2023;104(12). Epub 2023/12/19. pmid:38112154; PubMed Central PMCID: PMC10770922.
- 43. Vainio EJ, Chiba S, Ghabrial SA, Maiss E, Roossinck M, Sabanadzovic S, et al. ICTV Virus Taxonomy Profile: Partitiviridae. J Gen Virol. 2018;99(1):17–8. Epub 2017/12/08. pmid:29214972; PubMed Central PMCID: PMC5882087.
- 44. Sun MH, Ji YF, Li GH, Shao JW, Chen RX, Gong HY, et al. Highly adaptive Phenuiviridae with biomedical importance in multiple fields. J Med Virol. 2022;94(6):2388–401. Epub 2022/01/25. pmid:35072274.
- 45. Sasaya T, Palacios G, Briese T, Di Serio F, Groschup MH, Neriya Y, et al. ICTV Virus Taxonomy Profile: Phenuiviridae 2023. J Gen Virol. 2023;104(9). Epub 2023/09/13. pmid:37702592.
- 46. Walker PJ, Freitas-Astúa J, Bejerman N, Blasdell KR, Breyta R, Dietzgen RG, et al. ICTV Virus Taxonomy Profile: Rhabdoviridae 2022. J Gen Virol. 2022;103(6). Epub 2022/06/21. pmid:35723908.
- 47. Dietzgen RG, Kondo H, Goodin MM, Kurath G, Vasilakis N. The family Rhabdoviridae: mono- and bipartite negative-sense RNA viruses with diverse genome organization and common evolutionary origins. Virus Res. 2017;227:158–70. Epub 2016/11/05. pmid:27773769; PubMed Central PMCID: PMC5124403.
- 48. Sõmera M, Fargette D, Hébrard E, Sarmiento C, Ictv Report C. ICTV Virus Taxonomy Profile: Solemoviridae 2021. J Gen Virol. 2021;102(12). Epub 2021/12/25. pmid:34951396; PubMed Central PMCID: PMC8744267.
- 49. Li F, Du J, Wu Z, Zhang W, Fu S, Song J, et al. Identification and genetic analysis of a totivirus isolated from the Culex tritaeniorhynchus in northern China. Arch Microbiol. 2020;202(4):807–13. Epub 2019/12/18. pmid:31844947.
- 50. Kodama F, Yamaguchi H, Park E, Tatemoto K, Sashika M, Nakao R, et al. A novel nairovirus associated with acute febrile illness in Hokkaido, Japan. Nat Commun. 2021;12(1):5539. Epub 2021/09/22. pmid:34545081; PubMed Central PMCID: PMC8452618.
- 51. Lindquist L, Vapalahti O. Tick-borne encephalitis. Lancet. 2008;371(9627):1861–71. Epub 2008/06/03. pmid:18514730.
- 52. Wang ZD, Wang B, Wei F, Han SZ, Zhang L, Yang ZT, et al. A New Segmented Virus Associated with Human Febrile Illness in China. N Engl J Med. 2019;380(22):2116–25. Epub 2019/05/30. pmid:31141633.
- 53. Wang YC, Wei Z, Lv X, Han S, Wang Z, Fan C, et al. A new nairo-like virus associated with human febrile illness in China. Emerging microbes & infections. 2021;10(1):1200–8. Epub 2021/05/29. pmid:34044749; PubMed Central PMCID: PMC8212832.
- 54. Kong Y, Zhang G, Jiang L, Wang P, Zhang S, Zheng X, et al. Metatranscriptomics Reveals the Diversity of the Tick Virome in Northwest China. Microbiology spectrum. 2022;10(5):e0111522. Epub 2022/10/11. pmid:36214702; PubMed Central PMCID: PMC9602664.
- 55. Wang ZD, Wang W, Wang NN, Qiu K, Zhang X, Tana G, et al. Prevalence of the emerging novel Alongshan virus infection in sheep and cattle in Inner Mongolia, northeastern China. Parasit Vectors. 2019;12(1):450. Epub 2019/09/13. pmid:31511049; PubMed Central PMCID: PMC6740026.
- 56. Xing Y, Schmitt HJ, Arguedas A, Yang J. Tick-borne encephalitis in China: A review of epidemiology and vaccines. Vaccine. 2017;35(9):1227–37. Epub 2017/02/06. pmid:28153343.
- 57. Uckeley ZM, Koch J, Tischler ND, Léger P, Lozach PY. [Cell biology of phlebovirus entry]. Virologie (Montrouge). 2019;23(3):176–87. Epub 2019/06/19. pmid:31210134.
- 58. Wang YN, Jiang RR, Ding H, Zhang XL, Wang N, Zhang YF, et al. First Detection of Mukawa Virus in Ixodes persulcatus and Haemaphysalis concinna in China. Front Microbiol. 2022;13:791563. Epub 2022/03/22. pmid:35308357; PubMed Central PMCID: PMC8930188.
- 59. Jia N, Wang J, Shi W, Du L, Sun Y, Zhan W, et al. Large-Scale Comparative Analyses of Tick Genomes Elucidate Their Genetic Diversity and Vector Capacities. Cell. 2020;182(5):1328–40.e13. Epub 2020/08/20. pmid:32814014.
- 60. Zhao GP, Wang YX, Fan ZW, Ji Y, Liu MJ, Zhang WH, et al. Mapping ticks and tick-borne pathogens in China. Nature communications. 2021;12(1):1075. Epub 2021/02/19. pmid:33597544; PubMed Central PMCID: PMC7889899.
- 61. Miao D, Dai K, Zhao GP, Li XL, Shi WQ, Zhang JS, et al. Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods. Emerg Microbes Infect. 2020;9(1):817–26. Epub 2020/03/28. pmid:32212956; PubMed Central PMCID: PMC7241453.
- 62. Sulyok M, Richter H, Sulyok Z, Kapitány-Fövény M, Walker MD. Predicting tick-borne encephalitis using Google Trends. Ticks Tick Borne Dis. 2020;11(1):101306. Epub 2019/10/19. pmid:31624027.