Ticks are important vectors and reservoirs of several zoonotic pathogens. Recently, both known and unknown tick-borne pathogens have emerged and re-emerged, causing unpredictable epidemics. In this study, 211 soft tick samples were collected from Tongliao and Alxa in Inner Mongolia, China. Tick species were identified by morphological and molecular biological analyses. Morphological analysis showed that there was no significant difference in surface features between ticks from the 2 areas. Cloning by polymerase chain reaction (PCR) and sequencing of the 16S rRNA gene showed that all ticks belonged to the species Argas persicus. Analysis using Genetyx software indicated that there was a limited degree of diversity between ticks from the 2 areas. Three base changes were detected in the 16S rRNA gene. We constructed phylogenetic trees using MEGA 6.0 software and showed that the ticks from the 2 areas might have evolved independently from species in other geographical areas. To assess the presence of Rickettsia, Streptococcus suis, and Staphylococcus aureus pathogens in tick samples, over 100 16S rRNA sequences belonging to these 3 pathogens were obtained from GenBank. We used CLC Sequence Viewer 7.0 to determine conserved sequences for the design of degenerate primers. Using standard PCR, we detected Rickettsia-specific genes, including 16S rRNA, 17KD, and ompB, in gDNA samples of ticks from Alxa. This study has laid a foundation for future studies on the biodiversity of ticks and for a new pathogen information database of ticks in local areas.

Changes in the global climate and ecology of local areas have led to significant changes in the disease spectrum of domestic animals. For example, new exotic animal diseases are constantly emerging, and diseases that have been effectively controlled for many years are again causing outbreaks (Du et al., 2017; Zhan et al., 2017). Recently, vector insects have gained increasing attention as changes in climate and ecology affect the types, activities, ability to adapt to different ecosystems, and spectrum of insect diseases.

Ticks are some of the most important insect vectors of human and animal diseases and play a critical role in carrying pathogens (Cupp, 1991; Harrison and Bennett, 2012; Lwande et al., 2014; Brackney and Armstrong, 2016; Braga et al., 2016; Nakao et al., 2016; Tahir et al., 2016). Approximately 899 species of ticks belonging to the families Argasidae, Ixodidae, and Nuttalliellidae have been identified to date (Dantastorres et al., 2012). In China, 117 species have been identified belonging to the genera Amblyomma (8 species), Anomalohimalaya (2 species), Argas (7 species), Carios (4 species), Dermacentor (12 species), Haemaphysalis (44 species), Hyalomma (6 species), Ixodes (24 species), Ornithodoros (2 species), and Rhipicephalus (8 species) and to the families Argasidae and Ixodidae (Chen et al., 2010). Approximately 10% of known tick species act as vectors for a wide range of infectious pathogens that affect animals and humans (Jongejan and Uilenberg, 2004). Many studies have been conducted on hard tick-borne diseases such as Lyme disease (McPherson et al., 2017), Q fever (Lu et al., 2013), Colorado tick fever (Kotlyar, 2017), tularemia (Kormilitsyna et al., 2016; Solomon, 2016), tick-borne relapsing fever (Gürcan, 2014), babesiosis (Sivakumar et al., 2014; Jongejan et al., 2018), dengue (Kazimírová et al., 2012), and animal piroplasmosis (Ozubek and Aktas, 2017). Although soft tick-borne pathogens have also been reported around the world (Milhano et al., 2014; Lafri et al., 2015; Pietschmann et al., 2016; Sánchez-Montes et al., 2016; Tahir et al., 2016; Quembo et al., 2017), there have been few reports of pathogens transmitted by soft ticks in China.

With the development of molecular tools that can be applied to the identification of new species and genotypes, and the assessment of tick biodiversity, the number of identified tick-borne pathogens is continually increasing (Dantastorres et al., 2012). In the present study, soft ticks were collected from Tongliao and Alxa in the border regions of Inner Mongolia and identified using morphological and molecular biological techniques. Two new genotypes of Argas persicus were identified in these 2 areas and a Rickettsia-specific gene was detected in gDNA isolated from ticks collected in Alxa. This study lays the foundation for further studies on tick biodiversity and the creation of a new pathogen information database of ticks in local areas of China.

Tick collection

Ticks were collected from cracks in the walls of naturally infested henhouses in the Tongliao (122°17′E, 43°39′N) and Alxa (101°03′E, 41°57′N) regions of Inner Mongolia, China (Fig. 1). Tongliao is a semi-humid region whereas Alxa is a semi-arid or desert zone. In total, 88 and 123 samples of ticks were randomly collected from Tongliao and Alxa, respectively. The tick samples were maintained in a sealed container and used in experiments as soon as possible.

Figure 1.

Location of tick samples. Flags represent sampling points and black dashed lines represent the straight-line distance between 2 points.

Figure 1.

Location of tick samples. Flags represent sampling points and black dashed lines represent the straight-line distance between 2 points.

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Morphological analysis of ticks

Adult ticks were soaked in 70% alcohol to anesthetize them and were then observed under a dissecting microscope (Discovery V20, Zeiss, Göttingen, Germany) for species-level identification based on morphological criteria of adult ticks (Barker and Walker, 2014). The dorsal groove, marginal groove, mouthparts, genital aperture, and anal structure were observed at ×100 magnification.

DNA extraction

The gDNA was extracted from the entire bodies of all adult ticks and purified. Prior to DNA extraction, each sample was washed in 70% alcohol for 1 hr followed by double-distilled water for 1 hr. DNA was extracted from individual ticks according to the procedure described by Marrelli et al. (2007). Individual ticks were frozen and ground in a mortar to a fine powder with liquid nitrogen. The powder was re-suspended in 400 μl of TE buffer (20 mM Tris-HCl, pH 8.0; 1 mM EDTA, pH 7.5; 10 mM NaCl; and 1% SDS) containing 30 μl proteinase K (20 mg/ml). After incubation overnight at 56 C, DNA was extracted by shaking in phenol/chloroform/isoamyl alcohol (25:24:1) and precipitated by adding 2 volumes of ice-cold ethanol for 4−6 hr. After centrifugation (12,000 g for 5 min), the pellet was re-suspended in 50 μl TE buffer. Extracted DNA was used as the template for PCR.

Polymorphism analysis of the 16S rRNA gene of ticks

A portion of the 16S rRNA gene was amplified using the primers 16S PF (forward: 5′-TCTAAAATTAAATCCTTTGAAT-3′) and 16S PR (reverse: 5′-AAGAGCCCAAATTCCATTTTC-3′). PCR was performed in 25-μl volumes containing 0.4 μM of each primer pair, 0.5 U rTaq DNA polymerase (TaKaRa, Dalian, China), 2 mM MgCl2, and 1 μl gDNA template. PCR was performed using the following steps: an initial denaturation at 95 C for 5 min, 35 cycles of denaturation at 95 C for 30 sec, annealing at 55 C for 1 min, and extension at 72 C for 1 min, with a final extension at 72 C for 7 min. A negative control (no DNA template) was included for each PCR. Two gene products from each PCR were examined using 1% (w/v) agarose gel electrophoresis to validate amplification efficiency. Specific PCR products were sequenced, and gene polymorphism analysis was performed using Genetyx version 6 software (Genetyx, Tokyo, Japan). We then randomly selected 4 amplification products of each of the 16S rRNA gene products from each of the 2 species for sequencing. The recombinant vector was sequenced by Sangon Biotechnology Co. Ltd. (Shanghai, China). Polymorphisms in the 16S rRNA genes were compared between the 2 genotypes at the nucleic acid level using Genetyx 6 software (Genetyx). We also compared gene polymorphisms identified in the 2 genotypes with those of the domestic strain A. persicus XJ, ID:KR297208.1 and the foreign strain A. persicus Romania, ID:FN394341.1.

Construction of phylogenetic trees

The 16S rRNA genes of soft ticks from Tongliao and Alxa were clustered with the 16S rRNA genes of other Argasidae family members listed in the GenBank database (https://www.ncbi.nlm.nih.gov/genbank/). Sequence homology was assessed using the Clustal X program in MEGA 6.0 software (Tamura et al., 2013). Phylogenetic trees were constructed using the maximum likelihood (ML) method. Branch supports were calculated using bootstrap analysis with 1,000 ML replicates. Phylogenetic trees were also constructed for the 16S rRNA genes of pathogens detected in ticks using similar methods.

Detection of pathogens in ticks

The 16S rRNA genes of 3 pathogens were used as targets. In total, 104 gene sequences were obtained from GenBank. We designed 2 pairs of degenerate primers to recognize conserved sequences using CLC Sequence Viewer 7.0.2 (http://www.clcbio.com). Pathogens belonging to the genus Rickettsia were identified using the primers PFr (forward: 5′-CTACGGGARGCAGCAG-3′, R=A/G) and PRr (reverse: 5′-GTTTACGGCGTGGACT-3′). Streptococcus suis and Staphylococcus aureus were identified using the primers PFs (forward: 5′-GGCTCAGGAKGAACGC-3′, K=G/T) and PRs (reverse: 5′-GGAGTCTGGRCCGTGT-3′, R=A/G). The PCR procedure described above was used for pathogen detection. Each PCR product was sequenced by Sangon Biotechnology Co. Ltd. Information regarding primers and target pathogen genes is listed in Table I.

Table I

Degenerate primers and sources for PCR detection of 16S rRNA microbial genes in Rickettsia, Streptococcus suis, and Staphylococcus aureus.

Degenerate primers and sources for PCR detection of 16S rRNA microbial genes in Rickettsia, Streptococcus suis, and Staphylococcus aureus.
Degenerate primers and sources for PCR detection of 16S rRNA microbial genes in Rickettsia, Streptococcus suis, and Staphylococcus aureus.

Detection of ompB- and 17KD-specific genes of Rickettsiae

We selected the specific genes ompB and 17KD to further confirm the reliability of Rickettsia detection in ticks. The primer pairs PFompB (forward: 5′-CCgCAgggTTggTAACTgC-3′) and PRompB (reverse: 5′-TCgCCggTAATTRTAgCAT-3′), and PF17kDa (forward: 5′-gCTCTTgCAgCTTCTATgTTACA-3′) and PR17kDa (reverse: 5′-ACTTgCCATTgTCCgTCAggTTg-3′), were used to detect Rickettsia-specific genes in gDNA samples of ticks (Table II) using the procedure described above. The PCR products were then sequenced. Phylogenetic trees of the 2 genes were also created using MEGA 6.0 software.

Table II

Primer pairs used for amplification of Rickettsia genes.

Primer pairs used for amplification of Rickettsia genes.
Primer pairs used for amplification of Rickettsia genes.

Morphological observations

The morphological characteristics of the soft ticks collected were consistent with the description of A. persicus (Pantaleoni et al., 2010). Ticks were flat with a sharp lateral margin and had a lateral suture at the body margin marked by ridges radiating outward. The basis capituli could not be seen from the rear, as it sagged into the abdomen. Ticks had a central toothed hypostome and a pair of palps. The anus was visible as an oval structure and there was no anal groove structure near the anus. The female genital aperture was observed as a broad horizontal slit (Figs. 2, 3).

Figure 2.

Results of morphological observation of Argas persicus TL (white pointed tip). (A) Dorsal view (female), (B) ventral view (female), (C) dorsal view (male), (D) ventral view (male), (E) mouthpart, (F) anus, (G) genital aperture. Color version available online.

Figure 2.

Results of morphological observation of Argas persicus TL (white pointed tip). (A) Dorsal view (female), (B) ventral view (female), (C) dorsal view (male), (D) ventral view (male), (E) mouthpart, (F) anus, (G) genital aperture. Color version available online.

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Figure 3.

Results of morphological observation of A. persicus ALX (black pointed tip). (A) Dorsal view (female), (B) ventral view (female), (C) dorsal view (male)., (D) ventral view (male), (E) mouthpart, (F) anus, (G) genital aperture. Color version available online.

Figure 3.

Results of morphological observation of A. persicus ALX (black pointed tip). (A) Dorsal view (female), (B) ventral view (female), (C) dorsal view (male)., (D) ventral view (male), (E) mouthpart, (F) anus, (G) genital aperture. Color version available online.

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16S rRNA gene sequences and polymorphism analysis

The length of the 16S rRNA gene PCR products was 366 base pairs (bp), which is consistent with theoretically expected values. The sequencing results suggested that there was >99% homology between the target genes and the reference sequence of A. persicus. Thus, the 2 genotypes were identified as A. persicus TL and A. persicus ALX (16S rRNA gene registration numbers in GenBank: LC209197.1 and LC209198.1, respectively).

Interestingly, Genetyx software analysis of polymorphisms at the nucleic acid level revealed 3 base changes in the 16S rRNA gene sequences of the A. persicus TL and A. persicus ALX genotypes including C to T transitions at 2 sites and a G to A transition at 1 site. Other genetic differences between the 2 genotypes and other reference sequences from GenBank were also identified (Fig. 4). Results of the polymorphism analysis are shown in Table III.

Figure 4.

Diversity of the 16S RNA gene among multiple soft tick genotypes. The box indicated by the black dotted line indicates nucleotide sequence differences between the 2 genotypes.

Figure 4.

Diversity of the 16S RNA gene among multiple soft tick genotypes. The box indicated by the black dotted line indicates nucleotide sequence differences between the 2 genotypes.

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Table III

Summary statistics for sequenced 16S rRNA gene fragments from 5 strain of Argas persicus.

Summary statistics for sequenced 16S rRNA gene fragments from 5 strain of Argas persicus.
Summary statistics for sequenced 16S rRNA gene fragments from 5 strain of Argas persicus.

Phylogenetic tree analysis of ticks

A phylogenetic tree was constructed using the 16S rRNA genes of the 2 genotypes from our study and 23 reference genotypes. We found that the 2 genotypes from our study were located adjacent to Xinjiang genotypes but distant from South African genotypes, indicating that the 2 genotypes may have evolved independently from species in other areas (Fig. 5).

Figure 5.

Phylogenetic tree of soft ticks. Based on the 16S rRNA gene sequence, soft ticks were divided into 2 main branches, Argas (I) and Ornithodoros (II), which were further subdivided into 6 sub-branches, I-1 to I-6. The box indicated by the black dashed line indicates the 2 genotypes from this study, which were classified as sub-branch I-5. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site.

Figure 5.

Phylogenetic tree of soft ticks. Based on the 16S rRNA gene sequence, soft ticks were divided into 2 main branches, Argas (I) and Ornithodoros (II), which were further subdivided into 6 sub-branches, I-1 to I-6. The box indicated by the black dashed line indicates the 2 genotypes from this study, which were classified as sub-branch I-5. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site.

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Pathogens detected in tick samples

Neither Streptococcus suis- nor Staphylococcus aureus-specific genes were detected in any tick sample from either area. However, Rickettsia-specific genes were detected in the gDNA of ticks from Alxa. According to the phylogenetic tree of the Rickettsia 16S rRNA gene, we found that members of the genus Rickettsia identified in the ticks were most similar to Rickettsia helvetica (L36212.1) (Fig. 6). Lengths of the 17KD and ompB PCR products were 440 bp and 1,540 bp, respectively. The 17KD gene of Rickettsia in A. persicus ALX was closely related to that of Rickettsia prowazekii (CP004888.A) (Fig. 7), and the ompB gene was closely related to that of Rickettsia hoogstraalii (EF629536.1) (Fig. 8).

Figure 6.

Phylogenetic tree of the 16S RNA gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site. Legend: ▪ Rickettsia isolate from tick.

Figure 6.

Phylogenetic tree of the 16S RNA gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site. Legend: ▪ Rickettsia isolate from tick.

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Figure 7.

Phylogenetic tree of the 17KD gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site. Legend: ▪ Rickettsia isolate from tick.

Figure 7.

Phylogenetic tree of the 17KD gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number of substitutions per site. Legend: ▪ Rickettsia isolate from tick.

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Figure 8.

Phylogenetic tree of the ompB gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number substitutions per site. Legend: ▪ Rickettsia isolate from tick.

Figure 8.

Phylogenetic tree of the ompB gene of Rickettsia. The phylogenetic tree constructed by maximum likelihood methods. Bootstrap percentages are given in the nodes (number of bootstrap replicates: 1,000). The branch length represents the number substitutions per site. Legend: ▪ Rickettsia isolate from tick.

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Although Argas spp. have been reported in Alxa based on morphological analyses, we found no relevant literature demonstrating their presence in this area. In Tongliao, local residents have reported that Argas spp. have recently begun to affect humans; however, this has not been accompanied by any written reports. Therefore, the current study is the first report of the presence of 2 A. persicus genotypes in Inner Mongolia, China.

We compared the morphology of the 2 collected genotypes and showed that, with the exception of body color, their surface features were similar. The reason for the difference in color may be related to the different sampling methods used. Argas persicus TL ticks were killed by direct immersion in 70% alcohol before transfer to the laboratory, for safety considerations, causing their bodies to shrivel and their color to diminish. In contrast, A. persicus ALX ticks were transported to the laboratory live in a ventilated container and disinfected with 70% alcohol after their arrival; therefore, their body surfaces were fresh, 4 of their legs were stretched, and their body color was bright. The morphological structures of the 2 genotypes of ticks, including the mouthparts, genital aperture, and anus, were intact, which is consistent with the typical characteristics of soft ticks (Barker and Walker, 2014; Muñoz-Leal et al., 2016).

To assess conserved genetic sequences, we successfully sequenced the 16S rRNA gene of the 2 tick genotypes. We found that ticks from the same area had similar genetic sequences. However, we did observe a few differences at the nucleotide level between ticks from Alxa and Tongliao. This is likely due to the fact that the 2 sampling sites are approximately 2,000 km apart and have significantly different geographical and climate characteristics. These finding are similar to the results of Livanova et al. (2016), who found low levels of biodiversity in different tick species from Russia, Siberia, and Kazakhstan. One possible explanation for the low number of polymorphisms is that tick genotypes might be transported between areas, such as during the transportation of breeding hens or the migration of parasitized wild birds, and so the genotypes might have been native to the different locations. However, the genetic sequences that we obtained were all partial sequences; therefore, it is difficult to know whether other differences exist between the genetic sequences of the 2 genotypes.

We also compared gene polymorphisms of the 2 genotypes with A. persicus sequences from GenBank to identify polymorphisms that might be influenced by environmental factors or individual differences between tick genotypes. We observed distinct polymorphisms in the 16S rRNA gene between the 2 genotypes from our study and other Chinese genotypes (e.g., A. persicus XJ, ID:KR297208.1).

For phylogenetic trees, all branches, except the 2 major branches of Argas and Ornithodoros, were previously known. To display the evolutionary relationship between soft ticks, we divided branch I of Argas into 6 sub-branches according to the following laws of evolution (with the exception of some independent branches such as No. 10): I-1, I-2, I-3, I-4, I-5, and I-6. Our results show that A. persicus TL and A. persicus ALX may have evolved independently from other species, as they are classified to sub-branch I-5. The Xinjiang strain (A. persicus XJ) was adjacent to the above 2 genotypes but the evolutionary distance was not close. In addition, A. persicus XJ was closer to other foreign genotypes. Consequently, we suggest that A. persicus TL and A. persicus ALX tick species are native to local areas of China.

We assessed the presence of the pathogens Rickettsia, S. suis, and S. aureus in gDNA samples from all ticks collected using degenerate primers. A Rickettsia-specific gene was detected using standard PCR methods. However, no S. suis- or S. aureus-specific gene was detected. To date, neither S. suis nor S. aureus have been reported to be tick-borne diseases. However, outbreaks of their corresponding diseases usually occur in the same area and season as frequent tick activity. We suspected that these pathogens might be linked to ticks, so we assessed their presence in tick samples. However, our findings support the conclusion that there is no correlation between S. suis or S. aureus and ticks. Because Rickettsia-specific 16S rRNA was identified, we also assessed the presence of 2 other Rickettsia-specific genes described in the literature (Jiang et al., 2013). Phylogenetic trees of 16S rRNA, ompB, and 17KD genes in Rickettsia are not consistent. The 16S rRNA is the more-conserved gene and is frequently used in taxonomic analyses (Barker and Murrell, 2004; Lu et al., 2013) whereas ompB and 17KD are used for detecting Rickettsia-specific genes in gDNA samples of ticks. All above-mentioned results further confirmed the existence of Rickettsia in A. persicus ALX.

In conclusion, we identified 2 genotypes of A. persicus ticks, which we named A. persicus TL and A. persicus ALX, using morphological and molecular biological methods. Genes from these 2 genotypes have been registered in GenBank as LC209197 and LC209198, respectively. We also described for the first time a Rickettsia-specific gene detected in gDNA isolated from A. persicus ALX. To our knowledge, this is the first report of 2 new A. persicus genotypes in Inner Mongolia, China. Our findings suggest that A. persicus could carry pathogens and potentially spread tick-related diseases in animal populations.

This work was supported by the National Project for Prevention and Control of Transboundary Animal Diseases (Grant No. 2017YFD0501800), which is the National Key R&D Program for the 13th Five-Year Plan of the Ministry of Science and Technology, the National Natural Science Foundation of China (Grant No. 31660709), China, and the Inner Mongolia Autonomous Region Science and Technology Innovation Guide Incentive Funds project. We thank International Science Editing (http://www.internationalscienceediting.com) for editing this manuscript.

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Author notes

*

These authors contributed equally to this work.