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Zoonotic pathogens identified in rodents and shrews from four provinces, China, 2015–2022

Published online by Cambridge University Press:  07 September 2023

Shen Tian
Affiliation:
Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China Guangzhou Center for Disease Control and Prevention, Guangzhou, P.R. China Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Bao-Gui Jiang
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Wan-Shuang Liu
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Hao-Rong Chen
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Zi-Hou Gao
Affiliation:
Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
En-Nian Pu
Affiliation:
Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
Yu-Qiong Li
Affiliation:
Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
Jin-Jin Chen
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Li-Qun Fang
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Guo-Lin Wang
Affiliation:
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
Chun-Hong Du
Affiliation:
Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
Yue-Hong Wei*
Affiliation:
Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China Guangzhou Center for Disease Control and Prevention, Guangzhou, P.R. China Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China
*
Corresponding author: Yue-Hong Wei; Email: [email protected]
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Abstract

Rodents and shrews are major reservoirs of various pathogens that are related to zoonotic infectious diseases. The purpose of this study was to investigate co-infections of zoonotic pathogens in rodents and shrews trapped in four provinces of China. We sampled different rodent and shrew communities within and around human settlements in four provinces of China and characterised several important zoonotic viral, bacterial, and parasitic pathogens by PCR methods and phylogenetic analysis. A total of 864 rodents and shrews belonging to 24 and 13 species from RODENTIA and EULIPOTYPHLA orders were captured, respectively. For viral pathogens, two species of hantavirus (Hantaan orthohantavirus and Caobang orthohantavirus) were identified in 3.47% of rodents and shrews. The overall prevalence of Bartonella spp., Anaplasmataceae, Babesia spp., Leptospira spp., Spotted fever group Rickettsiae, Borrelia spp., and Coxiella burnetii were 31.25%, 8.91%, 4.17%, 3.94%, 3.59%, 3.47%, and 0.58%, respectively. Furthermore, the highest co-infection status of three pathogens was observed among Bartonella spp., Leptospira spp., and Anaplasmataceae with a co-infection rate of 0.46%. Our results suggested that species distribution and co-infections of zoonotic pathogens were prevalent in rodents and shrews, highlighting the necessity of active surveillance for zoonotic pathogens in wild mammals in wider regions.

Type
Original Paper
Creative Commons
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

Emerging infectious diseases (EIDs) are a serious challenge to public health and economic development in the world. Over 70% of zoonotic EID events originate in wild animals [Reference Jones, Patel, Levy, Storeygard, Balk, Gittleman and Daszak1]. Rodents and shrews live in close contact with humans and act as a bond among humans, domestic animals, and arthropod vectors [Reference Meerburg, Singleton and Kijlstra2]. As two common types of wild mammals, they are recognised as reservoir hosts for many zoonotic pathogens, for example, Anaplasma, Babesia, spotted fever group Rickettsiae (SFGR), Borrelia, and hantavirus [Reference Jonsson, Figueiredo and Vapalahti3, Reference Gu, Su, Zhou, Fang, Zhu, Ma, Jiang, Li, Li, Duan, Peng, Wang, Jiang, Han and Yu4]. What is more, about 10% of the 2,277 living rodent species are hosts for 66 zoonotic pathogens, including viruses, bacteria, fungi, worms, and protozoans [Reference Dahmana, Granjon, Diagne, Davoust, Fenollar and Mediannikov5]. However, the links between these pathogens are still rarely investigated. Thus, a comprehensive understanding of zoonotic pathogens prevalence in rodents and shrews, as well as the geographical distribution and co-infection status, will be valuable for preventing and controlling wildlife-origin EIDs.

China is a megadiversity country and harbours various rodents and shrews. The rodents and shrews belong to the RODENTIA and EULIPOTYPHLA orders, and there are 235 species of 12 families and 92 species of 3 families in the RODENTIA and EULIPOTYPHLA orders in China, respectively [Reference Chen, Xu, Wang, Meng, Li, Fang and Liu6]. Rodents and shrews can transmit zoonotic pathogens to human directly when humans consume food, water, or air that is contaminated with faeces and bodies [Reference Avšič-Županc, Saksida and Korva7] or indirectly when humans are bitten by arthropod vectors [Reference Che, Jiang, Xu, Zhang, Lv, Chen, Tian, Yang, Hay, Liu and Fang8Reference Yang, Liu, Guan, Liu, Li, Chen, Ma, Liu, Ren, Luo and Yin13]. Especially, China is the most severe endemic country of haemorrhagic fever with renal syndrome caused by hantaviruses, with 20,000–50,000 human cases reported annually in China [Reference Fang, Yan, Liang, de Vlas, Feng, Han, Zhao, Xu, Bian, Yang, Gong, Richardus and Cao14]. Most of the previous studies only focus on one or a few pathogens in rodents and shrews, and the source areas of samples are limited [Reference Yu, Xie, Bi, Zuo, Du, Bi, Li and Rao15Reference Chen, Ye, Fan, Li, Tang, Liu, Ren and Bai18]. In this study, we screened representative zoonotic pathogens in a great variety of rodents and shrews from four provinces in China to identify the prevalence and co-infection of zoonotic pathogens.

Materials and methods

Sample collection

All animals were trapped in mist nets or harp traps using fried foods as bait at night between June 2015 and January 2022, and they were kept alive after being captured. A total of 864 wild rodents and shrews were captured in Guangdong, Henan, Inner Mongolia, and Yunnan provinces in China. The species of rodents and shrews were initially identified by experienced field biologists and then confirmed by sequencing of mitochondrial cytochrome b gene [Reference Zhang, Song, Xiu, Liu, Yang, Yao and Peng19]. All animals were anesthetised with ether before they were executed, and all efforts were made to minimise the pain. Within 12 hours of placement of the capture tool, the captured animals were killed at the site of cervical dislocation. The heart, liver, spleen, lung, and kidney samples of each animal were collected and stored at liquid nitrogen until further use.

Nucleic acid extraction

The samples for further nucleic acid extraction were prepared by mixing equal amounts of tissues from five different organs, including heart, liver, spleen, lung, and kidney. And then the nucleic acid of each animal was extracted using AllPrep DNA/RNA Mini Kit (Qiagen, Cat. No. 80204, Hilden, Germany) according to the manufacturer’s instructions. All DNA/RNA samples were stored at −80°C until use.

Hantavirus screening

The oligonucleotide primers used for nested reverse transcription-polymerase chain reaction (RT-PCR) and polymerase chain reaction (PCR) product sizes are shown in Supplementary Table S1 [Reference Klempa, Fichet-Calvet, Lecompte, Auste, Aniskin, Meisel, Denys, Koivogui, ter Meulen and Krüger20]. The second (nested) PCR was performed using the same reaction solution as the first PCR, and the first PCR product used as the template for the second PCR. Positive and negative controls were included in each PCR run. The first PCR was performed in a total volume of 25 μL, including 1 μL of PrimeScript One-Step Enzyme Mix, 12.5 μL of 2X One-Step Buffer (Dye Plus) (Takara, Cat. No. 057A, Maebashi, Japan), 1 μL of LF-1 forward primer and 1 μL of LR-1 reverse primer, 2 μL RNA, and 7.5 μL dH2O. The first amplification of PCR products consisted of 38 cycles (30 s at 94°C, 30 s at 54°C, and 45 s at 72sC) was performed using PCR System 9700 (Applied Biosystems, San Francisco, CA). Then, the 2 μL DNA product amplified by the first PCR was used as the template, and the forward (LF-2) and reverse (LR-2) primers were used for PCR detection under similar amplification conditions [Reference Klempa, Fichet-Calvet, Lecompte, Auste, Aniskin, Meisel, Denys, Koivogui, ter Meulen and Krüger20].

Bacterial and parasitic pathogens screening

The amplification conditions and primers of PCR used in this study can be found in Supplementary Table S1 [Reference Zhuang, Du, Cui, Li, Tang, Zhang, Hu, Tong, Feng and Liu21Reference Tayebwa, Tuvshintulga, Guswanto, Nugraha, El-Saber Batiha, Gantuya, Rizk, Vudriko, Sivakumar, Yokoyama and Igarashi27]. For the nested PCR assays, both the first and second reactions were run to a final volume of 25 μL, including 12.5 μL of DreamTaq Green PCR Master Mix (2X) (Thermo Fisher Scientific, Waltham, MA), 0.5 μL of 2 μM forward and reverse primers (Sangon Biotech, Shanghai, China), 9.5 μL RNase-free ddH2O, and 2 μL of genomic DNA sample for the first PCR or 2 μL of the first PCR product for the second PCR. Positive and negative controls were run alongside the samples in each assay to eliminate the interference of false negative and false positive.

Sequencing and phylogenetic analysis

The amplified products were first detected by 1.5% agarose gel electrophoresis and then sequenced by the Sanger method. The sequences were assembled by CLC Genomics Workbench 3, and the low-signal sequences at both ends were discarded and entered into NCBI for homology search by BLAST. The multiple alignments were done by the MAFFT version 7 programme with default parameters. Relationships between individuals were assessed using a maximum-likelihood method with nucleotide distance with 1,000 replications for a bootstrap test. The phylogenetic trees of nucleotide sequences (547-bp L segment of hantavirus (GTR + G + I), 210-bp ITS gene of Bartonella spp. (HKY + G), 280-bp 16S rRNA gene of Anaplasmataceae (K2 + G), 153-bp 18S rRNA gene of Babesia spp. (HKY + G), 1,230-bp 16S rRNA gene of Leptospira spp.(K2 + G + I), 347-bp OmpA gene of SFGR (T92 + G), 347-bp 16S rRNA gene of Borrelia spp.(K2 + G), and 710-bp 16S rRNA gene of Coxiella burnetii (HKY + G + I)) were constructed using the MEGA X software.

Statistical analysis

The chi-square or Fisher’s exact test was used for the prevalence comparison of the zoonotic pathogens among the different geographic region. Statistical analyses were performed by R software (version 3.5.3). All statistical tests were two-tailed, and P-value of lower than 0.05 was considered significant.

Result

Sample collection and species identification

From June 2015 to January 2022, a total of 864 wild small mammals, including rodents and shrews, were captured in Guangdong, Henan, Inner Mongolia, and Yunnan provinces in China (Figure 1). Species identification showed that these captured animals included 24 species of Cricetidae, Muidae, Sciuridae, and Spalacidae families from the RODENTIA order, and 13 species of Erinaceidae, Soricidae, and Talpidae families of the EULIPOTYPHLA order. Regarding the sampling provinces, we found that the most abundant species of rodents and shrews were collected from Yunnan province (27 species), followed by Henan (8), Guangdong (5), and Inner Mongolia (4) (Figure 1 and Table 1).

Figure 1. Geographical distribution of rodents and shrews in four provinces of China. From June 2015 to January 2022, small wild animals were collected in different parts of China. The total number of small wild animals and the proportion at the level of family collected from each region were shown.

Prevalence and distribution of zoonotic pathogens in rodents and shrews

All 864 small mammals from 37 species were screened for eight different zoonotic pathogens. All eight zoonotic pathogens can be detected in Henan province, whereas Leptospira spp. and C. burnetii were not found in Guangdong, Yunnan, and Inner Mongolia provinces (Figure 2 and Table 1). In detail, we found that 30 (3.47%) samples from rodents and shrews were positive for hantavirus. The overall number and prevalence of Bartonella spp., Anaplasmataceae, Babesia spp., Leptospira spp., SFGR., Borrelia spp. and C. burnetii were 270 (31.25%), 77 (8.91%), 36 (4.17%), 34 (3.94%), 31 (3.59%), 30 (3.47%), and 5 (0.58%), respectively. The zoonotic pathogens were detected from 33 species (89.2%), including 22 species (91.7%) of the RODENTIA order and 10 species (76.9%) of the EULIPOTYPHLA order.

Figure 2. The carrying status of eight pathogens in rodents and shrews from four provinces.

The distribution of the zoonotic pathogens in different species and provinces can be found in Table 1. Hantavirus were detected in eight (8/37, 21.62%) species, including six species of the RODENTIA order and two species of the EULIPOTYPHLA order. The statistical analysis demonstrated that no significant difference of hantavirus prevalence was found between samples from EULIPOTYPHLA and RODENTIA (Supplementary Table S3). The number of positive results against hantavirus was mostly detected in Rattus tanezumi (10 animals), Anourosorex squamipes (6), and Apodemus chevrieri (5), respectively. Yunnan province had the highest prevalence of 90% (27/30) for hantavirus.

Table 1. Detection rate of rodent species with different pathogens in Henan, Guangdong, Inner Mongolia, and Yunnan from 2015 to 2022

Bartonella spp. was detected from 28 (28/37, 75.68%) species, including 20 species of the RODENTIA order and 8 species of the EULIPOTYPHLA order. The number of positive results against Bartonella spp. was mostly detected in R. tanezumi (51 animals), Suncus murinus (46), and Apodemus ilex (35), respectively. Yunnan province had the highest prevalence of 46.30% (125/270) for Bartonella spp. (Table 1). The prevalence of Bartonella spp. was significantly higher in samples from RODENTIA than those from EULIPOTYPHLA (Supplementary Table S3).

Anaplasmataceae was found from 14 (14/37, 37.8%) species, including 12 species of the RODENTIA order and 2 species of the EULIPOTYPHLA order. Anaplasmataceae was mostly detected in A. ilex (26 animals) and R. tanezumi (17), respectively. Yunnan province had the highest prevalence of 53.25% (41/77) for Anaplasmataceae (Table 1). No significant prevalence of Anaplasmataceae was observed in samples from EULIPOTYPHLA and RODENTIA (Supplementary Table S3).

Babesia spp. was found from eight (8/37, 21.62%) species, including six species of the RODENTIA order, two species of the EULIPOTYPHLA order. Babesia spp. was mostly found in A. ilex (19 animals) and R. tanezumi (11), respectively. All the positive samples against Babesia spp. were collected from Yunnan province, with the prevalence of 86.11% (31/36) (Table 1). There was no significant difference of Babesia spp. prevalence in samples between EULIPOTYPHLA and RODENTIA (Supplementary Table S3). Leptospira spp. was only found from four (4/37, 10.8%) species of the RODENTIA order. The number of positive results against Leptospira spp. was mostly detected in Apodemus agrarius (14 animals) and R. tanezumi (13), respectively. All the positive samples against Leptospira spp. were collected from Henan province (Table 1 and Supplementary Table S3).

Borrelia spp. was found from 10 (10/37, 27%) species, including 8 species of the RODENTIA order and 2 species of the EULIPOTYPHLA order. Borrelia spp. was mostly detected in R. tanezumi (eight animals) and S. murinus (seven animals). Henan province had the highest prevalence of 45.16% (14/31) for Borrelia spp. (Table 1).

SFGR was only found from six (16.2%) species of the RODENTIA order and was mostly detected in R. tanezumi (19 animals). Henan province had the highest positive rate of 7.25% (29/400) for SFGR (Table 1).

C. burnetii was only found from four (10.8%) species of the RODENTIA order and was mostly detected in R. tanezumi (two animals). All the positive samples against C. burnetii were collected from Henan province (Table 1).

Co-infection status

A total of 127 samples (14.70%) possessed more than one zoonotic pathogen. And, two, three, four, and five different pathogens were found in 127, 24, 5, and 1 samples. Statistical analysis of all samples revealed that the highest co-infection status among three pathogens was Bartonella spp., Leptospira spp., and Anaplasmataceae with co-infection rate of 0.46%, and the top three co-infections with two zoonotic pathogens were Bartonella spp.–Anaplasmataceae (3.36%), Anaplasmataceae–Babesia spp. (2.08%), and Bartonella spp.–Leptospira spp. (1.50%). SC-21-14 (Niviventer confucianus, Henan) was co-infected with five pathogens at the same time. Relatively low co-infection rate was observed among other pathogens (Figure 3).

Figure 3. Co-infection between pathogens. The size of the circle represents the number of infections, and the thickness of the line represents the number of samples in which co-infections were present.

Phylogenetic analysis

Hantavirus

Phylogenetic analysis of the partial L gene showed that the hantavirus identified in the study formed into two distinct lineages with nucleotide identities of 71.4%–85.7% (Figure 4A). Seven strains in our study shared high sequence similarity and were closely related to the Caobang orthohantavirus found in Vietnam, in 2006, with 85.7% nucleotide identities and other six strains shared high sequence similarity and were closely related to the Hantaan orthohantavirus identified in China, in 2006, with 99.2%–99.7% nucleotide identities.

Figure 4. Rodents detect phylogenetic trees of pathogens. Phylogenetic trees based on the sequence of this study and the known species of this pathogen. The sequences obtained in this study are marked in red. (A) Hantavirus L segment. (B) Bartonella spp. ITS gene. (C) Anaplasmataceae 16S rRNA. (D) Babesia spp. 18S rRNA. (E) Leptospira spp. 16S rRNA. (F) SFGR OmpA gene. (G) Borrelia spp. 16S rRNA. (H) Coxiella burnetii 16S rRNA. The maximum likelihood tree was constructed under the best model, which was selected based on the BIC scores. Phylogenetic tree construction based on the MAGE X software. The link between the host and the detection of the pathogens.

Bartonella spp.

Phylogenetic analysis of the partial ITS gene showed that the Bartonella spp. identified in the study formed into four distinct lineages with nucleotide identities of 47%–92.5% (Figure 4B). Nine strains shared high sequence similarity and were closely related to the Candidatus Bartonella thailandensis identified in Thailand, with 58.8%–91.5% nucleotide identities. YunL-39B (Niviventer andersoni, Yunnan) was closely related to the Bartonella callosciuri identified in Thailand, with 95.5% nucleotide identity. TC-19 (R. tanezumi, Yunnan) and YL-60A (A. chevrieri, Yunnan) were closely related to the Bartonella silvatica found in Japan, with 84.4%–92.5% nucleotide identities. 118A (A. chevrieri, Yunnan) was closely related to the Bartonella japonica identified in Japan, with 97.8% nucleotide identity. SC-21-123 (R. tanezumi, Henan) was closely related to the Bartonella coopersplainsensis found in Australian, with 100% nucleotide identity. TC-37 (R. tanezumi, Yunnan) was closely related to the Bartonella elizabethae, with 99.5% nucleotide identity.

Anaplasmataceae

Phylogenetic analysis of the partial 16S rRNA gene showed that the Anaplasmataceae identified in the study formed into three distinct lineages with nucleotide identities of 92.2%–95.4% (Figure 4C). Seven strains shared high sequence similarity and were closely related to the Anaplasma sp. identified in China, with 98.5%–100% nucleotide identities. Another seven strains were closely related to the Ehrlichia minasensis identified in Egypt, with 100% nucleotide identity, and four strains were closely related to the Ehrlichia sp. identified in China, with 100% nucleotide identity. In addition, four strains shared high sequence similarity and were closely related to the Candidatus Neoehrlichia mikurensis identified in China, with 98.5%–100% nucleotide identities.

Babesia spp.

Phylogenetic analysis of the partial 18S rRNA gene showed that the Babesia spp. identified in the study formed into two distinct lineages with nucleotide identities of 90.1%–91.6% (Figure 4D). Three strains were closely related to the Babesia felis identified in Romania, with 100% nucleotide identity, and another three strains shared high sequence similarity and were closely related to the Babesia microti found in Japan, with 97.4%–98.1% nucleotide identities.

Leptospira spp.

Phylogenetic analysis of the partial 16S rRNA gene showed that all Leptospira spp. identified in the study clustered into the same lineage and were closely related to the Leptospira interrogans identified in the Federation of Saint Kitts and Nevis, with 98.5%–100% nucleotide identities (Figure 4E).

Spotted fever group Rickettsiae

Phylogenetic analysis of the OmpA gene showed that the SFGR identified in the study formed into two distinct lineages with nucleotide identities of 91.7%–93.8% (Figure 4F). Five strains shared high sequence similarity and were closely related to the Rickettsia raoultii found in Russia, with 98.4%–100% nucleotide identities, and four strains shared high sequence similarity and were closely related to the Rickettsia heilongjiangensis identified in Russia, with 99.5%–100% nucleotide identities.

Borrelia spp.

Phylogenetic analysis of the partial 16S rRNA gene showed that the Borrelia spp. identified in the study formed into two distinct lineages with nucleotide identities of 92.2%–97% (Figure 4G). Four strains shared high sequence similarity and were closely related to the Borrelia spp. identified in Australia, with 99.2%–100% nucleotide identities. The nucleotide homology of the remaining two JP-14 (A. squamipes, Yunnan) and Yunl-26 (A. ilex, Yunnan) with Borrelia miyamotoi found in Japan was 97.9% and 98.3%, respectively. SG21-1 (Rattus andamanensis, Guangdong) was closely related to the Borrelia yangtzensis found in Japan, with 98.3% nucleotide identity.

Coxiella burnetii

Phylogenetic analysis of the partial 16S rRNA gene showed that all C. burnetii identified in the study clustered into the same lineage and were closely related to the C. burnetii identified in Indonesia, in 2017, with 99.4% nucleotide identity (Figure 4H).

Discussion

Through active surveillance of eight zoonotic pathogens in rodents and shrews from four provinces in China, we found that zoonotic pathogens were ubiquitous in different species and the co-infection rates of zoonotic pathogens in the same samples were relatively high. The types of pathogens carried by samples from four provinces were slightly different. Eight, five, five, and four pathogen species carried by the sample were found in Henan, Inner Mongolia, Yunnan, and Guangdong, respectively. The highest positive results of hantavirus, Anaplasmataceae, Bartonella spp., and Babesia spp. were observed in Yunnan province, whereas Henan province had the most positive sample number against Borrelia spp., C. burnetii, Leptospira spp., and SFGR. Therefore, specific zoonotic pathogens surveillance should be conducted in different regions.

In recent decades, hantavirus is distributed globally and is mainly endemic in Asia, such as Seoul orthohantavirus and Hantaan orthohantavirus. More common in China are Seoul orthohantavirus and Hantaan orthohantavirus; Caobang orthohantavirus has not been found in mainland China but only in shrews from Taiwan, China [Reference Gu, Arai, Yu, Lim, Kang and Yanagihara28]. Hantavirus has been found in 31 provinces in China, and the number of human cases in Zhejiang, Jiangsu, and other provinces has been on the rise since 2011 [Reference Liu, Zhang, Xie and Xie29Reference Wang, Yue, Yao, Zhu, Ai, Hu, Zhang, Yang, Yang, Luo, Wang, Hou and Tan33]. Our study found that the Caobang orthohantavirus were first identified in A. squamipes of Yunnan province. More importantly, the partial L gene of Caobang orthohantavirus identified in our study were clustered with but distinct from the previous Caobang orthohantavirus identified in Vietnam, with nucleotide identity lower than 90%. However, previous studies showed that the sero-positive rates of haemorrhagic fever with renal syndrome, Anaplasmosis, and Cat Scratch Disease in Yunnan were relatively low compared with those in other provinces [Reference Deng34Reference Fang, Liu, Li, Liang, Yang, Yao, Sun, Sun, Chen, Zuo, Ma, Li, Jiang, Liu, Yang, Gray, Krause and Cao37]. Therefore, we should strengthen the surveillance of zoonotic pathogens in rodent and shrew species, and strengthen the protection of susceptible human groups by publicity, education, and vaccination. Moreover, the first report of Caobang orthohantavirus in A. squamipes in China expanded the currently known geographic scope, host types, and the genetic heterogeneity of Caobang orthohantavirus.

Anaplasmataceae mainly detected in ticks and domestic animals, which can cause an acute, nonspecific febrile illness of humans that named, Human granulocytotropic anaplasmosis [Reference Bakken and Dumler38]. In wild animals, the positive rates of Anaplasmataceae reported in Gansu and Xinjiang provinces were 0.7% and 19.2%, respectively [Reference Yang, Liu, Guan, Liu, Li, Chen, Ma, Liu, Ren, Luo and Yin13, Reference Duan, Lv, Fan, Fu, Mu, Xi, Lu, Chun, Hua, He, Qin, Huang, Xiao, Yang, Jing and Wang39]. Our study showed that the positive rate of Anaplasmataceae from different provinces ranged from 2% to 14.8%.

Bartonella spp. positive samples were mostly identified in Yunnan province, but it was the dominant pathogen in samples from Inner Mongolia. Among all pathogens, Bartonella spp. had the highest positive rate (31.3%). Previous studies reported that the positive rates of Bartonella spp. in wild animals were 8.4%, 14.9%, 26.1%, and 57.7% in east, southeast, northwest, and northeast China, respectively [Reference Yu, Xie, Bi, Zuo, Du, Bi, Li and Rao15, Reference Qin, Liu, Yu and Yu40Reference Li, Hou, Song, Fu, Li, Li, Eremeeva, Wu, Pang, Yue, Huang, Lu, Wang and Liu43]. Consistent with those previous studies, the positive rate of Bartonella spp. from different provinces ranged from 17.8% to 50% in this study.

Between 1986 and 2020, a total of 2,584 confirmed human cases who infected by Borrelia spp. have been reported in 25 provinces of China [Reference Che, Jiang, Xu, Zhang, Lv, Chen, Tian, Yang, Hay, Liu and Fang8]. Erythema migrans are often accompanied by discomfort, fatigue, headache, fever, and local lymph node enlargement when humans are infected by Borrelia spp. In wild animals, two previous studies showed that Borrelia spp. was found in 40.7% and 32% samples collected in Jiangxi province and Tianjin city [Reference Che, Jiang, Xu, Zhang, Lv, Chen, Tian, Yang, Hay, Liu and Fang8]. However, only 3.6% samples in our study were detected positive for Borrelia spp.

Symptoms caused by C. burnetii usually manifest as pulmonary and influenza-like complications [Reference Dragan and Voth44]. A previous study showed that the C. burnetii was only detected in Rattus flavipectus in Yunnan province in China with a positive rate of 15.9% [Reference Fu, He, OuYang, Yu, Wen, Zhou, Xiong, Yuan and Jiao9]. Differently, our study found that the C. burnetii can also be found in four species in Henan province, with a positive rate of 0.58%, suggesting that the host range and geographical distribution of C. burnetii are much larger than ever reported.

Leptospirosis is a systemic disease of humans and domestic animals, characterised by fever, renal and hepatic insufficiency, pulmonary manifestations, and reproductive failure [Reference Adler and de la Peña Moctezuma45]. L. interrogans is the predominant Leptospira species in China and A. agrarius is the main animal host [Reference Hu, Xa and Yan46], and most of Leptospirosis cases were caused by L. interrogans [Reference Zhang, Wang and Yan47]. Similarly, our study found that the L. interrogans was mostly detected in the species of A. agrarius in Henan province.

Clinical manifestations caused by SFGR include skin necrosis and acrogangrene, pneumonia, meningoencephalitis, and multiple organ failure [Reference Abdad, Abdallah, Fournier, Stenos and Vasoo48]. Rodents play an important role in the inter-species transmission of SFGR from, and recent surveys have shown significant diversity, prevalence, and geographic distribution of Rickettsial bacteria in rodents [Reference Fang, Liu, Li, Liang, Yang, Yao, Sun, Sun, Chen, Zuo, Ma, Li, Jiang, Liu, Yang, Gray, Krause and Cao37, Reference Kang, Diao, Zhao, Chen, Xiong, Shi, Fu, Guo, Pan, Chen, Holmes, Gillespie, Dumler and Zhang49]. It was reported that the prevalence of SFGR were 13.95%, 16.05%, and 33.3% in southeast, southwest, and south of China, respectively [Reference Lu, Tang, Ren, Zhang, Wang, Qin and Li50Reference Zhang, Han, Xu, Turchetto, Mediannikov, Rolain, Raoult and Fournier52]. However, SFGR was mostly found in the species of R. tanezumi in Henan province in our study, with a lower prevalence of 7.3%. Phylogenetic analysis demonstrated that R. heilongjiangensis was found in Henan, and R. raoultii was found in Inner Mongolia and Henan. R. raoultii and R. heilongjiangensis are both zoonotic pathogens. Rodents and shrews are extremely important natural hosts for the natural circulation of SFGR, posing increased threat to global public health [Reference Zhang, Sun, Chen, Teng, Wang, Li, Hay, Fang, Yang and Liu53].

Human babesiosis caused by Babesia spp. is an emerging tick-borne disease, and most of the cases are clinically asymptomatic [Reference Beri, Singh, Rodriguez, Yazdanbakhsh and Lobo54]. Babesia spp. found in several provinces in China from 1940 to 2013, and a field investigation confirmed the presence of Babesia spp. in rodents near human cases infected in Henan province [Reference Zhou, Xia, Huang, Tambo, Zhuge and Zhou55]. Previous surveillance showed that the positive rates of Babesia spp. in rodents were 3.94% and 12.1% in Beijing city and Fujian province, respectively [Reference Wei, Wang, Wang, Wang, Guan, Zhang, Dou and Wang56, Reference Zeng, Zhou, Xu, Liu, Han, Liu, Wang, Deng and Xiao57]. Similarly, our study showed that the positive rate of Babesia spp. may be vary in different provinces, ranged from 0.73% to 11.2%.

R. tanezumi was found to carry the largest number of zoonotic pathogen species (eight species), and it was distributed widespread in China [Reference Chen, Xu, Wang, Meng, Li, Fang and Liu6]. However, due to the small number of animal samples collected in Inner Mongolia, R. tanezumi was captured in three provinces in our study, and the surveillance of R. tanezumi should be strengthened in the future. Our study also indicated that RODENTIA had significantly prevalence of Bartonella spp., Leptospira spp., and SFGR than EULIPOTYPHLA.

As rodents are important vectors for many pathogens, co-infection may have important consequences in terms of disease transmission and risk of zoonotic transmission [Reference Bakaletz58]. A previous study of zoonotic pathogens in Austrian rodents reported double and triple infection rates of 6.4% and 1.8% [Reference Schmidt, Essbauer, Mayer-Scholl, Poppert, Schmidt-Chanasit, Klempa, Henning, Schares, Groschup, Spitzenberger, Richter, Heckel and Ulrich59]. Differently, our study found that the double and triple infection rates were 3.4% and 0.5%. The most common co-infection of the three pathogens, Bartonella spp.–Leptospira spp.–Anaplasmataceae, which was observed in four animals (three N. confucianus and one A. agrarius). The co-infection of four and five pathogens mainly occurred in N. confucianus in Henan province. The risk of host infection after interaction with the environment depends on the ability of zoonotic pathogens to persist, survive, and inter-species transmission [Reference Schmidt, Essbauer, Mayer-Scholl, Poppert, Schmidt-Chanasit, Klempa, Henning, Schares, Groschup, Spitzenberger, Richter, Heckel and Ulrich59, Reference Tadin, Tokarz, Markotić, Margaletić, Turk, Habuš, Svoboda, Vucelja, Desai, Jain and Lipkin60]. Surveillance should primarily focus on species of rodents or shrews that carried multiple pathogens.

There are three limitations in our study. First, we only screened several representative zoonotic pathogens in the rodents and shrews rather than for all pathogens through next-generation sequencing. Second, partial gene sequences were obtained rather than the whole genome for the zoonotic pathogens. Finally, the sampling number of rodents and shrews from different provinces and different species was varied.

In conclusion, our study expands the knowledge of the prevalence, distribution, and co-infection status against zoonotic pathogens in rodents and shrews from different provinces in China. The CaoBang orthohantavirus was first identified in the mainland of China, and prospective surveillance of zoonotic pathogens in wild animals is imperative.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1017/S0950268823001450.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary Material.

Data availability statement

All data are incorporated into the article and its Supplementary Material.

Acknowledgements

We would like to thank all patients who contributed to the data and clinicians who collected the data. We gratefully acknowledge all authors from the submitting laboratories who contributed to sharing information to literature, books, and websites, as most of our analyses were made possible by the sharing of their work.

Author contribution

Y.-H.W. and C.-H.D. designed and supervised the research. Y.-H.W., B.-G.J., C.-H.D., W.-S.L., H.-R.C., Z.-H.G., E.-N.P., and Y.-Q.L. collected samples and data. S.T. and J.-J.C. performed laboratory testing. S.T., J.-J.C., and G.-L.W. analysed the data. S.T., G.-L.W., L.-Q.F., Y.-H.W., and C.-H.D. drafted the manuscript. All authors reviewed and approved the final manuscript.

Financial support

This work was supported by the Key Research and Development Program of China (Grant No. 2021YFC230200-12), Science and Technology Plan Grant of Guangzhou (Grant No. 202102080035), the Key Project of Medicine Discipline of Guangzhou (Grant No. 2021-2023-11) and the Basic Research Project of Key Laboratory of Guangzhou (Grant No. 202102100001). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Competing interest

The authors declare no competing interest.

Ethical standard

The study protocol was approved by the Academy of Military Medical Sciences. All animals were treated by the guidelines in the regulations for the Administration of Laboratory Animals (Decree No. 2 of the State Science and Technology Commission of the People’s Republic of China, 1988). All animals were treated strictly according to the guidelines for the rules for surveillance methods for vector density of Rodent (2009) from People’s Republic of China Ministry of Health (GB/T23798-2009).

References

Jones, KE, Patel, NG, Levy, MA, Storeygard, A, Balk, D, Gittleman, JL and Daszak, P (2008) Global trends in emerging infectious diseases. Nature 451(7181), 990993.CrossRefGoogle ScholarPubMed
Meerburg, BG, Singleton, GR and Kijlstra, A (2009) Rodent-borne diseases and their risks for public health. Critical Reviews in Microbiology 35(3), 221270.CrossRefGoogle ScholarPubMed
Jonsson, CB, Figueiredo, LTM and Vapalahti, O (2010) A global perspective on hantavirus ecology, epidemiology, and disease. Clinical Microbiology Reviews 23(2), 412441.CrossRefGoogle ScholarPubMed
Gu, X-L, Su, W-Q, Zhou, C-M, Fang, L-Z, Zhu, K, Ma, D-Q, Jiang, F-C, Li, Z-M, Li, D, Duan, S-H, Peng, Q-M, Wang, R, Jiang, Y, Han, H-J and Yu, X-J (2022) SFTSV infection in rodents and their ectoparasitic chiggers. PLoS Neglected Tropical Diseases 16(8), e0010698.CrossRefGoogle ScholarPubMed
Dahmana, H, Granjon, L, Diagne, C, Davoust, B, Fenollar, F and Mediannikov, O (2020) Rodents as hosts of pathogens and related zoonotic disease risk. Pathogens 9(3), 202.CrossRefGoogle ScholarPubMed
Chen, J-J, Xu, Q, Wang, T, Meng, F-F, Li, Z-W, Fang, L-Q and Liu, W (2022) A dataset of diversity and distribution of rodents and shrews in China. Scientific Data 9(1), 304.CrossRefGoogle ScholarPubMed
Avšič-Županc, T, Saksida, A and Korva, M (2019) Hantavirus infections. Clinical Microbiology and Infection 21S, e6e16.CrossRefGoogle ScholarPubMed
Che, T-L, Jiang, B-G, Xu, Q, Zhang, Y-Q, Lv, C-L, Chen, J-J, Tian, Y-J, Yang, Y, Hay, SI, Liu, W and Fang, L-Q (2022) Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: A geospatial modelling analysis. Emerging Microbes & Infections 11(1), 12151226.CrossRefGoogle Scholar
Fu, M, He, P, OuYang, X, Yu, Y, Wen, B, Zhou, D, Xiong, X, Yuan, Q and Jiao, J (2022) Novel genotypes of Coxiella burnetii circulating in rats in Yunnan Province, China. BMC Veterinary Research 18(1), 204.CrossRefGoogle ScholarPubMed
Gutiérrez, R, Krasnov, B, Morick, D, Gottlieb, Y, Khokhlova, IS and Harrus, S (2015) Bartonella infection in rodents and their flea ectoparasites: An overview. Vector Borne and Zoonotic Diseases 15(1), 2739.CrossRefGoogle ScholarPubMed
Persing, DH, Mathiesen, D, Marshall, WF, Telford, SR, Spielman, A, Thomford, JW and Conrad, PA (1992) Detection of Babesia microti by polymerase chain reaction. Journal of Clinical Microbiology 30(8), 20972103.CrossRefGoogle ScholarPubMed
Su, Q, Chen, Y, Wang, B, Huang, C, Han, S, Yuan, G, Zhang, Q and He, H (2020) Epidemiology and genetic diversity of zoonotic pathogens in urban rats (Rattus spp.) from a subtropical city, Guangzhou, Southern China. Zoonoses and Public Health 67(5), 534545.CrossRefGoogle ScholarPubMed
Yang, J, Liu, Z, Guan, G, Liu, Q, Li, Y, Chen, Z, Ma, M, Liu, A, Ren, Q, Luo, J and Yin, H (2013) Prevalence of Anaplasma phagocytophilum in ruminants, rodents and ticks in Gansu, North-Western China. Journal of Medical Microbiology 62(Pt 2), 254258.CrossRefGoogle ScholarPubMed
Fang, L, Yan, L, Liang, S, de Vlas, SJ, Feng, D, Han, X, Zhao, W, Xu, B, Bian, L, Yang, H, Gong, P, Richardus, JH and Cao, W (2006) Spatial analysis of hemorrhagic fever with renal syndrome in China. BMC Infectious Diseases 6, 77.CrossRefGoogle ScholarPubMed
Yu, J, Xie, B, Bi, G-Y, Zuo, H-H, Du, X-Y, Bi, L-F, Li, D-M and Rao, H-X (2022) Prevalence and diversity of small rodent-associated Bartonella species in Shangdang Basin, China. PLoS Neglected Tropical Diseases 16(6), e0010446.CrossRefGoogle ScholarPubMed
Xu, G, Qiu, H, Liu, W, Jiang, X, Chang, Y-F, Wang, J, Li, Z, Zhu, Y, Zhang, C and Xiao, F (2022) Serological and molecular characteristics of pathogenic Leptospira in rodent populations in Fujian Province, China, 2018–2020. BMC Microbiology 22(1), 151.CrossRefGoogle ScholarPubMed
Wang, C and He, H (2013) Leptospira spp. in commensal rodents, Beijing, China. Journal of Wildlife Diseases 49(2), 461463.CrossRefGoogle ScholarPubMed
Chen, X-R, Ye, LI, Fan, J-W, Li, C, Tang, F, Liu, W, Ren, L-Z and Bai, J-Y (2017) Detection of Kobe-type and Otsu-type Babesia microti in wild rodents in China’s Yunnan province. Epidemiology and Infection 145(13), 27042710.CrossRefGoogle ScholarPubMed
Zhang, C, Song, F, Xiu, L, Liu, Y, Yang, J, Yao, L and Peng, J (2018) Identification and characterization of a novel rodent bocavirus from different rodent species in China. Emerging Microbes & Infections 7(1), 48.CrossRefGoogle ScholarPubMed
Klempa, B, Fichet-Calvet, E, Lecompte, E, Auste, B, Aniskin, V, Meisel, H, Denys, C, Koivogui, L, ter Meulen, J and Krüger, DH (2006) Hantavirus in African wood mouse, Guinea. Emerging Infectious Diseases 12(5), 838840.CrossRefGoogle ScholarPubMed
Zhuang, L, Du, J, Cui, X-M, Li, H, Tang, F, Zhang, P-H, Hu, J-G, Tong, Y-G, Feng, Z-C and Liu, W (2018) Identification of tick-borne pathogen diversity by metagenomic analysis in Haemaphysalis longicornis from Xinyang, China. Infectious Diseases of Poverty 7(1), 45.CrossRefGoogle ScholarPubMed
Ning, W, Mu-zi, J, Lan-fen, J, Sheng, Z, Hua, Y, Hong, L, Pan-he, Z, Hao, L and Chun-xia, M (2020) Pathogen investigation of rodents in the western ground crossings of inner Mongolia. Chinese Journal of Disease Control and Prevention 24(6), 716722.Google Scholar
Seo, M-G, Lee, S-H, VanBik, D, Ouh, I-O, Yun, S-H, Choi, E, Park, Y-S, Lee, S-E, Kim, JW, Cho, G-J, Kwon, O-D and Kwak, D (2016) Detection and genotyping of Coxiella burnetii and Coxiella-like bacteria in horses in South Korea. PLoS One 11(5), e0156710.CrossRefGoogle ScholarPubMed
Natarajaseenivasan, K, Raja, V and Narayanan, R (2012) Rapid diagnosis of leptospirosis in patients with different clinical manifestations by 16S rRNA gene based nested PCR. Saudi Journal of Biological Sciences 19(2), 151155.CrossRefGoogle ScholarPubMed
Regnery, RL, Spruill, CL and Plikaytis, BD (1991) Genotypic identification of rickettsiae and estimation of intraspecies sequence divergence for portions of two Rickettsial genes. Journal of Bacteriology 173(5), 15761589.CrossRefGoogle ScholarPubMed
Jia, N, Zheng, Y-C, Jiang, J-F, Ma, L and Cao, W-C (2013) Human infection with Candidatus Rickettsia tarasevichiae. New England Journal of Medicine 369(12), 11781180.CrossRefGoogle ScholarPubMed
Tayebwa, DS, Tuvshintulga, B, Guswanto, A, Nugraha, AB, El-Saber Batiha, G, Gantuya, S, Rizk, MA, Vudriko, P, Sivakumar, T, Yokoyama, N and Igarashi, I (2018) The effects of nitidine chloride and camptothecin on the growth of Babesia and Theileria parasites. Ticks and Tick-Borne Diseases 9(5), 11921201.CrossRefGoogle ScholarPubMed
Gu, SH, Arai, S, Yu, H-T, Lim, BK, Kang, HJ and Yanagihara, R (2016) Genetic variants of Cao Bang hantavirus in the Chinese mole shrew (Anourosorex squamipes) and Taiwanese mole shrew (Anourosorex yamashinai). Infection, Genetics and Evolution 40, 113118.CrossRefGoogle Scholar
Liu, X, Zhang, T, Xie, C and Xie, Y (2016) Changes of HFRS incidence caused by vaccine intervention in Yichun City, China, 2005–2013. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research 22, 295301.CrossRefGoogle ScholarPubMed
Wu, H, Wang, XY, Xue, M, Wu, C, Lu, Q, Ding, Z, Zhai, Y and Lin, J (2018) Spatial-temporal characteristics and the epidemiology of haemorrhagic fever with renal syndrome from 2007 to 2016 in Zhejiang Province, China. Scientific Reports 8(1), 10244.CrossRefGoogle ScholarPubMed
Xiang, J, Hansen, A, Liu, Q, Tong, MX, Liu, X, Sun, Y, Cameron, S, Hanson-Easey, S, Han, G-S, Williams, C, Weinstein, P and Bi, P (2018) Impact of meteorological factors on hemorrhagic fever with renal syndrome in 19 cities in China, 2005–2014. Science of the Total Environment 636, 12491256.CrossRefGoogle Scholar
Zou, L-X, Chen, M-J and Sun, L (2016) Haemorrhagic fever with renal syndrome: Literature review and distribution analysis in China. International Journal of Infectious Diseases 43, 95100.CrossRefGoogle ScholarPubMed
Wang, Q, Yue, M, Yao, P, Zhu, C, Ai, L, Hu, D, Zhang, B, Yang, Z, Yang, X, Luo, F, Wang, C, Hou, W and Tan, W (2020) Epidemic trend and molecular evolution of HV family in the Main hantavirus epidemic areas from 2004 to 2016, in P.R. China. Frontiers in Cellular and Infection Microbiology 10, 584814.CrossRefGoogle ScholarPubMed
Deng, XF (2023) Epidemiological characteristics of hemorrhagic fever with renal syndrome in China, 2004–2021. Disease Surveillance 38(1), 70.Google Scholar
Zhang, L, Liu, H, Xu, B, Zhang, Z, Jin, Y, Li, W, Lu, Q, Li, L, Chang, L, Zhang, X, Fan, D, Cao, M, Bao, M, Zhang, Y, Guan, Z, Cheng, X, Tian, L, Wang, S, Yu, H, Yu, Q, Wang, Y, Zhang, Y, Tang, X, Yin, J, Lao, S, Wu, B, Li, J, Li, W, Xu, Q, Shi, Y and Huang, F (2014) Rural residents in China are at increased risk of exposure to tick-borne pathogens Anaplasma phagocytophilum and Ehrlichia chaffeensis. BioMed Research International 2014, 313867.Google Scholar
Xia, Z (2019) Epidemic and research progress of babesiosis. Chinese Journal of Schistosomiasis Control 31(1), 6370.Google ScholarPubMed
Fang, L-Q, Liu, K, Li, X-L, Liang, S, Yang, Y, Yao, H-W, Sun, R-X, Sun, Y, Chen, W-J, Zuo, S-Q, Ma, M-J, Li, H, Jiang, J-F, Liu, W, Yang, XF, Gray, GC, Krause, PJ and Cao, W-C (2015) Emerging tick-borne infections in mainland China: An increasing public health threat. Lancet Infectious Diseases 15(12), 14671479.CrossRefGoogle ScholarPubMed
Bakken, JS and Dumler, JS (2006) Clinical diagnosis and treatment of human granulocytotropic anaplasmosis. Annals of the New York Academy of Sciences 1078, 236247.CrossRefGoogle ScholarPubMed
Duan, R, Lv, D, Fan, R, Fu, G, Mu, H, Xi, J, Lu, X, Chun, H, Hua, J, He, Z, Qin, S, Huang, Y, Xiao, M, Yang, J, Jing, H and Wang, X (2022) Anaplasma phagocytophilum in Marmota himalayana. BMC Genomics 23(1), 335.CrossRefGoogle ScholarPubMed
Qin, X-R, Liu, J-W, Yu, H and Yu, X-J (2019) Species detected in rodents from Eastern China. Vector Borne and Zoonotic Diseases (Larchmont, NY) 19(11), 810814.CrossRefGoogle ScholarPubMed
Liu, H, Han, T, Liu, W, Xu, G, Zheng, K and Xiao, F (2022) Epidemiological characteristics and genetic diversity of Bartonella species in rodents from Southeastern China. Zoonoses and Public Health 69(3), 224234.CrossRefGoogle ScholarPubMed
An, CH, Chen, BB, Lyu, W, Nie, SM, Li, SZ, Fan, SP, Sun, YX, Liu, JR, Li, DM and Xu, JR (2020) Species investigated among rodents from Shaanxi Province of China. Biomedical and Environmental Sciences 33(3), 201205.Google Scholar
Li, D-M, Hou, Y, Song, X-P, Fu, Y-Q, Li, G-C, Li, M, Eremeeva, ME, Wu, H-X, Pang, B, Yue, Y-J, Huang, Y, Lu, L, Wang, J and Liu, Q-Y (2015) High prevalence and genetic heterogeneity of rodent-borne Bartonella species on Heixiazi Island, China. Applied and Environmental Microbiology 81(23), 79817992.CrossRefGoogle ScholarPubMed
Dragan, AL and Voth, DE (2020) Coxiella burnetii: International pathogen of mystery. Microbes and Infection 22(3), 100110.CrossRefGoogle ScholarPubMed
Adler, B and de la Peña Moctezuma, A (2010) Leptospira and leptospirosis. Veterinary Microbiology 140(3–4), 287296.CrossRefGoogle ScholarPubMed
Hu, W, Xa, L and Yan, J (2014) Leptospira and leptospirosis in China. Current Opinion in Infectious Diseases 27(5), 432436.CrossRefGoogle ScholarPubMed
Zhang, C, Wang, H and Yan, J (2012) Leptospirosis prevalence in Chinese populations in the last two decades. Microbes and Infection 14(4), 317323.CrossRefGoogle ScholarPubMed
Abdad, MY, Abdallah, RA, Fournier, P-E, Stenos, J and Vasoo, S (2018) A concise review of the epidemiology and diagnostics of rickettsioses: Rickettsia and Orientia spp. Journal of Clinical Microbiology 56(8), e01728.CrossRefGoogle ScholarPubMed
Kang, Y-J, Diao, X-N, Zhao, G-Y, Chen, M-H, Xiong, Y, Shi, M, Fu, W-M, Guo, Y-J, Pan, B, Chen, X-P, Holmes, EC, Gillespie, JJ, Dumler, SJ and Zhang, Y-Z (2014) Extensive diversity of Rickettsiales bacteria in two species of ticks from China and the evolution of the Rickettsiales. BMC Evolutionary Biology 14, 167.CrossRefGoogle ScholarPubMed
Lu, M, Tang, G, Ren, Z, Zhang, J, Wang, W, Qin, X and Li, K (2022) Ehrlichia, Coxiella and Bartonella infections in rodents from Guizhou Province, Southwest China . Ticks and Tick-Borne Diseases 13(5), 101974.CrossRefGoogle ScholarPubMed
Lu, M, Li, F, Liao, Y, Shen, J-J, Xu, J-M, Chen, Y-Z, Li, J-H, Holmes, EC and Zhang, Y-Z (2019) Epidemiology and diversity of Rickettsiales bacteria in humans and animals in Jiangsu and Jiangxi provinces, China. Scientific Reports 9(1), 13176.CrossRefGoogle ScholarPubMed
Zhang, LJ, Han, J, Xu, JG, Turchetto, J, Mediannikov, O, Rolain, J-M, Raoult, D and Fournier, P-E (2009) Identification of a new serotype of Rickettsia heilongjiangensis in wild rats from Guangdong Province, China. Clinical Microbiology and Infection 15(Suppl 2), 338339.CrossRefGoogle ScholarPubMed
Zhang, Y-Y, Sun, Y-Q, Chen, J-J, Teng, A-Y, Wang, T, Li, H, Hay, I, Fang, L-Q, Yang, Y and Liu, W (2023) Mapping the global distribution of spotted fever group Rickettsiae: A systematic review with modelling analysis. Lancet Digital Health 5(1), E5E15.CrossRefGoogle ScholarPubMed
Beri, D, Singh, M, Rodriguez, M, Yazdanbakhsh, K and Lobo, CA (2021) Sickle cell anemia and Babesia infection. Pathogens 10(11), 1435.CrossRefGoogle ScholarPubMed
Zhou, X, Xia, S, Huang, J-L, Tambo, E, Zhuge, H-X and Zhou, X-N (2014) Human babesiosis, an emerging tick-borne disease in the People’s Republic of China. Parasites & Vectors 7, 509.Google ScholarPubMed
Wei, C-Y, Wang, X-M, Wang, Z-S, Wang, Z-H, Guan, Z-Z, Zhang, L-H, Dou, X-F and Wang, H (2020) High prevalence of Babesia microti in small mammals in Beijing. Infectious Diseases of Poverty 9(1), 155.CrossRefGoogle ScholarPubMed
Zeng, Z, Zhou, S, Xu, G, Liu, W, Han, T, Liu, J, Wang, J, Deng, Y and Xiao, F (2022) Prevalence and phylogenetic analysis of Babesia parasites in reservoir host species in Fujian province, Southeast China. Zoonoses and Public Health 69(8), 915924.CrossRefGoogle ScholarPubMed
Bakaletz, LO (2004) Developing animal models for polymicrobial diseases. Nature Reviews Microbiology 2(7), 552568.CrossRefGoogle ScholarPubMed
Schmidt, S, Essbauer, SS, Mayer-Scholl, A, Poppert, S, Schmidt-Chanasit, J, Klempa, B, Henning, K, Schares, G, Groschup, MH, Spitzenberger, F, Richter, D, Heckel, G and Ulrich, RG(2014) Multiple infections of rodents with zoonotic pathogens in Austria. Vector Borne and Zoonotic Diseases 14(7), 467475.CrossRefGoogle ScholarPubMed
Tadin, A, Tokarz, R, Markotić, A, Margaletić, J, Turk, N, Habuš, J, Svoboda, P, Vucelja, M, Desai, A, Jain, K and Lipkin, WI (2016) Molecular survey of zoonotic agents in rodents and other small mammals in Croatia. American Journal of Tropical Medicine and Hygiene 94(2), 466473.CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. Geographical distribution of rodents and shrews in four provinces of China. From June 2015 to January 2022, small wild animals were collected in different parts of China. The total number of small wild animals and the proportion at the level of family collected from each region were shown.

Figure 1

Figure 2. The carrying status of eight pathogens in rodents and shrews from four provinces.

Figure 2

Table 1. Detection rate of rodent species with different pathogens in Henan, Guangdong, Inner Mongolia, and Yunnan from 2015 to 2022

Figure 3

Figure 3. Co-infection between pathogens. The size of the circle represents the number of infections, and the thickness of the line represents the number of samples in which co-infections were present.

Figure 4

Figure 4. Rodents detect phylogenetic trees of pathogens. Phylogenetic trees based on the sequence of this study and the known species of this pathogen. The sequences obtained in this study are marked in red. (A) Hantavirus L segment. (B) Bartonella spp. ITS gene. (C) Anaplasmataceae 16S rRNA. (D) Babesia spp. 18S rRNA. (E) Leptospira spp. 16S rRNA. (F) SFGR OmpA gene. (G) Borrelia spp. 16S rRNA. (H) Coxiella burnetii 16S rRNA. The maximum likelihood tree was constructed under the best model, which was selected based on the BIC scores. Phylogenetic tree construction based on the MAGE X software. The link between the host and the detection of the pathogens.

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