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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: wei_yh0928@163.com
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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.

Information

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
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
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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