spp. in wild rodents in the Poyang Lake region, China

Cryptosporidium spp. are zoonotic protozoan parasites that cause diarrheal disease worldwide. Rodents can harbor diverse Cryptosporidium spp. and facilitate their transmission to the environment and other hosts, including humans. However, data on Cryptosporidium infection in wild rodents in the Poyang Lake region, China’s largest freshwater lake, remain scarce. Here, we investigated Cryptosporidium spp. in 273 wild rodents collected from seven sites adjacent to villages around Poyang Lake between 2022 and 2024. The rodents were identified by cytochrome c oxidase subunit I (COI) gene sequencing as Apodemus agrarius (n = 148) and Rattus losea (n = 125). Nested PCR targeting the small subunit ribosomal RNA (SSU rRNA) gene revealed an overall Cryptosporidium spp. infection rate of 16.5% (45/273, 95% CI: 12.3–21.9%), with 20.3% (30/148, 95% CI: 14.2–27.8%) in A. agrarius and 12.0% (15/125, 95% CI: 6.9–19.0%) in R. losea. Sequence and phylogenetic analyses identified seven Cryptosporidium species/genotypes: C. apodemi, C. canis, C. muris, C. suis, C. ubiquitum, rat genotype II, and rat genotype III. Notably, the detection of four zoonotic species (C. canis, C. muris, C. suis, and C. ubiquitum) highlights the potential risk of zoonotic transmission of Cryptosporidium spp. from wild rodents to humans in this region. These findings underscore the need for systematic surveillance and control of Cryptosporidium spp. in wild rodent communities around Poyang Lake.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-09-25
DOI
https://doi.org/10.1051/parasite/2025056/pdf
Primary Topic
Parasitic Infections and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

spp. in wild rodents in the Poyang Lake region, China

Springer Link (Chiba Institute of Technology)
Parasitic Infections and Diagnostics
article

spp. in wild rodents in the Poyang Lake region, China

article en

Abstract

Cryptosporidium spp. are zoonotic protozoan parasites that cause diarrheal disease worldwide. Rodents can harbor diverse Cryptosporidium spp. and facilitate their transmission to the environment and other hosts, including humans. However, data on Cryptosporidium infection in wild rodents in the Poyang Lake region, China’s largest freshwater lake, remain scarce. Here, we investigated Cryptosporidium spp. in 273 wild rodents collected from seven sites adjacent to villages around Poyang Lake between 2022 and 2024. The rodents were identified by cytochrome c oxidase subunit I (COI) gene sequencing as Apodemus agrarius (n = 148) and Rattus losea (n = 125). Nested PCR targeting the small subunit ribosomal RNA (SSU rRNA) gene revealed an overall Cryptosporidium spp. infection rate of 16.5% (45/273, 95% CI: 12.3–21.9%), with 20.3% (30/148, 95% CI: 14.2–27.8%) in A. agrarius and 12.0% (15/125, 95% CI: 6.9–19.0%) in R. losea. Sequence and phylogenetic analyses identified seven Cryptosporidium species/genotypes: C. apodemi, C. canis, C. muris, C. suis, C. ubiquitum, rat genotype II, and rat genotype III. Notably, the detection of four zoonotic species (C. canis, C. muris, C. suis, and C. ubiquitum) highlights the potential risk of zoonotic transmission of Cryptosporidium spp. from wild rodents to humans in this region. These findings underscore the need for systematic surveillance and control of Cryptosporidium spp. in wild rodent communities around Poyang Lake.

Springer Link (Chiba Institute of Technology)
Life in Land
Openalex Percentile: Top 34%
Parasitic Infections and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.