Emergence of zoonotic Cryptosporidium, Giardia duodenalis and Enterocytozoon bieneusi in wild rodent from Yunnan: first detection of C. parvum IIdA24G1 in wild rodents in China

Abstract

Introduction

Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi are critical zoonotic diarrheal pathogens threatening human and animal health. Wild rodents act as key reservoirs for cross-species pathogen transmission, while systematic epidemiological data of these pathogens in Yunnan rodents remain scarce.

Methods

To elucidate the prevalence and genetic characteristics of Cryptosporidium, G. duodenalis, and E. bieneusi in wild rodents in Yunnan Province, a total of 304 wild rodent samples were collected from seven cities in Yunnan Province, China: Baoshan, Chuxiong, Dali, Diqing, Kunming, Lincang, and Yuxi. Intestinal contents were collected for DNA extraction, and the infection status and species/assemblages/genotypes of Cryptosporidium (targeting SSU rRNA gene), G. duodenalis (targeting TPI gene), and E. bieneusi (targeting ITS gene) in these animals were determined by nested PCR and DNA sequencing.

Results

The results showed that the overall prevalence of Cryptosporidium spp., G. duodenalis, and E. bieneusi were 13.8% (42/304), 18.1% (55/304), and 11.2% (34/304), respectively. The prevalence varied significantly across regions and rodent species. Notably, Apodemus chevrieri had a significantly higher risk of Cryptosporidium prevalence (OR = 8.70, 95% CI: 2.81–26.94) compared to Rattus norvegicus. Eight Cryptosporidium species/genotypes: C. muris, C. meleagridis, C. baileyi, C. parvum, rat genotype I-IV, two G. duodenalis assemblages (B and G) and five E. bieneusi genotypes: three zoonotic genotypes (D, EpbC, Type IV), as well as two known genotype (SDD5, CHY1) were identified. Notably, the zoonotic C. parvum IIdA24G1 subtype was first documented in wild rodents in China.

Discussion

Multiple zoonotic genotypes were detected with potential public health risks. This study fills the epidemiological gap of intestinal zoonotic pathogens in Yunnan wild rodents. The newly identified endemic IIdA24G1 subtype and prevalent zoonotic genotypes reveal high spillover risks, providing baseline data for regional pathogen surveillance and public health prevention.

1. Introduction

Cryptosporidium spp., Giardia duodenalis (also known as Giardia lamblia or Giardia intestinalis), and Enterocytozoon bieneusi are the major pathogens responsible for diarrhea diseases in humans and animals worldwide, with E. bieneusi being classified as a microsporidial infection, posing a significant threat particularly to immunocompromised individuals (Adam, 2021; Guérin and Striepen, 2020; Nourrisson et al., 2024). These three pathogens are spread chiefly by the fecal-oral route and can infect a variety of animal species, showing particularly high prevalence in wildlife populations. Pathogen-carrying wildlife are highly likely to contaminate water sources. Furthermore, since the pathogens can be transmitted reciprocally among humans, wildlife and livestock, sophisticated transmission chains are ultimately established in their common living environments (Adam, 2021; Nourrisson et al., 2024; Xiao et al., 2004).

Since the discovery of Cryptosporidium, over 48 valid species and more than 100 genotypes have been reported, some of which exhibit strong host specificity while others are zoonotic pathogens (Ryan et al., 2021). The majority of human cryptosporidiosis is caused by Cryptosporidium hominis and Cryptosporidium parvum. In recent years, with the advancement of molecular epidemiological investigations, cases of cryptosporidiosis caused by Cryptosporidium meleagridis have gradually increased (Ryan et al., 2014). Cryptosporidium baileyi primarily infects avian species; however, waterborne transmission via animal-contaminated water has been suggested, with rare cases reported in humans (Feng and Xiao, 2017; Kopacz et al., 2020). Cryptosporidium muris is a gastric Cryptosporidium species that can infect a variety of mammals (Mahdavi et al., 2024). In addition to various rodents, natural infections have also been found in many other mammalian species (Feng et al., 2011). Currently, effective vaccines or drugs against cryptosporidiosis are still lacking. Nitazoxanide, the only drug approved by the U. S. Food and Drug Administration (FDA) for the treatment of human cryptosporidiosis, shows no significant clinical efficacy in immunocompromised or malnourished patients (Amadi et al., 2009). Moreover, the only commercially approved vaccine against cryptosporidiosis is intended solely to protect newborn calves from severe diarrhea, and its efficacy is limited (Timmermans et al., 2024).

Giardia duodenalis is classified into eight assemblages or groups (A–H) based on protein and DNA polymorphisms (Klotz et al., 2022). Different assemblages exhibit distinct host distributions. The genotypes infecting humans typically belong to assemblages A and B, which are also found in most mammalian species, indicating broad host specificity and zoonotic transmission (Adam, 2021). In contrast, assemblages C/D, E, F, and G are mainly found in canids, artiodactyls, felids, and rodents, respectively (Zhang et al., 2018). Numerous reports indicate that in children, G. duodenalis infection—even in the absence of diarrheal symptoms—may lead to growth retardation or other manifestations of malnutrition (Sackey et al., 2003; Prado et al., 2005; Boeke et al., 2010; Donowitz et al., 2016). For symptomatic giardiasis, there is no specific targeted therapy; the commonly used 5-nitroimidazole drugs, metronidazole and tinidazole, have similar therapeutic efficacy, but cases of treatment failure and drug resistance have been reported (Minetti et al., 2016; Einarsson et al., 2016).

Microsporidia have a broad host range. To date, 10 genera and 17 species have been reported to infect humans, with Enterocytozoon bieneusi being the most common pathogen (Zhang et al., 2024). Over 820 genotypes of E. bieneusi have been identified in humans and animals, among which 52 are zoonotic genotypes (Koehler et al., 2022). Based on host specificity and zoonotic potential, E. bieneusi genotypes are classified into 15 groups (Zhao et al., 2024); groups 1 and 2 contain more zoonotic genotypes, while the remaining groups exhibit stronger host specificity (Koehler et al., 2022). Wild rodents infected with E. bieneusi may also carry a greater variety of viruses (Yu et al., 2025), posing a greater threat to humans and other animals. To date, E. bieneusi cannot be maintained in in-vitro culture, which limits our understanding of its biology (Nourrisson et al., 2024). The only drug validated to be effective against E. bieneusi is fumagillin, a methionine aminopeptidase type 2 inhibitor, whose efficacy has been confirmed in a randomized double-blind placebo-controlled clinical trial (Molina et al., 2002); however, due to its hematological toxicity, its use was discontinued in 2019 (Maillard et al., 2021). Nitazoxanide has also been reported to achieve successful treatment in some cases (Zhou et al., 2023), but for the majority of immunocompromised patients, it still lacks significant efficacy.

Yunnan Province, known for its diverse geography, mild climate, and rich ecosystems, is home to an extraordinary variety of wild rodent species. These rodents not only serve as natural reservoirs for multiple zoonotic pathogens but also frequently act as vectors in the transmission of these pathogens, thereby posing significant threats to public health. Cryptosporidiosis, E. bieneusi infection, and G. duodenalis infection are all parasitic diseases with zoonotic potential, and effective therapeutic drugs are relatively lacking. Therefore, it is particularly important to prevent the occurrence of these diseases, and molecular epidemiological investigations of these three pathogens carry significant public health implications. Wild rodents represent a unique study subject in global surveys due to their remarkable species diversity, worldwide distribution, and habitats that are closely intertwined with human activities. They serve as a link between humans, domestic animals, pets, various pathogens, and wildlife, thereby increasing the risk of rodent-borne disease transmission (Chen et al., 2022). The core concept of One Health is that the health of humans, animals, and our shared environment is inseparable and closely interconnected. To date, no systematic report has been published on the molecular epidemiology of Cryptosporidium, E. bieneusi, and G. duodenalis infections in wild rodents in Yunnan, China. Therefore, this study aims to determine the prevalence and genotype distribution of these three intestinal protozoa in wild rodents in Yunnan Province, adding to the epidemiological data on these pathogens in wild rodents in Yunnan, China, and providing a scientific basis for their prevention and control.

2. Materials and methods

2.1. Ethics approval and consent to participate

This study involved the capture and euthanasia of wild rodents for sample collection. The procedures followed were reviewed and approved by the Life Science Ethics Committee of Yunnan Agricultural University (IACUC Issue No: APYNAU202503111). The capture, handling, and euthanasia of rodents were carried out in accordance with the requirements of the Administrative Regulations of Laboratory Animals of China (2017).

2.2. Sample collection

Between March 22, 2025, and January 21, 2026, a total of 304 wild rodents were collected from seven areas adjacent to human settlements or farms in Yunnan Province, China (Baoshan, Chuxiong, Dali, Diqing, Kunming, Lincang, and Yuxi) (Figure 1). These sampling sites were selected to represent different altitudinal gradients (ranging from 511 m to 3,459 m) and climate types (from subtropical to cold-temperate), as well as varying degrees of human-wildlife interface. (Table 1). Rodents were trapped using corn as bait; traps were placed at various rodent-active sites, with approximately 30 traps set each night and retrieved before sunrise. Trapping was conducted for 3–5 consecutive nights at each location, totaling approximately 60–100 trap-nights per site. The collection time and location were recorded for each capture. Within 48 h post-capture, all wild rodents were transported to the laboratory and euthanized by CO₂ inhalation (Zhao et al., 2018). Sex was recorded, and fresh intestinal contents (500 mg) were immediately obtained from the intestine of each wild rodent, along with 200 mg of muscle tissue. All samples were stored at −20 °C until further use, and DNA extraction was completed within 1 week.

Figure 1.

Map of wild rodents sampling sites in Yunnan Province, China. Base map from Tianditu (National Platform for Common Geospatial Information Services), https://www.tianditu.gov.cn/ (Approval No. GS(2024)0650).

Table 1.

Geographical distribution and sample collection details of wild rodents at seven locations in Yunnan Province, China.

Location	Geographical coordinates	Average elevation (m)	Climate	No. of samples				Total
				Rattus tanezumi	Rattus norvegicus	Apodemus chevrieri	Rattus nitidus
Baoshan	99°14′25.26″E, 24°43′16.94″N	1,460	Subtropical	13				13
Chuxiong	102°24′16.78″E, 25°31′51.46″N	1910	Temperate		34			34
Dali	99°54′23.27″E, 26°32′14.97″N	2,200	Alpine	13	29			42
Diqing	99°45′0.50″E, 27°50′19.15″N	3,459	Cold-temperate		10	15	6	31
Kunming	102°42′31.81″E, 25°2′37.49″N	1887	Mild	1	63			64
Lincang	99°5′0.59″E, 23°33′22.02″N	511	Southern subtropical	56				56
Yuxi	102°10′7.98″E, 24°40′13.23″N	1,585	Mid-subtropical	14	50			64
Total				97	186	15	6	304

2.3. Species identification of wild rodents

Species identification of captured rodents was performed using both morphological and molecular biological methods. Morphological identification was carried out primarily following the descriptions in The Identification Atlas of Medical Vector Organisms at Chinese Border Ports and The Classification and Identification Manual of Common Disease Vectors. Molecular identification was first performed as follows: genomic DNA was extracted from 25 mg of muscle tissue using the Magnetic Beads Animal Tissue Genomic DNA Extraction Kit (Cat. No. DP341; TIANGEN, Beijing, China) according to the manufacturer’s instructions. Subsequently, the mitochondrial cytochrome c oxidase subunit I (COI) was amplified by polymerase chain reaction (PCR) for species identification (Robins et al., 2007).

2.4. DNA extraction from intestinal contents

Genomic DNA was then extracted from 200 mg of the intestinal contents samples using an E.Z.N.A.® Stool DNA Kit (OMEGA Bio-Tek, Inc., Norcross, GA, USA) according to the manufacturer’s instructions. The extracted DNA was eluted in 100 μL of elution buffer and stored at −20 °C prior to PCR analysis.

2.5. PCR amplification

Nested PCR based on the small ribosomal subunit RNA (SSU rRNA) gene was used to detect and identify Cryptosporidium species in all DNA samples, with a target product size of approximately 830 bp (Xiao et al., 1999). Nested PCR was also employed for subtype identification of C. parvum based on the 60 kDa glycoprotein (gp60) gene, with product sizes of approximately 850 bp (Chen et al., 2019). G. duodenalis and E. bieneusi were detected by nested PCR targeting the TPI and ITS genes, respectively, to amplify the target fragments, with product sizes of approximately 530 bp and 392 bp (Zhao et al., 2015; Zou et al., 2018) (Table 2). All PCR amplifications were performed with positive controls consisting of C. andersoni DNA from cattle for Cryptosporidium, G. duodenalis assemblage E DNA from pigs for G. duodenalis, and Enterocytozoon bieneusi EbpC genotype DNA from pigs for E. bieneusi, along with a negative control without DNA.

Table 2.

Primers and PCR conditions used in this study.

Pathogen	Target gene	Primer sequence (5′ → 3′)	Annealing temperature (°C)	Product size (bp)	References
Cryptosporidium spp.	SSU rRNA	F1: CCCTAATCCTTCGAAACAGGA	55	830	(Robins et al., 2007)
		R1: TTCTAGAGCTAATACATGCG
		F2: AAGGAGTAAGGAACAACCTCCA	56
		R2: GGAAGGGTTGTATTTATTAGATAAAG
C. parvum	gp60	F1: TTACTCTCCGTTATAGTCTCC	52	850	(Xiao et al., 1999)
		R1: GGAAGGAACGATGTATCTGA
		F2: TCCGCTGTATTCTCAGCC	52
		R2: GCAGAGGAACCAGCATC
Giardia duodenalis	TPI	F1: AAATTATGCCTGCTCGTCG	58	530	(Chen et al., 2019)
		R1: CAAACCTTTTCCGCAAACC
		F2: CCCTTCATCGGIGGTAACTT	62
		R2: GTGGCCACCACTCCCGTGCC
Enterocytozoon bieneusi	ITS	F1: GGTCATAGGGATGAAGAG	55	392	(Zhao et al., 2015)
		R1: TTCGAGTTCTTTCGCGCTC
		F2: GCTCTGAATATCTATGGCT	55
		R2: ATCGCCGACGGATCCAAGTG

2.6. Sequencing and phylogenetic analysis

Based on the gel electrophoresis results, all secondary positive PCR products were sent to Sangon Biotech (Kunming, China) for bidirectional sequencing on an ABI 3730 sequencer (Applied Biosystems, Foster City, CA, USA). Each raw sequence was assembled using ChromasPro 2.1.5.0¹. Assembled sequences were compared with GenBank datebase to select appropriate reference sequences. The resulting sequences were then aligned using ClustalX software 2.1.5.0² with Cryptosporidium, G. duodenalis, and E. bieneusi reference sequences obtained from GenBank³. A phylogenetic tree was constructed using MEGA 6.0 software⁴ based on the maximum likelihood method. The genetic relationship and reliability of the phylogenetic tree were assessed using the general time-reversible model and by bootstrapping with 1,000 replicates.

2.7. Statistical analysis

IBM SPSS Statistics 27.0 (IBM Corp., Armonk, NY, USA) software was used to analyze the effects of region, species, sex and other factors on the infection of wild rodents with Cryptosporidium, G. duodenalis and E. bieneusi. Statistical difference was considered significant at p < 0.05. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess whether the associated factors were risk factors. Prevalence 95% CIs were calculated using the Wilson score method to avoid lower bounds below zero for proportions near 0 or 100%.

Due to the small sample sizes of some rodent species (Apodemus chevrieri, n = 15; Rattus nitidus, n = 6) and zero counts in certain subgroups, Fisher’s exact test was used instead of chi-square test when expected cell counts were <5. ORs with 95% CIs were calculated using univariable logistic regression. Multivariable analysis was not performed due to the limited sample size in some strata, which would result in unstable estimates. This limitation is acknowledged in the discussion.

3. Results

3.1. Wild rodent species

Based on morphological and molecular identification, among the 304 wild rodents collected from seven prefectures and cities in Yunnan Province, there were 97 Rattus tanezumi, 186 Rattus norvegicus, 15 Apodemus chevrieri, and 6 Rattus nitidus (Table 1). Analysis of the distribution characteristics of wild rodents across different habitats revealed that Rattus norvegicus was mostly distributed in temperate monsoon climate zones, Rattus tanezumi was predominantly found in subtropical regions, while Apodemus chevrieri and Rattus nitidus were distributed in alpine cold regions.

3.2. Prevalence of Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi

Among the 304 samples collected from seven prefectures and cities, the prevalence of Cryptosporidium, G. duodenalis, and E. bieneusi were 13.82% (42/304), 18.09% (55/304), and 11.18% (34/304), respectively (Table 3). Significant differences were observed in the prevalence of Cryptosporidium and E. bieneusi across different regions (χ² = 16.642, df = 6, p = 0.011; and χ² = 16.722, df = 4, p = 0.002, respectively), while the difference in G. duodenalis infection rate was highly significant (χ² = 24.018, df = 4, p < 0.001). After classifying samples from different regions into three elevation intervals, significant differences were observed in the infection rate of E. bieneusi among different elevations (χ² = 6.120, df = 2, p = 0.047), while no statistically significant differences were found for Cryptosporidium (χ² = 0.563, p = 0.755) and G. duodenalis (χ² = 0.361, p = 0.548). Regarding rodent species, the prevalence of Cryptosporidium and E. bieneusi differed highly significantly (χ² = 18.173, df = 3, p < 0.001; and χ² = 28.782, df = 2, p < 0.001, respectively), whereas the difference in G. duodenalis infection rate was not statistically significant (χ² = 0.993, p = 0.319). For sex, no significant differences were found in the prevalence of the three pathogens (χ² = 0.476, p = 0.490; χ² = 0.347, p = 0.556; and χ² = 0.126, p = 0.723, respectively). Thus, in this study, geographical region significantly influenced the infection of all three pathogens, rodent species significantly affected Cryptosporidium and E. bieneusi infections, while sex had no impact on the infection status of any of the three pathogens.

Table 3.

Occurrence and factors associated with Cryptosporidium spp. Giardia duodenalis and Enterocytozoon bieneusi infection in wild rodent in Yunnan Province, China.

Factor	Category	No. tested	Cryptosporidium spp.				G. duodenalis				E. bieneusi
			No. positive	Prevalence (%) (95% CI)	OR (95%, CI)	p-Value	No. positive	Prevalence (%) (95% CI)	OR (95%, CI)	p-value	No. positive	Prevalence (%) (95% CI)	OR (95%, CI)	p-value
Region	Baoshan	13	4	30.77 (12.68–57.63)	8.89 (1.41–56.25)	<0.05	1	7.69 (1.37–33.31)	Reference	<0.01	2	15.38 (4.33–42.23)	10.00 (0.83–120.16)	<0.05
	Chuxiong	34	2	5.88 (1.63–19.09)	1.25 (0.17–9.37)		18	52.94 (36.34–68.55)	13.50 (1.58–115.70)		–	–	–
	Dali	42	2	4.76 (1.32–15.79)	Reference		–	–	–		–	–	–
	Diqing	31	9	29.03 (16.10–46.59)	8.18 (1.62–41.26)		–	–	–		10	32.26 (18.57–49.86)	26.19 (3.16–217.37)
	Kunming	64	5	7.81 (3.38–17.02)	1.70 (0.31–9.17)		7	10.94 (5.40–20.90)	1.74 (0.17–13.11)		8	12.50 (6.47–22.77)	7.86 (0.95–64.93)
	Lincang	56	9	16.07 (8.69–27.81)	3.83 (0.78–18.76)		15	26.79 (16.96–39.59)	4.39 (0.35–36.72)		1	1.79 (0.32–9.45)	Reference
	Yuxi	64	11	17.19 (9.88–28.21)	4.15 (0.87–19.78)		14	21.88 (13.50–33.43)	3.36 (0.40–28.11)		13	20.31 (12.27–31.71)	14.02 (1.77–111.03)
Average Elevation (m)	>2000	73	11	15.07 (8.63–25.00)	1.23 (0.57–2.70)	>0.05	–	–	–	>0.05	10	13.70 (7.61–23.41)	8.73 (1.08–70.39)	<0.05
	1,000–2000	175	22	12.57 (8.45–18.30)	Reference		40	22.86 (17.26–29.62)	Reference		23	13.14 (8.92–18.95)	8.32 (1.10–63.10)
	<1,000	56	9	16.07 (8.69–27.80)	1.33 (0.57–3.09)		15	26.79 (16.96–39.59)	1.24 (0.62–2.46)		1	1.79 (0.32–9.45)	Reference
Rodent species	Rattus tanezumi	97	17	17.53 (11.24–26.29)	2.11 (1.02–4.35)	<0.01	22	22.68 (15.48–31.96)	0.74 (0.40–1.35)	>0.05	6	6.19 (2.87–12.83)	Reference	<0.01
	Rattus norvegicus	186	17	9.14 (5.78–14.15)	Reference		33	17.74 (12.92–23.87)	Reference		20	10.75 (7.07–16.02)	1.83 (0.71–4.71)
	Apodemus chevrieri	15	7	46.67 (24.81–69.88)	8.70 (2.81–26.94)			–	–		8	53.33 (30.12–75.19)	17.33 (4.69–64.13)
	Rattus nitidus	6	1	16.67 (3.01–56.35)	1.99 (0.22–18.02)			–	–		–	–	–
Sex	Male	166	25	15.06 (10.41–21.29)	1.26 (0.65–2.45)	>0.05	32	19.28 (14.00–25.95)	1.19 (0.66–2.16)	>0.05	17	10.24 (6.49–15.79)	Reference	>0.05
	Female	138	17	12.32 (7.84–18.84)	Reference		23	16.67 (11.37–23.77)	Reference		17	12.32 (7.84–18.84)	1.23 (0.60–2.51)
Total		304	42	13.82 (10.39–18.15)	–	–	55	18.09 (14.17–22.81)	–	–	34	11.18 (8.11–15.22)	–	–

No, number; CI, confidence interval; OR, odds ratio.

3.3. Distribution of Cryptosporidium species and subtypes

Sequence analysis of the SSU rRNA gene products from 42 Cryptosporidium isolates revealed eight species: C. muris (11/42, 26.19%), rat genotype I (9/42, 21.43%), rat genotype II (1/42, 2.38%), rat genotype III (10/42, 23.81%), rat genotype IV (6/42, 14.29%), C. meleagridis (3/42, 7.14%), C. baileyi (1/42, 2.38%), and C. parvum (1/42, 2.38%), with C. muris being the predominant species (Table 4). Among these, the C. parvum isolate was identified as subtype IIdA24G1 based on gp60 analysis. In terms of rodent species, only a single Cryptosporidium species/genotype was detected in Apodemus chevrieri and Rattus nitidus, whereas Rattus norvegicus and Rattus tanezumi exhibited a richer diversity of Cryptosporidium species/genotypes due to their broader distribution.

Table 4.

Species/assemblages/genotypes identification of Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi from wild rodent in Yunnan Province, China.

Factor	Category	Species/assemblages/genotypes (n)
		Cryptosporidium spp.	G. duodenalis	E. bieneusi
Region	Baoshan	rat genotype III (3) rat genotype IV (1)	G (1)	D (1) EpbC (1)
	Chuxiong	C. meleagridis (1) C. parvum (1), IIdA24G1	G (18)	–
	Dali	rat genotype III (1) C. muris (1)	–	–
	Diqing	rat genotype I (1) rat genotype IV (1) C. muris (7)	–	D (1) SDD5 (9)
	Kunming	rat genotype I (1) rat genotype III (1) rat genotype IV (1) C. muris (2)	G (7)	D (6) Type IV (1) CHY1 (1)
	Lincang	rat genotype I (1) rat genotype II (1) rat genotype III (4) rat genotype IV (1) C. baileyi (1) C. muris (1)	G (15)	D (1)
	Yuxi	rat genotype I (6) rat genotype III (1) rat genotype IV (2) C. meleagridis (2)	B (3) G (11)	D (13)
Rodent species	Rattus tanezumi	rat genotype I (1) rat genotype II (1) rat genotype III (10) rat genotype IV (2) C. baileyi (1) C. muris (1) C. meleagridis (1)	B (1) G (21)	D (5) EpbC (1)
	Rattus norvegicus	rat genotype I (8) rat genotype IV (3) C. muris (3) C. meleagridis (2) C. parvum (1), IIdA24G1	B (2) G (31)	D (17) Type IV (1) CHY1 (1) SDD5 (1)
	Apodemus chevrieri	C. muris (7)	–	SDD5 (8)
	Rattus nitidus	rat genotype IV (1)	–	–
Total		C. muris (11), rat genotype I (9), rat genotype II (1), rat genotype III (10), rat genotype IV (6), C. meleagridis (3), C. baileyi (1), and C. parvum (1), IIdA24G1	B (3) G (52)	D (22), SDD5 (9), Type IV (1), CHY1 (1), and EpbC (1)

Sequence analysis showed that certain genetic differences existed among sequences detected from different wild rodent species infected with the same parasite species. However, all 42 isolates shared >98% sequence similarity with the GenBank sequences under accession numbers GU319783, MW090935, PQ362262, MW090930, MK982463, JX294363, JX294365, and MW090928, and were successfully submitted to the NCBI database, obtaining accession numbers PZ437590–PZ437631. For C. parvum, the gp60-based identification showed 98.99% similarity with OK317684, and the sequence was deposited in NCBI under accession number PZ454254. Based on these results, representative sequences from this study (PZ437631, PZ437608, PZ437612, PZ437607, PZ437605, PZ437604, PZ437599, PZ437591, PZ437593, PZ437590, PZ437625) were used to construct a phylogenetic tree using the maximum-likelihood method together with reference sequences (Figure 2). The different parasite species each clustered with their respective reference sequences, indicating high homology.

Figure 2.

(a) Maximum-likelihood phylogenetic tree of Cryptosporidium species based on SSU rRNA gene sequence. (b) Maximum-likelihood phylogenetic tree of C. parvum partial genotype based on gp60 gene sequence. Sequences identified in this study are marked by filled red symbols.

3.4. Distribution of Giardia duodenalis assemblages

Sequence analysis of the TPI gene products from 55 G. duodenalis isolates identified Assemblage B (3/55, 5.45%) and Assemblage G (52/55, 94.55%), with Assemblage G being the dominant group, consistent with its characteristic host specificity (Table 4). In this study, Assemblage B was detected only in the Yuxi region, indicating a risk of zoonotic giardiasis transmission from wild rodents in this area.

Sequence analysis showed that the G. duodenalis isolates shared >99% sequence similarity with GenBank sequences under accession numbers AY368169 and PP236014. The isolates were submitted to NCBI and assigned accession numbers PZ411443–PZ411497. Based on these results, representative sequences from this study (PZ411443, PZ411444, PZ411447, PZ411457, and PZ411477) exhibited extremely strong homology with reference sequences in the phylogenetic tree (Figure 3), further confirming their assemblage assignment.

Figure 3.

Maximum-likelihood phylogenetic tree of Giardia duodenalis assemblages based on TPI gene sequences. Sequences identified in this study are marked by filled red symbols.

3.5. Distribution of Enterocytozoon bieneusi genotypes

Sequence analysis of the ITS gene products from 34 E. bieneusi isolates identified five genotypes (Table 4): genotype D (22/34, 64.70%), SDD5 (9/34, 26.47%), Type IV (1/34, 2.94%), CHY1 (1/34, 2.94%), and EpbC (1/34, 2.94%). The predominant genotype D belongs to the zoonotic group 1. Except for SDD5 (group 9) and CHY1 (group 10), the other three genotypes belong to group 1, which contains zoonotic genotypes, indicating a substantial zoonotic risk. Genotype D was the dominant genotype in Rattus norvegicus and Rattus tanezumi, while only genotype SDD5 was detected in Apodemus chevrieri, suggesting a relatively specific association between different wild rodent species and E. bieneusi genotypes.

Sequence analysis showed that the E. bieneusi isolates shared >98% sequence similarity with GenBank sequences under accession numbers PP158568, KJ651436, MN704935, PZ261611, and PP158571. The isolates were submitted to NCBI and assigned accession numbers PZ418477–PZ418510. Based on these results, a phylogenetic tree was constructed together with reference sequences from other groups to further clarify the group assignment of the five genotypes (Figure 4).

Figure 4.

Maximum-likelihood phylogenetic tree of Enterocytozoon bieneusi genotypes based on ITS gene sequences. Sequences identified in this study are marked by filled red symbols.

4. Discussion

The overall infection rate of Cryptosporidium in wild rodents in this study was 13.8%, which was higher than those reported in brown rats (Rattus norvegicus) in Heilongjiang, China (9.1%) (Zhao et al., 2018), wild rodents in Fujian and Henan provinces, China (8.2%) (Zhao et al., 2015), rodents across China (11.5%) (Lv et al., 2009), and wild rodents in China (3.4%) (Ni et al., 2021). The infection rate was similar to that reported in the same host species in the Canary Islands, Spain (13.86%) (García-Livia et al., 2020), but lower than those in pet rats in Yunnan Province, China (17.2%) (Li et al., 2026) and wild rodents in Malaysia (21.3%) (Tijjani et al., 2020). These differences may be partly explained by geographical and climatic variations. For instance, the high-altitude, cold environment of the eastern Tibetan Plateau (average elevation >4,000 m, annual mean temperature <0 °C) has been shown to prolong oocyst survival in the environment, potentially increasing transmission risks (Zuo et al., 2025). Conversely, lower temperatures may also reduce host activity and contact rates, leading to variable prevalence across regions (Zuo et al., 2025). In addition, host species composition and population density—particularly the dominance of Rattus norvegicus and Rattus tanezumi in the present study—likely contribute to the observed differences, as different rodent species exhibit varying susceptibilities and roles in pathogen maintenance.

The infection rate of G. duodenalis was 18.1%, which was higher than that in wild rodents in Fujian and Henan provinces (6.0%) (Zhao et al., 2015), but lower than that in wild rodents in northeastern Portugal (32.8%) (Lux et al., 2023) and far lower than the prevalence in wild rodents in Germany (73%) (Helmy et al., 2018). The infection rate of E. bieneusi was 11.2%, which was higher than that in laboratory rodents in China (4.8%) (Li et al., 2020), but lower than those in wild rodents in Inner Mongolia Autonomous Region and Liaoning Province, China (17.4%) (Zhao et al., 2024) and wild rodents in Xinjiang, Sichuan, and Guangdong provinces, China (12.2%) (Feng et al., 2024), and far lower than that in southwestern Poland (38.9%) (Perec-Matysiak et al., 2015). Notably, previous studies have demonstrated strong host specificity for G. duodenalis infections. For example, Zuo et al. (2025) reported that in small wild mammals on the eastern Tibetan Plateau, different host species harbored distinct parasite assemblages. In the present study, the dominant host species—Rattus norvegicus and Rattus tanezumi—are synanthropic rodents that frequently inhabit human settlements and livestock farms, which may increase their exposure to zoonotic pathogens and facilitate cross-species transmission. This ecological characteristic likely contributes to the observed infection patterns of G. duodenalis and E. bieneusi.

These differences may be attributed to variations in geographical location, habitat environment, rodent species, sample size, and study design. Moreover, as demonstrated in previous studies, factors such as altitude, climate (especially low temperature favoring environmental persistence of oocysts/cysts), sympatric livestock-wildlife interfaces, and human activities profoundly influence pathogen transmission dynamics (Zuo et al., 2025). In the present study, the infection rate of E. bieneusi showed a significant difference across different elevation intervals (χ² = 6.120, df = 2, p = 0.047), further indicating that elevation-related environmental changes may play a crucial role in shaping the distribution and prevalence of this pathogen in wild rodent populations. The samples collected in this study covered different latitudes and climate types, and the significant differences in prevalence further demonstrated that varying living environments and multiple conditional factors may influence the infection of these three pathogens in wild rodents. Nevertheless, the findings of this study are generally consistent with previous reports from around the world (Li et al., 2026), reinforcing the notion that wild rodents serve as important reservoirs for zoonotic parasites, and that regional ecological contexts must be carefully considered when interpreting prevalence data.

In this study, eight Cryptosporidium species were identified. Except for Cryptosporidium spp. rat (the rodent-adapted species with strong host specificity), the remaining species—C. muris (Wang et al., 2023), C. baileyi (Wu et al., 2021), C. meleagridis (Penumarthi et al., 2024), and C. parvum (Osborn et al., 1977) all pose a risk of cross-species transmission, demonstrating that wild rodents have the potential to transmit these pathogens to humans, livestock, and poultry through contaminated water, although direct transmission remains to be confirmed by epidemiological investigations (Feng and Xiao, 2017). The C. parvum identified in wild rodents is a known zoonotic pathogen and one of the two most common Cryptosporidium species infecting humans (Nader et al., 2019). Based on the gp60 gene, the genotype of C. parvum was identified as IIdA24G1, which is one of the most common genotypes of C. parvum (Bujila et al., 2024). This genotype has been found in multiple foodborne outbreaks of C. parvum infection in Sweden (Bujila et al., 2024; Gherasim et al., 2012) and has also been reported in a study on Cryptosporidium infection in lambs and goat kids in Spain (Quílez et al., 2008); however, it was detected for the first time in wild rodents in the present study. Regarding G. duodenalis, this study identified Assemblage B and Assemblage G. Among these, Assemblage B detected in the Yuxi region has a broad host range (Klotz et al., 2022) and was reported as early as 2013 in wild rodents on the Canary Islands, Spain (Fernandez-Alvarez et al., 2014). Therefore, more attention should be paid to the prevention and control of giardiasis in the Yuxi region where this assemblage was detected. For E. bieneusi, a total of five genotypes (D, SDD5, Type IV, CHY1, and EpbC) were identified in this study. The presence of these genotypes is not coincidental, as they have all been previously reported in wild rodents infected with E. bieneusi across various regions of China (Zhao et al., 2024; Zhao et al., 2020; Gao et al., 2024). Among them, genotypes D, Type IV, and EpbC belong to group 1 (Zhao et al., 2020). Given the widespread infection of wild rodents with zoonotic genotypes of E. bieneusi, more precise prevention and control strategies should be developed to curb its transmission and spread.

As wild rodents are the most frequently encountered wild animals in human daily life, the prevalence of zoonotic subtypes of the three pathogens detected in this study raises increasing public health concerns. With human encroachment into peri-urban areas, more infectious Cryptosporidium, G. duodenalis, and E. bieneusi may enter rodent populations (Egan et al., 2024). In particular, pathogen types with broad host ranges are likely to spread from infected wild rodents to humans or livestock over an expanding area. Based on the One Health concept, which recognizes that human health is inseparable from animal health and environmental health, it is imperative to implement hygiene and health promotion measures in urban environments and rural livestock farms to reduce both direct and indirect transmission of these rodent-associated pathogens (Feng et al., 2024).

Several limitations of this study should be acknowledged. Firstly, due to the inherent randomness of wild rodent capture, the sample sizes for certain rodent species were relatively small, which may have limited the statistical power to detect species-specific differences. Secondly, sampling was confined to seven locations within Yunnan Province, and thus the Prevalence reported herein may not be fully representative of the entire province. Furthermore our detection relied solely on PCR amplification of nucleic acids from intestinal contents, which detects DNA/RNA but does not confirm the presence of viable, infective parasites. Finally, the use of single-locus genotyping for G. duodenalis (TPI) and E. bieneusi (ITS) may have underestimated the true genetic diversity of these pathogens. Future studies incorporating multilocus sequence typing and viability assays are warranted to more comprehensively assess the zoonotic potential and transmission dynamics of these pathogens in wild rodent populations.

5. Conclusion

This study reveals the prevalence and genetic diversity of Cryptosporidium, G. duodenalis, and E. bieneusi in wild rodents in Yunnan Province, China. These three pathogens exhibit distinct geographical differences among wild rodent populations. Moreover, the detection of zoonotic subtypes of all three pathogens indicates that wild rodents may serve as potential reservoirs for infection of humans, livestock, and poultry. Therefore, public health education and management should be strengthened to reduce the probability of cryptosporidiosis, giardiasis, and E. bieneusi microsporidiosis infection. In future studies, more extensive wild rodent surveillance data and pathogen genetic diversity across broader geographic regions are needed to elucidate the transmission dynamics and public health risks of Cryptosporidium, G. duodenalis, and E. bieneusi.

Funding Statement

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the Yunnan Key Laboratory of Veterinary Etiological Biology (Grant No. 202449CE340019), Special Project for Basic Research of Young Talents in Education Department of Yunnan Province (Grant no. 2026J0394) and the Yunnan Fundamental Research Projects-General Program (Grant no. 202601AT070065).

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.

Ethics statement

The procedures followed in this study were reviewed and approved by the Life Science Ethics Committee of Yunnan Agricultural University (IACUC Issue no: APYNAU202503111).

Author contributions

RD: Data curation, Investigation, Writing – original draft, Formal analysis. FS: Data curation, Writing – original draft. ZS: Data curation, Resources, Investigation, Writing – original draft. PiW: Data curation, Investigation, Resources, Writing – original draft. HL: Writing – original draft, Resources, Investigation, Data curation. MD: Investigation, Writing – original draft, Validation, Resources. PeW: Validation, Investigation, Writing – original draft. XW: Writing – original draft, Resources, Data curation. FZ: Resources, Writing – review & editing, Funding acquisition. JY: Conceptualization, Data curation, Resources, Writing – review & editing. LW: Writing – review & editing, Supervision, Conceptualization.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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