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. 2025:32:35.
doi: 10.1051/parasite/2025029. Epub 2025 Jun 11.

Prevalence and characterization of Cryptosporidium in sika deer from Northern China

Yan Tang #  1 , Nian-Yu Xue #  2 , Yang Gao  3 , Zhen-Qiu Gao  4 , Hong-Di Zhuang  5 , Guang-Rong Bao  6 , Hong-Wei Cao  4 , Jing Liu #  7 , Jian-Ming Li  5 , Shuo Liu  6
Affiliations

Prevalence and characterization of Cryptosporidium in sika deer from Northern China

Yan Tang et al. Parasite. 2025.

Abstract
in English, French

Cryptosporidium spp. are important zoonotic parasites that can cause moderate to severe diarrhea in humans and animals. However, the epidemiological data of Cryptosporidium in sika deer in China need to be updated. In this study, a total of 466 fecal samples were collected from sika deer in Shandong, Jilin, Liaoning, and Heilongjiang provinces. Nested PCR was used to amplify the SSU rRNA gene to detect Cryptosporidium spp. The results showed that the overall infection rate of Cryptosporidium spp. was 14.81%, with no significant differences among regions (p = 0.05). The highest infection rate was found in Heilongjiang Province (23.60%) and the lowest in Jilin Province (10.71%). The infection rate in summer (23.61%) seemed higher than that in autumn (13.20%), but the difference was not statistically significant (p = 0.30). Notably, young sika deer showed a significantly higher infection rate (28.21%) compared to adults (10.32%) (p < 0.0001). Sequence analysis identified two Cryptosporidium species/genotypes: Cryptosporidium deer genotype (98.55%) and Cryptosporidium ubiquitum (1.45%). Subtyping revealed that the C. ubiquitum isolate belonged to the zoonotic XIIa subtype. These findings provide new insights into the prevalence and genetic diversity of Cryptosporidium in sika deer and suggest that sika deer may act as a potential reservoir for zoonotic Cryptosporidium transmission.

Title: Prévalence et caractérisation de Cryptosporidium chez le cerf sika du nord de la Chine.

Abstract: Les Cryptosporidium spp. sont d’importants parasites zoonotiques pouvant provoquer des diarrhées modérées à sévères chez l’homme et l’animal. Cependant, les données épidémiologiques concernant Cryptosporidium chez le cerf sika en Chine doivent être mises à jour. Dans cette étude, 466 échantillons fécaux ont été prélevés sur des cerfs sika dans les provinces du Shandong, du Jilin, du Liaoning et du Heilongjiang. La PCR nichée a été utilisée pour amplifier le gène de l’ARNr SSU afin de détecter les Cryptosporidium spp. Les résultats ont montré que le taux d’infection global par Cryptosporidium spp. était de 14,81 %, sans différence significative entre les régions (p = 0,05). Le taux d’infection le plus élevé a été observé dans la province du Heilongjiang (23,60 %) et le plus faible dans la province du Jilin (10,71 %). Le taux d’infection en été (23,61 %) semblait plus élevé qu’en automne (13,20 %), mais la différence n’était pas statistiquement significative (p = 0,30). De manière notable, les jeunes cerfs sika ont montré un taux d’infection significativement plus élevé (28,21 %) que les adultes (10,32 %) (p < 0,0001). L’analyse de séquence a identifié deux espèces/génotypes de Cryptosporidium : Cryptosporidium génotype « deer » (98,55 %) et Cryptosporidium ubiquitum (1,45 %). Le sous-typage a révélé que l’isolat de C. ubiquitum appartenait au sous-type zoonotique XIIa. Ces résultats apportent de nouvelles perspectives sur la prévalence et la diversité génétique de Cryptosporidium chez le cerf sika et suggèrent que le cerf sika pourrait agir comme un réservoir potentiel pour la transmission zoonotique de Cryptosporidium.

Keywords: China; Cryptosporidium sp.; Prevalence; Sika deer; Subtype.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflicts of interest.

Figures

Figure 1
Figure 1
A map of the People’s Republic of China showing the sampling regions marked with letters.
Figure 2
Figure 2
Phylogenetic relationships between the sequences in this study and the reference sequences of Cryptosporidium in GenBank and an outgroup, using a neighbor-joining (NJ) method. The genetic distance was calculated based on the Kimura 2-parameter model. Representative nucleotide sequences identified in this study are marked by black dots. The numbers on the branches represent the bootstrap percentage values for 1,000 replicates and are shown in the tree with values greater than 50%.
See this image and copyright information in PMC

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