Introduction

Cryptosporidium and Enterocytozoon bieneusi are the most important enteropathogens, which can infect a wide range of animals including cattle and sika deer (Cervus nippon) (Huang et al. 2014, 2018; Parsons et al. 2015; Ma et al. 2015; Naguib et al. 2015; Zhang et al. 2016; Baroudi et al. 2018; Wu et al. 2018; Amer et al. 2019; Lombardelli et al. 2019). Transmission of Cryptosporidium and E. bieneusi were mainly through ingestion of water and food contaminated by infective spores or oocysts, respectively (Wang et al. 2017). In general, the two pathogens infection in humans may cause acute or chronic diarrhea. However, their co-infection with immune-compromised individuals could cause death (Checkley et al. 2015). Moreover, they also have negative effects on the growth and cognitive functions of children (Pawlowic et al. 2017).

More than 96 Cryptosporidium species/genotypes and 240 distinct ITS E. bieneusi genotypes have been identified worldwide (Zhang et al. 2015a, 2016). C. parvum, C. andersoni, C. ryanae, and C. bovis are the four commonest species which are responsible for infections in cattle (Chalmers and Katzer 2013), and C. parvum mostly infects pre-weaned calves and causes diarrhea (Santín et al. 2004; Mercado et al. 2015). Only 12 Cryptosporidium species/genotypes (including Cryptosporidium deer genotype) have also been found in cervids around the world (Huang et al. 2018). E. bieneusi genotype group 1 were the zoonotic genotypes and group 2 were bovine-specific genotypes (Ma et al. 2015), but some genotypes (I, J, and BEB4) from group 2 also have recently been reported in humans (Li et al. 2016a). Of these, C. hominis and C. parvum are the commonest species for human cryptosporidiosis and group 1 genotypes of E. bieneusi are responsible for the majority of human microsporidiosis (Naguib et al. 2018; Zhang et al. 2018a). Sika deer and cattle are the important reservoir hosts of Cryptosporidium and E. bieneusi (Hu et al. 2017; Huang et al. 2018; Santin and Fayer 2015). To date, more than 10 Cryptosporidium species/genotypes and 35 distinct E. bieneusi genotypes have been found in cattle and sika deer (Wang et al. 2011a; Del Coco et al. 2014; Ma et al. 2014; Zhao et al. 2015; Jiang et al. 2015; Li et al. 2016b; Huang et al. 2017, 2018). Although some information regarding prevalence and molecular characterization of Cryptosporidium and E. bieneusi in dairy cattle and sika deer have been reported, the information regarding the two pathogens in dairy cattle and sika deer in China is also limited.

In this study, we further investigated the prevalence of Cryptosporidium and E. bieneusi and infection in dairy cattle and sika deer (Cervus nippon) in northern China and identified species/genotypes/subtypes of these pathogens. Moreover, the present study also aims to estimate their zoonotic potential for transmission to humans.

Materials and methods

Specimen collection and preparation

One thousand one hundred and thirty-nine fecal samples of dairy calves and sika deer (Cervus nippon) were randomly collected from farms from Heilongjiang Province (43° 26′~53° 33′ N, 121° 11′~135° 05′ E), Jilin Province (40° 50′~46° 19′ N, 121° 38′~131° 19′ E), Inner Mongolia (37° 24′~53° 33′ N, 97° 12′~126° 04′ E), Liaoning Province (38° 43′~43° 26′ N, 118° 53′~125° 46′ E), Northern China, between September 2017 and December 2018. All the sika deer are the same species. The pre-weaned sika deer was considered the young deer, the post-weaned sika deer was the adults. Every fresh fecal sample was collected from the rectum of each animal, and then placed into sterile gloves and transported back to the laboratory. The Stool DNA kit (OMEGA, USA) was used to extract the genomic DNAs of the fresh fecal samples. All the operations were strictly performed according to the manufacturer’s instructions. Then, DNA were stored at − 20 °C and analyzed by PCR. Information regarding geographic origin, breed, and age was recorded and listed in Tables 1, 2, 3, and 4.

Table 1 Distribution of Cryptosporidium species and E. bieneusi genotype in dairy calves in different farms from Heilongjiang Province
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Table 2 Distribution of Cryptosporidium species and E. bieneusi genotype in sika deer in different farms from four provinces, northern China
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Table 3 Prevalence of Cryptosporidium and E. bieneusi infection in dairy calves and sika deer in different related factors
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Table 4 Prevalence of Cryptosporidium and/or E. bieneusi in dairy calves and sika deer
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PCR amplification

The PCR based on the SSU rRNA gene was performed to determine the Cryptosporidium spp. species (Zhang et al. 2015a). The nested PCR of the ITS region of the ribosomal RNA (rRNA) gene was used to identify the E. bieneusi genotype (Wang et al. 2016). PCR reaction (25 μl) composed of 1× Ex Taq buffer (Mg2+ free), 2 mM MgCl2, 200 μM each deoxy-ribonucleoside triphosphate (dNTP), 0.4 μM of each primer, 0.625 U of Ex Taq DNA polymerase (TAKARA, Japan), and 2 μl of DNA template. The cycling conditions were 5 min at 95 °C, 35 cycles of 45 s at 94 °C, 45 s at suitable temperature, and 1 min at 72 °C, followed by final extension at 72 °C for 10 min. Both positive and negative controls were included in each test. Amplification products were observed under UV light after electrophoresis in 1.5% agarose gel containing GoldView (Solarbio, China).

Sequencing and phylogenetic analyses

Positive secondary PCR products were sent to Sangon Biotech Company (Shanghai, China) for sequencing. The Cryptosporidium and E. bieneusi species/subtypes were determined by alignments with known reference sequences available in GenBank using the BLAST (http://www.ncbi.nlm.nih.gov/BLAST/), and the computer program ClustalX 1.83. The phylogenetic trees were re-constructed by using neighbor-joining (NJ) method (Kimura two-parameter model) in Mega 5.0 (http://www.megasoftware.net/), and bootstrapping was performed using 1000 replicates.

Statistical analysis

The variation in Cryptosporidium and E. bieneusi prevalence (y) of dairy calves and sika deer of different geographical location (x1), season (x2), and age (x3) were analyzed by Chi-square in Statistical Analysis System (SAS, Version 9.0), respectively. Results were considered statistically significant when P < 0.05. Odds ratios (ORs) and their 95% confidence intervals (95% CIs) were also provided.

Data availability statement

Representative nucleotide sequences were submitted to GenBank under accession numbers: MH754165-MH754181 and MN056193-MN056201 for Cryptosporidium and MH732748-MH732751 and MN056202-MN056217 for E. bieneusi.

Committee of Ethics and Animal Welfare

This study was approved by the Animal Ethics Committee of Heilongjiang Bayi Agricultural University (registration protocol Mar 2017). The dairy calves and sika deer, which the feces were collected, were handled in accordance with good animal practices required by the Animal Ethics Procedures and Guidelines of the People’s Republic of China.

Results

A total of 62 (19.31%) out of 321 examined fecal samples of dairy calves were test positive for Cryptosporidium (Table 1), whereas only 9 (1.10%) samples were Cryptosporidium positive among 858 sika deer samples (Table 2). All the Cryptosporidium-positive samples in sika deer were detected from farm 18 (n = 8) from Jilin Province and farm 25 (n = 1) from Heilongjiang Province. Pre-weaned dairy calves (22.75%, 38/167) had a higher Cryptosporidium infection rate than post-weaned dairy calves (15.58%, 24/154), but prevalence of Cryptosporidium in young sika deer (0/31) was lower than adults (9/787) (Table 3). The prevalence of Cryptosporidium in dairy calves collected in different seasons ranging from 1.03% (1/97) in summer to 33.67% (33/98) in spring, and the difference was statistically significant (P < 0.0001) (Table 3). Moreover, no Cryptosporidium-positive samples were found in female sika deer; whereas, 9 (1.29%) male sika deer were detected as Cryptosporidium positive. Sequencing and phylogenetic analysis suggested five Cryptosporidium species/genotypes were detected in the present study. Of which, C. parvum (n = 46), C. ryanae (n = 5), C. bovis (n = 7), and C. andersoni (n = 4) were only found in dairy calves (Table 1), and Cryptosporidium deer genotype (n = 9; 8 from farm 18 in Jilin Province and 1 from farm 25 in Heilongjiang Province) was only found in sika deer (Table 2; Fig. 1).

Fig. 1
figure 1

Neighbor-joining (NJ) phylogenetic analyses of Cryptosporidium spp. based on the 830-bp sequence of the small subunit (SSU) rRNA gene (Kimura two-parameter model, 1000 replicates). Cryptosporidium isolates identified in this study are pointed out by a solid circle

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Of the 818 sika deer specimens analyzed, 111 (13.57%) were positive for E. bieneusi infection (Table 3). By sequence analysis, 6 known genotypes, namely JLD-III, JLD-IX, JLD-VII, EbpC, BEB6, and I) and 10 novel genotypes (namely LND-I and JLD-XV to JLD-XXIII) were identified (Table 2; Fig. 2). Prevalence of E. bieneusi in sika deer in different provinces ranges from 0% (0/106) in Inner Mongolia to 17.84% (96/538) in Jilin; the difference was statistically significant (P < 0.0001) (Table 3). Pre-weaned dairy calves (38.92%, 65/167) had a significant higher E. bieneusi infection rate than post-weaned dairy calves (18.18%, 28/154, P<0.0001), but prevalence of E. bieneusi in young sika deer (0%, 0/31) was lower than adults (14.10%, 111/787) (Table 3). Significant differences in infection rate were also observed among dairy calves collected during different seasons (Spring, 25.51%, 25/98; Summer, 20.62%, 20/97; Autumn, 45.35%, 39/86; Winter, 15.00%, 9/60; P = 0.0001; Table 3). In this study, prevalence of E. bieneusi in dairy calves was 28.97% (93/321), which was much higher than that in investigated sika deer (13.57%, 111/699), although only J, I, and BEB4 were identified in dairy calves (Table 1). Phylogenetic analysis revealed that EbpC was clustered into group 1d, and JLD-III, JLD-XIX, JLD-XVII, JLD-XXII, and JLD-XVI were classified in group 1a, and other 13 genotypes (JLD-IX, JLD-VII, BEB4, BEB6, I, J, LND-I, JLD-XV, JLD-IX, JLD-XXIII, JLD-XX, JLD-XVII, and JLD-XXI) were grouped in group 2 (Fig. 2).

Fig. 2
figure 2

Phylogenetic analyses of Enterocytozoon bieneusi using neighbor-joining (NJ) method (Kimura two-parameter model, 1000 replicates). E. bieneus identified in this study are indicated by a solid circle

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In this study, 4 (0.49%, n = 818) samples were detected as co-infection of E. bieneusi and Cryptosporidium in sika deer. All the samples were adult sika deer collected from Shuangyang City. Moreover, 18 (5.61%) out of 321 dairy calves were positive to E. bieneusi and Cryptosporodium (Table 4).

Discussion

In this study, the overall prevalence of Cryptosporidium infection in sika deer was 1.1%, which was lower than that in sika deer in Henan (2.41%, 2/83) and Jilin (Wang et al. 2008) but higher than the 0% in red deer and Pere David’s deer in Zhengzhou, China (Wang et al. 2008). It is also lower than that of the 1.3–80% prevalence of Cryptosporidium in other deer species in the USA, Nepal, Spain, Japan, Czech Republic, UK, Australia, and some regions of China (Deng and Cliver 1999; Feng et al. 2012; García-Presedo et al. 2013; Santin and Fayer 2015; Wells et al. 2015; Koehler et al. 2016; Kotkova et al. 2016; Kato et al. 2016; Huang et al. 2018). The overall 23.01% Cryptosporidium prevalence was found in dairy calves in this study, which was higher than the reported infection rates in Heilongjiang (19.15%, 158/825) (Zhao et al. 2014a), Anhui (14.9%, 52/350), Shanghai (12.5%, 55/440), Jiangsu (20.7%, 251/1215) (Chen and Qiu 2012), Henan (21.5%, 172/801) (Wang et al. 2011b), Ningxia (5.5%, 92/1688; 1.69%, 23/1366) (Huang et al. 2014; Zhang et al. 2015a), Gansu (4.6%, 58/1257) (Zhang et al. 2015a), and Shaanxi (20.2%, 52/258) (Qi et al. 2015) but lower than that in Heilongjiang (47.62%, 72/151) (Zhang et al. 2013) and Shanghai (37%, 303/818) (Cai et al. 2017). The differences in prevalence might partially be related to the timing of specimen collection, the different susceptibility of different animal species, different sample sizes, the ecological conditions, the different susceptibility of domesticated deer and wild deer, and host health status. In addition, geographical and seasonal differences can also affect the prevalence of Cryptosporidium.

Since Cryptosporidium infection in dairy cattle and sika deer were recorded, 13 genotypes/genotypes (C. parvum, C. andersoni, C. suis-like, C. hominis, C. bovis, C. ryanae, C. ubiquitum, C. muris, Cryptosporidium deer genotype, Cryptosporidium muskrat II genotype, Cryptosporidium suis-like genotype, Cryptosporidium hominis-like genotype, Cryptosporidium caribou genotype) have been found in sika deer worldwide (Jellison et al. 2009; Perz and Le Blancq 2001; García-Presedo et al. 2013; Kváč et al. 2014; Wells et al. 2015; Koehler et al. 2016; Kotkova et al. 2016), and at least 9 Cryptosporidium species/genotypes, namely C. andersoni, C. bovis, C. parvum, C. ryanae, C. ubiquitum, C. meleagridis, C. xiaoi, C. serpentis, and C. suis-like (Liu et al. 2009; Wang et al. 2011b; Chen and Huang 2012; Zhang et al. 2013; Cui et al. 2014; Ma et al. 2014, 2015) have been detected in cattle in China. However, only Cryptosporidium deer genotype was found in sika deer (Table 2) and only four Cryptosporidium spp., namely C. parvum (n = 71), C. ryanae (n = 7), C. bovis (n = 7), and C. andersoni (n = 4) were found in dairy calves in the present study (Table 1), which indicated that the five Cryptosporidium spp. were endemic in sika deer and dairy calves in investigated areas, respectively. The results of the present study also indicated that C. parvum (in 6 farms) was the commonest species on dairy cattle farms, which were similar with previous observations in pre-weaned calves in Ningxia (Huang et al. 2014), Henan (Wang et al. 2011b), and Xinjiang. Because C. parvum was frequently found in humans (Naguib et al. 2018), dairy calf has been indicated as one of the most important potential resources for human cryptosporidiosis. Cryptosporidium deer genotype was only identified in deer, including Red deer (UK), Roe deer (UK), White-tailed deer (USA, Czech Republic), and sika deer (Japan, China) (Robinson et al. 2011; Santin and Fayer 2015; Wells et al. 2015; Kotkova et al. 2016; Kato et al. 2016; Huang et al. 2018), which suggested that it seems to be a host-adapted genotype. Other deer-derived Cryptosporidium species/genotypes (including C. parvum) were not found in this study, which suggested that more sample size should be collected for further studies.

Presently, the prevalence of E. bieneusi in sika deer was 13.57% (111/818), which was higher than that in white-tailed deer in New York, USA (12.2%, 6/49) (Guo et al. 2014), sika deer in Jilin Province (7.1%, 23/326), China (Zhang et al. 2016), sambar deer (Rusa unicolor) (0%, 0/3), fallow deer (Dama dama) (0%, 0/7), and Pere David’s deer (Elaphurus davidianus) (0%, 0/3) in Sichuan, China (Li et al. 2016b), and sambar deer (Rusa unicolor) (4.1%, 25/516), red deer (Cervus elaphus) (0%, 0/77), and fallow deer (Dama dama) (0%, 0/17) in Australia (Zhang et al. 2018b) but lower than the 17.04–75% prevalence of E. bieneusi in various species of deer in the USA (Santin and Fayer 2015), Korea (Amer et al. 2019), and China (Zhao et al. 2014b; Zhang et al. 2015b; Li et al. 2016b; Huang et al. 2017; Song et al. 2018). In the present study, only four farms were positive for E. bieneusi, with infection rates ranging between 5.71 and 47.96%. The highest infection rate in sika deer was found in farm 18 (47.96%, 94/196), while the lowest (0%) was in farms 17 (0/34), 19 (0/59), 20 (0/58), 21 (0/60), 22 (0/58), 24 (0/44), 27 (0/58), and 28 (0/106) (Table 2). The overall infection rate of E. bieneusi was 30.16% (122/386) in dairy calves, which was lower than that in cattle in Jilin (37.6%, 35/93) (Zhang et al. 2011), but it was higher than that in cattle in Shandong (2.0%, 3/148) (Ma et al. 2015) and Heilongjiang (30.1%, 40/133 and 5.89%, 31/526) (Zhao et al. 2015; Jiang et al. 2015) and calves in Shanghai (26.5%, 214/809) (Tang et al. 2018) and Shaanxi 19.68% (73/371) (Wang et al. 2016). The infection rate in this study was higher than in most parts of China, which may be due to the difference in detection methods, the different susceptibility of different animal species, diagnostic methods, study design, and climate. E. bieneusi-positive samples were detected in 13 dairy cattle farms (all in Heilongjiang) and 4 sika deer farms (2 from Jilin, 1 from Heilongjiang, 1 from Liaoning) in this study, which may be due to worse livestock management, host health status, and animal welfare in these farms. Moreover, all the investigated sika deer were collected in farms in the present study which differ from most samples of deer reported previously which are collected from wild deer. In addition, the breeding periods of these deer in each farm may also affect the pathogen transmission in the farm, which will be investigated in further studies.

Sequence analysis revealed that three known genotypes were detected in dairy calves, including J (n = 63), I (n = 36), and BEB4 (n = 23) (Table 1). We found genotype J was predominant in dairy calves in this study. Genotype J was also the dominant genotype found in dairy cattle in Xinjiang (Qi et al. 2017), Henan, and Ningxia (Li et al. 2016a). Meanwhile, similar results have been reported in pre-weaned calves in Shanghai (Tang et al. 2018). In contrast, other results reported genotype I was the dominant genotype in dairy cattle in Henan and Shandong (Ma et al. 2015) and in beef and dairy cattle in Shaanxi (Wang et al. 2016), genotype O was the dominant genotype in dairy cattle in Heilongjiang (Zhao et al. 2015), and genotype CHN3 was the dominant genotype in cows in Jilin (Zhang et al. 2011). The differences in the distribution of E. bieneusi genotypes in cattle from different areas in China may be because of geographical and host segregation. More than 60 E. bieneusi genotypes have been found in deer worldwide (Guo et al. 2014; Zhao et al. 2014b; Santin and Fayer 2015; Zhang et al. 2015b, 2016, 2018b; Li et al. 2016b; Huang et al. 2017; Song et al. 2018; Amer et al. 2019). However, only 16 genotypes, including 6 known genotypes (JLD-III, JLD-IX, JLD-VII, EbpC, BEB6, and I) and 10 novel genotypes (namely LND-I and JLD-XV to JLD-XXIII), were identified in this study. Genotypes BEB4, J, I, and BEB6, clustered in group 2, were widely found in lots of animals; however, all of them have also been found in humans (Huang et al. 2017; Yang et al. 2018). Genotype EbpC, known to cause human microsporidiosis (Liu et al. 2017; Huang et al. 2017), and genotypes JLD-III, JLD-XIX, JLD-XVII, JLD-XXII, and JLD-XVI clustered in group 1, have zoonotic potential. The findings suggested that the investigated dairy calves and sika deer may play an important role in the transmission of E. bieneusi to humans and other animals. Further studies will investigate the molecular characterization of E. bieneusi in these animals’ feeders in order to further prove the evidence of transmission of E. bieneusi between humans and dairy calves or sika deer.

Conclusion

Cryptosporidium and E. bieneusi infection frequently occurred in dairy cattle and sika deer in Northern China. Co-infection of Cryptosporidium and E. bieneusi was present in investigated dairy calves and sika deer. Five Cryptosporidium species/genotypes were identified, of which C. parvum, C. ryanae, C. bovis, and C. andersoni were only found in dairy calves, and only Cryptosporidium deer genotype was found in sika deer. Moreover, J, I, and BEB4 ITS genotypes of E. bieneusi were found in dairy calves; 6 known genotypes (JLD-III, JLD-IX, JLD-VII, EbpC, BEB6, and I) and 10 novel genotypes (namely LND-I, JLD-XV to JLD-XXIII) were found in sika deer in this study. C. parvum and E. bieneusi genotype J were identified as the predominant species/genotypes in dairy calves, whereas the predominance of Cryptosporidium spp. and E. bieneusi in sika deer was Cryptosporidium deer genotype and BEB6, respectively. Genotypes EbpC, JLD-III, JLD-XIX, JLD-XVII, JLD-XXII, and JLD-XVI were clustered in group 1; the members of which have zoonotic potential, which also suggested that the investigated dairy calves and sika deer may play an important role in the transmission of Cryptosporidium and E. bieneusi to humans.