Background

Members of the Cryptosporidium genus of intestinal protozoa infect a wide range of hosts including humans, non-human primates, birds, amphibians, fish and reptiles [1]. Global concern was raised following an outbreak of cryptosporidiosis in Wisconsin, USA, in 1993, in which 403,000 individuals were affected and 100 fatalities were reported [2]. Only small quantities of oocysts are needed to establish infection, and once food or drinking water is contaminated with Cryptosporidium oocysts, or humans come into contact infected individuals or animals, cryptosporidiosis outbreaks may occur [3]. Cluster outbreaks of cryptosporidiosis reported worldwide have represented a great threat to public health [3, 4]. Symptoms of human cryptosporidiosis range from self-limiting diarrhea in (mainly) immunocompetent individuals, to persistent diarrhea (especially in children younger than 5-years-old). Cryptosporidiosis has been described as the second ranked causative agent of diarrhea in children in developing countries in southern Africa [5]. However, no effective drugs or vaccines have been developed, hence early detection and tracing the source of infection are of great importance for preventing outbreaks of cryptosporidiosis.

Globally, cryptosporidiosis is more endemic in developing countries than in developed countries [6]. In China, the reported human prevalence of Cryptosporidium has ranged from 0.0 to 16.5% since the first two cases were reported in Jiangsu Province in 1987, and a strong correlation was found between the infection and HIV/AIDS [7,8,9,10,11,12]. Moreover, Cryptosporidium was responsible for about 1.4 to 10.4% of diarrhea episodes in China [9].

To date, at least 39 species of Cryptosporidium have been identified [13,14,15,16], and at least 21 species are considered zoonotic, among which C. hominis and C. parvum are the two main pathogens causing cryptosporidiosis in humans [17]. However, in recent years, with the development of molecular biological technologies, the number of cryptosporidiosis cases confirmed to be caused by other Cryptosporidium species has increased, and some species or genotypes are predominant in specific countries or regions. For example, studies in Jiangsu and Shanghai, China, revealed unusually high prevalence of C. andersoni in diarrhea patients [17, 18]. C. cuniculus, for which the natural host is rabbit, was found in patients with diarrhea in the UK [19], and C. xiaoi, mainly found in sheep and goat, was detected in HIV/AIDS sufferers with clinical manifestations including vomiting [20]. To our knowledge, seven species of Cryptosporidium—C. hominis, C. parvum, C. andersoni, C. meleagridis, C. felis, C. canis and C. suis have been identified in humans in China [1].

At present, cryptosporidiosis is not included in the National Disease Reporting System in China [21], and Cryptosporidium oocyst examination is not performed routinely on patients with diarrhea or other gastrointestinal symptoms, so the prevalence of Cryptosporidium in China may be underestimated. The present study aimed to investigate the prevalence, risk factors and species/genotype distribution of Cryptosporidium among a rural population in China, which are of great relevance to public health.

Methods

Study area

Guangxi is situated in southern China, between 22°54′–26°24′ N and 104°26′–112°04′ E. It borders the Beibu Gulf to the south, and is adjacent to Vietnam in the southwest. Binyang County, which belongs to Nanning City of Guangxi Zhuang Autonomous Region, is located in the south–central part of Guangxi and the northeast part of Nanning City. It is high-altitude in the south and low-altitude in the north, surrounded by earthy mountains to the east, south and west, with an open basin in the middle and a large alluvial plain. It has a subtropical monsoon climate with abundant light and heat, long summer and short winter, and abundant rainfall.

Study design and population

A cross-sectional survey was carried out to investigate the prevalence of, risk factors for, and species/genotype distribution of Cryptosporidium in a rural population in Binyang County. The study was conducted in two villages (A and B) from two towns (village A from town C1, and village B from town C2) selected at random. A total of 400 individuals were involved in our study. All participants were grouped according to gender, age, education level, and so on. Males accounted for 48.8% (195/400) and females 51.2% (205/400) of participants. The average age was 35.7 ± 25.3, ranging from 7 months to 89 years old. Participants with primary school education and below accounted for 56.8% (227/400), followed by junior high school level (36.0%; 144/400), and high school education and above (7.2%; 29/400); 65.3% (261/400) of participants reported raising animals at home. Basic information on all participants is shown in Table 1.

Table 1 Basic information on participants and assessment of risk factors for Cryptosporidium infection
Full size table

Sample collection and questionnaire

From August to December 2016, 400 fresh fecal samples (>5 g) were collected from villagers in the two selected villages. Samples were taken from the middle of the stool to avoid contamination from soil, animal manure or other human feces, and transported to the laboratory of the local Center for Disease Control within 4 h of collection. Samples were mixed with 2.5% potassium dichromate and stored in a refrigerator at 4 °C. All samples were eventually sent to the laboratory of the National Institute of Parasitic Diseases, Center for Disease Control and Prevention of China. During sampling, villagers involved in the survey were presented with a structured questionnaire to collect data on sociodemographic factors (gender, age, education level), and possible risk factors (drinking and eating habits, hygiene habits, animals raising), as well as common clinical symptoms (diarrhea).

DNA extraction

Fecal samples (180–220 mg) were washed with deionized water and centrifuged at 20,000 g for 10 min three times to remove potassium dichromate, and DNA was extracted using a QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. To increase the DNA yield, the lysis temperature was adjusted to 95 °C according to the manufacturer’s recommendation. The final 200 μl DNA samples were stored at − 30 °C for subsequent Polymerase Chain Reaction (PCR) analysis.

PCR amplification and sequencing

Nested PCR was used to identify Cryptosporidium species/genotype, initially by amplifying part of the small-subunit rRNA (SSU rRNA) gene (approximately 840 bp) of Cryptosporidium using primer sets and cycling parameters described previously [22]. Primers used to amplify an 805-bp fragment of the 60-kDa glycoprotein-encoding (gp60) gene of C. viatorum were described by Stensvold [23]. Heat shock protein 70 (hsp70) and actin genes of C. occultus were amplified using primers described by Sulaiman [24, 25] (see Additional file 1: Table S1).

All DNA samples were analyzed at least three times. A Cryptosporidium- positive DNA (cattle-derived C. andersoni) sample and nuclease-free water were used as positive and negative controls, respectively, and PCR products were analyzed by 2% agarose gel electrophoresis and ethidium bromide staining. Products of the expected size were analyzed using an ABI 3730 DNA Analyzer (Applied Biosystems, Foster City, USA) and Big Dye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems). ContigExpress software was used for sequence assembly and wave peak evaluation. Sequences were searched using the basic local alignment search tool (BLAST) and aligned with representative Cryptosporidium sequences.

Phylogenetic analysis

Phylogenetic trees were constructed using MEGA6.0 software [26] based on 1000 bootstrap replicates from sequences obtained in this study and representative Cryptosporidium sequences downloaded from the NCBI database. The subtype of C. viatorum was designated using the subtype naming guidelines [24].

Statistical analysis

SPSS 16.0 software was used for statistical analyses. Fisher’s exact test were performed to compare infection rates between groups. Differences were regarded as statistically significant when P < 0.05.

Results

The prevalence of and risk factors for Cryptosporidium infection

The prevalence of Cryptosporidium was 0.5% (2/400). All 400 participants completed the questionnaire effectively. In the present study, several factors were analyzed. Univariate analysis of risk factors for Cryptosporidium are summarized in Table 1. No statistical association was found between these factors and Cryptosporidium infection.

Both infected individuals were males from two villages. The person infected with C. viatorum was a 60-year-old man with gastric cancer who raised dogs. The other, infected with C. occultus, was a child younger than 5 years old who often drank unboiled water, and dogs and chickens were raised in his home (Table 2). Both Cryptosporidium-infected individuals failed to display gastrointestinal symptoms.

Table 2 Characteristics of the two Cryptosporidium infection cases identified in Guangxi, China
Full size table

Genotype of Cryptosporidium spp

Two samples were identified as Cryptosporidium-positive, and they corresponded to C. viatorum and C. occultus respectively, based on the SSU rRNA gene sequences. The gp60 gene of C. viatorum and actin and hsp70 genes of C. occultus were also successfully amplified. A novel subtype of C. viatorum was found and named XVaA3h.

Cryptosporidium sequences identified in the present study were submitted to GenBank under accession numbers MH807495 (C. viatorum SSU rRNA gene), MH807494 (C. viatorum gp60 gene), MH807493 (C. occultus SSU rRNA gene), MN177696 (C. occultus actin gene) and MN177697 (C. occultus hsp70 gene),

Phylogenetic analysis of C. viatorum and C. occultus

Phylogenetic analysis based on SSU rRNA gene sequences confirmed that one sample belonged to C. viatorum, and it was closely related to an isolate identified previously in a human in Kenya (accession no. JX978271) (Fig. 1), with one genetic variation. Sequence analysis based on the gp60 gene revealed three contiguous TCA trinucleotides in the serine repeat region, and two genetic variations in the non-repetitive region compared with an isolate from Nepal (accession no. KP115940). The sequence was designated XVaA3h (accession no. MH807494) (Fig. 2).

Fig. 1
figure 1

Phylogenetic relationships between Cryptosporidium species. Phylogenetic tree based on the partial SSU rRNA gene sequence of Cryptosporidium species constructed by the neighbor-joining distance method with 1000 bootstrap replicates using MEGA 6.0 software. Individual GenBank accession numbers precede species, which are followed by host names. Squares represent Cryptosporidium sequences from this study

Full size image

The other positive sample clustered with C. occultus sequences isolated from deer in China (accession no. KX259135) and Meriones unguiculatus in the Czech Republic (accession nos. MG699171 and MG699175) based on SSU rRNA, actin and hsp70 gene sequences, with which it shares > 99% sequence identity (Figs. 1 and 3).

Fig. 2
figure 2

Phylogenetic relationships between different subtypes of C. viatorum. Phylogenetic tree based on gp60 gene sequences of C. viatorum constructed by the neighbor-joining distance method with 1000 bootstrap replicates using MEGA 6.0 software. Individual GenBank accession numbers precede species and subtype names, which are followed by host names or water. The square indicates the C. viatorum subtype identified from a stool DNA sample in this study

Full size image
Fig. 3
figure 3

Phylogenetic relationships between different species of Cryptosporidium based on actin gene (a) and heat shock protein 70 (hsp70) gene (b) sequences. The phylogenetic tree was constructed by the neighbor-joining distance method with 1000 bootstrap replicates using MEGA 6.0 software. Individual GenBank accession numbers precede species names, which are followed by host names. The square indicates C. occultus identified from a stool DNA sample in this study

Full size image

Discussion

Traditionally, the identification of Cryptosporidium mainly depends on microscopy, which is time-consuming and experience-requiring, and this method is not applicable in the case of mild infection [27]. Compared with traditional morphological methods, molecular techniques are more sensitive for detection of Cryptosporidium in feces [17]. Nested PCR has been widely used in the detection of Cryptosporidium. Molecular epidemiology study on Cryptosporidium has been conducted in several provinces/cities/autonomous regions of China, including Guangxi, Guangdong, Henan, Hubei, Jiangsu, Shanghai, Xinjiang and Yunnan, with the prevalence ranging from 0.0 to 16.5% [7, 8, 10,11,12, 17, 18, 28,29,30] (Table 3). In the present study, two Cryptosporidium-positive samples were detected based on the SSU rRNA gene, revealing a prevalence of 0.5%, which is lower than that reported previously for a rural population in southwest China (12.6%) and diarrhea patients in Jiangsu (9.9%) and Shanghai (13.5%) [17, 18, 31]. Comparing with the prevalence of Cryptosporidium in humans in other countries, this is lower than that reported for children in Egypt (1.4%), Cambodia (7.7%), and rural Ghana (5.2%) and diarrhea patients in Canada (15.7%) [32,33,34,35], but higher than that reported in a population-based laboratory surveillance in a large Canadian health region (~ 6.0 per 100,000 members of the population per year) [36]. The prevalence of Cryptosporidium varies from country to country, and even within different areas in the same region, which may be related to the immune status, living environment, and even sampling time of the selected subjects.

Table 3 Species, positive rate, and risk factors associated with Cryptosporidium infection in humans in China
Full size table

Cryptosporidium is a common opportunistic pathogen in immunodeficient/immunocompromised individuals, especially HIV-infected patients, cancer patients and children younger than 5 years old [10, 29, 37]. In the present study, one case was a cancer patient and another was a child younger than 5 years old, both of whom were susceptible to Cryptosporidium. Age is one of the most important factors for cryptosporidiosis [7, 11], but no statistical association was observed in our present study, which could be mostly attributed to the population groups. Indeed, a previous study conducted in an underdeveloped rural community of southwest China found no association between infection and age groups [38] .

Diarrhea is the most common clinical symptom associated with Cryptosporidium infection, and a statistically significant association between Cryptosporidium infection and diarrhea has been reported previously [39]. However, no statistical association was observed between Cryptosporidium infection and diarrhea in the present study (p = 1.000) which could be attributed to the species or subtypes of Cryptosporidium. The relationship between diarrhea and these two Cryptosporidium species (C. viatorum and C. occultus) remains unclear due to the lack of cases.

Cryptosporidium is a waterborne parasite and listed as one of the indispensable indicators of water quality according to the Hygienic Standards for Drinking Water in China (GB 5479–2006). However, in this study, statistically significant difference was not observed between individuals drinking unboiled water or not, which is contrary to the results of a study conducted in Russia [40]. The reason may be that people drinking boiled water in the present study accounted for 60.2% (241/400) of all the respondents. Although Cryptosporidium oocysts are resistant to low temperature and chlorine disinfectant in the external environment, heating at 65–70 °C for 30 min can kill Cryptosporidium oocysts. Some other factors (e.g. gender, education level, drinking water source, washing hands before meals, eating unwashed vegetables and fruits, and raising animals) were also analyzed, but no statistical correlation was found between those factors and Cryptosporidium infection.

Globally, C. hominis and C. parvum are the most common species causing cryptosporidiosis in humans, accounting for > 90% of cases [41]. Seven species of Cryptosporidium have been identified in humans in China with C. hominis and C. parvum being the commonest, but the distribution of Cryptosporidium species in China varies by region; C. hominis is mainly present in the east, while C. parvum is mainly found in the south–central region (Hunan Province) [42,43,44]. In the present study, C. viatorum and C. occultus were identified for the first time in humans in China.

C. viatorum, previously believed to be a human-specific pathogen, was first isolated from travelers returning to Britain from India in 2012 [45]. C. viatorum has since been identified in people from or who travelled to Bangladesh, Barbados, Colombia, Dubai, Ethiopia, Guatemala, India, Kenya, Nepal, Nigeria, Pakistan and Australia [20, 23, 45,46,47,48,49,50,51,52,53]. Recently, researchers in Australia and China identified C. viatorum in rats, underlining its zoonotic potential [54, 55]. It was also identified in untreated water in China [56]. In the present study, we identified the subtype XVaA3h of C. viatorum in a human for the first time (Table 4).

Table 4 C. viatorum identified in humans, animals, and water samples worldwide
Full size table

Based on the gp60 gene sequence, which is applied in subtype analysis of several pathogenic Cryptosporidium species, including C. hominis, C. parvum, C. ubiquitum, C. meleagridis, C. viatorum, Cryptosporidium skunk genotype and Cryptosporidium chipmunk genotype I [56], C. viatorum has evolved into 13 subtypes, named XVaA3a–h, XVaA6, XVbA2G1, XVcA2G1a, XVcA2G1b and XVdA3. The sequence of the gp60 gene of XVaA3h identified in our study shares > 98% identity with other C. viatorum subtypes, isolated from humans in Nepal (accession no. KP115940), Guatemala (accession no. KP115938), India (accession nos. KP115941 and KP115936) and Kenya (accession no. KP115939), and is 97% identical to an isolate from waste water in China (accession no. KX190061). High genetic identity among C. viatorum subtypes XVaA3a–h may suggest that C. viatorum recently spread from the source population and is now spreading further through global human travel [54]. However, no travel history was reported in our study. Perhaps animals or contaminated water contribute to the infection, considering the fact that C. viatorum has been identified in animals and water [54,55,56].

C. occultus, named by Martin Kvác in 2018 [15], and was previously known as Cryptosporidium suis-like, due to the close phylogenetic relationship with C. suis. However, oocysts of C. occultus are morphologically indistinguishable from other species/genotypes, while oocysts of C. occultus are smaller than those of C. suis [15]. Previous phylogenetic analyses based on SSU rRNA, actin, and hsp70 genes revealed 0.3, 2.0, and 2.1% sequence divergence from C. suis, respectively, hence C. occultus and C. suis can be distinguished genetically [15].

Although C. occultus has a wide host range (cattle, yak, water buffalo, and rat), one study showed that rats are the main host [15]. To date, only two cases of humans infected with C. occultus have been reported, in Canada and in England [57, 58]. C. occultus has been detected in cattle, yak, and wild rats in China [55, 59, 60]. Our present study is the first report of C. occultus in a human in China. However, the transmission route is not clear due to limited detection of C. occultus in animals and humans.

Various zoonotic Cryptosporidium species (C. hominis, C. parvum, C. meleagridis, C. andersoni, C. felis, C. ubiquitum, Cryptosporidium horse genotype, C. suis and C. viatorum) have been found in different water bodies that may be contaminated by animal and human feces, indicating a transmission cycle of Cryptosporidium among humans, animals and water [1, 61]. Study also suggested that water may be contaminated with C. occultus [15]. To better understand the transmission dynamics of cryptosporidiosis and provide targeted preventive measures, further molecular investigations of Cryptosporidium in animal and water samples are required.

Conclusions

The present study identified C. viatorum and C. occultus in humans in China for the first time, and also documents the novel C. viatorum subtype XVaA3h, expanding the known range of Cryptosporidium species infecting humans worldwide. Those two Cryptosporidium species have both been identified in animals, suggesting the possibility of zoonotic transmission of Cryptosporidium in this locale. Further systematic molecular investigation of Cryptosporidium should focus on humans, animals and water samples to clarify the transmission routes.