Cryptosporidium is an important zoonotic parasite that causes diarrhea in humans and animals worldwide. Previous studies suggested geographic differences in the distribution of Cryptosporidium species in sheep. However, molecular characterization studies of Cryptosporidium species in sheep have been carried out in only a few provinces in China, and the limited data available do not reflect the real situation. In this study, five districts, covering most areas where sheep are bred in China, were selected for examination of Cryptosporidium species, and Cryptosporidium infections were detected at all farms assessed, suggesting that Cryptosporidium is widespread in sheep in China. We also found geographic differences in the distribution of Cryptosporidium species but did not detect any differences between sheep age groups or seasons. Subtyping analyses showed that all of the subtypes identified in this study have been reported in humans, suggesting that sheep may be a potential source of zoonotic cryptosporidiosis.
KEYWORDS: Cryptosporidium spp., molecular epidemiology, sheep, China
ABSTRACT
In this study, we assessed the prevalence and genetic characteristics of Cryptosporidium in sheep from 10 provinces in China. Fecal samples from 1,035 sheep originating from 16 farms were collected, and 295 (28.5%) were found to be Cryptosporidium positive by nested PCR. Cryptosporidium was detected at all farms, with infection rates between 5.7% and 50.0%. Three Cryptosporidium species were identified, including Cryptosporidium xiaoi (73.2%, 216/295), Cryptosporidium ubiquitum (21.7%, 64/295), and Cryptosporidium parvum (5.1%, 15/295). The distribution of Cryptosporidium species differed by province and by farm. All three species were detected in lambs and adult sheep but the highest infection rate was found in postweaned lambs. All three species were detected in all four seasons, with the highest prevalence found in autumn. Four C. parvum subtypes (IIaA15G2R1, IIaA17G2R1, IIdA18G1, and IIdA19G1) and one C. ubiquitum subtype (XIIa) were identified. For most provinces in this study, we are not aware of a previously published description or molecular characterization of Cryptosporidium infections in sheep. This information will improve our knowledge and understanding of the epidemiology of cryptosporidiosis in China.
IMPORTANCE Cryptosporidium is an important zoonotic parasite that causes diarrhea in humans and animals worldwide. Previous studies suggested geographic differences in the distribution of Cryptosporidium species in sheep. However, molecular characterization studies of Cryptosporidium species in sheep have been carried out in only a few provinces in China, and the limited data available do not reflect the real situation. In this study, five districts, covering most areas where sheep are bred in China, were selected for examination of Cryptosporidium species, and Cryptosporidium infections were detected at all farms assessed, suggesting that Cryptosporidium is widespread in sheep in China. We also found geographic differences in the distribution of Cryptosporidium species but did not detect any differences between sheep age groups or seasons. Subtyping analyses showed that all of the subtypes identified in this study have been reported in humans, suggesting that sheep may be a potential source of zoonotic cryptosporidiosis.
INTRODUCTION
Cryptosporidium is a protozoan parasite that infects humans and many animals. It is the second leading cause of diarrhea in children, after rotavirus (1). Cryptosporidiosis is now considered an important disease, causing diarrhea in neonatal ruminants worldwide and clinical characteristics in animals ranging from asymptomatic infections to death (2). Cryptosporidiosis has caused great economic losses to farmers, in part due to the lack of effective prophylactic or therapeutic treatment options for livestock (3).
Cryptosporidium is a major cause of diarrhea and is associated with high morbidity and mortality in lambs. Oocyst excretion by healthy adults and lambs can serve as a source of infection for other animals (2). The first Cryptosporidium infection in diarrheic lambs was described in Australia (2) and the parasite has since been reported worldwide, with prevalence rates in sheep between 5% and 70% (4). To date, many species and genotypes have been identified in sheep using molecular tools. The most prevalent species in sheep are Cryptosporidium ubiquitum, C. parvum, and C. xiaoi (2). Other species that have also been found in sheep include C. bovis, C. hominis, C. andersoni, C. suis, C. fayeri, C. baileyi, C. ryanae, C. scrofarum, C. canis, and Cryptosporidium sheep genotype 1 (5–7).
According to statistical data from the Food and Agriculture Organization of the United Nations (FAO), China has the largest sheep population in the world, with approximately 162.06 million sheep reported in China at the end of 2016 (http://www.fao.org/faostat/en/#data/QA). However, there have been no systematic studies of cryptosporidiosis in sheep, and the molecular characterization of Cryptosporidium species in sheep in China was previously not complete. Previous studies showed that C. ubiquitum is the major species in sheep in Henan and Sichuan (8, 9). In contrast, C. xiaoi was the most prevalent species in sheep in Inner Mongolia and Qinghai (10, 11). Other species, such as C. andersoni, C. canis, and C. parvum, have also been found in China (7–9). Given the scarce data on the distribution of Cryptosporidium in sheep in China, the present study aimed to improve our knowledge of cryptosporidiosis epidemiology in China and to evaluate the potential threat of Cryptosporidium infections in sheep to human health.
RESULTS
Cryptosporidium infection in different regions of China.
In this study, the overall prevalence of Cryptosporidium infection was 28.5% (295/1035; 95% confidence interval [CI], 25.8 to 31.4) (Table 1). All positive PCR products were sequenced for Cryptosporidium species determination using BLAST (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Of the three species detected, C. xiaoi (73.2%, 216/295) was the most prevalent, followed by C. ubiquitum (21.7%, 64/295) and C. parvum (5.1%, 15/295) (Table 1). The phylogenetic tree constructed using Molecular Evolutionary Genetics Analysis (MEGA) software is shown in Fig. 1.
TABLE 1.
Prevalence and distribution of Cryptosporidium species in different regions of China
| Region | No. of samples | No. positive (%) | 95% CI | Species (%) |
||
|---|---|---|---|---|---|---|
| C. xiaoi | C. ubiquitum | C. parvum | ||||
| Central China | 35 | 11 (31.4) | 16.9–49.3 | 7 (63.6) | 0 | 4 (36.4) |
| Eastern China | 468 | 125 (26.7) | 22.8–31.0 | 103 (82.4) | 16 (12.8) | 6 (4.8) |
| Northern China | 166 | 40 (24.1) | 17.8–31.3 | 29 (72.5) | 8 (20.0) | 3 (7.5) |
| Northeast China | 70 | 23 (32.9) | 22.1–45.1 | 4 (17.4) | 17 (73.9) | 2 (8.7) |
| Northwest China | 296 | 96 (32.4) | 27.1–38.1 | 73 (74.0) | 23 (26.0) | 0 |
| Total | 1,035 | 295 (28.5) | 25.8–31.4 | 216 (73.2) | 64 (21.7) | 15 (5.1) |
FIG 1.
Phylogenetic analysis of Cryptosporidium spp. based on small subunit (SSU) rRNA gene sequences. The evolutionary history was inferred using the neighbor-joining method, and evolutionary analyses were conducted in MEGA 7.0. The percentages of replicate trees in which the associated taxa clustered together in the bootstrap test (1,000 replicates) are shown next to the branches. Bootstrap values >50% are shown. ▲, partial sequence obtained in the present study.
Of the five regions tested for the presence of Cryptosporidium infections in sheep, the highest prevalence was found in northeast China (32.9%, 23/70; 95% CI, 22.1 to 45.1), followed by northwest China (32.4%, 96/296; 95%, CI, 27.1 to 38.1), central China (31.4%, 11/35; 95% CI, 16.9 to 49.3), eastern China (26.7%, 125/468; 95% CI, 22.8 to 31.0), and northern China (24.1%, 40/166; 95% CI, 17.8 to 31.3). However, the difference between regions was not statistically significant (P > 0.05) (Table 1). C. xiaoi was the most prevalent species in all regions except northeast China, where C. ubiquitum was the most prevalent species. All three species were found in all regions except central China, where we did not detect C. ubiquitum, and western China, where we did not detect C. parvum (Table 1).
Cryptosporidium infection in different provinces of China.
Cryptosporidium was found in all provinces assessed, with prevalence rates ranging from 6.6% to 45.5%. The highest Cryptosporidium prevalence was found in Ningxia (45.5%, 55/121; 95% CI, 36.4 to 54.8), followed by Xinjiang (36.4%, 36/99) (95% CI, 36.9 to 46.6), Jilin (32.9%, 23/70; 95% CI, 22.1 to 45.1), and Henan (31.4%, 11/35; 95% CI, 16.9 to 49.3); however, the difference was not statistically significant (P > 0.05). There was also no significant difference between Jilin, Henan, Beijing (29.7%, 19/64; 95% CI, 18.9 to 42.4), Shanghai (29.3%, 86/294; 95% CI, 24.1 to 34.8), Shandong (23.8%, 29/122; 95% CI, 16.5 to 32.3), Inner Mongolia (21.6%, 21/102; 95% CI, 13.2 to 29.7), and Anhui (19.2%, 10/52; 95% CI, 9.6 to 32.5) (P > 0.05). The prevalence in Xinjiang was not significantly different from that in Jilin, Henan, Beijing, or Shanghai (P > 0.05) but was significantly different from that in Shandong, Inner Mongolia, and Anhui (P < 0.001). The lowest prevalence was found in Qinghai (6.6%, 5/76) (95% CI, 2.2 to 14.7), which was significantly different from that in the other provinces (P < 0.001) (Table 2). C. xiaoi was the most prevalent species in all provinces except Xinjiang and Jilin, where C. ubiquitum was the most prevalent species. All three species identified were found in Jilin, Beijing, and Shanghai. C. ubiquitum was not detected in Henan, Shandong, or Anhui, whereas C. parvum was not detected in Ningxia, Xinjiang, or Inner Mongolia. Only one species (C. xiaoi) was found in Qinghai Province (Table 2).
TABLE 2.
Prevalence and distribution of Cryptosporidium species in different provinces of China
| Region | Province/city | No. of samples | No. positive (%) | 95% CI | Species (%) |
||
|---|---|---|---|---|---|---|---|
| C. xiaoi | C. ubiquitum | C. parvum | |||||
| Central China | Henan | 35 | 11 (31.4) | 16.9–49.3 | 7 (63.6) | 0 | 4 (36.4) |
| Eastern China | Anhui | 52 | 10 (19.2) | 9.6–32.5 | 7 (70.0) | 0 | 3 (30.0) |
| Shandong | 122 | 29 (23.8) | 16.5–32.3 | 27 (93.1) | 0 | 2 (6.9) | |
| Shanghai | 294 | 86 (29.3) | 24.1–34.8 | 69 (80.2) | 16 (18.6) | 1 (1.2) | |
| Northern China | Beijing | 64 | 19 (29.7) | 18.9–42.4 | 11 (57.9) | 5 (26.3) | 3 (15.8) |
| Inner Mongolia | 102 | 21 (20.6) | 13.2–29.7 | 18 (85.7) | 3 (14.3) | 0 | |
| Northeast China | Jilin | 70 | 23 (32.9) | 22.1–45.1 | 4 (17.4) | 17 (73.9) | 2 (8.7) |
| Northwest China | Ningxia | 121 | 55 (45.5) | 36.4–54.8 | 51 (92.7) | 4 (7.3) | 0 |
| Qinghai | 76 | 5 (6.6) | 2.2–14.7 | 5 (100) | 0 | 0 | |
| Xinjiang | 99 | 36 (36.4) | 36.9–46.6 | 17 (47.2) | 19 (52.8) | 0 | |
| Total | 1,035 | 295 (28.5) | 25.8–31.4 | 216 (73.2) | 64 (21.7) | 15 (5.1) | |
Cryptosporidium infection in different farms.
Cryptosporidium infections were detected at all farms assessed, with infection rates ranging from 5.7% to 50.0% (Table 3). The highest prevalence was observed in Dunhua (50.0%, 15/30; 95% CI, 31.3 to 68.7) and the lowest prevalence was found in Tengzhou-2 (5.7%, 4/53; 95% CI 2.1, to 18.2) (Table 3). There was a significant difference between different farms (P < 0.001). C. xiaoi was the most prevalent species in all farms except Dunhua, Baicheng, and Korla, where C. ubiquitum was the most prevalent species. All three species were found at four farms (Baicheng, Dunhua, Jiading, and Tongzhou). C. xiaoi and C. ubiquitum were found at six farms (Abag Banner-1, Abag Banner-2, Changji, Helan, Korla, and Yanchi), whereas C. xiaoi and C. parvum were found at four farms (Lingbao, Shouxian, Tengzhou-1, and Tengzhou-2). C. xiaoi alone was detected at two farms (Tengzhou-2 and Haiyan).
TABLE 3.
Prevalence and distribution of Cryptosporidium species in different farms
| Province/city | Farm | No. of samples | No. positive (%) | 95% CI | Species (%) |
||
|---|---|---|---|---|---|---|---|
| C. xiaoi | C. ubiquitum | C. parvum | |||||
| Anhui | Shouxian | 52 | 10 (19.2) | 9.6–32.5 | 7 (70.0) | 0 | 3 (30.0) |
| Beijing | Tongzhou | 64 | 19 (29.7) | 18.9–42.4 | 11 (57.9) | 5 (26.3) | 3 (15.8) |
| Henan | Lingbao | 35 | 11 (31.4) | 16.9–49.3 | 7 (63.6) | 0 | 4 (36.4) |
| Inner Mongolia | Abag Banner-1 | 52 | 11 (21.2) | 11.1–34.7 | 9 (81.8) | 2 (18.2) | 0 |
| Abag Banner-2 | 50 | 10 (20.0) | 10.0–33.7 | 9 (90.0) | 1 (10.0) | 0 | |
| Jilin | Baicheng | 40 | 8 (20.0) | 9.1–35.7 | 2 (25.0) | 5 (62.5) | 1 (12.5) |
| Dunhua | 30 | 15 (50.0) | 31.3–68.7 | 2 (13.3) | 12 (80.0) | 1 (6.7) | |
| Ningxia | Helan | 61 | 28 (45.9) | 33.1–59.2 | 25 (89.3) | 3 (10.3) | 0 |
| Yanchi | 60 | 27 (45.0) | 32.1–58.4 | 26 (96.3) | 1 (3.7) | 0 | |
| Qinghai | Haiyan | 76 | 5 (6.6) | 2.2–14.7 | 5 (100.0) | 0 | 0 |
| Shandong | Tengzhou-1 | 49 | 20 (40.8) | 27.0–55.8 | 19 (95.0) | 0 | 1 (5.0) |
| Tengzhou-2 | 53 | 4 (5.7) | 2.1–18.2 | 3 (75.0) | 0 | 1 (25.0) | |
| Tengzhou-3 | 20 | 5 (25.0) | 8.7–49.1 | 5 (100.0) | 0 | 0 | |
| Shanghai | Jiading | 294 | 86 (29.3) | 24.1–34.8 | 69 (80.2) | 16 (18.6) | 1 (1.2) |
| Xinjiang | Changji | 47 | 17 (32.7) | 22.7–51.5 | 11 (64.7) | 6 (35.3) | 0 |
| Korla | 52 | 19 (40.4) | 23.6–51.0 | 6 (31.6) | 13 (68.4) | 0 | |
| Total | 1,035 | 295 (28.5) | 25.8–31.4 | 216 (73.2) | 64 (21.7) | 15 (5.1) | |
Cryptosporidium infection in different age groups of sheep.
Infection rates were compared between three age groups. A significant difference was observed between the age groups (P < 0.05), with the highest infection rates occurring in postweaned lambs (34.6%, 116/335; 95% CI, 29.5 to 40.0), followed by preweaned lambs (28.2%, 108/383; 95% CI, 23.8 to 33.0), and adult sheep (22.4%, 71/317; 95% CI, 17.9 to 27.4). Statistical analysis showed that there was no significant difference between preweaned lambs and postweaned lambs (P > 0.05) or adult sheep (P > 0.05); however, a significant difference was observed between postweaned lambs and adult sheep (P < 0.05). While all three Cryptosporidium species were found in all three age groups, C. xiaoi was the most prevalent species in all three groups (Table 4).
TABLE 4.
Prevalence and distribution of Cryptosporidium species by host age group
| Age group | No. of samples | No. positive (%) | 95% CI | Species (%) |
||
|---|---|---|---|---|---|---|
| C. xiaoi | C. ubiquitum | C. parvum | ||||
| Pre-weaned lambs | 383 | 108 (28.2) | 23.8–33.0 | 68 (63.0) | 32 (29.6) | 8 (7.1) |
| Post weaned lambs | 335 | 116 (34.6) | 29.5–40.0 | 87 (75.0) | 26 (22.4) | 3 (2.6) |
| Adult sheep | 317 | 71 (22.4) | 17.9–27.4 | 61 (85.9) | 6 (8.5) | 4 (5.6) |
| Total | 1,035 | 295 (28.5) | 25.8–31.4 | 216 (73.2) | 64 (21.7) | 15 (5.1) |
Cryptosporidium infection in different seasons.
Of the four seasons investigated in this study, the highest infection rate was observed in autumn (32.5%, 102/314; 95% CI, 27.3 to 38.0), followed by winter (29.3%, 86/294; 95% CI, 24.1 to 34.8), summer (25.5%, 83/325; 95% CI, 20.9 to 30.6), and spring (23.5%, 24/102; 95% CI, 15.7 to 33.0); however, the difference between the seasons was not statistically significant (P > 0.05). All three species were detected in all four seasons, except for C. ubiquitum, which was not found in spring. C. xiaoi was the most prevalent species in all four seasons (Table 5).
TABLE 5.
Prevalence and distribution of Cryptosporidium species in different seasons
| Season | No. of samples | No. positive (%) | 95% CI | Species (%) |
||
|---|---|---|---|---|---|---|
| C. xiaoi | C. ubiquitum | C. parvum | ||||
| Spring | 102 | 24 (23.5) | 15.7–33.0 | 22 (91.7) | 0 | 2 (8.3) |
| Summer | 325 | 83 (25.5) | 20.9–30.6 | 59 (71.1) | 14 (16.9) | 10 (12.0) |
| Autumn | 314 | 102 (32.5) | 27.3–38.0 | 66 (64.7) | 34 (33.3) | 2 (2.0) |
| Winter | 294 | 86 (29.3) | 24.1–34.8 | 69 (80.2) | 16 (18.6) | 1 (1.2) |
| Total | 1,035 | 295 (28.5) | 25.8–31.4 | 216 (73.2) | 64 (21.7) | 15 (5.1) |
Prevalence of Cryptosporidium subtypes.
In this study, all samples positive for C. parvum (15) and C. ubiquitum (64) were subtyped using the gp60 gene. Nine C. parvum-positive samples were subtyped successfully, and two subtypes, IIa and IId, were identified. The IIaA15G2R1 subtype was detected in five provinces, including Anhui (1), Beijing (2), Henan (1), and Jilin (1), whereas the IIaA17G2R1 subtype was detected only in Henan (Table 6). The IIdA19G1 subtype was found in Shandong (1) and Shanghai (1), and the IIdA18G1 subtype was detected in Shandong. Fifty-five C. ubiquitum-positive samples were subtyped successfully, all of which belonged to subtype XIIa (Table 6).
TABLE 6.
Subtypes of C. parvum and C. ubiquitum in different provinces in China
| Province/city | No. C. parvum positive | C. parvum subtype (no.) | No. C. ubiquitum positive | C. ubiquitum subtype (no.) |
|---|---|---|---|---|
| Anhui | 3 | IIaA15G2R1 (1) | 0 | |
| Beijing | 3 | IIaA15G2R1 (2) | 5 | XIIa (4) |
| Henan | 4 | IIaA15G2R1 (1), IIaA17G2R1 (1) | 0 | |
| Inner Mongolia | 0 | 3 | XIIa (3) | |
| Jilin | 2 | IIaA15G2R1 (1) | 17 | XIIa (13) |
| Ningxia | 0 | 4 | XIIa (4) | |
| Shandong | 2 | IIdA19G1 (1), IIdA18G1 (1) | 0 | |
| Shanghai | 1 | IIdA19G1 (1) | 16 | XIIa (16) |
| Xinjiang | 0 | 19 | XIIa (15) | |
| Total | 15 | 9 | 64 | 55 |
DISCUSSION
Cryptosporidium infections have been identified in sheep all over the world using methods such as microscopic analysis, immunofluorescence, enzyme-linked immunosorbent assays, and PCR. Molecular methods to identify species and genotypes of Cryptosporidium have also been widely applied in recent years. According to previous reports, the distribution of Cryptosporidium species in sheep varies between geographic regions. For example, C. parvum was reported to be the main species in European countries, including Greece (12), Ireland (6), Italy (13–15), Poland (16), Portugal (17), Romania (18), Spain (19–24), and the United Kingdom (25–30), whereas C. xiaoi was reportedly the dominant species in African and Oceanic countries, including Australia (31, 32), Egypt (33), Ghana (34), Tanzania (35), and Tunisia (36) (Table 7). In contrast, C. ubiquitum was reported to be the major species in Asian, North American, and South American countries, including Brazil (37, 38), China (8, 9), and the United States (39) (Table 7). However, reports from recent years have suggested that the prevalence in different areas may be shifting. For example, C. parvum was the most commonly detected species in recent reports from Australia (40), Papua New Guinea (41), the United States (42), and Zambia (43), whereas C. xiaoi was recently reported to be the most prevalent species in China (10, 11), Jordan (44), Poland (45), and the United Kingdom (46) (Table 7). Other recent reports found that C. ubiquitum was the major species in Australia (5, 47), Belgium (48), Ethiopia (49), Norway (50), and the United Kingdom (51, 52) (Table 7). Therefore, the distribution of Cryptosporidium in sheep in different areas of the world is still unclear.
TABLE 7.
Prevalence and distribution of Cryptosporidium species/subtypes in sheep in published reports
| Continent | Country | Infection rate (% [no./total]) and assay method | Species (no.) | Subtype(s) (no.) | Reference(s) |
|---|---|---|---|---|---|
| Africa | Egypt | 2.5% (3/120) | C. xiaoi (3) | 33 | |
| Ethiopia | 2.1% (8/389) | C. ubiquitum (8) | 49 | ||
| Ghana | 34.1% (74/217) | C. xiaoi (24), C. ubiquitum (2), C. bovis (1) | XIIa (1) | 34 | |
| Tanzania | 22.2% (2/9) | C. xiaoi (2) | 35 | ||
| Tunisia | 11.2% (10/89) | C. xiaoi (3) | 36 | ||
| Zambia | 12.5% (19/152) | C. parvum (5), C. suis (1) | 43 | ||
| Asia | China | 4.8% (82/1,701) | C. ubiquitum (74), C. xiaoi (4), C. andersoni (4) | 8 | |
| 14.6% (31/213) | C. ubiquitum (4) | 9 | |||
| 13.1% (49/375) | C. xiaoi (31), C. ubiquitum (17), C. parvum (1) | IIaA15G2R1 (1) | 10 | ||
| 12.3% (43/350) | C. xiaoi (39), C. ubiquitum (4) | XIIa (4) | 11 | ||
| 6.2% (4/65) | C. canis (2), C. parvum (2) | 7 | |||
| Jordan | 15.9% (10/63) | C. xiaoi (5), C. parvum (3), C. andersoni (1) | IIaA19G2R1 (2), IIaA16G1R1 (1) | 44 | |
| North America | United States | 9.0% (17/189) Mby mcroscopy, 30.0% (57/189) by PCR | C. ubiquitum (48), C. xiaoi (7), C. parvum (2) | 39 | |
| 23.6% (17/72) | C. parvum (12), C. xiaoi (5) | 42 | |||
| South America | Brazil | 1.6% (2/125) | C. ubiquitum (2) | 37 | |
| 25.0% (25/100) PCR, 13.0% (13/100) by EIA | C. ubiquitum (19), C. parvum (3) | IIaA15G2R1 (3) | 38 | ||
| Oceania | Australia | 2.2% (43/1,647) by microscopy, 26.2% (131/500) by PCR | C. ubiquitum (33), C. bovis (14), C. fayeri (4), C. scrofarum (4), C. suis (2), C. andersoni (1), C. hominis (1), sheep genotype (1) | 5 | |
| 24.5% (117/477) | C. parvum (53), C. bovis (42), C. ubiquitum (10), C. bovis + C. parvum (10) | 40 | |||
| 29.8% (401/1,347) | C. xiaoi (299), C. ubiquitum (38), C. parvum (23), C. andersoni (4), C. xiaoi + C. parvum (30), C. ubiquitum + C. parvum (1), sheep genotype I (6) | IIdA20G1 (18) | 31 | ||
| 59.5% (119/200) | C. ubiquitum (53), C. xiaoi (38), C. parvum (25), C. xiaoi + C. parvum (3) | IIdA20G1 (28) | 47 | ||
| 16.9% (576/3,412) | C. xiaoi (345), C. ubiquitum (88), C. parvum (49), C. scrofarum (4), C. andersoni (1), sheep genotype I (1), C. parvum + C. xiaoi (12) | IIaA15G2R1 (5), IIdA18G1 (23), IIdA19G1 (10), XIIa (88) | 32 | ||
| Papua New Guinea | 2.2% (6/276) | C. parvum (4), C. andersoni (1), C. scrofarum (1) | IIaA15G2R1 (2), IIaA19G4R1 (1) | 41 | |
| Europe | Belgium | 13.1% (18/137) | C. ubiquitum (9), C. parvum (1) | IIaA15G2R1 (1) | 48 |
| Greece | 5.1% (22/429) | C. parvum (7), C. ubiquitum (3) | IIdA4G2T14, IIdA4G3T13 | 12 | |
| Ireland | 14%-16.5% FAT, 49.0% (51/104) PCR | C. parvum (14), C. xiaoi (10), C. ryanae (9), C. ubiquitum (7), C. bovis (1), C. xiaoi/C. bovis (18), Cryptosporidium spp. (15) | 6 | ||
| Italy | 17.5% (26/149) | C. parvum (26) | 13 | ||
| C. parvum (21) | 14 | ||||
| 14.8% (4/27) | C. parvum (4) | IIaA20G2R1 (3), IIaA15G2R1 (1) | 15 | ||
| Norway | 3.83% (42/1,095) | C. ubiquitum (35), C. xiaoi (7) | 50 | ||
| Poland | 10.1% (16/159) | C. parvum (2) | 16 | ||
| 19.2% (45/234) | C. xiaoi (26), C. bovis (8), C. ubiquitum (3), C. xiaoi/C. parvum (1), C. xiaoi/Cryptosporidium spp. (1), C. xiaoi/C. parvum/C. hominis (1) | IIaA17G1R1 | 45 | ||
| Portugal | C. parvum (2) | IIdA21G1 (1), IIaA15G2R1 (1) | 17 | ||
| Romania | 13.7% (24/175) | C. parvum (20), C. xiaoi (2), C. ubiquitum (2) | IIA17G1R1 (2), IIdA20G1 (2), IIdA24G1 (1), IIdA22G2R1 (1), IIaA16G1R1 (1) | 18 | |
| Spain | 45.7% (360/788) | C. parvum | 19 | ||
| C. parvum (137) | IIaA15G2R1 (2), IIaA18G3R1 (1), IIdA17G1a (44), IIdA19G1 (33), IIdA17G1b (26), IIdA18G1 (15), IIdA26G1 (3), IIdA15G1 (3), IIdA25G1 (2), IIdA24G1 (2), IIdA22G1 (2), IIdA14G1 (2), IIdA21G1 (1) | 20 | |||
| 30.7% (39/127) by microscopy, 18.1% (23/127) by PCR | C. parvum (14), C. ubiquitum (9) | IIaA16G3R1 (7), IIaA15G2R1 (3) | 21 | ||
| 11.1% (42/377) | C. parvum (27) | 22 | |||
| 31.6% (54/171) | C. parvum (32), C. ubiquitum (11) | IIaA15G2R1 (16), IIaA16G3R1 (8), IIaA13G1R1 (1), IIaA14G2R1 (1) | 23 | ||
| 5.9% (19/324) | C. parvum (13), C. xiaoi (3), C. ubiquitum (1) | IIaA15G2R1 (6), IIaA14G2R1 (2), XIIa (1) | 24 | ||
| United Kingdom | C. parvum (16) | 25 | |||
| 36.1% (56/155) | C. parvum (16) | 26 | |||
| 18.0% (48/266) | C. parvum (43), C. bovis (3), C. hominis (1), C. parvum/C. bovis (1) | 27, 28 | |||
| 74.4% (67/90) by IFA, 53.3% (48/90) by microscopy/PCR | C. ubiquitum (22), C. xiaoi (4), C. bovis (1), C. xiaoi + C. ubiquitum (3), C. bovis + C. ubiquitum (1) | 51, 52 | |||
| 42.8% (127/297) | C. parvum (53), C. xiaoi (8), C. ubiquitum (1) | 29 | |||
| 39.6% (103/260) | C. parvum (31), C. bovis (3) | IIaA17G1R1 (9), IIaA15G2R1 (1), IIaA17G2R1 (1) | 30 | ||
| C. xiaoi (32), C. hominis (29), C. parvum (23), C. ubiquitum (17), mixture (139)a | IbA10G2 (11), IIaA19G1R1 (1) | 46 |
A mixture of two or more Cryptosporidium species identified.
In the current study, Cryptosporidium infections were assessed in five regions that covered most parts of China. Southeastern and southwestern China were not included in this study because of the limited number of sheep farms compared to goat farms, which is due to the tropical and subtropical climate (warm and humid all year round). According to our results, there was not a significant difference in prevalence rates among the different regions (P > 0.05); this may be due to differences in the ages of the animals studied or in sampling sites. In central China, only 35 samples from adult sheep in Henan were tested. However, further study and increased sample collection is needed in this region.
The prevalence of Cryptosporidium in sheep has been reported in only a few provinces in China, including Henan (8), Inner Mongolia (10), Qinghai (7, 11, 53), and Sichuan (9), with infection rates ranging from 4.8% to 34.4%. In this study, seven provinces produced first reports of Cryptosporidium spp. in sheep, including Anhui, Beijing, Jilin, Ningxia, Shandong, Shanghai and Xinjiang. There were significant differences in the prevalence of Cryptosporidium between different provinces. Because of similar environments for sheep from all the farms, the differences between provinces might be affected by the weather, the birthing seasons, etc. For example, the prevalence in Xinjiang was significantly different from Shandong (P < 0.05); this might be because the different seasons of sample collection. The samples from Xinjiang were collected in summer and autumn, while samples from Shandong were collected in spring and summer (data not shown).
In this study, the overall prevalence of Cryptosporidium infection was 28.5% (295/1035), which was similar to that in previous reports of Cryptosporidium in sheep in Australia (29.8%) (31), Brazil (25.0%) (38), and Spain (30.7%; 31.6%) (21, 23). However, the prevalence rates of Cryptosporidium infections that we found in Henan (31.4%, 11/35) and Inner Mongolia (20.6%, 21/102) were higher than the previously reported rates of 4.8% (82/1701) in Henan (8) and 13.1% (49/375) in Inner Mongolia (10). In the current study, the infection rate in Qinghai (6.6%, 5/75) was lower than reported in previous studies that identified Cryptosporidium using immunofluorescence (34.4%, 21/61) and PCR (12.3%, 43/350) (11, 53) but was similar to a recent report that the prevalence of Cryptosporidium infection in this area was 6.2% (4/65) (7). The differences in infection rates between our study and those in previous reports may be due to differences in the ages of sheep assessed, the season during which specimens were collected, or the numbers of samples collected. According to previous reports, more adult sheep (pregnant ewes and postparturition ewes) were selected for Cryptosporidium examination in Henan (2.2%, 16/738) (8) and Inner Mongolia (6.1%, 13/213) (10), while only 65 samples from adult sheep were examined in Henan (31.4%, 11/35) and Inner Mongolia (66.7%, 2/30) in this study (data not shown). Therefore, in future research, larger numbers of samples in these areas will be collected for Cryptosporidium examination.
In the present study, Cryptosporidium infections were detected at all farms assessed, suggesting that Cryptosporidium is widespread in sheep in China. Of the three species identified in this study, C. xiaoi was the most common (73.2%), followed by C. ubiquitum (21.7%), and C. parvum (5.1%). These findings are similar to those from a study done in Inner Mongolia by Ye et al. (10), who found similar patterns of C. xiaoi (63.3%), C. ubiquitum (34.7%), and C. parvum (2.0%) in sheep. The results are also in agreement with reports from Australia, where C. xiaoi, C. ubiquitum, and C. parvum were reportedly the most common species in sheep (31, 32). Other species, including C. andersoni, C. scrofarum, and sheep genotype I, were also detected in these studies but were not detected in our study.
According to our results, the distribution of Cryptosporidium species differs between provinces and between farms, including between farms located in the same province. For example, C. xiaoi was the most prevalent species in all provinces except Xinjiang and Jilin, where C. ubiquitum was the most common species. However, infection rates differed at two farms in Xinjiang; C. xiaoi was the most prevalent species at the Changji farm, whereas C. ubiquitum was the most prevalent species at the Korla farm. Other geographic differences in the distribution of Cryptosporidium species in sheep were also found in the present study. For example, C. xiaoi was detected in all of the provinces and sheep farms assessed, but only two species (i.e., C. ubiquitum/C. xiaoi or C. parvum/C. xiaoi) were found in some provinces and farms, and only C. xiaoi was found in Haiyan (Qinghai) and Tengzhou-3 (Shandong) sheep farms. Similar results were also found in Australia (32, 40, 47), Norway (50), Romania (18), Spain (22), and the United Kingdom (29), where the distributions of Cryptosporidium species differ between farms.
The results of the present molecular analyses are consistent with reports from other laboratories. For example, C. xiaoi was reported to be the dominant Cryptosporidium species in Australia (31, 32) and the United Kingdom (46). However, other studies have found that C. ubiquitum was the most prevalent species in Australia (5, 47), and the United Kingdom (52). Similar discrepancies in the distribution of Cryptosporidium in sheep also exist in China. Similarly to the current study, C. xiaoi was reported to be the most common species in Inner Mongolia (10) and Qinghai (11). However, those studies also detected C. parvum in Inner Mongolia and C. ubiquitum in Qinghai, whereas we did not detect these species in these provinces. Similarly, C. ubiquitum, C. xiaoi, and C. andersoni were previously reported in sheep in Henan, with C. ubiquitum as the dominant species (8). In contrast, we detected C. parvum, but not C. ubiquitum, in Henan. Other species that have been reported in China, such as C. andersoni in Henan (8) and C. canis in Qinghai (7), were not detected in our study. These differences may be explained by differences in the ages of animals, season of collection, or sample numbers between the different studies.
Similarly to most previous surveys in sheep (15, 19, 24, 30, 31, 33, 34, 36, 37, 39), we found a higher prevalence of Cryptosporidium in lambs than in adults. These results were consistent with those of Ye et al. (10), who found the prevalence of Cryptosporidium in 15- to 16-week-old lambs (postweaned) in Inner Mongolia was higher than that in 3- to 4-week-old lambs (preweaned). Similar results were also reported in Australia, where the infection rates in postweaned lambs were higher than in preweaned lambs (10, 31, 40). However, we did not observe a relationship between Cryptosporidium species and age of the animals, as all of the three species were detected in all age groups in this survey. Similar results have been reported in many previous studies of sheep in Australia (32), Poland (45), and the United States (39), where C. xiaoi, C. ubiquitum, and C. parvum were identified in all age groups. In contrast, other studies have found only one or two species in preweaned/postweaned lambs and adult sheep in China (8, 10, 11).
To our knowledge, few studies have reported the seasonal dynamics of Cryptosporidium infections in sheep. In our study, samples were collected in all four seasons, and the highest infection rates were observed in autumn. In contrast, previous studies reported that the highest infection rates occurred in spring in Jordan (44), in summer in Ireland (6), and in winter in India (54). We found all three species in all seasons except spring, when C. ubiquitum was absent. Because there were no significant differences between seasons, we suggest that season is not a significant variable in the distribution of Cryptosporidium species in sheep. However, these conclusions need to be further verified.
In the current study, two C. parvum subtype families, IIa and IIb, were identified. IIaA15G2R1 (5/6) was the most common IIa subtype and was detected in four provinces. Similar results were reported by Ye et al. (10), who identified an IIaA15G2R1 subtype in a lamb in Inner Mongolia. According to previous reports, subtype IIaA15G2R1 is the most common subtype in sheep in many countries, including Australia (32), Belgium (48), Brazil (38), Italy (15), Papua New Guinea (41), Portugal (17), Spain (20, 21, 23, 24), and the United Kingdom (30). In addition, an IIaA17G2R1 subtype was identified in this study. This subtype is rare but has previously been detected in sheep in the United Kingdom (30). In China, subtypes IIaA15G2R1 and IIaA17G2R1 have also been found in goats in Shanghai (55). For the IId subtype families, we found IIdA18G1 and IIdA19G1 subtypes, which have previously been reported in Australia (32) and Spain (20) but not in sheep in China. Subtyping analyses revealed that all C. ubiquitum-positive samples were XIIa, which is in accordance with a recent study that found the XIIa subtype in sheep in Qinghai (11). This subtype has also been reported in sheep in Australia (32), Ghana (34), and Spain (24), and in goats in Australia (32), China (55, 56), and Spain (24), which suggests that C. ubiquitum subtype XIIa may be the most common subtype in small ruminants. We are not aware of any previous reports of subtypes IIaA17G2R1, IIdA18G1, and IIdA19G1 in sheep in China. Furthermore, all of the subtypes identified in this study have been found in humans, indicating that zoonotic Cryptosporidium poses a potential threat to human health.
In conclusion, 1,035 fecal samples were collected from sheep in five regions (16 farms in 10 different provinces) of China and assessed for the presence of Cryptosporidium. Cryptosporidium infections were detected at all of the farms, indicating that Cryptosporidium infections are widespread in sheep in China. The overall infection rate was 28.5%, and the highest infection rate was found in postweaned lambs. Three Cryptosporidium species were identified in all age groups across the four seasons. We observed geographical differences in the distribution of Cryptosporidium species in sheep but did not find a relationship between host age or sampling season and the distribution of Cryptosporidium species. Four C. parvum subtypes and one C. ubiquitum subtype were identified in sheep in this study. All the subtypes are zoonotic subtypes, and there may be a risk for zoonotic transmission to humans. This information will improve our knowledge and understanding of the epidemiology of cryptosporidiosis in China.
MATERIALS AND METHODS
Study area.
Between 2013 and 2016, 1,035 fecal specimens were collected from 16 sheep farms in 10 provinces in five regions of China. Sampling locations in central China included one farm in Lingbao City, Henan Province (34°52′N, 110°88′E). Sampling locations in eastern China included one farm in Shouxian County, Anhui Province (32°50′N, 116°60′E), three in Tengzhou City, Shandong Province (Tengzhou-1, 35°04′N, 116°89′E; Tengzhou-2, 35°11′N, 117°16′E; Tengzhou-3, 35°07′N, 117°00′E), and one in Jiading District, Shanghai City (31°20′N, 121°14′E). Sampling locations in northern China included one farm in Tongzhou District, Beijing City (39°90′N, 116°73′E) and two in Abag Banner, Inner Mongolia Autonomous Region (Abag Banner-1, 44°02′N, 114°93′E; Abag Banner-2, 44°02′N, 115°44′E). Sampling locations in northeastern China included one farm in Dunhua City (43°37′N, 128°24′E) and one in Baicheng City (45°61′N, 122°86′E), both in Jilin Province. Sampling locations in northwestern China included one farm in Changji Hui Autonomous Prefecture (44°01′N, 87°31′E) and one in Korla City (41°39′N, 86°08′E), both in Xinjiang Uyghur Autonomous Region, one from Helan County (38°41′N, 106°17′E) and one from Yanchi County (37°78′N, 107°41′E), both in Ningxia Hui Autonomous Region, and one from Haiyan County, Qinghai Province (36°90′N, 100°99′E) (Fig. 2).
FIG 2.
Geographic map of sampling locations included in this study. ▲, sampling sites. The data for the underlying map were downloaded from the Database of Global Administrative Areas (GADM) website (https://gadm.org/download_country_v3.html) and revised with ArcMap 10.3 (ArcGIS software).
China covers a large territory and the climate varies widely in different regions. Anhui and Shanghai are in subtropical regions with a monsoonal climate characterized by hot, humid summers and generally mild winters. Beijing has a monsoon-influenced humid continental climate characterized by high humidity in summer and cold, windy, dry winters. Henan has a distinct seasonal climate characterized by hot, humid summers and generally cool to cold, windy, dry winters. Inner Mongolia has a typical temperate monsoon climate with limited and sporadic precipitation and large differences in temperature between summer and winter. Jilin has a northern continental monsoon climate with long, cold winters and short, warm summers. Ningxia and Qinghai have a continental climate with cold winters, mild summers, and large diurnal temperature variation. Shandong has a warm-temperate monsoonal climate with hot, rainy summers and cold, dry winters. Xinjiang has a semiarid or desert climate with extreme seasonal variations in temperature (57). The flocks were kept within fenced areas during the day and in houses with wooden, slatted floors or cement floors at night.
Specimen collection.
Farms and animals were randomly chosen for sampling in the following four seasons: spring (March to May), summer (June to August), autumn (September to November), and winter (December to February). Animals were categorized into three age groups: preweaned lambs (<3 months), postweaned lambs (3 to 12 months), and adult sheep (>12 months). Samples were collected with sterile gloves either directly from the rectum or from feces freshly deposited on the ground, placed in sealable bags, labeled, and sent to the laboratory to be processed within 1 week. None of the sheep selected for this study had been previously examined for Cryptosporidium infection.
DNA extraction.
Genomic DNA was extracted from approximately 300 mg of each fecal sample. Each sample was washed twice with sterile water. DNA was then extracted using a FastDNA SPIN kit for soil (MP Biomedicals, Santa Ana, CA) following the manufacturer's instructions and stored at −20°C prior to use.
PCR amplification.
The small subunit (SSU) rRNA locus of each sample was screened for identification of Cryptosporidium species. A fragment of approximately 830 bp was amplified using the nested PCR protocol previously described by Xiao et al. (58, 59). Positive and negative controls were included for each PCR. PCR products were analyzed on a 1.2% agarose gel.
Sequencing and phylogenetic analyses.
All positive PCR products were purified using an AxyPrep DNA gel extraction kit (Axygen, Suzhou, China) and sequenced using an ABI 3730xl DNA analyzer (Applied Biosystems, Foster City, CA). All sequences were analyzed using the BLAST program (http://blast.ncbi.nlm.nih.gov/Blast.cgi) for homology searches. The reference sequences of Cryptosporidium species were obtained from GenBank. Phylogenetic evolutionary analysis of SSU rRNA sequences of different Cryptosporidium species and genotypes was performed using MEGA 7.0 software (http://www.megasoftware.net/).
Subtype identification.
Subtyping was carried out by sequence analysis of the 60-kDa glycoprotein (gp60) gene. A 400-bp fragment of the gp60 gene was amplified for C. parvum identification as described by Sulaiman et al. (60), and an approximately 950-bp fragment was amplified for C. ubiquitum subtyping as described by Li et al. (61). The gp60 loci of the PCR products were then sequenced to identify Cryptosporidium subtypes, as previously described (60, 61).
Statistical analysis.
Infection rates were estimated as a percentage of positive samples with 95% confidence intervals (CI) calculated using the exact binomial method (62). Pearson's Chi-square (χ2) tests were performed using IBM SPSS Statistics for Windows, Version 21.0 (IBM Corp., Armonk, NY, USA) to assess differences in the prevalence of Cryptosporidium spp. between different regions, ages, and seasons. Differences were considered statistically significant when P < 0.05.
Accession number(s).
The unique sequences described here have been deposited in the GenBank database under accession numbers MH059800 to MH059808.
ACKNOWLEDGMENTS
This study was supported in part by The National Key Research and Development Program of China (grant 2017YFD0500401), the National Natural Science Foundation of China (grant 31702025), the National Risk Assessment Project for Quality and Safety of Agricultural Products (grant GJFP201800703), the Shanghai Agriculture Applied Technology Development Program, China (grant G20150110), and the Key Technology R&D Program of Ningxia District, China (grant 201601). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We thank Rui An at Changji State Animal Husbandry Bureau, Haining Zhou at the Ningxia Center for Animal Disease Control and Prevention, Wei Zhu at Tengzhou Animal Husbandry and Veterinary Technology Service Center, and Yibin Hu at Polytron Technologies Inc. (Beijing center) for their help on sample collecting. We thank Long Cheng in SHVRI-CAAS for his help on some sample detection. We also thank International Science Editing for editing the manuscript.
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