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Performance of diagnostic assays used to detect Cryptosporidium oocysts in faecal samples of cattle in Kuwait and genotyping of Cryptosporidium species

BMC Veterinary Research volume 18, Article number: 336 (2022) Cite this article

Abstract

Backgroud

Cryptosporidium species are zoonotic protozoan parasites responsible for gastroenteritis in various animals and humans. The diagnosis of Cryptosporidium presents many challenges. This research attempted to match the diagnostic efficiency of the modified Ziehl–Neelsen technique (mZN), immunochromatographic assays (IC), and enzyme-linked immunosorbent assay (ELISA) for the detection of Cryptosporidium in faecal samples of cattle in Kuwait. In addition, polymerase chain reaction (PCR) was utilised to determine the predominant species infecting cattle in Kuwait and correlating the detected species with the results of different diagnostic tests used, the presence or absence of clinical signs, and the age group of the infected cattle.

Results

Of 400 analysed faecal samples, Cryptosporidium positive samples were 23%, 15.25%, and 14% using IC, ELISA, and mZN. IC had the highest sensitivity (74.07%), and mZN had the highest specificity (98.29%) using a composite reference standard (CRS) as a gold standard. The rapid IC test results in high false-positive results of cryptosporidiosis, whereas using mZN alone is insufficient to declare a negative faecal sample. Only 74.5% (35/47) of Cryptosporidium-positive samples by the three assays could be amplified by PCR. This study was the first to genotype Cryptosporidium in Kuwait. Cryptosporidium parvum (n = 26) was the dominant species detected from cattle samples, followed by C. andersoni (n = 6), C. bovis (n = 2), and C. raynae (n = 1). The findings showed a statistically relevant relationship between diarrhoea and the detection of Cryptosporidium spp. in faecal samples of cattle (p-value = 0.0003). Pre-weaned calves were the most vulnerable age group to Cryptosporidium spp. infection (p-value = 0.0007).

Conclusion

For screening of Cryptosporidium infection in faecal samples, antigen detection or PCR methods combined with one of the microscopy techniques should be used. Cryptosporidium parvum was the prepoderant Cryptosporidium spp. recovered from cattle samples in Kuwait followed by C. andersoni. Cryptosporidium parvum is a significant risk factor for diarrhoea in pre-weaned calves. However, further study is needed as many other causes of diarrhoea in calves must be ruled out before a diagnosis of Cryptosporidium diarrhoea can be made.

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Background

Cryptosporidium species, the enteric apicomplexan protozoan parasite, can infect various hosts, including humans, livestock and poultry. However, cattle are the most significant host from a veterinary and public health perspective [1]. However, ten Cryptosporidium spp. have already been recorded in cattle, only four spp.; Cryptosporidium parvum, C. bovis, C. ryanae, and C. andersoni are the most frequently found [2,3,4,5]. Nevertheless, C. parvum is the only spp. linked to clinical illness in neonatal calves, with older animals (> 6 weeks) demonstrating asymptomatic oocyst shedding [3]. Cryptosporidium bovis and C. ryanae are the predominant species in post-weaned calves [3,4,5]. There is little evidence on the clinical symptoms caused by C. bovis and C. ryanae; although, diarrhoea was reported in native calves in Nigeria, presumably due to C. bovis and C. ryanae infection [6]. Cryptosporidium andersoni is more commonly found in adults than in young cattle. Cryptosporidium andersoni infections are clinically associated with weight gain impairment and reduced milk yield in adult cows [2, 7].

Diagnosis of Cryptosporidium spp. in clinical cases, the specimen typically contains considerable oocysts count and a high concentration of the parasite antigen, even though methods with low sensitivity grant a positive result. Whereas specimens with few oocysts may necessitate an epidemiological investigation to detect asymptomatic carriers, using an initial screening method then a confirmatory test, for example, molecular or microscopic techniques, can boost reliance in the diagnosis [8]. Furthermore, accurate and rapid detection of Cryptosporidium spp. during diarrhoea epidemics in calves can help perform timely interventions, reduce economic losses, and improve animal welfare [9].

Several diagnostic assays were applied to detect Cryptosporidiosis in various hosts. They include 1- conventional (faecal smears stained by mZN), 2- antigens-detection tests (IC and ELISA), and 3- detection of Cryptosporidium DNA (PCR). Conventional microscopy is time-consuming, laborious, and needs expert microscopists to identify oocysts accurately. Simultaneously ELISA and PCR are costly and require well-equipped laboratories and skilled technicians. Although IC is a rapid test and easy to perform and interpret but may have many false-positive results [10, 11].

Many diagnostic circumstances lack a gold standard, and it can be argued that what is popularly known as a gold standard may not be a proper one. As a result, numerous approaches to assessing diagnostic tests in the lack of a gold standard have been established [12, 13]. For instance, a composite reference standard (CRS) can be created by combining the results of numerous imperfect tests, excluding the index test (the test to be evaluated). Based on a predetermined rule, a CRS is thought to have better discriminatory qualities than each individual reference standard [14]. Additionally, when more than two reference tests are included in the composite reference standard, the final definition of the disease may become muddled [15]. The exclusion of the index test from the composite reference standard is essential to avoid incorporation bias [16].

All assays used commonly in Kuwait for detecting clinical and asymptomatic cryptosporidiosis in cattle have not been evaluated. Thus, the objectives of this study were to assess routinely used laboratory tests such as microscopic examination of mZN stained faecal smears, IC, and ELISA. Given that there is no gold standard assay for diagnosis of Cryptosporidiosis [8], we applied a composite reference standard to create a pseudo-gold standard for evaluating the tests used to detect Cryptosporidium oocysts. Genotyping of Cryptosporidium species was applied. In addition, correlating the detected species with the results of different diagnostic tests used, the presence or absence of clinical signs, and the age group of the infected cattle were also studied.

Results

The total number of cattle on the visited farms was 9365. Rectal faecal samples were collected randomly from 400 cattle: 175 pre-weaned, 49 post-weaned, and 176 adults.

Performance of mZN, IC, and ELISA in diagnosis of Cryptosporidium

Examination of 400 cattle faecal samples for Cryptosporidium oocysts and antigens revealed that the Cryptosporidium positive samples were 23%, 15.25%, and 14% using IC, ELISA, and mZN, respectively (Table. 1). Results of the three diagnostic tests used showed that 287 (71.75%) faecal samples were negative, whereas 33 (8.25%) faecal samples were positive using the three tests (Table 1). Different distribution of Cryptosporidium results according to the examined test used, mZN, IC, ELISA, in faecal samples of cattle were recorded in Table 1. Concerning other entero-pathogens discovered by the IC test, rotavirus, coronavirus, and E. coli were found in 21 (5.25%), 4 (1.0%), and 73 (18.25%), respectively. In addition, coinfections of rotavirus with Cryptosporidium spp. and E. coli with Cryptosporidium spp. were detected in 2.25% (9/400) and 4.5% (18/400), respectively. Mixed infections with Cryptosporidium spp., rotavirus, and E. coli were detected in two of 400 examined faecal samples (0.5%).

Table 1 Distribution of Cryptosporidium results according to the test used; mZN, IC, ELISA, in faecal samples of cattle (N = 400)
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The diagnostic sensitivity of mZN, IC, and ELISA to detect Cryptosporidium in cattle faeces was 47.22%, 74.07%, and 48.00%, respectively. In contrast, the diagnostic specificity was 98.29%, 89.97%, and 95.67% for mZN, IC, and ELISA, respectively. The agreement between IC and the pseudo-gold standard was substantial (κ = 0.61). On the other hand, a moderate agreement was reported for both mZN and ELISA compared to the pseudo-gold standard (κ = 0.54 and 0.50, respectively). Table 2 summarises the diagnostic performance meassures of the three test, including accuracy, Positive Predictive Value (PPV), and Negative Predictive Value (NPV).

Table 2 Performance of the three test (mZN, IC, ELISA) used to detect Cryptosporidium in feces of cattle compared with the CRS
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Comparison between the three diagnostic tests with the PCR results

A comparison between the three diagnostic tests used to detect Cryptosporidium with the PCR results and the genotype identified in 47 faecal samples was reported in Table 3. Out of 47 faecal samples, 35 samples (74.5%) were positive by nested PCR for detection of Cryptosporidium species. Thirty-two of the 35 positive PCR samples gave positive result by IC (91.4%), 28 samples were positive by mZN (80.0%), and 24 samples were positive by ELISA (68.6%). Cryptosporidium parvum was detected in 26 samples; 15 samples were positive by mZN, IC and ELISA, six were positive by IC and ELISA, and five were positive by mZN and IC. Cryptosporidium andersoni was detected in six samples; two were positive by both mZN and IC, whereas two were positive by both mZN, and ELISA. The other two samples were positive only by one test, mZN or IC (Table 3). Twelve faecal samples were negative by PCR; 100% (12/12) were positive by IC, 75% (9/12) were positive by mZN, and 66.6% (8/12) were positive by ELISA (Table 3).

Table 3 Comparison of positive results of different diagnostic tests used for the detection of Cryptosporidium with the PCR results and the genotype identified in the examined 47 faecal samples
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Cryptosporidium spp. association with diarrhoea and age groups

Statistical correlation between faecal consistency, age group, and different genotypes of Cryptosporidium spp. showed that C. parvum was recorded in 46.8% (22/47) diarrheic pre-weaned cattle and four adult cattle (8.5%) with normal faecal consistency (Table 4). Whereas C. andersoni was detected in four adult cattle (8.5%) with normal faecal consistency, one pre-weaned cattle with normal faecal consistency, and one diarrheic post-weaned cattle. C. bovis was detected in two pre-weaned cattle with normal faecal consistency, and one C. ryanae was diagnosed in post-weaned cattle with normal faecal consistency (Table 4). Diarrhoea and the diagnosis of Cryptosporidium spp. had a statistically strong relationship (p-value = 0.0003). Pre-weaned calves were the age group most likely to contract Cryptosporidium spp. infection (p-value = 0.0007).

Table 4 Statistical correlation between PCR results and the different Cryptosporidium spp. with faecal consistency, and age group in the examined cattle (47 faecal samples)
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Phylogenetic analysis of detected Cryptosporidium species

The phylogenetic tree shows that the current strains isolated from cattle clustered based on the species of Cryptosporidium, forming 4 groups (Ryanae, Bovis, Parvum, and Andersoni). Among the same species of Cryptosporidium, subgroups were formed like in the C. andersoni group. This indicates genetic variation within the genus Cryptosporidium (Fig. 1).

Fig. 1
figure 1

Phylogenetic sequence relationship of recovered Cryptosporidium spp. to other species in Genbank; C. andersoni isolated from cattle in China (KC580754), C. parvum; strain Bovine C. parvum genotype (BOH6) isolated from calf in Ohio (AF093490), C. bovis; Bovis 2622 isolated from cattle (AY120911), C. ryanae isolated from calves in China (HQ009807), and C. parvum_2_Sheep_Kuwait isolated from sheep in Kuwait

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Discussion

The detection and diagnosis of Cryptosporidium present many challenges. The presence of oocysts (itself, antigen, or DNA) is routinely used to detect Cryptosporidium infection in faecal samples using various laboratory techniques [17]. Because of the variety of diagnostic procedures used and the inconsistent use of typing methodologies, direct comparisons between clinical, veterinary, and environmental tests can be difficult or, indeed, impossible [17].

Previous studies evaluated different diagnostic techniques applied to identify Cryptosporidium oocysts in faecal samples of various animals using a variety of gold standards such as cumulative positivity [18] and latent class analysis model [10]. However, Danišová et al. [19] considered PCR the gold standard reference test because PCR has high accuracy, although PCR results could be affected by the presence of low-density oocysts in the faecal samples that may contain PCR inhibitors [20]. Additionally, the preservatives may penetrate the oocysts, which cannot be removed by washing, consequently inhibiting PCR results [17]. Furthermore, PCR techniques are expensive and need specialized equipment, which is not available in every laboratory. However, the main advantage of using PCR is identifying the infecting species since most diagnostic assays only detect the presence or absence of Cryptosporidium oocysts. Identifying Cryptosporidium species is significant because different species have different epidemiology, clinical manifestations, and sequelae [1].

In the present study, the performance of the three tests (mZN, IC, ELISA) used to detect Cryptosporidium in cattle faeces was studied. The results revealed that IC had the highest sensitivity, and mZN had the highest specificity using a CRS as a gold standard. The sensitivity of the three tests ranged from low in mZN and ELISA (47.22%, 48%, respectively) to moderate in the IC test (74%), whereas the specificity of the three tests was high (90% or higher). The low sensitivity of the three tests may be due to the low intensity of infection rate in the studied cattle population, and the present study was a cross-sectional study where only one faecal sample was collected from each animal. However, repeated examination of more than one faecal sample on three consecutive days enhances the detection of Cryptosporidium oocysts [21].

Ezzaty Mirhashemi et al. [10] found that ELISA and PCR had higher specificity than standard microscopic assay (Kinyoun’s carbol-fuchsin acid-fast staining) in cattle samples. While utilizing LCA as the gold standard, routine microscopic analysis in sheep samples exhibited the highest specificity when compared to ELISA and PCR [10]. A previous study evaluated different diagnostic methods used to detect Cryptosporidium in stools of diarrheic children using PCR as a gold standard. mZN revealed higher specificity than ELISA and rapid strip, while ELISA showed the highest sensitivity [22]. In another study, using PCR as a gold standard to evaluate immunological tests for diagnosis of Cryptosporidium in diarrheic animals (pigs, calves, and lambs), ELISA (40.9%) showed higher sensitivity than IC (22.7%), while IC (100%) showed higher specificity than ELISA (78.9%) [19]. Papini et al. [18] studied the performance of three IC tests to detect C. parvum in diarrheic calves using cumulative positivity as a gold standard. They found that the three kits had high sensitivity and specificity (SE 100%, 100%, and 90.24%, SP 96%, 92%, 100%, respectively).

Different sensitivities and specificities of diagnostic tests used to diagnose Cryptosporidium in faecal samples have been reported. These differences are highly dependent on infecting species and the concentration of oocysts in the faecal sample [10, 23].

The diagnostic performance of mZN revealed a high PPV and NPV; such a higher value may be because mZN confirms the diagnosis by tracing the parasites. It was reported that the microscopic method for detection of Cryptosporidium spp. in faeces is highly specific and less sensitive [24] and can be used as a confirmatory test. However, there is a great demand for an alternative test to overcome the limitations of this assay, such as the lack of experts microscopist for accurate identification of oocysts [25].

Detecting Cryptosporidium antigens (copro-antigens) in faecal samples using ELISA and IC assays is widely used. However, ELISA and IC detection limits ranged from 3 × 105 to 106 oocysts per ml [8, 26], which is not significantly more sensitive than conventional microscopy. In comparison to microscopy, ELISA, and PCR procedures, the rapid IC assay was quicker and simpler to do because it didn't call for any extra special equipment. This reaerch reported false-positive results with rapid IC tests consistent with previous studies [22, 27]. The IC test had a PPV of 65.22%, indicating that positive results with this assay need to be confirmed microscopically or using PCR. Hence, rapid IC kits can be used as a screening test during diarrhoea outbreaks.

In the present study, the results of immunological tests used to detect different Cryptosporidium spp. were controversial. One possible explanation is that not all commercially produced antibodies recognize all Cryptosporidium spp. oocyst antigens of individual species. Hence, immunological testing cannot detect every copro-antigen found in the more than 30 species and genotypes identified until 2016 [19].

Only 74.5% (35/47) of Cryptosporidium-positive samples recovered by the three assays could be identified by PCR. This could be attributable to different factors, including the low PPV of IC and ELISA or PCR inhibition. Cryptosporidium parvum was the most common species detected from cattle samples in Kuwait, with only a few samples containing C. andersoni (n = 6), C. bovis (n = 2), and C. raynae (n = 1). There have been few studies of Cryptosporidium molecular diagnosis in the Middle East. In terms of Cryptosporidium spp. distribution, our results differ from those of previous studies. Cryptosporidium parvum was the only discovered species in Tunisia and Syria [28,29,30]. In contrast, other studies reported C. parvum and other Cryptosporidium spp. infecting cattle farms. Cryptosporidium parvum was recorded as the most predominant species, with C. andersoni in Iran [31], C. raynae in Turkey [32], C. bovis and C. raynae in Egypt [33], and C. ryanae, C. andersoni, and C. bovis in Sudan [34]. The most prevalent Cryptosporidium identified in Jordan was C. ryanae, then C. parvum and C. andersoni [35]. In Algeria, C. bovis was the most detected spp. in cattle, then C. ryanae and C. parvum [36]. The four Cryptosporidium spp. that infect cattle are distributed differently over the world [1].

In this study, C. andersoni was detected in six samples from four adult cattle, one post-weaned and one pre-weaned. All positive animals were from the same farm. Only one animal had diarrhoea (post-weaned), also was positive for both rotavirus and E. coli by rapid IC test. Another positive animal was a cow with a history of decreased milk production and severely emaciated. Cryptosporidium andersoni was identified in adult cattle more than in young cattle [37]. In addition, infections with C. andersoni have been linked to decreased weight gain and milk production in adult cows [7]. Whereas C. bovis was reported in two healthy pre-weaned calves, and C. ryanae was identified from one healthy post-weaned animal. Previous studies reported that neither C. bovis nor C. ryanae have been implicated in clinical disease in cattle of any age group [4, 38,39,40].

In the present research, C. parvum was the prepoderant species detected from cattle in Kuwait. It was identified in four adult cattle without signs of diarrhoea, and 22 pre-weaned calves suffered from diarrhoea. C. parvum is a widely endemic pathogen that causes self-limiting gastroenteritis in pre-weaned calves suffered from profuse watery diarrhoea as a common symptom and can be fatal in severe cases [41, 42]. Multiple pathogens (rotavirus, coronavirus, pathogenic strains of Escherichia coli, and Salmonella spp.) can cause neonatal diarrhoea [41]. In contrast, cryptosporidiosis is confirmed as a major diarrhoeal cause in pre-weaned calves by detecting significant numbers of oocysts in the absence of other pathogens; however, coinfection has been commonly believed to alter the clinical presentation and lead to more severe cryptosporidiosis [42].

The detected Cryptosporidium spp. were clustered into four groups (Ryanae, Bovis, Parvum, and Andersoni) in the phylogenetic tree. In addition, subgroups of Cryptosporidium were formed among the same species. This indicates genetic variation within the genus Cryptosporidium [43].

Conclusions

The antigen detection test results in false-positive results of cryptosporidiosis, whereas using mZN alone is insufficient to declare a negative faecal sample. As a result, for screening of Cryptosporidium infection in faecal samples, antigen detection or PCR methods combined with one of the microscopy techniques should be used. Cryptosporidium parvum is a significant risk factor for diarrhoea in pre-weaned calves. However, further study is needed as many other causes of diarrhoea in calves must be ruled out before a diagnosis of Cryptosporidium diarrhoea can be made.

Methods

Study design

Between October 2014 to September 2015, a 1-year cross-sectional study was carried out to assess the diagnostic performance of several tests used to identify Cryptosporidium infections in cattle with or without clinical symptoms. The farms were chosen without being aware of the level of Cryptosporidium infestation. Twenty-two dairy cattle farms were visited once in the Sulaibiya area.

Sample collection

Four hundred cattle were randomly selected to examine their faecal samples. Five to ten grams of faeces were collected from the rectum or immediately after defecation and kept in a sterile capped cup. The faecal samples were categorised according to their consistency into diarrhoeic (n = 127) and non-diarrhoeic (n = 273).

Processing of samples

Each sample was split into three parts in the lab: the first part was used to identify Cryptosporidium oocysts using mZN; the second part was utilised to identify Cryptosporidium antigens using IC and ELISA; and the third part was stored either in 2.5% potassium dichromate or at -20 °C. If the sample was determined to be positive for a Cryptosporidium oocyst or antigen by mZN, IC, and/or ELISA, the stored sample was sent to Prof. Dr. Lihua Xiao for typing and subtyping of Cryptosporidium spp.

Detection of Cryptosporidium oocyst

Cryptosporidium oocysts were identified conventionally using faecal smears stained with mZN (Fig. 2). Fresh and concentrated faecal smears were prepared, stained, and examined as formerly described [44]. Concisely, faecal smears were prepared on a microscope slide, air-dried at room temperature, then fixed for 5 min with pure alcohol (methanol). Fixed smears were stained for 3–5 min with dilute carbol-fuchsin (1: 10) before rinsing using water. Decolourisation step for 10–15 min with 3% HCL in ethanol, then counterstained for one minute with 0.5% malachite green solution. Finally, Smear slides were washed with tap water, air dried, and examined at × 400 magnification under the light microscope. Oocysts of Cryptosporidium spp. appear as pink to red bodies that are spherical to ovoid against a green to purple background. Samples were considered positive if at least one morphologically distinct Cryptosporidium species.

Fig. 2
figure 2

A mZN stained faecal smear, Cryptosporidium oocyst (arrow) pink spherical body against purple background

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Detection of Cryptosporidium antigen

Rapid BoviD-4 Ag immunochromatography test kit (BioNote Inc., Gyeonggi-do, Korea) was utilised to discover Cryptosporidium spp., rotavirus, coronavirus, and E. coli K99 antigens in faeces. The right quantity of faeces was collected using a sterile swab stick. The swab placed into the dilution tube and left till fully dissolved in the diluent, then vigorously stirred. The tube was then covered and allowed for sedimentation for 30 min. One drop of supernatant was dispensed into the sample holes of the BoviD-4 Ag testing apparatus using a disposable dropper. The findings were interpreted in accordance with the manufacturer's recommendations (Fig. 3).

Fig. 3 
figure 3

Bovid-4 kit device showed a positive result for Cryptosporidium antigen and negative for Rotavirus, coronavirus, and E. coli antigens. Diluted sample added into the sample hole, the results were interpreted after 5–10 min; the sample was considered negative if only the control line “C” appeared and positive if both “C” and “T” lines appeared

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A sandwich, double wells ELISA kit (Bio-X Diagnostics, Rochefort, Belgium) was used to detect Cryptosporidium antigens. The plate is coated with the anti-Cryptosporidium-specific antibody. The methodology, and interpretation of the results were performed according to the manufacturer’s guidelines. Samples were stored at -20◦C without preservatives and the test was applied within a month from the day of collection. Faecal samples were diluted and added to the coated wells, then the plate was incubated for 1 h at 21◦ ± 3◦C. Next, the conjugated anti-Cryptosporidium monoclonal antibody was appended and reincubated. Finally, tetramethylbenzidine (TMB) was visualized the reaction as showed in Fig. 4, and the results were measured at 450 nm using a microplate reader (BioTeck ELX800G reader, BioTeck Instruments Inc., Winooski, USA).

Fig. 4
figure 4

A sandwich, double wells ELISA plate showed positive samples for Cryptosporidium antigen. Rows A, C, E, G were sensitized with the anti-Cryptosporidium-specific antibody and rows B, D, F, H coated nonspecific antibodies. Control positive added in wells A1 and B1. The diluted samples added to the wells as follows: sample 1 in wells C1 and D1, sample 2 in wells E1 and F1, sample 3 G1 and H1, etc., till sample 47 in wells G12 and H12. Validation of the test; positive control optical density net (Delta) value < 1.151. Positive samples were numbers 25, 26, 42, 44 and 47 their S/P% (Delta optical density of sample/ Delta optical density of positive control *100) were > 7%

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Extraction of Cryptosporidium DNA

Forty-seven samples were selected for PCR testing and molecular typing of Cryptosporidium species. Criteria of selection of samples for PCR test was mainly those positive by two or more methods except four samples were positive using one test (3 samples from cattle suffered from profuse watery diarrhoea and were positive only using IC, whereas one sample was positive only using mZN from a cow with a history of decreased milk production and severely emaciated). The samples preserved in potassium dichromate were centrifugated twice in distilled water. DNA was extracted from all specimens (frozen and preserved) using the FastDNA SPIN kit for soil (MP Biomedicals, Santa Ana, CA, USA).

Nested PCR and RF LP of restriction enzymes SspI and MboII

Using a nested PCR targeting an approximately 830-bp fragment length of small subunit (SSU) rRNA gene was applied [45]. The primers utilized and the thermocycler program as formerly described [46, 47] are summarised in Supplementary file 1. Cryptosporidium molecularly differentiated by RFLP of the secondary PCR products using SspI and MboII (Fig. 5) as previously described [45]. Sequence analysis of the 60 KDa glycoprotein (gp60) gene was used to further analyze samples that tested positive for C. parvum at the SSU rRNA locus [47, 48].

Fig. 5
figure 5

RFLP analysis identifying the four species of Cryptosporidium isolated from cattle samples. M: Markers; 100-bp molecular markers. Lanes 1–3: C. andersoni SspI products 448, 397 bp, and lanes 14–16: C. andersoni MboII products 769, 76 bp. Lane 4: C. ryanae SspI products 432, 267,103, 33 bp, and lane 17: C. ryanae MboII products 574, 185, 76 bp. Lane 5: C. bovis SspI products 432, 267,103, 33 bp, and lane18: C. bovis MboII products 412, 185, 162, 76 bp. Lanes 6–11 C. parvum SspI products 449, 267, 397, 12, 11 bp, and lanes 19–24: C. parvum MboII products 771, 76 bp. Lanes 12 and 25: C. baileyi (control sample)

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Phylogenetic analysis

The 18S rRNA gene sequences of the recovered Cryptosporidium spp. were aligned with publicly available sequences to determine the relationship between Cryptosporidium species using ClustalX (http://www.Clustal.Org/). The 18S rRNA sequences of C. andersoni isolated from cattle in China (KC580754), C. parvum; strain Bovine C. parvum genotype (BOH6) isolated from calf in Ohio (AF093490), C. bovis; Bovis 2622 isolated from cattle (AY120911), C. ryanae RYanaeS6293a1 isolated from calves in China (HQ009807), and C. parvum_2_Sheep_Kuwait isolated from sheep in Kuwait [49].

Statistical analysis

A composite reference standard was applied to build a pseudo-gold standard for evaluating mZN, IC, and ELISA used to detect Cryptosporidium. The animal was classified as Cryptosporidium spp.-infected if either one of the reference tests, excluding the index test, were positive. For instance, to evaluate IC (index test), results of mZN and ELISA were used to build the pseudo-gold standard. The diagnostic performances and the 95% confidence interval of the three tests was computed using MdCalc® Statistical software. Using QuickCalcs, GraphPad Software®, kappa (κ) test agreement was computed and assessed. The Chi-square test (χ2) was used to evaluate the correlation between the different Cryptosporidium spp. diagnosed by PCR with the presence or absence of diarrhoea, and age group in the examined 47 faecal samples.

Availability of data and materials

The datasets used and/or analysed during the current study are not publicly available due [The authors still working on data for preparation of another manuscript] but are available from the corresponding author on reasonable request.

Abbreviations

C.:

Cryptosporidium

Spp.:

Species

mZN:

Modified Ziehl–Neelsen technique

IC:

Immunochromatography test

ELISA:

Enzyme Linked Immunosorbent Assay

PCR:

Polymerase Chain Reaction

RFLP:

Restriction Fragment Length Polymorphism

PPV:

Positive predictive value

NPV:

Negative predictive value

CI:

Confidence interval

κ-values:

Kappa test agreement

χ2 :

Chi-square test

References

  1. Xiao L. Molecular epidemiology of cryptosporidiosis: an update. Exp Parasitol. 2010;124(1):80–9. https://doi.org/10.1016/j.exppara.2009.03.018.

    Article  CAS  PubMed  Google Scholar 

  2. Lindsay DS, Upton SJ, Owens DS, Morgan UM, Mead JR, Blagburn BL. Cryptosporidium andersoni n. sp. (Apicomplexa: Cryptosporiidae) from cattle. Bos taurus J Eukaryot Microbiol. 2000;47(1):91–5. https://doi.org/10.1111/j.1550-7408.2000.tb00016.x.

  3. Santín M, Trout JM, Xiao L, Zhou L, Greiner E, Fayer R. Prevalence and age-related variation of Cryptosporidium species and genotypes in dairy calves. Vet Parasitol. 2004;122(2):103–17. https://doi.org/10.1016/j.vetpar.2004.03.020.

    Article  PubMed  Google Scholar 

  4. Fayer R, Santín M, Xiao L. Cryptosporidium bovis n. sp. (Apicomplexa: Cryptosporidiidae) in cattle (Bos taurus). J Parasitol. 2005;91(3):624–9. https://doi.org/10.1645/GE-3435.

    Article  PubMed  Google Scholar 

  5. Fayer R, Santín M, Trout JM. Cryptosporidium ryanae n. sp. (Apicomplexa: Cryptosporidiidae) in cattle (Bos taurus). Vet Parasitol. 2008;156(3–4):198. https://doi.org/10.1016/j.vetpar.2008.05.024.

    Article  Google Scholar 

  6. Ayinmode AB, Olakunle FB, Xiao L. Molecular characterization of Cryptosporidium spp. in native calves in Nigeria. Parasitol Res. 2010;107(4):1019–21. https://doi.org/10.1007/s00436-010-1972-1.

    Article  PubMed  Google Scholar 

  7. Ralston B, Thompson RC, Pethick D, McAllister TA, Olson ME. Cryptosporidium andersoni in Western Australian feedlot cattle. Aust Vet J. 2010;88(11):458–60. https://doi.org/10.1111/j.1751-0813.2010.00631.x.

    Article  CAS  PubMed  Google Scholar 

  8. Smith H. Diagnostic. In: Fayer R, Xiao L, editors. Cryptosporidium and Cryptosporidiosis. Boca Raton, Florida: CRC Press; 2008. p. 173–207.

  9. Foster DM, Smith GW. Pathophysiology of diarrhea in calves. Vet Clin North Am Food Anim Pract. 2009;25(1):13–36. https://doi.org/10.1016/j.cvfa.2008.10.013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Ezzaty Mirhashemi M, Zintl A, Grant T, Lucy FE, Mulcahy G, De Waal T. Comparison of diagnostic techniques for the detection of Cryptosporidium oocysts in animal samples. Exp Parasitol. 2015;151–152:14–20. https://doi.org/10.1016/j.exppara.2015.01.018.

    Article  CAS  PubMed  Google Scholar 

  11. Manouana GP, Lorenz E, Mbong Ngwese M, Nguema Moure PA, Maiga Ascofaré O, Akenten CW, et al. Performance of a rapid diagnostic test for the detection of Cryptosporidium spp. in African children admitted to hospital with diarrhea. PLoS Negl Trop Dis. 2020;14(7):e0008448. https://doi.org/10.1371/journal.pntd.0008448.

  12. Enøe C, Georgiadis MP, Johnson WO. Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown. Prev Vet Med. 2000;45(1–2):61–81. https://doi.org/10.1016/s0167-5877(00)00117-3.

    Article  PubMed  Google Scholar 

  13. Hui SL, Zhou XH. Evaluation of diagnostic tests without gold standards. Stat Methods Med Res. 1998;7(4):354–70. https://doi.org/10.1177/096228029800700404.

    Article  CAS  PubMed  Google Scholar 

  14. Thijs JC, van Zwet AA, Thijs WJ, Oey HB, Karrenbeld A, Stellaard F, et al. Diagnostic tests for Helicobacter pylori: a prospective evaluation of their accuracy, without selecting a single test as the gold standard. Am J Gastroenterol. 1996;91(10):2125–9.

    CAS  PubMed  Google Scholar 

  15. Rutjes AW, Reitsma JB, Coomarasamy A, Khan KS, Bossuyt PM. Evaluation of diagnostic tests when there is no gold standard. A review of methods. Health Technol Assess. 2007;11(50):iii–51. https://doi.org/10.3310/hta11500.

    Article  Google Scholar 

  16. Alonzo TA, Pepe MS. Using a combination of reference tests to assess the accuracy of a new diagnostic test. Stat Med. 1999;18(22):2987–3003. https://doi.org/10.1002/(sici)1097-0258(19991130)18:22%3c2987::aid-sim205%3e3.0.co;2-b.

    Article  CAS  PubMed  Google Scholar 

  17. Chalmers RM, Katzer F. Looking for Cryptosporidium: the application of advances in detection and diagnosis. Trends Parasitol. 2013;29(5):237–51. https://doi.org/10.1016/j.pt.2013.03.001.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Papini R, Bonelli F, Montagnani M, Sgorbini M. Evaluation of three commercial rapid kits to detect Cryptosporidium parvum in diarrhoeic calf stool. Ital J Anim Sci. 2018;17(4):1059–64. https://doi.org/10.1080/1828051X.2018.1452055.

    Article  Google Scholar 

  19. Danišová O, Halánová M, Valenčáková A, Luptáková L. Sensitivity, specificity and comparison of three commercially available immunological tests in the diagnosis of Cryptosporidium species in animals. Braz J Microbiol. 2018;49(1):177–83. https://doi.org/10.1016/j.bjm.2017.03.016.

    Article  CAS  PubMed  Google Scholar 

  20. Elwin K, Robinson G, Hadfield SJ, Fairclough HV, Iturriza-Gómara M, Chalmers RM. A comparison of two approaches to extracting Cryptosporidium DNA from human stools as measured by a real-time PCR assay. J Microbiol Methods. 2012;89(1):38–40. https://doi.org/10.1016/j.mimet.2012.02.006.

    Article  CAS  PubMed  Google Scholar 

  21. Flanigan TP, Soave R. Cryptosporidiosis. Prog Clin Parasitol. 1993;3:1–20. https://doi.org/10.1007/978-1-4612-2732-8_1.

    Article  CAS  PubMed  Google Scholar 

  22. Eassa S, Flefel W, El-Masry S, Abdul-Fattah A. Evaluation of Different Diagnostic Approaches for Detection of Cryptosporidium in Stools of Diarrheic Children. J High Inst Public Health. 2017;47(1):29–38. https://doi.org/10.21608/jhiph.2017.19975.

  23. Jex A, Smith H, Monis P, Campbell B, Gasser R. Cryptosporidium — biotechnological advances in the detection, diagnosis and analysis of genetic variation. Biotechnol Adv. 2008;26(4):304–17. https://doi.org/10.1016/j.biotechadv.2008.02.003.

    Article  CAS  PubMed  Google Scholar 

  24. Vastert D, Brinkman M, Wilke H, Mulder B. Diagnosis of Cryptosporidium parvum with microscopy, striptest, ELISA and real- time PCR. In: Regional Public Health Laboratory, Enschede, The Netherlands.; 2012. Abstract: P857. https://www.corisbio.com/pdf/Science/DUO-Crypto-Giardia/Diagnosis%20of%20Cryptosporidium%20with%20microscopy.pdf. Accessed 26 Dec 2021.

  25. Laude A, Valot S, Desoubeaux G, Argy N, Nourrisson C, Pomares C, et al. Is real-time PCR-based diagnosis similar in performance to routine parasitological examination for the identification of Giardia intestinalis, Cryptosporidium parvum/Cryptosporidium hominis and Entamoeba histolytica from stool samples? Evaluation of a new commercial multiplex PCR assay and literature review. Clin Microbiol Infect. 2016;22(2):1–190. https://doi.org/10.1016/j.cmi.2015.10.019.

    Article  Google Scholar 

  26. Anusz KZ, Mason PH, Riggs MW, Perryman LE. Detection of Cryptosporidium parvum oocysts in bovine feces by monoclonal antibody capture enzyme-linked immunosorbent assay. J Clin Microbiol. 1990;28(12):2770–4. https://doi.org/10.1128/jcm.28.12.2770-2774.1990.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Weitzel T, Dittrich S, Möhl I, Adusu E, Jelinek T. Evaluation of seven commercial antigen detection tests for Giardia and Cryptosporidium in stool samples. Clin Microbiol Infect. 2006;12(7):656–9. https://doi.org/10.1111/j.1469-0691.2006.01457.x.

    Article  CAS  PubMed  Google Scholar 

  28. Soltane R, Guyot K, Dei-Cas E, Ayadi A. Cryptosporidium parvum (Eucoccidiorida: Cryptosporiidae) in calves: results of a longitudinal study in a dairy farm in Sfax. Tunisia Parasite. 2007;14(4):309–12. https://doi.org/10.1051/parasite/2007144309.

    Article  CAS  PubMed  Google Scholar 

  29. Rahmouni I, Essid R, Aoun K, Bouratbine A. Glycoprotein 60 diversity in Cryptosporidium parvum causing human and cattle cryptosporidiosis in the rural region of Northern Tunisia. Am J Trop Med Hyg. 2014;90(2):346–50. https://doi.org/10.4269/ajtmh.13-0522.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kassouha M, Soukkarieh C, Alkhaled A. First genotyping of Cryptosporidium spp. in pre-weaned calves, broiler chickens and children in Syria by PCR-RFLP analysis. Vet Parasitol. 2016;225:86–90. https://doi.org/10.1016/j.vetpar. 2016.06.009

  31. Mirzai Y, Yakhchali M, Mardani K. Cryptosporidium parvum and Cryptosporidium andersoni infection in naturally infected cattle of northwest Iran. Vet Res Forum. 2014;5(1):55–60.

    PubMed  PubMed Central  Google Scholar 

  32. Taylan-Ozkan A, Yasa-Duru S, Usluca S, Lysen C, Ye J, Roellig DM, et al. Cryptosporidium species and Cryptosporidium parvum subtypes in dairy calves and goat kids reared under traditional farming systems in Turkey. Exp Parasitol. 2016;170:16–20. https://doi.org/10.1016/j.exppara.2016.06.014.

    Article  PubMed  Google Scholar 

  33. Naguib D, El-Gohary AH, Mohamed AA, Roellig DM, Arafat N, Xiao L. Age patterns of Cryptosporidium species and Giardia duodenalis in dairy calves in Egypt. Parasitol Int. 2018;67(6):736–41. https://doi.org/10.1016/j.parint.2018.07.012.

    Article  PubMed  Google Scholar 

  34. Taha S, Elmalik K, Bangoura B, Lendner M, Mossaad E, Daugschies A. Molecular characterization of bovine Cryptosporidium isolated from diarrheic calves in the Sudan. Parasitol Res. 2017;116(11):2971–9. https://doi.org/10.1007/s00436-017-5606-8.

    Article  PubMed  Google Scholar 

  35. Hijjawi N, Mukbel R, Yang R, Ryan U. Genetic characterization of Cryptosporidium in animal and human isolates from Jordan. Vet Parasitol. 2016;228:116–20. https://doi.org/10.1016/j.vetpar.2016.08.015.

    Article  PubMed  Google Scholar 

  36. Benhouda D, Hakem A, Sannella AR, Benhouda A, Cacciò SM. First molecular investigation of Cryptosporidium spp. in young calves in Algeria. Parasite. 2017;24:15. https://doi.org/10.1051/parasite/2017014.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kvác M, Vítovec J. Prevalence and pathogenicity of Cryptosporidium andersoni in one herd of beef cattle. J Vet Med B Infect Dis Vet Public Health. 2003;50(9):451–7. https://doi.org/10.1046/j.0931-1793.2003.00701.x.

    Article  PubMed  Google Scholar 

  38. Starkey SR, Zeigler PE, Wade SE, Schaaf SL, Mohammed HO. Factors associated with shedding of Cryptosporidium parvum versus Cryptosporidium bovis among dairy cattle in New York State. J Am Vet Med Assoc. 2006;229(10):1623–6. https://doi.org/10.2460/javma.229.10.1623.

    Article  PubMed  Google Scholar 

  39. Fayer R, Santín M, Trout J. Cryptosporidium in cattle: from observing to understanding. In: Ortega-Pierres G, Cacciò S, Fayer R, Mank T, Smith H, Thompson R, editors. Giardia and Cryptosporidium: From Molecules to Diseases; Wallingford, Oxfordshire, England. CABI; 2009. p. 12–24. Available from: https://doi.org/10.1079/9781845933913.0000

  40. Åberg M, Emanuelson U, Troell K, Björkman C. Infection dynamics of Cryptosporidium bovis and Cryptosporidium ryanae in a Swedish dairy herd. Vet Parasitol X. 2019;1: 100010. https://doi.org/10.1016/j.vpoa.2019.100010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Lorenz I, Fagan J, More SJ. Calf health from birth to weaning. II. Management of diarrhoea in pre-weaned calves. Ir Vet J. 2011;64(1):9. https://doi.org/10.1186/2046-0481-64-9

  42. Santín M. Clinical and subclinical infections with Cryptosporidium in animals. N Z Vet J. 2013;61(1):1–10. https://doi.org/10.1080/00480169.2012.731681.

    Article  PubMed  Google Scholar 

  43. Xiao L, Escalante L, Yang C, Sulaiman I, Escalante AA, Montali RJ, et al. Phylogenetic analysis of Cryptosporidium parasites based on the small-subunit rRNA gene locus. Appl Environ Microbiol. 1999;65(4):1578–83. https://doi.org/10.1128/AEM.65.4.1578-1583.1999.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Clarke SC, McIntyre M. Acid-fast bodies in faecal smears stained by the modified Ziehl-Neelsen technique. Br J Biomed Sci. 2001;58(1):7–10.

    CAS  PubMed  Google Scholar 

  45. Feng Y, Ortega Y, He G, Das P, Xu M, Zhang X, et al. Wide geographic distribution of Cryptosporidium bovis and the deer-like genotype in bovines. Vet Parasitol. 2007;144(1–2):1–9. https://doi.org/10.1016/j.vetpar.2006.10.001.

    Article  PubMed  Google Scholar 

  46. Xiao L, Singh A, Limor J, Graczyk TK, Gradus S, Lal A. Molecular characterization of Cryptosporidium oocysts in samples of raw surface water and wastewater. Appl Environ Microbiol. 2001;67(3):1097–101. https://doi.org/10.1128/AEM.67.3.1097-1101.2001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Alves M, Xiao L, Sulaiman I, Lal AA, Matos O, Antunes F. Subgenotype analysis of Cryptosporidium isolates from humans, cattle and zoo ruminants in Portugal. J Clin Microbiol. 2003;41(6):2744–7. https://doi.org/10.1128/JCM.41.6.2744-2747.2003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li N, Xiao L, Alderisio K, Elwin K, Cebelinski E, Chalmers R, et al. Subtyping Cryptosporidium ubiquitum, a zoonotic pathogen emerging in humans. Emerg Infect Dis. 2014;20(2):217–24. https://doi.org/10.3201/eid2002.121797.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Majeed QAH, El-Azazy OME, Abdou NMI, Al-Aal, ZA, El-Kabbany AI, Tahrani L, et al. Epidemiological observations on cryptosporidiosis and molecular characterization of Cryptosporidium spp. in sheep and goats in Kuwait. Parasitol Res 2018; 117(5): 1631– 1636. https://doi.org/10.1007/s00436-018-5847-1

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Acknowledgements

Authors would like to thank Dr. Amr Abdelaziz, Dr. Eman Hamza (Faculty of Veterinary Medicine, Cairo University) for their help in phylogenetic analysis.

Funding

This work was funded by the Kuwait Foundation for Advancement of Sciences (KFAS) [grant number 2012–1207-04].

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Authors and Affiliations

  1. GCC-Early Warning Center, PAAFR, Postal code, 1307, Rabyia, Kuwait

    Nadra-Elwgoud M. I. Abdou

  2. Department of Medicine and Infectious Diseases, Faculty of Veterinary Medicine, Cairo University, Post code 12211, Giza, Egypt

    Nadra-Elwgoud M. I. Abdou

  3. Department of Science, College of Basic Education, PAAET, Post code 23167, Aridyia, Kuwait

    Maha S. AlAzemi, Mohammed T. Al-Sayegh & Qais A. H. Majeed

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Contributions

Abdou, N.-E.M.I., Majeed, Q.A.H., Al-Sayegh, M.T., and AlAzemi, M.S. designed the experiments and methodology. Abdou, N.-E.M.I., Majeed, Q.A.H., carried out all assays. Abdou, N.-E.M.I. analysed all data and drafted the manuscript. All authors read and approved the final manuscript.

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Correspondence to Nadra-Elwgoud M. I. Abdou.

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Ethics approval and consent to participate

The Ethics Committee of Kuwait Foundation for Advancement of Sciences approved this field study (KFAS-Award Number 2012–1207-04). All methods were carried out in accordance with relevant institutional, national, and international guidelines and regulations and the manuscript conforms to the journal’s policies. A written informed consent was obtained from the owners of the farms prior collection of samples.

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Not Applicable.

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The authors declare no conflict of interest during the course of this study.

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Supplementary Information

Additional file1.

Nested PCR and RF LP of restriction enzymes SspI and MboII

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Abdou, NE.M.I., AlAzemi, M.S., Al-Sayegh, M.T. et al. Performance of diagnostic assays used to detect Cryptosporidium oocysts in faecal samples of cattle in Kuwait and genotyping of Cryptosporidium species. BMC Vet Res 18, 336 (2022). https://doi.org/10.1186/s12917-022-03435-w

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BMC Veterinary Research

ISSN: 1746-6148

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