|Year : 2014 | Volume
| Issue : 2 | Page : 129-137
Use of nested PCR-RFLP for genotyping of Cryptosporidium parasites isolated from calves and children suffering from diarrhea
Gehan S Sadek MD
Department of Parasitology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
|Date of Submission||21-Jun-2014|
|Date of Acceptance||09-Sep-2014|
|Date of Web Publication||19-Jan-2015|
Gehan S Sadek
10th Ahmed Zaky Street, El Noza El Gedeeda, 11769, Cairo
Source of Support: None, Conflict of Interest: None
The vast majority of human cases of cryptosporidiosis worldwide are caused by two species: Cryptosporidium hominis (C. parvum type 1), which causes infection in humans only, and Cryptosporidium parvum (C. parvum type 2), which causes infections in humans and animals. In Egypt, calves carrying the zoonotic C. parvum represent the largest farm animal source of infection for humans. Information on the source of Cryptosporidium spp. contamination is necessary for effective evaluation and selection of management practices for reducing the risk for cryptosporidiosis.
The aim of the study was to genotypically characterize Cryptosporidium spp. in a sample of isolates from calves and children suffering from diarrhea.
Materials and methods
One hundred stool samples were collected from diarrheic calves housed at the Tropical Diseases Clinic, Faculty of Veterinary Medicine, Cairo University. A total of 110 stool samples were also collected from diarrheic children attending the Gastroenteritis Unit, Abo El Reesh Pediatric Hospital, Cairo University. Each stool sample of children or calves was examined microscopically after staining with modified Ziehl-Neelsen stain for the diagnosis of Cryptosporidium spp. Positive samples were then subjected to nested PCR-restriction-fragment length polymorphism (PCR-RFLP) targeting Cryptosporidium oocyst wall protein (COWP) gene for determination of Cryptosporidium genotypes.
Screening by modified Ziehl-Neelsen staining detected Cryptosporidium in stools of 40% of diarrheic calves. Nested PCR-RFLP analysis showed that all positive samples were related to C. parvum genotype 2 (C. parvum). In diarrheic children, screening diagnosed 12/110 (10.9%) positive cases; 9/12 (75%) of them were confirmed positive by nested PCR. RFLP analysis showed that 8/9 (88.9%) samples were C. parvum genotype 1 (C. hominis), whereas one sample was not digested.
Genotype 2 C. parvum is relatively highly prevalent in the sample of calves examined compared with genotype 1 in the sample of children, indicating that transmission of cryptosporidiosis among this sample of children is anthroponotic and not zoonotic. It is advised to include PCR-RFLP technique in routine clinical diagnosis and epidemiological investigations.
Keywords: calves, children, COWP gene, Cryptosporidium, PCR-RFLP
|How to cite this article:|
Sadek GS. Use of nested PCR-RFLP for genotyping of Cryptosporidium parasites isolated from calves and children suffering from diarrhea. Parasitol United J 2014;7:129-37
|How to cite this URL:|
Sadek GS. Use of nested PCR-RFLP for genotyping of Cryptosporidium parasites isolated from calves and children suffering from diarrhea. Parasitol United J [serial online] 2014 [cited 2018 Dec 18];7:129-37. Available from: http://www.new.puj.eg.net/text.asp?2014/7/2/129/149568
| Introduction|| |
Cryptosporidium is an apicomplexan parasite that infects the microvillus border of the gastrointestinal epithelium in a wide range of vertebrate hosts, including humans and cattle  . Infection with Cryptosporidium spp. leads to severe but usually self-limiting diarrhea in immunocompetent individuals but can be life threatening in immunocompromised hosts  . The entire life cycle of this parasite takes place in the intestinal epithelium and transmission occurs in the form of environmentally resistant oocysts by the fecal oral route through contaminated food and/or water , . Oocysts are even resistant to chlorine disinfection and can survive for days in treated water  . This has resulted in major waterborne outbreaks  , which together with lack of effective treatment makes cryptosporidiosis a major public health issue and economic problem  . The vast majority of human cases of cryptosporidiosis worldwide are caused by two species: Cryptosporidium hominis and Cryptosporidium parvum  . C. hominis is known as C. parvum type 1 and C. parvum is known as C. parvum type 2  . However, other species including Cryptosporidium felis, Cryptosporidium meleagridis, Cryptosporidium canis, Cryptosporidium suis, and Cryptosporidium muris can also infect humans  . Of the two major genotypes that infect humans, C. hominis causes infections in humans only (anthroponotic infection), whereas C. parvum causes infections in humans and animals (zoonotic infection). Clinically, C. hominis reportedly causes long-term diarrhea and more oocyst excretions, whereas C. parvum causes short-term diarrhea and less oocyst excretion  .
Information on the source of Cryptosporidium contamination is necessary for effective evaluation and selection of management practices for reducing the risk for cryptosporidiosis  . C. parvum has long been considered zoonotic and the ability of this species to be transmitted from animals to humans is well documented  . Contact with infected calves has been implicated as the cause of many cryptosporidiosis outbreaks in veterinary students, research technicians, and children residing in agricultural areas  . In Egypt, calves carrying the zoonotic C. parvum may be considered the biggest farm animal source of infection to humans. High prevalence rates of cryptosporidiosis among calves recorded by several studies indicate the potential risk of parasite transmission to humans through contact with infected cattle feces or through milk and food contaminated with oocysts  .
Laboratory diagnosis is generally based on microscopic detection of oocysts in stained smears, which offers no information on the infecting species  and may prove inadequate in diagnosing a small number of parasites  . Besides, it is not suitable for epidemiological investigations  . Immunofluorescence assay has been used widely for the detection of Cryptosporidium spp. The use of monoclonal antibodies in immunofluorescence and confocal microscopy has revealed fluorescent staining specifically confined to the oocyst walls of C. muris and C. parvum  . Kamal et al.  concluded that immunofluorescence is rapid and more sensitive and specific than the conventional acid fast and merthiolate-iodine-formaldehyde concentration for the detection of Cryptosporidium oocysts and Giardia cysts. However, oocyst morphology, host specificity, or preferences in infection sites do not provide sufficient information for the identification of Cryptosporidium spp., genotypes, or subgenotypes , . Consequently, molecular analysis used to characterize the genetic structure of Cryptosporidium parasites and to assess their zoonotic significance  proved to be a sensitive diagnostic method capable of determining Cryptosporidium spp. with high selectivity in environmental and clinical samples and allowing for genotyping  . In recent years, researchers have developed PCR-based techniques for the detection and identification of Cryptosporidium spp. These techniques target the genes of thrombospondin-related adhesive protein 1 (TRAP-C1)  , thrombospondin-related adhesive protein 2 (TRAP-C2), polythreonine repeat (Poly-T)  , small subunit rRNA  , internally transcribed spacer 1 (ITS1)  , Cryptosporidium oocyst wall protein (COWP)  , dihydrofolate reductase (DHFR)  , and undefined genomic sequences among strains that infect humans and most animals , . The most commonly used genotyping tool is a small subunit rRNA gene-based RFLP, which has been used effectively for genotyping Cryptosporidium oocysts  . Molecular analysis of C. parvum revealed several families among isolates from humans and/or cattle as well as several subtypes within each family  .
Although cryptosporidiosis is frequent in humans and livestock in Egypt  , little information is available about the genetic diversity of this parasite. Exposition of Cryptosporidium genotypes by molecular assays is required to recognize sources of infections and routes of transmission, facilitating the improvement of risk assessment and measures for prevention and control  . Hence, the present work aimed to determine Cryptosporidium genotypes in stool samples of calves and children suffering from diarrhea using nested PCR-RFLP targeting the COWP gene.
| Materials and methods|| |
Type of the study
Descriptive analytical study.
The study was conducted from August 2013 to December 2013.
Study design and collection of samples
One hundred samples were collected from diarrheic calves at the Tropical Diseases Clinic, Faculty of Veterinary Medicine, Cairo University. Fifty-two samples were from calves aged less than 1 month (group A) and 48 samples were from calves aged 1-2 months (group B). A total of 110 samples were also collected from diarrheic children attending the Gastroenteritis Unit, Abo El Reesh Pediatric Hospital, Cairo University. The children were aged 3 months to 8 years and were of both sexes. They were classified according to their age into four groups: group 1 included children aged 3-6 months (23 cases); group 2 included children aged 7-12 months (33 cases); group 3 included children aged 1-5 years (41 cases); and group 4 included children aged 6-8 years (13 cases). Parents were asked about the duration of diarrhea, presence of vomiting, abdominal colic, and fever. The consistency of stool of every child was also recorded. Each stool sample was divided into two parts. The first was subjected to concentration and microscopic examination and the second was kept at −20°C for molecular assay.
Microscopic examination of samples
The first part of each sample was concentrated twice by formalin ether sedimentation method  , and smears were stained by modified Ziehl-Neelsen (MZN) stain  . Stained smears were examined through ×40 objective and then ×100 objective.
Polymerase chain reaction
Molecular assay was performed at the Diagnostic and Research Unit of Parasitic Diseases, Medical Parasitology Department, Kasr Al-Ainy School of Medicine, Cairo University. Samples proved positive by microscopic examination were subjected to DNA extraction. Before extraction, each sample was subjected to eight cycles of freezing in liquid nitrogen for 1 min, followed by thawing at 98°C for 1 min to disrupt the oocyst wall ,,, . DNA extraction was performed with the Favor Stool DNA Spin Columns Isolation Mini Kit (cat. no. FAST1; Favorgen Biotech Corporation, Taiwan) following the manufacturer's instructions. Incubation was performed at 56°C for 10 min and then the temperature was raised to 95°C for 1 h. This gave a better yield of extracted DNA with excellent DNA/protein ratio, indicating that the proteinase K in the extraction buffer eliminated all or most of the protein.
Nested polymerase chain reaction of the Cryptosporidium oocyst wall protein gene
According to Spano et al.  and Pedraza-Díaz et al.  , nested PCR of the COWP gene included two consecutive PCR reactions. The first reaction amplified the 769 bp fragment by using an external pair of primer sets - BCOWPF: 5´-ACC GCT TCT CAA CAA CCA TCT TGT CCT C-3´; and BCOWPR: 5´-CGC ACC TGT TCC CAC TCA ATG TAA ACC C-3´. The second reaction contained two nested primers internal to the first primer pair and delimits a 553 bp fragment. These were nest Cry-15: 5´-GTA GAT AAT GGA AGA GAT TGT G-3´ and Cry-9: 5´-GGA CTG AAA TAC AGG CAT TAT CTT G-3´. The larger fragment produced by the first reaction was used as a template for the second reaction. Oligonucleotide primers were synthesized by Fermentas (Fermentas UAB, Lithuania). Amplification in each reaction was done on the PCR mix, which consisted of 12.5 μl PCR Master Mix (product no. K1081; Thermo Scientific, UK), 1 μl (200 nmol/l) of each forward and reverse primer, 2.5 μl of template DNA, 0.1 μl Taq polymerase (5 U/μl) (product no. EP0701; Thermo Scientific), and 7.9 μl of sterile distilled water to complete a total volume of 25 μl. Reactions were performed in a gradient thermal cycler (professional thermocycler, Biometra; Applied Biosystems, California, USA) after adjusting the thermal profile to initial denaturation at 95°C for 4 min, followed by 30 cycles of amplification consisting of denaturation at 94°C for 60 s, annealing at 65°C for 60 s, and extension at 72°C for 60 s. Final elongation was performed at 72°C for 10 min. The second-round PCR was identical to the first-round PCR except for denaturation at 94°C for 50 s, annealing at 54°C for 30 s, and extension at 72°C for 50 s. The amplified PCR products were separated by electrophoresis on 2% agarose gel in TBE buffer and visualized under a transilluminator after staining with ethidium bromide.
Restriction-fragment length polymorphism analysis
RFLP analysis was performed according to the manufacturer's instructions by digesting 10 μl of nested PCR product (target DNA) with 1 μl of RsaI (product no. ER1121; Thermo Scientific) in 2 μl green buffer and adding 17 μl nuclease-free water to reach a final volume of 30 μl. Gentle mixing was done followed by spinning down for a few seconds and then incubation at 37°C for 5 min. Cryptosporidium genotypes were detected by using electrophoresis in 3.2% typing-grade agarose gels containing ethidium bromide, and gels were recorded by UV transillumination. By using restriction enzyme RsaI for digestion of nested PCR products targeting the COWP gene, we detected two genotypes of Cryptosporidium: genotype 1 (C. hominis), when four bands appeared at 34, 106, 125, and 285 bp; and genotype 2 (C. parvum), when three bands appeared at 34, 106, and 410 bp , .
Data were collected, tabulated, and statistically analyzed by means of a computer using SPSS (version 16; SPSS Inc., Chicago, Illinois, USA); two types of statistical analyses were performed. Descriptive statistics including qualitative data expressed in number and percentage and quantitative data expressed to measure the central tendency of data and diversion around the mean (X) and SD. The Mann-Whitney test was used to compare between two quantitative variables not normally distributed. The χ2 - test was used to compare categorical outcomes, and Fischer's exact test was used to compare categorical outcomes of 2 × 2 tables if one of the cells is less than 5. P values less than or equal to 0.05 were considered statistically significant.
| Results|| |
Examination of MZN-stained fecal samples of children and calves revealed Cryptosporidium oocysts as round or ovoid 2-6 μm bright red structures against a green background. They had distinct thick walls and various inner structures, as four dark sporozoites could be seen in some oocysts ([Figure 1] and [Figure 2]). This preliminary screening detected 40% of diarrheic samples from calves positive for Cryptosporidium. Nested PCR-RFLP analysis showed that all of these positive samples were of C. parvum genotype 2 (C. parvum) ([Figure 3]), 25/52 were from group A (48.07%) and 15/48 (31.25%) were from group B. There was no statistically significant difference between the two groups (P>0.05) ([Table 1]). Screening of 110 children's fecal smears revealed 12 positive Cryptosporidium samples (10.9%). By nested PCR, the COWP gene was successfully amplified in only 9/12 (75%) samples ([Figure 3]). RFLP analysis showed that 8/9 (88.9%) samples were positive by PCR, classified as genotype 1 (C. hominis), whereas one sample was not digested (11.1%) ([Figure 3]).
|Figure 1 Cryptosporidium oocysts ↑ in feces of an infected child (modified Ziehl– Neelsen stain, ×800).|
Click here to view
|Figure 2 Cryptosporidium oocyst ↑ in stool of an infected calf (modified Ziehl– Neelsen stain, ×1000).|
Click here to view
|Figure 3 Agarose gel electrophoresis for the products of the nested PCR targeting the Cryptosporidium oocyst wall protein (COWP) gene of Cryptosporidium at 553 bp and restriction-fragment length polymorphism products after digestion with RsaI endonuclease. Lane 1: 100 bp DNA marker ladder. Lanes 2, 3, and 4: Cryptosporidium parvum genotype 2 digestion products at 34, 106, and 410 bp (34 band is very small, faint, and difficult to see). Lanes 5 and 6: Cryptosporidium hominis genotype 1 digestion products at 34, 106, 125, and 285 bp. Lanes 7 and 8: product of nested PCR targeting the COWP gene at 553 bp.|
Click here to view
|Table 1 Results of examination of 100 fecal samples from two age groups of diarrheic calves by modified Ziehl– Neelsen stain|
Click here to view
On correlating the age of infected children with Cryptosporidium infection, 2/12 (16.7%) positive cases were found to be from group 1 (3-6 months), two (16.7%) cases from group 2 (7-12 months), five (41.6%) cases from group 3 (1-5 years), and three (25%) cases from group 4 (6-8 years). The difference between these four age groups regarding Cryptosporidium infection was not statistically significant (P > 0.05) ([Table 2]). Correlation between sex and infection in the 12 positive cases showed equally positive occurrence in male and female children (50%). The difference between the two sexes was not significant (P > 0.05) ([Table 2]). The relation between consistency of children's stools and infection showed that 6/12 (50%) positive cases had formed stool, four (33.3%) cases had loose stool, and two (16.7%) cases had watery stool. There was no statistically significant correlation between consistency of stool and Cryptosporidium infection (P > 0.05) ([Table 2]).
|Table 2 Correlation between age groups, sex, consistency of stool, duration of diarrhea, clinical manifestations, and Cryptosporidium infection in examined children|
Click here to view
The relation between duration of diarrhea and infection showed that 5/12 (41.7%) positive cases had diarrhea for 1-5 days, whereas seven (58.3%) cases had diarrhea for more than 5 days, with nonsignificant difference (P > 0.05) between these two groups ([Table 2]). The clinical manifestations of the examined children recorded the occurrence of vomiting in 2/12 (16.7%) positive cases and 54/98 (55.1%) negative cases. Abdominal colic occurred in 9/12 (75.5%) positive cases and in 91/98 (92.9%) negative cases. In addition, 6/12 (50%) positive cases suffered from fever versus 83/98 (84.7%) negative cases. Statistical analysis showed that there was no significant correlation between these three clinical manifestations and occurrence of Cryptosporidium infection (P > 0.05) ([Table 2]).
| Discussion|| |
Cryptosporidiosis is a cause of diarrhea in children and immunocompromised patients worldwide  . It also frequently affects domestic animals, with a strong relation found between cryptosporidiosis infection and diarrhea among Egyptian buffalo calves  . In Egypt, several studies have been devoted to ascertain cryptosporidiosis in humans , and animals , . The application of genotyping techniques has provided a better understanding of the epidemiology of cryptosporidiosis  , including its different sources of transmission , . At present, a variety of genotypic markers are available to differentiate species and subspecies within the genus Cryptosporidium  . Nested PCR has proven more beneficial than primary PCR and produces more positive results  . Hence, the present work aimed to determine Cryptosporidium genotypes in stools of calves and children suffering from diarrhea using nested PCR-RFLP targeting the COWP gene.
Cryptosporidium oocysts detected in this study were morphologically similar to those detected in many previous studies , . Morgan-Ryan et al.  cited that morphometric measurement of oocysts represents the cornerstone of Cryptosporidium taxonomy and is one of the requirements for establishing a new species; however, it is not adequate by itself and other parameters must be used.
In the present study, the infection rate of cryptosporidiosis in examined calves was 40%. This result is not unexpected as traditionally cattle have been considered the primary nonhuman species impacted by cryptosporidiosis and the major source of Cryptosporidium for human infections  . Having targeted diarrheic calves, our recorded rate proved higher than that of previous studies in Egypt, in which the prevalence was 30.2% in dairy calves  and 21.7% in buffalo calves  . It is also higher than the 26% recorded in Brazil  . However, it is lower than the 54.4% recorded in diarrheic calves from Behira locality in Egypt  , and in the USA (95%)  . Several factors may be responsible for the differences in infection rates between the present and previous studies, such as the breeding conditions of the calves, husbandry and management system, exact age and nursing conditions of the calves, season of the sample collection, and the sanitary conditions inside and around the farms. Some of these factors may act individually or collectively to increase the risk factors associated with transmission and prevalence of Cryptosporidium between calves  . In the present study, the infection rate of cryptosporidiosis in calves aged less than 1 month was higher than that in calves aged 1-2 months (48.07 and 31.25%, respectively). This result is consistent with that of Hassanain et al.  in Egypt but was contradictory to that of the Brazilian study  in which the lowest prevalence was in calves aged less than 1 month. However, another study stated that only preweaned calves are important sources of zoonotic cryptosporidiosis in humans  . All of our positive fecal samples from calves were classified as genotype 2 (C. parvum) by RFLP analysis. This result is in agreement with the majority of worldwide studies, which have reported C. parvum as the most prevalent and widely distributed species in neonatal and preweaned dairy cattle  .
The infection rate in the present sample of diarrheic children was 10.9%. A higher rate of 17% was recorded in Egypt by Abdel-Messih et al.  , whereas similar rates of 10.3% were recorded in Pakistan by Mojarad et al.  and in a cross-sectional study of cryptosporidiosis in Saudi diarrheal children in whom the overall prevalence was 9.6%  . The discrepancy in infection rates is expected, because of differences in the living conditions of children or differences in their immune status. In the present study, the COWP gene was successfully amplified in 75% of samples that were positive on MZN staining. Another report noted lower positivity of PCR as opposed to microscopy  . This may be attributed to failure of amplification of some fecal samples derived from a diminished quantity of DNA, either due to its degradation in time or due to the presence of some PCR inhibitors such as lipids, hemoglobin, bile salts, polysaccharides from mucus, bacteria, and food degradation products  . As indicated, PCR inhibitors may act at three levels: interference in cellular lysis, degradation or uptake of nucleic acids, and inactivation of thermostable polymerases  . It was proved that the QIAamp DNA Stool Mini Kit removes these inhibitors by absorbing them in the Inhibitex matrix  . Naeini et al.  stated that the inhibitors may be removed by repeated washing of collected oocysts with PBS buffer, but with the disadvantage of possible decrease in the recovery rate of oocysts and consequent reduction in the final DNA concentration and sensitivity of PCR. However, in another report by Coupe et al.  PCR-RFLP was applied to routine clinical samples, with 98.5% detection rate of infection in patients with positive microscopic results and in two other stool samples that had not been found positive on microscopic examination. The same authors added that they believed those results were not PCR false positives but rather they reflected the higher sensitivity of PCR for low-level infection. This group of researchers  used the previously mentioned QIAamp DNA Stool Mini Kit for DNA extraction, that removes DNA inhibitors by absorbing them in the Inhibitex matrix  , which may explain the high diagnostic yield obtained in that study. However, in our study, following the manufacturer's instructions, no extra measures were taken for removing DNA inhibitors as it was mentioned in the kit manual that inhibitors are removed. Besides, Yu et al.  stated that although microscopy was useful for identification of infection, this tool is relatively insensitive when a small number of oocysts are excreted or the period of oocyst shedding is short. Therefore, many infections may escape microscopic detection. Moreover, Silva et al.  claimed that their results and those of previous studies indicate that the detection of Cryptosporidium oocysts in fecal smears by microscopy is less sensitive than the detection of DNA by PCR. Furthermore, Nikaeen et al.  mentioned that the nested PCR procedure described in their study further enhanced the sensitivity of PCR, so that they could detect as few as one oocyst in purified samples. Bairami Kuzehkanan et al.  reported that nested PCR was better than primary PCR as it detected one more case that was negative on both microscopy and primary PCR. Another advantage over microscopy is the ability of PCR tools to differentiate Cryptosporidium spp. by incorporating RFLP analysis as well as DNA sequencing or other molecular procedures that allow the differentiation of species or genotypes  .
In the current work, RFLP analysis classified 88.9% of the children's positive fecal samples as genotype 1 (C. hominis), whereas one (11.1%) sample was not digested. None of the samples were classified as genotype 2 (C. parvum). These results are in agreement with previous studies reporting the predominance of C. hominis species in some nations such as Brazil  , Malawi  , the USA  , Thailand  , Japan  , and South Africa  . In France, Coupe et al.  obtained 98.5% of stool samples from patients with microscopically proven cryptosporidiosis and two other stool samples positive by PCR and had them genotyped by PCR-RFLP analysis as 47.7% related to C. hominis, 34.1% related to C. parvum, 13.6% related to C. meleagridis, and 4.5% to C. felis. Interestingly one of their negative PCR samples that had microscopically shown rare oocysts proved to contain a potent inhibitor that could not be efficiently removed. Also, Gatei et al.  in Kenya found that 87% of the PCR-positive cases were C. hominis, 9% were C. parvum, and the remaining 4% were C. canis, C. felis, C. meleagridis, and C. muris. Moreover, Feng et al.  reported that C. hominis was the predominant species in wastewater in Shanghai (China). They indicated that anthroponotic transmission is important in cryptosporidiosis epidemiology in that area, and commented that C. hominis is responsible for far more infections than C. parvum in humans in developing countries where genotyping studies were conducted. It was suggested that anthroponotic transmission of Cryptosporidium spp. in outbreaks that had occurred in swimming pools might be associated with fecal contamination from a single infected person (especially in toddler pools), in which case a single genotype is recovered from the patients  . However, our results contradict those obtained by some previous authors in the Netherlands and UK where C. parvum was more predominant than C. hominis in humans , . Several authors previously stressed on the zoonotic transmission of Cryptosporidium spp. Pedraza-Díaz et al.  mentioned that patients reporting contact with animals or farms were almost all infected by genotype 2 (C. parvum). Also Mojarad et al.  found that C. parvum infection predominated in children in Iran (83.4%), indicating the probability of high prevalence of bovine cryptosporidiosis in that area. Moreover, Usluca and Aksoy  stated that the majority of cases diagnosed in their study infected with C. parvum and C. meleagridis species lived and bred animals in rural areas. They also mentioned that lack of hygiene, poor living conditions, and direct contact with farm animals in which cryptosporidiosis has a high prevalence account for the spread of infection. Pedraza-Díaz et al.  in their study on 1300 sporadic cases indicated that patients reporting contact with animals or farms were almost all infected by genotype 2, which was apparently also exclusively responsible for the spring peak. Genotype 1 was significantly more common in patients infected during the late summer-autumn peak and in those with a history of foreign travel. There were also distinct geographical variations in the distribution of genotypes.
It must be mentioned that waterborne cryptosporidiosis and giardiasis are significant public health concerns  . Cryptosporidium and Giardia spp. are threats in water supplies because their infecting stages are resistant to chlorine disinfection; moreover, they have a low infectious dose and they are harbored by many animal species  . Consequently, numerous waterborne outbreaks of cryptosporidiosis and giardiasis have been documented  . Cryptosporidium and Giardia spp. are reportedly the two major pathogens specifically identified in drinking water regulations in industrialized countries  . The incorporation of flow cytometry improved the sensitivity of detection of Giardia cysts and Cryptosporidium oocysts and the accurate estimation of their quantity and viability in water samples from Alexandria (Egypt)  . Oocysts of both genotypes 1 and 2 are water transmissible, and in one report of seven drinking waterborne outbreaks four were almost exclusively due to genotype 1 and three due to genotype 2  . Thus, controlling agricultural and human sewage discharge is important in watershed protection  .
In the present work, the highest percentage of infection was recorded in children aged 1-5 years and the lowest in children under 1 year. This result is in accordance with reports by Wellington et al.  and Yoder et al.  . Children under 1 year may be protected by immunoglobulins conferred by breast feeding or by unexposure to contaminated water. Although it is generally believed that a high percentage of infected children complain of watery stools  , we found fewer number of positive children with watery diarrhea. This may be explained by a difference in the immune status of examined children or a difference in the method of their selection. In addition, we found no significant relation between duration of diarrhea and cryptosporidiosis, an observation consistent with that of Usluca and Aksoy  . Our recorded clinical manifestations in infected children, such as vomiting, abdominal colic, and fever, are consistent with previous studies , . However, it was found that there was no significant statistical difference between negative and positive cases regarding these clinical manifestations.
| Conclusion|| |
Hence, it can be concluded that C. parvum (genotype 2) is relatively highly prevalent in the sample of calves examined. All infected children showed C. hominis (genotype 1). Thus, it seems that transmission of cryptosporidiosis in these children was anthroponotic and not zoonotic. Attention must be given for periodic determination of Cryptosporidium spp. in watersheds or sources of water, which in turn will be helpful in the development of strategies for their scientific management and protection. Nested PCR-RFLP is an added advantage for the determination of Cryptosporidium genotype in suspected cases. Information generated from this study is useful not only in identifying the sources of contamination but also in helping public healthcare systems in the prevention and management of cryptosporidiosis through development of precautionary measures.
| Acknowledgements|| |
The author expresses her gratitude to Professor Dr. Ayman A. El-Badry, Head of Diagnostic and Research Unit of Parasitic Diseases, Medical Parasitology Department, Kasr Al-Ainy School of Medicine, Cairo University, for his assistance in performing nested PCR-RFLP.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Silva FM, Lopes RS, Araújo-Junior JP. Identification of Cryptosporidium
species and genotypes in dairy cattle in Brazil. Rev Bras Parasitol Vet 2013; 22:22-28.
Clark EL, Blake DP. Genetic mapping and coccidial parasites: past achievements and future prospects. J Biosci 2012; 37:879-886.
Dawson D. Foodborne protozoan parasites. Int J Food Microbiol 2005; 103:207-227.
Smith HV, Nichols RA. Cryptosporidium
detection in water and food. Exp Parasitol 2010; 124:61-79.
Naeini KM, Asadi M, Chaleshtori MH. Detection and molecular characterization of Cryptosporidium
species in recreational waters of Chaharmahal va Bakhtiyari Province of Iran using nested PCR-RFLP. Iran J Parasitol 2010; 6:20-27.
Hassanain MA, Khalil FAM, Abd El-Razik KA, Shaapan RM. Prevalence and molecular discrimination of Cryptosporidium parvum
in calves in Behira Provinces, Egypt. Res J Parasitol 2011; 6:101-108.
Coupe S, Sarfati C, Hamane S, Derouin F. Detection of Cryptosporidium
and identification to the species level by nested PCR and restriction fragment length polymorphism. J Clin Microbiol 2005; 43:1017-1023.
Del Chierico F, Onori M, Di Bella S, et al
. Cases of cryptosporidiosis co-infections in AIDS patients: a correlation between clinical presentation and GP 60 subgenotype lineages from aged formalin-fixed stool samples. Ann Trop Med Parasitol 2011; 105:339-349.
Hunter PR, Hadfield SJ, Wilkinson D, Lake IR, Harrison FCD, Chalmers RM. Subtypes of Cryptosporidium parvum
in humans and disease risk. Emerg Infect Dis 2007; 13:82-88.
Xiao L, Ryan UM. Cryptosporidiosis: an update in molecular epidemiology. Curr Opin Infect Dis 2004; 17:483-490.
Usluca S, Aksoy U. Detection and genotyping of Cryptosporidium
spp. in diarrheic stools by PCR-RFLP analyses. Turk J Med Sci 2011; 41:1029-1036.
Xiao L, Lal AA, Jiang J. Detection and differentiation of Cryptosporidium
oocysts in water by PCR-RFLP. In: John FT, Ruget S, Alicia L, Otawa NJ, editors: The public health microbiology, methods and protocols, 2004. Totowa, NJ: Human Press, 163-267.
Widmer G, Sullivan S. Genomics and population biology of Cryptosporidium
species. Parasite Immunol 2012; 34:61-71.
Coco DVF, Cordoba MA, Basualdo JA. Cryptosporidiosis: an emerging zoonosis. Rev Argent Microbiol 2009; 41:185-196.
Yu J, Lee S, Park W. Comparative sensitivity of PCR primer sets for detection of Cryptosporidium parvum
. Korean J Parasitol 2009; 47:293-297.
Kaushik K, Khurana S, Wanchu A, Malla N. Evaluation of staining techniques, antigen detection and nested PCR for the diagnosis of cryptosporidiosis in HIV seropositive and seronegative patients. Acta Trop 2008; 107:1-7.
Yu JR, O'Hara SP, Lin JL, Dailey ME, Cain G, Lin JL. A common oocyst surface antigen of Cryptosporidium
recognized by monoclonal antibodies. Parasitol Res 2002; 88:412-420.
Kamal KA, El Dib NA, Hassanin FS. Evaluation of immunoflourescent antibody (IFA) kit for the detection of Cryptosporidium parvum
oocysts and Giardia lamblia
cysts in stool specimens. PUJ 2008; 1:145-147.
Fall A, Thompson RC, Hobbs RP, Morgan-Ryan UJ. Morphology is not a reliable tool for delineating species within Cryptosporidium
. Parasitology 2003; 89:399-402.
Jex AR, Gasser RB. Genetic richness and diversity in Cryptosporidium hominis
and Cryptosporidium parvum
reveals major knowledge gaps and a need for the application of 'next generation' technologies research review. Biotechnol Adv 2010; 28:17-26.
Xiao L. Molecular epidemiology of cryptosporidiosis: an update. Exp Parasitol 2010; 124:80-89.
Spano F, Putignani L, Guida S, Crisanti A. Cryptosporidium parvum
PCR-RFLP analysis of the TRAP-C1 (thrombospondin-related adhesive protein ofCryptosporidium
-1) gene discriminates between two alleles differentially associated with parasite isolates of animal and human origin. Exp Parasitol 1998; 90:195-198.
Sulaiman IM, Xiao L, Lal AA. Evaluation of Cryptosporidium parvum
genotyping techniques. Appl Environ Microbiol 1999; 65:4431-4435.
Xiao L, Escalante L, Yang C, et al
. Phylogenetic analysis of Cryptosporidium
parasites based on the small subunit rRNA locus. Appl Environ Microbiol 1999; 65:1578-1583.
Morgan-Ryan UM, Monis P, Possenti A, Crisanti A, Spano F. Cloning and phylogenetic analysis of the ribosomal internal transcribed spacer-1 (TSI1) of Cryptosporidium wrairi
and its relationship to Cryptosporidium parvum
genotypes. Parasitologia 2001; 43:159-163.
Akiyoshi DE, Feng X, Buckholt MA, Widmer G, Tzipori S. Genetic analysis of a Cryptosporidium parvum
human genotype 1 isolate passaged through different host species. Infect Immun 2002; 70:5670-5675.
Cama V, Gilman RH, Vivar A, et al
. Mixed Cryptosporidium
infections and HIV. Emerg Infect Dis 2006; 12:1025-1028.
Sulaiman IM, Lal AA, Xiao L. Molecular phylogeny and evolutionary relationships of Cryptosporidium
parasites at the action locus. J Parasitol 2002; 88:388-394.
Mojarad EN, Keshavaraz A, Taghipour N, Haghighi A, Kazemi B, Athari A. Genotyping of Cryptosporidium
spp. in clinical samples PCR-RFLP analysis of the TRAP-C2 gene. Gastroenterol Hepatol 2011; 4:29-33.
Feng Y, Zhao X, Chen J, et al
. Occurrence, source and human infection potential of Cryptosporidium
spp. in source and tap water in Shanghai, China. Appl Environ Microbiol 2011; 77:3609-3616.
Wielinga PR, de Vries A, Van der Goot TH, et al
. Molecular epidemiology of Cryptosporidium
in humans and cattle in the Netherlands. Int J Parasitol 2008; 38:809-817.
Helmy YA, Krücken J, Nöckler K, von Samson-Himmelstjerna G, Zessin KH. Molecular epidemiology of Cryptosporidium
in livestock animals and humans in the Ismailia province of Egypt. Vet Parasitol 2013; 193:15-24.
Fayer R, Ungar BLP. Cryptosporidium
and cryptosporidiosis. Microbiol Rev 1986; 50:458-483.
Henriksen SA, Pohlenz JFL. Staining of cryptosporidia by a modified Ziehl-Neelsen technique. Acta Vet Scand 1981; 22:594-596.
Nikaeen M, Mesdaghinia AR, Jeddi Tehrani M, Rezaeian M, Makimura K. A nested-PCR assay for detection of Cryptosporidium parvum
oocysts in water samples. Iran J Public Health 2005; 34:13-18.
Bairami Kuzehkanan A, Rezaeian M, Zeraati H, Mohebali M, Meamar AR, Babaei Z, et al
. A sensitive and specific PCR based method for identification of Cryptosporidium
species using new primers from 18S ribosomal RNA. Iran J Parasitol 2011; 6:1-7.
Spano F, Putignani L, McLauchlin J, Casemore DP, Crisanti A. PCR-RFLP analysis of the Cryptosporidium
oocysts wall protein (COWP) gene discriminates between C. wrairi and C. parvum, and between C. parvum isolates of human and animal origin. FEMS Microbiol Lett 1997; 150:209-217.
Pedraza-Díaz S, Amar C, Nichols GL, McLauchlin J. Nested polymerase chain reaction for amplification of the Cryptosporidium
oocyst wall protein gene. Emerg Infect Dis 2001; 7:49-56.
El-Khodary SA, Osman SA. Cryptosporidiosis in buffalo calves (Bubalus bubalis): prevalence and potential risk factors. Trop Anim Health Prod 2008; 40:419-426.
El Hamshary EM, El Sayed HF, Hussein EM, Rayan HZ. Comparison of polymerase chain reaction, immunochromatographic assay and staining techniques in diagnosis of cryptosporidiosis. PUJ 2008; 1:77-86.
Soliman RH, Othman AA. Evaluation of DNA melting curve analysis real time PCR for detection and differentiation of Cryptosporidium
species. PUJ 2009; 2:47-54.
Rayan HZ, Eida OM, El Hamshry EM, Ahmed SA. Detection of human Cryptosporidium
species in surface water sources in Ismailia using polymerase chain reaction. PUJ 2009; 2:119-126.
Quilez J, Torres E, Chalmers RM, Robinson G, Cacho ED, Sanchez-Acedo C. Cryptosporidium
species and subtype analysis from dairy calves in Spain. Parasitology 2008; 135:1613-1620.
Morgan-Ryan UM, Fall A, Ward LA. Cryptosporidium hominis
n. species (Apicomplexa: Cryptosporidiidae) from Homo sapiens
. J Eukaryot Microbiol 2002; 49:433-440.
Hunter P, Zmirou-Navier D, Hartemann P. Estimating the impact on health of poor reliability of drinking water interventions in developing countries. Sci Total Environ 2009; 407:2621-2624.
Amer S, Honma H, Ikarashi M, et al
genotypes and subtypes in dairy calves in Egypt. Vet Parasitol 2010; 169:382-386.
Ramirez NE, Ward LA, Sreevatsan SA. Review of biology and epidemiology of cryptosporidiosis in humans and animals. Microbiol Infect 2004; 6:773-785.
Fayer R, Santin M, Trout JM, Greiner E. Prevalence of species and genotypes of Cryptosporidium
found in 1-2 years and dairy cattle in the eastern United States. Vet Parasitol 2006; 135:105-112.
Abdel-Messih IA, Wierzba TF, Abu-Elyazeed R, et al
. Diarrhea associated with Cryptosporidium parvum
among young children of the Nile River Delta in Egypt. J Trop Pediatr 2005; 1:154-159.
Al Hussainy NH. Prevalence of Cryptosporidium
spp. infection in Saudi children. PUJ 2013; 6:149-156.
Amar CFL, Dear PH, McLauchlin J. Detection and identification by real time PCR/RFLP analysis of Cryptosporidium
species from human feces. Lett Appl Microbiol 2004, 38:217-222.
Abbaszadegan MR, Velayati A, Tavasoil A, Dadkhah E. Rapid DNA extraction protocol from stool, suitable for molecular genetics diagnosis of colon cancer. Iran Biomed J 2007; 11:203-208.
Molina N, Polverino D, Minvielle M, Basualdo J. PCR amplification of triosephosphate isomerase gene of Giardia lamblia
in formalin-fixed feces. Rev Latinoam Microbiol 2007; 49:6-11.
Babaei Z, Oormazdi H, Akhlaghi L et al.
Molecular characterization of the Iranian isolates of Giardia lamblia
: application of the glutamate dehydrogenase gene. Iran J Public Health 2008; 37:75-82.
Jiang J, Alderisio KA, Xiao L. Distribution of Cryptosporidium
genotypes in storm event water samples from three watersheds in New York. Appl Environ Microbiol 2005; 71:4446-4454.
Araújo RS, Dropa M, Fernandes LN, et al
. Genotypic characterization of Cryptosporidium hominis
from water samples in Sao Paulo, Brazil. Am J Trop Med Hyg 2011; 85:834-838.
Peng MM, Meshnick SR, Cunliffe NA, et al
. Molecular epidemiology of cryptosporidiosis in children in Malawi. J Eukaryot Microbiol 2003; 50(Suppl):557-559.
Gatei W, Greensill J, Ashford RW, et al
. Molecular analysis of the 18SrRNA gene of Cryptosporidium
parasites from patients with or without human immuno-deficiency virus infections living in Kenya, Malawi, Brazil, the United States and Vietnam. J Clin Microbiol 2003; 41:1458-1462.
Tiangtip R, Jongwutiwes S. Molecular analysis of Cryptosporidium
species isolated from HIV-infected patients in Thailand. Trop Med Int Health 2002; 7:357-364.
Yagita K, Izumiyama S, Tachibana H, et al
. Molecular characterization of Cryptosporidium
isolates obtained from human and bovine infections in Japan. Parasitol Res 2001; 87:950-955.
Samie A, Bessong PO, Obi CL, et al
species: preliminary descriptions of the prevalence and genotypic distribution among school children and hospital patients in the Venda region, Limpopo province in South Africa. Exp Parasitol 2006; 114:314-322.
Gatei W, Wamae CN, Mbae C, et al
. Cryptosporidiosis: prevalence, genotype analysis and symptoms associated with infections in children in Kenya. Am J Trop Med Hyg 2006; 75:78-82.
Feng Y, Li N, Xiao L. Cryptosporidium
genotype distribution in raw wastewater in Shanghai, China: evidence for possible unique Cryptosporidium
transmission. J Clin Microbiol 2009; 47:153-157.
McLauchlin J, Amar C, Pedraza-Diaz S, Nichols GL. Molecular epidemiological analysis of Cryptosporidium
spp. in the United Kingdom: results of genotyping Cryptosporidium
spp. in 1705 fecal samples from humans and 105 fecal samples from live stock animals. J Clin Microbiol 2000; 38:3984-3990.
Xiao L, Fayer R. Molecular characterization of species and genotypes of Cryptosporidium
and assessment of zoonotic transmission. Int J Parasitol 2008; 38:1239-1255.
Yoder JS, Beach MJ. Cryptosporidium
surveillance and risk factors in the United States. Exp Parasitol 2010; 124:31-39.
Khalifa AM, Ibrahim IR, Said DE, Abdel Aleem EA, Nabil RA. Cryptosporidium
in water in Alexandria: detection and evaluation of viability by flow cytometry and different stains. PUJ 2011; 4:155-164.
Wellington O, Chika O, Teslim O, Oladipo O, Adetayo F, Godswell I. Cryptosporidium
and other intestinal protozoans in children with diarrhea in Lagos, Nigeria. Int J Trop Med 2008; 5:42-47.
Yoder JS, Harral C, Beach MJ. Cryptosporidiosis surveillance. United States, 2006-2008. MMWR Surveill Summ 2010; 59 (SS06):1-14.
Kirkpatrick BD, Haque R, Duggal P, et al
. Association between Cryptosporidium
infection and human leukocyte antigen class I and class II. J Infect Dis 2008; 197:474 -478.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2]