ABSTRACT
Due to the small number of Cryptosporidium oocysts in water, the number of samples taken and the analyses performed can affect the results of detection. In this study, 42 water samples were collected from one watershed during 20 storm events over 1 year, including duplicate or quadruplicate samples from 16 storm events. Ten samples from four events had three to eight subsamples. They were processed by EPA method 1623, and Cryptosporidium oocysts present were detected by immunofluorescent microscopy or PCR. Altogether, 24 of 39 samples (47 of 67 samples and subsamples) analyzed by microscopy were positive for Cryptosporidium. In contrast, 36 of 42 samples (62 of 76 samples and subsamples) were positive by PCR, including 10 microscopy-negative samples (13 microscopy-negative samples and subsamples). Six of the 24 microscopy-positive samples were negative by PCR, and all samples had one or less oocyst in a 0.5-ml packed pellet volume calculated. Discordant results were obtained by microscopy and PCR from six and three of the storm events, respectively, with multiple samples. Discordant microscopy or PCR results were also obtained among subsamples. Most of the 14 Cryptosporidium genotypes were found over a brief period. Cryptosporidium-positive samples had a mean of 1.9 genotypes per sample, with 39 of the 62 positive samples/subsamples having more than one genotype. Samples/subsamples with more than one genotype had an overall PCR-positive rate of 73%, compared to 34% for those with one genotype. The PCR amplification rate of samples was affected by the volume of DNA used in PCR.
Waterborne cryptosporidiosis presents a serious threat to human health due to the ubiquitous distribution of Cryptosporidium spp. in humans, animals, and water and the resistance of the oocysts to harsh environmental conditions, various disinfectants, and some treatment practices. Many Cryptosporidium species and genotypes have been found in domestic and wild animals, but only five Cryptosporidium spp. are major human pathogens: C. parvum, C. hominis, C. meleagridis, C. canis, and C. felis (25). Because oocysts of all Cryptosporidium spp. have the potential to be present in water and because most of them are morphologically similar, sensitive detection of Cryptosporidium oocysts in water and the correct diagnosis of species and genotypes of Cryptosporidium oocysts are essential for source water management and risk assessment. This becomes more important with the recent implementation of the Long Term 2 Enhanced Surface Water Treatment Rule (LT2ESWTR) in the United States, which requires the regular monitoring of Cryptosporidium oocysts in source water (21). Regulations for the occurrence of Cryptosporidium oocysts in water have also been implemented, and tightened, in the United Kingdom and some other industrialized nations (4, 11).
Currently, the identification of Cryptosporidium oocysts in environmental samples is made largely by use of U.S. Environmental Protection Agency method 1622 (for Cryptosporidium) or 1623 (for both Cryptosporidium and Giardia) and its equivalents in the United Kingdom and other countries (19). This largely involves the concentration of oocysts by filtration, isolation of oocysts by immunomagnetic separation (IMS), staining of recovered oocysts with a fluorescent antibody and 4′,6-diamidino-2-phenylindole dihydrochloride (DAPI), and microscopic detection and enumeration of the stained oocysts (20). The method has been evaluated extensively with water samples seeded with known numbers of oocysts (2, 3, 6, 7, 14, 16, 18, 22). Nevertheless, the method suffers from variations in oocyst recovery rates and an inability to differentiate species (23).
PCR-based methods have been used increasingly in the detection and analysis of Cryptosporidium oocysts in water (26). Compared to method 1622/1623, the new generation of PCR methods (genotyping techniques) has the ability to differentiate Cryptosporidium species that are infective to humans from those that are not infective to humans. Because of the host-adapted nature of most Cryptosporidium species and genotypes (specific Cryptosporidium spp. are likely to be found in a particular group of animals), genotyping techniques are also used in tracking the source of contamination. One tool, a small-subunit (SSU) rRNA gene-based PCR-restriction fragment length polymorphism (RFLP) technique, has been used effectively for genotyping Cryptosporidium oocysts in surface water, storm water, and wastewater samples (9, 17, 24, 26-28).
Little is known about the reproducibility of method 1622/1623 and SSU rRNA-based PCR-RFLP in detecting Cryptosporidium oocysts in field water samples. The low number of oocysts present in water samples can potentially make the test results erratic if only single samples are analyzed. In this study, we evaluated the effect of the number of samples and analytic replicates on the detection of Cryptosporidium oocysts by method 1622/1623 and SSU rRNA-based PCR-RFLP.
MATERIALS AND METHODS
Sample collection.All storm samples for this study were collected between April 2003 and April 2004 from a stream in the N5 basin within the New York City water supply in New York. The N5 basin is located in the Kensico Reservoir watershed in Valhalla, New York. The N5 stream basin is 298 acres in area and consists mostly of residential lots (91%), with some wooded areas (4%). Water samples were collected from the stream with preset autosamplers (ISCO 6700; ISCO, Inc., Lincoln, NE) that were designed to capture significant precipitation events. The method for the collection of storm water samples was described previously (9). In general, autosamplers were set to trigger when a predetermined flow rate was reached. Once the trigger value was reached, discrete 1-liter samples were collected at volume-weighted intervals based on the predicted intensity of the event. Each 1-liter sample was combined into a single 20-liter carboy. After collection, the carboy with approximately 20 liters of the composed sample was put in a cooler on ice and delivered to the Pathogen Laboratory of the New York City Department of Environmental Protection (NYC DEP) for initial processing. To collect multiple samples from the stream, two or more autosamplers with identical settings were installed next to each other.
Number of samples analyzed.In this study, 42 water samples were collected from the N51 stream basin during 20 storm events, including single samples from four events, duplicate samples from 13 events, and quadruplicate samples from three events. Ten samples from four storm events took three to eight filters to process the approximately 20 liters of water collected, generating 44 subsamples (four with three subsamples, four with four subsamples, and two with eight subsamples). Thus, altogether, 76 samples and subsamples were processed by EPA method 1623.
Sample processing.In the NYC DEP laboratory, samples were filtered through an Envirochek HV filter (Pall Gelman Laboratory, Ann Arbor, MI) using procedures described by the U.S. Environmental Protection Agency in method 1623 (20), whereby the 20-liter carboy contents from each storm were captured on the filter. Because of the high turbidity of some samples, several filters were sometimes required to filter each sample. These filters were processed separately, labeled as subsamples A to H, depending on the number of filters used, and examined for Cryptosporidium oocysts individually. Material on the filter was eluted, and the eluate was centrifuged to pellet the oocysts and solids. For samples processed with a single filter, the volume of the pellet varied from 1.5 to 34.0 ml, with a median volume size of 3.0 ml. Once the total pellet size was measured, a portion of the pellet was saved in the NYC DEP laboratory for microscopic detection, whereas the remaining sample concentrate was sealed and transported by express mail to the laboratory at the Centers for Disease Control and Prevention (CDC) for Cryptosporidium oocyst detection and genotyping by PCR. Genotyping for each sample was done without knowledge of microscopy results. Comparison of results from the two detection techniques was done at the end of the project.
Cryptosporidium detection by microscopy.At the NYC DEP laboratory, Cryptosporidium oocysts that presented in 0.5 ml of pellet for each sample and subsample were detected and enumerated according to procedures described in method 1623 (20). A total of 67 samples and subsamples were analyzed for Cryptosporidium oocysts by immunofluorescence microscopy. Cryptosporidium oocysts were initially isolated by IMS using Dynal (Lake Success, NY) magnetic beads coated with an anti-Cryptosporidium monoclonal antibody and detected and counted by epifluorescence and differential interference contrast microscopy after staining with florescence-labeled monoclonal antibodies against Cryptosporidium and Giardia (Merifluor; Meridian Bioscience, Cincinnati, OH). Among the samples or subsamples processed for microscopy detection, 23 had 0.5 ml of packed pellet volume analyzed, 39 had 1.0 to 3.0 ml, four had 5.0 ml, and one had 7.0 ml. The projected number of Cryptosporidium oocysts in the samples was calculated based on the number of filters used and the size of the pellet from each filter using the following formula: number of oocysts in 20 liters of water samples = (number of oocysts detected × total pellet volume × 20)/(volume of pellet analyzed × volume of sample).
Cryptosporidium detection and differentiation by PCR. Cryptosporidium oocysts present in 0.5 ml of the concentrates eluted from filters were analyzed by the PCR-RFLP genotyping technique for all 76 samples and subsamples. Only 0.5 ml of packed pellet volume was analyzed by PCR for each sample or subsample. For DNA extraction, Cryptosporidium oocysts were isolated from 0.5-ml water pellets by IMS as described above. Magnetic beads without dissociation of oocysts were used directly in the DNA extraction with the QIAamp DNA Mini kit (QIAGEN, Valencia, CA), as previously described (9). The extracted DNA was eluted into 100 μl of reagent-grade water and used in the PCR. Each sample was analyzed by an SSU rRNA-based nested PCR (9) using six different volumes of extracted DNA (0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 μl). The number of Cryptosporidium species and genotypes present in each sample or subsample was estimated by restriction fragment analysis of 5 μl of the secondary PCR products with enzyme SspI (New England BioLabs, Beverly, Mass.) or VspI (Promega, Madison, Wis.). This also allowed the tentative identification of Cryptosporidium genotypes. The identifications were confirmed by DNA sequencing of all positive PCR products in both directions using an ABI 3100 autosequencer (Applied Biosystems, Foster City, CA). The nucleotide sequences obtained were aligned with reference sequences from known Cryptosporidium species and genotypes using the Clustal X 1.81 software package (ftp://ftp-igbmc.u-strasbg.fr/pub/ClustalX/ ).
RESULTS
Prevalence of Cryptosporidium oocysts.Altogether, 24 (62%) of 39 samples analyzed by microscopy were positive for Cryptosporidium oocysts. In contrast, 36 (86%) of 42 samples were positive by PCR. Ten samples from four storm events took three to eight filters to process the approximately 20 liters of water collected because of high turbidity, generating 44 subsamples. Combining all samples and subsamples, 47 (70%) of 67 samples and subsamples analyzed by microscopy were positive, compared to 62 (82%) of 76 analyzed by PCR (Table 1). Microscopy-positive samples and subsamples had a range of 1 to 5 oocysts per 0.5 ml of water pellet, but only five samples or subsamples had 2 to 5 oocysts per 0.5 ml of packed pellet volume. The calculated number of oocysts per 20 liters of positive samples ranged from 2 to 163.
Comparison between microscopy and PCR for detecting Cryptosporidium oocysts in storm water concentrates (packed pellets)
Agreement or discordance between microscopy and PCR.Among all microscopy-positive samples and subsamples, only six were negative by PCR, including four with one oocyst in 1.0, 2.0, 2.0, and 2.5 ml of packed pellets; one with three oocysts in 2.0 ml of pellet; and one with six oocysts in 3.0 ml of pellet. Ten of the 15 microscopy-negative samples or 13 of the 20 microscopy-negative samples and subsamples were also positive for Cryptosporidium oocysts by PCR.
Discordant results (negative versus positive) were obtained by microscopy from 6 of the 14 storm events with multiple samples analyzed (Table 1). The calculated density of oocysts based on the number of oocysts detected in the volume of the water pellet, and the total volume of the pellet could be zero oocysts when no oocysts were detected to as high as 163 oocysts per 20 liters when three oocysts were detected in 0.5 ml of packed pellet by microscopy (Table 2). Discordant PCR results for 3 of the 16 storm events with multiple samples analyzed were also obtained (Table 1). Between subsamples of each sample, discordant microscopy results for three of the eight samples analyzed were obtained, compared to 4 of the 10 samples analyzed by PCR (Table 1). Between the group of samples/subsamples with discordant PCR results and the group without discordant PCR results, there was a significant difference (26% versus 56%) in the overall PCR amplification rates (percentage of positive results among all PCR tests conducted for a sample or subsample).
Examples of discrepancies between duplicate or quadruplicate storm water samples from six rain events in the detection of Cryptosporidium oocysts by microscopy
Effect of volumes of DNA suspension on PCR performance.Each sample or subsample was analyzed six times with different volumes of the DNA suspension. The PCR-positive rate was affected by the amount of DNA used in the PCR, with amplification rates of 24%, 41%, 50%, 51%, 57%, and 59% for PCR conducted with 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 μl of DNA suspension, respectively (Fig. 1 and Table 3).
PCR amplification of DNA from samples and subsamples of storm water collected from the same N5 basin site on 27 October 2003. DNA 8509, 8510, 8511, 8512, 8513, 8514, 8515, and 8516 are from samples and subsamples 1120, 1121, 1122A, 1122B, 1122C, 1122D, 1123A, and 1123B, respectively. Lanes 1 to 14 are PCR products using 0.5 μl of DNA suspension, lanes 15 to 28 are PCR products using 1 μl of DNA suspension, lanes 29 to 42 are PCR products using 1.5 μl of DNA suspension, and P is the positive control (Cryptosporidium serpentis DNA). DNA labeled “a” and “b” are from two different DNA extractions using 0.5 ml of packed pellet from the same subsample. Eight, 9, and 11 of the 14 DNA preparations were amplified when 0.5, 1, and 1.5 μl of DNA suspension, respectively, was used in the PCR.
Effect of the volume of DNA suspension used on PCR detection of Cryptosporidium oocysts in storm water samples
Cryptosporidium genotypes.Altogether, 14 Cryptosporidium genotypes were found in these samples, including W1, W3, W4 (cervine genotype), W5, W7 (muskrat genotype I), W8 (opossum genotype II), W10 (C. baileyi), W13 (skunk genotype), W15, W16 (muskrat genotype II), W17, W18, W19, and W21 (Table 4). These Cryptosporidium genotypes were described in detail previously (9). The most common Cryptosporidium genotype was W4, which was found in 41 of the 62 positive samples and subsamples and in 17 of 20 storm events studied. Other common genotypes included W1, W7, W13, and W19, with the rest found at a low frequency. Only W4 was found year-around in water samples (Table 4).
Distribution of Cryptosporidium genotypes in storm water samples over 1 year (April 2003 to April 2004)
Occurrence of mixed Cryptosporidium genotypes.Among the 62 water samples/subsamples that were positive for Cryptosporidium oocysts by PCR, 39 (63%) had more than one Cryptosporidium genotype in each sample/subsample (Fig. 2 and Table 5). The mean number of Cryptosporidium genotypes per positive sample or subsample was 1.9. Because each sample/subsample was analyzed by PCR six times, it was possible to calculate the mean amplification rate for the two groups of samples/subsamples with or without more than one Cryptosporidium genotype. The group of samples/subsamples with more than one Cryptosporidium genotype had an overall PCR amplification rate of 73%, compared to 34% for the group with one genotype (Table 5). Because of the presence of more than one genotype in some samples/subsamples, some PCR products from had mixed Cryptosporidium genotypes as revealed by RFLP analysis. Altogether, 44 of the 181 (24%) PCR-positive products generated had mixed Cryptosporidium genotypes. Between the group of PCR products with mixed Cryptosporidium genotypes and the group without, there was a significant difference (85% versus 43%) in the overall PCR amplification rates (ease of amplification) (Table 5). However, the volume of the DNA suspension used in the PCR did not affect the probability of having mixed genotypes per PCR product (Table 3).
Diversity of Cryptosporidium genotypes in storm water samples as indicated by RFLP analysis (one PCR run of one batch of samples taken on 19 September 2003). DNA 8218, 8219, and 8220 are from three subsamples of one sample; 8221 and 8222 are from two subsamples of a second sample; and 8223 and 8224 are from two subsamples of the third sample (a, b, and c are different DNA extractions of the same subsample). Most PCR products had only one subtype (except for lane 7), even though most samples or subsamples had more than one genotype. Upper panel, SspI digestion products; lower panel, VspI digestion products; P, positive control (C. serpentis).
Correlation between PCR-positive rate and the likelihood of samples/subsamples with more than one Cryptosporidium genotype or PCR products with mixed Cryptosporidium genotypes
DISCUSSION
Results of the study clearly indicate that the number of samples analyzed affected the performance of both microscopy (standard method 1623) and PCR (an SSU rRNA-based genotype technique) in detecting Cryptosporidium oocysts in water. Discrepant results (positive versus negative) were obtained between duplicate or quadruplicate samples from 6 of 14 rain events for microscopy and 3 of 16 events for PCR. Similar results were also obtained between subsamples of samples that took more than one filter to process. Judged by the low number of oocysts present in water and the small amount of packed pellet (0.5 ml) that can be handled by both methods at one time, it is really not surprising to see discrepancies in test results among samples or subsamples taken at the same location at the same time. Even though this was usually seen in water concentrates with few oocysts (with the exception of samples from rain event 15), this minor difference in the number of oocysts detected in 0.5 ml of packed pellet volume could lead to drastic differences in the calculated number of oocysts per sample, as shown in Table 2. Thus, analysis of multiple samples or at least the complete water concentrate from each sample is required to increase the accuracy of Cryptosporidium oocyst detection. Even though this was not specified in the description of method 1623, the newly implemented LT2ESWTR requires the analysis of at least 10 liters of sample or at least 2 ml of packed pellet volume or as much volume as two approved filters can accommodate before clogging (21).
Results of the study also suggest that the SSU rRNA PCR-based method is more sensitive than the microscopy method described in method 1623. The SSU rRNA PCR-based method detected Cryptosporidium oocysts in 86% of samples or 82% of all samples and subsamples analyzed, whereas the latter detected oocysts in only 62% of the samples or 70% of all samples and subsamples, despite the fact that many samples and subsamples had more than 0.5 ml of packed pellet volume analyzed by microscopy. Previously, other studies have also shown that PCR-based methods have higher sensitivities than microscopy-based methods such as method 1622/1623 for detecting Cryptosporidium oocysts in water (5, 9, 10, 12, 13, 24). In the present study, the higher detection rate by PCR occurred largely in samples where microscopy failed to detect any oocysts. The reasons for the lower sensitivity by microscopy are not yet clear. Because samples were processed in the same way until the IMS step, it is likely the difference seen between the two methods was due to oocyst losses occurring after the IMS step. For microscopy, IMS-isolated oocysts have to be detached from the magnetic beads before being transferred to the slide for immunofluorescence and DAPI staining. Because of the extra detachment process and washing steps involved in the microscopic examination of water samples during staining, more oocyst losses can occur. It has recently been shown that poor dissociation of oocysts from magnetic beads is a major factor contributing to poor oocyst recovery using method 1622/1623 (22).
Because only a small volume of DNA extracted can be analyzed by PCR, each sample or subsample was analyzed by PCR six times to increase the chance of detecting a single oocyst in a water concentrate. This was based on the five-copy nature of the targeted SSU rRNA gene per sporozoite, four sporozoites per oocyst, and the 100-μl total volume of DNA extracted. Since DNA extracted from IMS-purified oocysts is known to contain residual PCR inhibitors (8), different volumes (0.5 to 3 μl) of the DNA suspension were used in the PCR to counter potential PCR inhibition. This strategy led to high rates of detection of Cryptosporidium for samples and good agreement of genotyping results between duplicate or quadruplicate samples. The use of multiple PCR replicates in the analysis of water samples has been a common practice (8, 9, 17, 24, 27, 28). Results of the study have further shown that higher amplification rates could be achieved by using 3 μl of DNA in PCR without encountering significant PCR inhibition (Table 3). This was probably due to the use of a high concentration (400 ng/μl) of nonacetylated bovine serum albumin to neutralize residual PCR inhibitors (8). Thus, the performance of PCR can be improved and the number of PCR replicates can be potentially reduced if all PCR replicates use 3 μl of DNA instead of 0.5 to 3 μl of DNA.
The use of multiple PCR replicates per sample also increased the chance of detecting mixed Cryptosporidium genotypes in water. In agreement with previous studies conducted in the NYC DEP watershed, storm water samples frequently contain multiple Cryptosporidium genotypes from wild animals (9, 24). In this study, an average of 1.9 genotypes per Cryptosporidium-positive sample was detected. As expected, the chance of detecting more than one genotype increased with increased amplification rates (ease of amplification) of sample DNA as determined by PCR (Table 5). This strategy has also been used for the detection of mixed Cryptosporidium genotypes in surface water and wastewater (17, 27, 28).
There were apparent temporal variations in the distribution of the 14 Cryptosporidium genotypes found in the watershed studied. Only one Cryptosporidium genotype, the cervine genotype (W4), was found year-around. It is mainly a parasite of deer and sheep but has also recently been found in a few cases in humans, nonhuman primates, squirrels, and a mouse, indicating that there may be other reservoirs for this parasite (1, 15, 25). Deer, squirrels, and mice are known to be active year-around in the watershed studied. In contrast, all other Cryptosporidium genotypes occurred only during a short period between late May and early November (Table 4). During the rest of the year, W4 was the dominant genotype found. Nevertheless, there was very good agreement in the occurrence of a particular Cryptosporidium genotype in duplicate or quadruplicate samples or subsamples when multiple PCR products were available for genotyping. Frequently, a rare Cryptosporidium genotype occurred with high frequency in multiple samples taken within a week (Table 4).
In summary, the numbers of both samples and analytic replicates affect the detection of Cryptosporidium oocysts in water by both method 1623 and PCR. Presently, because of the high cost associated with the detection of Cryptosporidium oocysts in water, analysis of multiple samples has not been recommended. As shown in this study, substantial differences in the calculated numbers of oocysts per sample can be generated between duplicate or quadruplicate samples or when a sample requires multiple filters to process and/or when the packed pellet volume is large. This greatly reduces test accuracy and can be especially problematic in the era of LT2ESWTR, where the stringency of treatment practices implemented by water treatment plants depends on the number of Cryptosporidium oocysts found in source water (21). Thus, the analysis of multiple samples or at least the complete packed pellet volume from each sample is required to increase the accuracy of Cryptosporidium oocyst detection.
ACKNOWLEDGMENTS
This study was supported in part by funds from the Awwa Research Foundation.
We acknowledge the work of the NYC DEP Pathogen Laboratory staff for microscopy results and the Pathogen Field Group for sample collection during storm events.
The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
FOOTNOTES
- Received 19 April 2006.
- Accepted 5 June 2006.
- Copyright © 2006 American Society for Microbiology
