Research Article
5 September 2008

Cryptosporidium Source Tracking in the Potomac River Watershed


To better characterize Cryptosporidium in the Potomac River watershed, a PCR-based genotyping tool was used to analyze 64 base flow and 28 storm flow samples from five sites in the watershed. These sites included two water treatment plant intakes, as well as three upstream sites, each associated with a different type of land use. The uses, including urban wastewater, agricultural (cattle) wastewater, and wildlife, posed different risks in terms of the potential contribution of Cryptosporidium oocysts to the source water. Cryptosporidium was detected in 27 base flow water samples and 23 storm flow water samples. The most frequently detected species was C. andersoni (detected in 41 samples), while 14 other species or genotypes, almost all wildlife associated, were occasionally detected. The two common human-pathogenic species, C. hominis and C. parvum, were not detected. Although C. andersoni was common at all four sites influenced by agriculture, it was largely absent at the urban wastewater site. There were very few positive samples as determined by Environmental Protection Agency method 1623 at any site; only 8 of 90 samples analyzed (9%) were positive for Cryptosporidium as determined by microscopy. The genotyping results suggest that many of the Cryptosporidium oocysts in the water treatment plant source waters were from old calves and adult cattle and might not pose a significant risk to human health.
Waterborne cryptosporidiosis remains one of the prominent public health concerns in industrialized nations (39). Many Cryptosporidium species and genotypes have been found in domestic and wild animals, and all of them can potentially occur in water. However, only two Cryptosporidium spp. are major human pathogens, C. parvum and C. hominis (59, 61). Because oocysts of all Cryptosporidium spp. are morphologically similar and have the potential to be present in water, sensitive and specific detection and typing of Cryptosporidium oocysts in water to determine both the species and the genotype are essential for source water management and risk assessment. This has become more important because of the recent implementation of the Long Term 2 Enhanced Surface Water Treatment Rule in the United States, which requires monitoring of Cryptosporidium oocysts in source water to determine the level of treatment needed at a water treatment plant (WTP) (52). Regulations for Cryptosporidium oocysts in water have also been implemented and tightened in the United Kingdom and some other industrialized nations (8, 26).
Currently, identification of Cryptosporidium oocysts in environmental samples is largely performed by using U.S. Environmental Protection Agency (USEPA) method 1622 (for Cryptosporidium) or method 1623 (for both Cryptosporidium and Giardia) and their equivalents in the United Kingdom and other countries (55). This involves concentration of oocysts by filtration, isolation of oocysts by immunomagnetic separation, 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 (51).
PCR-based methods have been used increasingly for detection and analysis of Cryptosporidium oocysts in water (60), and unlike methods 1622 and 1623, the more recent PCR methods (e.g., genotyping techniques) can differentiate Cryptosporidium species that infect humans from species that do not infect humans. Because most Cryptosporidium species and genotypes are host specific, genotyping techniques are also used for tracking sources 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 (1, 18, 20, 40, 41, 56, 60, 62, 63).
The Potomac River is a water supply that is critical to many communities in the Mid-Atlantic region of the United States. The population of the Potomac River basin is approximately 5.35 million (2000 census) and is growing rapidly. The Washington, DC, metropolitan area has approximately 3.7 million residents or almost three-quarters of the basin's population, and the nontidal Potomac River is the main water supply for these people. One of the common contaminants of concern that has been identified in all of the source water assessments for the various Potomac River WTPs is Cryptosporidium. Currently, only limited data whose quality varies are available for the occurrence of Cryptosporidium oocysts in the Potomac River watershed, and there are no specific data indicating the likely source of contamination and the public health significance of oocysts found in the water.
To obtain critical information to better inform source water protection efforts targeting Cryptosporidium, the Potomac River Basin Drinking Water Source Protection Partnership, in cooperation with the USEPA and the Centers for Disease Control and Prevention, began a 15-month monitoring research project in the Potomac River watershed in October 2006 to identify the major sources of Cryptosporidium oocysts found in local drinking water source waters. This project included monthly and storm event sampling at five sites with different land uses associated with different species of Cryptosporidium. The project took advantage of the recent developments in Cryptosporidium genotyping to track the sources of Cryptosporidium oocyst contamination in the Potomac River watershed.


Sampling sites.

Surface water samples were collected at five sites in the Potomac River basin, including two WTP intakes and three watershed sites (Fig. 1). The two WTP intake sites were sites at Fairfax Water's Corbalis WTP in Herndon, VA, and Washington Suburban Sanitary Commission's Potomac Water Filtration Plant (WFP) in Potomac, MD. These two plants were selected to determine the characteristics of the source waters on the south (Virginia) and north (Maryland) sides of the Potomac River. The two intakes are located about 6 miles apart from one another on opposite sides of the main stem of the Potomac River and represent the primary supply sources for two of the three major water utilities in the Washington, DC, metropolitan region. The source water at the Potomac WFP is considered comparable to the source water for the third major water utility (the Washington Aqueduct), whose intake is also on the north side of the Potomac River.
FIG. 1.
FIG. 1. Geographic locations of the five sites sampled in the Potomac River basin.
The three watershed sampling sites were selected so that they represented different land uses in the watershed drainage area and different contributions of potential agricultural (cattle) and urban (wastewater treatment) sources to the overall Cryptosporidium load (Table 1). The North Fork Shenandoah River site is located just northeast of Edinburg, VA, in Shenandoah County. It is downstream of significant dairy and beef feedlot operations, and there are no major wastewater treatment plant (WWTP) (>1 million gallons per day) discharges upstream. The Monocacy River site is just north of Frederick, MD, in Frederick County and is downstream of significant dairy cattle operations and several major WWTP discharges. It is estimated that 25 to 30% of the stream flow under low-flow conditions is WWTP discharge.
TABLE 1. Land uses in the Potomac River basin upstream of the five sampling sites
Land use and contamination sourceAcres (%)a
Monocacy RiverNorth Fork Shenandoah RiverGreat Seneca CreekCorbalis WTP and Potomac WFPb
Total area447,397415,7916,2187,286,006
Residential9,359 (2.1)8,238 (2.0)1,521 (24.5)141,047 (1.9)
Commercial/industrial103 (0)434 (0.1)243 (3.9)111,123 (1.5)
Agricultural pasture/hay194,291 (43.4)126,423 (30.4)176 (2.8)1,742,238 (23.9)
Agricultural crop93,192 (20.8)11,522 (2.8)1,127 (18.1)773,018 (10.6)
Park/grass15,718 (3.5)17,911 (4.3)118 (1.9)4,363 (0.1)
Forest/woods119,012 (26.6)250,022 (60.1)2,911 (46.8)4,391,526 (60.3)
Water/wetland11,049 (2.5)1,041 (0.3)11 (0.2)88,055 (1.2)
Other4,673 (1.0)200 (0.1)1 (0)34,617 (0.5)
Determined by geographic information system mapping. The potential sources of contamination are as follows: for the Monocacy River, Corbalis WTP, and Potomac WFP, agricultural and wastewater discharge; for the North Fork Shenandoah River, agricultural; and for the Great Seneca Creek, wastewater discharge.
The data are data for the Potomac WFP site, but the data for the Corbalis WTP site would be similar, as the latter is only 6 miles upstream on the Potomac River, into which the Monocacy River, North Fork Shenandoah River, and Great Seneca Creek watersheds all drain. The Corbalis WTP site, however, is not believed to be influenced by the Great Seneca Creek discharge.
The third watershed site represents an area largely influenced by urban sources and is on the Great Seneca Creek in Maryland, about 200 feet downstream of the discharge point of the Seneca WWTP. This site is located in Seneca State Park, and its coverage includes significant wooded areas (Table 1). It was targeted in order to assess the human contributions of Cryptosporidium due to WWTP discharges (specifically from the Seneca WWTP, which is a tertiary WWTP with UV disinfection). The WWTP discharge comprises a significant portion of the stream flow at this location during dry-weather flows (as much as 50%). Great Seneca Creek is not believed to influence the quality of the Corbalis WTP source water because the intake for this WTP is slightly upstream of the Great Seneca Creek outlet and the river is too wide at this point for the Great Seneca Creek flow to reach the Corbalis WTP intake, but it does influence the quality of the source water of the Potomac WFP because it is upstream of and on the same side of the river as the WFP intake.

Sample collection and processing.

Storm flow and base flow samples were collected from the two WTP sites and three watershed sites. During the study period, one monthly 20-liter base flow grab sample was collected at each site, and 6- to 8-h composite storm flow samples were collected at the five affected sites after significant rain events in the upstream watersheds at times estimated to correspond to the first-flush storm flow from upstream sources. Each water sample was split into two 10-liter aliquots, and each aliquot was filtered through Envirochek HV filters by using procedures specified in USEPA method 1623 (51). The filters for one aliquot were processed by certified commercial laboratories contracted by the Potomac River Basin Drinking Water Source Protection Partnership members for detection and enumeration of Cryptosporidium oocysts and Giardia cysts using USEPA method 1623. The filters for the other aliquot were shipped to a laboratory at the Centers for Disease Control and Prevention for Cryptosporidium detection and genotyping by a PCR technique. PCR analyses of the samples were conducted by a technician who was unaware of the sample codes and microscopy results. Microscopy and PCR results were compared only after analyses of all samples were complete.
For water quality analyses, Escherichia coli was enumerated for base flow samples from the Monocacy River, Great Seneca Creek, and Potomac WFP sites using Quanti-Tray/2000 (Idexx, Westbrook, ME) as specified by SM 9223B, and turbidity was determined for all samples using USEPA method 180.1-approved bench turbidimeters (a 2100N or 2000P turbidimeter from Hach Co., Loveland, CO, for base flow and storm flow samples from most sites, or a Hydrolab DS5 multiprobe from Hach Co. for storm flow samples from the North Fork Shenandoah site).

DNA extraction.

Cryptosporidium oocysts were isolated from 0.5-ml water concentrates by immunomagnetic separation using magnetic beads coated with an anti-Cryptosporidium monoclonal antibody (Dynal, Lake Success, NY) and the procedure recommended by the manufacturer. Oocysts still bound to magnetic beads were directly used for DNA extraction with a QIAamp DNA mini kit (Qiagen, Valencia, CA). To break the oocyst wall, 180 μl ATL buffer from the kit was added into 1.5-ml tubes containing the oocysts and beads and the preparations were subjected to five freeze-thaw cycles at −70 and 56°C for at least 1 h (17).


Each sample was analyzed by performing an SSU rRNA-based nested PCR-RFLP analysis using restriction enzymes SspI and VspI as described by Xiao et al. (18, 56, 58). Each water sample was analyzed five times (i.e., five replicates) by the PCR-RFLP technique, using 2 μl of the DNA solution per PCR mixture. Nonacetylated bovine serum albumin (400 ng/μl; Sigma-Aldrich, St. Louis, MO) was used in all primary PCRs to neutralize residual PCR inhibitors in the extracted DNA. Ten microliters of the secondary PCR products was digested at 37°C overnight in a 40-μl (total volume) reaction mixture. The digested products were visualized by 2% agarose gel electrophoresis.

Sequencing analysis.

All positive secondary PCR products generated in this study were sequenced in both directions using an ABI Prism 3130 genetic analyzer (Applied Biosystems) as described previously (18, 56, 58). Nucleotide sequences were read using the software ChromasPro ( ). The consensus sequences obtained and sequences from the GenBank database were aligned using ClustalX ( ). Sequence alignments were edited using the BioEdit program, version 7.0.4 ( ).

Statistical analysis.

Cryptosporidium detection rates for sampling sites were compared by using chi-square analysis or Fisher's exact test. Differences in contamination intensity, as reflected by differences in sample PCR amplification rates between sites or genotypes, were compared by using a t test. The association between Cryptosporidium PCR positivity and log turbidity or log E. coli counts was assessed by logistic regression. In chi-square, Fisher's exact test, and logistic regression analyses, odds ratios (OR) were also calculated. All statistical analyses were performed with EpiInfo 3.3.2 (Centers for Disease Control and Prevention, Atlanta, GA).

Nucleotide sequence accession numbers.

Unique sequences generated in this study have been deposited in the GenBank database under accession numbers EU825733 to EU825751 .


Water samples.

A total of 64 base flow samples and 28 storm flow samples were collected at the five study sites during the period from October 2006 to February 2008. Base flow samples (one sample per month per site) were collected from October 2006 to October 2007. Storm flow samples were collected in March, April, and August to December 2007 and in February 2008, and four to seven samples per site were obtained.

Numbers of Cryptosporidium-positive samples as determined by microscopy and PCR.

Microscopy was performed for 90 samples, and Cryptosporidium oocysts were detected in only 8 samples, including one base flow sample each from the Potomac WFP and Great Seneca Creek sites, two base flow samples from the Corbalis WTP site, one storm flow sample from the Corbalis WTP site, and three storm flow samples from the North Fork Shenandoah River site. Seven of the Cryptosporidium-positive samples contained one oocyst per 10-liter aliquot, and one sample contained two oocysts per 10-liter aliquot. Microscopy revealed Giardia cysts in 12 samples, and 1, 2, 4, and 5 samples from the Potomac WFP, Great Seneca Creek, North Fork Shenandoah River, and Corbalis WTP sites, respectively, were positive. Most of the Giardia-positive samples were collected at base flow; the exceptions were two samples from the North Fork Shenandoah River site and one sample from the Corbalis WTP site. The number of Giardia cysts varied from 1 to 50 per 10-liter aliquot for positive samples.
Much greater occurrence of Cryptosporidium oocysts in water samples was detected by PCR. Altogether, 50 of the 92 water samples generated the expected SSU rRNA PCR products, including 27/64 (42%) of the base flow samples and 23/28 (82%) of the storm flow samples (Table 2). Six of the eight microscopy-positive samples were also positive as determined by PCR; the two PCR-negative samples which were microscopy positive included one sample each from the Potomac WFP and Great Seneca Creek sites, both of which were base flow samples. For two watershed sites that were influenced by cattle farms, the Monocacy River and North Fork Shenandoah River sites, the PCR posivitity was higher for base flow samples (7/13 [54%] of samples). In contrast, for the two source water intake sites (Corbalis WTP and Potomac WFP) and the watershed site influenced by treated urban wastewater the occurrence of Cryptosporidium oocysts was lower in base flow samples (3/12 to 5/13 [25 to 38%] of the samples) (OR, 2.2; P = 0.06).
TABLE 2. Occurrence of Cryptosporidium PCR-positive samples by site
SiteLog turbidity (mean ± SD)Log E. coli count (mean ± SD)aCryptosporidium PCR positiveC. andersoni PCR positiveWildlife genotype PCR positive
RateIntensity (mean ± SD)bRateIntensity (mean ± SD)bRateIntensity (mean ± SD)b
Base flow        
    Corbalis WTP0.86 ± 0.30NDc5/133.80 ± 1.305/133.00 ± 1.412/130.80 ± 1.30
    Potomac WFP0.76 ± 0.521.42 ± 0.925/133.40 ± 1.825/133.00 ± 2.002/130.40 ± 0.55
    Monocacy River0.54 ± 0.491.92 ± 0.707/134.43 ± 1.137/134.29 ± 1.111/130.44 ± 0.38
    North Fork Shenandoah River0.33 ± 0.25ND7/133.71 ± 1.386/133.14 ± 1.952/130.57 ± 1.13
    Great Seneca Creek0.60 ± 0.391.86 ± 0.463/122.00 ± 1.000/1203/122.00 ± 1.00
Storm flow        
    Corbalis WTP1.28 ± 0.75ND4/65.00 ± 0.004/65.00 ± 0.000/60
    Potomac WFP1.59 ± 0.73ND5/73.80 ± 1.104/72.80 ± 2.282/71.10 ± 1.41
    Monocacy River1.21 ± 0.48ND6/65.00 ± 0.006/65.00 ± 0.000/60
    North Fork Shenandoah River1.05 ± 0.07ND3/44.67 ± 0.583/44.33 ± 1.151/40.33 ± 0.58
    Great Seneca Creek1.71 ± 0.46ND5/52.00 ± 0.711/50.20 ± 0.454/51.80 ± 1.10
Number of colonies per 100 ml of sample.
Number of PCR-positive replicates/5 PCR replicates for all positive samples.
ND, not done.
As determined by PCR, the occurrence of Cryptosporidium was higher at the five sites for storm flow than for base flow (OR, 6.3; P < 0.001), and there was no significant difference in the detection rates (67 to 100%) among the sites (P = 0.637) (Table 2).

Turbidity, E. coli counts, and Cryptosporidium positivity as determined by PCR.

Samples collected during storm flow had significantly higher turbidity than samples collected during base flow (P < 0.001), and samples collected during base flow at the North Fork Shenandoah site had much lower turbidity than samples collected at the Corbalis WTP and Potomac WFP (P = 0.002). At base flow, Cryptosporidium PCR-positive samples had higher turbidity than negative samples (OR, 3.69; P = 0.05; Table 3). Likewise, Cryptosporidium PCR-positive samples also had higher mean E. coli counts than negative samples collected during base flow (OR, 3.40; P = 0.04) (Table 3).
TABLE 3. Effect of turbidity and E. coli counts on Cryptosporidium PCR positivity of water samples
GroupnLog turbidityLog E. coli count
Mean ± SDPMean ± SDaP
Base flow     
    Positive270.73 ± 0.510.052.05 ± 0.910.04
    Negative370.52 ± 0.33 1.50 ± 0.53 
Storm flow     
    Positive231.56 ± 0.52NCbNDcND
    Negative50.58 ± 0.35 ND 
Number of colonies per 100 ml of sample.
NC, a value could not be calculated due to the small sample size of the negative group.
ND, not done.

Monthly occurrence of Cryptosporidium in water samples as determined by PCR.

Base flow samples were taken at all five study sites once every month during a 13-month period (October 2006 to October 2007). Twenty of the 27 samples positive for Cryptosporidium as determined by PCR (74%) were obtained during the period from November 2006 to March 2007 (OR, 16.5; P < 0.001), a period with initially higher-than-normal precipitation (October and November 2006) and then normal precipitation. Only five (19%) of the positive samples were obtained during the 6-month period from May to October 2007, a period during which a major drought occurred in the study area, as judged by the precipitation deficit (Table 4).
TABLE 4. Occurrence of Cryptosporidium PCR-positive samples by month
SiteCryptosporidium detection
October (122)aNovember (135)December (44)January (54)February (65)March (74)April (86)May (9)June (74)July (45)August (42)September (36)October (89)November (38)December (75)February (68)
    Corbalis WTP+++++NSNSNS
    Potomac WFP+++++NSNSNS
    Monocacy River+++++++NSNSNS
    North Fork Shenandoah River+++++++NSNSNS
    Great Seneca Creek+NS++NSNSNS
Storm flow                
    Monocacy RiverNSNSNSNSNS++NSNSNS+NS+++NS
    North Fork Shenandoah RiverNSNSNSNSNS+NSNSNSNSNSNSNS++
The numbers in parentheses indicate the monthly total precipitation (in mm) at the nearby Washington Dulles International Airport according to the National Weather Service.
NS, not sampled.
Two storm flow samples were obtained in March and December 2007 for the Potomac WFP site.
Storm flow water samples were taken after seven precipitation events only in the later part of the study period. Most storm flow samples, including those collected during the drought, were positive for Cryptosporidium (Table 4).

Cryptosporidium genotype distribution in the watershed.

Altogether, 15 Cryptosporidium species or genotypes were found in the 50 Cryptosporidium-positive samples as determined by RFLP analysis and DNA sequencing of the SSU rRNA PCR products; these species or genotypes included C. andersoni, C. felis, C. meleagridis, C. serpentis, deer mouse genotypes III (W1) and IV (W3), the cervine genotype (W4), muskrat genotype I (W7), the snake genotype (W11), the skunk genotype (W13), the vole genotype (W15), the tortoise genotype, genotype W12, a C. bovis-like genotype, and a mouse genotype II-like Cryptosporidium. The most common species or genotype in water samples was C. andersoni, which was found in 41 PCR-positive samples or 167 PCR products (Table 5). In contrast, other genotypes were found in only one to four samples. Because almost all of the latter genotypes are parasites of wildlife, they are referred to as wildlife genotypes in this report for convenience. Of the 50 PCR-positive samples, 12 (24%) contained more than one genotype; these samples included 9 samples containing two genotypes and 3 samples containing three genotypes.
TABLE 5. Cryptosporidium genotypes found in water samples in the Potomac watershed
Species or genotypeMajor known host(s)Minor known host(s)No. of samples positiveNo. of detectionsaDetection site(s)
C. andersoniCattleSheep, humans (?)41167 (151 type A, 14 type B, and 2 type C sequences)All except Great Seneca Creekb
C. felisCatsCattle, humans23Great Seneca Creek
C. meleagridisBirdsHumans, dogs, deer mice, brown rats11Great Seneca Creek
C. serpentisSnakes, lizards 11Potomac WFP
Deer mouse genotype III (W1)Deer miceSquirrels35Great Seneca Creek, Potomac WFP, Corbalis WTP
Deer mouse genotype IV (W3)Deer mice 11Great Seneca Creek
Cervine genotype (W4)Sheep, zoo and wild ruminants, squirrels, chipmunks, woodchucksDeer mice, beavers, raccoons, lemurs, humans35Great Seneca Creek
Muskrat genotype I (W7)Muskrats, voles 34Corbalis WTP, North Fork Shenandoah River, Monocacy River
Snake genotype (W11)Snakes 11Potomac WFP
W12  11Great Seneca Creek
Skunk genotype (W13)SkunksRaccoons, otters, opossums, squirrels, humans45Great Seneca Creek, Potomac WFP, Corbalis WTP
Vole genotype (W15)Voles 11North Fork Shenandoah River
Tortoise genotypeTortoises 11Great Seneca Creek
C. bovis-like genotype  11Potomac WFP
Mouse genotype II-likeMice 13North Fork Shenandoah River
Total number of positive samples for five PCR replicates of all samples.
Detected in one PCR replicate of one storm flow water sample from the Great Seneca Creek.
There were apparent differences in the distribution of Cryptosporidium genotypes among the five sampling sites. C. andersoni was the dominant genotype found in base flow and storm flow water samples from the Corbalis WTP, Potomac WFP, Monocacy River, and North Fork Shenandoah River sites. However, it was never detected in base flow samples from the Great Seneca Creek and was detected in only one of five PCR replicates of one storm flow sample from this site (Tables 2 and 5). In contrast, wildlife genotypes were detected mostly in samples from Great Seneca Creek (15 times in seven samples) and Potomac WFP (seven times in four samples) and only occasionally in samples from the Corbalis WTP (four times in two samples), North Fork Shenandoah River (five times in three samples), and Monocacy River (once in one sample) (OR of 26.4 and P < 0.001 for comparisons of Great Seneca Creek and other sites).

Cryptosporidium intragenotypic heterogeneity.

For most of the genotypes, the SSU rRNA sequences obtained were identical to each other and to those deposited in the GenBank database; the exceptions were the single sequences for C. meleagridis, C. serpentis, and the vole genotype (W15), which had minor differences (2 to 3 nucleotides) compared with reference sequences. The C. bovis-like genotype sequence had five nucleotide differences compared with the C. bovis sequence from cattle (accession number AY120911 ), five or seven nucleotide differences compared with the C. bovis sequence from sheep (accession numbers EF362478 and DQ991389 ), and six nucleotide differences compared with the C. bovis sequence from a goat (accession number EF613338 ). The mouse genotype II-like Cryptosporidium sequence had seven nucleotide differences compared with the mouse genotype II sequence (accession number EF546483 ), all in the form of insertions and deletions. These sequences may represent new Cryptosporidium genotypes or subtypes.
Three types of intragenotypic sequences were identified in C. andersoni. Most of the C. andersoni sequences obtained (151/167) were identical to the type A sequence (accession number AF093296 ), which differed from the type B sequence (accession number AB362934 ) by having one T deletion (three Ts instead of four Ts) (32). This deletion was found in 14 PCR products. A third type of sequence, type C, of C. andersoni was found in PCR products from one sample, and compared with the type A sequence it had one A deletion right before the three-T region and one C-to-AT substitution shortly after this region. The 14 C. andersoni type B sequences were obtained from 10 water samples; 10 of the type B sequences were detected in samples that also produced type A sequences. Only two sequences each were obtained from two samples that had no type A sequence. Likewise, the two type C sequences were also found in a sample that produced one type A sequence.
Intragenotypic sequence variations were also found in the muskrat and cervine genotypes. In the four muskrat genotype I sequences obtained, two sequences from two samples had one A-to-G nucleotide substitution and a four-T deletion (four Ts instead of eight Ts). Likewise, for the five cervine genotype sequences obtained from three samples, one had a TA deletion (one TA instead of two TAs) compared to the other four. The two types of cervine genotype sequences were found in one sample from the Great Seneca Creek; two PCR replicates produced the common sequence with two TAs, and one PCR replicate produced the sequence with one TA. These intragenotypic variations in C. andersoni, muskrat genotype I, and the cervine genotype likely represent sequence differences between different copies of the SSU rRNA gene.

Differences in contamination levels between C. andersoni and wildlife genotypes.

Because each sample was analyzed by PCR five times, it was possible to assess the Cryptosporidium contamination intensity in water at both the sample and genotype levels by determining the rates of PCR amplification (number of PCR-positive replicates per sample or genotype). Overall, the positive water samples generated 3.84 ± 1.39 PCR products (mean ± standard deviation) for five PCR replicates. There were no significant differences in contamination intensity among most of the sampling sites for both the base flow and the storm flow; the exception was the findings for the Great Seneca Creek site, at which the intensity was much lower than that at the other sites. As expected, the contamination intensity was higher in storm flow samples than in base flow samples at all sites except the Great Seneca Creek site (Table 2).
At the genotype level, the intensity of contamination by C. andersoni was much higher than the intensity of contamination by the wildlife genotypes. For all 50 Cryptosporidium-positive water samples, C. andersoni had an overall contamination intensity of 3.20 ± 2.02 replicates per 5 PCR replicates, and the wildlife genotypes had an overall contamination intensity of 0.64 ± 1.03 replicates per 5 PCR replicates (P < 0.001). For both the base flow and the storm flow, the Great Seneca Creek site had much higher overall wildlife genotype contamination intensity than the other four study sites (Table 2). For the 41 samples positive for C. andersoni, the contamination intensity for this genotype was 3.90 ± 1.48 replicates per 5 PCR replicates. In contrast, for the 17 samples positive for wildlife genotypes, the contamination intensity for these genotypes was 1.88 ± 0.86 replicates per 5 PCR replicates (P < 0.001).


In this study the prevalence of Cryptosporidium in water samples was high as determined by SSU rRNA-based PCR. Despite the occurrence of a major drought during the study period, 42% of the base flow samples were positive for Cryptosporidium. The high prevalence of Cryptosporidium oocysts in river water samples was expected, as three of the sampling sites were immediately downstream of potential agricultural or urban wastewater discharge sites. Nevertheless, the prevalence of Cryptosporidium oocysts in base flow samples is similar to data in recent reports for the occurrence of Cryptosporidium detected by PCR in river water samples in Japan (69%) and Portugal (>33%) (1, 29). Similar high prevalence values (56 to 100%) for Cryptosporidium oocysts in river water were also obtained by using microscopy in some recent studies conducted in the United States, Canada, Spain, The Netherlands, Brazil, Taiwan, and Japan (2, 7, 12, 15, 20, 35, 41, 46, 50). In this study, as expected, a much higher prevalence of Cryptosporidium oocysts was detected by PCR in water samples collected at the five sampling sites during storm flow (82%) than during base flow (42%). Likewise, the prevalence of Cryptosporidium in storm flow water was similar (88%) to findings of a multiyear study of three streams draining wooded or forested, residential, and commercial areas in the New York City drinking water supply system (18).
A much lower prevalence of Cryptosporidium oocysts in the water samples analyzed in this study was obtained when standard USEPA method 1623 was used (oocysts were present in only 6% of the base flow samples and 14% of the storm flow samples). Previous studies have shown that PCR methods have greater sensitivity than microscopy for detection of Cryptosporidium oocysts in water samples (10, 18, 19, 21, 27, 28, 56) A more recent study also suggested that the difference between the microscopy results and the SSU rRNA-based PCR results was largely due to detection of Cryptosporidium by PCR in microscopy-negative samples (58). It was suggested that the poor dissociation of oocysts from magnetic beads during the immunomagnetic separation step and more downstream processing steps likely contributed to the inferior performance of microscopy (54, 58). Because the difference between the detection rates with microscopy and the detection rates with PCR in this study was so great, it was unlikely that the difference in sensitivity was solely responsible.
Apparent variation was detected in the monthly occurrence of Cryptosporidium PCR-positive samples collected during base flow. Two-thirds of the positive samples were collected during a 5-month study period from November 2006 to March 2007, and less than one-fifth of the positive samples were collected from May to October 2007, a period accounting for nearly one-half of the sampling time and during which a major drought occurred in the study area. The hypothesis that precipitation had an effect on the occurrence of Cryptosporidium oocysts was supported by the significantly higher percentage and intensity of PCR-positive samples for samples collected under storm flow conditions. Previously, the number of Cryptosporidium oocysts in river water samples was shown to increase from the late summer to the early autumn (from August to November) in studies performed in the United States and Japan (20, 49). Similarly, in Spain river water samples were positive for Cryptosporidium significantly more frequently during the autumn than during the spring and winter (2). In contrast, no monthly variation in the occurrence of Cryptosporidium oocysts was detected in river water samples in other studies in Norway and Spain (30, 38).
The turbidities and E. coli counts of the samples correlated with detection of Cryptosporidium oocysts. In this study, Cryptosporidium-positive river water samples had higher turbidities and E. coli counts than negative samples. Similar observations concerning the relationship between the occurrence of Cryptosporidium oocysts on the one hand and the turbidity and E. coli or fecal coliform counts on the other hand have been made previously (2, 23, 38, 48). In one study performed in Finland, the presence of E. coli was correlated with the detection of Cryptosporidium in river water samples, although there were no significant correlations between E. coli or coliform counts and the presence of Cryptosporidium (14).
There were apparent differences in the occurrence of Cryptosporidium oocysts among the three watershed sites. At base flow, each of the two sites influenced by cattle farms, the North Fork Shenandoah River and Monocacy River, had a much higher occurrence of Cryptosporidium oocysts based on the PCR positivity and intensity (defined as the number of PCR-positive replicates for the five PCR replicates per sample) than the site influenced by urban wastewater discharge, the Great Seneca Creek. At storm flow, the Great Seneca Creek site also had lower contamination intensity than the other two sites (2.00 ± 0.71, 4.67 ± 0.58, and 5.00 ± 0.00 PCR-positive replicates per five PCR replicates for Great Seneca Creek, North Fork Shenandoah River, and Monocacy River, respectively). As expected, the prevalence and contamination intensity of Cryptosporidium at the two treatment plant intake sites downstream of these sites were similar to those at the North Fork Shenandoah River and Monocacy River sites. This is in agreement with the results of a recent study performed in Korea, where livestock wastes were more serious pollutants than sewage for Cryptosporidium contamination of rivers (24). In a study conducted at Lake Texoma on the border of Texas and Oklahoma, both agricultural land use and sewage discharge contributed to Cryptosporidium contamination in surface water (20). In contrast, a study performed in Hungary reported that higher oocyst densities were associated with source water receiving effluents from sewage treatment plants (37). In Trinidad and Tobago, urban and forested lands were the two most important sources of oocysts, rather than agricultural lands (36).
The results of genotyping of samples have supported the hypothesis that cattle farms have a role in Cryptosporidium oocyst contamination in rivers. In this study, C. andersoni was the dominant species at both base and storm flow at four of the sites, all of which are downstream of cattle farms. In contrast, C. andersoni was rarely detected at the Great Seneca Creek site, where there are very few farm animal activities. Instead, wildlife genotypes were the dominant genotypes at this site under both base and storm flow conditions. C. andersoni is predominantly a parasite of adult cattle and has been found rarely in other farm animals, such as sheep, pigs, and horses (3-6, 9, 22, 42-44, 47). Interestingly, several other common bovine Cryptosporidium genotypes, such as C. parvum in preweaned calves and C. bovis and C. ryanae in older calves (45), were not found in water samples. Calves, especially preweaned dairy calves, however, are usually managed very differently from adult cattle, which could be one of the reasons for the low levels of these genotypes detected in water samples in this study. In other studies, C. andersoni was also commonly detected in river water samples when genus-specific PCR tools were used for genotyping (16, 29, 34, 40, 41, 53, 57, 62). Although some of the studies also identified C. parvum in river water samples, C. bovis and C. ryanae were never found. A C. bovis-like genotype was found in this study in one water sample. However, there were substantial sequence differences between this genotype and C. bovis found in cattle, sheep and goats; thus, this genotype is likely a parasite of wild mammals.
One of the other reasons for the frequent detection of C. andersoni in water samples is probably the shedding intensity of this species. Samples positive for C. andersoni were more easily amplified by PCR than samples positive for the wildlife genotypes; positive samples had a mean PCR-positive rate of 3.2 replicates/5 replicates for C. andersoni and a mean of 0.6 replicate/5 PCR replicates for wildlife genotypes. This is especially remarkable when primer sequence mismatch is taken into consideration, as the SSU rRNA primers used have minor mismatches with sequences of gastric Cryptosporidium spp., C. andersoni is a gastric species, and almost all wildlife genotypes detected in this study are intestinal species. The high C. andersoni contamination intensity and template competition in PCR were probably also responsible for the low rates of detection of wildlife genotypes at the four sites influenced by cattle farms, as there was also significant coverage by woods and forest in their drainage areas (Tables 1 and 2).
Surprisingly, urban wastewater discharge was not found to be a significant contributor to Cryptosporidium oocyst contamination in river water in this study. Although two watershed sites (the Great Seneca Creek and Monocacy River sites) are downstream of discharges of treated urban wastewater and the two downstream treatment intake sites are under the cumulative influence of all the environmental factors considered in this study, the most common Cryptosporidium genotypes in raw urban wastewater, C. hominis and C. parvum (11, 13, 53, 57, 62, 63), were never found in river water samples in this study. This finding differs from the results of a previous study conducted in neighboring areas. In a limited study of samples collected in 1999 from six rivers in the Maryland portion of the Chesapeake Bay area, Xiao et al. (62) compared the distribution of Cryptosporidium genotypes at sites downstream of wastewater discharge sites and the distribution of Cryptosporidium genotypes at sites downstream of beef cattle farms. Both C. parvum and C. hominis were found at sites downstream of wastewater discharge sites in three rivers. In contrast, only C. parvum was found at sites downstream of cattle farms in three other rivers. C. andersoni was never detected in water samples at these sites, although its occurrence could have been masked by the wide occurrence of C. hominis and C. parvum in these samples. However, C. andersoni was detected in the only sample taken from the Potomac River (62). The reasons for the difference in the role of treated urban wastewater discharge in Cryptosporidium contamination are not clear. It is possible that improvements in discharge regulations and wastewater treatment practices, including the increased stringency of treatment and the incorporation of new technology, such as UV treatment, could have contributed to the less important role of wastewater discharges in Cryptosporidium contamination in recent years.
Most of the genotypes found in water samples in this study are the genotypes which have been found previously in wildlife, indicating that wildlife is also a significant source of Cryptosporidium contamination in the Potomac River watershed. Most of the wildlife genotypes (8/14) were also previously found in three streams in the New York City drinking watershed (18), and some of them (4/14) were also found in the South Nation watershed in Ontario, Canada (41). Among the 14 non-C. andersoni species and genotypes found in this study, only C. felis and C. meleagridis are known to infect domestic animals (cats and chicken or turkeys, respectively). C. meleagridis, however, is known to infect various wild birds, and C. felis may also infect wild felines (feral cats and bobcats). These and other known hosts of the wildlife genotypes found in water samples (Table 5) are known to be active in the Potomac River watershed. The hypothesis that wildlife had a role in the Cryptosporidium contamination observed in this study was further supported by the following observations: (i) the wildlife genotypes were found mostly at the Great Seneca Creek site, at which there were few farm animal activities; (ii) the level of detection of wildlife genotypes was very low (once in one sample) at the Monocacy River site, which has much less forested and wooded area than the other sites; and (iii) the level of detection of wildlife genotypes at the Potomac WFP site (seven times in four samples) was higher than the level of detection of wildlife genotypes at the Corbalis WTP site (four times in two samples) (the land uses at these two sites are similar, but only the former site is influenced by the Great Seneca Creek discharge).
Results of this study corroborate observations made in a recent study performed in the South Nation watershed in Ontario, Canada (41). In the Canadian study, which was a similar size, C. andersoni was the dominant species in the watershed (present at 11/14 sites), and its presence correlated with cattle activities. All of the other genotypes (7/7) found in the watershed are known parasites of wildlife, and they were found mostly at sites where there were fewer farms and less C. andersoni was detected. Despite the potential influence of urban wastewater discharge at some of the sites, C. hominis was never found in the watershed (41). One significant difference between the Canadian watershed study and the present study is the higher level of detection of Cryptosporidium oocysts by method 1623 microscopy (77% of 120 samples).
The Cryptosporidium genotypes found in this study are not commonly found in humans. Of the 15 genotypes found in the Potomac River watershed, only C. andersoni, C. felis, C. meleagridis, the cervine genotype, and the skunk genotype have been found in humans (33). However, most human Cryptosporidium infections (>95% in most areas) are caused by C. hominis and C. parvum (61). Even though C. meleagridis and C. felis are also responsible for small numbers of human infections (61), they were found in this study at a very low frequency. Human infections with the skunk genotype and with C. andersoni have each been reported in only one to four cases (25, 31, 33). Thus, as suggested previously (18, 41, 56, 61), a large proportion of the Cryptosporidium oocysts in water from the sample sites are not oocysts of species known to be harmful to humans.
In conclusion, current standard detection methods for Cryptosporidium oocysts in water do not differentiate pathogenic species from nonpathogenic species. Thus, risk assessment models that do not take this into consideration would overestimate the human health impact of Cryptosporidium. More studies with systematic sampling of different types of water would provide a better picture of the extent of contamination of water with Cryptosporidium species that infect humans in different environmental settings. Periodic determination of the species of Cryptosporidium in a watershed or source water can be helpful in developing strategies for the scientific management and protection of source water and human health.


This study was supported in part by an interagency agreement between the USEPA (through a USEPA Region 3 Regional Applied Research Effort program) and the Centers for Disease Control and Prevention (grant DW75922331-01-0) and by the Potomac River Basin Drinking Water Source Protection Partnership.
We thank Michelle Titman of the Virginia Department of Environmental Quality, Jan Ducnuigeen, Jim Palmer, and Adam Griggs of the Interstate Commission for the Potomac River Basin, and staffs at the Corbalis, Potomac, and City of Frederick WTPs and Seneca WWTP for assistance with sample collection.
The USEPA through its Office of Research and Development managed the research described here, which has been subjected to administrative review by the USEPA and approved for publication. 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.


Alves, M., A. M. Ribeiro, C. Neto, E. Ferreira, M. J. Benoliel, F. Antunes, and O. Matos. 2006. Distribution of Cryptosporidium species and subtypes in water samples in Portugal: a preliminary study. J. Eukaryot. Microbiol.53:S24-S25.
Carmena, D., X. Aguinagalde, C. Zigorraga, J. C. Fernandez-Crespo, and J. A. Ocio. 2007. Presence of Giardia cysts and Cryptosporidium oocysts in drinking water supplies in northern Spain. J. Appl. Microbiol.102:619-629.
Chalmers, R. M., A. L. Thomas, B. A. Butler, and M. C. Morel. 2005. Identification of Cryptosporidium parvum genotype 2 in domestic horses. Vet. Rec.156:49-50.
Elwin, K., and R. M. Chalmers. 2008. Contemporary identification of previously reported novel Cryptosporidium isolates reveals Cryptosporidium bovis and the cervine genotype in sheep (Ovis aries). Parasitol. Res.102:1103-1105.
Fayer, R., M. Santin, and J. M. Trout. 2007. Prevalence of Cryptosporidium species and genotypes in mature dairy cattle on farms in eastern United States compared with younger cattle from the same locations. Vet. Parasitol.145:260-266.
Fayer, R., M. Santin, J. M. Trout, and E. Greiner. 2006. Prevalence of species and genotypes of Cryptosporidium found in 1-2-year-old dairy cattle in the eastern United States. Vet. Parasitol.135:105-112.
Franco, R. M., R. Rocha-Eberhardt, and R. Cantusio Neto. 2001. Occurrence of Cryptosporidium oocysts and Giardia cysts in raw water from the Atibaia River, Campinas, Brazil. Rev. Inst. Med. Trop. Sao Paulo43:109-111.
Gostin, L. O., Z. Lazzarini, V. S. Neslund, and M. T. Osterholm. 2000. Water quality laws and waterborne diseases: Cryptosporidium and other emerging pathogens. Am. J. Public Health90:847-853.
Hajdusek, O., O. Ditrich, and J. Slapeta. 2004. Molecular identification of Cryptosporidium spp. in animal and human hosts from the Czech Republic. Vet. Parasitol.122:183-192.
Hallier-Soulier, S., and E. Guillot. 2000. Detection of cryptosporidia and Cryptosporidium parvum oocysts in environmental water samples by immunomagnetic separation-polymerase chain reaction. J. Appl. Microbiol.89:5-10.
Hanninen, M. L., A. Horman, R. Rimhanen-Finne, H. Vahtera, S. Malmberg, S. Herve, and K. Lahti. 2005. Monitoring of Cryptosporidium and Giardia in the Vantaa River basin, southern Finland. Int. J. Hyg. Environ. Health208:163-171.
Hashimoto, A., S. Kunikane, and T. Hirata. 2002. Prevalence of Cryptosporidium oocysts and Giardia cysts in the drinking water supply in Japan. Water Res.36:519-526.
Hashimoto, A., H. Sugimoto, S. Morita, and T. Hirata. 2006. Genotyping of single Cryptosporidium oocysts in sewage by semi-nested PCR and direct sequencing. Water Res.40:2527-2532.
Horman, A., R. Rimhanen-Finne, L. Maunula, C. H. von Bonsdorff, N. Torvela, A. Heikinheimo, and M. L. Hanninen. 2004. Campylobacter spp., Giardia spp., Cryptosporidium spp., noroviruses, and indicator organisms in surface water in southwestern Finland, 2000-2001. Appl. Environ. Microbiol.70:87-95.
Hsu, B. M., C. P. Huang, G. Y. Jiang, and C. L. L. Hsu. 1999. The prevalence of Giardia and Cryptosporidium in Taiwan water supplies. J. Toxicol. Environ. Health57:149-160.
Jellison, K. L., H. F. Hemond, and D. B. Schauer. 2002. Sources and species of Cryptosporidium oocysts in the Wachusett Reservoir watershed. Appl. Environ. Microbiol.68:569-575.
Jiang, J., K. A. Alderisio, A. Singh, and L. Xiao. 2005. Development of procedures for direct extraction of Cryptosporidium DNA from water concentrates and for relief of PCR inhibitors. Appl. Environ. Microbiol.71:1135-1141.
Jiang, J., K. A. Alderisio, and L. Xiao. 2005. Distribution of Cryptosporidium genotypes in storm event water samples from three watersheds in New York. Appl. Environ. Microbiol.71:4446-4454.
Johnson, D. W., N. J. Pieniazek, D. W. Griffin, L. Misener, and J. B. Rose. 1995. Development of a PCR protocol for sensitive detection of Cryptosporidium oocysts in water samples. Appl. Environ. Microbiol.61:3849-3855.
Keeley, A., and B. R. Faulkner. 2008. Influence of land use and watershed characteristics on protozoa contamination in a potential drinking water resources reservoir. Water Res.42:2803-2813.
Kostrzynska, M., M. Sankey, E. Haack, C. Power, J. E. Aldom, A. H. Chagla, S. Unger, G. Palmateer, H. Lee, J. T. Trevors, and S. A. De Grandis. 1999. Three sample preparation protocols for polymerase chain reaction based detection of Cryptosporidium parvum in environmental samples. J. Microbiol. Methods35:65-71.
Langkjaer, R. B., H. Vigre, H. L. Enemark, and C. Maddox-Hyttel. 2007. Molecular and phylogenetic characterization of Cryptosporidium and Giardia from pigs and cattle in Denmark. Parasitology134:339-350.
LeChevallier, M. W., W. D. Norton, and R. G. Lee. 1991. Occurrence of Giardia and Cryptosporidium spp. in surface water supplies. Appl. Environ. Microbiol.57:2610-2616.
Lee, S. H., C. H. Lee, Y. H. Kim, J. H. Do, and S. H. Kim. 2007. Occurrence of Cryptosporidium oocysts and Giardia cysts in the Nakdong River and their removal during water treatment. J. Water Health5:163-169.
Leoni, F., C. Amar, G. Nichols, S. Pedraza-Diaz, and J. McLauchlin. 2006. Genetic analysis of Cryptosporidium from 2414 humans with diarrhoea in England between 1985 and 2000. J. Med. Microbiol.55:703-707.
Lloyd, A., and D. Drury. 2002. Continuous monitoring for Cryptosporidium—a novel approach to public health protection. Water Sci. Technol.46:297-301.
Lowery, C. J., J. E. Moore, B. C. Millar, D. P. Burke, K. A. McCorry, E. Crothers, and J. S. Dooley. 2000. Detection and speciation of Cryptosporidium spp. in environmental water samples by immunomagnetic separation, PCR and endonuclease restriction. J. Med. Microbiol.49:779-785.
Lowery, C. J., P. Nugent, J. E. Moore, B. C. Millar, X. Xiru, and J. S. Dooley. 2001. PCR-IMS detection and molecular typing of Cryptosporidium parvum recovered from a recreational river source and an associated mussel (Mytilus edulis) bed in Northern Ireland. Epidemiol. Infect.127:545-553.
Masago, Y., K. Oguma, H. Katayama, and S. Ohgaki. 2006. Quantification and genotyping of Cryptosporidium spp. in river water by quenching probe PCR and denaturing gradient gel electrophoresis. Water Sci. Technol.54:119-126.
Montemayor, M., F. Valero, J. Jofre, and F. Lucena. 2005. Occurrence of Cryptosporidium spp. oocysts in raw and treated sewage and river water in north-eastern Spain. J. Appl. Microbiol.99:1455-1462.
Morse, T. D., R. A. Nichols, A. M. Grimason, B. M. Campbell, K. C. Tembo, and H. V. Smith. 2007. Incidence of cryptosporidiosis species in paediatric patients in Malawi. Epidemiol. Infect.135:1307-1315.
Nagano, S., M. Matsubayashi, T. Kita, T. Narushima, I. Kimata, M. Iseki, T. Hajiri, H. Tani, K. Sasai, and E. Baba. 2007. Detection of a mixed infection of a novel Cryptosporidium andersoni and its subgenotype in Japanese cattle. Vet. Parasitol.149:213-218.
Nichols, G. L., R. M. Chalmers, W. Sopwith, M. Regan, C. A. Hunter, P. Grenfell, F. Harrison, and C. Lane. 2006. Cryptosporidiosis: a report on the surveillance and epidemiology of Cryptosporidium infection in England and Wales. Drinking Water Directorate contract number DWI 70/2/201. Drinking Water Inspectorate, London, United Kingdom.
Nichols, R. A., B. M. Campbell, and H. V. Smith. 2006. Molecular fingerprinting of Cryptosporidium oocysts isolated during water monitoring. Appl. Environ. Microbiol.72:5428-5435.
Ono, K., H. Tsuji, S. K. Rai, A. Yamamoto, K. Masuda, T. Endo, H. Hotta, T. Kawamura, and S. Uga. 2001. Contamination of river water by Cryptosporidium parvum oocysts in western Japan. Appl. Environ. Microbiol.67:3832-3836.
Phillip, D. A., S. C. Rawlins, S. Baboolal, R. Gosein, C. Goddard, G. Legall, and A. Chinchamee. 2008. Relative importance of the various environmental sources of Cryptosporidium oocysts in three watersheds. J. Water Health6:23-34.
Plutzer, J., M. H. Tako, K. Marialigeti, A. Torokne, and P. Karanis. 2007. First investigations into the prevalence of Cryptosporidium and Giardia spp. in Hungarian drinking water. J. Water Health5:573-584.
Robertson, L. J., and B. Gjerde. 2001. Occurrence of Cryptosporidium oocysts and Giardia cysts in raw waters in Norway. Scand. J. Public Health29:200-207.
Rose, J. B., D. E. Huffman, and A. Gennaccaro. 2002. Risk and control of waterborne cryptosporidiosis. FEMS Microbiol. Rev.26:113-123.
Ruecker, N. J., N. Bounsombath, P. Wallis, C. S. Ong, J. L. Isaac-Renton, and N. F. Neumann. 2005. Molecular forensic profiling of Cryptosporidium species and genotypes in raw water. Appl. Environ. Microbiol.71:8991-8994.
Ruecker, N. J., S. L. Braithwaite, E. Topp, T. Edge, D. R. Lapen, G. Wilkes, W. Robertson, D. Medeiros, C. W. Sensen, and N. F. Neumann. 2007. Tracking host sources of Cryptosporidium spp. in raw water for improved health risk assessment. Appl. Environ. Microbiol.73:3945-3957.
Ryan, U. M., C. Bath, I. Robertson, C. Read, A. Elliot, L. McInnes, R. Traub, and B. Besier. 2005. Sheep may not be an important zoonotic reservoir for Cryptosporidium and Giardia parasites. Appl. Environ. Microbiol.71:4992-4997.
Ryan, U. M., B. Samarasinghe, C. Read, J. R. Buddle, I. D. Robertson, and R. C. Thompson. 2003. Identification of a novel Cryptosporidium genotype in pigs. Appl. Environ. Microbiol.69:3970-3974.
Santin, M., J. M. Trout, and R. Fayer. 2007. Prevalence and molecular characterization of Cryptosporidium and Giardia species and genotypes in sheep in Maryland. Vet. Parasitol.146:17-24.
Santin, M., J. M. Trout, L. Xiao, L. Zhou, E. Greiner, and R. Fayer. 2004. Prevalence and age-related variation of Cryptosporidium species and genotypes in dairy calves. Vet. Parasitol.122:103-117.
Schets, F. M., J. H. van Wijnen, J. F. Schijven, H. Schoon, and A. M. de Roda Husman. 2008. Monitoring of waterborne pathogens in surface waters in Amsterdam, The Netherlands, and the potential health risk associated with exposure to Cryptosporidium and Giardia in these waters. Appl. Environ. Microbiol.74:2069-2078.
Suarez-Luengas, L., A. Clavel, J. Quilez, M. P. Goni-Cepero, E. Torres, C. Sanchez-Acedo, and E. Del Cacho. 2007. Molecular characterization of Cryptosporidium isolates from pigs in Zaragoza (northeastern Spain). Vet. Parasitol.148:231-235.
Touron, A., T. Berthe, G. Gargala, M. Fournier, M. Ratajczak, P. Servais, and F. Petit. 2007. Assessment of faecal contamination and the relationship between pathogens and faecal bacterial indicators in an estuarine environment (Seine, France). Mar. Pollut. Bull.54:1441-1450.
Tsushima, Y., P. Karanis, T. Kamada, L. Makala, X. Xuan, Y. Tohya, H. Akashi, and H. Nagasawa. 2003. Seasonal change in the number of Cryptosporidium parvum oocysts in water samples from the rivers in Hokkaido, Japan, detected by the ferric sulfate flocculation method. J. Vet. Med. Sci.65:121-123.
Tsushima, Y., P. Karanis, T. Kamada, H. Nagasawa, X. Xuan, I. Igarashi, K. Fujisaki, E. Takahashi, and T. Mikami. 2001. Detection of Cryptosporidium parvum oocysts in environmental water in Hokkaido, Japan. J. Vet. Med. Sci.63:233-236.
U.S. Environmental Protection Agency. 2005. Method 1623: Cryptosporidium and Giardia in water by filtration/IMS/FA. Office of Water, U.S. Environmental Protection Agency, Washington, DC. .
U.S. Environmental Protection Agency. 2006. National primary drinking water regulations: long term 2 enhanced surface water treatment rule. Fed. Regist.71:654-786.
Ward, P. I., P. Deplazes, W. Regli, H. Rinder, and A. Mathis. 2002. Detection of eight Cryptosporidium genotypes in surface and waste waters in Europe. Parasitology124:359-368.
Ware, M. W., L. Wymer, H. D. Lindquist, and F. W. Schaefer. 2003. Evaluation of an alternative IMS dissociation procedure for use with method 1622: detection of Cryptosporidium in water. J. Microbiol. Methods55:575-583.
Weintraub, J. M. 2006. Improving Cryptosporidium testing methods: a public health perspective. J. Water Health4(Suppl 1):23-26.
Xiao, L., K. Alderisio, J. Limor, M. Royer, and A. A. Lal. 2000. Identification of species and sources of Cryptosporidium oocysts in storm waters with a small-subunit rRNA-based diagnostic and genotyping tool. Appl. Environ. Microbiol.66:5492-5498.
Xiao, L., K. Alderisio, and A. Singh. 2006. Development and standardization of a Cryptosporidium genotyping tool for water samples. AWWA Research Foundation, Denver, CO.
Xiao, L., K. A. Alderisio, and J. Jiang. 2006. Detection of Cryptosporidium oocysts in water: effect of the number of samples and analytic replicates on test results. Appl. Environ. Microbiol.72:5942-5947.
Xiao, L., R. Fayer, U. Ryan, and S. J. Upton. 2004. Cryptosporidium taxonomy: recent advances and implications for public health. Clin. Microbiol. Rev.17:72-97.
Xiao, L., A. A. Lal, and J. Jiang. 2004. Detection and differentiation of Cryptosporidium oocysts in water by PCR-RFLP. Methods Mol. Biol.268:163-176.
Xiao, L., and U. M. Ryan. 2008. Molecular epidemiology, p. 387-410. In R. Fayer and L. Xiao (ed.), Cryptosporidium and cryptosporidiosis, 2nd ed. CRC Press and IWA Publishing, Boca Raton, FL.
Xiao, L., A. Singh, J. Limor, T. K. Graczyk, S. Gradus, and A. Lal. 2001. Molecular characterization of Cryptosporidium oocysts in samples of raw surface water and wastewater. Appl. Environ. Microbiol.67:1097-1101.
Zhou, L., A. Singh, J. Jiang, and L. Xiao. 2003. Molecular surveillance of Cryptosporidium spp. in raw wastewater in Milwaukee: implications for understanding outbreak occurrence and transmission dynamics. J. Clin. Microbiol.41:5254-5257.

Information & Contributors


Published In

cover image Applied and Environmental Microbiology
Applied and Environmental Microbiology
Volume 74Number 211 November 2008
Pages: 6495 - 6504
PubMed: 18776033


Received: 16 June 2008
Accepted: 22 August 2008
Published online: 5 September 2008


Request permissions for this article.



Wenli Yang
Centers for Disease Control and Prevention, Atlanta, Georgia 30341
Plato Chen
Washington Suburban Sanitary Commission, Laurel, Maryland 20705
Eric N. Villegas
National Exposure Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, Ohio 452683
Ronald B. Landy
EPA Region III, Fort Meade, Maryland 20755
Charles Kanetsky
EPA Region III, Fort Meade, Maryland 20755
Vitaliano Cama
Centers for Disease Control and Prevention, Atlanta, Georgia 30341
Theresa Dearen
Centers for Disease Control and Prevention, Atlanta, Georgia 30341
Cherie L. Schultz
Interstate Commission for the Potomac River Basin, Rockville, Maryland 20850
Kenneth G. Orndorff
Frederick County Division of Utilities and Solid Waste Management, Frederick, Maryland 21704
Gregory J. Prelewicz
Fairfax Water, Fairfax, Virginia 22031
Miranda H. Brown
Washington Aqueduct, Washington, DC 20016
Kim Roy Young
EPA Region III, Fort Meade, Maryland 20755
Centers for Disease Control and Prevention, Atlanta, Georgia 30341

Metrics & Citations



  • For recently published articles, the TOTAL download count will appear as zero until a new month starts.
  • There is a 3- to 4-day delay in article usage, so article usage will not appear immediately after publication.
  • Citation counts come from the Crossref Cited by service.


If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.

View Options

Figures and Media






Share the article link

Share with email

Email a colleague

Share on social media

American Society for Microbiology ("ASM") is committed to maintaining your confidence and trust with respect to the information we collect from you on websites owned and operated by ASM ("ASM Web Sites") and other sources. This Privacy Policy sets forth the information we collect about you, how we use this information and the choices you have about how we use such information.
FIND OUT MORE about the privacy policy