Identification of Cryptosporidium parvum oocysts by an artificial neural network approach

Microscopic detection of Cryptosporidium parvum oocysts is time-consuming, requires trained analysts, and is frequently subject to significant human errors. Artificial neural networks (ANN) were developed to help identify immunofluorescently labeled C. parvum oocysts. A total of 525 digitized images of immunofluorescently labeled oocysts, fluorescent microspheres, and other miscellaneous nonoocyst images were employed in the training of the ANN. The images were cropped to a 36- by 36-pixel image, and the cropped images were placed into two categories, oocyst and nonoocyst images. The images were converted to grayscale and processed into a histogram of gray color pixel intensity. Commercially available software was used to develop and train the ANN. The networks were optimized by varying the number of training images, number of hidden neurons, and a combination of these two parameters. The network performance was then evaluated using a set of 362 unique testing images which the network had never "seen" before. Under optimized conditions, the correct identification of authentic oocyst images ranged from 81 to 97%, and the correct identification of nonoocyst images ranged from 78 to 82%, depending on the type of fluorescent antibody that was employed. The results indicate that the ANN developed were able to generalize the training images and subsequently discern previously unseen oocyst images efficiently and reproducibly. Thus, ANN can be used to reduce human errors associated with the microscopic detection of Cryptosporidium oocysts.     

Use of Artificial Neural Networks To Accurately Identify Cryptosporidium Oocyst and Giardia Cyst Images

Cryptosporidium parvum and Giardia lamblia are protozoa capable of causing gastrointestinal diseases. Currently, these organisms are identified using immunofluorescent antibody (IFA)-based microscopy, and identification requires trained individuals for final confirmation. Since artificial neural networks (ANN) can provide an automated means of identification, thereby reducing human errors related to misidentification, ANN were developed to identify Cryptosporidium oocyst and Giardia cyst images. Digitized images of C. parvum oocysts and G. lamblia cysts stained with various commercial IFA reagents were used as positive controls. The images were captured using a color digital camera at 400× (total magnification), processed, and converted into a binary numerical array. A variety of “negative” images were also captured and processed. The ANN were developed using these images and a rigorous training and testing protocol. The Cryptosporidium oocyst ANN were trained with 1,586 images, while Giardia cyst ANN were trained with 2,431 images. After training, the best-performing ANN were selected based on an initial testing performance against 100 images (50 positive and 50 negative images). The networks were validated against previously “unseen” images of 500 Cryptosporidium oocysts (250 positive, 250 negative) and 282 Giardia cysts (232 positive, 50 negative). The selected ANNs correctly identified 91.8 and 99.6% of the Cryptosporidium oocyst and Giardia cyst images, respectively. These results indicate that ANN technology can be an alternate to having trained personnel for detecting these pathogens and can be a boon to underdeveloped regions of the world where there is a chronic shortage of adequately skilled individuals to detect these pathogens.     

Use of artificial neural networks to accurately identify Cryptosporidium oocyst and Giardia cyst images

Cryptosporidium parvum and Giardia lamblia are protozoa capable of causing gastrointestinal diseases. Currently, these organisms are identified using immunofluorescent antibody (IFA)-based microscopy, and identification requires trained individuals for final confirmation. Since artificial neural networks (ANN) can provide an automated means of identification, thereby reducing human errors related to misidentification, ANN were developed to identify Cryptosporidium oocyst and Giardia cyst images. Digitized images of C. parvum oocysts and G. lamblia cysts stained with various commercial IFA reagents were used as positive controls. The images were captured using a color digital camera at 400 x (total magnification), processed, and converted into a binary numerical array. A variety of "negative" images were also captured and processed. The ANN were developed using these images and a rigorous training and testing protocol. The Cryptosporidium oocyst ANN were trained with 1,586 images, while Giardia cyst ANN were trained with 2,431 images. After training, the best-performing ANN were selected based on an initial testing performance against 100 images (50 positive and 50 negative images). The networks were validated against previously "unseen" images of 500 Cryptosporidium oocysts (250 positive, 250 negative) and 282 Giardia cysts (232 positive, 50 negative). The selected ANNs correctly identified 91.8 and 99.6% of the Cryptosporidium oocyst and Giardia cyst images, respectively. These results indicate that ANN technology can be an alternate to having trained personnel for detecting these pathogens and can be a boon to underdeveloped regions of the world where there is a chronic shortage of adequately skilled individuals to detect these pathogens.     

Species-Specific, Nested PCR-Restriction Fragment Length Polymorphism Detection of Single Cryptosporidium parvum Oocysts

Concurrent with recent advances seen with Cryptosporidium parvum detection in both treated and untreated water is the need to properly evaluate these advances. A micromanipulation method by which known numbers of C. parvum oocysts, even a single oocyst, can be delivered to a test matrix for detection sensitivity is presented. Using newly developed nested PCR-restriction fragment length polymorphism primers, PCR sensitivity was evaluated with 1, 2, 3, 4, 5, 7, or 10 oocysts. PCR detection rates (50 samples for each number of oocysts) ranged from 38% for single oocysts to 92% for 5 oocysts, while 10 oocysts were needed to achieve 100% detection. The nested PCR conditions amplified products from C. parvum, Cryptosporidium baileyi, and Cryptosporidium serpentis but no other Cryptosporidium sp. or protozoan tested. Restriction enzyme digestion with VspI distinguished between C. parvum genotypes 1 and 2. Restriction enzyme digestion with DraII distinguished C. parvum from C. baileyi and C. serpentis. Use of known numbers of whole oocysts encompasses the difficulty of liberating DNA from the oocyst and eliminates the standard deviation inherent within a dilution series. To our knowledge this is the first report in which singly isolated C. parvum oocysts were used to evaluate PCR sensitivity. This achievement illustrates that PCR amplification of a single oocyst is feasible, yet sensitivity remains an issue, thereby illustrating the difficulty of dealing with low oocyst numbers when working with environmental water samples.     

DEVELOPMENT OF ARTIFICIAL NEURAL NETWORKS CAPABLE OF IDENTIFYING CRYPTOSPORIDIUM PARVUM OOCYSTS STAINED WITH 4', 6 DIAMIDINO-2-PHENYLINDOLE

Cryptosporidium parvum is a coccidian protozoan parasite capable of infecting a variety of mammalian hosts, and can cause gastro-enteric disease within humans. C. parvum oocysts were stained with varying concentrations of 4', 6 diamidino-2-phenylindole (DAPI). After microscopic observation, objects of interest were captured using a CCD color digital camera. The microscopic images were classified based on their DAPI stain properties as either DAPI positive or negative. Individual oocysts were cropped, converted to grayscale, applied to a binary threshold filter, and were further processed into a numerical data array. DAPI positive and negative images (100 each) were randomly removed for artificial neural network (ANN) testing. The remaining image data were used for ANN training using a commercially available software program. After training experimentation, a final network design was implemented possessing 95 input, 400 hidden, and 2 output neurons. Additional control image sets (ranging from 165 to 119 images) were collected to better ascertain ANN performance. These images consisted of DAPI positive oocysts and two types of DAPI negative images (either formalin treated oocysts or algal cultures). Selected ANN correctly identified, as a range, 82.4–93.8% of the DAPI positive oocysts, 97–98.2% of the DAPI negative oocysts, and 52.9–57% of the DAPI negative algal cells. The control image sets were unique data, never presented during ANN training. Because of this, combined with the high number of correct image identifications for certain image sets, ANN technology may provide a means to identify C. parvum oocysts through automated analysis.     

Influence of Surface Characteristics on the Stability of Cryptosporidium parvum Oocysts

Microelectrophoresis is a common technique for probing the surface chemistry of the Cryptosporidium parvum oocyst. Results of previous studies of the electrophoretic mobility of C. parvum oocysts in which microelectrophoresis was used are incongruent. In this work we demonstrated that capillary electrophoresis may also be used to probe the surface characteristics of C. parvum oocysts, and we related the surface chemistry of C. parvum oocysts to their stability in water. Capillary electrophoresis results indicated that oocysts which were washed in a phosphate buffer solution had neutrally charged surfaces. Inactivation of oocysts with formalin did not influence their electrophoretic mobility, while oocyst populations that were washed in distilled water consisted of cells with both neutral and negative surface charges. These results indicate that washing oocysts in low-ionic-strength distilled water can impart a negative charge to a fraction of the oocysts in the sample. Rapid coagulation experiments indicated that oocysts did not aggregate in a 0.5 M NaCl solution; oocyst stability in the salt solution may have been the result of Lewis acid-base forces, steric stabilization, or some other factor. The presence of sucrose and Percoll could not be readily identified on the surface of C. parvum oocysts by attenuated total reflectance-Fourier transform infrared spectroscopy, suggesting that these purification reagents may not be responsible for the stability of the uncharged oocysts. These findings imply that precipitate enmeshment may be the optimal mechanism of coagulation for removal of oocysts in water treatment systems. The results of this work may help elucidate the causes of variation in oocyst surface characteristics, may ultimately lead to improved removal efficiencies in full-scale water treatment systems, and may improve fate and transport predictions for oocysts in natural systems.     

Association of Cryptosporidium parvum with Suspended Particles: Impact on Oocyst Sedimentation

The association of Cryptosporidium parvum oocysts with suspended particles can alter the oocysts' effective physical properties and influence their transport in aquatic systems. To assess this behavior, C. parvum oocysts were mixed with various suspended sediments under a variety of water chemical conditions, and the resulting settling of the oocysts was observed. Direct microscopic observations showed that oocysts attached to suspended sediments. Settling column and batch experiments demonstrated that oocysts are removed from suspension at a much higher rate when associated with sediments. The rate of oocyst sedimentation depended primarily on the type of sediment with which the oocysts were mixed. Changes in background water conditions had a relatively small impact on the extent of oocyst-particle association and the resulting oocyst deposition. We believe that the ubiquitous association of C. parvum oocysts with suspended particles enhances the sedimentation of oocysts in natural waters and that this interaction should generally be considered when predicting the migration of pathogens in the environment.     

Detection and Discrimination of Cryptosporidium parvum and C. hominis in Water Samples by Immunomagnetic Separation-PCR

Cryptosporidium parvum and C. hominis have been the cause of large and serious outbreaks of waterborne cryptosporidiosis. A specific and sensitive recovery-detection method is required for control of this pathogen in drinking water. In the present study, nested PCR-restriction fragment length polymorphism (RFLP), which targets the divergent Cpgp40/15 gene, was developed. This nested PCR detected only the gene derived from C. parvum and C. hominis strains, and RFLP was able to discriminate between the PCR products from C. parvum and C. hominis. To evaluate the sensitivity of nested PCR, C. parvum oocysts inoculated in water samples of two different turbidities were recovered by immunomagnetic separation (IMS) and detected by nested PCR and fluorescent antibody assay (FA). Genetic detection by nested PCR and oocyst number confirmed by FA were compared, and the results suggested that detection by nested PCR depends on the confirmed oocyst number and that nested PCR in combination with IMS has the ability to detect a single oocyst in a water sample. We applied an agitation procedure with river water solids to which oocysts were added to evaluate the recovery and detection by the procedure in environmental samples and found some decrease in the rate of detection by IMS.     

Use of Semiconductor Quantum Dots for Photostable Immunofluorescence Labeling of Cryptosporidium parvum

Cryptosporidium parvum is a waterborne pathogen that poses potential risk to drinking water consumers. The detection of Cryptosporidium oocysts, its transmissive stage, is used in the latest U.S. Environmental Protection Agency method 1622, which utilizes organic fluorophores such as fluorescein isothiocyanate (FITC) to label the oocysts by conjugation with anti-Cryptosporidium sp. monoclonal antibody (MAb). However, FITC exhibits low resistance to photodegradation. This property will inevitably limit the detection accuracy after a short period of continuous illumination. In view of this, the use of inorganic fluorophores, such as quantum dot (QD), which has a high photobleaching threshold, in place of the organic fluorophores could potentially enhance oocyst detection. In this study, QD605-streptavidin together with biotinylated MAb was used for C. parvum oocyst detection. The C. parvum oocyst detection sensitivity increased when the QD605-streptavidin concentration was increased from 5 to 15 nM and eventually leveled off at a saturation concentration of 20 nM and above. The minimum QD605-streptavidin saturation concentration for detecting up to 4,495 ± 501 oocysts (mean ± standard deviation) was determined to be 20 nM. The difference in the enumeration between 20 nM QD605-streptavidin with biotinylated MAb and FITC-MAb was insignificant (P > 0.126) when various C. parvum oocyst concentrations were used. The QD605 was highly photostable while the FITC intensity decreased to 19.5% ± 5.6% of its initial intensity after 5 min of continuous illumination. The QD605-based technique was also shown to be sensitive for oocyst detection in reservoir water. This observation showed that the QD method developed in this study was able to provide a sensitive technique for detecting C. parvum oocysts with the advantage of having a high photobleaching threshold.     

Efficacy of Two Peroxygen-Based Disinfectants for Inactivation of Cryptosporidium parvum Oocysts

Two commercial peroxygen-based disinfectants containing hydrogen peroxide plus either peracetic acid (Ox-Virin) or silver nitrate (Ox-Agua) were tested for their ability to inactivate Cryptosporidium parvum oocysts. Oocysts were obtained from naturally infected goat kids and exposed to concentrations of 2, 5, and 10% Ox-Virin or 1, 3, and 5% Ox-Agua for 30, 60, and 120 min. In vitro excystation, vital dyes (4′,6′-diamidino-2-phenylindole and propidium iodide), and infectivity in neonatal BALB/c mice were used to assess the viability and infectivity of control and disinfectant-treated oocysts. Both disinfectants had a deleterious effect on the survival of C. parvum oocysts, since disinfection significantly reduced and in some cases eliminated their viability and infectivity. When in vitro assays were compared with an infectivity assay as indicators of oocyst inactivation, the excystation assay showed 98.6% inactivation after treatment with 10% Ox-Virin for 60 min, while the vital-dye assay showed 95.2% inactivation and the infectivity assay revealed 100% inactivation. Treatment with 3% Ox-Agua for 30 min completely eliminated oocyst infectivity for mice, although we were able to observe only 74.7% inactivation as measured by excystation assays and 24.3% with vital dyes (which proved to be the least reliable method for predicting C. parvum oocyst viability). These findings indicate the potential efficacy of both disinfectants for C. parvum oocysts in agricultural settings where soil, housing, or tools might be contaminated and support the argument that in comparison to the animal infectivity assay, vital-dye and excystation methods overestimate the viability of oocysts following chemical disinfection.     

Detection of Infectious Cryptosporidium parvum Oocysts in Surface and Filter Backwash Water Samples by Immunomagnetic Separation and Integrated Cell Culture-PCR

A new strategy for the detection of infectious Cryptosporidium parvum oocysts in water samples, which combines immunomagnetic separation (IMS) for recovery of oocysts with in vitro cell culturing and PCR (CC-PCR), was field tested with a total of 122 raw source water samples and 121 filter backwash water grab samples obtained from 25 sites in the United States. In addition, samples were processed by Percoll-sucrose flotation and oocysts were detected by an immunofluorescence assay (IFA) as a baseline method. Samples of different water quality were seeded with viable C. parvum to evaluate oocyst recovery efficiencies and the performance of the CC-PCR protocol. Mean method oocyst recoveries, including concentration of seeded 10-liter samples, from raw water were 26.1% for IMS and 16.6% for flotation, while recoveries from seeded filter backwash water were 9.1 and 5.8%, respectively. There was full agreement between IFA oocyst counts of IMS-purified seeded samples and CC-PCR results. In natural samples, CC-PCR detected infectious C. parvum in 4.9% (6) of the raw water samples and 7.4% (9) of the filter backwash water samples, while IFA detected oocysts in 13.1% (16) of the raw water samples and 5.8% (7) of the filter backwash water samples. All CC-PCR products were confirmed by cloning and DNA sequence analysis and were greater than 98% homologous to the C. parvum KSU-1 hsp70 gene product. DNA sequence analysis also revealed reproducible nucleotide substitutions among the hsp70 fragments, suggesting that several different strains of infectious C. parvum were detected.     

Comparative Sensitivity of PCR Primer Sets for Detection of Cryptosporidium parvum

Improved methods for detection of Cryptosporidium oocysts in environmental and clinical samples are urgently needed to improve detection of cryptosporidiosis. We compared the sensitivity of 7 PCR primer sets for detection of Cryptosporidium parvum. Each target gene was amplified by PCR or nested PCR with serially diluted DNA extracted from purified C. parvum oocysts. The target genes included Cryptosporidium oocyst wall protein (COWP), small subunit ribosomal RNA (SSU rRNA), and random amplified polymorphic DNA. The detection limit of the PCR method ranged from 10³ to 10⁴ oocysts, and the nested PCR method was able to detect 10⁰ to 10² oocysts. A second-round amplification of target genes showed that the nested primer set specific for the COWP gene proved to be the most sensitive one compared to the other primer sets tested in this study and would therefore be useful for the detection of C. parvum.     

Quantitative Flow Cytometric Evaluation of Maximal Cryptosporidium parvum Oocyst Infectivity in a Neonate Mouse Model

The importance of waterborne transmission of Cryptosporidium parvum to humans has been highlighted by recent outbreaks of cryptosporidiosis. The first step in a survey of contaminated water currently consists of counting C. parvum oocysts. Data suggest that an accurate risk evaluation should include a determination of viability and infectivity of counted oocysts in water. In this study, oocyst infectivity was addressed by using a suckling mouse model. Four-day-old NMRI (Naval Medical Research Institute) mice were inoculated per os with 1 to 1,000 oocysts in saline. Seven days later, the number of oocysts present in the entire small intestine was counted by flow cytometry using a fluorescent, oocyst-specific monoclonal antibody. The number of intestinal oocysts was directly related to the number of inoculated oocysts. For each dose group, infectivity of oocysts, expressed as the percentage of infected animals, was 100% for challenge doses between 25 and 1,000 oocysts and about 70% for doses ranging from 1 to 10 oocysts/animal. Immunofluorescent flow cytometry was useful in enhancing the detection sensitivity in the highly susceptible NMRI suckling mouse model and so was determined to be suitable for the evaluation of maximal infectivity risk.     

Cryptosporidium parvum Infection in SCID Mice Infected with Only One Oocyst: qPCR Assessment of Parasite Replication in Tissues and Development of Digestive Cancer

Dexamethasone (Dex) treated Severe Combined Immunodeficiency (SCID) mice were previously described as developing digestive adenocarcinoma after massive infection with Cryptosporidium parvum as soon as 45 days post-infection (P.I.). We aimed to determine the minimum number of oocysts capable of inducing infection and thereby gastrointestinal tumors in this model. Mice were challenged with calibrated oocyst suspensions containing intended doses of: 1, 10, 100 or 10⁵ oocysts of C. parvum Iowa strain. All administered doses were infective for animals but increasing the oocyst challenge lead to an increase in mice infectivity (P = 0.01). Oocyst shedding was detected at 7 days P.I. after inoculation with more than 10 oocysts, and after 15 days in mice challenged with one oocyst. In groups challenged with lower inocula, parasite growth phase was significantly higher (P = 0.005) compared to mice inoculated with higher doses. After 45 days P.I. all groups of mice had a mean of oocyst shedding superior to 10,000 oocyst/g of feces. The most impressive observation of this study was the demonstration that C. parvum-induced digestive adenocarcinoma could be caused by infection with low doses of Cryptosporidium, even with only one oocyst: in mice inoculated with low doses, neoplastic lesions were detected as early as 45 days P.I. both in the stomach and ileo-caecal region, and these lesions could evolve in an invasive adenocarcinoma. These findings show a great amplification effect of parasites in mouse tissues after challenge with low doses as confirmed by quantitative PCR. The ability of C. parvum to infect mice with one oocyst and to develop digestive adenocarcinoma suggests that other mammalian species including humans could be also susceptible to this process, especially when they are severely immunocompromised.     

Effect of Particles on the Recovery of Cryptosporidium Oocysts from Source Water Samples of Various Turbidities

Cryptosporidium parvum can be found in both source and drinking water and has been reported to cause serious waterborne outbreaks which threaten public health safety. The U.S. Environmental Protection Agency has developed method 1622 for detection of Cryptosporidium oocysts present in water. Method 1622 involves four key processing steps: filtration, immunomagnetic separation (IMS), fluorescent-antibody (FA) staining, and microscopic evaluation. The individual performance of each of these four steps was evaluated in this study. We found that the levels of recovery of C. parvum oocysts at the IMS-FA and FA staining stages were high, averaging more than 95%. In contrast, the level of recovery declined significantly, to 14.4%, when the filtration step was incorporated with tap water as a spiking medium. This observation suggested that a significant fraction of C. parvum oocysts was lost during the filtration step. When C. parvum oocysts were spiked into reclaimed water, tap water, microfiltration filtrate, and reservoir water, the highest mean level of recovery of (85.0% ± 5.2% [mean ± standard deviation]) was obtained for the relatively turbid reservoir water. Further studies indicated that it was the suspended particles present in the reservoir water that contributed to the enhanced C. parvum oocyst recovery. The levels of C. parvum oocyst recovery from spiked reservoir water with different turbidities indicated that particle size and concentration could affect oocyst recovery. Similar observations were also made when silica particles of different sizes and masses were added to seeded tap water. The optimal particle size was determined to be in the range from 5 to 40 μm, and the corresponding optimal concentration of suspended particles was 1.42 g for 10 liters of tap water.     

Development of a Cryptosporidium oocyst assay using an automated fiber optic-based biosensor

An intestinal protozoan parasite, Cryptosporidium parvum, is a major cause of waterborne gastrointestinal disease worldwide. Detection of Cryptosporidium oocysts in potable water is a high priority for the water treatment industry to reduce potential outbreaks among the consumer populace. Anti-Cryptosporidium oocyst polyclonal and monoclonal antibodies were tested as capture and detection reagents for use in a fiber optic biosensor assay for the detection of Cryptosporidium oocysts. Antibodies were validated using enzyme-linked immunosorbent assays, flow cytometry, Western blotting and fluorescent microscopy. Oocysts could be detected at a concentration of 10⁵ oocysts/ml when the polyclonal antibodies were used as the capture and detection reagents. When oocysts were boiled prior to detection, a ten-fold increase in sensitivity was achieved using the polyclonal antibody. Western blotting and immunofluorescence revealed that both the monoclonal and polyclonal antibodies recognize a large (>300 kDa) molecular weight mucin-like antigen present on the surface of the oocyst wall. The polyclonal antibody also reacted with a small (105 kDa) molecular weight antigen that was present in boiled samples of oocysts. Preliminary steps to design an in-line biosensor assay system have shown that oocysts would have to be concentrated from water samples and heat treated to allow detection by a biosensor assay.     

Improved Quantitative Estimates of Low Environmental Loading and Sporadic Periparturient Shedding of Cryptosporidium parvum in Adult Beef Cattle

Our primary goal was to generate an accurate estimate of the daily environmental loading rate of Cryptosporidium parvum oocysts for adult beef cattle, using immunomagnetic separation coupled with direct immunofluorescence microscopy for a highly sensitive diagnostic assay. An additional goal was to measure the prevalence and intensity of fecal shedding of C. parvum oocysts in pre- and postparturient cows as an indicator of their potential to infect young calves. This diagnostic method could detect with a ≥90% probability oocyst concentrations as low as 3.2 oocysts g of feces⁻¹, with a 54% probability of detecting just one oocyst g of feces⁻¹. Using this diagnostic method, the overall apparent prevalence of adult beef cattle testing positive for C. parvum was 7.1% (17 of 240), with 8.3 and 5.8% of cattle shedding oocysts during the pre- and postcalving periods, respectively. The mean intensity of oocyst shedding for test-positive cattle was 3.38 oocysts g of feces⁻¹. The estimated environmental loading rate of C. parvum ranged from 3,900 to 9,200 oocysts cow⁻¹ day⁻¹, which is substantially less than a previous estimate of 1.7 × 10⁵ oocysts cow⁻¹ day⁻¹ (range of 7.7 × 10⁴ to 2.3 × 10⁵ oocysts cow⁻¹ day⁻¹) (B. Hoar, E. R. Atwill, and T. B. Farver, Quant. Microbiol. 2:21-36, 2000). Use of this highly sensitive assay functioned to detect a greater proportion of low-intensity shedders in our population of cattle, which reduced the estimated mean intensity of shedding and thereby reduced the associated environmental loading rate compared to those of previous studies.     

Ultrastructure of Cryptosporidium parvum Oocysts and Excysting Sporozoites as Revealed by High Resolution Scanning Electron Microscopy1

Cryptosporidium parvum oocysts isolated from calf feces were examined by scanning electron microscopy during excystation. Intact C. parvum oocysts were spheroid to ellipsoid, ?3.5 × 4.0 μm, with length: width ratio = 1.17. The oocyst wall had a single suture at one pole, which spanned 1/3 to 1/2 the circumference of the oocyst. During excystation the suture dissolved, resulting in a slit-like opening, which the sporozoites used to exit the oocyst. Sporozoites were 3.8 times 0.6 μm and had a rough outer surface.     

Detection of Cryptosporidium parvum in Soil Extracts

Epifluorescent microscopy and flow cytometry were used in different combinations with fluorescein isothiocyanate-labeled immunoglobulins M and G3 to estimate the numbers of Cryptosporidium parvum oocysts in soil extracts containing 10 to 10,017 oocysts/ml. No combination had a systematic effect on accuracy or precision. Background debris may have produced overestimates at low oocyst concentrations when flow cytometry was used.     

Evaluation of water treatment plant UV reactor efficiency against Cryptosporidium parvum oocyst infectivity in immunocompetent suckling mice

Aim: To assess the efficiency of a medium‐pressure UV reactor under full‐scale water treatment plant (WTP) conditions on the infectivity of Cryptosporidium parvum oocysts in an Naval Medical Research Institute (NMRI) suckling mice infectivity model. Methods and Results: Six/seven‐day‐old mice were administered orally 2–10 × 10⁴Cryptosporidium parvum oocysts. Compared with nonirradiated oocysts, 40 mJ cm^?2 UV irradiation of ingested oocysts resulted 7 days later in a 3·4–4·0 log₁₀ reduction in the counts of small intestine oocysts, using a fluorescent flow cytometry assay. Conclusion: Present data extend to industrial conditions previous observations of the efficiency of UV irradiation against Cryptosporidium parvum oocyst in vivo development. Significance and Impact of the study: Present results suggest that in WTP conditions, a medium‐pressure UV reactor is efficient in reducing the infectivity of Cryptosporidium parvum oocysts, one of the most resistant micro‐organisms present in environmental waters.