Genotyping Cryptosporidium parvum with an hsp70 single-nucleotide polymorphism microarray

We investigated the application of an oligonucleotide microarray to (i) specifically detect Cryptosporidium spp., (ii) differentiate between closely related C. parvum isolates and Cryptosporidium species, and (iii) differentiate between principle genotypes known to infect humans. A microarray of 68 capture probes targeting seven single-nucleotide polymorphisms (SNPs) within a 190-bp region of the hsp70 gene of Cryptosporidium parvum was constructed. Labeled hsp70 targets were generated by PCR with biotin- or Cy3-labeled primers. Hybridization conditions were optimized for hybridization time, temperature, and salt concentration. Two genotype I C. parvum isolates (TU502 and UG502), two C. parvum genotype II isolates (Iowa and GCH1), and DNAs from 22 non-Cryptosporidium sp. organisms were used to test method specificity. Only DNAs from C. parvum isolates produced labeled amplicons that could be hybridized to and detected on the array. Hybridization patterns between genotypes were visually distinct, but identification of SNPs required statistical analysis of the signal intensity data. The results indicated that correct mismatch discrimination could be achieved for all seven SNPs for the UG502 isolate, five of seven SNPs for the TU502 isolate, and six of seven SNPs for both the Iowa and GCH1 isolates. Even without perfect mismatch discrimination, the microarray method unambiguously distinguished between genotype I and genotype II isolates and demonstrated the potential to differentiate between other isolates and species on a single microarray. This method may provide a powerful new tool for water utilities and public health officials for assessing point and nonpoint source contamination of water supplies.     

Evaluation of Cryptosporidium parvum Genotyping Techniques

We evaluated the specificity and sensitivity of 11 previously described species differentiation and genotyping PCR protocols for detection of Cryptosporidium parasites. Genomic DNA from three species of Cryptosporidium parasites (genotype 1 and genotype 2 of C. parvum, C. muris, and C. serpentis), two Eimeria species (E. neischulzi and E. papillata), and Giardia duodenalis were used to evaluate the specificity of primers. Furthermore, the sensitivity of the genotyping primers was tested by using genomic DNA isolated from known numbers of oocysts obtained from a genotype 2 C. parvum isolate. PCR amplification was repeated at least three times with all of the primer pairs. Of the 11 protocols studied, 10 amplified C. parvum genotypes 1 and 2, and the expected fragment sizes were obtained. Our results indicate that two species-differentiating protocols are not Cryptosporidium specific, as the primers used in these protocols also amplified the DNA of Eimeria species. The sensitivity studies revealed that two nested PCR-restriction fragment length polymorphism (RFLP) protocols based on the small-subunit rRNA and dihydrofolate reductase genes are more sensitive than single-round PCR or PCR-RFLP protocols.     

Relevance of Cryptosporidium parvum hsp70 mRNA amplification as a tool to discriminate between viable and dead oocysts

Two mRNA extraction methods were compared in this study to clarify the discrepancies found between authors regarding the presence of mRNA in inactivated Cryptosporidium parvum oocysts. Cryptosporidium parvum heat shock protein 70 (hsp70) mRNA extraction was performed by using oligo(dT)20-labeled magnetic beads or by incubating oocyst lysates with DNase I. Significant differences in mRNA recovery rates between these 2 techniques were observed when working on inactivated oocysts. We consistently detected hsp70 mRNA in oocysts heated at 60 C for 30 min and oocysts incubated in 10% formalin for 2 hr when using DNase I in the mRNA extraction procedure. In contrast, no mRNA was detected in such oocysts when magnetic beads were used for the mRNA extraction. The selective capture of long poly-A tail mRNA, when using oligo(dT)20-labeled magnetic beads, is proposed in this paper for explaining the discrepancies observed between the two mRNA extraction methods compared in this study. DNA decay in inactivated and aging oocysts makes quantitative polymerase chain reaction a potential alternative technique for assessing C. parvum oocyst viability status in environmental samples.     

Extensive Polymorphism in Cryptosporidium parvum Identified by Multilocus Microsatellite Analysis

Restriction fragment length polymorphism and DNA sequence analysis discern two main types of Cryptosporidium parvum. We present a survey of length polymorphism at several microsatellite loci for type 1 and type 2 isolates. A total of 14 microsatellite loci were identified from C. parvum DNA sequences deposited in public databases. All repeats were mono-, di-, and trinucleotide repeats of A, AT, and AAT, reflecting the high AT content of the C. parvum genome. Several of these loci showed significant length polymorphism, with as many as seven alleles identified for a single locus. Differences between alleles ranged from 1 to 27 bp. Karyotype analysis using probes flanking three microsatellites localized each marker to an individual chromosomal band, suggesting that these markers are single copy. In a sample of 19 isolates for which at least three microsatellites were typed, a majority of isolates displayed a unique multilocus fingerprint. Microsatellite analysis of isolates passaged between different host species identified genotypic changes consistent with changes in parasite populations.     

Cryptosporidium parvum Mixed Genotypes Detected by PCR-Restriction Fragment Length Polymorphism Analysis

Combinations of 10 Cryptosporidium parvum oocysts, with various ratios of genotype I to genotype II, were isolated and subjected to PCR-restriction fragment length polymorphism analysis. Amplification of both genotypes in these samples ranged from 31 to 74% and yielded no information about the genotype proportions. In addition, since both genotypes were not always detected, amplification of a single genotype is not conclusive evidence that the sample contains only a single genotype.     

Intraspecies Polymorphism of Cryptosporidium parvum Revealed by PCR-Restriction Fragment Length Polymorphism (RFLP) and RFLP-Single-Strand Conformational Polymorphism Analyses

A glycoprotein (Cpgp40/15)-encoding gene of Cryptosporidium parvum was analyzed to reveal intraspecies polymorphism within C. parvum isolates. Forty-one isolates were collected from different geographical origins (Japan, Italy, and Nepal) and hosts (humans, calves, and a goat). These isolates were characterized by means of DNA sequencing, PCR-restriction fragment length polymorphism (PCR-RFLP), and RFLP-single-strand conformational polymorphism (RFLP-SSCP) analyses of the gene for Cpgp40/15. The sequence analysis indicated that there was DNA polymorphism between genotype I and II, as well as within genotype I, isolates. The DNA and amino acid sequence identities between genotypes I and II differed, depending on the isolates, ranging from 73.3 to 82.9% and 62.4 to 80.1%, respectively. Those among genotype I isolates differed, depending on the isolates, ranging from 69.0 to 85.4% and 54.8 to 79.2%, respectively. Because of the high resolution generated by PCR-RFLP and RFLP-SSCP, the isolates of genotype I could be subtyped as genotypes Ia1, Ia2, Ib, and Ie. The isolates of genotype II could be subtyped as genotypes IIa, IIb, and IIc. The isolates from calves, a goat, and one Japanese human were identified as genotype II. Within genotype II, the isolates from Japan were identified as genotype IIa, those from calves in Italy were identified as genotype IIb, and the goat isolate was identified as genotype IIc. All of the genotype I isolates were from humans. The Japanese isolate (code no. HJ3) and all of the Nepalese isolates were identified as genotypes Ia1 and Ia2, respectively. The Italian isolates were identified as genotype Ib, and the Japanese isolate (code no. HJ2) was identified as genotype Ie. Thus, the PCR-RFLP-SSCP analysis of this glycoprotein Cpgp40/15 gene generated a high resolution that has not been achieved by previous methods of genotypic differentiation of C. parvum.     

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.     

Infection status of pigs with Cryptosporidium parvum

To investigate the infection status of pigs with Cryptosporidium parvum, 589 fecal samples were collected from pigs raised at farm in Chungcheongbuk-do and Chungcheongnam-do. Of the 589 pig fecal samples, 62 (10.5%) were positive for C. parvum. The area showing the highest positive rate was Dangjin-gun, Chungcheongnam-do (14.0%), and the lowest (0%) Salmi-myon, Chungcheongbuk-do. The positive rate of C. parvum in Judok-eup increased from 12.7% in the winter to 22.1% in the summer. The results of this study suggest that the pigs may be a source of human C. parvum infection.     

A Transmission/Disequilibrium Test That Allows for Genotyping Errors in the Analysis of Single-Nucleotide Polymorphism Data

The present study assesses the effects of genotyping errors on the type I error rate of a particular transmission/disequilibrium test (TDT(std)), which assumes that data are errorless, and introduces a new transmission/disequilibrium test (TDT(ae)) that allows for random genotyping errors. We evaluate the type I error rate and power of the TDT(ae) under a variety of simulations and perform a power comparison between the TDT(std) and the TDT(ae), for errorless data. Both the TDT(std) and the TDT(ae) statistics are computed as two times a log-likelihood difference, and both are asymptotically distributed as chi(2) with 1 df. Genotype data for trios are simulated under a null hypothesis and under an alternative (power) hypothesis. For each simulation, errors are introduced randomly via a computer algorithm with different probabilities (called "allelic error rates"). The TDT(std) statistic is computed on all trios that show Mendelian consistency, whereas the TDT(ae) statistic is computed on all trios. The results indicate that TDT(std) shows a significant increase in type I error when applied to data in which inconsistent trios are removed. This type I error increases both with an increase in sample size and with an increase in the allelic error rates. TDT(ae) always maintains correct type I error rates for the simulations considered. Factors affecting the power of the TDT(ae) are discussed. Finally, the power of TDT(std) is at least that of TDT(ae) for simulations with errorless data. Because data are rarely error free, we recommend that researchers use methods, such as the TDT(ae), that allow for errors in genotype data.     

Caspase-dependent apoptosis during infection with Cryptosporidium parvum

The protozoan parasite Cryptosporidium parvum causes persistent diarrhea and malnutrition in children and the diarrhea-wasting syndrome in AIDS. No therapy exists for eliminating the parasite in the absence of a healthy immune response. Although it had been reported that infection of intestinal cell lines with C. parvum leads to host cell death, the mechanisms of cytolysis have not been characterized. We show here that infection with C. parvum leads to typical apoptotic nuclear condensation and DNA fragmentation in host cells. Both nuclear condensation and DNA fragmentation are inhibited by a caspase inhibitor, showing that caspases are involved in this type of apoptosis. Finally, blocking apoptosis with the caspase inhibitor increases the percentage of infected cells, suggesting that parasites may use apoptosis to exit from the infected cell or that the infected cells may eliminate the parasite through apoptosis. These results suggest that apoptosis could be involved in the pathogenesis of C. parvum infections in vivo, and raise the possibility that therapeutic interference with host cell death could alter the course of the pathology in vivo.     

Ultrahigh-Density Linkage Map for Cultivated Cucumber (Cucumis sativus L.) Using a Single-Nucleotide Polymorphism Genotyping Array

Genotyping arrays are tools for high-throughput genotyping, which is beneficial in constructing saturated genetic maps and therefore high-resolution mapping of complex traits. Since the report of the first cucumber genome draft, genetic maps have been constructed mainly based on simple-sequence repeats (SSRs) or on combinations of SSRs and sequence-related amplified polymorphism (SRAP). In this study, we developed the first cucumber genotyping array consisting of 32,864 single-nucleotide polymorphisms (SNPs). These markers cover the cucumber genome with a median interval of ~2 Kb and have expected genotype calls in parents/F₁ hybridizations as a training set. The training set was validated with Fluidigm technology and showed 96% concordance with the genotype calls in the parents/F₁ hybridizations. Application of the genotyping array was illustrated by constructing a 598.7 cM genetic map based on a ‘9930’ × ‘Gy14’ recombinant inbred line (RIL) population comprised of 11,156 SNPs. Marker collinearity between the genetic map and reference genomes of the two parents was estimated at R² = 0.97. We also used the array-derived genetic map to investigate chromosomal rearrangements, regional recombination rate, and specific regions with segregation distortions. Finally, 82% of the linkage-map bins were polymorphic in other cucumber variants, suggesting that the array can be applied for genotyping in other lines. The genotyping array presented here, together with the genotype calls of the parents/F₁ hybridizations as a training set, should be a powerful tool in future studies with high-throughput cucumber genotyping. An ultrahigh-density linkage map constructed by this genotyping array on RIL population may be invaluable for assembly improvement, and for mapping important cucumber QTLs.     

Cryptosporidium parvum merozoites share neutralization-sensitive epitopes with sporozoites

Sporozoites and merozoites are stages in the life cycle of Cryptosporidium parvum that can cyclically infect intestinal cells, causing persistent infection and severe diarrhea in immunodeficient patients. Infection by sporozoites can be neutralized by surface-reactive mAb. We show that merozoite infectivity can also be neutralized by surface-reactive mAb. To do this, viable C. parvum merozoites were isolated by differential and isopycnic. centrifugation, and distinguished from sporozoites by transmission electron microscopy. Differential reactivity with a panel of seven mAb was used to determine the amount of sporozoite contamination in isolated merozoite preparations. The isolated merozoites were distinguished from sporozoites (p less than 0.0001) by four sporozoite-specific mAb (16.332, 16.502, 17.25, and 18.357) in an indirect immunofluorescence assay. Three mAb (16.29, 17.41, and 18.44) consistently reacted with both merozoites and sporozoites. Isolated merozoites were infectious for neonatal mice when administered by intraintestinal injection. Infectivity for mice was significantly neutralized (p less than 0.05) when 1 to 2 x 10(5) merozoites were incubated with sporozoite-neutralizing mAb 17.41 or 18.44, before inoculation. Merozoites incubated with an isotype control mAb remained infectious for neonatal mice. We conclude that C. parvum merozoites share neutralization-sensitive epitopes with sporozoites.     

Cloning and Analysis of a Cryptosporidium parvum Gene Encoding a Protein with Homology to Cytoplasmic Form Hsp70

ABSTRACT. An intronless gene encoding a protein of 674 amino acid residues with a molecular mass of 73,403 Da showing homology to the cytoplasmic form of the 70 kDa heat shock proteins has been cloned and sequenced from the intestinal pathogen Cryptosporidium parvum . Monospecific polyclonal antibodies obtained to recombinant protein recognized a single band with an approximate molecular mass of 70 kDa on a Western blot of C. parvum proteins, as well as the 70 kDa heat shock protein from bovine brain. Southern blot analysis suggested the gene was single copy in the C. parvum genome. Eleven perfect repeats of the sequence GGMP were found in the predicted protein near the carboxyl terminus.     

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.     

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.