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Applied and Environmental Microbiology, April 2002, p. 1817-1826, Vol. 68, No. 4
0099-2240/02/$04.00+0     DOI: 10.1128/AEM.68.4.1817-1826.2002
Copyright © 2002, American Society for Microbiology. All Rights Reserved.

Genotyping Cryptosporidium parvum with an hsp70 Single-Nucleotide Polymorphism Microarray

Analytical Microbiology,¹ Applied Statistics Group, Pacific Northwest National Laboratory, Richland, Washington 99352,² Metropolitan Water District of Southern California, LaVerne, California 91750³

Received 2 October 2001/ Accepted 14 January 2002

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.

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