Development of a reverse transcription-PCR-DNA enzyme immunoassay for detection of "Norwalk-like" viruses and hepatitis A virus in stool and shellfish
- PMID: 11157239
- PMCID: PMC92643
- DOI: 10.1128/AEM.67.2.742-749.2001
Development of a reverse transcription-PCR-DNA enzyme immunoassay for detection of "Norwalk-like" viruses and hepatitis A virus in stool and shellfish
Abstract
Outbreaks of food- and waterborne gastroenteritis are being increasingly reported throughout the world. The analysis of environmental samples by newer diagnostic techniques such as reverse transcription-PCR (RT-PCR) amplification of nucleic acid has begun to identify human enteric viruses (predominantly "Norwalk-like" viruses [NLVs]) as the cause of many of these outbreaks. To streamline NLV detection from environmental samples such as shellfish, we have developed an RT-PCR-oligoprobe amplification and detection method using several new procedures that enable confirmed RT-PCR amplification and product detection in 1 day. The new steps include replacing reverse transcriptase and Taq polymerase with rTth polymerase, a heat-stable enzyme that functions as both a reverse transcriptase and DNA polymerase, in a single-tube, single-buffer, elevated temperature reaction. An internal standard Norwalk virus (NV) RNA control is added to each RT-PCR to identify sample inhibition, and thermolabile uracil N-glycosylase is incorporated into the reaction to prevent PCR product carryover contamination. Finally, RT-PCR-generated amplicons are detected in microtiter wells using virus-specific biotinylated oligoprobes in an enzyme-linked immunosorbent assay-based format. The DNA enzyme immunoassay is based on the capture of PCR product by biotinylated probes fixed onto individual streptavidin-coated wells. Using this method, low levels of NV were detected in stool and both NLV and hepatitis A virus were detected in bivalve mollusks following bioaccumulation. The method also successfully detected NLV in oysters implicated in an outbreak of NLV gastroenteritis. This method dramatically decreases the time needed for analysis and is amenable to automation.
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