Validation of an Optimised Method for Quantitative Detection of Hepatitis E Virus in Pork Sausage

Abstract

Hepatitis E virus (HEV) infection is an emerging zoonosis that can be transmitted to humans through the consumption of raw or undercooked pork products. Several methods have been described to detect the virus in food, but there are few data on qualitative and quantitative performance characteristics. In this study, we have developed an optimised method for quantitative detection of HEV in pork sausage based on a combination of previously published protocols. The method utilises sample disruption and phase separation with tri-reagent and 1-bromo-3-chloropropane followed by RNA concentration with isopropanol precipitation. We validated the method for use on reverse transcription quantitative real-time PCR (RT-qPCR) and reverse transcription droplet digital (RT-ddPCR). The 95% limit of detection and limit of quantification was 200 copies/g for both RT-qPCR and RT-ddPCR. RT-ddPCR technology has previously shown promise as a more precise alternative to RT-qPCR. However, we found no evidence for improved performance using RT-ddPCR instead of RT-qPCR for this method. Additionally, we further verified the performance of the HEV RT-PCR assay using the WHO International Standard and Reference Panel for HEV RNA. Finally, we assessed different combinations of RNA concentration protocols and RT-PCR detection strategies. This showed that isopropanol precipitation of viral RNA was at least twice as efficient as magnetic silica bead-based extraction when an inhibitor-tolerant RT-qPCR detection strategy was used. In summary, we present an efficient and well-characterised method for quantitative detection of HEV in pork sausage. Such methods are valuable to provide high-quality data for risk assessments and food monitoring.

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