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The presence of foodborne protozoan pathogens including Cryptosporidium parvum, Giardia duodenalis, Toxoplasma gondii, and Cyclospora cayetanensis in commercial shellfish has been reported across diverse geographical regions. In the present study, a novel multiplex nested polymerase chain reaction (PCR) assay was validated to simultaneously detect and discriminate these four targeted parasites in oyster tissues including whole tissue homogenate, digestive gland, gills, and hemolymph, as well as seawater where shellfish grow. To differentiate viable and non-viable protozoan (oo)cysts, we further evaluated reverse transcription quantitative PCR (RT-qPCR) assays through systematic laboratory spiking experiments by spiking not only dilutions of viable parasites but also mixtures of viable and non-viable parasites in the oyster tissues and seawater. Results demonstrate that multiplex PCR can detect as few as 5-10 (oo)cysts in at least one oyster matrix, as well as in 10 L of seawater. All parasites were detected at the lowest spiking dilution (5 (oo)cysts per extract) in hemolymph, however the probability of detection varied across the difference matrices tested for each parasite. RT-qPCR further discriminated viable from non-viable (heat-inactivated) C. parvum and T. gondii in seawater and hemolymph but did not perform well in other oyster matrices. This systematic spiking study demonstrates that a molecular approach combining multiplex PCR for sensitive and affordable screening of protozoan DNA and subsequent RT-qPCR assay for viability discrimination presents an important advance for accurately determining the risk of protozoal illness in humans due to consumption of contaminated shellfish.Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Citation

Minji Kim, Lezlie Rueda, Andrea Packham, James Moore, Stefan Wuertz, Karen Shapiro. Molecular detection and viability discrimination of zoonotic protozoan pathogens in oysters and seawater. International journal of food microbiology. 2023 Sep 11;407:110391110391


PMID: 37742524

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