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Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
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Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
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Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad

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Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad
Journal Article

Evaluation of Porcine Gastric Mucin-Based Method for Extraction of Noroviruses from Seaweed Salad

2025
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Overview
Human noroviruses (HuNov) are the major cause of foodborne illness globally. Several HuNoV outbreaks have been linked to contaminated ready-to-eat seaweed products. Standard protocols such as the ISO 15216 show limited efficiency in extracting foodborne viruses from seaweed products. Therefore, we evaluated the efficiency of an extraction protocol based on porcine gastric mucin conjugated magnetic beads (PGM-MBs) to recover HuNoVs from Wakame seaweed salad. Compared to other HuNoV extraction methods, the PGM-MB method was more efficient. We then aimed to further improve this protocol by modifying several factors such as the buffers, pH, bead concentration, centrifugation and incubation time. The optimized PGM-MB method yielded 19 ± 3% and 17 ± 4% recovery, for HuNoV GI and GII, respectively. The limit of detection (LOD95) for Wakame seaweed salad was 131 and 56 genomic equivalents per 25 g for HuNoV GI and GII. Although some variability in recovery efficiency was observed between the PGM sources, the optimized PGM-MB protocol effectively extracts HuNoVs from Wakame seaweed salads of various brands and other commodities such as dates, green onions, and salted seaweed. These results support the implementation of the optimized PGM-MB method as a viable alternative for HuNoV surveillance in complex food matrices.