Development of a multiplex PCR assay for the authentication of six commercial Pyropia species.

Authors

Eun Soo Noh, Chun Mae Dong, Hee Jeong Park, Hyo Sun Jung, Bo Yeon Kim, In Joon Hwang, Jung-Ha Kang

Published in

Food chemistry. Molecular sciences. Volume 13. Pages 100458. Epub Sep 25, 2026.

Abstract

The global expansion of the Pyropia (laver) market requires reliable methods to authenticate species and prevent economically motivated adulteration (EMA). While automated molecular techniques exist, their reliance on specialized instrumentation limits routine application in standard laboratories. We hypothesized that pairing species-specific SNPs within the rbcL gene with mismatch-engineered primers enables the discrimination of closely related Pyropia species without advanced instrumentation. In this study, we developed a multiplex PCR assay targeting the rbcL gene to differentiate six Pyropia species (P. yezoensis, P. tenera, P. dentata, P. haitanensis, P. seriata, and P. suborbiculata). By analyzing 162 rbcL sequences, we identified conserved species-specific SNPs. We designed a primer set comprising six forward primers with intentional mismatches to improve specificity, paired with a single common reverse primer. The optimized assay (annealing temperature of 54 °C) generated a step-wise pattern of amplicons ranging from 172 to 781 bp, which were resolvable on a conventional 1.5% agarose gel. The assay demonstrated species specificity with no cross-reactivity and exhibited an analytical sensitivity of 10 ng/μL of genomic DNA. To validate the method, we tested 20 commercial laver products using a multi-point sampling strategy. The assay authenticated single-species compositions and identified multi-species blends. These results indicate that analyzing multiple regions per sheet is necessary to determine the true composition of commercial products. These findings support our hypothesis that mismatch-engineered multiplex PCR effectively discriminates target species in complex matrices, providing an accessible and practical tool for verifying composition during routine quality control.

PMID:
42841010
Bibliographic data and abstract were imported from PubMed on 07 Oct 2026.

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