194: Development of a Multiplex PCR Method for Simultaneous Detection of Five Tropical Fruit Species

Introduction

Food allergies are abnormal immune responses to certain proteins found in food, and their prevalence is rising, particularly in response to increased global consumption of tropical fruits. This study develops a multiplex PCR assay to detect five tropical fruit species: mango, pineapple, avocado, banana, and coconut.

Methods

Novel species-specific primer sets were designed to target the chloroplast matK gene and internal transcribed spacer (ITS) regions. Primer concentrations were optimized for multiplex PCR, with final concentrations of 2.8 μM for mango, 0.2 μM for pineapple, 0.6 μM for avocado, 2.4 μM, for banana, and 4.0 μM for coconut. The optimized assay produced amplicons of 114, 132, 158, 183, and 242 bp for mango, pineapple, avocado, banana, and coconut, respectively. The specificity and sensitivity of the assay were validated through multiplex PCR amplification and capillary electrophoresis.

Results

The assay demonstrated no cross-reactivity when tested against 27 other plant species, including a range of fruits and vegetables. The limit of detection (LOD) for the multiplex PCR assay was determined to be 1 pg/ μL. Additionally, the assay successfully amplified all target species in 32 commercial tropical fruit products, which included 14 juices, 8 dried fruits, 2 frozen fruits, 4 freeze-dried fruits, 2 canned fruits, and 2 sauces. The assay results confirmed the successful amplification of target species in all tested samples with 100% accuracy, aligning exactly with the fruit species listed on the product labels.

Significance

The PCR method developed in this study provides a promising tool for detecting allergenic tropical fruits in complex food matrices. By simultaneously and sensitively detecting five tropical fruits, this multiplex PCR assay aims to prevent allergic reactions in consumers by ensuring accurate identification of allergenic ingredients in food products.

Authors: Jae-Eun Cha, Seung-Man Suh, Inae Lee, Soojin jun, and Hae-Yeong Kim