Detection and Quantification of Botanical Impurities in Commercial Oregano (Origanum vulgare) Using Metabarcoding and Digital PCR

Abstract

DNA technology for food authentication is already well established, and with the advent of Next Generation Sequencing (NGS) and, more specifically, metabarcoding, compositional analysis of food at the molecular level has rapidly gained popularity. This has led to several reports in the media about the presence of foreign, non-declared species in several food commodities. As herbs and spices are attractive targets for fraudulent manipulation, a combination of digital PCR and metabarcoding by NGS was employed to check the purity of 285 oregano samples taken from the European market. By using novel primers and analytical approaches, it was possible to detect and quantify both adulterants and contaminants in these samples. The results highlight the high potential of NGS for compositional analysis, although its quantitative information (read count percentages) is unreliable, and other techniques are therefore needed to complement the sequencing information for assessing authenticity ('true to the name') of food ingredients.

Keywords: NGS; ddPCR; food authentication; metabarcoding; oregano.

Figure 1

Metabarcoding read distribution of three oregano plant vouchers from Meise Botanical Garden, Belgium.

Figure 2

Overview of the species identified in oregano commercial samples (n = 285) as measured by metabarcoding. The y-axis shows the percentage of samples in which the plant species (x-axis) was found (at least one read). Species present in less than 5% of samples are not shown.

Figure 3

Overview of the quantification results. Both axes are in log scale to adequately represent the orders of magnitude across which the results are spread. The figure shows the relation between the percentage of reads attributed to a contaminant and its measurement in ddPCR.