A 16S Next Generation Sequencing Based Molecular and Bioinformatics Pipeline to Identify Processed Meat Products Contamination and Mislabelling.

Nyaradzo Stella Chaora,Frederick Tawi Tabit,Kudakwashe Magwedere,Farai Catherine Muchadeyi,Khulekani Sedwell Khanyile,Rian Pierneef

doi:10.3390/ani12040416

Abstract

Simple SummaryMeat adulteration and fraud encompasses the deliberate fraudulent addition or substitution of proteins of animal or plant origin in edible products primarily for economic gain. The mitochondrial 16S ribosomal (rRNA) gene was used to identify species that are present in pure and processed meat samples. The meat samples were sequenced using an Illumina sequencing platform, and bioinformatics analysis was carried out for species identification. The results indicated that pork was the major contaminant in most of the meat samples. The bioinformatics pipeline demonstrated its specificity through identification of species specific and quantification of the contamination levels across all samples. Food business operators and regulatory sectors can validate this method for food fraud checks and manage any form of mislabeling in the animal or plant protein food ecosystem.Processed meat is a target in meat adulteration for economic gain. This study demonstrates a molecular and bioinformatics diagnostic pipeline, utilizing the mitochondrial 16S ribosomal RNA (rRNA) gene, to determine processed meat product mislabeling through Next-Generation Sequencing. Nine pure meat samples were collected and artificially mixed at different ratios to verify the specificity and sensitivity of the pipeline. Processed meat products (n = 155), namely, minced meat, biltong, burger patties, and sausages, were collected across South Africa. Sequencing was performed using the Illumina MiSeq sequencing platform. Each sample had paired-end reads with a length of ±300 bp. Quality control and filtering was performed using BBDuk (version 37.90a). Each sample had an average of 134,000 reads aligned to the mitochondrial genomes using BBMap v37.90. All species in the artificial DNA mixtures were detected. Processed meat samples had reads that mapped to the Bos (90% and above) genus, with traces of reads mapping to Sus and Ovis (2–5%) genus. Sausage samples showed the highest level of contamination with 46% of the samples having mixtures of beef, pork, or mutton in one sample. This method can be used to authenticate meat products, investigate, and manage any form of mislabeling.

Highlights

Meat species identification is a subject that has received special attention worldwide, mainly due to the increased incidence of fraudulent practices that have been reported [1,2,3,4]
Meat species substitution is common in processed meat products that are difficult to accurately identify morphologically once processed into value-added products
Pure meat samples were collected as controls to verify the use of the 16S ribosomal RNA (rRNA) gene in the molecular and bioinformatics pipeline developed

Summary

Introduction

Meat species identification is a subject that has received special attention worldwide, mainly due to the increased incidence of fraudulent practices that have been reported [1,2,3,4]. These reports have led to consumers demanding the accurate identification and labelling of meat products [5]. Incidents of meat species substitution include contamination of a product with a cheaper-priced protein. Meat species substitution is common in processed meat products that are difficult to accurately identify morphologically once processed into value-added products. Meat adulteration predominately occurs in ground meat products [8]

Objectives

Methods

Findings

Conclusion