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A 16S Next Generation Sequencing Based Molecular and Bioinformatics Pipeline to Identify Processed Meat Products
Nyaradzo Stella Chaora1,2, Khulekani Sedwell Khanyile2, Kudakwashe Magwedere3
1Department of Life and Consumer Sciences, College of Agriculture and Environmental Sciences, University of South Africa, Rooderpoort 1709, South Africa.
Abstract:
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.
Insights
This study developed a DNA sequencing method to detect processed meat adulteration. The pipeline accurately identified species in artificial mixtures and found significant mislabeling in South African sausages.
Area of Science:
- Food Science
- Molecular Biology
- Bioinformatics
Background:
- Processed meat is frequently adulterated for economic reasons.
- Accurate species identification in processed meat is crucial for consumer protection and regulatory compliance.
Purpose of the Study:
- To develop and validate a molecular and bioinformatics pipeline for detecting mislabeling in processed meat products.
- To assess the prevalence of meat adulteration in various processed meat products sold in South Africa.
Main Methods:
- Utilized the mitochondrial 16S ribosomal RNA (rRNA) gene for DNA analysis.
- Employed Next-Generation Sequencing (Illumina MiSeq) for high-throughput data generation.
- Developed a bioinformatics pipeline for sequence alignment and species identification.
Main Results:
- The diagnostic pipeline successfully detected all species in artificially created DNA mixtures, demonstrating high specificity and sensitivity.
- Analysis of 155 processed meat products revealed that 46% of sausage samples contained mixtures of beef, pork, or mutton.
- Significant mislabeling was identified, with most samples containing primarily *Bos* (cattle) DNA but with traces of *Sus* (pigs) and *Ovis* (sheep).
Conclusions:
- The developed Next-Generation Sequencing pipeline is effective for authenticating meat products and identifying mislabeling.
- The findings highlight a substantial issue with meat adulteration, particularly in sausage products, necessitating improved regulatory oversight.
