Simultaneous traceability and microbiome characterisation across beef supply chains with Oxford Nanopore sequencing

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ID: 332432
2026
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Abstract
Abstract The advent of portable sequencing technologies, such as Oxford Nanopore Technologies (ONT), has created opportunities for real-time traceability across food supply chains, specifically for beef products from paddock to plate. The stability of DNA across an animal’s lifespan and its presence in carcasses and beef make a DNA-based system an effective means for traceability from paddock to restaurant or supermarket, circumventing the risk of tag loss and potentially preventing cattle theft, substitution, and food fraud. In this study, we investigated whether long-read Nanopore sequencing can identify the animal of origin at different stages of the supply chain, including in the feedlot, the abattoir processing plant, and the butcher shop. Twenty-one animals were sampled at three different levels of the supply chain: 1) hair samples at the feedlot, 2) muscle samples at the abattoir and 3) unknown muscle cuts from the butcher shop. When sampled at different points across the supply chain, samples from the same animals matched with 99-100% identity, while samples from different animals showed good discrimination. This study also illustrated the potential of ONT to detect microorganisms in the same dataset, thereby characterising the relative abundance of bacterial communities across the supply chain. Despite the high sequencing cost, the portability of the Nanopore technologies, requiring only a sequencer of the size of a small phone, is a significant advantage and suggests that it could be deployed for traceability purposes at various points in the supply chain, such as race, processing plant, butchers, supermarkets and restaurants. Future validation of the complete extraction and sequencing workflow under field conditions will be essential to confirm practical applicability in these settings.
Reference Key
openalex_W7222078275 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors L T Nguyen, H J Lamb, E M Ross, Timothy John Mahony, D Morgan, B J Hayes
Journal Translational animal science
Year 2026
DOI
10.1093/tas/txag160
URL
https://doi.org/10.1093/tas/txag160
Keywords Keywords not found

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