bioRxivMicrobiology
Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples
A. J. McHugh, M. Yap, F. Crispie, C. Feehily, C. Hill, P. D. Cotter
Abstract
Food processing environments can harbor microorganisms responsible for food spoilage or foodborne disease. Efficient and accurate identification of microorganisms throughout the food chain can allow the identification of sources of contamination and the timely implementation of control measures. Currently, microbial monitoring of the food chain relies heavily on culture-based techniques. These assays are determined on the microbes expected to be present in the environment, and thus do not cater for unexpected contaminants. Many culture-based assays are also unable to distinguish between undesirable taxa and closely related harmless species. Furthermore, even when multiple culture-based approaches are used in parallel, it is still not possible to comprehensively characterize the entire microbiology of a food-chain sample. High throughput DNA sequencing represents a potential means through which microbial monitoring of the food chain can be enhanced. While sequencing platforms, such as the Illumina MiSeq, NextSeq and NovaSeq, are most typically found in research or commercial sequencing laboratories, newer portable platforms, such as the Oxford Nanopore Technologies (ONT) MinION, offer the potential for rapid analysis of food chain microbiomes. In this study, having initially assessed the ability of rapid MinION-based sequencing to discriminate between different microbes within a simple mock metagenomic mixture of related food spoilage, spore-forming microorganisms. Subsequently, we proceeded to compare the performance of both ONT and Illumina sequencing for environmental monitoring of an active food processing facility. Overall, ONT MinION sequencing provided accurate classification to species level, which was comparable to Illumina-derived outputs. However, while the MinION-based approach provided a means of easy library preparations and portability, the high concentrations of DNA needed to run the rapid sequencing protocols was a limiting factor, requiring the random amplification of template DNA in order to generate sufficient material for analysis.
- assay: metagenomics
- research focus: benchmarking
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Direct Metatranscriptome RNA-seq and Multiplex RT-PCR Amplicon Sequencing on Nanopore MinION - Promising Strategies for Multiplex Identification of Viable Pathogens in Food
M. Yang, A. Cousineau, … B. Zhang·Frontiers in MicrobiologyPeer-reviewed·Apr 9, 2020
- Multi-Locus And Long Amplicon Sequencing Approach To Study Microbial Diversity At Species Level Using The MinION™ Portable Nanopore Sequencer
A. Benitez-Paez, Y. Sanz·bioRxiv·Jun 8, 2017
- Introducing NOMAD: A Field-Deployable Workflow for Rapid, On-Site Microbiome Analysis of Raw Bovine Milk Using Full-Length 16S rRNA Sequencing
Valeria R. Parreira, Melinda Precious, … Lawrence D. Goodridge·bioRxiv·Sep 29, 2025
- Long reads from Nanopore sequencing as a tool for animal microbiome studies
B. Delgado, M. Serrano, … O. Gonzalez-Recio·bioRxiv·Dec 21, 2019
- Monitoring the microbiome for food safety and quality using deep shotgun sequencing
K. L. Beck, N. Haiminen, … Consortium for Sequencing the Food Supply Chain·bioRxiv·May 18, 2020
- A metagenomic framework for rapid Listeria monocytogenes surveillance in food production environments
Francis Muchaamba, Tim Reska, … Lara Urban·bioRxiv·Apr 23, 2026