Novel application of metagenomics for the strain-level detection of bacterial contaminants within non-sterile industrial products - a retrospective, real-time analysis

Cunningham-Oakes, Edward ORCID: 0000-0003-0260-5508, Pointon, Tom, Murphy, Barry, Campbell-Lee, Stuart, Connor, Thomas R and Mahenthiralingam, Eshwar (2022) Novel application of metagenomics for the strain-level detection of bacterial contaminants within non-sterile industrial products - a retrospective, real-time analysis. MICROBIAL GENOMICS, 8 (11). mgen000884-.

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Abstract

The home and personal care (HPC) industry generally relies on initial cultivation and subsequent biochemical testing for the identification of microorganisms in contaminated products. This process is slow (several days for growth), labour intensive, and misses organisms which fail to revive from the harsh environment of preserved consumer products. Since manufacturing within the HPC industry is high-throughput, the process of identification of microbial contamination could benefit from the multiple cultivation-independent methodologies that have developed for the detection and analysis of microbes. We describe a novel workflow starting with automated DNA extraction directly from a HPC product, and subsequently applying metagenomic methodologies for species and strain-level identification of bacteria. The workflow was validated by application to a historic microbial contamination of a general-purpose cleaner (GPC). A single strain of <i>Pseudomonas oleovorans</i> was detected metagenomically within the product. The metagenome mirrored that of a contaminant isolated in parallel by a traditional cultivation-based approach. Using a dilution series of the incident sample, we also provide evidence to show that the workflow enables detection of contaminant organisms down to 100 CFU/ml of product. To our knowledge, this is the first validated example of metagenomics analysis providing confirmatory evidence of a traditionally isolated contaminant organism, in a HPC product.

Item Type:	Article
Uncontrolled Keywords:	microbial contamination, metagenomics, strain identification, bioinformatics, metagenome binning
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences
Depositing User:	Symplectic Admin
Date Deposited:	13 Jan 2023 09:25
Last Modified:	15 Mar 2024 18:09
DOI:	10.1099/mgen.0.000884
Open Access URL:	https://doi.org/10.1099/mgen.0.000884
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3167027