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

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 Pseudomonas oleovorans 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.

Genomics reveals the novel species placement of industrial contaminant isolates incorrectly identified as Burkholderia lata.

The Burkholderia cepacia complex (Bcc) is a closely related group of bacteria, composed of at least 20 different species, the accurate identification of which is essential in the context of infectious diseases. In industry, they can contaminate non-food products, including home and personal care products and cosmetics. The Bcc are problematic contaminants due to their ubiquitous presence and intrinsic antimicrobial resistance, which enables them to occasionally overcome preservation systems in non-sterile products. Burkholderia lata and Burkholderia contaminans are amongst the Bcc bacteria encountered most frequently as industrial contaminants, but their identification is not straightforward. Both species were historically established as a part of a group known collectively as taxon K, based upon analysis of the recA gene and multilocus sequence typing (MLST). Here, we deploy a straightforward genomics-based workflow for accurate Bcc classification using average nucleotide identity (ANI) and core-gene analysis. The workflow was used to examine a panel of 23 Burkholderia taxon K industrial strains, which, based on MLST, comprised 13 B. lata, 4 B. contaminans and 6 unclassified Bcc strains. Our genomic identification showed that the B. contaminans strains retained their classification, whilst the remaining strains were reclassified as Burkholderia aenigmatica sp. nov. Incorrect taxonomic identification of industrial contaminants is a problematic issue. Application and testing of our genomic workflow allowed the correct classification of 23 Bcc industrial strains, and also indicated that B. aenigmatica sp. nov. may have greater importance than B. lata as a contaminant species. Our study illustrates how the non-food manufacturing industry can harness whole-genome sequencing to better understand antimicrobial-resistant bacteria affecting their products.

Genome Sequence of Pluralibacter gergoviae ECO77, a Multireplicon Isolate of Industrial Origin.

In order to expand the limited understanding of the genomics of antimicrobial-resistant industrial bacteria, we report the genome sequence of Pluralibacter gergoviae ECO77, a historical contaminant strain of industrial origin. The multireplicon 6.16-Mbp genome of ECO77 consists of a 5.37-Mbp main chromosome, a megaplasmid (605,666 bp), and a large plasmid (182,007 bp).

Understanding the challenges of non-food industrial product contamination.

Preventing microbial contamination of non-food products is a major area of industrial microbiology where preservatives are used to stop microbial growth. However, microorganisms occasionally overcome product preservation, causing recalls and the implementation of multiple procedures to prevent further contamination. Correct reporting of microbial contamination in non-food industrial products is vital, especially if spoilage organisms are antimicrobial resistant and pose a health threat. Gram-negative bacteria such as Pseudomonas, Burkholderia and Enterobacteriaceae are frequently reported as non-food product contaminants, including species that overlap current antimicrobial resistance priorities. Historical analysis of recall databases highlighted that for greater than 15% of contamination incidents, the causative microbial agents are reported as unidentified. Here we review the current antimicrobial resistant bacterial species associated with non-food product contamination and evaluate recall reporting in Europe from 2005 to 2018. Our review shows that 49% of microbial contaminants are reported as unidentified despite frequent detection of antimicrobial resistant pathogens; in contrast, 98% of food-related microbial contaminants are classified. Recommendations to fill this microbial identification gap in non-food product recalls are made. Overall, reporting standards for microbial contamination in non-food products must be improved to enable surveillance and for understanding the risks associated with antimicrobial resistant microorganisms.