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.
