Transcriptomic Responses and Survival Mechanisms of Staphylococci to the Antimicrobial Skin Lipid Sphingosine.

Sphingosines are antimicrobial lipids that form part of the innate barrier to skin colonization by microbes. Sphingosine deficiencies can result in increased epithelial infections by bacteria including Staphylococcus aureus. Recent studies have focused on the potential use of sphingosine resistance or its potential mechanisms. We used RNA-Seq to identify the common d-sphingosine transcriptomic response of the transient skin colonizer S. aureus and the dominant skin coloniser S. epidermidis. A common d-sphingosine stimulon was identified that included downregulation of the SaeSR two-component system (TCS) regulon and upregulation of both the VraSR TCS and CtsR stress regulons. We show that the PstSCAB phosphate transporter, and VraSR offer intrinsic resistance to d-sphingosine. Further, we demonstrate increased sphingosine resistance in these staphylococci evolves readily through mutations in genes encoding the FarE-FarR efflux/regulator proteins. The ease of selecting mutants with resistance to sphingosine may impact upon staphylococcal colonization of skin where the lipid is present and have implications with topical therapeutic applications.

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.

In-vivo impact of common cosmetic preservative systems in full formulation on the skin microbiome.

Preservatives play an essentially role in ensuring that cosmetic formulations remain safe for use via control of microbial contamination. Commonly used preservatives include organic acids, alcohols and phenols and these play an essential role in controlling the growth of bacteria, fungi and moulds in substrates that can potentially act as a rich food source for microbial contaminants. Whilst the activity of these compounds is clear, both in vitro and in formulation, little information exists on the potential impact that common preservative systems, in full formulation, have on the skin's resident microbiome. Dysbiosis of the skin's microbiome has been associated with a number of cosmetic conditions but there currently are no in vivo studies investigating the potential for preservative ingredients, when included in personal care formulations under normal use conditions, to impact the cutaneous microbiome. Here we present an analysis of four in vivo studies that examine the impact of different preservation systems in full formulation, in different products formats, with varying durations of application. This work demonstrates that despite the antimicrobial efficacy of the preservatives in vitro, the skin microbiome is not impacted by preservative containing products in vivo.

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.