Alteration of barrier properties, stratum corneum ceramides and microbiome composition in response to lotion application on cosmetic dry skin.

Xerosis, commonly referred to as dry skin, is a common dermatological condition affecting almost a third of the population. Successful treatment of the condition traditionally involves the application of cosmetic products facilitating the moisturisation of the skin with a range of ingredients including glycerol and fatty acids. While the effectiveness of these treatments is not in question, limited information exists on the impact on the skin microbiome following use of these products and the improvement in skin hydration. Here, we describe improvements in skin barrier properties together with increased levels of cholesterol, ceramides and long-chain fatty acids following application of Body Lotion. Concomitant alterations in the skin microbiome are also seen via 16S rRNA metataxonomics, in combination with both traditional and novel informatics analysis. Following 5 weeks of lotion use, beneficial skin bacteria are increased, with improvements in microbiome functional potential, and increases in pathways associated with biosynthesis of multiple long chain fatty acids.

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiome's role in human health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the collection of leg skin microbiome samples from two healthy cohorts of women with the application of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes with explanations. The explanations are expressed in terms of variations in the relative abundance of key microbes that drive the predictions. We predict skin hydration, subject's age, pre/post-menopausal status and smoking status from the leg skin microbiome. The changes in microbial composition linked to skin hydration can accelerate the development of personalized treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal/gut microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any condition from microbiome samples and has the potential to accelerate the development of microbiome-based personalized therapeutics and non-invasive diagnostics.

The diversity and abundance of fungi and bacteria on the healthy and dandruff affected human scalp.

Dandruff is a skin condition that affects the scalp of up to half the world's population, it is characterised by an itchy, flaky scalp and is associated with colonisation of the skin by Malassezia spp. Management of this condition is typically via antifungal therapies, however the precise role of microbes in the aggravation of the condition are incompletely characterised. Here, a combination of 454 sequencing and qPCR techniques were used to compare the scalp microbiota of dandruff and non-dandruff affected Chinese subjects. Based on 454 sequencing of the scalp microbiome, the two most abundant bacterial genera found on the scalp surface were Cutibacterium (formerly Propionibacterium) and Staphylococcus, while Malassezia was the main fungal inhabitant. Quantitative PCR (qPCR) analysis of four scalp taxa (M. restricta, M. globosa, C. acnes and Staphylococcus spp.) believed to represent the bulk of the overall population was additionally carried out. Metataxonomic and qPCR analyses were performed on healthy and lesional buffer scrub samples to facilitate assessment of whether the scalp condition is associated with differential microbial communities on the sampled skin. Dandruff was associated with greater frequencies of M. restricta and Staphylococcus spp. compared with the healthy population (p<0.05). Analysis also revealed the presence of an unclassified fungal taxon that could represent a novel Malassezia species.

Spatial variations in the microbial community structure and diversity of the human foot is associated with the production of odorous volatiles.

The human foot provides an ideal environment for the colonization and growth of bacteria and subsequently is a body site associated with the liberation of odour. This study aimed to enumerate and spatially map bacterial populations' resident across the foot to understand any association with odour production. Culture-based analysis confirmed that Staphylococci were present in higher numbers than aerobic corynebacteria and Gram-positive aerobic cocci, with all species being present at much higher levels on the plantar sites compared to dorsal sites. Microbiomic analysis supported these findings demonstrating that Staphylococcus spp. were dominant across different foot sites and comprised almost the entire bacterial population on the plantar surface. The levels of volatile fatty acids, including the key foot odour compound isovaleric acid, that contribute to foot odour were significantly increased at the plantar skin site compared to the dorsal surface. The fact that isovaleric acid was not detected on the dorsal surface but was present on the plantar surface is probably attributable to the high numbers of Staphylococcus spp. residing at this site. Variations in the spatial distribution of these microbes appear to be responsible for the localized production of odour across the foot.

Functional characterisation of a SNP in the ABCC11 allele - effects on axillary skin metabolism, odour generation and associated behaviours.

BACKGROUND: A single nucleotide polymorphism (SNP), 538G→A, leading to a G180R substitution in the ABCC11 gene results in reduced concentrations of apocrine derived axillary odour precursors. OBJECTIVE: Determine the axillary odour levels in the SNP ABCC11 genotype variants and to investigate if other parameters associated with odour production are affected. METHODS: Axillary odour was assessed by subjective quantification and gas chromatography headspace analysis. Metabolite profiles, microbiome diversity and personal hygiene habits were also assessed. RESULTS: Axillary odour in the A/A homozygotes was significantly lower compared to the G/A and G/G genotypes. However, the perception-based measures still detected appreciable levels of axillary odour in the A/A subjects. Metabolomic analysis highlighted significant differences in axillary skin metabolites between A/A subjects compared to those carrying the G allele. These differences resulted in A/A subjects lacking specific volatile odourants in the axillary headspace, but all genotypes produced odoriferous short chain fatty acids. Microbiomic analysis revealed differences in the relative abundance of key bacterial genera associated with odour generation between the different genotypes. Deodorant usage indicated a high level of self awareness of axillary odour levels with A/A individuals less likely to adopt personal hygiene habits designed to eradicate/mask its presence. CONCLUSIONS: The SNP in the ABCC11 gene results in lower levels of axillary odour in the A/A homozygotes compared to those carrying the G allele, but A/A subjects still produce noticeable amounts of axillary odour. Differences in axillary skin metabolites, bacterial genera and personal hygiene behaviours also appear to be influenced by this SNP.