Exploring the interrelationship between the skin microbiome and skin volatiles: A pilot study

Abstract

Unravelling the interplay between a human’s microbiome and physiology is a relevant task for understanding the principles underlying human health and disease. With regard to human chemical communication, it is of interest to elucidate the role of the microbiome in shaping or generating volatiles emitted from the human body. In this study, we characterized the microbiome and volatile organic compounds (VOCs) sampled from the neck and axilla of ten participants (five male, five female) on two sampling days, by applying different methodological approaches. Volatiles emitted from the respective skin site were collected for 20 min using textile sampling material and analyzed on two analytical columns with varying polarity of the stationary phase. Microbiome samples were analyzed by a culture approach coupled with MALDI-TOF-MS analysis and a 16S ribosomal RNA gene (16S RNA) sequencing approach. Statistical and advanced data analysis methods revealed that classification of body sites was possible by using VOC and microbiome data sets. Higher classification accuracy was achieved by combination of both data pools. Cutibacterium, Staphylococcus, Micrococcus, Streptococcus, Lawsonella, Anaerococcus, and Corynebacterium species were found to contribute to classification of the body sites by the microbiome. Alkanes, esters, ethers, ketones, aldehydes and cyclic structures were used by the classifier when VOC data were considered. The interdisciplinary methodological platform developed here will enable further investigations of skin microbiome and skin VOCs alterations in physiological and pathological conditions.

Can Perfusion-Based Brain Tissue Oxygenation MRI Support the Understanding of Cerebral Abscesses In Vivo?

“…All samples were analyzed by microscopy after Gram-staining and by aerobic and anaerobic culture for 7 days. Bacterial or fungal colonies were identified with MALDI-TOF mass spectrometry (Bruker Daltonik GmbH, Bremen, Germany) as described before [24]. In many cases, molecular detection of bacteria in the samples was performed by PCR amplification of the 16S rDNA gene and, if positive, conventional Sanger sequencing of amplicons as previously described [25].…”

Predicting Chronological Age via the Skin Volatile Profile

“…Machine learning (ML) and multivariate statistical approaches are now routinely employed for the analysis of human volatilomics to include skin as well as breath emissions. − Both unsupervised, such as principal component analysis (PCA) , and hierarchical clustering (HCA) which have discriminatory power, and supervised learning, such as multiple linear regression (MLR), partial least-squares-discriminant analysis (PLS-DA), linear discriminant analysis (LDA), others, ,, which allow classification have been frequently used. These approaches allow for analysis through reducing dimensionality and aid in discrimination, clustering, classification and correlation of VOCs that may be linked to disease ,, and other physiological factors. , …”

“…These approaches allow for analysis through reducing dimensionality and aid in discrimination, clustering, classification and correlation of VOCs that may be linked to disease 35,36,43 and other physiological factors. 38,42 To our knowledge, research on age-associated changes in the skin volatile profile is limited, 28,29 and shows a lack of agreement on age-dependent volatiles. This work aims to build on earlier research by employing a larger healthy participant…”

Mass Specthoscope: A Hand-held Extendable Probe for Localized Noninvasive Sampling of Skin Volatome for Online Analysis

“…Volatile organic compounds (VOCs) emitted by the human body can provide information about the physiological state . These VOCs are emitted due to metabolic activities, interactions with microbiota, and environmental exposure . In recent studies, several factors that can influence profiles of VOCs emitted from the human skin have been identified: (i) systemic diseases; (ii) metabolic activity changes related to age; (iii) dietary intake; and (iv) endogenous compounds in blood vessels that pass the skin barrier .…”