Sarah J. Dixon

Individual and gender fingerprints in human body odour

Individuals are thought to have their own distinctive scent, analogous to a signature or fingerprint. To test this idea, we collected axillary sweat, urine and saliva from 197 adults from a village in the Austrian Alps, taking five sweat samples per subject over 10 weeks using a novel skin sampling device. We analysed samples using stir bar sorptive extraction in connection with thermal desorption gas chromatograph–mass spectrometry (GC–MS), and then we statistically analysed the chromatographic profiles using pattern recognition techniques. We found more volatile compounds in axillary sweat than in urine or saliva, and among these we found 373 peaks that were consistent over time (detected in four out of five samples per individual). Among these candidate compounds, we found individually distinct and reproducible GC–MS fingerprints, a reproducible difference between the sexes, and we identified the chemical structures of 44 individual and 12 gender-specific volatile compounds. These individual compounds provide candidates for major histocompatibility complex and other genetically determined odours. This is the first study on human axillary odour to sample a large number of subjects, and our findings are relevant to understanding the chemical nature of human odour, and efforts to design electronic sensors (e-nose) for biometric fingerprinting and disease diagnoses.

Analysis of Volatile Organic Compounds in Human Saliva by a Static Sorptive Extraction Method and Gas Chromatography-Mass Spectrometry

Human saliva not only helps control oral health (with anti-microbial proteins), but it may also play a role in chemical communication. As is the case with other mammalian species, human saliva contains peptides, proteins, and numerous volatile organic compounds (VOCs). A high-throughput analytical method is described for profiling a large number of saliva samples to screen the profiles of VOCs. Saliva samples were collected in a non-stimulated fashion. The method utilized static stir bar extraction followed by gas chromatography-mass spectrometry (GC-MS). The method provided excellent reproducibility for a wide range of salivary compounds, including alcohols, aldehydes, ketones, carboxylic acids, esters, amines, amides, lactones, and hydrocarbons. Furthermore, substantial overlap of salivary VOCs and the previously reported skin VOCs in the same subject group was found in this study by using pattern recognition analyses. Sensitivity, precision, and reproducibility of the method suggest that this technique has potential in physiological, metabolomic, pharmacokinetic, forensic, and toxicological studies of small organic compounds where a large number of human saliva samples are involved.

Comparison of human axillary odour profiles obtained by gas chromatography mass spectrometry and skin microbial profiles obtained by denaturing gradient gel electrophoresis using multivariate pattern recognition

Several studies have shown that microbial action is responsible for many compounds responsible for human odour. In this paper, we compare the pattern of microbial profiles and that of chemical profiles of human axillary odour by using multivariate pattern matching techniques. Approximately 200 subjects from Carinthia, Austria, participated in the study. The microbial profiles were represented by denaturing gradient gel electrophoresis (DGGE) analysis and the axillary odour profiles were determined in the sweat samples collected by a stir-bar sampling device and analysed by gas chromatography/mass spectrometry (GC/MS). Both qualitative and quantitative distance metrics were used to construct dissimilarity matrices between samples which were then used to represent the patterns of these two types of profiles. The distance matrices were then compared by using the Mantel test and the Procrustean test. The results show that on the overall dataset there is no strong correlation between microbial and chemical profiles. When the data are split into family groups, correlations vary according to family with a range of estimated p values from 0.00 to 0.90 that the null hypothesis (no correlation) holds. When 32 subjects who followed four basic rules of behaviour were selected, the estimated p-values are 0.00 using qualitative and <0.01 using quantitative distance metrics, suggesting excellent evidence that there is a connection between the microbial and chemical signature.

Mouse Urinary Biomarkers Provide Signatures of Maturation, Diet, Stress Level, and Diurnal Rhythm

Body fluids such as urine potentially contain a wealth of information pertaining to age, sex, social and reproductive status, physiologic state, and genotype of the donor. To explore whether urine could encode information regarding environment, physiology, and development, we compared the volatile compositions of mouse urine using solid-phase microextraction and gas chromatography-mass spectrometry (SPME-GC/MS). Specifically, we identified volatile organic compounds (VOCs) in individual urine samples taken from inbred C57BL/6J-H-2(b) mice under several experimental conditions-maturation state, diet, stress, and diurnal rhythms, designed to mimic natural variations. Approximately 1000 peaks (i.e., variables) were identified per comparison and of these many were identified as potential differential biomarkers. Consistent with previous findings, we found groups of compounds that vary significantly and consistently rather than a single unique compound to provide a robust signature. We identified over 49 new predictive compounds, in addition to identifying several published compounds, for maturation state, diet, stress, and time-of-day. We found a considerable degree of overlap in the chemicals identified as (potential) biomarkers for each comparison. Chemometric methods indicate that the strong group-related patterns in VOCs provide sufficient information to identify several parameters of natural variations in this strain of mice including their maturation state, stress level, and diet.