Abstract
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.
Similar content being viewed by others
References
Brereton R.G. (2003) Chemometrics: Data Analysis for the Laboratory and Chemical Plant. Wiley, Chichester
Box G.E.P., Cox D.R. (1964) An analysis of transformations. J. R. Stat. Soc. B, 26:211–252
Dixon, S.J., Brereton, R.G., Soini, H.A., Novotny, M.V. and Penn D.J. (2006). An automated method for peak detection and alignment in gas chromatography-mass spectrometry as applied to a large metabolomic dataset from human sweat. J. Chemomet. in press
Gentle J.E. (1998) Numerical Linear Algebra for Applications in Statistics. Springer-Verlag, Berlin
Golub G.H., Loan C.F.V. (1996) Matrix Computations. The Johns Hopkins University Press, London
Gower J.C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis Biometrika 53:325–338
Gower D.B., Bird S., Sharma P., House F.R. (1985) Axillary 5α-androst-16-en-3-one in men and women: Relationships with olfactory activity to odorous 16-androstenes Cell. Mol. Life Sci. 41:1134–1136
Gower J.C., Legendre P. (1986) Metric and Euclidean properties of dissimilarity coefficients, J. Classif. 3, 5–48
Graepel T., Herbrich R., Bollmann-Sdorra P., Obermayer K. (1998) Classification on pairwise proximity data. In: Jordan MI, Kearns MJ, Solla SA (Eds) Proceedings of the 1998 Conference on Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA, pp 438–444
Huber W., von Heydebrek A., Sültmann H., Poustka A., Vingron M. (2002) Variance stabilization applied to microarray data calibration and to the quantification of differential expression, Bioinformatics, 18(suppl. 1):S96–S104
Jaccard, P. (1908). Bull. Soc. Vaud. Sci. Nat. 44, 223–270
Jackson D.A. (1995) Protest: A Procrustean randomization test of community environment concordance. Ecoscience 2:297–303
Krzanowski W.J., Marrior F.H.C. (1994) Multivariate Analysis, Part I. Distributions, Ordination and Inference. Arnold, London
Mantel N.A. (1967) The detection of disease clustering and a generalized regression approach. Can. Res. 27:209–220
Marples M.J. (1969) Life on the human skin. Sci. Am. 220:108–115
Muyzer G., de Waal E.C., Uitterlinden A.G. (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes encoding for 16S rRNA. Appl. Environ. Microbiol. 59:695–700
Muyzer G., Hottenträger S., Teske A., Wawer C. (1995) Denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA: A new molecular approach to analyse the genetic diversity of mixed microbial communities. In: Akkermans A.D., van Elsas J.D., de Bruijin F.J. (Eds) Molecular Microbial Ecology Manual. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 1–23
Pekalska E., Paclik P., Duin R.P.W. (2002) A generalized Kernel approach to dissimilarity-based classification, J. Mach. Learn. Res. 2:175–221
Penn D.J., Oberzaucher E., Grammer K., Fischer G., Soini H.A., Wiesler D., Novotny M.V., Dixon S.J., Xu Y., Brereton R.G. (2007) Individual and gender fingerprints in body odour, J. R. Soc.: Interface, 4:331–340
Peres-Neto P.R., Jackson D.A. (2001) How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test, Oecologia 129:169–178
Rennie P.J., Gower D.B., Holland K.T., Mallet A.I., Watkins W.J. (1990) The skin microflora and the formation of human axillary odour. Int. J. Cosmet. Sci. 12:197–208
Rennie P.J., Gower D.B., Holland K.T. (1991) In-vitro and in-vivo studies of human axillary odour and the cutaneous microflora Br. J. Dermatol. 124:596–602
Rodrìguez-Lázaro D.A., Jofré T., Aymerich M., Hugas M., Pla M. (2004) Rapid quantitative detection of Listeria monocytogenes by Real-Time PCR. Appl. Environ. Microbiol. 70:6299–6301
Rohlf F.J., Slice D.E. (1990) Extensions of the Procrustes method of the optimal superimposition of landmarks. Syst. Zool. 39:40–59
Sanguinetti C.J., Dias Neto E., Simpson A.J.G. (1994) Rapid silver staining and recovery of PCR products separated on polyacrylamide gels, Biotechniques 17:915–919
Sastry S.D., Buck K.T., Janak, J., Dressler M., Preti G. (1980) Volatiles emitted by humans. Waller G.R., Dermer O.C. (Eds) Biochemical Applications of Mass Spectrometry John Wiley & Sons, New York, pp 1085–1129
Sato K., Leidal R., Sato F. (1987) Morphology and development of an apoeccrine sweat gland in human axillae. Am. J. Physiol. Regul. Integr. Comp. Physiol. 252:R166–180
Soini H.A., Bruce K.E., Klouckova I., Brereton R.G., Penn D.J., Novotny M.V. (2006) In-situ surface sampling of biological objects and preconcentration of their volatiles for chromatographic analysis. Anal. Chem. 78:7161–7168
Wold S., Esbensen K., Geladi P. (1987) Principal component analysis, Chemom. Intell. Lab. Syst. 2:37–52
Williamson P., Kligman A.M. (1965) A new method for the quantitative investigation of cutaneous bacteria, J. Invest. Dermatol. 45:498–503
Zwillinger D. (1997) Handbook of Differential Equations, 3rd edition. Academic Press, Boston
Acknowledgements
Alexandra Katzer is thanked for her superb organisational skills. Hejun Duan of the Centre for Chemometrics is thanked for helping organise the GC/MS data, and Fan Gong for preliminary help in the microbial analysis. This work was sponsored by ARO Contract DAAD19-03-1-0215. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xu, Y., Dixon, S.J., Brereton, R.G. et al. 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. Metabolomics 3, 427–437 (2007). https://doi.org/10.1007/s11306-007-0054-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11306-007-0054-6