Optimising SERS for the simultaneous multiplex detection and quantification of thiols associated to axillary malodour

SERS has been developed and independently tested for the quantitative detection of multiple malodorous thiols.


Abstract Text:

Axillary malodour results from microbial conversion of human secretions into volatile organic compounds, particularly thiols, which are key contributors but difficult to detect due to their low concentrations and volatility.  In this presentation we will show how we have developed and applied surface-enhanced Raman scattering (SERS) with chemometrics to quantify four thiols linked to body odour, both individually and in quadruplex mixtures. Univariate and multivariate partial least squares regression (PLSR) methods were used to determine detection limits, yielding similar results, with LoDs between 0.0153 and 0.0227 ppm.  PLSR was further used to quantify thiols in 120 mixtures, showing strong linearity (Q²: 0.9712-0.9827) and low prediction errors (0.0359-0.0459 ppm).  The models were also successfully tested on 15 blind samples, accurately predicting thiol concentrations.  These findings demonstrate that SERS when combined with PLSR is effective for multiplex thiol detection and quantification, suggesting potential for future applications in detecting volatile thiols from skin and other body areas.

Colleran, A. et al. (2024) Using surface-enhanced Raman scattering for simultaneous multiplex detection and quantification of thiols associated to axillary malodour.  Analyst 149, 3989-4001.  https://doi.org/10.1039/D4AN00762J