Abstract

Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components’ unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices.

Label-free surface-enhanced Raman spectroscopy is an emergent method for the detection and discrimination of biological analytes. Here, the authors describe SERS sensors with arrayed mildly-selective surface chemistries to give a fingerprint based on different interactions for analysing biological samples.

Details

Title
Surface enhanced Raman scattering artificial nose for high dimensionality fingerprinting
Author
Kim, Nayoung 1   VIAFID ORCID Logo  ; Thomas, Michael R 1 ; Bergholt, Mads S 1 ; Pence, Isaac J 1   VIAFID ORCID Logo  ; Hyejeong, Seong 1   VIAFID ORCID Logo  ; Charchar, Patrick 2   VIAFID ORCID Logo  ; Todorova Nevena 2   VIAFID ORCID Logo  ; Nagelkerke Anika 1 ; Belessiotis-Richards Alexis 1   VIAFID ORCID Logo  ; Payne, David J 3   VIAFID ORCID Logo  ; Gelmi, Amy 1 ; Yarovsky Irene 2   VIAFID ORCID Logo  ; Stevens, Molly M 1   VIAFID ORCID Logo 

 Department of Materials, Department of Bioengineering and Institute of Biomedical Engineering, Imperial College London, London, UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111) 
 School of Engineering, RMIT University, Melbourne, Victoria, Australia (GRID:grid.1017.7) (ISNI:0000 0001 2163 3550) 
 Department of Materials, Imperial College London, London, UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2343026518
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.