Bioanalytical applications of surface-enhanced Raman spectroscopy: de novo molecular identification

Surface-enhanced Raman scattering (SERS) has become a powerful technique for trace analysis of biomolecules. The use of SERS-tags has evolved into clinical diagnostics; the enhancement of the intrinsic signal of biomolecules on SERS active materials shows tremendous promise for the analysis of biomo...

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Bibliographic Details
Published in:Reviews in analytical chemistry 2017-12, Vol.36 (4), p.S435-S450
Main Authors: Nguyen, Anh H., Peters, Emily A., Schultz, Zachary D.
Format: Article
Language:English
Subjects:
Amino acids
Biomedical materials
Biomolecules
Control methods
Metabolites
Nucleic acids
Peptides
Proteins
Quantitative analysis
Raman spectra
Raman spectroscopy
SERS
Spectrum analysis
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Summary:Surface-enhanced Raman scattering (SERS) has become a powerful technique for trace analysis of biomolecules. The use of SERS-tags has evolved into clinical diagnostics; the enhancement of the intrinsic signal of biomolecules on SERS active materials shows tremendous promise for the analysis of biomolecules and potential biomedical assays. The detection of the signal from a wide range of biomolecules has been reported to date. In this review, we examine different classes of biomolecules for the signals observed and experimental details that enable their detection. In particular, we survey nucleic acids, amino acids, peptides, proteins, metabolites, and pathogens. The signals observed show that the interaction of the biomolecule with the enhancing nanostructure has a significant influence on the observed spectrum. Additional experiments demonstrate that internal standards can correct for intensity fluctuations and provide quantitative analysis. Experimental methods that control the interaction at the surface are providing for reproducible SERS signals. Results suggest that combining advances in methodology with the development of libraries for SERS spectra may enable the characterization of biomolecules complementary to other existing methods.
ISSN:0793-0135
2191-0189
DOI:10.1515/revac-2016-0037