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Reproducible surface-enhanced Raman quantification of biomarkers in multicomponent mixtures

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DeLuca_Nano_2014_Pure.pdf (680.0Kb)
Date
25/03/2014
Author
De Luca, Anna Chiara
Reader-Harris, Peter
Mazilu, Michael
Mariggio, Stefania
Corda, Daniela
Di Falco, Andrea
Funder
EPSRC
Grant ID
EP/I004602/1
Keywords
SERS
Biosensor
Glycerophosphoinositol
Nanofabrication
Label-free detection
Tandem mass-spectrometry
Spectroscopy
Scattering
Substrate
Silver
Glycerophosphoinositols
Nanosensors
Spectra
Arrays
QC Physics
QH301 Biology
BDC
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Abstract
Direct and quantitative detection of unlabeled glycerophosphoinositol (GroPIns), an abundant cytosolic phosphoinositide derivative, would allow rapid evaluation of several malignant cell transformations. Here we report label-free analysis of GroPIns via surface-enhanced Raman spectroscopy (SERS) with a sensitivity of 200 nM, well below its apparent concentration in cells. Crucially, our SERS substrates, based on lithographically defined gold nanofeatures, can be used to predict accurately the GroPIns concentration even in multicomponent mixtures, avoiding the preliminary separation of individual compounds. Our results represent a critical step toward the creation of SERS-based biosensor for rapid, label-free, and reproducible detection of specific molecules, overcoming limits of current experimental methods.
Citation
De Luca , A C , Reader-Harris , P , Mazilu , M , Mariggio , S , Corda , D & Di Falco , A 2014 , ' Reproducible surface-enhanced Raman quantification of biomarkers in multicomponent mixtures ' , ACS Nano , vol. 8 , no. 3 , pp. 2575-2583 . https://doi.org/10.1021/nn406200y
Publication
ACS Nano
Status
Peer reviewed
DOI
https://doi.org/10.1021/nn406200y
ISSN
1936-0851
Type
Journal article
Rights
This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Nano, copyright © 2014 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/nn406200y.
Description
A.C.D.L. is supported by an AIRC Start-up Grant 11454 and a FIR project RBFR12WAPY. A.D.F. is supported by an EPSRC Career Acceleration Fellowship (EP/I004602/1). D.C. is supported by an AIRC Grant IG10341 and the projects PON01-00117 and PON01-00862. S.M. is supported by a PRIN project 2012CK5RPF_05.
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/6443

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