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Multiplex surface-enhanced Raman scattering detection of deoxynivalenol and ochratoxin A with a linear polymer affinity agent

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Abstract

A linear, methacrylamide polymer affinity agent was explored to capture two mycotoxins, deoxynivalenol (DON) and ochratoxin A (OTA), for multiplex surface-enhanced Raman scattering (SERS) detection. These mycotoxins are naturally occurring small molecules from fungi that can be dangerous at low concentrations. SERS detection was completed for each polymer-toxin complex at concentrations relevant to current safety regulation by the FDA: 1 ppm for DON and 5 ppb for OTA. Visibly distinguishable vibrational modes were observed in the multiplex spectra that were attributed to each mycotoxin individually, thus, not requiring any additional chemometric analysis. Density functional theory (DFT) was used to model DON and OTA to accurately label the vibrational modes in the experimental spectra as well as provide insight on the binding between both targets and the affinity agent. Fully modeled vibrations of these toxins are novel contributions due to OTA never being modeled and there being only a few published vibrational modes of DON. DFT guides empirical observations regarding hydrogen bonding at multiple sites of each mycotoxin target molecule through the amine groups on the polymer, confirming the capabilities of a single polymer affinity agent to facilitate multiplex detection of a class of molecules through less-specific interactions than traditional affinity agents.

Graphical abstract: Multiplex surface-enhanced Raman scattering detection of deoxynivalenol and ochratoxin A with a linear polymer affinity agent

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Article information


Submitted
15 Aug 2020
Accepted
25 Oct 2020
First published
26 Oct 2020

This article is Open Access

Mater. Adv., 2020, Advance Article
Article type
Paper

Multiplex surface-enhanced Raman scattering detection of deoxynivalenol and ochratoxin A with a linear polymer affinity agent

R. S. Rodriguez, V. M. Szlag, T. M. Reineke and C. L. Haynes, Mater. Adv., 2020, Advance Article , DOI: 10.1039/D0MA00608D

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