4.7 Article

ssDNA-C3N4 conjugates-based nanozyme sensor array for discriminating mycotoxins

Journal

MICROCHIMICA ACTA
Volume 190, Issue 1, Pages -

Publisher

SPRINGER WIEN
DOI: 10.1007/s00604-022-05593-y

Keywords

Sensor array; Mycotoxins; Principal component analysis; Food safety

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In this study, a nanozyme sensor array based on the ssDNA-distensible C3N4 nanosheet sensor elements was developed for discriminating multiple mycotoxins commonly existing in contaminated cereals. The sensor array was capable of separating five mycotoxins from each other with 100% accuracy at concentrations as low as 1 nM, and it performed well in discriminating mycotoxin mixtures with different ratios. The practicality of this sensor array was demonstrated, validating its potential as a flexible detection tool for food safety.
A nanozyme sensor array based on the ssDNA-distensible C3N4 nanosheet sensor elements for discriminating multiple mycotoxins commonly existing in contaminated cereals has been explored. The sensor array exploited (a) three DNA nonspecific sequences (A40, T40, C40) absorbed on the C3N4 nanosheets as sensor elements catalyzing the oxidation of TMB; (b) the presence of five mycotoxins affected the catalytic activity of three nanozymes with various degrees. The parameter (A(0)-A) was employed as the signal output to obtain the response patterns for different mycotoxins with the same concentration where A(0) and A were the absorption peak values at 650 nm of oxTMB in the absence and presence of target mycotoxins, respectively. After the raw data was subjected to principal component analysis, 3D canonical score plots were obtained. The sensor array was capable of separating five mycotoxins from each other with 100% accuracy even if the concentration of the mycotoxins was as low as 1 nM. Moreover, the array performed well in discriminating the mycotoxin mixtures with different ratios. Importantly, the practicality of this sensor array was demonstrated by discriminating the five mycotoxins spiking in corn-free samples in 3D canonical score plots, validating that the sensor array can act as a flexible detection tool for food safety.

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