Combining nanoflares biosensor and mathematical resolution technique for multi-class mycotoxin analysis in complex...

Area of Science:

• Nanotechnology
• Biosensing
• Food Safety

Background:

• Mycotoxin contamination in food poses significant health risks.
• Current detection methods can be time-consuming and lack multiplexing capabilities.

Purpose of the Study:

• To develop an ultra-sensitive, multi-target biosensor for mycotoxin analysis in food.
• To utilize gold nanoparticles and oligonucleotide nanoflares for enhanced detection.

Main Methods:

• Fabrication of a spherical gold nanoparticle (Au NP) biosensor modified with fluorophore-labeled oligonucleotides (ONS).
• Design of multiplexed ONS hairpin structures for specific mycotoxin binding and fluorescence recovery.
• Application of Excitation-Emission Matrix (EEM) fluorescence detection and alternative trilinear decomposition (ATLD) for spectral resolution.

Main Results:

• Simultaneous quantification of four mycotoxins (Aflatoxin B1, zearalenone, Fumonisins B1, ochratoxin A) at very low levels (<0.02 μg kg⁻¹).
• Achieved average recovery accuracies exceeding 91.7% across diverse food matrices.
• Demonstrated effective resolution of overlapping spectra using the ATLD algorithm.

Conclusions:

• The developed nanoflare biosensor represents a breakthrough for sensitive, simultaneous mycotoxin detection.
• This technology shows potential as an alternative strategy for on-site mycotoxin monitoring in food safety applications.