Vertical flow immunoassay for multiplex mycotoxins based on photonic nitrocellulose and SERS nanotags
Here, we report a SERS based VFA using PNC as a sensing substrate for highly sensitive multiplex mycotoxins detection. The PNC was fabricated by filtration-based self-assembled monodisperse SiO<sub>2</sub> NPs on a filter membrane as a template, and the obtained PNC had an ordered complementary inverse opal structure. In parallel, three kinds of Raman dyes encoding Au@<sup>NBA</sup>Ag, Au@<sup>4-MBA</sup>Ag and Au@<sup>DNTB</sup>Ag SERS nanotags were synthesized for the detection of OTA, AFB1 and ZON. In the immunoassay, because of the slow-photon effect of the PNC substrate, which facilitates the light coupling with SERS nanotags, the SERS signal was highly enhanced. The LODs of 8.2, 13.7 and 47.6 fg mL<sup>-1</sup> were achieved for simultaneous detection of OTA, AFB1 and ZON, respectively, which were lower than the tolerable cutoff values recommended by the EC. Therefore, this proposed PNC based SERS VFA is expected to be a powerful method for multiplex mycotoxins detection.
Authors
- Liang Yang (ORCID: https://orcid.org/0000-0003-3382-819X)
- Ruipeng Chen (ORCID: https://orcid.org/0000-0003-2489-9922)
- Xiangwei Zhao (ORCID: https://orcid.org/0000-0003-0678-5219)
- Yuxuan Chen (ORCID: https://orcid.org/0000-0003-2327-2511)
- Cheng Li (ORCID: https://orcid.org/0000-0003-0675-0390)
- Hui Wang (ORCID: https://orcid.org/0000-0003-2633-6015)
- Haiqi Kang
- Benhai Xiong
- Jingfang Hu (ORCID: https://orcid.org/0009-0001-2514-1200)
- Xiangfang Tang (ORCID: https://orcid.org/0000-0002-1622-5891)
Institutions
- Institute of Food Science and Technology (CN)
- Beijing University of Agriculture (CN)
- Chinese Academy of Agricultural Sciences (CN)
- State Key Laboratory of Digital Medical Engineering (CN)
- Southeast University (CN)
- Beijing Information Science & Technology University (CN)
Publication Details
- Journal
- Food Chemistry X
- Published
- 2024-12-31
- DOI
- https://doi.org/10.1016/j.fochx.2024.102152
- Citations
- 5
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.92