High-throughput multiplex analysis method based on Fluorescence-SERS quantum Dot-Embedded silver bumpy nanoprobes

Biological encoding, multiplex biomarker imaging, and immunoassays require a multiplex spectroscopic detection and analysis technique that uses surface-enhanced Raman scattering (SERS)-based dual-modal nanoprobes. In the present study, dual-modal fluorescence-SERS quantum dot (QD)-embedded silver bumpy nanoparticles are developed for high-throughput multiplex analysis. Forty-five different dual-modal (FRGBRSERS) nanoprobes are prepared from silica-coated silver bumpy nanoshells (AgNS@SiO2) with 15 different types of Raman label compounds and 3 types of QDs (red, green, and blue). Each FRRSERS nanoprobe produces strong SERS and fluorescence signals for multiplex analysis. Based on this dual-modality, a barcode-based machine learning algorithm that transforms spectra into barcodes and identifies chemical information is created. As a proof-ofconcept experiment, single- and triplex-label spectra are identified from a library comprising 15 types of Raman labels. The multiplex detection platform comprising the FRRSERS nanoprobes and the high-throughput analysis algorithm will be extremely useful for analyzing and encoding biological targets.