Single-Cell Analysis and Classification according to Multiplexed Proteins via Microdroplet-Based Self-Driven Magnetic Surface-Enhanced Raman Spectroscopy Platforms Assisted with Machine Learning Algorithms

A microdroplet-based surface-enhanced Raman spectroscopy(microdropletSERS) platform was constructed to envelop individual cells in microdroplets,followed by the SERS detection of their extracellular vesicle-proteins(EV-proteins) via the in-drop immunoassays by use of immunomagneticbeads (iMBs) and immuno-SERS tags (iSERS tags). A unique phenomenon is found that iMBscan start a spontaneous reorientation on the probed cell surface basedon the electrostatic force-driven interfacial aggregation effect,which leads EV-proteins and iSERS tags to be gatheredfrom a liquid phase to a cell membrane interface and significantlyimproves SERS sensitivity to the single-cell analysis level due tothe formation of numbers of SERS hotspots. Three EV-proteins fromtwo breast cancer cell lines were collected and further analyzed bymachine learning algorithmic tools, which will be helpful for a deeperunderstanding of breast cancer subtypes from the view of EV-proteins.