Prospective Use of High-Refractive Index Materials for Single Molecule Detection in Flow Cytometry.

Phenotyping extracellular vesicles (EVs), where surface receptor expression is often as low as one molecule per EV, remains problematic due to the inability of commercial flow cytometers to provide single-fluorescent molecule sensitivity. While EVs are widely considered to be of great potential as diagnostic, prognostic and theranostic biomarkers, their use is currently hindered by the lack of tools available to accurately and reproducibly enumerate and phenotype them. Herein, we propose a new class of labels that leverage the biophysical properties of materials with unique complex refractive indices and demonstrate that this class of labels has the possibility of allowing single-epitope detection using conventional flow cytometry.

High-fidelity detection and sorting of nanoscale vesicles in viral disease and cancer.

Biological nanoparticles, including viruses and extracellular vesicles (EVs), are of interest to many fields of medicine as biomarkers and mediators of or treatments for disease. However, exosomes and small viruses fall below the detection limits of conventional flow cytometers due to the overlap of particle-associated scattered light signals with the detection of background instrument noise from diffusely scattered light. To identify, sort, and study distinct subsets of EVs and other nanoparticles, as individual particles, we developed nanoscale Fluorescence Analysis and Cytometric Sorting (nanoFACS) methods to maximise information and material that can be obtained with high speed, high resolution flow cytometers. This nanoFACS method requires analysis of the instrument background noise (herein defined as the "reference noise"). With these methods, we demonstrate detection of tumour cell-derived EVs with specific tumour antigens using both fluorescence and scattered light parameters. We further validated the performance of nanoFACS by sorting two distinct HIV strains to >95% purity and confirmed the viability (infectivity) and molecular specificity (specific cell tropism) of biological nanomaterials sorted with nanoFACS. This nanoFACS method provides a unique way to analyse and sort functional EV- and viral-subsets with preservation of vesicular structure, surface protein specificity and RNA cargo activity.