Glioblastoma-derived extracellular vesicle subpopulations following 5-aminolevulinic acid treatment bear diagnostic implications.

Liquid biopsy is a minimally invasive alternative to surgical biopsy, encompassing different analytes including extracellular vesicles (EVs), circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), proteins, and metabolites. EVs are released by virtually all cells, but at a higher rate by faster cycling, malignant cells. They encapsulate cargo native to the originating cell and can thus provide a window into the tumour landscape. EVs are often analysed in bulk which hinders the analysis of rare, tumour-specific EV subpopulations from the large host EV background. Here, we fractionated EV subpopulations in vitro and in vivo and characterized their phenotype and generic cargo. We used 5-aminolevulinic acid (5-ALA) to induce release of endogenously fluorescent tumour-specific EVs (EVPpIX ). Analysis of five different subpopulations (EVPpIX , EVCD63 , EVCD9 , EVEGFR , EVCFDA ) from glioblastoma (GBM) cell lines revealed unique transcriptome profiles, with the EVPpIX transcriptome demonstrating closer alignment to tumorigenic processes over the other subpopulations. Similarly, isolation of tumour-specific EVs from GBM patient plasma showed enrichment in GBM-associated genes, when compared to bulk EVs from plasma. We propose that fractionation of EV populations facilitates detection and isolation of tumour-specific EVs for disease monitoring.

Detection and Sorting of Extracellular Vesicles and Viruses Using nanoFACS.

Extracellular vesicles (EVs) are sub-micron-sized membranous spheres secreted by cells. EVs play a functional role as intercellular communicators and are associated with a number of diseases. Research into EVs is an area of growing interest due their many potential uses as therapeutic agents, as diagnostic and theranostic biomarkers, and as regulators of cellular biology. Flow cytometry is a popular method for enumerating and phenotyping EVs, even though the majority of EVs are below the detection sensitivity of most commercially available flow cytometers. Here, we present optimized protocols for EV labeling that increase the signal-to-noise ratio of EVs by removing residual antibody. Protocols for alignment of high-resolution jet-in-air flow cytometers are also provided. Published 2020. U.S. Government. Basic Protocol 1: Bulk EV staining with CFSE protein binding dye Basic Protocol 2: Antigen-specific staining of EV markers with fluorochrome-conjugated antibodies Basic Protocol 3: Astrios EQ instrument setup and sample acquisition Basic Protocol 4: Counting particles and EVs on Astrios EQ with spike-in reference beads.

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.