Laser trapping Raman spectroscopy (LTRS) of clinical extracellular vesicles (EVs): accounting for heterogeneity at single particle resolution

Extracellular vesicles (EVs) are membrane-bound nano-assemblies shed from all cells and reflect cellular state, giving them incredible clinical biomarker potential for monitoring disease progression or a patient’s response to certain drugs. EVs also have unique qualities that are of interest for drug delivery application due to their ability to cross the blood-brain barrier, as well as target specific organs and tumor sites. The specific mechanisms and interactions that allow EVs such abilities are ever-elusive, in large part due to complexity arising from their inherent heterogeneity. EVs come in many different shapes, sizes, and molecular compositions, even leading to controversy about how exactly EVs are defined. In addition, studies often examine EVs in bulk, which does not account for EV heterogeneity at single vesicle resolution. Not accounting for EV heterogeneity results in an underrepresentation of EV subpopulations. In the case of recent work to apply EVs as next-generation drug delivery vehicles, this leads to a danger of drug off-targeting. Thus, it is imperative to capture native EV heterogeneity by single-particle analysis to maximize EVs’ clinical potential. Current single-particle detection techniques, including nanoparticle tracking analysis (NTA), flow cytometry, and enzyme-linked immunosorbent assay (ELISA), which are typically used for EV characterization, lack sufficient sensitivity and are diffraction-limited. Hence, current single-particle detection techniques do not completely or accurately characterize EV populations. Here, an optimized single-molecule detection technique, laser trapping Raman spectroscopy (LTRS) that combines optical tweezers and Raman spectroscopy, is introduced and evaluated by its capacity to better capture native EV heterogeneity. I apply LTRS in two major test cases, to distinguish EVs from structurally similarly composed contaminating lipoprotein complexes and to characterize loaded EVs with relevance to drug delivery