High content, quantitative AFM analysis of the scalable biomechanical properties of extracellular vesicles. Issue 12 (17th March 2021) - Gazze, Salvatore Andrea; Thomas, Samantha J.; Garcia-Parra, Jetzabel; James, David W.; Rees, Paul; Marsh-Durban, Victoria; Corteling, Randolph; Gonzalez, Deyarina; Conlan, R. Steven; Francis, Lewis W.
Abstract : This work combines high-content AFM with a data extraction tool for rapid analysis of EVs and other nanoparticles. It is applied here to evaluate the effects of two common processing techniques on the biophysical properties of EVs. Abstract : Extracellular vesicles (EVs) are studied extensively as natural biomolecular shuttles and for their diagnostic and therapeutic potential. This exponential rise in interest has highlighted the need for highly robust and reproducible approaches for EV characterisation. Here we optimise quantitative nanomechanical tools and demonstrate the advantages of EV population screening by atomic force microscopy (AFM). Our high-content informatics analytical tools are made available for use by the EV community for widespread, standardised determination of structural stability. Ultracentrifugation (UC) and sonication, the common mechanical techniques used for EV isolation and loading respectively, are used to demonstrate the utility of optimised PeakForce-Quantitative Nano Mechanics (PF-QNM) analysis. EVs produced at an industrial scale exhibited biochemical and biomechanical alterations after exposure to these common techniques. UC resulted in slight increases in physical dimensions, and decreased EV adhesion concurrent with a decrease in CD63 content. Sonicated EVs exhibited significantly reduced levels of CD81, a decrease in size, increased Young's modulus and decreased adhesive force. These biomechanical and biochemical changes highlight the effect of EV sample preparation techniques on critical properties linked to EV cellular uptake and biological function. PF-QNM offers significant additional information about the structural information of EVs following their purification and downstream processing, and the analytical tools will ensure consistency of analysis of AFM data by the EV community, as this technique continues to become more widely implemented.