Thesis Defence: Extracellular Vesicles INFOCUS

Shilong Pan, supervised by Dr. Isaac Li, will defend their thesis titled “Extracellular Vesicles INFOCUS: A Novel Technique for Biological Nanoparticle Size Analysis” in partial fulfillment of the requirements for the degree of Master of Science in Chemistry.

An abstract for Shilong Pan’s thesis is included below.

Defences are open to all members of the campus community as well as the general public. Registration is not required for in-person defences.

Abstract

Small extracellular vesicles (EVs) such as exosomes are physiologically and pathophysiologically relevant biological nanoparticles derived from cells. Their diverse roles in homeostasis and pathology could allow for the sensitive diagnosis or monitoring of various conditions such as cancers, infections, and genetic diseases. However, due to their complex structures, lack of specific markers, broad population heterogeneity, similarity to other functional particles, and often sub-diffraction limit size, the tools and methods used to study EVs are often compromised in their utility or reliability. Further advancement in EV diagnostic medicine will require the development of new techniques that can quickly and reliably produce accurate information about different types of EVs.

The author proposes the Inferred Focal Centers of Uniform Spheres (INFOCUS) method as a solution to address the many demands required by the EV field. This method takes advantage of the properties of small EVs: sub-diffraction-limit diameters, lipid membranes, and high sphericality due to membrane tension, to measure particle sizes with high accuracy and throughput, while also allowing for parallel functional analyses of EV markers.

Using a set of polystyrene nanoparticles, the INFOCUS method is demonstrated in its entirety from sample preparation to analysis and output. Various considerations are examined and corrected as necessary. Instrument parameters and sample preparation are optimized for higher quality data, while a complex set of optical and spectral variables are compensated through experimental design and calculation.

INFOCUS is then validated against tunable resistive-pulse sensing (TRPS), a competitive commercial EV-size analysis solution. The INFOCUS method was found to have superior accuracy but worse precision, with less than 10 nm deviation from expected mean values of particles from 40 to 170 nm and approximately double the expected distribution sizes, demonstrating the power and potential of the method. However, testing on real EV samples demonstrates that further challenges related to EV labelling must be solved to make it fully applicable to the EV field.