Monitoring Populations of Single Extracellular Vesicles from Pseudomonas aeruginosa Using Large Parallel Arrays of Zero-Mode Waveguides

Extracellular vesicles (EV) have emerged as key factors for intercellular communication, disease biomarkers, and vaccines, but EV populations generally exhibit broad heterogeneity, making single-vesicle measurements critical in order to understand the roles played by EVs and the pathways they utilize. To circumvent the exhaustive isolation and concentration protocols and/or long incubation periods required by common single-vesicle characterization methods, we have developed a method for the in situ study of single EVs from crude Pseudomonas aeruginosa culture in real-time with minimal sample preparation using nanopore-based zero-mode waveguides (ZMW). The dimensions of the ZMW allow only a single EV to occupy the nanopore volume, making it possible to monitor large arrays of single EVs one-at-a-time in parallel. Furthermore, the attoliter-volume ZMW nanopores restrict the much larger P. aeruginosa cells from entering the observation volume, eliminating the need to isolate EVs from their parent cells. Lipophilic fluorophores are used to selectively tag the EV membrane, thereby restricting optical observations to single EVs captured one-at-a-time in individual ZMW nanopores. By fashioning the ZMWs into 21 × 21 arrays, 441 individual observation volumes can be observed in parallel, revealing the heterogeneity of single EV responses, which is usually masked by ensemble averaging when examining hundreds of events at once without spatial segregation. The minimal sample preparation and ability to monitor the sample in situ enables real-time analysis of changes in the bacterial culture environment, since detection of EVs is governed solely by diffusion of the particle into the ZMW optical volume. The work described here presents an approach for studying EV heterogeneity in crude bacterial culture and makes it possible to observe shifts in the vesicle population in response to culture perturbations in real-time.