Super-Resolution Imaging of Self-Assembled Nanocarriers Using Quantitative Spectroscopic Analysis for Cluster Extraction

Self-assembled nanocarriers have inspired a range of applications for bioimaging, diagnostics, and drug delivery. The noninvasive visualization and characterization of these nanocarriers are important to understand their structure to function relationship. However, the quantitative visualization of nanocarriers in the sample's native environment remains challenging with the use of existing technologies. Single-molecule localization microscopy (SMLM) has the potential to provide both high-resolution visualization and quantitative analysis of nanocarriers in their native environment. However, nonspecific binding of fluorescent probes used in SMLM can introduce artifacts, which imposes challenges in the quantitative analysis of SMLM images. We showed the feasibility of using spectroscopic point accumulation for imaging in nanoscale topography (sPAINT) to visualize self-assembled polymersomes (PS) with molecular specificity. Furthermore, we analyzed the unique spectral signatures of Nile Red (NR) molecules bound to the PS to reject artifacts from nonspecific NR bindings. We further developed quantitative spectroscopic analysis for cluster extraction (qSPACE) to increase the localization density by 4-fold compared to sPAINT; thus, reducing variations in PS size measurements to less than 5%. Finally, using qSPACE, we quantitatively imaged PS at various concentrations in aqueous solutions with ∼20 nm localization precision and 97% reduction in sample misidentification relative to conventional SMLM.