Characterization of Plasma Membrane Ceramides by Super‐Resolution Microscopy

Parameter-free molecular super-structures quantification in single-molecule localization microscopy

Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information is only useful if these patterns can be quantified and interpreted. We provide a new approach for the analysis of SMLM data that develops the concept of structures and super-structures formed by interconnected elements, such as smaller protein clusters. Using a formal framework and a parameter-free algorithm, (super-)structures formed from smaller components are found to be abundant in classes of nuclear proteins, such as heterogeneous nuclear ribonucleoprotein particles (hnRNPs), but are absent from ceramides located in the plasma membrane. We suggest that mesoscopic structures formed by interconnected protein clusters are common within the nucleus and have an important role in the organization and function of the genome. Our algorithm, SuperStructure, can be used to analyze and explore complex SMLM data and extract functionally relevant information.

Switchable Solvatochromic Probes for Live-Cell Super-resolution Imaging of Plasma Membrane Organization

Visualization of the nanoscale organization of cell membranes remains challenging because of the lack of appropriate fluorescent probes. Herein, we introduce a new design concept for super-resolution microscopy probes that combines specific membrane targeting, on/off switching, and environment sensing functions. A functionalization strategy for solvatochromic dye Nile Red that improves its photostability is presented. The dye is grafted to a newly developed membrane-targeting moiety composed of a sulfonate group and an alkyl chain of varied lengths. While the long-chain probe with strong membrane binding, NR12A, is suitable for conventional microscopy, the short-chain probe NR4A, owing to the reversible binding, enables first nanoscale cartography of the lipid order exclusively at the surface of live cells. The latter probe reveals the presence of nanoscopic protrusions and invaginations of lower lipid order in plasma membranes, suggesting a subtle connection between membrane morphology and lipid organization.

Super-resolution Imaging of Structure, Molecular Composition, and Stability of Single Oligonucleotide Polyplexes

The successful application of gene therapy relies on the development of safe and efficient delivery vectors. Cationic polymers such as cell-penetrating peptides (CPPs) can condense genetic material into nanoscale particles, called polyplexes, and induce cellular uptake. With respect to this point, several aspects of the nanoscale structure of polyplexes have remained elusive because of the difficulty in visualizing the molecular arrangement of the two components with nanometer resolution. This limitation has hampered the rational design of polyplexes based on direct structural information. Here, we used super-resolution imaging to study the structure and molecular composition of individual CPP-mRNA polyplexes with nanometer accuracy. We use two-color direct stochastic optical reconstruction microscopy (dSTORM) to unveil the impact of peptide stoichiometry on polyplex structure and composition and to assess their destabilization in blood serum. Our method provides information about the size and composition of individual polyplexes, allowing the study of such properties on a single polyplex basis. Furthermore, the differences in stoichiometry readily explain the differences in cellular uptake behavior. Thus, quantitative dSTORM of polyplexes is complementary to the currently used characterization techniques for understanding the determinants of polyplex activity in vitro and inside cells.

The Rényi divergence enables accurate and precise cluster analysis for localization microscopy

Motivation

Clustering analysis is a key technique for quantitatively characterizing structures in localization microscopy images. To build up accurate information about biological structures, it is critical that the quantification is both accurate (close to the ground truth) and precise (has small scatter and is reproducible).

Results

Here, we describe how the Rényi divergence can be used for cluster radius measurements in localization microscopy data. We demonstrate that the Rényi divergence can operate with high levels of background and provides results which are more accurate than Ripley’s functions, Voronoi tesselation or DBSCAN.

Availability and implementation

The data supporting this research and the software described are accessible at the following site: https://dx.doi.org/10.18742/RDM01-316. Correspondence and requests for materials should be addressed to the corresponding author.

Supplementary information

Supplementary data are available at Bioinformatics online.