Lorenzo Albertazzi; P. (Pietro) Delcanale (2020): DNA-PAINT super-resolution imaging data of surface exposed active sites on particles - Revised. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:50bd0ad4-52d8-4138-8eb1-40b4d7fc2286

Dataset

x choose version: version 1 - 2020-02-05

• Optical Physics

DNA-PAINT, Microscopy, Nanoscale, super-resolution microscopy

CC BY-NC 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Lorenzo Albertazzi , P. (Pietro) Delcanale

Surface functionalization with targeting ligands confers to nanomaterials the ability of selectively recognize a biological target. Therefore, a quantitative characterization of surface functional molecules is critical for the rational development of nanomaterials-based applications, especially in nanomedicine research. Single-molecule localization microscopy can provide visualization of surface molecules at the level of individual particles, preserving the integrity of the material and overcoming the limitations of analytical methods based on ensemble averaging. Here we provide single-molecule localization data obtained on streptavidin-coated polystyrene particles, which can be exploited as a model system for surface-functionalized materials. After loading of the active sites of streptavidin molecules with a biotin-conjugated probe, they were imaged with a DNA-PAINT imaging approach, which can provide single-molecule imaging at subdiffraction resolution and molecule counting. Both raw records and analysed data, consisting in a list of space-time single-molecule coordinates, are shared. Additionally, Matlab functions are provided that analyse the single-molecule coordinates in order to quantify features of individual particles. These data might constitute a valuable reference for applications of similar quantitative imaging methodologies to other types of functionalized nanomaterials.

• 2020-03-16 first online, published, posted

4TU.Centre for Research Data

media types: application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/zip, image/tiff, text/plain, text/x-matlab

• https://doi.org/10.1016/j.dib.2020.105468

TU Eindhoven, department of Biomedical Engineering