English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

A high-throughput image correlation method for rapid analysis of fluorophore photoblinking and photobleaching rates

MPS-Authors
/persons/resource/persons302517

Glembockyte,  Viktorija
Chemical Biology, Max Planck Institute for Medical Research, Max Planck Society;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Sehayek, S., Gidi, Y., Glembockyte, V., Brandão, H. B., François, P., Cosa, G., et al. (2019). A high-throughput image correlation method for rapid analysis of fluorophore photoblinking and photobleaching rates. ACS Nano, 13(10), 11955-11966. doi:10.1021/acsnano.9b06033.


Cite as: https://hdl.handle.net/21.11116/0000-000F-F7E8-5
Abstract
Super-resolution fluorescence imaging based on localization microscopy requires tuning the photoblinking properties of fluorescent dyes employed. Missing is a rapid way to analyze the blinking rates of the fluorophore probes. Herein we present an ensemble autocorrelation technique for rapidly and simultaneously measuring photoblinking and bleaching rate constants from a microscopy image time series of fluorescent probes that is significantly faster than individual single-molecule trajectory analysis approaches. Our method is accurate for probe densities typically encountered in single-molecule studies as well as for higher density systems which cannot be analyzed by standard single-molecule techniques. We also show that we can resolve characteristic blinking times that are faster than camera detector exposure times, which cannot be accessed by threshold-based single-molecule approaches due to aliasing. We confirm this through computer simulation and single-molecule imaging data of DNA-Cy5 complexes. Finally, we demonstrate that with sufficient sampling our technique can accurately recover rates from stochastic optical reconstruction microscopy super-resolution data.