A High-Throughput Image Correlation Method for Rapid Analysis of Fluorophore Photoblinking and Photobleaching Rates.
Simon SehayekYasser GidiViktorija GlembockyteHugo B BrandãoPaul FrançoisGonzalo CosaPaul W WisemanPublished in: ACS nano (2019)
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.
Keyphrases
- single molecule
- living cells
- fluorescence imaging
- atomic force microscopy
- high resolution
- high throughput
- deep learning
- fluorescent probe
- quantum dots
- photodynamic therapy
- high speed
- hydrogen peroxide
- big data
- convolutional neural network
- small molecule
- machine learning
- computed tomography
- data analysis
- artificial intelligence
- nitric oxide
- magnetic resonance
- sensitive detection
- single cell
- circulating tumor cells
- case control