Quantifying and optimizing single-molecule switching nanoscopy at high speeds

PLoS One. 2015 May 26;10(5):e0128135. doi: 10.1371/journal.pone.0128135. eCollection 2015.

Abstract

Single-molecule switching nanoscopy overcomes the diffraction limit of light by stochastically switching single fluorescent molecules on and off, and then localizing their positions individually. Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. However, it has not been quantified whether this speed increase comes at the cost of compromised image quality. The spatial and temporal resolution depends on many factors, among which laser intensity and camera speed are the two most critical parameters. Here we quantitatively compare the image quality achieved when imaging Alexa Fluor 647-immunolabeled microtubules over an extended range of laser intensities and camera speeds using three criteria - localization precision, density of localized molecules, and resolution of reconstructed images based on Fourier Ring Correlation. We found that, with optimized parameters, single-molecule switching nanoscopy at high speeds can achieve the same image quality as imaging at conventional speeds in a 5-25 times shorter time period. Furthermore, we measured the photoswitching kinetics of Alexa Fluor 647 from single-molecule experiments, and, based on this kinetic data, we developed algorithms to simulate single-molecule switching nanoscopy images. We used this software tool to demonstrate how laser intensity and camera speed affect the density of active fluorophores and influence the achievable resolution. Our study provides guidelines for choosing appropriate laser intensities for imaging Alexa Fluor 647 at different speeds and a quantification protocol for future evaluations of other probes and imaging parameters.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • COS Cells
  • Chlorocebus aethiops
  • Image Processing, Computer-Assisted / methods*
  • Microscopy, Fluorescence
  • Microscopy, Video
  • Microtubules / ultrastructure
  • Nanotechnology / methods*
  • Software