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Estimating the dynamic range of quantitative single-molecule localization microscopy.

Daniel F Nino1, Joshua N Milstein1

  • 1Department of Physics, University of Toronto, Toronto, Ontario, Canada; Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario, Canada.

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|August 26, 2021
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Summary

Single-molecule localization microscopy (SMLM) advances molecule counting but struggles with high fluorophore density. This study defines SMLM dynamic range, exploring factors like blinking and photobleaching to improve accuracy in molecular counting experiments.

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Area of Science:

  • Biophysics
  • Microscopy
  • Molecular Biology

Background:

  • Single-molecule localization microscopy (SMLM) enables precise quantification of molecule copy number and protein stoichiometry.
  • Increasing fluorophore density in SMLM complicates distinguishing individual detection events, impacting measurement accuracy.

Purpose of the Study:

  • To define and investigate the dynamic range of SMLM counting techniques.
  • To identify photophysical and experimental parameters influencing SMLM dynamic range.

Main Methods:

  • Developed a two-state blinking fluorophore model, extended to include photobleaching and camera temporal binning.
  • Validated theoretical models using realistic photoswitching simulations and direct stochastic optical reconstruction microscopy (dSTORM) data.

Main Results:

  • Provided a working definition of dynamic range for quantitative SMLM based on missed localizations or blinks.
  • Demonstrated that dynamic range is inversely proportional to the duty cycle when counting both blinks and localizations.
  • Confirmed theoretical estimates align with simulation and experimental data.

Conclusions:

  • The study provides a theoretical framework and practical insights into the dynamic range of SMLM.
  • Understanding these parameters is crucial for optimizing SMLM experimental design for accurate molecular counting.
  • Results guide researchers in improving the reliability of SMLM-based quantitative experiments.