Stochastic approach to the molecular counting problem in superresolution microscopy

Geoffrey C. Rollins, Jae Yen Shin, Carlos Bustamante, Steve Pressé

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


Superresolution imaging methods-now widely used to characterize biological structures below the diffraction limit-are poised to reveal in quantitative detail the stoichiometry of protein complexes in living cells. In practice, the photophysical properties of the fluorophores used as tags in superresolution methods have posed a severe theoretical challenge toward achieving this goal. Here we develop a stochastic approach to enumerate fluorophores in a diffraction-limited area measured by superresolution microscopy. The method is a generalization of aggregated Markov methods developed in the ion channel literature for studying gating dynamics. We show that the method accurately and precisely enumerates fluorophores in simulated data while simultaneously determining the kinetic rates that govern the stochastic photophysics of the fluorophores to improve the prediction's accuracy. This stochastic method overcomes several critical limitations of temporal thresholding methods.

Original languageEnglish (US)
Pages (from-to)E110-E118
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number2
StatePublished - Jan 13 2015
Externally publishedYes


  • Counting problem
  • Fluorescence
  • Protein complexes
  • Single molecule
  • Superresolution

ASJC Scopus subject areas

  • General


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