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High-precision estimation of emitter positions using Bayesian grouping of localizations

Author

Listed:
  • Mohamadreza Fazel

    (University of New Mexico)

  • Michael J. Wester

    (University of New Mexico
    University of New Mexico)

  • David J. Schodt

    (University of New Mexico)

  • Sebastian Restrepo Cruz

    (University of New Mexico Health Science Center)

  • Sebastian Strauss

    (Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Florian Schueder

    (Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Thomas Schlichthaerle

    (Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Jennifer M. Gillette

    (University of New Mexico Health Science Center
    University of New Mexico)

  • Diane S. Lidke

    (University of New Mexico Health Science Center
    University of New Mexico)

  • Bernd Rieger

    (Delft University of Technology)

  • Ralf Jungmann

    (Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Keith A. Lidke

    (University of New Mexico
    University of New Mexico)

Abstract

Single-molecule localization microscopy super-resolution methods rely on stochastic blinking/binding events, which often occur multiple times from each emitter over the course of data acquisition. Typically, the blinking/binding events from each emitter are treated as independent events, without an attempt to assign them to a particular emitter. Here, we describe a Bayesian method of inferring the positions of the tagged molecules by exploring the possible grouping and combination of localizations from multiple blinking/binding events. The results are position estimates of the tagged molecules that have improved localization precision and facilitate nanoscale structural insights. The Bayesian framework uses the localization precisions to learn the statistical distribution of the number of blinking/binding events per emitter and infer the number and position of emitters. We demonstrate the method on a range of synthetic data with various emitter densities, DNA origami constructs and biological structures using DNA-PAINT and dSTORM data. We show that under some experimental conditions it is possible to achieve sub-nanometer precision.

Suggested Citation

  • Mohamadreza Fazel & Michael J. Wester & David J. Schodt & Sebastian Restrepo Cruz & Sebastian Strauss & Florian Schueder & Thomas Schlichthaerle & Jennifer M. Gillette & Diane S. Lidke & Bernd Rieger , 2022. "High-precision estimation of emitter positions using Bayesian grouping of localizations," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34894-2
    DOI: 10.1038/s41467-022-34894-2
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    References listed on IDEAS

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    1. Lisa S. Fischer & Christoph Klingner & Thomas Schlichthaerle & Maximilian T. Strauss & Ralph Böttcher & Reinhard Fässler & Ralf Jungmann & Carsten Grashoff, 2021. "Quantitative single-protein imaging reveals molecular complex formation of integrin, talin, and kindlin during cell adhesion," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
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