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BNP-Track: a framework for superresolved tracking.

Ioannis Sgouralis1, Lance W Q Xu2,3, Ameya P Jalihal4

  • 1Department of Mathematics, University of Tennessee, Knoxville, TN, USA.

Nature Methods
|July 22, 2024
PubMed
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This summary is machine-generated.

We developed Bayesian nonparametric track (BNP-Track), a new superresolution method for dynamic biological samples. BNP-Track accurately tracks molecules in crowded environments without relying on photodynamics.

Area of Science:

  • Biophysics
  • Microscopy
  • Cell Biology

Background:

  • Superresolution microscopy techniques like PALM and STORM offer nanoscale precision but are limited to static samples due to their reliance on specific photophysical events.
  • Existing single-particle tracking methods struggle with accuracy in dense biological environments.

Purpose of the Study:

  • To extend superresolution microscopy to dynamic biological samples.
  • To develop a framework capable of simultaneously determining emitter numbers and their tracks with high localization accuracy per frame.
  • To overcome limitations of current methods in crowded cellular environments.

Main Methods:

  • Introduced the Bayesian nonparametric track (BNP-Track) framework.
  • Developed a joint posterior distribution to quantify uncertainty in emitter number and track estimation.

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  • Integrated spatiotemporal information to improve accuracy in dynamic and crowded conditions.
  • Validated the framework using both in cellulo and synthetic data.

    • Main Results:

    • BNP-Track achieves localization accuracy comparable to widefield superresolution on immobilized emitters (≈50 nm).
    • The framework quantifies uncertainties arising from noise, artifacts, and motion.
    • Demonstrated accurate tracking in crowding regimens exceeding the capabilities of other single-particle tracking tools.
    • Successfully applied to both cellular and synthetic datasets.

    Conclusions:

    • BNP-Track enables superresolution tracking of dynamic processes in biological systems.
    • The method provides robust quantification of uncertainty in molecular tracking.
    • BNP-Track significantly advances the ability to study molecular dynamics in complex, crowded cellular environments.