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Extracting Transition Rates in Particle Tracking Using Analytical Diffusion Distribution Analysis.

Jochem N A Vink1, Stan J J Brouns1, Johannes Hohlbein2

  • 1Department of Bionanoscience, Delft University of Technology, HZ Delft, the Netherlands; Kavli Institute of Nanoscience, Delft, the Netherlands.

Biophysical Journal
|October 21, 2020
PubMed
Summary
This summary is machine-generated.

Analytical diffusion distribution analysis (anaDDA) extracts molecular transition rates from single-particle tracking data. This method accurately quantifies fast molecular interactions in live cells, advancing biomolecular kinetics research.

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Area of Science:

  • Biophysics
  • Cell Biology
  • Molecular Kinetics

Background:

  • Single-particle tracking (SPT) is crucial for studying biomolecule dynamics in vivo.
  • Analyzing diffusion coefficients helps determine molecular interactions (free, complexed, or bound).
  • Extracting kinetic models for rapidly switching molecules remains a challenge.

Purpose of the Study:

  • Introduce analytical diffusion distribution analysis (anaDDA) for quantitative kinetic modeling.
  • Enable extraction of transition rates from short SPT trajectories.
  • Improve analysis of fast molecular dynamics (0.1-10 transitions/frame).

Main Methods:

  • Developed anaDDA framework for analyzing apparent diffusion coefficient distributions.
  • Utilized short trajectories (<10 localizations/track) with Markovian and Brownian motion assumptions.
  • Incorporated effects of confinement and tracking boundaries; enabled global fitting across frame times.

Main Results:

  • anaDDA accurately predicts distributions from simulations.
  • Outperforms existing methods in retrieving kinetics, particularly in the fast regime.
  • Reanalyzed DNA polymerase I data in E. coli, revealing increased long-lived interactions upon DNA damage.
  • Quantified fast DNA probing interactions (<10 ms).

Conclusions:

  • anaDDA provides a mathematically rigorous framework for SPT data analysis.
  • Expands the accessible timescale for probing molecular interactions in live cells.
  • Reveals new insights into DNA polymerase roles in DNA repair and probing dynamics.