Characterizing Intracellular Structure and Dynamics Through Trajectory Analysis and Single-particle Tracking of QDs in Live PC12 Cells

SummarySingle Particle Tracking (SPT) is one of the most widespread techniques to evaluate particle mobility in a variety of situations, such as in cellular and model membrane dynamics. The proposed TRAIT2D Python library is developed to provide object tracking, trajectory analysis and produce simulated datasets with graphical user interface. The tool allows advanced users to customise the analysis to their requirements.Availability and implementation: the software has been coded in Python, and can be accessed from: https://github.com/Eggeling-Lab-Microscope-Software/TRAIT2D, or the pypi and condaforge repositories.A comprehensive user guide is provided at https://eggeling-lab-microscope-software.github.io/TRAIT2D/.

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Information-Efficient, Off-Center Sampling Results in Improved Precision in 3D Single-Particle Tracking Microscopy

Entropy ◽

10.3390/e23050498 ◽

2021 ◽

Vol 23 (5) ◽

pp. 498

Author(s):

Chen Zhang ◽

Kevin Welsher

Keyword(s):

Fisher Information ◽

Particle Tracking ◽

Single Particle ◽

Biological Samples ◽

Tracking System ◽

Single Particle Tracking ◽

Uniform Sampling ◽

Single Dimension ◽

3D Localization ◽

Particle Localization

In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations predicted by Fisher information utilizes photons most efficiently. When performing localization in a single dimension, optimized off-center sampling patterns gave doubled precision compared to uniform sampling. A ~20% increase in precision compared to uniform sampling can be achieved when a similar off-center pattern is used in 3D localization. Here, we systematically investigated the photon efficiency of different emission patterns in a diffraction-limited system and achieved higher precision than uniform sampling. The ability to maximize information from the limited number of photons demonstrated here is critical for particle tracking applications in biological samples, where photons may be limited.

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Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments

The Journal of Chemical Physics ◽

10.1063/5.0038174 ◽

2021 ◽

Vol 154 (23) ◽

pp. 234105

Author(s):

Jakob Tómas Bullerjahn ◽

Gerhard Hummer

Keyword(s):

Maximum Likelihood ◽

Particle Tracking ◽

Single Particle ◽

Diffusion Coefficients ◽

Single Particle Tracking ◽

Maximum Likelihood Estimates

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Single Particle Tracking Reveals Corralling of a Transmembrane Protein in a Double-Cushioned Lipid Bilayer Assembly

Langmuir ◽

10.1021/la104133m ◽

2011 ◽

Vol 27 (1) ◽

pp. 320-327 ◽

Cited By ~ 17

Author(s):

Kumud R. Poudel ◽

David J. Keller ◽

James A. Brozik

Keyword(s):

Lipid Bilayer ◽

Particle Tracking ◽

Single Particle ◽

Transmembrane Protein ◽

Single Particle Tracking ◽

Bilayer Assembly

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Single-Particle Tracking of DNA-Binding Biomolecules in Cells: Power-Law Distributions of Dwell Times

Biophysical Journal ◽

10.1016/j.bpj.2020.11.2222 ◽

2021 ◽

Vol 120 (3) ◽

pp. 359a-360a

Author(s):

Michael J. Saxton

Keyword(s):

Dna Binding ◽

Power Law ◽

Particle Tracking ◽

Single Particle ◽

Single Particle Tracking ◽

Power Law Distributions ◽

In Cells

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pH-Mediated nanoparticle dynamics in hydrogel nanocomposites

Soft Matter ◽

10.1039/d0sm02213f ◽

2021 ◽

Author(s):

Katie A. Rose ◽

Daeyeon Lee ◽

Russell J. Composto

Keyword(s):

Quantum Dot ◽

Ethylene Glycol ◽

Particle Tracking ◽

Single Particle ◽

Silica Particles ◽

Single Particle Tracking ◽

Poly Ethylene Glycol ◽

Hydrogel Nanocomposites ◽

Poly Ethylene ◽

Nanoparticle Dynamics

The effect of static silica particles on the dynamics of quantum dot (QD) nanoparticles grafted with a poly(ethylene glycol) (PEG) brush in hydrogel nanocomposites is investigated using single particle tracking (SPT).

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