scholarly journals TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data

2021 ◽  
Author(s):  
Francesco Reina ◽  
John M. A. Wigg ◽  
Mariia Dmitrieva ◽  
Joёl Lefebvre ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Particle Tracking ◽  
Single Particle ◽  
Trajectory Analysis ◽  
Membrane Dynamics ◽  
Single Particle Tracking ◽  
Particle Diffusion ◽  
Particle Mobility ◽  
Link Type ◽  
Tracking Trajectory

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/.

scholarly journals TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 838
Author(s):  
Francesco Reina ◽  
John M.A. Wigg ◽  
Mariia Dmitrieva ◽  
Joël Lefebvre ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Data Analysis ◽  
User Interfaces ◽  
Single Particle ◽  
Membrane Dynamics ◽  
Single Particle Tracking ◽  
Particle Diffusion ◽  
Analysis Pipeline ◽  
Particle Mobility ◽  
Technological Developments ◽  
High Degree

Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox – 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience.

scholarly journals Determination of diffusion coefficient by image-based fluorescence recovery after photobleaching and single particle tracking system implemented in a single platform

2020 ◽  
pp. 2150005
Author(s):  
Donghee Lee ◽  
Jeonghoon Lee ◽  
Jung Kyung Kim
Keyword(s):  
Diffusion Coefficient ◽  
Particle Tracking ◽  
Single Particle ◽  
Fluorescence Recovery After Photobleaching ◽  
Tracking System ◽  
Membrane Dynamics ◽  
Single Particle Tracking ◽  
Submicron Particles ◽  
Fluorescence Recovery ◽  
Small Scale

Fluorescence recovery after photobleaching (FRAP) and single particle tracking (SPT) techniques determine the diffusion coefficient from average diffusive motion of high-concentration molecules and from trajectories of low-concentration single molecules, respectively. Lateral diffusion coefficients measured by FRAP and SPT techniques for the same biomolecule on cell membrane have exhibited inconsistent values across laboratories and platforms with larger diffusion coefficient determined by FRAP, but the sources of the inconsistency have not been investigated thoroughly. Here, we designed an image-based FRAP-SPT system and made a direct comparison between FRAP and SPT for diffusion coefficient of submicron particles with known theoretical values derived from Stokes–Einstein equation in aqueous solution. The combined [Formula: see text]FRAP-SPT technique allowed us to measure the diffusion coefficient of the same fluorescent particle by utilizing both techniques in a single platform and to scrutinize inherent errors and artifacts of FRAP. Our results reveal that diffusion coefficient overestimated by FRAP is caused by inaccurate estimation of the bleaching spot size and can be corrected by simple image analysis. Our [Formula: see text]FRAP-SPT technique can be potentially used for not only cellular membrane dynamics but also for quantitative analysis of the spatiotemporal distribution of the solutes in small scale analytical devices.

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

Entropy ◽  
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.

pH-Mediated nanoparticle dynamics in hydrogel nanocomposites

Soft Matter ◽  
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).

Sign in / Sign up

Export Citation Format

Share Document