scholarly journals Robust evaluation of diffusion coefficient against displacement threshold parameter of single particle tracking algorithm

2017 ◽  
Vol 12 (8) ◽  
pp. 506-510 ◽  
Author(s):  
Reiji Motohashi ◽  
Itsuo Hanasaki ◽  
Yuto Ooi ◽  
Yu Matsuda
Keyword(s):  
Diffusion Coefficient ◽  
Particle Tracking ◽  
Single Particle ◽  
Single Particle Tracking ◽  
Tracking Algorithm ◽  
Threshold Parameter ◽  
Displacement Threshold ◽  
Particle Tracking Algorithm

EGF RECEPTOR DYNAMICS IN EGF-RESPONDING CELLS REVEALED BY FUNCTIONAL IMAGING DURING SINGLE PARTICLE TRACKING

2013 ◽  
Vol 08 (03n04) ◽  
pp. 229-242 ◽  
Author(s):  
H. DE KEERSMAECKER ◽  
S. ROCHA ◽  
E. FRON ◽  
H. UJI-I ◽  
J. HOFKENS ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Functional Imaging ◽  
Particle Tracking ◽  
Single Particle ◽  
Egf Receptor ◽  
Single Particle Tracking ◽  
Fast Mode ◽  
Egf Receptors ◽  
Special Issue ◽  
Physiological Concentration

The epidermal growth factor (EGF) receptor transduces the extracellular EGF signal into the cells. The distribution of these EGF receptors in the plasma membrane is heterogeneous and dynamic, which is proposed to be important for the regulation of cell signaling. The response of the cells to a physiological concentration of EGF is not homogeneous, which makes it difficult to analyze the dynamics related to the response. Here we developed a system to perform functional imaging during single particle tracking (SPT) analysis. This system made it possible to observe the cytosolic Ca 2+ concentration to monitor the cell response while tracking individual EGF molecules and found that about half of the cells responded to the stimulation with 1.6 nM EGF. In the responding cells, the EGF receptor showed 3 modes of movement: fast (the diffusion coefficient of 0.081 ± 0.009 μm2/sec, 29 ± 9%), slow (0.020 ± 0.005 μm2/sec, 22 ± 6%), and stationary (49 ± 13%). The diffusion coefficient of the fast mode movement in the responding cells was significantly larger than that in the nonresponding cells (0.069 ± 0.009 μm2/sec, p < 0.05). The diffusion coefficient of the fast mode movement is thought to reflect the monomer–dimer equilibrium of the EGF receptor. We assumed that the feedback regulation via the Ca 2+ signaling pathway slightly shifts the equilibrium from dimer to monomer in the responding cells. [Formula: see text]Special Issue Comment: This research paper is about the diffusion of EGF receptors in the membrane. It is therefore related with various projects in this Special Issue: the reviews about FRET41 and enzymes,42 and the projects about solving single molecules trajectories.43

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 Adaptive settings for the nearest-neighbor particle tracking algorithm

2014 ◽  
Vol 31 (8) ◽  
pp. 1279-1285 ◽  
Author(s):  
Javier Mazzaferri ◽  
Joannie Roy ◽  
Stephane Lefrancois ◽  
Santiago Costantino
Keyword(s):  
Particle Tracking ◽  
Nearest Neighbor ◽  
Tracking Algorithm ◽  
Neighbor Particle ◽  
Particle Tracking Algorithm

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.

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