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Protein Dynamics in Living Cells

Protein Dynamics in Living Cells

Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...

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3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

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Identifying directional persistence in intracellular particle motion using Hidden Markov Models.

Magnus Röding¹, Ming Guo², David A Weitz²

¹Department of Mathematical Statistics, Chalmers University of Technology and Gothenburg University, Gothenburg, Sweden.

Mathematical Biosciences

|January 15, 2014

Summary

This study introduces a new method to identify distinct motion states in living cells by analyzing particle movement. The technique accurately differentiates between random and directed intracellular transport, enhancing our understanding of cellular dynamics.

Keywords:

Hidden Markov Models Intracellular transport Particle tracking Transport processes

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Area of Science:

Cellular and Molecular Biology
Biophysics
Statistical Mechanics

Background:

Living cells exhibit complex intracellular dynamics driven by active processes.
Particle tracking is crucial for studying these dynamics, but motion is often heterogeneous.
Distinguishing between random and directed motion is key to understanding cellular transport.

Purpose of the Study:

To develop a novel method for identifying distinct motion states within individual particle trajectories.
To characterize different types of directional persistence in intracellular particle movement.
To provide a tool for analyzing active and passive transport mechanisms in cells.

Main Methods:

Utilized a multi-scale turning angle model to locally characterize particle motion.
Employed a Hidden Markov Model with two states to represent different directional persistence.
Defined a reference state using data from inhibited active cellular processes.

Main Results:

The method successfully identified distinct states of motion with varying directional persistence.
Analysis of vesicle and nanosphere transport demonstrated the method's utility.
Mean squared displacement analysis showed strong agreement between the reference state and one identified state.

Conclusions:

The developed method accurately identifies states of motion with different directional persistence.
This approach enhances the analysis of heterogeneous intracellular transport.
The findings offer a valuable tool for studying non-equilibrium processes in living cells.