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Updated: Jun 27, 2025
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In Vitro Disassembly of Influenza A Virus Capsids by Gradient Centrifugation
Published on: March 27, 2016
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Directional change during active diffusion of viral ribonucleoprotein particles through cytoplasm
Kathleen C Smith1, Ryan Oglietti2, Steven J Moran3
1Department of Chemistry, Wake Forest University, Winston-Salem, North Carolina.
Biophysical Journal
|April 26, 2024
Summary
Cytoskeletal networks hinder large particle movement in cells, but active diffusion allows transport. Machine learning reveals how ribonucleoprotein (RNP) particles navigate this mesh by switching between distinct states.
Area of Science:
- Cellular biology
- Biophysics
- Molecular dynamics
Background:
- Mammalian cells possess a cytoskeletal meshwork of microtubules, intermediate filaments, and actin fibers.
- This mesh restricts Brownian diffusion for particles larger than 0.10 μm, including vesicular stomatitis virus ribonucleoprotein (RNP) particles.
Purpose of the Study:
- To extend previous machine learning analyses of RNP particle movement within the cell.
- To investigate the dynamics of RNP particle movement within and between identified states.
Main Methods:
- Utilized machine learning, including variational Bayesian analysis, Gaussian mixture models, and hidden Markov models, to analyze particle tracks.
- Extended prior methods to analyze intra-state particle movement and inter-state directionality.
Main Results:
- RNP particles exhibit active diffusion, a nonthermal transport process powered by ATP and motor proteins like myosin II.
- Machine learning analysis revealed that RNP particles are spatially clustered into distinct states, with transitions occurring every 0.2-1.0 seconds.
Conclusions:
- Active diffusion, driven by cytoskeletal dynamics and motor proteins, is crucial for RNP particle transport in cells.
- Advanced machine learning techniques provide a more comprehensive understanding of particle dynamics and state transitions than traditional methods.
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