Virus Traffic

Animation of motor protein stepping, D.Bolinsky
All known cellular cargos including protein and RNA complexes, vesicles, organelles and pathogens are bidirectionally transported by molecular motors on polarized microtubules to the cell center and periphery. This enables fine tuning and reversibility of transport. However, it is unknown if the motor activity is coordinated or works stochastically. Viruses are simple cargos, and their replication requires dynein and kinesin mediated transport. Here we carried out live cell microscopy, single virus tracking and trajectory segmentation (to extract directed runs length and velocity distributions) as a basis to computationally model bidirectional transport of human adenovirus type 2 on microtubules. Directed runs are the fastest intracellular motions observed for adenoviruses and are shown to be microtubule dependent.

A stochastic model for virus traffic

We used a tug of war model in which the motors dynein (D) and kinesin (K) step [1-2] along a 1D microtubule,  bind [3-5] to and unbind [4-6] from the cargo. The number of available binding sites on the virus is indicated with ρ. Given the parameters r and ρ, trajectories are stochastically simulated and then segmented to extract length and velocity distributions for the directed (fast) motion runs.

tug of war model in which the motors dynein (D) and kinesin (K) step [1-2] along a 1D microtubule, bind [3-5] to and unbind [4-6] from the cargo.

tug of war model in which the motors dynein (D) and kinesin (K) step [1-2] along a 1D microtubule, bind [3-5] to and unbind [4-6] from the cargo.

Model parameters identified from experimental data using Evolution Strategies

The model parameters are identified by using a Covariance Matrix Adaptation Evolutionary Strategy to minimize the distance (Kullback-Leibler Divergence) between simulated and biological length and velocity distributions.

Covariance Matrix Adaptation Evolutionary Strategy to minimize the distance (Kullback-Leibler Divergence) between simulated and biological length and velocity distributions

Covariance Matrix Adaptation Evolutionary Strategy to minimize the distance (Kullback-Leibler Divergence) between simulated and biological length and velocity distributions

Model predictions for virus binding sites

Given the predicted range of 6-16 binding sites and the viral capsid structure, interfaces between protein hexon and protein IX (pIX) are left as candidates to harbor the motor binding sites. We imaged pIX deficient adenoviruses and the corresponding run length and velocity distributions show that bidirectionality is preserved.

pIX deficient adenoviruses and the corresponding run length and velocity distributions

pIX deficient adenoviruses and the corresponding run length and velocity distributions

Summary of Findings

  • The proposed model accurately reproduces motor activity
  • Found an optimal range of 6-16 binding sites
  • Virus dynamics are characterized by low number of bound motors
  • Strong correlation between velocity and number of motors
  • High dependence on the unbinding rates
  • We predict that hexon provides the motor binding sites

People: Mattia Gazzola, Basil Bayati

Collaborators: Urs Greber, Christoph Burkhardt (University of Zurich, Institute of Zoology)

Funding:SystemsX

Publications

2009

  • M. Gazzola, C. J. Burckhardt, B. Bayati, M. Engelke, U. F. Greber, and P. Koumoutsakos, “A stochastic model for microtubule motors describes the in vivo cytoplasmic transport of human adenovirus,” PLoS Comput. Biol., vol. 5, iss. 12, p. e1000623, 2009.

BibTeX

@article{gazzola2009a,
author = {Mattia Gazzola and Christoph J. Burckhardt and Basil Bayati and Martin Engelke and Urs F. Greber and Petros Koumoutsakos},
doi = {10.1371/journal.pcbi.1000623},
editor = {Herbert M. Sauro},
journal = {{PLoS Comput. Biol.}},
month = {dec},
number = {12},
pages = {e1000623},
publisher = {Public Library of Science ({PLoS})},
title = {A Stochastic Model for Microtubule Motors Describes the In Vivo Cytoplasmic Transport of Human Adenovirus},
url = {https://cse-lab.seas.harvard.edu/files/cse-lab/files/gazzola2009a.pdf},
volume = {5},
year = {2009}
}

Abstract

Cytoplasmic transport of organelles, nucleic acids and proteins on microtubules is usually bidirectional with dynein and kinesin motors mediating the delivery of cargoes in the cytoplasm. Here we combine live cell microscopy, single virus tracking and trajectory segmentation to systematically identify the parameters of a stochastic computational model of cargo transport by molecular motors on microtubules. The model parameters are identified using an evolutionary optimization algorithm to minimize the Kullback-Leibler divergence between the in silico and the in vivo run length and velocity distributions of the viruses on microtubules. The present stochastic model suggests that bidirectional transport of human adenoviruses can be explained without explicit motor coordination. The model enables the prediction of the number of motors active on the viral cargo during microtubule-dependent motions as well as the number of motor binding sites, with the protein hexon as the binding site for the motors.