Valeri Barsegov (University of Massachusetts - Lowell): CellDynaMo – Stochastic Reaction-Diffusion-Dynamics Model: Application to Search-and-Capture Process of Mitotic Spindle Assembly

Title: CellDynaMo – Stochastic Reaction-Diffusion-Dynamics Model: Application to Search-and-Capture Process of Mitotic Spindle Assembly

Speaker: Valeri Barsegov, University of Massachusetts – Lowell

Hosted by: Garegin Papoian

Abstract: 

We introduce a Stochastic Reaction-Diffusion-Dynamics Model (SRDDM) for simulations of cellular processes with high spatial and temporal resolution. The SRDDM model is mapped into the CellDynaMo package, which couples the spatially inhomogeneous reaction-diffusion master equation to account for biochemical reactions and molecular transport and the Langevin Dynamics framework to describe dynamic mechanical processes. This computational infrastructure allows the simulation of hours of cell dynamics in reasonable GPU time. We apply the model to test the performance of Search-and-Capture model of mitotic spindle assembly by simulating dynamic instability of elastic microtubules anchored in two centrosomes, movement and deformations of geometrically realistic centromeres with flexible kinetochores and chromosome arms, mechanics and kinetics of transient attachments/detachments of microtubules to the chromosomal kinetochores with attachment/detachment rates depending on phosphorylation states of the Ndc80 linkers, which are regulated by Aurora A and B kinase enzymes undergoing restricted diffusion. There is an optimal rate of microtubule-kinetochore detachments which maximizes the accuracy of the chromosome connections. Adding chromosome arms to kinetochores improve the accuracy by slowing down chromosome movements. Aurora A and kinetochore deformations have a small positive effect on the attachment accuracy. Thermal fluctuations of the microtubules increase the rates of kinetochore capture and also improve the accuracy of spindle assembly.