title: Insights into cytoskeletal behavior from computational modeling of dynamic microtubules in a cell-like environment.
abstract: Microtubule dynamic instability plays a fundamental role in cell biology, enabling microtubules to find and interact with randomly distributed cargo and spatially localized signals. In vitro, microtubules transition between growth and shrinkage symmetrically, consistent with the theoretical understanding of the mechanism of dynamic instability. In vivo, however, microtubules commonly exhibit asymmetric dynamic instability, growing persistently in the cell interior and experiencing catastrophe near the cell edge. What is the origin of this behavior difference? One answer is that the cell edge causes the asymmetry by inducing catastrophe in persistently growing microtubules. However, the origin of the persistent growth itself is unclear. Using a simplified coarse-grained stochastic simulation of a system of dynamic microtubules, we provide evidence that persistent growth is a predictable property of a system of nucleated, dynamic, microtubules containing sufficient tubulin in a confined space--MAP activity is not required. Persistent growth occurs because cell-edge-induced catastrophe increases the concentration of free tubulin at steady-state. Our simulations indicate that other aspects of MT dynamics thought to require temporal or spatial changes in MAP activity are also predictable, perhaps unavoidable, outcomes of the "systems nature" of the cellular microtubule cytoskeleton. These include the mitotic increase in microtubule dynamics and the observation that defects in nucleation cause changes in the behavior of microtubule plus ends. These predictions are directly relevant to understanding of the microtubule cytoskeleton, but they are also attractive from an evolutionary standpoint because they provide evidence that apparently complex cellular behaviors can originate from simple interactions without a requirement for intricate regulatory machinery.
authors.affiliation: Interdisciplinary Center for the Study of Biocomplexity, University of Notre Dame, Notre Dame, IN 46556 USA.
authors.forename: Ivan V
authors.initials: IV
authors.lastname: Gregoretti
authors.forename: Gennady
authors.initials: G
authors.lastname: Margolin
authors.forename: Mark S
authors.initials: MS
authors.lastname: Alber
authors.forename: Holly V
authors.initials: HV
authors.lastname: Goodson
mesh_terms: D048430:Cell Shape; D003198:Computer Simulation; D003599:Cytoskeleton / Q000502:physiology*; D006153:Guanosine Diphosphate / Q000378:metabolism; D006160:Guanosine Triphosphate / Q000378:metabolism; D008869:Microtubule-Associated Proteins / Q000502:physiology; D008870:Microtubules / Q000502:physiology; D008938:Mitosis / Q000502:physiology; D008954:Models, Biological; D020409:Molecular Motor Proteins / Q000502:physiology*; D009010:Monte Carlo Method; D009038:Motion; D013269:Stochastic Processes; D014404:Tubulin / Q000502:physiology*
chemical_list: D008869:Microtubule-Associated Proteins; D020409:Molecular Motor Proteins; D014404:Tubulin; D006153:Guanosine Diphosphate; D006160:Guanosine Triphosphate