Molecular motor-based models of random intermittent search

Friday, September 30, 2011 - 16:00 to 16:50
Speaker Information
Paul Bressloff
University of Utah

Abstract or Additional Information

Random search strategies occur throughout nature as a means of efficiently searching large areas for one or more targets of unknown location, which can only be detected when the searcher is within a certain range. Examples include animals foraging for food or shelter, the motor-driven transport and delivery of macromolecules to particular compartments within cells, and a promoter protein searching for a specific target site on DNA. One particular class of model, which can be applied both to foraging animals and active transport in cells, treats a random searcher as a particle that switches between a slow motion (diffusive) or stationary phase in which target detection can occur and a fast motion "ballistic" phase; transitions between bulk movement states and searching states are governed by a Markov process.

In this talk we review recent work on the analysis of random intermittent search models of motor-driven transport within cells. The stochastic search process is modeled in terms of a differential Chapman-Kolmogorov equation, which is then reduced to a scalar Fokker-Planck equation using perturbation theory. The reduced FP equation is used to compute various quantities that characterise the efficiency of the search process, including the mean first passage time (MFPT) to target absorption. We illustrate the theory by considering a multiple motor model of bidirectional transport, in which opposing motors compete in a "tug-of-war," and use this to explore how local signaling mechanisms could regulate the delivery of cargo to synaptic targets. We end by discussing extensions to higher dimensional searches.

Research Area