AMS-SS: Multiscale stochastic model of myxobacteria dynamics

点击翻译按钮获取中文摘要

Swarming, the coordinated motion of many cells, facilitates their spread on the surface of a suitably moist solid medium. Unlike aggregation that concentrates cells, swarming disperses cells across a surface. As a result of evolution the use of energy is optimized by the swarm in order for it to expand and cover the largest possible area, allowing individual cells maximal access to nutrient and oxygen. Despite years of experiments the main problem of swarm dynamics is wide open: how is this optimal cell arrangement produced by individual cells with only local knowledge of their surroundings? The research group will use a large amount of available reliable experimental data on cell behavior and interactions between cells as building blocks for developing comprehensive mathematical and computational multi-dimensional hybrid models of bacterial swarming based on short and long range interactions. Better understanding of the collective motion of bacteria will shed light on how bacteria infect human tissues in disease. For example, in Cystic Fibrosis the pathogenic bacterium, Pseudomonas aeruginosa swarms over the surface of the lung, clogging the patient's airways. Proteus, another pathogen, also infects by swarming.The proposed modeling approach will be demonstrated by studying swarming of Myxococcus xanthus; which swarms rapidly, has been studied for decades, and whose numerous swarming mutants have been identified and characterized. To bring different scale levels of description together (from thousands to millions of cells), new mathematical techniques and tools will be developed including elements of stochastic analysis, nonlinear analysis and kinetic theory. The essential part of the project will be to connect results of modeling with experimental results and propose new biological experiments. An important component of the project will be the interdisciplinary training of graduate students in biology and mathematics.