A scalable multi-scale framework for parallel simulation and visualization of microbial evolution

Abstract

Bacteria are some of the most ubiquitous, simple and fastest evolving life forms in the planet, yet even in their case, evolution is painstakingly difficult to trace in a laboratory setting. However, evolution of microorganisms in controlled and/or accelerated settings is crucial to advance our understanding on how various behavioral patterns emerge, or to engineer new strains with desired proprieties (e.g. resilient strains for recombinant protein or bio-fuels production). We present a microbial evolution simulator, a tool to study and analyze hypotheses regarding microbial evolution dynamics. The simulator employs multi-scale models and data structures that capture a whole ecology of interactions between the environment, populations, organisms, and their respective gene regulatory and biochemical networks. For each time point, the evolutionary "fossil record" is recorded in each run. This dataset (stored in HDF5 format for scalability) includes all environmental and cellular parameters, cellular (division, death) and evolutionary events (mutations, Horizontal Gene Transfer). This leads to the creation of a coherent dataset that could not have been obtained experimentally. To efficiently analyze it, we have developed a novel visualization tool that projects information in multiple levels (population, phylogeny, networks, and phenotypes). Additionally, we present some of the unique insights in microbial evolution that were possible through simulations in TeraGrid, and we describe further steps to address scalability issues for populations beyond 32,000 cells.