Project Title: "Do Mutations that Disrupt Gene Regulation Increase the Evolutionary Creativity of Bacteria and Digital Organisms?"
This project is awarded under the Postdoctoral Research Fellowships in Biological Informatics Program for 2006. This research will test the commonly held belief that there is a tradeoff in Darwinian systems such that increasing evolvability (the frequency of adaptive mutations) decreases robustness (the likelihood that a random mutation will result in a viable organism). Specifically, the Fellow will test whether targeted mutations that disrupt existing gene regulation networks in bacteria and digital organisms make them more evolvable and less robust. To do this he will first create Escherichia coli variants where he has disabled regulatory systems that silence certain genes under conditions where they are not necessary for growth (e.g. carbon catabolite repression and Rho-dependent transcription termination). He will then compare the abilities of normal and mutant bacteria to evolve to utilize 190 different carbon sources in long-term laboratory experiments. He will perform analogous tests using the Avida software program enabling digital organisms to evolve the ability to sense the reward structures of their environments and then examine whether short-circuiting this regulation causes greater evolvability at the cost of decreased robustness. Together, these studies will provide a greater understanding of the evolutionary pathways by which new chemical diversity evolves in bacteria and answer whether there is a tension between how optimized a species is for growth under one condition and how readily it can creatively evolve to thrive under new circumstances.
The research will be carried out at Michigan State University in the labs of Richard Lenski and Charles Ofria where the Fellow will learn experimentation with bacteria and digital organisms, classical microbiological methods, and advanced high-throughput technologies such as phenotype microarrays, DNA microarrays, metabolomics profiling, and polony genome resequencing. Informatics training will include contributing C++ programming language modules to the Avida software, and analysis of large datasets using computing clusters. This training will significantly enhance the Fellow's current background in the test tube evolution of functional protein and nucleic acid sequences.
