Intellectual Merit: The ability of an organism to change its phenotype in response to various environmental cues is of fundamental biological importance, but the detailed mechanisms are not fully understood even for the best studied systems. The soil bacterium Bacillus subtilis detects currently unidentified starvation cues and processes this information via its gene regulatory networks, resulting in formation of a spore. Using this simple unicellular organism as a model, the long-term goal of this research is to discover general principles underlying the information processing by gene regulatory networks. Specifically, this project will uncover how B. subtilis processes information under conditions of environmental uncertainty and makes appropriate cell-fate decisions at the systems level. The cornerstone of the approach is a combination of in vivo and in vitro experiments as well as deterministic (population-average) and stochastic (single-cell) mathematical models. The key to success is the construction of synthetic strains which perturb various processes in the networks and the comparison of their responses to one another and to those in the wild-type strain. The experimental results will be analyzed using integrative mathematical models. The interdisciplinary nature of this research will uncover how signal-response characteristics and cell-fate decisions of the network are affected by its architecture.
Broader Impacts: As a model system, B. subtilis offers significant experimental advantages including powerful genetic tools, large collections of mutant strains, and a fully sequenced genome. Unraveling the mechanisms of information processing by the sporulation network is a key step towards understanding the molecular basis of cell-fate decision at the unicellular level. Thus, the innovative approaches in this project may be applicable for addressing similar problems in other organisms and can be used for teaching system-level concepts to students of various levels and backgrounds. In particular, the resulting collection of synthetic strains can be used for educational purposes in the undergraduate laboratory setting because their networks are easy to perturb by varying the inducer levels. As a result, students will gain an understanding of the relationship between network architecture and system level properties. In addition, mathematical models can be used as a cornerstone for systems biology curriculum. The project will also provide abundant interdisciplinary training opportunities for the participating students from various backgrounds working together on experimental and/or mathematical modeling.
