Elucidating the network design principles of biological signal processing

项目总结

Project Summary Cells live in diverse environments and cellular communities, from the cells in our bodies to single-celled organisms surviving in the soil. To navigate these complex environments, cells must be able to sense and respond to a variety of signals. This is done through biological signaling pathways, consisting of sensors and interacting proteins, which process external signals and transmit information. My research program focuses on understanding how these biological networks transmit information about external signals to the activity of intracellular effectors, such as transcription factors, to generate an appropriate cellular response or state and how these cell states affect community-level phenotypes. Understanding this signal processing represents a key gap in our knowledge of how healthy and diseased cells make decisions and guide the behavior of cellular communities. Specifically, we ask (1) How do signaling networks transform extracellular signals into appropriate intracellular signals? (2) How are intracellular signals interpreted by the cell to generate appropriate responses? and (3) How do individual cell decisions affect population-level community phenotypes? Our research is focused on understanding signaling specificity and kinetics in the mitogen-activated kinase (MAPK) pathways as well as transcription factor dynamics and subsequent gene expression in response to environmental stress. MAP kinase pathways are conserved from yeast to humans and control vital cellular processes including proliferation, differentiation, and stress response. We use a variety of systems to address the questions outlined in this research proposal including Saccharomyces cerevisiae, the human fugal pathogen Candida albicans, synthetic signaling pathways, and mammalian cell culture. We take a multi-pronged approach that uses microfluidic and optogenetic tools to perturb signaling pathways and combine these perturbations with mathematical modeling to understand how different properties of signaling pathways, including bandwidth and crosstalk, allow them to appropriately transform their input signals. Furthermore, we use these tools to drive dynamics of intracellular effectors, such as transcription factors, and ask how these different effector dynamics generate cellular responses. And finally, we use the exquisite spatiotemporal control available with light to generate desired states in individual or populations of cells, including fungal biofilms, and ask how this affects community-level phenotypes.