Using optogenetics to characterize signal propagation and control within gene regulatory networks

Trustees Of Boston University, Boston

Investigators

Abstract

Biological systems use complex networks of sensors and regulatory pathways to respond to and change their surrounding environments. In recent years, synthetic biologists strived to modify and repurpose these networks to change what organisms can do, and to use the modified or synthetic organisms for biotechnology, biomedicine and agriculture applications. However, our lack of knowledge about network function and organization often made it difficult to rationally design and successfully repurpose these networks, which in turn made it difficult to modify organisms in a predicable way. This project aims to define some of the underlying principles behind the function of such networks, and ultimately to use this knowledge to create synthetic organisms with particular downstream applications. Additionally, the project includes support for educational outreach activities, including a multi-day workshop for high school students that introduces cutting-edge concepts from synthetic biology, electrical circuit design, and data analysis techniques. By training young students and supporting undergraduate researchers, the project contributes to developing the next generation of scientific talent. This research project will identify the fidelity with which downstream genes can be controlled as a function of regulatory network architecture. Signal propagation will be tested in synthetic networks designed to systematically assess the impact of network architecture, and in the endogenous PhoP stress response network. The project uses an optogenetic strategy, where light will be used to drive time-varying expression of a transcription factor that regulates downstream target genes. First, the researchers will use well-defined synthetic networks to test how dynamic input signals are propagated within regulatory networks with increasing levels of complexity. The synthetic circuits will encompass common motifs from biological networks including multi-layer regulatory cascades and networks involving negative and positive feedback. Second, the project will test the extent to which it is possible for an upstream time-varying input to precisely drive the expression of a downstream target from which it may be distantly removed. The project will establish which downstream dynamics are possible to achieve as a function of network architecture. Third, signal propagation and control will be tested in the context of the endogenous PhoP stress response network. This network is subject to additional regulation and plays a critical role in regulating acid stress resistance, and these studies will be used to probe natural network dynamics and their phenotypic consequences. Overall, this project capitalizes on optogenetic methods for driving gene expression in single cells, using programmed light signals, deep learning models, and feedback control to precisely test how dynamic biological signals are utilized within regulatory networks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.