SemiSynBio: Collaborative Research: Very Large-Scale Genetic Circuit Design Automation

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The computing power of biology is incredible, evident in the natural world in the intricate patterns underlying materials and the body plan of animals. Cells build these structures by using networks of interacting bio-molecules, encoded in their DNA, that function as microscopic computers, the power of which grows as many cells communicate to work together on a problem. The goal of this project is to significantly scale-up the ability to build these systems by design such that cells can be programmed to perform complex computational tasks. This will be done by creating software that allows a user to write code, exactly as one would program a computer, which is then compiled to a DNA sequence. New theoretical tools will be applied to determine the power required by the cell to run these programs and how best to distribute tasks between circuits encoded in cells and conventional electronic systems. This research will broadly impact biotechnology, which is increasingly being used to commercially produce a wide range of products, from consumer goods to high-end advanced materials. Current products do not harness the computational potential of cells; in other words, all the genes are turned on all the time. This research will enable cells to be programmed to build chemicals and materials in multiple steps, both by performing the computations inside of the cells and also communicating across cells. This work is interdisciplinary and requires backgrounds in Biology, Chemistry, Mathematics, Biological Engineering, Electrical Engineering, and Computer Science. As such, the project includes the development of new educational platforms in anticipation of a need in industry for students trained at the interface between traditionally separated fields. This includes a new undergraduate-level Synthetic Biology Design course, an industrial co-op, and curriculum material "How to Grow Almost Anything," which will be made public at an international level. To build the complexity of the natural world, cells use regulatory networks made up of interacting bio-molecules to control the timing and conditions for gene regulation. For the last 20 years, researchers have been able to build synthetic genetic circuits by artfully combining regulatory interactions. The problem is that the largest of such circuits only consist of ~10 regulators, far smaller than natural networks, which drastically limits the computation that can be performed. The proposed research will develop technologies that collectively enable a massive scale-up in computational complexity to ~10^5 regulators. The first objective seeks to increase the size of circuits within cells. Logic gates based on Cas9 have enormous scale-up potential, but are limited by dCas9 toxicity and sequence repeats. A set of gates will be designed to fix these problems, guided by mathematical modeling. A framework for design automation will be developed that enables a Verilog specification to be converted into a logic diagram, that is then divided up amongst many interacting cells. The second objective seeks to distribute a genetic circuit design across multiple communicating cells. The number and reliability of cell-cell communication signals will be improved by directed evolution to increase the number of channels from 2 to 8. These will be implemented in living cells and non-living systems, thus enabling a broad range of applications inside and outside the bioreactor. Combined with 50 gates/cell, this platform offers the possibility of multicellular circuits containing 10^5+ gates. Some applications require deployment as a non-living system, for example when the application is outside of the lab, thus requiring containment. The third objective seeks to translate the parts developed in Objectives 1 and 2 to operate in multiple communicating lipid vesicles encapsulating cell-free protein extract. Cas9 gates and additional communication channels will be characterized to expand the computational potential. These will be characterized as gates and implemented using Electronic Design Automation tools to automate the design of large systems.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.