A Synthetic Biology Approach to Multicellular Patterning
September 1, 2018 - August 31, 2021
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Director: Hon Man Alex NgInstitution: California Institute of Technology
The transformation of individual cells into a complex, highly-organized multicellular structure is one of the most astonishing processes in biology. To achieve successful organization of trillions of cells in diverse states, these cells must continually produce and respond to a constantly changing stream of information in their local environments. Understanding these information processing mechanisms is critical to understanding multicellular development. However, it is difficult to explore this information processing behavior in natural organisms as they develop due to the many real-world challenges that are encountered—cross-talk between concurrent processes, pleiotropic effects of genetic perturbations, and the difficulty of controlling circuit architectures, to name a few.
Employing engineered cells would allow researchers to isolate the activities being studied and remove external distractions and challenges. Recent advances in genome engineering, reconstitution of morphogen gradients, and quantitative live cell analysis make this “synthetic biology” approach possible for the first time. This project will leverage synthetic biology approaches to design, construct, and analyze a broad range of genetic circuits operating within and between individual cells, observe what kinds of multicellular patterns each one can produce, and quantify what tradeoffs exist between different designs.
Alex Ng of the California Institute of Technology will engineer cells that are able to self-generate specific spatial patterns de novo through engineered morphogenetic information processing systems and design genetic circuits that implement three classic multicellular patterning behaviors. These multicellular behaviors represent crucial elementary steps that can be combined in the longer term to enable the engineering of more complex spatial structures, resembling digit patterning. This approach should reveal fundamental new information processing and design principles for multicellular pattern formation equally relevant to natural development and tissue engineering.
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