Synthetic Circuits for Multicellular Spatial Patterning

Author: Wang, Sheng

Year: 2023

Degree: Dissertation (Ph.D.)

Advisor: Elowitz, Michael B.

Committee Members: Goentoro, Lea A.; Murray, Richard M.; Meister, Markus; Elowitz, Michael B.

Option: Bioengineering

DOI: 10.7907/3rbk-g805

Abstract

Self-organized spatial periodic patterning mechanisms are responsible for the generation of repetitive structures, such as digits, vertebrae, and teeth, during multicellular development. Adopting a synthetic biology approach, we aim to unravel the core principles of multicellular spatial patterning by designing and reconstituting it in tissue-cultured cell lines.

The reaction-diffusion mechanism, as an established paradigm, has successfully elucidated and forecasted pattern formation across varying scales and species. However, the potential for reconstituting synthetic reaction-diffusion patterns using unconventional reaction-diffusion elements within mammalian cell cultures has been insufficiently explored, thus leaving a gap in our comprehension of how spatial periodic patterns could be generated.

The simplest reaction-diffusion systems are thought to necessitate a minimum of two morphogens to generate periodic patterns. In contrast, with the help of mathematical modeling, we illustrate that a simpler circuit, comprising only a single diffusible morphogen, can adequately produce long-range, spatially periodic patterns. These patterns propagate outward from transient initiating perturbations and remain stable after the disturbance is removed. Moreover, introducing an additional bistable intracellular feedback or operation on a growing cell lattice can enhance the robustness of the patterning against noise.

Concurrently, we reconstruct the Turing pattern in mammalian cell culture utilizing a bottom-up approach. We construct a synthetic circuit based on two signaling pathways. After validation of each circuit component, we exhibit the spatial pattern formation driven by a synthetic reaction-diffusion circuit within the mammalian cell line. This adaptable circuit facilitates us to adjust circuit parameters or implement various boundary conditions, thereby revealing the impact of these alterations on patterning dynamics.

Collectively, these findings lay the groundwork for the engineering of pattern formation in the nascent field of synthetic developmental biology.

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