Engineering self-assembling living structures with mammalian synthetic biology
Author(s)Tordoff, Jesse(Jessica Jane)
Massachusetts Institute of Technology. Computational and Systems Biology Program.
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The shapes and structures created by living organisms have properties that any engineer would desire: they are self-healing, growing, adaptive, and range in complexity and material property from the strength of bone to the lightweight flexibility of an insect wing. The goal of this thesis is to use synthetic biology to design, control, and understand the range of structures that can be constructed using a ubiquitous tool for self-organization in animal development: cell sorting. We first use experiments and computational modeling to demonstrate how incompletely sorted structures can be systematically designed by quantitative control of cell composition. By varying the number of highly adhesive and less adhesive cells in multicellular aggregates, we find that cell type ratio and total number of cells are controllers of pattern formation, and the resulting structures are maintained over the course of days.Next, we establish a set of design rules for cell sorting-driven shape assembly using cell lines with engineered genetic circuits that can induce expression of different cadherins. We show that, even when well mixed, populations of cells with different cadherin expression profiles sort themselves in predictable ways. The resulting shapes vary significantly, including planes of semi-regular polka dots, a sphere engulfed by an outer shell, maze-like intertwined populations, and radial protrusions from a core. We can reliably select between these shapes and control their properties by changing induction of cadherin expression, population ratio, cadherin identity, and total aggregate size. Finally, we have designed and constructed a recombinase-based tool to break symmetry in a population of cells, with the ultimate goal of controlling the autonomous creation of different subpopulations from a single cell.By creating a platform to programmably generate multicellular forms, this thesis aims to establish design principles for synthetic morphogenesis and provide a framework to control living shapes.
Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 114-124).
DepartmentMassachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology
Computational and Systems Biology Program.