A synthetic biology programming language and foundational control theory with application to guided multicellular mammalian 3D shape shifters
Abstract
Composing reliable synthetic circuits in cells has been surprisingly difficult because reaction mechanisms are inherently stochastic and the cellular milieu is heterogeneous. The resulting effects go far beyond phenotypic noise, and can completely change stability properties and qualitative behaviors. Stochastic dynamics are often too counterintuitive to infer broader principles without formal proofs, depend on parameters that are rarely known, and lead to mathematical models that rarely can be solved analytically even in the simplest cases. We are addressing these challenges by considering generalized families of stochastic processes describing reaction networks, and by deriving broad and exact analytical rules that hold even when crucial aspects of the whole systems are unknown. As many broad rules in mathematics and science - from the laws of thermodynamics to criteria for what types of effects are possible in dynamical systems - such rules identify what cannot happen rather than what will happen. We derived many such impossibility proofs in our preliminary results which already substantially facilitated rational composition by ruling out many otherwise seemingly sound compositions, and in many cases also identified optimal mechanisms. This project will leverage a deep understanding of the aforementioned fundamental limitations to develop a new framework that allows the designer to identify sets of mechanisms that produce the desired behavior.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 06, 2024
- Source ID
- FA95502310529
Entities
People
- Ron Weiss
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- United States Air Force