Modeling Frameworks for Modular and Scalable Biological Circuit Design

Citation

Pandey, Ayush (2024) Modeling Frameworks for Modular and Scalable Biological Circuit Design. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/qacp-dw76. https://resolver.caltech.edu/CaltechTHESIS:06062023-021337351

Abstract

Synthetic biology is a rapidly evolving interdisciplinary field that combines principles from biology, bioengineering, biochemistry, and computational sciences to design and engineer new biological systems for various applications. This thesis focuses on addressing the challenges in engineering large and complex biological circuits. We develop modular modeling frameworks, formal theory, and computer-assisted design (CAD) tools for design and analysis of biological systems at a larger scale.

This thesis introduces a new problem of robustness in structured model reduction of dynamical systems and provides bounds on a robustness distance metric for linear and nonlinear systems. With this theory, we show the discrimination and quantification of different mathematical models, considering resource loading effects in biological circuits.

Using our proposed model reduction robustness theory and its associated software development, we build a modeling, analysis, and parameter identification pipeline. This pipeline is demonstrated through the characterization of DNA recombination enzymes in a cell-free protein expression system. This pipeline is a general approach to systematically develop mathematical models, infer parameters from experimental data, and guide experimental design choices.

Identification of parameters in detailed mathematical models is a major challenge in synthetic biology where only sparse data is available. This prevents the application of our detail-driven modeling approach to larger biological systems. Hence, to address this limitation, we present a formal methods-based approach for specifying and synthesizing implementations for the design of biological circuits. We present a contract-based design framework for synthetic biology. We write formal description of design objectives at a higher level of abstraction without modeling the details of each component. This design framework facilitates the design and prediction of complex synthetic biological circuits at scale.

Overall, this thesis contributes to the advancement of synthetic biology by providing novel modeling frameworks, analysis methods, and design approaches. These contributions aim to enable the design and analysis of complex biological systems and foster the systematic engineering of biological circuits.

Thesis Files