Open Access
Zomorrodi, Ali Reza
Graduate Program:
Industrial Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Costas D Maranas, Thesis Advisor
  • Soundar Rajan Tirupatikumara, Thesis Advisor
  • Biobrick
  • MIT registry of standard biological parts
  • Synthetic genetic circuits
  • Integer linear programming
The comprehensive compilation of the building blocks of synthetic genetic circuits in the MIT registry of standard biological parts (http://parts.mit.edu/) has provided a repository of spare parts to rationally create devices and systems with desired properties. The performance and interactions of the biological components in this database are primarily of a qualitative nature complicating their effective utilization for circuit design. Modeling approaches capable of harnessing the qualitative knowledge contained in this database are thus timely. Here, we introduce a computational framework that relies on the available qualitative information in the MIT registry to automatically identify the circuit components and connectivity for a desired response to the presence/absence of input signals. The promoters and ribosome binding sites are categorized as high, medium, and low efficiency and the protein expressions in the circuit are described using piecewise linear differential equations. The desired function of the circuit is also mathematically described as the maximization/minimization of an appropriately constrained objective function. We applied this framework to a variety of applications including design of a genetic toggle switch, a genetic decoder and a genetic half adder unit. The identified designs are consistent with previously constructed circuit configurations and in some cases point at completely new architectures. The non-intuitive circuit structures hint at the role of ribosome binding sites and relative protein abundance levels as controlling factors in circuit design. Our results demonstrate the value of the qualitative information in the MIT registry for coarse-grained circuit design and simulation in the absence of detailed quantitative and/or kinetic information.