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Synthesizing Configurable Biochemical Implementation of Linear Systems from Their Transfer Function Specifications
Tai-Yin Chiu1, Hui-Ju K Chiang2, Ruei-Yang Huang3
1Department of Physics, National Taiwan University, Taipei, Taiwan; Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan.
Plos One
|September 10, 2015
Summary
This study introduces an automated design flow for synthetic biochemical systems, enabling precise control using DNA strand displacement. The novel method ensures adaptive systems that precisely match transfer function specifications.
Area of Science:
- Biochemical Engineering
- Synthetic Biology
- Control Theory
Background:
- Linear system design is crucial for control tasks but faces challenges in biochemical realization.
- Existing methods lack automation, dynamic adaptivity, and precise rate constant matching.
- Previous work by Oishi and Klavins laid groundwork but left issues unresolved.
Purpose of the Study:
- To develop an automated design flow for linear systems in a biochemical context.
- To overcome limitations of existing methods, including lack of adaptivity and precise specification conformance.
- To enable precise implementation of transfer function specifications using DNA strand displacement.
Main Methods:
- Developed a design flow transforming transfer function specifications into chemical reactions.
- Utilized DNA strand displacement for system implementation.
- Incorporated configurability via primitive components and template modules for adaptivity.
Main Results:
- Achieved precise input-output response conforming to transfer function specifications.
- Demonstrated dynamic adaptivity to environmental changes through embedded configurability.
- Validated the feasibility and superiority of the proposed synthesis flow via simulation.
Conclusions:
- The proposed design flow automates the creation of adaptive synthetic biochemical systems.
- DNA strand displacement offers a robust platform for implementing complex linear control systems.
- This advancement significantly improves the engineering of synthetic biological systems.
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