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Energy Aware Technology Mapping of Genetic Logic Circuits
Erik Kubaczka1,2, Maximilian Gehri1,2, Jérémie J M Marlhens1,3,2
1Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.
ACS Synthetic Biology
|October 8, 2024
Summary
We developed Energy Aware Technology Mapping to design energy-efficient genetic logic circuits. This approach optimizes circuits for energy use, improving efficiency by 37.2% and reducing costs.
Area of Science:
- Synthetic biology
- Systems biology
- Computational biology
Background:
- Energy dissipation is crucial for all living systems, including cellular functions.
- Genetic design automation (GDA) currently lacks non-equilibrium models for energy dissipation and response curves.
- Cellular energy limitations can impair artificial genetic circuit functionality and survival.
Purpose of the Study:
- Introduce Energy Aware Technology Mapping (EATM) for automated genetic logic circuit design.
- Incorporate energy efficiency and functionality as key design considerations.
- Utilize non-equilibrium models to account for energy dissipation in genetic circuits.
Main Methods:
- Developed an energy-aware non-equilibrium steady-state model for gene expression.
- Modeled energy dissipation, linking it to entropy production rate.
- Incorporated transcriptional bursting relevant to both eukaryotes and prokaryotes.
Main Results:
- Demonstrated that functional performance and energy efficiency are often disjoint optimization goals for genetic circuits.
- Achieved an average energy efficiency improvement of 37.2% compared to functionally optimized variants.
- Observed a linear relationship between circuit size, energy expenditure, and protein expression.
Conclusions:
- EATM enables the design of genetic logic circuits with reduced energetic costs, equivalent to one to two fewer gates.
- Structural variants further enhance energy efficiency, with Pareto dominance observed among structures for a single Boolean function.
- Integrating energy demand into the design process, via EATM, leads to inherently energy-efficient genetic circuits, complementing existing burden-coping strategies.
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