TY - JOUR
T1 - Energy Aware Technology Mapping of Genetic Logic Circuits
AU - Kubaczka, Erik
AU - Gehri, Maximilian
AU - Marlhens, Jérémie J.M.
AU - Schwarz, Tobias
AU - Molderings, Maik
AU - Engelmann, Nicolai
AU - Garcia, Hernan G.
AU - Hochberger, Christian
AU - Koeppl, Heinz
N1 - Publisher Copyright:
© 2024 The Authors. Published by American Chemical Society.
PY - 2024/10/18
Y1 - 2024/10/18
N2 - Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell’s priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit’s functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.
AB - Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell’s priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit’s functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.
KW - computer aided design
KW - energy
KW - entropy production rate
KW - gene-expression
KW - genetic design automation
KW - metabolic burden
KW - non-equilibrium
KW - synthetic biology
KW - technology mapping
KW - thermodynamics
UR - https://www.scopus.com/pages/publications/85206489246
U2 - 10.1021/acssynbio.4c00395
DO - 10.1021/acssynbio.4c00395
M3 - Artículo
C2 - 39378113
AN - SCOPUS:85206489246
SN - 2161-5063
VL - 13
SP - 3295
EP - 3311
JO - ACS Synthetic Biology
JF - ACS Synthetic Biology
IS - 10
ER -