Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.
Centre for Synthetic Biology, TU Darmstadt, Darmstadt 64283, Germany.
ACS Synth Biol. 2024 Oct 18;13(10):3295-3311. doi: 10.1021/acssynbio.4c00395. Epub 2024 Oct 8.
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 .
能量及其耗散是所有生命系统的基础,包括细胞。能量载体的丰度不足——如人工遗传电路带来的额外负担——会将细胞的优先级转移到生存上,同时也会损害遗传电路的功能。此外,最近的研究表明能量消耗在信息传递中的重要性。尽管生物体是非平衡系统,但在遗传设计自动化 (GDA) 软件中尚未采用能够解释能量耗散和非平衡响应曲线的非平衡模型。为此,我们引入了节能技术映射,这是一种针对遗传逻辑电路的能量效率和功能的自动化设计。其基础是一个节能的非平衡稳态基因表达模型,该模型能够捕捉到能量耗散等特征——我们将其与熵产生速率联系起来——以及转录爆发,这对真核生物和原核生物都很重要。我们的评估表明,遗传逻辑电路的功能性能和能量效率是两个不相关的优化目标。对于我们的基准,与功能优化的变体相比,平均节能效率提高了 37.2%。我们发现能量消耗和整体蛋白质表达随着电路规模呈线性增加,而节能技术映射允许设计能量成本比电路小一到两个门的遗传逻辑电路。结构变体进一步提高了这一点,同时结果表明了单个布尔函数的结构之间的帕累托优势。通过将能量需求纳入设计中,节能技术映射实现了设计节能。这扩展了当前的 GDA 工具,并补充了应对负担的方法。