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遗传逻辑电路的能量感知技术映射

Energy Aware Technology Mapping of Genetic Logic Circuits.

作者信息

Kubaczka Erik, Gehri Maximilian, Marlhens Jérémie J M, Schwarz Tobias, Molderings Maik, Engelmann Nicolai, Garcia Hernan G, Hochberger Christian, Koeppl Heinz

机构信息

Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany.

Graduate School Life Science Engineering, TU Darmstadt, Darmstadt, 64283, Germany.

出版信息

bioRxiv. 2024 Sep 24:2024.06.27.601038. doi: 10.1101/2024.06.27.601038.

Abstract

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 (NESS) 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 372% 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 energy efficiency 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 .

摘要

能量及其耗散对于包括细胞在内的所有生命系统而言都是至关重要的。由于人工遗传回路带来的额外负担导致能量载体数量不足,这会将细胞的首要任务转变为生存,同时也会损害遗传回路的功能。此外,最近的研究表明了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,但能够解释能量耗散和非平衡响应曲线的非平衡模型尚未应用于遗传设计自动化(GDA)软件中。为此,我们引入了能量感知技术映射,即针对能量效率和功能对遗传逻辑电路进行自动化设计。其基础是一个基因表达的能量感知非平衡稳态(NESS)模型,该模型能够捕捉诸如能量耗散(我们将其与熵产生率联系起来)和转录爆发等特征,这些特征对于真核生物和原核生物均具有相关性。我们的评估表明,遗传逻辑电路的功能性能和能量效率是相互脱节的优化目标。以我们的基准为例,与功能优化的变体相比,能量效率平均提高了372%。我们发现能量消耗和总蛋白表达随电路规模呈线性增加,其中能量感知技术映射允许设计出能量效率与小一到两个门的电路相当的遗传逻辑电路。结构变体进一步改善了这一点,同时结果显示了单个布尔函数结构之间的帕累托优势。通过将能量需求纳入设计,能量感知技术映射实现了设计中的能量效率。这扩展了当前的GDA工具,并补充了应对负担的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fa2/11463650/fae602d8da1f/nihpp-2024.06.27.601038v2-f0001.jpg

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