Evidence map›Paper›PMID 39378113›Full record

ArticleACS synthetic biology2024

Energy Aware Technology Mapping of Genetic Logic Circuits.

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

Abstract read
In one paragraph

Article in ACS synthetic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Erik KubaczkaDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0009-0005-2467-5533
Maximilian GehriDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0009-0007-1720-0016
Jérémie J M MarlhensDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0009-0002-2117-976X
Tobias SchwarzDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0000-0002-6935-8073
Maik MolderingsDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0000-0002-6742-2780
Nicolai EngelmannDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0000-0002-6318-7859
Hernan G GarciaDepartment of Molecular and Cell Biology, UC Berkeley, Berkeley, California 924720, United States.ORCID 0000-0002-5212-3649
Christian HochbergerDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0000-0001-5516-7826
Heinz KoepplDepartment of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany.ORCID 0000-0002-8305-9379

Funding

Predictive understanding of the temporal control of transcription in Drosophila developmentR01GM139913 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI GARCIA, HERNAN GUSTAVO · 2021 to 2024
$1.2M
In vivo mechanisms of Dorsal-mediated transcriptional control in developmentR01GM152815 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI GARCIA, HERNAN GUSTAVO · 2024 to 2024
$306k
NIGMS NIH HHS R01 GM139913NIGMS NIH HHS R01 GM152815
6 · The paper itself

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 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

Indexed as

Gene Regulatory NetworksEnergy MetabolismEntropyModels, GeneticSoftwareSynthetic Biologycomputer aided designenergyentropy production rategene-expressiongenetic design automationmetabolic burdennon-equilibriumsynthetic biologytechnology mappingthermodynamics

Identifiers

PMID39378113
PMCPMC11494706

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.