bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.06.27.601038

Energy Aware Technology Mapping of Genetic Logic Circuits

Kubaczka, E.·Gehri, M.·Marlhens, J. J. M.·Schwarz, T.·Molderings, M.·Engelmann, N.·Hochberger, C.·Koeppl, H.
View original source ↗Export metadata ↓

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 cells 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 circuits 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 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 in vivo. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/601038v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@77317borg.highwire.dtl.DTLVardef@151a140org.highwire.dtl.DTLVardef@318c19org.highwire.dtl.DTLVardef@e4be6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Source connections

Explore related subjects

synthetic biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kubaczka, E., Gehri, M., Marlhens, J. J. M., Schwarz, T., Molderings, M., Engelmann, N., Hochberger, C., Koeppl, H.. 2024-06-27. Energy Aware Technology Mapping of Genetic Logic Circuits. https://doi.org/10.1101/2024.06.27.601038

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Associative Learning and Memory Erasure in a Synthetic Multicellular System

Learning is a basic form of adaptation that organisms display from neural systems to single cells. In associative learning, the pairing of two stimuli lets one of them evoke the response to the other. Engineering this behavior in a living cell is difficult, because coincidence detection, memory, and conditional readout must be wired into a single regulatory network. Here we build a consortium of five E. coli strains that distributes the operations of associative learning and communicates through one diffusible quorum-sensing signal. The same signal acts as the memory trace. One strain detects the coincidence of the two inputs, a second maintains the memory through positive feedback in the shared medium, a third reads it out on the conditioned stimulus, a fourth reports the unconditioned response, and a fifth erases the memory on command. We show experimentally that the assembled consortium learns the association, since a stimulus that is silent before training evokes a strong response after pairing. Memory is retained through a medium exchange in which both stimuli are removed, and then the conditioned stimulus alone evokes the response. The reporter is not produced without its input. An erase command returns the response to the background. A population model of the consortium accounts for the sequence of responses and gives design rules for writing, retention, and erasure, and a trade-off in storing memory in a shared extracellular signal. Distributing the operations over strains makes each of them separately tunable and testable and provides a route to microbial communities that learn from their history.

synthetic biology↗
bioRxiv2026

Self-organized criticality in a mammalian RNA-interference circuit

Living systems have been argued to operate near critical points, but their relevance at the cellular level is poorly understood. Critical states allow for a high sensitivity to external inputs and maximal information transfer and display fluctuations at all scales. Critical points are very special, and require the fine tuning of a control parameter, which is hard to reconcile with the robustness of living cells. Self-organized criticality (SOC) proposes that feedback, rather than tuning, brings a system to its critical point. Here we show that RNA interference, in which messenger RNAs compete for shared silencing machinery and so queue for service, together with negative feedback gives rise to SOC in mammalian cells. In a synthetic circuit, a protein repressor whose mRNA competes with the mRNA of a fluorescent reporter that it represses senses the congestion of the queue, closing the feedback loop. Theory and stochastic simulations show that the loop holds the queue near its critical point despite changes in its parameters, and that expression becomes intermittent, with scale-free bursts. Measurements in human cell lines show the predicted power-law distributions of single-cell fluorescence. RNA interference could thus support engineered SOC in animal cells and may also contribute to SOC in natural systems.

synthetic biology↗
bioRxiv2026

An anaerobic cell-free protein synthesis formulation for the in vitro study of oxygen sensitive proteins

Anaerobic microbes harbor unique enzymes and metabolic pathways with potential biotechnological applications, yet these microbes remain difficult to study and engineer. Research is limited by the labor-intensive workflows required to maintain anoxic environments and the lack of genetic tools available for non-model anaerobes. Here, we present an anaerobic cell-free protein synthesis (CFPS) platform for the in vitro study of oxygen-sensitive enzymes. This study establishes two methods for conducting anaerobic CFPS, achieving an anoxic environment by (1) sparging with inert gas or (2) lyophilizing to remove oxygenated water. We show the functionality of our anaerobic CFPS formulation by producing oxygen-independent fluorescent protein reporters and a [4Fe-4S] cluster pyruvate:ferredoxin oxidoreductase (PFOR) with a specific activity of 5.2 {+/-} 0.3 x 10-4 U/{micro}L cell-free extract. This highly modular platform will allow study of diverse oxygen-sensitive proteins and requires only minor modifications to commonly used CFPS workflows.

synthetic biology↗