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Biology subjects

Gehri, M.

Publications and source records attributed to Gehri, M..

2 recordsLinked to original sources

Entropy production constrains information throughput in gene regulation

Biochemical systems process signals through stochastic reaction dynamics that are inherently continuous in time and often exhibit memory, feedback, and nonequilibrium driving. At the same time, they are frequently modeled by effective reactions, e.g., multi-step processes such as transcription are treated as single events, while energetic bookkeeping is commonly omitted. Moreover, mesoscopic dissipation estimates are highly sensitive to whether coarse-graining and reservoir coupling are performed in a thermodynamically consistent way. Together, these features complicate the direct application of classical Shannon information theory and stochastic thermodynamics "as is" to biochemical reaction networks. This paper provides a self-contained route from first principles to a practically usable framework for studying information transmission through chemical reaction networks (CRNs) under energetic constraints. In particular, we discuss and extend the notions of classical information theory, methodically progressing to a level of generality that is necessary for the theme of causal communication through general CRNs. We then derive expressions for mutual information and directed information between bipartite CRN trajectories of disjoint sets of molecular species and show that the MI diverges without bipartiteness. These expressions account for cases in which different reactions are indistinguishable after projection to the respective subnetworks or where multiple driving mechanisms produce the same observable effect. We finally introduce a rigorous, operational Shannon-style continuous-time chemical communication model: messages are encoded by time-dependent chemostat protocols for a set of signaling molecules, the causal channel law is an immutable property of the reaction dynamics, and channel capacity is posed as an optimization over causal chemical encoders subject to thermodynamic costs of encoding and transmission. Trajectory information measures and the operational channel capacity are related by a Fano-type converse theorem. Complementary, we formulate the dual perspective of minimum-energy-per-bit necessary for reliable communication. A tractable promoter-switching example illustrates the practical application. Our work provides a formal and general framework to obtain universal energetic bounds for reliable communication in biochemical systems.

systems biology↗

Energy Aware Technology Mapping of Genetic Logic Circuits

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

synthetic biology↗