Information Thermodynamics of the Cell Signal Transduction as a Szilard Engine

Distributed physiology and the molecular basis of social life in eusocial insects

The traditional focus of physiological and functional genomic research is on molecular processes that play out within a single multicellular organism. In the colonial (eusocial) insects such as ants, bees, and termites, molecular and behavioral responses of interacting nestmates are tightly linked, and key physiological processes are regulated at the scale of the colony. Such colony-level physiological processes regulate nestmate physiology in a distributed fashion, through various social communication mechanisms. As a result of physiological decentralization over evolutionary time, organismal mechanisms, for example related to pheromone detection, hormone signaling, and neural signaling pathways, are deployed in novel contexts to influence nestmate and colony traits. Here we explore how functional genomic, physiological, and behavioral studies can benefit from considering the traits of eusocial insects in this light. We highlight functional genomic work exploring how nestmate-level and colony-level traits arise and are influenced by interactions among physiologically-specialized nestmates of various developmental stages. We also consider similarities and differences between nestmate-level (organismal) and colony-level (superorganismal) physiological processes, and make specific hypotheses regarding the physiology of eusocial taxa. Integrating theoretical models of distributed systems with empirical functional genomics approaches will be useful in addressing fundamental questions related to the evolution of eusociality and collective behavior in natural systems.

Entropy in Cell Biology: Information Thermodynamics of a Binary Code and Szilard Engine Chain Model of Signal Transduction

A model of signal transduction from the perspective of informational thermodynamics has been reported in recent studies, and several important achievements have been obtained. The first achievement is that signal transduction can be modelled as a binary code system, in which two forms of signalling molecules are utilised in individual steps. The second is that the average entropy production rate is consistent during the signal transduction cascade when the signal event number is maximised in the model. The third is that a Szilard engine can be a single-step model in the signal transduction. This article reviews these achievements and further introduces a new chain of Szilard engines as a biological reaction cascade (BRC) model. In conclusion, the presented model provides a way of computing the channel capacity of a BRC.

The Conservation of Average Entropy Production Rate in a Model of Signal Transduction: Information Thermodynamics Based on the Fluctuation Theorem

Cell signal transduction is a non-equilibrium process characterized by the reaction cascade. This study aims to quantify and compare signal transduction cascades using a model of signal transduction. The signal duration was found to be linked to step-by-step transition probability, which was determined using information theory. By applying the fluctuation theorem for reversible signal steps, the transition probability was described using the average entropy production rate. Specifically, when the signal event number during the cascade was maximized, the average entropy production rate was found to be conserved during the entire cascade. This approach provides a quantitative means of analyzing signal transduction and identifies an effective cascade for a signaling network.