Ion currents associated with channel proteins in the presence of membrane potential are ubiquitous in cellular and organelle membranes. When an ion current occurs through a channel protein, Joule heating should occur. However, this Joule heating seems to have been largely overlooked in biology. Here we show theoretical investigation of Joule heating involving channel proteins in biological processes. We used electrochemical potential to derive the Joule’s law for an ion current through an ion transport protein in the presence of membrane potential, and we suggest that heat production and absorption can occur. Simulation of temperature distribution around a single channel protein with the Joule heating revealed that the temperature increase was as small as <10^–3 K, although an ensemble of channel proteins was suggested to exhibit a noticeable temperature increase. Thereby, we theoretically investigated the Joule heating of systems containing ensembles of channel proteins. Nerve is known to undergo rapid heat production followed by heat absorption during the action potential, and our simulation of Joule heating for a squid giant axon combined with the Hodgkin-Huxley model successfully reproduced the feature of the heat. Furthermore, we extended the theory of Joule heating to uncoupling protein 1 (UCP1), a solute carrier family transporter, which is important to the non-shivering thermogenesis in brown adipose tissue mitochondria (BATM). Our calculations showed that the Joule heat involving UCP1 was comparable to the literature calorimetry data of BATM. Joule heating of ion transport proteins is likely to be one of important mechanisms of cellular thermogenesis.

With the recent global outbreak of COVID-19, there is an urgent need to establish a versatile diagnostic method for viral infections. Gene amplification test or antigen test are widely used to diagnose viral infections; however, these methods generally have technical drawbacks either in terms of sensitivity, accuracy, or throughput. To address this issue, we recently developed an amplification-free digital RNA detection method (SATORI), which can identify and detect viral genes at the single-molecule level in approximately 9 min, satisfying almost all detection performance requirements for the diagnosis of viral infections. In addition, we also developed practical platforms for SATORI, such as an automated platform (opn-SATORI) and a low-cost compact fluorescence imaging system (COWFISH), with the aim of application in clinical settings. Our latest technologies can be inherently applied to diagnose a variety of RNA viral infections, such as COVID-19 and Influenza A/B, and therefore, we expect that SATORI will be established as a versatile platform for point-of-care testing of a wide range of infectious diseases, thus contributing to the prevention of future epidemics. This article is an extended version of the Japanese article published in the SEIBUTSU BUTSURI Vol. 63, p. 115–118 (2023).

Single-cell behaviors cover many biological functions, such as cell division during morphogenesis and tissue metastasis, and cell migration during cancer cell invasion and immune cell responses. Symmetry breaking of the positioning of organelles and the cell shape are often associated with these biological functions. One of the main players in symmetry breaking at the cellular scale is the actin cytoskeleton, comprising actin filaments and myosin motors that generate contractile forces. However, because the self-organization of the actomyosin network is regulated by the biochemical signaling in cells, how the mechanical contraction of the actin cytoskeleton induces diverse self-organized behaviors and drives the cell-scale symmetry breaking remains unclear. In recent times, to understand the physical underpinnings of the symmetry breaking exhibited in the actin cytoskeleton, artificial cell models encapsulating the cytoplasmic actomyosin networks covered with lipid monolayers have been developed. By decoupling the actomyosin mechanics from the complex biochemical signaling within living cells, this system allows one to study the self-organization of actomyosin networks confined in cell-sized spaces. We review the recent developments in the physics of confined actomyosin networks and provide future perspectives on the artificial cell-based approach. This review article is an extended version of the Japanese article, The Physical Principle of Cell Migration Under Confinement: Artificial Cell-based Bottom-up Approach, published in SEIBUTSU BUTSURI Vol. 63, p. 163–164 (2023).

Adaptability to changing environments is one of the universal characteristics of living organisms. Because individual modes of adaptation are diverse, a unified understanding of these diverse modes is essential to comprehend adaptation. Adaptations can be categorized from at least two perspectives with respect to information. One is the passivity and activity of adaptation and the other is the type of information transmission. In Darwinian natural selection, organisms are selected among randomly generated traits under which individual organisms are passive in the sense that they do not process any environmental information. On the other hand, organisms can also adapt by sensing their environment and changing their traits. This is an active adaptation in that it makes use of environmental information. In terms of information transfer, adaptation through phenotypic heterogeneity, such as bacterial bet-hedging, is intragenerational in which traits are not passed on to the next generation. In contrast, adaptation through genetic diversity is intergenerational. The theory of population dynamics enables us to unify these various modes of adaptations and their properties can be analyzed qualitatively and quantitatively using techniques from quantitative genetics and information thermodynamics. In addition, such methods can be applied to situations where organisms can learn from past experiences and pass them on from generation to generation. In this work, we introduce the unified theory of biological adaptation based on population dynamics and show its potential applications to evaluate the fitness value of information and to analyze experimental lineage tree data. Finally, we discuss future perspectives for its development. This review article is an extended version of the Japanese article in SEIBUTSU BUTSURI Vol. 57, p. 287–290 (2017).

Neutron crystallography is a highly effective method for visualizing hydrogen atoms in proteins. In our recent study, we successfully determined the high-resolution (1.2 Å) neutron structure of high-potential iron-sulfur protein, refining the coordinates of some amide protons without any geometric restraints. Interestingly, we observed that amide protons are deviated from the peptide plane due to electrostatic interactions. Moreover, the difference in the position of the amide proton of Cys75 between reduced and oxidized states is possibly attributed to the electron storage capacity of the iron-sulfur cluster. Additionally, we have discussed about the rigidity of the iron-sulfur cluster based on the results of the hydrogen-deuterium exchange. Our research underscores the significance of neutron crystallography in protein structure elucidation, enriching our understanding of protein functions at an atomic resolution.