Biophysics and physicobiology最新文献

Chemical tongues are emerging powerful bioanalytical tools that mimic the mechanism of the human taste system to recognize the comprehensive characteristics of complex biological samples. By using an array of chromogenic or fluorogenic probes that interact non-specifically with various components in the samples, this tool generates unique colorimetric or fluorescence patterns that reflect the biological composition of a sample. These patterns are then analyzed using multivariate analysis or machine learning to distinguish and classify the samples. This review focuses on our efforts to provide an overview of the fundamental principles of chemical tongues, probe design, and their applications as versatile tools for analyzing proteins, cells, and bacteria in biological samples. Compared to conventional methods that rely on specific targeting (e.g., antibodies or enzymes) or comprehensive omics analyses, chemical tongues offer advantages in terms of cost and the ability to analyze samples without the need for specific biomarkers. The complementary use of chemical tongues and conventional methods is expected to enable a more detailed understanding of biological samples and lead to the elucidation of new biological phenomena.

Plant myosins have higher velocities than animal myosins. Among them, myosins in freshwater algae of the genus Chara have extremely high velocities. We have biochemically studied myosins that perform high-speed movements in the alga Chara. Our studies have elucidated the structural and enzymatic basis for the fast movement of Chara myosins. This review outlines the history leading to the discovery of the fastest myosin, algae Chara myosin XI, and the structure-function correlation of the fastest myosin. This review article is an extended version of the Japanese article, "Structure-function Relationship of the Fastest Myosin" by Ito et al., published in SEIBUTSU BUTSURI Vol. 63, p. 91-96 (2023).

Mycoplasma mobile is a parasitic bacterium that forms gliding machinery on the cell pole and glides on a solid surface in the direction of the cell pole. The gliding machinery consists of both internal and surface structures. The internal structure is divided into a bell at the front and chain structure extending from the bell. In this study, the internal structures prepared under several conditions were analyzed using negative-staining electron microscopy and electron tomography. The chains were constructed by linked motors containing two complexes similar to ATP synthase. A cylindrical spacer with a maximum diameter of 6 nm and a height of 13 nm, and anonymous linkers with a diameter of 0.9-8.3 nm and length of 14.7±6.9 nm were found between motors. The bell is bowl-shaped and features a honeycomb surface with a periodicity of 8.4 nm. The chains of the motor are connected to the rim of the bell through a wedge-shaped structure. These structures may play roles in the assembly and cooperation of gliding machinery units.

Single-molecule imaging in living cells is an effective tool for elucidating the mechanisms of cellular phenomena at the molecular level. However, the analysis was not designed for throughput and requires high expertise, preventing it from reaching large scale, which is necessary when searching for rare cells that induce singularity phenomena. To overcome this limitation, we have automated the imaging procedures by combining our own focusing device, artificial intelligence, and robotics. The apparatus, called automated in-cell single-molecule imaging system (AiSIS), achieves a throughput that is a hundred-fold higher than conventional manual imaging operations, enabling the analysis of molecular events by individual cells across a large population. Here, using AiSIS, we demonstrate the single-molecule imaging of molecular behaviors and reactions related to tau protein aggregation, which is considered a singularity phenomenon in neurological disorders. Changes in the dynamics and kinetics of molecular events were observed inside and on the basal membrane of cells after the induction of aggregation. Additionally, to detect rare cells based on the molecular behavior, we developed a method to identify the state of individual cells defined by the quantitative distribution of molecular mobility and clustering. Using this method, cellular variations in receptor behavior were shown to decrease following ligand stimulation. This cell state analysis based on large-scale single-molecule imaging by AiSIS will advance the study of molecular mechanisms causing singularity phenomena.

This paper describes a method for recording X-ray diffraction patterns from a small amount of fibrous protein materials while being oriented by using a micro shear-flow cell. This cell consists of two concentrically arranged glass tubes. The inner tube is stationary, while the outer one rotates at a high speed. The gap between the two tubes is about 100 μm, into which the suspension of fibrous protein materials is injected. By using synchrotron-radiation X-ray microbeams (diameter, 10 μm), clear diffraction images from oriented protein materials can be recorded. The required volume of the sample is only about 10 μl. This method can also be combined with the laser-flash photolysis of caged compounds. Examples of application of this method to the flagella of a green alga Chlamydomonas, and sperm of a tunicate Ciona are presented.

Blood cancer is a condition in which white blood cells grow uncontrollably. Tumor treating fields (TTF) are a modality of cancer treatment that utilizes electric fields to target malignant cells. To optimize the efficacy of TTF, it is necessary to investigate the distribution of electric field through varying electrode configurations and input parameters. This allows for enhancement of electric field intensity in targeted areas while minimizing intensity in sensitive areas. Analysis of electric field distribution was conducted through simulation of brachial models with varying electrode configurations and input parameters, utilizing the COMSOL Multiphysics 5.4 software. Additionally, investigations were carried out to assess tissue dose density. The dose density value at primary target for all electrode configurations and input parameters do not exceed the threshold value (770 W/m³), whereas the electric field value at the primary target satisfied the threshold value (100 V/m) on the system that used 4 plate-shaped electrodes and arm contour-shaped electrodes with an input voltage of 20 V, and at the input voltage 15 V, only 4 arm contour-shaped electrodes that satisfied the threshold value. An increase in input voltage, electrodes addition, and electrodes adjustment to skin contour shape result in an enhancement of electric field distribution and average electric field value at primary targets.

Phosphorylation regulates protein function by modulating stereospecific interactions between protein-protein or enzyme-ligand. On the other hand, many bioinformatics studies have demonstrated that phosphorylation preferably occurs in intrinsically disordered regions (IDRs), which do not have any secondary and tertiary structures. Although studies have demonstrated that phosphorylation changes the phase behavior of IDRs, the mechanism, which is distinct from the "stereospecific" effect, had not been elucidated. Here, we describe how phosphorylation in IDRs regulates the protein function by modulating phase behavior. Mitotic phosphorylation in the IDRs of Ki-67 and NPM1 promotes or suppresses liquid-liquid phase separation, respectively, by altering the "charge blockiness" along the polypeptide chain. The phosphorylation-mediated regulation of liquid-liquid phase separation by enhancing or suppressing "charge blockiness," rather than by modulating stereospecific interactions, may provide one of the general mechanisms of protein regulation by posttranslational modifications and the role of multiple phosphorylations.

Singularity biology is a scientific field that targets drastic state changes in multicellular systems, aiming to discover the key cells that induce the state change and investigate the mechanisms behind them. To achieve this goal, we developed a trans-scale optical imaging system (trans-scale scope), that is capable of capturing both macroscale changes across the entire system and the micro-scale behavior of individual cells, surpassing the cell observation capabilities of traditional microscopes. We developed two units of the trans-scale scope, named AMATERAS-1 and -2, which demonstrated the ability to observe multicellular systems consisting of over one million cells in a single field of view with sub-cellular resolution. This flagship instrument has been used to observe the dynamics of various cell species, with the advantage of being able to observe a large number of cells, allowing the detection and analysis of rare events and cells such as leader cells in multicellular pattern formation and cells that spontaneously initiate calcium waves. In this paper, we present the design concept of AMATERAS, the optical configuration, and several examples of observations, and demonstrate how the strength-in-numbers works in life sciences.

Considering the fundamental mechanism causing singularity phenomena, we performed the following abduction: Assuming that a multicellular system is driven by spontaneous fluctuation of each cell and dynamic interaction of the cells, state transition of the system would be experimentally predictable from cellular heterogeneity. This study evaluates the abductive hypothesis by analyzing cellular heterogeneity to distinguish pre-state of state transition of differentiating cells with Raman spectroscopy and human induced pluripotent stem cells (hiPSCs) technique. Herein, we investigated the time development of cellular heterogeneity in Raman spectra during cardiomyogenesis of six hiPSC lines and tested two types of analyses for heterogeneity. As expected, some spectral peaks, possibly attributed to glycogen, correctively exhibited higher heterogeneity, prior to intensity changes of the spectrum in the both analyses in the all cell-lines tested. The combination of spectral data and heterogeneity-based analysis will be an approach to the arrival of biology that uses not only signal intensity but also heterogeneity as a biological index.

In collective systems, influence of individuals can permeate an entire group through indirect interactionscom-plicating any scheme to understand individual roles from observations. A typical approach to understand an individuals influence on another involves consideration of confounding factors, for example, by conditioning on other individuals outside of the pair. This becomes unfeasible in many cases as the number of individuals increases. In this article, we review some of the unforeseen problems that arise in understanding individual influence in a collective such as single cells, as well as some of the recent works which address these issues using tools from information theory.