Quantitative analysis of nonlinear optical input/output of a quantum-dot network based on the echo state property.

The echo state property, which is related to the dynamics of a neural network excited by input driving signals, is one of the well-known fundamental properties of recurrent neural networks. During the echo state, the neural network reveals an internal memory function that enables it to remember past inputs. Due to the echo state property, the neural network will asymptotically update its condition from the initial condition and is expected to exhibit temporally nonlinear input/output. As a physical neural network, we fabricated a quantum-dot network that is driven by sequential optical-pulse inputs and reveals corresponding outputs, by random dispersion of quantum-dots as its components. In the network, the localized optical energy of excited quantum-dots is allowed to transfer to neighboring quantum-dots, and its stagnation time due to multi-step transfers corresponds to the hold time of the echo state of the network. From the experimental results of photon counting of the fluorescence outputs, we observed nonlinear optical input/output of the quantum-dot network due to its echo state property. Its nonlinearity was quantitatively verified by a correlation analysis. As a result, the relation between the nonlinear input/outputs and the individual compositions of the quantum-dot network was clarified.

Intracellular Protein-Labeling Probes for Multicolor Single-Molecule Imaging of Immune Receptor-Adaptor Molecular Dynamics.

Single-molecule imaging (SMI) has been widely utilized to investigate biomolecular dynamics and protein-protein interactions in living cells. However, multicolor SMI of intracellular proteins is challenging because of high background signals and other limitations of current fluorescence labeling approaches. To achieve reproducible intracellular SMI, a labeling probe ensuring both efficient membrane permeability and minimal non-specific binding to cell components is essential. We developed near-infrared fluorescent probes for protein labeling that specifically bind to a mutant ß-lactamase tag. By structural fine-tuning of cell permeability and minimized non-specific binding, SiRcB4 enabled multicolor SMI in combination with a HaloTag-based red-fluorescent probe. Upon addition of both chemical probes at sub-nanomolar concentrations, single-molecule imaging revealed the dynamics of TLR4 and its adaptor protein, TIRAP, which are involved in the innate immune system. Statistical analysis of the quantitative properties and time-lapse changes in dynamics revealed a protein-protein interaction in response to ligand stimulation.

Integrin LFA-1 regulates cell adhesion via transient clutch formation.

Integrin LFA-1 regulates immune cell adhesion and trafficking by binding to ICAM-1 upon chemokine stimulation. Integrin-mediated clutch formation between extracellular ICAM-1 and the intracellular actin cytoskeleton is important for cell adhesion. We applied single-molecule tracking analysis to LFA-1 and ICAM-1 in living cells to examine the ligand-binding kinetics and mobility of the molecular clutch under chemokine-induced physiological adhesion and Mn(2+)-induced tight adhesion. Our results show a transient LFA-1-mediated clutch formation that lasts a few seconds and leads to a transient lower-mobility is sufficient to promote cell adhesion. Stable clutch formation was observed for Mn(2+)-induced high affinity LFA-1, but was not required for physiological adhesion. We propose that fast cycling of the clutch formation by intermediate-affinity integrin enables dynamic cell adhesion and migration.

Automated single-molecule imaging in living cells.

An automated single-molecule imaging system developed for live-cell analyses based on artificial intelligence-assisted microscopy is presented. All significant procedures, i.e., searching for cells suitable for observation, detecting in-focus positions, and performing image acquisition and single-molecule tracking, are fully automated, and numerous highly accurate, efficient, and reproducible single-molecule imaging experiments in living cells can be performed. Here, the apparatus is applied for single-molecule imaging and analysis of epidermal growth factor receptors (EGFRs) in 1600 cells in a 96-well plate within 1 day. Changes in the lateral mobility of EGFRs on the plasma membrane in response to various ligands and drug concentrations are clearly detected in individual cells, and several dynamic and pharmacological parameters are determined, including the diffusion coefficient, oligomer size, and half-maximal effective concentration (EC50). Automated single-molecule imaging for systematic cell signaling analyses is feasible and can be applied to single-molecule screening, thus extensively contributing to biological and pharmacological research.

Dynamic polymorphism of actin as activation mechanism for cell motility.

Actin filament dynamics are crucial in cell motility. Actin filaments, and their bundles, networks, and gels assemble and disassemble spontaneously according to thermodynamic rules. These dynamically changing structures of actin are harnessed for some of its functions in cells. The actin systems respond to external signals, forces, or environments by biasing the fluctuation of actin assembly structures. In this study, dynamic conformation of actin molecules was studied by monitoring conformational dynamics of actin molecules at the single molecule level in real time. Actin conformation spontaneously fluctuates between multiple conformational states. Regarding myosin motility, the dynamic equilibrium of actin conformation was interpreted as between states that activates and inhibits the motility. The binding of myosin to actin filaments activates myosin motility by shifting the conformational fluctuation of actin towards the state that activates the motility. Thus, the activation mechanism based on thermal fluctuation is suggested at molecular level as well as at cellular level.

A Computational Framework for Bioimaging Simulation.

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

Dynamic polymorphism of single actin molecules in the actin filament.

Actin filament dynamics are critical in cell motility. The structure of actin filament changes spontaneously and can also be regulated by actin-binding proteins, allowing actin to readily function in response to external stimuli. The interaction with the motor protein myosin changes the dynamic nature of actin filaments. However, the molecular bases for the dynamic processes of actin filaments are not well understood. Here, we observed the dynamics of rabbit skeletal-muscle actin conformation by monitoring individual molecules in the actin filaments using single-molecule fluorescence resonance energy transfer (FRET) imaging with total internal reflection fluorescence microscopy (TIRFM). The time trajectories of FRET show that actin switches between low- and high-FRET efficiency states on a timescale of seconds. If actin filaments are chemically cross-linked, a state that inhibits myosin motility, the equilibrium shifts to the low-FRET conformation, whereas when the actin filament is interacting with myosin, the high-FRET conformation is favored. This dynamic equilibrium suggests that actin can switch between active and inactive conformations in response to external signals.