Research interests
I have been working on theoretical modeling and computer simulations, on (i) physical biology and mechanobiology, and (ii) out-of-equilibrium softmatter physics. My current interest, in particular, is dynamic self-organization processes in living organisms.
<(i) Physical Biology and Mechanobiology >
― You can find more in our group web site: https://mbitheorygroup.wixsite.com/oursite
Theoretical model for the chemotactic migration of a eukaryotic cell
* You can also find the outreach article about this subject on
https://researchoutreach.org/articles/mechanisms-motion-combining-physical-biology-numerical-models/
Living cells can be regarded as self-propelled objects; however, they are not only migrating around but also are taking advantage of detecting the external environment to decide the most favorable migration direction. The most well studied way of environemnt detection is to use the distribution of chemical attractant/repellent molecules. It is known that several kinds of eukaryotic cells, such as a Dictyostelium discoideum cell, migrate toward the gradient direction of the chemoattractant/repellent concentration. This kind of activity is called chemotaxis.
We study the theory on such eukaryotic cell migration with sensing of chemical gradient. In particular, we established a theoretical model for chemotactic migration of a eukaryotic cells with intrinsic polarity, spontaneously formed polarity in the cell body such as the directional bias of proteins. As a result, we found that such intrinsic polarity plays a role to keep the directional "memory" in a finite time and significantly improves the chemotaxis accuracy. This makes it possible to explain high chemotaxis accuracy under faint gradient, known in the Dity cell experiments (TH, et al., Physical Biology, 2014).
We also studied theories on the chemical gradient inference by a elliptically deformable cell and chemotactic migration of such deformable cell (A. Baba, TH and T. Shibata, Phys. Rev. E. 2012) (TH, A. Baba and T. Shibata, Euro. Phys. J. E. 2013). We revealed that taking into account the deformation alters the distribution of migration directions. Expression of distribution function in our result recapitulates the experimental data seen in Dicty cell migration (TH, A. Baba and T. Shibata, Euro. Phys. J. E. 2013).
Theoretical model for dynamic self-organization of migrating cells through cell-cell contact communication
* You can also find the outreach article about this subject on
https://researchoutreach.org/articles/mechanisms-motion-combining-physical-biology-numerical-models/
The emergence of coherent dynamics is a key aspect for understanding mechanisms underlying morphogenesis and functional processes of living systems. Even the fundamental unit of living systems – cells – can form many types of multicellular assemblies with coherent dynamics, which is called dynamic self-organization (DSO). This series of works focus on such DSO exhibited by cells migrating around on a substrate.
I extended the aforementioned model to multicellular cases and proposed a model of chemotactic migration with cell-cell communication. In particular, I investigated collective behavior in the presence of the cell-cell communication called "Contact Inhibition of Locomotion (CIL)" by which, when two cells touched with each other, the cells spontaneously modulate their intrinsic polarities to avoid mutual overlap. As a main result I found that, when the cells are performing CIL, the entire migration direction is ordered spontaneously and the chemotaxis accuracy is significantly improved comparing to each cell’s ability. (TH, Phys. Rev. E, 2019)
Prior studies have suggested that intercellular contact communication, such as contact following and contact inhibition/attraction of locomotion (CIL/CAL), play crucial roles for DSO of migrating cells. In a real-life situation, it is likely that different methods of contact communication are taking place, leading to a wide variety of cellular DSO. I proposes and numerically investigated a unified theoretical model of DSO of migrating cells caused through various types of contact communication. This proposed model can reproduce experimentally observed DSO only by the difference of strengths of each types of contact communication. The simulation further revealed a novel form of collective migration with highly dynamic structures, termed snake-like dynamic assembly (bottom subfigures in the above figure). These findings may open up new ways to understand the generation mechanisms and selection principles underlying emergence of dynamic multicellular organization. (TH, PRL 2020.)
Numerical modeling and simulation on epithelial tissue dynamics
* You can also find the outreach article about this subject on
https://researchoutreach.org/articles/mechanisms-motion-combining-physical-biology-numerical-models/
Bodies of multicellular organisms are covered by epithelial tissue, in which cells are spread in columns, and therefore which look like the polygon from the top view. We applied a mathematical model called a vertex model to study mechanism of collective cell movement in an epithelial tissue. Collaborating with the research group working on experiments in the field of developmental biology, we elucidated the mechanism of rotation of the disc-shaped epithelial tissue observed during morphogenesis of a male Drosophila (K. Sato, TH, E. Maekawa, E. Kuranaga et al. Nat. Comm. 2015) (K.Sato, TH and T. Shibata, Phys. Rev. Lett. 2015). In addition, our numerical simulation predicted that mechanical influence is propagating faster than cells themselves when epithelial cells move cooperatively by this mechanism (TH, E. Kuranaga, T. Shibata. 2017).
Mechanics/dynamics of a cortical actomyosin cytoskeleton
I am investigating the dynamics and motor-induced stress in a cell cortex cytoskeleton. We established a mathematical model of a fluidic network consisting of actin filaments, cross-linking molecules, and myosin motors. Numerical simulations based on this model revealed that motor-induced contractile stress cannot be generated without sufficient amount of crosslinking molecules. We also found that strength of contractile stress depends on the ratio of turnover times of actin filaments and of crosslinking molecules (TH and G. Salbreux, Phys. Rev. Lett. 2016).
I am now focusing on the density-fluctuation dynamics due to contractility and turnover dynamics, which has been found in this model (TH, Mol. Sim. Soc. Jpn “Ensemble” 2018 (in Japanese).).
<(ii) Softmatter Physics and Out-of-equilibrium Physics >
Dynamics and Viscoelasticity of (a) semiflexible polymer chain(s)
Using the same method, we have also studied the case with internal friction, which means the friction that cannot be described by the dissipation with respect to the translatory motion of segments in the solvent and is given by the generalized friction coefficients (TH and T. Ohta, J. Chem. Phys. 2010).
Recent experimental advances for the manipulation of single molecules, such as optical tweezers and atomic force microscopy as well as single-molecule fluorescence, allow us to examine mechanical and relaxational properties of single polymer chains on the nano-scale with piconewton sensitivity. Such experimental data have provided us with new kinds of information which is difficult to obtain in bulk experiments, and lead to better understanding of the relationship between the molecular morphology and the functionality of biological molecules. To elicit a wealth of information from such single polymer measurements, theoretical understandings taking into account the inextensibility and stiffness of a chain beyond the understandings based on Rouse-type models are required.
We are investigating the viscoelasticity of a single semiflexible polymer chain based on the so-called wormlike-chain model, that is the simplest model which takes account of the inextensibility and stiffness of the chain according to the symmetry of a uniform and directionless single chain. We elucidated the linear viscoelasticity of a single wormlike chain based on a multiple scale analysis and obtained the power-law exponents of complex modulus and compliance, which are deviated from those obtained from the Rouse model due to the inextensibility and the stiffness (TH and T. Ohta, JPSJ 2008) (TH and T. Ohta, Macromolecules 2009).
Along this line, I am also investigating the viscoelastic property of a filamentous network. We established a coarse-graining method to calculate storage and loss moduli of the network, by iteratively applying the convolution theory. Using this, we found that the storage and loss moduli of the entire network show the power-law dependency on the frequency of external oscillatory force, regardless of the mechanical characteristics of each filamentous segment. In addition, we found that our results based on this method agree well with the experimental data using the actin gel from earlier papers (TH and R. R. Netz, EPL 2018).
My next target is to investigate viscoelasticity of cytoskeletal networks in cells. Among the most important are chirality of a chain and the effect of active binding proteins, including the myosin II motor on the actin filaments. Development of the above-mentioned theory would enable us to establish a bottom-up theory to investigate the viscoelastic properties of the nonequilibrium cytoskeletal networks and, furthermore, lead to the understanding of the mechanical properties of the living cell.
Dynamics of a single deformable self-propelled particle
Shape, deformation, is one of important observable degrees of freedom of matter. Shape of the matter influences friction resistance from the external environment and flow and chemical-reaction fields, leading to influencing the dynamics of the matter. We have studied theoretically the dynamics of deformable self-propelled particles. Self-propelled particle is the matter which can move around spontaneously consuming the energy input from outside, such as living cells and some chemical and hydrodynamic artificial systems. There are plenty of examples exhibiting deformation during their motions, including eukaryotic cells and artificial systems in the context of softmatter. We are focusing on shape and motion-induced deformation of such object and its feedback to the motion.
For this purpose, we applied theoretical model based on the symmetry argument near the self-propulsion bifurcation point. In particular, we investigated theoretically the dynamics of deformable self-propelled particle in two dimensions and found that a wealth of new types of motile trajectories (TH, M. Matsuo, T. Ohkuma, T. Ohta and M. Sano, Europhys. Lett., 2010). For example, when the spontaneous-deformation induces the translational motion, such objects can exhibit the rectangular and quasi-periodic motions (TH, M. Matsuo, T. Ohkuma, T. Ohta and M. Sano, Europhys. Lett., 2010). We also found that in three dimensions, the deformable self-propelled particle can show both the in-plane circular motion and helical motion and that super-critical bifurcation occurs in between such circular and helical motions (TH, K. Shitara and T. Ohta, Softmatter, 2011).
We also studied the reduction method of the domain dynamics found in an excitable reaction-diffusion system to the above-mentioned symmetry-based model (K. Shitara, TH and T. Ohta, Phys. Rev. E, 2012).
Numerical simulations on collective motion of self-propelled objects
I am also studying collective dynamics of multi self-driven objects. It has been known that, if self-driven objects interact with each other in the way that motile directions of two objects are aligned by collision, the transition on which motile directions of all objects become aligned in the same direction (hereinafter referred to as the state with “directional order”) occurs when the object density is increased. As for such directional order, we investigated the effect of volume exclusion between objects on it based on both experiments using kinesin-microtubule motility assays and numerical simulations. As a result, we found that strong volume exclusion can violate directional order and induce clustered patterns instead of entire ordered state. This research was conducted at Sano Group (Univ. Tokyo), and I contributed to formulate the theoretical basis for data analysis method, to propose the numerical model and to carry out the simulations. (S. Tanida... TH... M. Sano, Phys. Rev. E 2020.)
