The cells and tissues that form an organism are made up of many molecules. On the other hand, living cells and tissues exhibit complex functions and behaviors that cannot be expected from their constituents. How can we understand such phenomenon of life "emergent phenomena" that cannot be reduced to the components? A major paradigm shift is required in the modern biology where elemental reductive understanding is the norm.

The modern biology lies the technology of genetic modification. The development of this technology has made it possible to visualize and manipulate the dynamics of molecules, the building blocks of organisms, at will. This has led to the clarification of the molecular mechanisms that control macroscopic behaviors, including tissue-level phenomena such as development and disease, and cellular-level phenomena such as cell proliferation, death, and movement. However, even if we accumulate the understandings of component molecules, it does not mean that we can understand biological phenomena as a whole, especially their "organismality".

A phenomenon called "self-organization" is typical of organisms that are made up of many cells. This multicellular self-organization is a phenomenon in which multiple cells interact with each other to form functional tissues and organs autonomously. This multicellular self-organization is different from the simple sum of the behaviors of individual cells and can therefore be considered an emergent phenomenon. So what are our cues for understanding this multicellular self-organization?

Multicellular morphogenesis is characterized by I) autonomous patterning of cell populations and II) active morphogenesis of cell populations. Patterning (I) is a phenomenon in which gene expressions and biochemical interactions between cells produce spatiotemporal patterns of cells exhibiting different gene expressions, while morphogenesis (II) is a dynamic change in three-dimensional structures of tissues due to the active forces generated by cells and the mechanical interactions between cells. These two features are common to the general phenomenon of multicellularity and may provide a great hint for understanding multicellular self-organization.

First, a bottom-up application problem is the interaction of (I) and (II) "mechanochemical coupling". The change in gene expression of a cell caused by the pattern formation in (I) simultaneously changes the active force produced by that cell. This change in force changes the three-dimensional structure of the tissue caused by (II) morphogenesis. However, the biochemical interactions between cells in (I) occur inside a three-dimensional tissue, which further alters the pattern formation in (I). Thus, the combination of pattern formation in (I) and morphogenesis in (II) is likely to lead to self-organization due to the autonomy of the entire system as described above. By using mathematical models, we have found a mechanism by which the interaction between pattern formation and morphogenesis produces a phenomenon different from the sum of the two (Sci Rep 2017).

In addition, the hierarchical structure of the tissues reminds us "local-whole cooperation," an interaction between the entire tissue and the constituent molecules and cells. Although the patterning and morphogenesis of the entire tissue changes depending on the active behaviors of individual molecules and cells, it is difficult to control the behaviors of the entire tissue appropriately with the unidirectional regulation from the microscopic to macroscopic scales, and feedback from the macroscopic to microscopic scales is necessary. By studying stem cell organoids and mathematical models, we found a mechanism by which morphological changes throughout the tissue feed back into active force generation in individual cells (Sci Adv 2018).

Our research has revealed some of the "mechanochemical coupling" and "local-whole cooperation" that are the basis of self-organization. However, we are far from understanding its essence. One of the reasons for this may be the complexity of multicellular self-organization. Therefore, we are building new experimental systems that simplify complex self-organizing processes while preserving their essence. We are also developing new measurement and prediction techniques to quantitatively evaluate complex self-organizing processes. In addition, we are mobilizing our proprietary technologies to understand the fundamental principles of multicellular dynamics in embryogenesis and carcinogenesis.

Our laboratory is interested in shaping of living organisms. In particular, in the shaping of multicellular organisms, each cell interacts with each other to autonomously form functional tissues and organs (self-organization). Our goal is to understand this multicellular self-organization from various angles. To achieve this goal, we are working on novel approaches that integrate technologies from biology, physics, and engineering, such as stem cell organoids that reproduce embryonic tissues in vitro and mechanics-based simulations that predict multicellular dynamics.

I. Mouse ES cell and human iPS cell-derived 3D tissue culture

In the cultur, we let cells to create 3D tissues in a self-organizing manner and observe multi-cellular interactions during morphogenesis. We aim to understand the self-organizing multicellular dynamics from a viewpoints of the molecular biology, cell biology, and biomechanics, using gene modification and fluorescence imaging techniques.

II. Mechanics-based simulation bridging molecules, cells and tissues

We are developing new methods of mechanics-based simulations to analyze 3D multi-cellular dynamics such as embryogenesis and carcinogenesis. By combining this technology with biological experiments, we aim to reveal new aspects of the shaping of living organisms.

III. Local mechanical and biochemical perturbations to tissues

Using atomic force microscopy (AFM) and motorized manipulators, we apply mechanical and biochemical perturbations to the local regions of the three-dimensional tissues and observe their responses. These perturbations aim to understand the cross-scale interactions between molecules, cells, and tissues that are key for self-organization.

IV. Theoretical analyses of multicellular dynamics

Based on the quantitative data and understandings obtained from experiments and simulations, we extract and formulate various elementary processes of multi-cellular dynamics. We aim to discover the principles common to a wide range of physiology and pathophysiology.