Computational Science Research Program, RIKEN
All living things consist of units called cells. More than 10 million kinds
of living things including single-cell organisms such as Escherichia
coli and multicellular organisms such as humans exist on the earth,
and the functions and forms of cells are different so that they are
optimum for their living things survival. However, it is known that
living things basic living cell functions have many things in common.
A cell has a very complicated and compact structures, and in the cell, various biochemical reactions occurs actively for each compartment which is known as an organelle. Due to this, molecules and reactions are differentiated to implement various living functions efficiently.
So far, much cell simulation research ignoring cell structures has been done by grinding up organs, the aggregates of cells, to understand the biological systems of organisms and to explore methods of treating diseases. In the cells, life is maintained by complex phenomena such as biochemical reactions (metabolism) and signaling. To reproduce these biochemical reactions, many simulators were developed, and it became possible to replicate intracellular metabolism and signaling. However, these simulators calculate a nondimensionalized field and replicate a chemical reaction uniformly in the cell, a so-called 'closed bag'. In actual cells, biochemical reactions differ for each organelle, and uneven reactions go on in the cell depending on the intracellular transfer of substances, inside and outside the cell, and entry and exit of substance from and to the inside and outside of the cell. We, the Cell Scale Research and Development Team, have been looking at these things, and are now developing the RIKEN Integrated Cell Simulator (RICS) which aims to perfect an intracellular time-space simulation. With this system, we undertook a coupled analysis of intracellular biochemical reactions and substance diffusions with the equations of reaction diffusion. This system uses the voxel analysis framework developed by the VACD research program of RIKEN for spatial expression, which is a simulation system that can represent the special complex space structures of the cell.
With this system, using the cell morphology obtained from actual microscopic data, we simulated the transporters, reactions and diffusion of calcium ion (Ca2+) in the cell. As concerns the cell morphology, we acquired the cell morphology and the form of the nucleus and mitochondria with a confocal laser microscope using a HepG2 cell, human liver-derived cells (Figure 1). The nucleus is the largest structure in the cell, and it packs DNA. Mitochondria have the function of producing energy for cellular activity, and are an important location for biochemical reactions such as metabolism. We prepared three-dimensional Volume data from microscopic images to use in the present calculation (Figure 2). We established 10 molecules involved in buffering reactions in the cell and 24 biochemical reactions. A channel passing Ca2+ only was localized in part of the cell membrane shown by an arrow in Figure 2, and simulated by influx of Ca2+.
The result of simulation is shown in Figure 3. When the buffering reaction of Ca2+ in the cell was set up (expressed as "reaction present"), the apparent diffusion speed of Ca2+ in the cell was decreased as compared with the case of no biochemical reaction (expressed as "reaction absent"). This suggested that kinetics of Ca2+ close to that in actual cells can be simulated.
This RICS makes it possible to calculate the phenomena occurring in cells such as biochemical reactions and diffusions, considering their location. In the future, we want to model various cell functions, and to show that the model can be utilized to elucidate the cause of drug reactions and disease. Moreover, we want to make this system a tool that can examine a mass of cells that functions as a tissue.
Figure 1 : Cross section image of a cell photographed using a confocal laser microscope
Figure 2 : Cell morphology reconstructed threedimensionally from successive cross section images of cells
Figure 3: Time-course of Ca2+ concentrations (volume rendering)