Worm Breeder's Gazette 14(5): 30 (February 1, 1997)
These abstracts should not be cited in bibliographies. Material contained herein should be treated as personal communication and should be cited as such only with the consent of the author.
Sony Computer Science Laboratory 3-14-13 Higashi-Gotanda, Shinagawa Tokyo 141 Japan
When Sydney Brenner proposed a new project to investigate C. elegans to the Medical Research Council, he chose it because it is the simplest possible differentiated organism. The decision was right, and now C. elegans is the most well investigated multi-cellular organism. Since the proposal to use this organism as a model organism, a series of research projects on various aspects of this organism were inititated. As a result, the complete cell lineage, neural circuits, and various genes and their functions were identified, and the complete DNA sequencing and the gene expression for each cell at different times in the embryogenesis will be identified in a few years. Despite the fact it is the simplest possible differentiated organism, it is still too complex to understand the dynamics and interactions taking place. Given the abundance of data, we consider that introducing a synthetic approach will further enhance our understanding of the underlying principles of development and behavior of C. elegans. We have started a project which we have named the Perfect C. elegans project, which aims at implementing detailed model of C. elegans on a computer system. As a first step, we have developed a computer graphics visualization system of embryogenesis on C. elegans. The system is based on existing data on the development of C. elegans, and missing information is interpolated using a simulation technique. The current system generates computer graphics images of the embryogenesis of C. elegans up until 500 minutes after the first cell division. The three dimensional (3D) visualization system is an appropriate starting point because it provides a 3D model of C. elegans, so that the cell-cell interaction dynamics, at both the physical and chemical level, can be implemented on top of this model. This would greatly help research on development. The current system is based on the cell lineage and cell location data published in Sulton's papper published in 1983. We are also working on the newer data from the Sanger Centre. It is a non-trivial task to create a reasonably accurate computer graphics image based on the available data because information necessary to create three dimensional models is missing. Following information were available: (1) the complete cell lineage chart, (2) hand-drawing pictures in 2-1/2 dimension (all 28 cells at 100 minutes, 55 out of 180 cells at 200 minutes, 137 out of more than 350 cells at 260 minutes, 156 out of more than 350 cells at 270 minutes, most cells at 430 minutes), qualitative descriptions of the shape of embryo, qualitative description of disparity in the size of divided cells, and general information on migration. In order to create an accurate computer graphics images, we need three dimensional data on the position and shape of the cell in a series of time steps. Obviously, such data is not available. The challenge is to how estimate reasonably accurate cell position data from available information. Our strategy to overcome this problem is to merge simulation with data. First, in order to assure the accuracy of the computer graphics image, cells must be in the position given in the observed data. Second, various simulation techniques are used to fill in the missing information, such as the location of cells not provided in the data. Essentially, this part of the system computes forces between cells, such as the force which pushes back colliding cells (equations not shown). However, if only dynamic simulation is used to decide the position of cells, some cells will not be in the position described in the observed data, because of cell movement. In order to compensate for this discrepancy, the force that a cell is supposed to generate for its movement was estimated using inverse kinematic techniques, and added to the cell's force vector. The motions of the cell are computed as in the case of the motion of objects in a viscous fluid. Along with other simulation techniques, the system creates reasonably realistic 3D computer graphics animation image from the first cell division to about 500 min after the first cell division. Cells are colored by their cell fate, or by their founder cells. Due to the animation capability, movement of the cell can be clearly identified, and helps intuitive understanding of the behaviors of cells during embryogenesis. We are now working on more accurate simulation using newer data sets, as well as implementation of genetic information into the simulation.