1. The beginning of the research (around 2006)
The prevailing notion that “the first life arose from a primordial soup of organic matter that underwent a series of alternating dry and wet cycles, eventually giving rise to a cell-like structure that, upon reaching a certain level of complexity, became life” fails to provide any meaningful explanation for the mechanisms underlying cell formation.
Neither biology, physics, nor the study of complex systems has shed clear light on the emergent process of life.
Driven by an insatiable curiosity about the genesis of the first cells, I have long sought to unravel this mystery. However, my background precludes me from pursuing this research through experimental means, prompting me to explore the potential of computational modeling.
Recognizing the limitations of differential equation-based approaches in addressing this intricate problem, I opted to investigate a cellular automaton model, a type of discrete model.
2. My Research History
(1) Self-replication of cell-like structures in a cellular automaton model (2010)
However, this research was limited by the complexity of its transition rules.
Figure 1 Cellular automaton model of self-replication of cell-like shape
[1] Takeshi Ishida, Simulating self-reproduction of cells in a two-dimensional cellular automaton, Journal of Robotics and Mechatronics, Vol.22, No.5(2010), pp.669-676
(2) Cell replication using a hybrid model combining the Grayscott model (difference equation model) and the cellular automaton model (2011) (published in Japanese)
Introduced a self-organizing mechanism into the cellular automaton model, enabling the simplification of transition rules.
Figure 2 Results of hybrid model use of cellular automata model and Gray Scott model
[2] Takeshi Ishida, Self-Reproduction Cellular Automata Model to Construct Artificial Cell
(Hybrid Model Use of Cellular Automata Model and Gray Scott Model) (published in Japanese)
https://doi.org/10.1299/kikaic.77.1706
(3) Development of a cellular emergence model for virtual particle systems (2014)
Employed the Young model, which can simulate Turing pattern formation in cellular automata, to construct a discrete model simulation and connect particles. While successful in replicating cellular emergence, the process was not without its challenges.
Figure 3 Result of discrete model simulation of Young model and connected particles
[3] Takeshi Ishida, Simulations of living cell origins using a cellular automata model, Origins of Life and Evolution of Biospheres, 2014 Apr;44(2):125-41.
https://link.springer.com/article/10.1007/s11084-014-9372-7
(4) Proposal of a novel model generating more lifelike movements (2018)
I proposed a Turing pattern model (Young model) augmented with life-game properties, henceforth referred to as the Ishida model. Extremely simple transition rules enabled the reproduction of cells exhibiting movement and division.
Figure 4 A self-replicating model that combines the Turing pattern model and Conway’s life game.
[4] Ishida, Takeshi, Possibility of controlling self-organized patterns with totalistic cellular automata consisting of both rules like game of life and rules producing Turing patterns, Micromachines, 9, 339, (2018), https://doi.org/10.3390/mi9070339
(5) Development of a stochastic multiset model for cell replication: henceforth referred to as the cell emergence model (2020)
To achieve cell emergence and replication, the Ishida model was replaced by a reaction network comprising 15 virtual molecules and 2 polymerized molecules.
Figure 5. Simulation of cell shape emergence by “multiset artificial chemical lattice model” .
[5] Takeshi Ishida, Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells, Discrete Dynamics in Nature and Society, Volume 2020, Article ID 2308074, 12 pages (2020.1)
https://doi.org/10.1155/2020/2308074
(6) Emergent model of cellular evolutionary capacity (2024)
The cell emergence model was enhanced by introducing a macromolecule representing information, demonstrating the evolutionary potential of cells.
[6] Takeshi Ishida, Simulation of the emergence of cell‑like morphologies with evolutionary potential based on virtual molecular interactions, Scientific Reports (2024) 14:2086
https://doi.org/10.1038/s41598-024-52475-9
(7) Extension of the Ishida model (2-state model of 0 and 1) to a multi-state model (2024)
The Ishida model (a two-state model of 0 and 1) was expanded into a multi-state model, enabling the generation of phenomena such as groups of cells preying on resources. This may provide insights into the mechanisms underlying the “vitality” of life. (Currently under preparation for publication.)
Figure 6 Example of multi-state Ishida model calculation results
3. Current Research
The cellular emergence model has been successfully employed to simulate the formation of cell boundaries, metabolism, self-replication, and information inheritance. However, this model is contingent upon the pre-existence of a polymerized molecule composed of 100 interconnected virtual molecules.
Given the absence of macromolecules like DNA or proteins at the time of the first cells’ emergence, this model falls short in explaining the initial origins of life. To address this limitation, a model that incorporates the emergence of polymerizes themselves is necessary.
I am currently in the process of developing a small molecule to polymerized molecule emergence model. (Target Publication: 2025)
4. Future Directions
(1) Realizing Artificial Cell Emergence
If the chemical reaction system depicted in my current cell emergence model can be replicated using actual chemical substances, the artificial emergence of cells should become a reality. Our immediate goal is to successfully embed the cell emergence model within the framework of existing biochemical reaction models.
(2) Unveiling the Origins of Life
Furthermore, developing a cellular emergence model that encompasses the emergence process of polymerized molecules could potentially shed light on the initial steps of life’s emergence.
(3) Engineering Cell-Like Capsules
From an engineering standpoint, we envision the design of novel cell-like capsules that possess a level of complexity surpassing that of microcapsules while maintaining simplicity compared to microorganisms.
(4) Building Self-Growing, Self-Replicating Robots
Ultimately, we aspire to construct robots that can accumulate artificial cells and exhibit self-growth and self-replication capabilities, akin to living organisms. While this ambitious goal may lie beyond my own lifetime, I hope to pass the torch to the next generation of researchers.