Theoretical Approaches for Cell Deaths

Understanding the boundary between cell life and death is a fundamental challenge and a highly important theme in biology. In this talk, focusing on microbial cell death, I would like to discuss how "cell death" can be understood from the perspective of mathematical sciences.
Research on microbial cell death has progressed by identifying the molecular mechanisms that drive relevant biochemical processes, which are identified based on empirically known cell death markers. However, there has been little discussion on what death actually is in the first place, or how it can be "defined." Furthermore, recent reports have shown that commonly used live/dead assays—such as dead-cell staining and metabolic activity measurements—can yield conflicting results regarding cell viability, highlighting the growing need to discuss what criteria we should use to define "death."
In this study, we propose a definition: a cell is "dead" if it cannot return to a predetermined "representative point of the living state," no matter how gene expression levels or external nutrient concentrations are controlled. Plant seeds may appear "dead" at first glance due to their lack of apparent biochemical activity, yet they germinate when watered. Our proposal in this study is to determine the life or death of a cell based on whether an operation equivalent to "watering" exists [1].
Of course, it is experimentally impossible to prove that a cell cannot regain activity under any operation; however, it is theoretically possible using mathematical models. We developed a method called "Stoichiometric Rays" to calculate the controllability of metabolic reaction systems. Using this, we calculated states that cannot be controlled back to the "representative point of the living state" regardless of how enzyme levels and external nutrient concentrations are manipulated. Consequently, we succeeded in quantifying the separating hyperplane between the "living state" and the "dead state" in a mathematical model of metabolism [2], which we call the Separating Alive and Non-life Zone (SANZ) Hypersurface.
In this talk, I will outline the theory, the quantification of the SANZ hypersurface, and its biological interpretation. In addition, through our research [3], we have partially identified a class of models that do not exhibit "death" in the sense described above. I would also like to discuss the relationship between the absence of "death" in these models and the autonomy of life.