Emergent Simplicities in Stochastic Intergenerational Homeostasis

Abstract

Biological systems are complex and hierarchical, with inherent stochasticity of constitutive molecular processes. Yet, key physiological “state” variables are held in homeostasis. To identify quantitative rules governing the responsible control systems, we reconceptualize homeostasis as a dynamical—albeit stochastic—process, focusing on cell size homeostasis as a case study. Using our SChemostat technology, we obtain high-precision multigenerational trains of statistically identical, non-interacting individual bacterial cell sizes in well-defined environments. We first establish that individual cells indeed maintain stochastic intergenerational size homeostasis. Through extensive analysis of experimental data from multiple growth conditions, we uncover hidden simplicities including an intergenerational scaling law governing fluctuations in cell sizes across generations. These “emergent simplicities” place strong constraints on the dynamics: they specify, without fitting parameters, the precise stochastic map for the intergenerational evolution of cell sizes. Importantly, we find that intergenerational cell size homeostasis is achieved through reflexive, elastic adaptation. Thus, under balanced growth conditions, cell size cannot serve as a repository of intergenerational memory.