Growth states of catalytic reaction networks exhibiting energy metabolism

TL;DR

This study models catalytic reaction networks in protocells to explore different growth phases driven by resource influx, revealing phase transitions and statistical properties that relate to cellular states.

Contribution

Introduces a protocell model with catalytic reactions and energy metabolism, analyzing phase transitions and statistical distributions of growth states.

Findings

Identifies four distinct growth phases based on resource influx and cell growth rates.

Explains phase transitions using a mean field bifurcation model.

Characterizes the statistical distributions of active and inefficient phases.

Abstract

All cells derive nutrition by absorbing some chemical and energy resources from the environment; these resources are used by the cells to reproduce the chemicals within them, which in turn leads to an increase in their volume. In this study, we introduce a protocell model exhibiting catalytic reaction dynamics, energy metabolism, and cell growth. Results of extensive simulations of this model show the existence of four phases with regard to the rates of both the influx of resources and the cell growth. These phases include an active phase with high influx and high growth rates, an inefficient phase with high influx but low growth rates, a quasi-static phase with low influx and low growth rates, and a death phase with negative growth rate. A mean field model well explains the transition among these phases as bifurcations. The statistical distribution of the active phase is characterized by a power law and that of the inefficient phase is characterized by a nearly equilibrium distribution. We also discuss the relevance of the results of this study to distinct states in the existing cells.