  The metabolic network plays a crucial role in regulating bacterial metabolism
and growth, but it is subject to inherent molecular stochasticity. Previous
studies have utilized flux balance analysis and the maximum entropy method to
predict metabolic fluxes and growth rates, while the underlying principles
governing bacterial metabolism and growth, especially the criticality
hypothesis, remain unclear. In this study, we employ a maximum entropy approach
to investigate the universality in various constraint-based metabolic networks
of Escherichia coli. Our findings reveal the existence of universal scaling
relations across different nutritional environments and metabolic network
models, similar to the universality observed in physics. By analyzing
single-cell data, we confirm that metabolism of Escherichia coli operates close
to the state with maximum Fisher information, which serves as a signature of
criticality. This critical state provides functional advantages such as high
sensitivity and long-range correlation. Moreover, we demonstrate that a
metabolic system operating at criticality takes a compromise solution between
growth and adaptation, thereby serving as a survival strategy in fluctuating
environments.
