  We propose a statistical model of a large random network with high
connectivity in order to describe the behavior of {\it E.\,coli} cells after
exposure to acute stress. The building blocks of this network are feedback
cycles typical of the genetic and metabolic networks of a cell. Each node on
the cycles is a spin degree of freedom representing a component in the cell's
network that can be in one of two states - active or inactive. The cycles are
interconnected by regulation or by the exchange of metabolites. Stress is
realized by an external magnetic field that drives the nodes into an inactive
state, and the time the magnetization passes zero value for the first time
represents the first division event of the cell after the stress period. The
numerical and analytical solutions for this first passage problem reproduce the
aging dynamics observed in the experimental data.
