Age distribution of inoculated cells and stochasticity of inter-division times generate pseudo-lag in population growth.

Population-level growth parameters, such as specific growth rate (or doubling time) and lag time, can be inferred directly from the distribution of the inter-division times of single cells. Applying stochastic branching process theory to the multiplication of bacterial cells, we demonstrate that a) the lag time, or time-shift, detectable at population level is primarily determined by the (random) time-to-first-division of the initial cells and b) exponentially growing populations converge to a stable age distribution characterized by a ratio of approximately 2:1 between the number of young and old cells. A consequence is that a random sample from an already growing population is dominated by younger cells. This bias increases the expected time of the initial cells to their first division when inoculated in a new environment, which induces an additional "pseudo-lag" for the growing population, due to statistical causes, independently of physiological adaptation. Our results establish a formal link between stochastic birth processes at the single-cell level and growth kinetics at population-level. The distinction between biological and statistical causes of the observed lag can be relevant to food processing environments, where pathogenic microorganisms are often present at low initial concentrations and stochastic single-cell dynamics can substantially influence the apparent lag time.