Noisy microbial population growth carries an imprint of initial conditions in its first-passage-time statistics

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. Interactions between noisy population growth and other biological processes (e.g., host immune response) can propagate, contributing to stochasticity in macroscopic biological functions. In several stochastic models of exponential growth we show power-law relationships that relate variability in the time required to reach a threshold population size to growth rate and inoculum size. Population-growth experiments in E. coli and S. aureus with inoculum sizes ranging between 1 and 100 are consistent with these relationships. We quantify how noise accumulates over time, finding that it encodes—and can be used to deduce—information about the early growth rate of a population.