Insights into Stochastic Growth and Division of Single Bacterial Cells, or A Bug's Life
Understanding cellular function(s) in terms of autonomous nonequilibrium processes requires knowing more than just the molecular players and their partner interactions. Another view is a "modular cell biology" perspective as proposed by Hopfield et al. (Nature, 402, 1999). In this talk I will illustrate how rules of organization of oscillators in regulatory biochemical networks emerge from measurements at the organismal level; that is, viewing the 'forest rather than the trees'. This is made possible, in part, with our development of a large data set microscopy and automated image analysis capability for measurement of large numbers of single cells of the bacterium Caulobacter crecentus. We are now able to elucidate fundamental insights about cell growth with high statistical precision. Our statistical mechanical generalization of an autocatalytic cycle model, based on the mechanism derived in a deterministic ODE form by Hinshelwood, yields nontrivial predictions of temperature-dependence of the growth and division time distributions, scaling relations of distributions of various observables (e.g. cell size during the cell cycle, growth rate, division time, etc.) and a measure of the "nonequilibriumness" of cell growth that are observed in experiment. Extension of the approach to cell contour analysis and continuum modeling of cell shape during growth and the concept of deducing properties of biochemical reaction network by the dynamics of information flow by pulsed perturbation/response function measurements will also be presented if time permits.