Illuminating cellular individuality through bacteriophage infection*

Going back almost a century, phage infection has served to highlight the individuality of living cells, by demonstrating that genetically identical cells, within a uniform environment, exhibit heterogeneous phenotypes in terms of gene expression, signaling, and consequent fate choice. In recent decades, these observations motivated a probabilistic picture of cellular behavior, in which the statistical properties of any cellular observable are calculable using stochastic modeling, but each individual cell remains unknowable. However, this "statistical mechanics" approach to biological function should not be taken too far. Unlike non-living matter, in which physics informs us of the limits of determinism, we do not yet know where this limit lies for living cells, which utilize elaborate regulation to function at the required precision. Thus, before defaulting to a stochastic description, we must endeavor to peel off the layers of single-cell unknowns, to reveal hidden variables—currently masked as "noise"—that drive cellular behavior. In this effort, the process bacteriophage infection again provides us with an ideal opportunity. By examining infection at the level of individual phages and cells, we aim to identify the factors driving the viral decision between dormancy and cell death, and to predict the outcome of individual infection events. I will briefly report on some of our recent efforts in this regard.