The biological cell is a complex system composed of numerous molecular building blocks that act collectively to determine the cell state or phenotype. An important characteristic of biological cells is their ability to generate a wide spectrum of phenotypes across the population, which is referred to as phenotypic variability. One of the fundamental open questions in biology is how a genetically identical cell population can generate phenotypic variability. This variability plays an important role in diverse biological phenomena including the response of the immune system to infections, the growth of cancer metastasis, the formation of tissues during development, virus infections and microbial behavior. 

Phenotypic variability can be characterized in many ways. We focus on the variation in the copy number of a protein (or proteins) that determines the behavior of the cell or its response to an environmental signal (Salman et al 2012). However, when examining gene expression at the level of single-cell in a dividing cell population, one finds that the expression of any protein is dynamic and is influenced by the cell growth rate, population structure (variability) and the environment. In addition, transitions between different states of expression follow complex dynamical patterns that depend on the internal history of the cell as well as the environment. We believe that progress in understanding phenotypic variability cannot be made without a deeper understanding of the complex interrelations of individual cells to their population structure and dynamics, and of the symbiotic interactions between the population and its environment.

For that purpose, we study quantitatively the dynamics of protein expression, growth rate, and the interactions between the two at the single-cell and population levels. We place special emphasis on studying the contribution of non-genetic inheritance to the observed dynamics of both measures, and to the resulting population structure.