Dynamic landscapes and statistical limits on growth during cell fate specification

The complexity of gene regulatory networks in multicellular organisms makes interpretable low-dimensional models highly desirable. An attractive geometric picture, attributed to Waddington, visualizes the differentiation of a cell into diverse functional types as gradient flow on a dynamic potential landscape. However, it is unclear under what biological constraints this metaphor is mathematically precise. Here, we show that growth-maximizing regulatory strategies that guide a single cell to a target distribution of cell types are described by time-dependent potential landscapes under certain generic growth-control tradeoffs. Our analysis leads to a sharp bound on the time it takes for a population to grow to a target distribution of a certain size. We show how the framework can be used to compute regulatory strategies and growth curves in an illustrative model of growth and differentiation. The theory suggests a conceptual link between nonequilibrium thermodynamics and cellular decision-making during development.