Tissues in higher organisms are organized as hierarchically structured cell populations, where only a small number of cells, the stem cells, have the capacity for infinite self-renewal. In this talk, we explore how stochastic models are used to show that such hierarchies protect against uncontrolled, cancer-like growth.
 
However, this design that protects most tissues has a drawback, slow regeneration, leading to an exception: the liver. After an injury, fully differentiated hepatocytes can re-enter the cell cycle and proliferate without requiring stem cells or progenitors to produce new cells.
 
To explore how this mechanism is controlled, we use single-cell RNA-seq to dissect the early events of liver regeneration. We show how macrophage signaling to hepatocytes drives the process, and how mathematical models, calibrated on the single-cell data, allow in-silico knockouts that identify a key regenerative signal.
 
Finally, we explore how these two concepts, restricted self-renewal for cancer protection and direct hepatocyte division for rapid repair, can be reconciled.