MPI-DS Colloquium: Stochastic processes in cells and tissues

Stochastic phenomena play a fundamental role in many biological systems, ranging from gene regulation to cell-fate determination. Understanding such phenomena raises new theoretical challenges at the interface between stochastic processes, statistical physics and computation. In this talk I will present some recent advances that our group has made in this direction. In the first part of the talk, I will show how cells can use phase coexistence to control and suppress protein concentration fluctuations. Us-ing a non-equilibrium model that links active protein synthesis and turnover to the physics of multicomponent phase separation, I will show that concentration fluctua-tions can be strongly reduced in the presence of phase separated compartments. I will present experimental single-cell data in synthetic and endogenous compartments, which support this prediction. In the second part of my talk, I will focus on inverse problems and how stochastic processes can be robustly inferred from limited experi-mental data. As an example, I will present a statistical method to quantify CTCF/cohesion-mediated chromatin looping dynamics from two-point live-imaging measurements. The method combines a simple polymer model with a Bayesian filtering approach to infer loop lifetimes and frequencies. When applied to experimental data, this method revealed that chromatin loops are surprisingly rare (~5% looped fraction) and short-lived (~10-30mins loop lifetime). I will conclude my talk by outlining sever-al important challenges for the future.