Fundamental Limits to Collective Sensing in Cell Populations

Cells live in inherently noisy environments. The machinery that cells use to sense their environment is also noisy. Yet, cells are exquisite environmental sensors, often approaching the limits of what is physically possible. This thesis investigates how the precision of environmental sensing is improved when cells behave collectively. We derive physical limits to cells' ability to collectively sense and respond to chemical concentrations and gradients. For concentration sensing, we find that when cell populations become sufficiently large, long-range communication can provide higher sensory precision than short-range communication, and that the optimal cell-cell separation in such a system can be large, due to a tradeoff between maintaining communication strength and reducing signal cross-correlations. We also show that concentration profiles formed diffusively are more precise for large profile lengths while those formed via directed transport are more precise for short profile lengths. These effects are due to increased molecule refresh rate and mean concentration respectively. For gradient sensing, we derive the sensory precision of the well-known the local excitation-global inhibition (LEGI) model and the more recently proposed regional excitation-global inhibition (REGI) model for two and three dimensional cell cluster geometries. We find that REGI systems achieve higher levels of precision than LEGI systems and give rise to optimally sensing geometries that are consistent with the shapes of naturally occurring gradient-sensing cell populations. Lastly, we analyze the precision with which migrating cell clusters can track a chemical gradient via an individual-based and emergent method. We show that one and two dimensional clusters utilizing the emergent chemotactic method have improved scaling with population size due to differences in the scaling properties of the variance in the total polarization. By completing these studies we aim to understand the limits and precise roles of collective behavior in environmental sensing.