Cells must make decisions in stochastic environments using stochastic biochemistry. The aim of our research is to uncover the information-processing strategies that allow cells to decide reliably despite such stochasticity.
Cells must infer the current and possible future state of the extracellular environment from local signals — those sensed at the cell membrane or intracellularly. They should then decide based on this inference, on the expected costs and benefits of each potential response, and on the possible presence of other organisms, be they either competitors or cooperators.
Factors influencing cellular decision-making. A cell senses signals generated by a change in the environment and must decide an appropriate response (Perkins & Swain (2009)).
Our current focus is nutrient-sensing by budding, or brewers, yeast. Extracellular nutrients in yeast can act analogously to hormones in mammalian cells, and nutrient-sensing networks control decisions to differentiate, sporulate, or grow and divide.
We use a combination of both experiment and theory: microfluidics to generate stochastically changing environments, fluorescence microscopy to quantitatively monitor the responses of individual cells, and techniques from stochastic processes, non-linear dynamics, information theory, statistical inference, and evolutionary biology to develop mathematical models of biochemical information-processing.