The issue of how to link the quantification and analysis of individual and population behavior naturally arises in bacterial communication (often referred to as quorum sensing (QS)). QS is a mechanism by which cells (i. e., at the single cell level) exchange information through the release and sensing of signal molecules called autoinducers, to regulate their behavior collectively (at the population level).

 

We investigate the QS of the plant-pathogenic bacterium Pseudomonas syringae on leaf surfaces, as an example of QS in a real habitat. QS in P. syringae regulates traits that contribute to epiphytic fitness as well as to distinct stages of disease development during plant infection.

 

In this context, there exist, on one side, experimental techniques to track QS at the single cell level (QS reporters) and, on another side, to measure the production of autoinducers in cultures of P. syringae (at the population level). Likewise, it is possible to measure frequency, size, and localization of single bacteria on leaf surfaces and population sizes of bacteria at different times after inoculation.

 

All these data are often not analyzed jointly. We show how we have integrated these data; to this end, we present a stochastic model of bacterial growth combined with a deterministic description of autoinducer concentration. We discuss how the issue of heterogeneity plays a role.