Abstract

Microbes play a significant role in human and planetary health. Many of these microbes live in dense, spatially structured communities known as biofilms, where cells interact closely by exchanging diffusible molecules. To understand and manipulate the functions of these communities, it is essential to uncover how community-level properties, such as composition, spatial arrangement, and growth rate, emerge from these interactions. Here, I demonstrate how combining single-cell microscopy with mathematical modelling can provide a quantitative understanding of how these community properties develop from the underlying molecular mechanisms of cell-cell interactions. This framework enables us to scale from molecular to community-level dynamics, laying the groundwork for a quantitative understanding of microbial community function.