The majority of cells in our body do not move around—but when they do, it is for an important reason: single and collectively migrating cells shape us during development, they protect us during immune response but can also harm us during cancer progression. Yet, the underlying dynamics of how cells move and interact with each other and their environment remains unclear. I will discuss how data-driven theoretical approaches can be used to learn the dynamical laws underlying cell movement, morphology and interactions of cells in controlled artificial environments. By inferring a stochastic equation of motion directly from experimental data, we show that cells exhibit intricate non-linear deterministic dynamics that adapt to the geometry of confinement. We extend this approach to interacting systems, by tracking how trajectories of colliding pairs of cells scatter. This allows us to develop and constrain a phenomenological theory of contact-interactions between cells. Finally, I will discuss how our approach can be generalized to identify the interactions rules underlying the many-body stochastic dynamics that controls collective migration in multicellular systems.
Colonies and biofilms are a predominant form of bacterial life. Surrounded by an extracellular matrix, bacteria form structured communities with emergent properties that protect them from external stresses and confer tolerance to antimicrobial treatments. In this talk, I will focus on how the attractive forces between cells control these emergent properties and how they influence the fitness of bacteria. We explore these questions using the human pathogen Neisseria gonorrhoeae as a model system. In colonies, the mechanical properties are determined by type 4 pili (T4P). Over two decades, we have established biophysical and microbiological methods related to these molecular motors and developed them into a toolbox that allows us to control the mechanical properties of colonies formed by N. gonorrhoeae, including colony shape, viscosity, surface tension, local order, and sorting. A characteristic feature of this system is that the cellular network formed by T4P is inherently active and consumes energy. We recently discovered that this energy consumption creates a chemical gradient within the colonies, which in turn renders the large-scale colony morphology metastable and susceptible to an instability that drives global inversion and spreading. We identify how energy consumption, active forces, and material instabilities interact to control morphology at the colony level, providing a physical understanding of shape dynamics in living, active matter systems.
