Substrate stiffness governs dynamics and self-organization of nascent biofilms (2508.01021v1)
Abstract: The evolutionary success of bacteria lies in their ability to form complex surface-associated communities in diverse biophysical settings. However, it remains poorly understood how compliance of soft surfaces, measured in terms of their elastic deformability, impacts the dynamics and self-organization of bacterial cells proliferating into colonies. Using experiments and biomechanical modelling, here we study the expansion and self-organization of bacterial cells into sessile colonies on soft substrates. The dynamics and spatiotemporal structures were captured by visualising growing bacterial colonies on nutrient-rich, soft agarose pads, with elastic modulus in the range ~0.3 kPA to ~100 kPA by varying the concentration of the agarose in the underlying substrate. Our results show that, at the scale of the colonies, significant differences emerge in the spreading dynamics and colony geometry as the substrate stiffness is altered: softer substrates promote distinct, multilayered colony structures, and as revealed by fractal analysis of the colony boundaries, they exhibit higher boundary roughness. In contrast, colonies growing on harder substrates first grow up to large monolayers, before undergoing the mono-to-multilayer transition (MTMT), showing nearly 300% increase in the overall colony area at MTMT. A simple biomechanical model captures the role of effective drag forces at different scales, acting on the colonies as they spread on substrates with different stiffness: higher drag in soft substrates drive early verticalisation of the colonies, while lower effective drag delays the MTMT, resulting in larger colony areas. Based on the results and biomechanical insights, a comprehensive data-backed numerical model is currently being developed. Our findings highlight the role of surface stiffness in determining the self-organization of bacterial cells into an expanding multi-scale colony.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.