Optimal foraging in Caenorhabditis elegans: A simple rule from a complex dataset Abstract »

Evolution is supposed to produce near-optimal organisms, but this optimality is often hidden behind the high complexity of biology. Optimal animal behavior is particularly hard to study, given the extreme complexity of the nervous system and the diversity of environmental cues it can face. We address this challenge on a simple and powerful model organism, the nematode Caenorhabditis elegans. Combining high-throughput experimental techniques, data analysis and modeling, we aim to test the optimality of behavior with unprecedented accuracy, breadth and detail.

Microbial growth and competition on liquid substrates Abstract »

Turbulent mixing near ocean surfaces generates phytoplankton blooms with fractal spatial structures. This is but one example of how fluid flows interact with biological growth to shape populations and promote the formation of ecological niches with enhanced genetic heterogeneity. Hydrodynamic transport can shape and reorganize populations across all scales, either mixing to uniformity or leading to the formation of differentiated structures. In the laboratory, microbial growth on agar plates has long been used to model how genetic spatial structure impacts evolution. However, because the substrate is solid and the microbial population is not advected, these experiments only mimic range expansion on land. In this talk, I will discuss how we have addressed this problem by studying the growth and morphology of microbial colonies on the surface of a viscous substrate. Combining experiments with numerical modeling, I will demonstrate that the positive feedback between flow and growth can lead to both colony fracture or microbial jetting phenomena, and dramatically impact the genetic segregation patterns. Our work thus introduces a controlled versatile system with which to study the intricate interplay between hydrodynamics, growth and competition.