Speaker
Description
This presentation explores the intricate relationship between selection, chance, and evolutionary history in microbial adaptation to dynamic environments. We implement a multiscale approach to experimental evolution, allowing us to simultaneously observe individual cells and entire populations. This integration of microfluidic technology with traditional batch cultures enables detailed observation and analysis of microbial interactions at the cellular level and the broader evolutionary adaptations occurring within populations. Additionally, our approach incorporates data-driven mathematical models and computer simulations to study the complex dynamics observed in our experimental setups. A central focus is the response of microbial communities to fluctuating selective pressures, especially those leading to antibiotic resistance. We investigate the metabolic and genetic interactions that drive ecological and evolutionary dynamics in mixed populations by employing image analysis for individual cell behaviors and whole genome sequencing for population dynamics. Our research explores microbial adaptation, with findings that could be relevant in shaping strategies for managing antibiotic resistance, a significant challenge in public health and medical treatment.
