The Venturelli Lab aims to understand how interactions at different scales of biological complexity combine to generate collective behaviors. We seek to understand and engineer the spatiotemporal behaviors of biological networks using tools from systems & synthetic biology. A major goal is to design novel strategies to precisely shift microbiomes to desired metabolic states. Our research combines multiplexed measurements of single cells, populations and ecosystems with concepts from nonlinear dynamical systems, control theory, multi-objective optimization and machine learning.
Microbial communities across space and time
Microbial communities are highly complex and exhibit spatial and temporal variability. Our lab studies the ecological, molecular and genetic factors that determine the dynamics, functional activities and spatial organization of microbial communities. We use bottom-up and top-down approaches to quantify interaction networks at different scales that are major determinants of community behaviors.
Interventions to steer microbial communities to desired states
We develop strategies using tools from synthetic biology to precisely steer microbial communities to desired states. We construct microbial control systems to sense, compute and perform target functions in complex environments for biotechnological and biomedical applications.
Methods to study microbiomes in high-throughput and mimic natural microenvironments
We are investigating the ecological and evolutionary processes of microbial communities using tools from microfluidics. These techniques enable precise control of spatiotemporal parameters to mimic natural microenvironments as well as high-throughput techniques to study large-scale interaction networks.