The Biodesign Lab

Our Research Focus

Our research is aimed at making the transition from unicellular to multicellular synthetic biology. To do this, we create synthetic biological systems capable of mimicking the emergent behaviors of complex multicellular organisms by integrating molecules, systems, and populations. Emergent behaviors in multicellular systems arise from the interactions of multiple cell types within the population. Each level of organization is important for emergent behaviors to arise. Molecules encode and regulate the genes needed to create the population. Gene networks regulate molecular interactions to bring about phenotype. Molecules transmit information within the population to give rise to emergent behavior. Because of this, population-level synthetic biology is not possible unless each level of organization, from molecules to systems to populations, is engineered to integrate into the whole.

Research Areas

Multicellular synthetic biology

We are studying the emergent properties of living systems composed of multiple interacting cell types. We are discovering new mechanisms for coordinating dynamic gene expression across lengthscales, creating periodic spatial patterns and sensing and maintaining cell type ratios.

Mimicking eukaryotic developmental processes in bacteria

We are exploring ways in which to engineer bacterial systems to mimic natural cellular processes found in multicellular organisms. We have engineered a system for synthetic differentiation in E. coli and are exploring the dynamics and pattern formation of differentiating populations.

Developing tools for robust cellular control

Collective behaviors require cells to be able to accurately sense their environment and make decisions despite external perturbations and intracellular noise. We are developing systems for improved environmental sensing, multi-input signal integration and robust adaptation to environmental perturbations.

Understanding the mathematics of cells

We are developing models that correctly predict the function and dynamics of synthetic gene circuits and populations. We are challenging existing paradigms by creating and analyzing gene expression models that incorporate stochasticity and delays as well as population models that incorporate emergent chemical gradients and mechanical interactions.