Our laboratory uses the tools of biomolecular engineering, synthetic biology, and systems biology for two purposes:
- To elucidate fundamental biological design principles that underlie cellular decision making, and
- To design new molecular and cellular therapeutics for applications in cancer, diabetes, and infectious diseases.
We couple methods from experimental disciplines such as molecular biology, protein biochemistry, microbiology, and mammalian cell biology with computational modeling and engineering analyses to develop quantitative and predictive frameworks for the biological processes that we interrogate and design.
Elucidating biological design principles in cellular decision making
The inherent complexity and our incomplete understanding of native cell signaling and transcriptional networks often obfuscate the biological design principles that govern how cells make decisions. We are utilizing both 'top-down' systems biology and 'bottom-up' synthetic biology approaches to study signal processing and multimodal decision making in stem/progenitor cells and cancer cells. In our systems biology approaches, we integrate quantitative cell biology experiments and mechanistic/data-driven models to elucidate new cellular control mechanisms. In our synthetic biology approaches, we test our understanding of biology by constructing, analyzing, and perturbing minimal, well-defined biomolecular networks with decision-making capabilities, illuminating design strategies for robustly controlling cell behavior.
Designing new molecular and cellular therapeutics
The creation of novel molecular and cellular reagents for specific biomedical or biotechnological applications can often benefit from a quantitative, holistic perspective in order to maximize the efficacy and utility of these products. We are using such systems-level approaches to identify and overcome a number of therapeutic bottlenecks that present clinical challenges, ranging from oral delivery of therapeutic proteins such as insulin to the suppression and eradication of tumors. Our work is highly multidisciplinary, integrating methods from directed evolution, chemical biology, microfluidics, and computational modeling to create new platform technologies and to discover novel, more effective therapeutic modalities.