A growing and largely descriptive single-cell atlas of tissues has begun providing insight into the spatial organization of microenvironments, yet it remains a challenge to understand cause-and-effect relationships from such data. How does the signaling state of one cell affect that of its neighbors? We aim to address this question by leveraging advances in in vivo imaging, nanotechnology, and synthetic biology to generate a framework for image-guided manipulation, real-time monitoring, and systems-level analysis of signal propagation. Although this project will yield fundamental insights into signaling propagation, we also aim to extend image-guided genetic reprogramming to therapeutic applications.

 Thousands of biomaterials and nanoparticles have been developed for drug and nucleic acid delivery, but molecular and cellular-level mechanisms of their action in tissue are often poorly understood. Our group expands on novel in vivo imaging techniques to analyze the combined distribution and action of biomaterials and nanoformulations at a multi-scale level. This project pursues a systematic, molecular-level understanding of drug action, with the goal of informing improved therapeutic and biomaterial designs.

 Through new technologies, including single-cell RNA sequencing (scRNAseq) and multiplexed tissue imaging (MTI), tissues can now be visualized with incredible molecular and cellular detail. However, such rich maps of tissue structure are typically static snapshots from a fixed sample, and lack important information about how the tissue actually functions — how cells, fluids, and biomolecules dynamically interact to govern multicellular behaviors. This project aims to overcome this limitation by building an integrated computational and experimental platform for quantitatively linking functional dynamics within tissue to a map of its molecular and cellular composition.