Case Study

My group is interested in understanding how cells sense and respond to their physical environment. Normal development, wound healing, cancer, and aging are intimately associated with changes in tissue mechanics. We use high content microscopy, as well as molecular and cell biological techniques, to study the signalling pathways that couple physical forces with cell behaviours such as gene expression, migration, and proliferation. We are also interested in exploring how cells interact with synthetic materials, such as nanoparticles, and how engineered materials impact cell fate. Our goals are to figure out how cells organise themselves into tissues, how these processes can go wrong in diseases, and how nanoscale biomaterials can be used to treat cancer and repair damaged tissues.

Biological images provide a wealth of information, but we are still in the process of inventing the tools that we need to make sense of the information we can derive. We use computer algorithms to automatically identify cells from microscope images and extract of measurements of features from cell shape and cell-cell contact to intracellular structures and protein localisation. The resulting datasets, comprised of millions of cells with hundreds of features are heterogeneous, and highly complex. We are working with mathematicians and computer scientists to develop models that can help us interpret single-cell imaging data and the map signalling networks that underlie human disease and tissue regeneration.