Linking GPCR organization states with functional heterogeneity in the pancreatic islet
| Title | Linking GPCR organization states with functional heterogeneity in the pancreatic islet |
|---|---|
| Acronym | IsletGPCR |
| Website | https://www.rdm.ox.ac.uk/people/david-hodson |
| Start date | 2022-12-01 |
| End date | 2027-11-30 |
| Sponsor | Horizon Europe Framework Programme |
| Institution | University of Oxford |
| Principal investigator | Prof David Hodson
E-Mail: david.hodson@ocdem.ox.ac.uk Phone: +441865857216 |
Associated cell lines
Project Description
The current view of tissue complexity is mainly based upon single-cell screening technologies, which classify cells according to shared traits, such as maturity, proliferative capacity and mutational potential. Often, inferences about cell function are based upon measurements made outside of the tissue context, as well as the characteristics of the state to which the cell belongs. Thus, immature cells tend to be considered as proliferative, but poorly functional, whereas more mature cells are long-lived and highly functional. While single-cell screening approaches are high-dimensional, they do not have the spatiotemporal resolution inherent to light microscopy. The present proposal will leverage recent advances in genome editing, protein labelling, super-resolution imaging and spatial transcriptomics to provide a higher-order in situ organization of cell heterogeneity at the tissue level, with repercussions for our understanding of tissue (dys)function. Using pancreatic islets as an exemplar micro-organ, and GPCRs as candidate cell surface signalling proteins, we will: 1) map GPCR organization/dynamics at the cell population level and integrate this information with underlying transcriptomic features, before re-classifying cell states; 2) understand how higher-order GPCR organization/dynamics change during cell stimulation, metabolic stress and other states of tissue perturbation; 3) functionally interrogate cell states defined by GPCR organization/dynamics using novel activity integrators and cell-specific transcription factor re-expression; and 4) examine higher-order cell heterogeneity across species. The proposed work will show for the first time how the organization and dynamics of individual signalling proteins relate to cell state and cell activity across the cell population. More broadly, these studies will establish a high-resolution view of cell heterogeneity, leading to a step-change in our understanding of the functional organisation of complex tissues.