Summary
One of the most fundamental challenges in contemporary biology is in fact also one of the most classical ones: how to comprehend macroscopic tissue function from the activities of its microscopic cellular components. The remarkable advent of single cell genomics over the last decade is realizing this challenge at unprecedented scales. Measurements of the molecular states of thousands or even millions of cells can now be acquired efficiently, and tools for describing cellular states phenomenologically became well established. But how to model ensemble of cells in tissues is paradoxically even more difficult than before given this new unprecedented experimental resolution. To this end we will develop a new computational and theoretical framework for understanding ensembles of single cells as they interact and dynamically differentiate, proliferate or degrade. Parametric and mechanistic models for defining microscopic cell states over a mathematical manifold will be developed, and the dynamics of ensembles of cells over time and in space will be inferred from new experimental approaches capturing whole tissues over time or within spatially registered domains. Importantly, our models will describe tissues dynamics as change in specific gene regulatory, epigenomic and signaling programs, and we will develop high throughput experiments to combinatorically perturb embryonic and hematopoietic systems in order to test such models extensively. Our research will thereby extend single cell-centric models toward describing dynamics in tissues, with experiments and data collection aiming at rapid translation of the models to actionable and testable strategies for manipulating systems of interest. This will be applied to transparent and epigenetically precise cell type engineering, to discoveries using a unique resource on human hematopoietic ageing and to deep tissue level analysis of combination immunotherapy.
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| Web resources: | https://cordis.europa.eu/project/id/101054948 |
| Start date: | 01-06-2023 |
| End date: | 31-05-2028 |
| Total budget - Public funding: | 2 937 179,00 Euro - 2 937 179,00 Euro |
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Original description
One of the most fundamental challenges in contemporary biology is in fact also one of the most classical ones: how to comprehend macroscopic tissue function from the activities of its microscopic cellular components. The remarkable advent of single cell genomics over the last decade is realizing this challenge at unprecedented scales. Measurements of the molecular states of thousands or even millions of cells can now be acquired efficiently, and tools for describing cellular states phenomenologically became well established. But how to model ensemble of cells in tissues is paradoxically even more difficult than before given this new unprecedented experimental resolution. To this end we will develop a new computational and theoretical framework for understanding ensembles of single cells as they interact and dynamically differentiate, proliferate or degrade. Parametric and mechanistic models for defining microscopic cell states over a mathematical manifold will be developed, and the dynamics of ensembles of cells over time and in space will be inferred from new experimental approaches capturing whole tissues over time or within spatially registered domains. Importantly, our models will describe tissues dynamics as change in specific gene regulatory, epigenomic and signaling programs, and we will develop high throughput experiments to combinatorically perturb embryonic and hematopoietic systems in order to test such models extensively. Our research will thereby extend single cell-centric models toward describing dynamics in tissues, with experiments and data collection aiming at rapid translation of the models to actionable and testable strategies for manipulating systems of interest. This will be applied to transparent and epigenetically precise cell type engineering, to discoveries using a unique resource on human hematopoietic ageing and to deep tissue level analysis of combination immunotherapy.Status
SIGNEDCall topic
ERC-2021-ADGUpdate Date
09-02-2023
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