Objetivo
The immune system consists of a complex continuum of cell types that communicate with each other and non-immune tissues in homeostasis, and during infections, autoimmunity and cancer. Conventional transcriptional and functional profiling enabled by cell surface marker sorting has revealed a great deal about how specific cell types operate en masse, yet important transcriptional heterogeneity that exists within cell populations remains unexplored. High-throughput single cell RNA-seq can overcome this limitation by profiling entire transcriptomes of thousands of individual cells, revealing cell-to-cell variation by decoding patterns within populations masked in bulk transcriptomes. We will exploit this to dissect the mouse CD4+ T cell compartment, a heterogeneous white blood cell population that initiates adaptive immune responses.
In AIM 1, we will chart the dynamics of in vivo CD4+ cell states in mouse before, during and after immune response challenges. By sequencing thousands of single cell transcriptomes, we will map the landscape of CD4+ T cell states in an unbiased, quantitative and comprehensive way.
In AIM 2, we will predict key transcription factors, cell surface markers, and signalling molecules, including cytokines/chemokines in each cell state through novel computational approaches. Furthermore, our analyses will establish regulatory modules and networks of gene-gene interactions active in immune responses.
In AIM 3, we will (a) confirm the in vivo impact of new cell states by performing adoptive cell transfer assays; and
(b) validate our predictions of regulatory molecules and interactions using a massively parallel CRISPR/Cas knockout screen in vitro.
This powerful integrated approach combines single cell RNA-sequencing, bioinformatics and genetic engineering to dissect CD4+ T cell states, a central compartment of mammalian adaptive immunity, and reveal basic principles of gene regulation.
Ámbito científico
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
- medical and health sciencesbasic medicinepharmacology and pharmacydrug discovery
- medical and health scienceshealth sciencesinfectious diseasesmalaria
- medical and health sciencesmedical biotechnologygenetic engineering
- medical and health sciencesbasic medicineimmunology
- medical and health sciencesbasic medicinephysiologyhomeostasis
Palabras clave
Programa(s)
Régimen de financiación
ERC-COG - Consolidator GrantInstitución de acogida
CB10 1SA SAFFRON WALDEN
Reino Unido