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ThDEFINE

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Re defining CD4 T Cell Identities One Cell at a Time

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 pr... ver más

30/06/2022

GRL

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

GENOME RESEARCH LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 3 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-06-30

ERC-CoG-2014: ERC Consolidator Grant

I+D

Cerrada hace 10 años

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3 Participantes

GRL

1.78M€ | Lider

CATALINA FOOD SOLUTIONS

447.90K€ | Participante

EMBL

202.23K€ | Participante

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Duración del proyecto: 80 meses Fecha Inicio: 2015-10-19
Fecha Fin: 2022-06-30

Líder del proyecto

GENOME RESEARCH LIMITED No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto 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.

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