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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... see more

30/06/2022

GRL

2M€

Project Budget: 2M€

Project leader

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

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo H2020 notifico la concesión del proyecto The day 2022-06-30

ERC-CoG-2014: ERC Consolidator Grant Scope:Objectives

I+D

Cerrada does 11 years

0% 100% 100%

characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Private Information

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3 Participantes

GRL

1.78M€ | Leader

CATALINA FOOD SOLUTIONS

447.90K€ | participant

EMBL

202.23K€ | participant

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Project duration: 80 months Date Start: 2015-10-19
End date: 2022-06-30

Project leader

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

TRL 4-5

Project Budget 2M€

participation deadline Sin fecha límite de participación.

Project description 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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