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Re(defining) CD4+ T Cell Identities One Cell at a Time

Total Cost €


EC-Contrib. €






 ThDEFINE project word cloud

Explore the words cloud of the ThDEFINE project. It provides you a very rough idea of what is the project "ThDEFINE" about.

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Project "ThDEFINE" data sheet

The following table provides information about the project.


Organization address
city: LONDON
postcode: NW1 2BE

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 1˙980˙685 €
 EC max contribution 1˙980˙685 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-CoG
 Funding Scheme ERC-COG
 Starting year 2016
 Duration (year-month-day) from 2016-01-01   to  2020-12-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    GENOME RESEARCH LIMITED UK (LONDON) coordinator 1˙778˙456.00


 Project objective

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.


year authors and title journal last update
List of publications.
2017 Tapio Lönnberg, Valentine Svensson, Kylie R. James, Daniel Fernandez-Ruiz, Ismail Sebina, Ruddy Montandon, Megan S. F. Soon, Lily G. Fogg, Arya Sheela Nair, Urijah N. Liligeto, Michael J. T. Stubbington, Lam-Ha Ly, Frederik Otzen Bagger, Max Zwiessele, Neil D. Lawrence, Fernando Souza-Fonseca-Guimaraes, Patrick T. Bunn, Christian R. Engwerda, William R. Heath, Oliver Billker, Oliver Stegle, Ashraful Haque, Sarah A. Teichmann
Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves T H 1/T FH fate bifurcation in malaria
published pages: eaal2192, ISSN: 2470-9468, DOI: 10.1126/sciimmunol.aal2192
Science Immunology 2/9 2019-04-09
2018 Ida Lindeman, Guy Emerton, Lira Mamanova, Omri Snir, Krzysztof Polanski, Shuo-Wang Qiao, Ludvig M. Sollid, Sarah A. Teichmann, Michael J. T. Stubbington
BraCeR: B-cell-receptor reconstruction and clonality inference from single-cell RNA-seq
published pages: 563-565, ISSN: 1548-7091, DOI: 10.1038/s41592-018-0082-3
Nature Methods 15/8 2019-04-09
2016 Michael J T Stubbington, Tapio Lönnberg, Valentina Proserpio, Simon Clare, Anneliese O Speak, Gordon Dougan, Sarah A Teichmann
T cell fate and clonality inference from single-cell transcriptomes
published pages: 329-332, ISSN: 1548-7091, DOI: 10.1038/nmeth.3800
Nature Methods 13/4 2019-05-30

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