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MAIT Cell Recognition of MR1 on Bacterially Infected and Uninfected Cells

Overview of attention for article published in PLOS ONE, January 2013
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Title
MAIT Cell Recognition of MR1 on Bacterially Infected and Uninfected Cells
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0053789
Pubmed ID
Authors

Mary H. Young, Lance U’Ren, Shouxiong Huang, Thierry Mallevaey, James Scott-Browne, Frances Crawford, Olivier Lantz, Ted H. Hansen, John Kappler, Philippa Marrack, Laurent Gapin

Abstract

Mucosal-associated invariant T cells are a unique population of T cells that express a semi-invariant αβ TCR and are restricted by the MHC class I-related molecule MR1. MAIT cells recognize uncharacterized ligand(s) presented by MR1 through the cognate interaction between their TCR and MR1. To understand how the MAIT TCR recognizes MR1 at the surface of APCs cultured both with and without bacteria, we undertook extensive mutational analysis of both the MAIT TCR and MR1 molecule. We found differential contribution of particular amino acids to the MAIT TCR-MR1 interaction based upon the presence of bacteria, supporting the hypothesis that the structure of the MR1 molecules with the microbial-derived ligand(s) differs from the one with the endogenous ligand(s). Furthermore, we demonstrate that microbial-derived ligand(s) is resistant to proteinase K digestion and does not extract with common lipids, suggesting an unexpected class of antigen(s) might be recognized by this unique lymphocyte population.

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Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 80 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 31%
Researcher 19 23%
Student > Doctoral Student 6 7%
Student > Bachelor 6 7%
Student > Master 4 5%
Other 12 15%
Unknown 9 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 31%
Immunology and Microbiology 22 27%
Medicine and Dentistry 13 16%
Biochemistry, Genetics and Molecular Biology 8 10%
Business, Management and Accounting 1 1%
Other 2 2%
Unknown 10 12%