The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
MAIT cells are licensed through granzyme exchange to kill bacterially sensitized targets
Open accessAbstract
Mucosal-associated invariant T (MAIT) cells are an innate-like T-cell population restricted by the non-polymorphic, major histocompatibility complex class I-related protein 1, MR1. MAIT cells are activated by a broad range of bacteria through detection of riboflavin metabolites bound by MR1, but their direct cytolytic capacity upon recognition of cognate target cells remains unclear. We show that resting human MAIT cells are uniquely characterized by a lack of granzyme (Gr) B and low perforin expression, key granule proteins required for efficient cytotoxic activity, but high levels of expression of GrA and GrK. Bacterial activation of MAIT cells rapidly induced GrB and perforin, licensing these cells to kill their cognate target cells. Using a novel flow cytometry-based killing assay, we show that licensed MAIT cells, but not ex vivo MAIT cells from the same donors, can efficiently kill Escherichia coli-exposed B-cell lines in an MR1- and degranulation-dependent manner. Finally, we show that MAIT cells are highly proliferative in response to antigenic and cytokine stimulation, maintaining high expression of GrB, perforin, and GrA, but reduced expression of GrK following antigenic proliferation. The tightly regulated cytolytic capacity of MAIT cells may have an important role in the control of intracellular bacterial infections, such as Mycobacterium tuberculosis.
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Betts, M. R., Brenchley, J. M., Price, D. A., De Rosa, S. C., Douek, D. C., Roederer, M., & Koup, R. A. (2003) · Journal of Immunological Methods · doi:10.1016/s0022-1759(03)00265-5 · Cited by 1,587
MR1 presents microbial vitamin B metabolites to MAIT cells
Kjer-Nielsen, L., Patel, O., Corbett, A. J., Le Nours, J., Meehan, B., Liu, L., Bhati, M., Chen, Z., Kostenko, L., Reantragoon, R., et al. (2012) · Nature · doi:10.1038/nature11605 · Cited by 1,351
Selection of evolutionarily conserved mucosal-associated invariant T cells by MR1
Treiner, E., Duban, L., Bahram, S., Radosavljevic, M., Wanner, V., Tilloy, F., Affaticati, P., Gilfillan, S., & Lantz, O. (2003) · Nature · doi:10.1038/nature01433 · Cited by 1,139
Human MAIT cells are xenobiotic-resistant, tissue-targeted, CD161hi IL-17–secreting T cells
Dusseaux, M., Martin, E., Serriari, N., Péguillet, I., Premel, V., Louis, D., Milder, M., Le Bourhis, L., Soudais, C., Treiner, E., et al. (2011) · Blood · doi:10.1182/blood-2010-08-303339 · Cited by 1,027
Antimicrobial activity of mucosal-associated invariant T cells
Le Bourhis, L., Martin, E., Péguillet, I., Guihot, A., Froux, N., Coré, M., Lévy, E., Dusseaux, M., Meyssonnier, V., Premel, V., et al. (2010) · Nature Immunology · doi:10.1038/ni.1890 · Cited by 936
SPICE: Exploration and analysis of post‐cytometric complex multivariate datasets
Roederer, M., Nozzi, J. L., & Nason, M. C. (2011) · Cytometry Part A · doi:10.1002/cyto.a.21015 · Cited by 831
Death by a Thousand Cuts: Granzyme Pathways of Programmed Cell Death
Chowdhury, D., & Lieberman, J. (2008) · Annual Review of Immunology · doi:10.1146/annurev.immunol.26.021607.090404 · Cited by 700
Human Mucosal Associated Invariant T Cells Detect Bacterially Infected Cells
Gold, M. C., Cerri, S., Smyk-Pearson, S., Cansler, M. E., Vogt, T. M., Delepine, J., Winata, E., Swarbrick, G. M., Chua, W.-J., Yu, Y. Y. L., et al. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000407 · Cited by 673
Self-citationMigueles, S. A., Osborne, C. M., Royce, C., Compton, A. A., Joshi, R. P., Weeks, K. A., Rood, J. E., Berkley, A. M., Sacha, J. B., Cogliano-Shutta, N. A., et al. (2008) · Immunity · doi:10.1016/j.immuni.2008.10.010 · Cited by 590
Reantragoon, R., Corbett, A. J., Sakala, I. G., Gherardin, N. A., Furness, J. B., Chen, Z., Eckle, S. B. G., Uldrich, A. P., Birkinshaw, R. W., Patel, O., et al. (2013) · Journal of Experimental Medicine · doi:10.1084/jem.20130958 · Cited by 589
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Mucosal-associated invariant T cells and disease
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Jeffery, H. C., van Wilgenburg, B., Kurioka, A., Parekh, K., Stirling, K., Roberts, S., Dutton, E. E., Hunter, S., Geh, D., Braitch, M. K., et al. (2016) · Journal of Hepatology · doi:10.1016/j.jhep.2015.12.017 · Cited by 212
Self-citationRiva, A., Patel, V., Kurioka, A., Jeffery, H. C., Wright, G., Tarff, S., Shawcross, D., Ryan, J. M., Evans, A., Azarian, S., et al. (2018) · Gut · doi:10.1136/gutjnl-2017-314458 · Cited by 150
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Metadata
- Authors
- Kurioka, A., Ussher, J. E., Cosgrove, C., Clough, C., Fergusson, J. R., Smith, K., Kang, Y.-H., Walker, L. J., Hansen, T. H., Willberg, C. B., & Klenerman, P.
- Venue
- Mucosal Immunology
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 8
- Issue
- 2
- Pages
- 429-440
- ISSN
- 1933-0219 (ISSN-L)
- OpenAlex
- W2042172298
- Cited by
- 398
- References
- 53
- FWCI
- 9.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Kurioka, A., Ussher, J. E., Cosgrove, C., Clough, C., Fergusson, J. R., Smith, K., Kang, Y.-H., Walker, L. J., Hansen, T. H., Willberg, C. B., & Klenerman, P. (2015). MAIT cells are licensed through granzyme exchange to kill bacterially sensitized targets. Mucosal Immunology. https://doi.org/10.1038/mi.2014.81
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