Differences in the molecular signatures of mucosal-associated invariant T cells and conventional T cells

Park, Daeui; Kim, Hong Gi; Kim, Miok; Park, Tamina; Ha, Hyung‐Ho; Lee, Dong Hoon; Park, Kang-Seo; Park, Seong Jun; Lim, Hae Ja; Lee, Chang Hoon

doi:10.1038/s41598-019-43578-9

Cited by 34 publications

(33 citation statements)

References 27 publications

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“…This pattern was corroborated by analysis of MAIT cells in a second published scRNAseq dataset on bronchoalveolar lavage fluid (33), which also confirmed the coexpression of KLRB1, SLC4A10, and IL7R in TRAV1-2 + cells ( fig. S1D) (34). MAIT cell counts in blood correlated inversely with serum levels of CCL20 and CXCL11 in our cohort ( Fig.…”

Section: Profound Mait Cell Decline In the Circulation And Enrichmentsupporting

confidence: 51%

MAIT cell activation and dynamics associated with COVID-19 disease severity

et al. 2020

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Severe COVID-19 is characterized by excessive inflammation of the lower airways. The balance of protective versus pathological immune responses in COVID-19 is incompletely understood. Mucosa-associated invariant T (MAIT) cells are antimicrobial T cells that recognize bacterial metabolites, and can also function as innate-like sensors and mediators of antiviral responses. Here, we investigated the MAIT cell compartment in COVID-19 patients with moderate and severe disease, as well as in convalescence. We show profound and preferential decline in MAIT cells in the circulation of patients with active disease paired with strong activation. Furthermore, transcriptomic analyses indicated significant MAIT cell enrichment and pro-inflammatory IL-17A bias in the airways. Unsupervised analysis identified MAIT cell CD69high and CXCR3low immunotypes associated with poor clinical outcome. MAIT cell levels normalized in the convalescent phase, consistent with dynamic recruitment to the tissues and later release back into the circulation when disease is resolved. These findings indicate that MAIT cells are engaged in the immune response against SARS-CoV-2 and suggest their possible involvement in COVID-19 immunopathogenesis.

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Section: Profound Mait Cell Decline In the Circulation And Enrichmentsupporting

confidence: 51%

MAIT cell activation and dynamics associated with COVID-19 disease severity

et al. 2020

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“…1B ). Eleven of the downregulated genes in LTBI (CEBPD, SLC4A10, ZBTB16, KLRB1, CCR6, SCRN1, COLQ, PHACTR2, HPGD, GPR65, and IL18RAP) were previously described as part of a transcriptomic signature of CD8 + CD161 hi T cells and Vα7.2 + CD161 + T cells ( 43 – 45 ), which are all populations enriched for MAITs. For example, both KLRB1 (CD161) and CCR6 have previously been described as surface markers of MAITs ( 15 , 19 , 20 ), and ZBTB16 (PLZF) has been identified as a transcription factor expressed by MAITs and other innate-like T cells ( 46 ).…”

Section: Resultsmentioning

confidence: 99%

“…The expression of several genes was confirmed at the protein level by flow cytometry. Previously described genes that are upregulated in MAITs include SLC4A10, LTK, FLT4, and DUSP2 (43,45) as well as downregulated genes LEF1, KLRC4, TBC1D4, ITK, and FYB as compared with memory CD8 + T cells.…”

Section: Discussionmentioning

confidence: 96%

“…For example, the MR1tet 2 cells had lower gene expression of CCR1 than MR1tet + cells, but this was not as evident at the protein level. CXCR4 and CXCR6 were expressed at similar mRNA levels in both MR1tet 2 and tet + cells; however, at the protein level, MR1tet 2 had lower CXCR4 and higher CXCR6 Finally, we wanted to investigate the expression of genes previously described as the transcriptomic signature of CD8 + CD161 hi T cells or described as genes expressed by MAITs (44,45,50) in our two MAIT subsets. Both MR1tet 2 and tet + cells had similar expressions of ZBTB16 (PLZF transcription factor), RORC, KLRB1, CCR6, CCR2, CEBPD, IL-18RAP, and LTK ( Fig.…”

Section: Mr1tet 2 Maits Have a Distinct Gene Expression Profile Compamentioning

confidence: 99%

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Quantitative and Qualitative Perturbations of CD8+ MAITs in Healthy Mycobacterium tuberculosis–Infected Individuals

et al. 2020

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CD8 T cells are considered important contributors to the immune response against Mycobacterium tuberculosis, yet limited information is currently known regarding their specific immune signature and phenotype. In this study, we applied a cell population transcriptomics strategy to define immune signatures of human latent tuberculosis infection (LTBI) in memory CD8 T cells. We found a 41-gene signature that discriminates between memory CD8 T cells from healthy LTBI subjects and uninfected controls. The gene signature was dominated by genes associated with mucosal-associated invariant T cells (MAITs) and reflected the lower frequency of MAITs observed in individuals with LTBI. There was no evidence for a conventional CD8 T cell-specific signature between the two cohorts. We, therefore, investigated MAITs in more detail based on Va7.2 and CD161 expression and staining with an MHC-related protein 1 (MR1) tetramer. This revealed two distinct populations of CD8 + Va7.2 + CD161 + MAITs: MR1 tetramer + and MR1 tetramer 2 , which both had distinct gene expression compared with memory CD8 T cells. Transcriptomic analysis of LTBI versus noninfected individuals did not reveal significant differences for MR1 tetramer + MAITs. However, gene expression of MR1 tetramer 2 MAITs showed large interindividual diversity and a tuberculosis-specific signature. This was further strengthened by a more diverse TCR-a and-b repertoire of MR1 tetramer 2 cells as compared with MR1 tetramer +. Thus, circulating memory CD8 T cells in subjects with latent tuberculosis have a reduced number of conventional MR1 tetramer + MAITs as well as a difference in phenotype in the rare population of MR1 tetramer 2 MAITs compared with uninfected controls. ImmunoHorizons, 2020, 4: 292-307.

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“…For each cancer, the set of genes comprising the finalized MAIT signature was separately defined according to the following ad hoc rules. Of the eleven genes in the full signature, we retained only those that (1) could be significantly correlated with SLC4A10 , which is consistently the most specific MAIT cell-expressed gene across transcriptomic datasets ( 19 , 62 , 63 , 75 , 76 ), (2) were correlated with all other genes or all but one gene comprising the finalized MAIT signature, and (3) were correlated with at least two pan-T cell markers. This step was implemented to specifically discard MAIT signature genes whose expression appeared uncoupled with other MAIT and T cell markers, possibly owing to their expression by non-T cells, and which could thus otherwise confound the estimation of MAIT cell abundance if retained.…”

Section: Methodsmentioning

confidence: 99%