Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identification of human T cells that recognize a mycobacterial adjuvant, trehalose monomycolate (TMM)

ABSTRACT: Mycobacterium tuberculosis (M. tb) causes tuberculosis (TB) which remains one of the world’s deadliest diseases. As M.tb are protected by its thick lipid cell wall, the host has developed specific immune receptors that recognize their unique lipids as antigens. Among them is a mycolipid-specific T cells restricted by common antigen-presenting molecules, such as CD1. However, complete understanding of their subsets, clonotypes and antigen-specificity has not been fully achieved. Here, we identified novel mycolipid-specific T cells by comprehensive screening using lipid biochemical ´ single cell-TCR-RNA-sequencing-based clonotypic analysis. When human PBMCs were co-cultured with mycobacterial crude lipid extract, a CD4+ CTL-like clone, Y-50, was highly proliferated. Indeed, NFAT-GFP reporter cells reconstituted TCRαβ chains expressed by Y-50 strongly reacted with crude lipids in the presence of monocyte-derived dendritic cells from syngenic/allogenic donors. Activity-based purification of crude lipids identified trehalose monomycolate (TMM) as an antigen. CD1b was necessary and sufficient for the presentation of TMM to be recognized by Y-50. TMM-loaded CD1b tetramer-positive T cells were detected in PBMCs and cord blood cells. The frequency of tetramer+ T cells in PBMCs was higher in active TB patients than uninfected donors. These results demonstrate the presence of novel unconventional T cells in humans that recognize TMM.

ORGANISM(S): Homo sapiens

PROVIDER: GSE261269 | GEO | 2025/02/14

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Identification of CD1b-restricted human T cells recognizing a mycobacterial adjuvant, trehalose monomycolate (TMM)

Project description:Mycobacterium tuberculosis causes tuberculosis (TB) which remains one of the world’s deadliest diseases. As mycobacteria are protected by its thick lipid cell wall, the host has developed immune systems targeting their unique lipids. Among them is an unconventional T cell subset called mycolipid-specific T cells restricted by common antigen-presenting molecules, such as CD1. Here, we identified novel mycolipid-specific T cells using a method combining bulk T cell stimulation with crude lipids and single cell-TCR-RNA-sequencing-based clonotypic analysis. In human PBMCs, a CD4+ T cell clone with cytotoxic signature, Y-50, was proliferated in response to mycobacterial crude lipid extract. Activity-based purification of using reporter cells reconstituted with Y-50 TCR identified trehalose monomycolate (TMM) as an antigen. CD1b was necessary and sufficient for the presentation of TMM to be recognized by Y-50. Y-50 TCRab chains displayed characteristic features, such as positively-charged CDR3a and extra-long CDR3b. Mutagenesis and structural analysis of TCRab suggested that these unique CDR3 properties were required for the recognition of TMM presented by CD1b. CD1b tetramer loaded with TMM could detect T cells with similar characteristics to Y-50 in uninfected healthy donors, but their frequency was significantly higher in PBMCs from TB patients. In this study, we identified pre-set unconventional T cells specific for a mycobacterial adjuvant, TMM.

2025-02-14 | GSE260931 | GEO

CD8+ T cell gene expression after different antigen dose stimulations

Project description:This study aimed to identify the human T cell response toward different antigen doses. Fresh isolated CD8+ T cells from peripheral blood mononuclear cells (PBMCs) were stimulated with influenza M1 peptide-loaded autologous monocyte-derived dendritic cells for 2 weeks. A high M1 peptide antigen dose (10uM on moDC, HD1-5) and an optimal antigen dose (10nM on moDC OD1-5) were used. M1-specific CD8 T cells were tetramer sorted at the end of the 2 weeks. RNA was extracted and analyzed for gene expression using Agilent 8X60K gene expression microarrays. 5 independent samples from 3 different HLA A2+ blood donors.

2013-12-01 | E-GEOD-39761 | biostudies-arrayexpress

CD8+ T cell gene expression after different antigen dose stimulations

2013-12-01 | GSE39761 | GEO

Proteome and lipidome of Urine-derived Exosomes in Mycobacterium tuberculosis Infected Patients

Project description:This study confirmed the aberrant lipids and protein spectrum in exosomes of Mtb infected individuals, uncovered novel potential lipid biomarkers for TB/LTBI diagnosis and revealed integral role of exosomal lipid-raft-dependent biological processes in TB pathogenesis.

2024-03-04 | PXD050345 |

A glance over drug detoxification systems through the transcriptomic profiling of Mycobacterium tuberculosis during lipid metabolism

Project description:Tuberculosis (TB) is currently the number one killer among infectious diseases worldwide. Lipids are abundant molecules during the infectious cycle of Mycobacterium tuberculosis (Mtb) and studies better mimicking its actual metabolic state during pathogenesis are needed. Though most studies have focused on the mycobacterial lipid metabolism under standard conditions (carbon source, drugs, stress), little is known about the transcriptome of Mtb in a lipid environment. Here we determine the transcriptome of Mtb H37Rv in a lipid-rich environment (mixture of cholesterol, palmitic, stearic and oleic acids), under aerobic and hypoxic conditions, using RNAseq technology. Lipids significantly induced the expression of 368 genes. A main core lipid response was observed involving efflux systems, iron caption and sulfur reduction. In co-expression with ncRNAs and other genes discussed below, may act coordinately to prepare the machinery conferring drug tolerance and increasing a persistent population. Our findings could be useful to tag relevant pathways for the development of new drugs, vaccines and new strategies to control TB.

2018-01-12 | GSE100097 | GEO

Human cerebrospinal fluid autoantibody lipid microarray profiling (Fig. 2C)

2012-05-09 | GSE37826 | GEO

Human cerebrospinal fluid autoantibody lipid microarray profiling (Fig. 2A)

2012-05-09 | GSE37670 | GEO

Human cerebrospinal fluid autoantibody lipid microarray profiling (Fig. 1A)

2012-05-09 | GSE37664 | GEO

Human cerebrospinal fluid autoantibody lipid microarray profiling (Fig. 2A)

Project description:Lipids comprise 70% of the myelin sheath, and autoantibodies against lipids may contribute to the demyelination that characterizes multiple sclerosis (MS). We used lipid antigen microarrays and lipid mass spectrometry to identify bona fide lipid targets of the autoimmune response in MS brain and an animal model of MS to explore the role of the identified lipids in autoimmune demyelination. We found that autoantibodies in MS target a phosphate group in phosphatidylserine and oxidized phosphatidylcholine derivatives. Administration of these lipids ameliorated experimental autoimmune encephalomyelitis by suppressing activation and inducing apoptosis of autoreactive T cells, effects mediated by the lipids' saturated fatty-acid side chains. Thus, phospholipids represent a natural anti-inflammatory class of compounds that have potential as novel therapeutics for MS. Fig. 2A. Mini-Array I: IgG antibody reactivity to various glycero-3-phosphocholine lipids in CSF samples from patients with relapsing remitting MS and from control patients with other neurological disease. Lipid hits with the lowest FDR (q=0.029) were clustered according to their reactivity profiles. 47 different lipids were custom-spotted in duplicate using the CAMAG Automatic TLC Sampler (ATS4) robot to spray 200 nl of 10 to 100 pmol of lipids onto PVDF membranes affixed to the surface of microscope slides. The slides were probed with cerebrospinal fluid (CSF) from 24 human patient samples. 25 slides total: 13 relapsing-remitting MS, 11 other neurological disease, and 1 secondary Ab alone (not included in this submission). CSF diluted 1/20. HRP-conjugated secondary Ab (goat anti-human IgM/IgG) diluted 1/175. ECL for 3 minutes.

2012-05-08 | E-GEOD-37670 | biostudies-arrayexpress

Transcriptional signature of MAITs in LTBI (memory CD8 T cells and subsets of TRAV1-2+CD161+ MAITs)

Project description:We applied a cell population transcriptomics strategy to sorted human memory CD8 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and understand the phenotype of tuberculosis (TB)-specific T cells. We found a 41-gene signature that could discriminate between memory CD8 T cells from healthy LTBI subjects and noninfected controls. The gene signature was dominated by genes known to be 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 the MAITs in more detail in these cohorts. Phenotyping based on Vα7.2 and CD161 expression and MR1 tetramers revealed 2 distinct populations of CD8+Vα7.2+CD161+ T cells: MR1 tetramer+ and MR1 tetramer−, both of which had a distinct gene expression profile compared to CD8 memory T cells. Transcriptomic analysis of LTBI vs. noninfected individuals did not reveal significant differences for MR1 tetramer+ cells. However, gene expression of MR1 tetramer− cells showed a very different profile with large inter-individual diversity and a TB-specific signature. This was further strengthened by a more diverse TCR-α and -β repertoire of MR1 tetramer− cells as compared to MR1 tetramer+. Thus, cell population transcriptomics revealed a dominant MAIT signature in CD8 memory T cells that upon detailed investigation provided novel insights into the phenotype of different MAIT populations implicated in tuberculosis.

2020-05-13 | GSE132932 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data