Transcriptomics

Dataset Information

0

Natural killer T-cell characterization through gene expression profiling


ABSTRACT: Natural killer T (NKT) cells are a distinct lymphocyte lineage thought to operate primarily at the interface between the innate and adaptive immune response. Yet, their unique role in the immune system remains elusive. Whilst NKT cells show high similarities to other cells of the innate and adaptive immune system, they express unique functional features such as rapid, concomitant production of Th1 and Th2 cytokines upon TCR ligation. In order to portray gene expression of NKT cells and to analyze their complete functional potential, we performed comparative microarray analyses of naive NKT cells, naive NK cells as well as naive conventional CD4+ T cells (Th, CD4+CD25–) and naive regulatory CD4+CD25+ T cells (Treg ). Furthermore, we compared the gene expression profiles of naive versus alpha-galactosylceramide activated NKT cells to elucidate the gene set rapidly expressed upon activation. We describe profound gene expression differences between the different cell types as well as between naive and activated NKT cells allowing the identification of a unique gene expression profile of NKT cells. In addition to known NKT cell specific markers, a high number of genes were expressed and detected which had not been attributed to NKT cells. Notably, our analyses reveals that NKT cells are not only of Th1 and Th2 type but also fulfil criteria of Th17 cells. Hence, our data provide new insight into the genetic décor of NKT cells which will facilitate a better understanding of their versatile role during the immune response. Keywords: NKT, NK, Th and Treg cell type comparison

ORGANISM(S): Mus musculus

PROVIDER: GSE6782 | GEO | 2007/02/01

SECONDARY ACCESSION(S): PRJNA98927

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2023-11-27 | MODEL1909260003 | BioModels
2009-06-01 | E-MEXP-2153 | biostudies-arrayexpress
2019-02-14 | PXD004532 | Pride
2023-01-04 | PXD036065 | JPOST Repository
2017-11-10 | E-MTAB-5739 | biostudies-arrayexpress
2014-07-18 | GSE56179 | GEO
2022-08-05 | GSE200250 | GEO
2024-09-02 | BIOMD0000000769 | BioModels
2024-09-02 | BIOMD0000000770 | BioModels
2010-06-10 | E-GEOD-8352 | biostudies-arrayexpress