Single-cell RNA sequencing analysis of T helper cell differentiation and heterogeneity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081707%3A_____%2F22%3A00559610" target="_blank" >RIV/68081707:_____/22:00559610 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/65269705:_____/22:00076202 RIV/00216224:14310/22:00127718

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0167488922001136?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0167488922001136?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.bbamcr.2022.119321" target="_blank" >10.1016/j.bbamcr.2022.119321</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Single-cell RNA sequencing analysis of T helper cell differentiation and heterogeneity

Popis výsledku v původním jazyce

Single-cell transcriptomics has emerged as a powerful tool to investigate cells' biological landscape and focus on the expression profile of individual cells. Major advantage of this approach is an analysis of highly complex and heterogeneous cell populations, such as a specific subpopulation of T helper cells that are known to differentiate into distinct subpopulations. The need for distinguishing the specific expression profile is even more important considering the T cell plasticity. However, importantly, the universal pipelines for single-cell analysis are usually not sufficient for every cell type. Here, the aims are to analyze the diversity of T cell phenotypes employing classical in vitro cytokine-mediated differentiation of human T cells isolated from human peripheral blood by single-cell transcriptomic approach with support of labelled antibodies and a comprehensive bioinformatics analysis using combination of Seurat, Nebulosa, GGplot and others. The results showed high expression similar-ities between Th1 and Th17 phenotype and very distinct Th2 expression profile. In a case of Th2 highly specific marker genes SPINT2, TRIB3 and CST7 were expressed. Overall, our results demonstrate how donor difference, Th plasticity and cell cycle influence the expression profiles of distinct T cell populations. The results could help to better understand the importance of each step of the analysis when working with T cell single-cell data and observe the results in a more practical way by using our analyzed datasets.

Název v anglickém jazyce

Single-cell RNA sequencing analysis of T helper cell differentiation and heterogeneity

Popis výsledku anglicky

Single-cell transcriptomics has emerged as a powerful tool to investigate cells' biological landscape and focus on the expression profile of individual cells. Major advantage of this approach is an analysis of highly complex and heterogeneous cell populations, such as a specific subpopulation of T helper cells that are known to differentiate into distinct subpopulations. The need for distinguishing the specific expression profile is even more important considering the T cell plasticity. However, importantly, the universal pipelines for single-cell analysis are usually not sufficient for every cell type. Here, the aims are to analyze the diversity of T cell phenotypes employing classical in vitro cytokine-mediated differentiation of human T cells isolated from human peripheral blood by single-cell transcriptomic approach with support of labelled antibodies and a comprehensive bioinformatics analysis using combination of Seurat, Nebulosa, GGplot and others. The results showed high expression similar-ities between Th1 and Th17 phenotype and very distinct Th2 expression profile. In a case of Th2 highly specific marker genes SPINT2, TRIB3 and CST7 were expressed. Overall, our results demonstrate how donor difference, Th plasticity and cell cycle influence the expression profiles of distinct T cell populations. The results could help to better understand the importance of each step of the analysis when working with T cell single-cell data and observe the results in a more practical way by using our analyzed datasets.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Biochimica Et Biophysica Acta-Molecular Cell Research

ISSN

0167-4889

e-ISSN

1879-2596

Svazek periodika

1869

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

119321

Kód UT WoS článku

000828701100002

EID výsledku v databázi Scopus

2-s2.0-85134466656