Dissection of intercellular communication using the transcriptome-based framework ICELLNET.
Nat Commun
; 12(1): 1089, 2021 02 17.
Article
em En
| MEDLINE
| ID: mdl-33597528
ABSTRACT
Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain global integration of cell-to-cell communication; biological interpretation; and application to individual cell population transcriptomic profiles. We develop ICELLNET, a transcriptomic-based framework integrating 1) an original expert-curated database of ligand-receptor interactions accounting for multiple subunits expression; 2) quantification of communication scores; 3) the possibility to connect a cell population of interest with 31 reference human cell types; and 4) three visualization modes to facilitate biological interpretation. We apply ICELLNET to three datasets generated through RNA-seq, single-cell RNA-seq, and microarray. ICELLNET reveals autocrine IL-10 control of human dendritic cell communication with up to 12 cell types. Four of them (T cells, keratinocytes, neutrophils, pDC) are further tested and experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Comunicação Celular
/
Bases de Dados Factuais
/
Biologia Computacional
/
Perfilação da Expressão Gênica
/
Transcriptoma
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Nat Commun
Assunto da revista:
BIOLOGIA
/
CIENCIA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
França