Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses.

Détails

ID Serval
serval:BIB_5EC5E6043FB7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Standardized Whole-Blood Transcriptional Profiling Enables the Deconvolution of Complex Induced Immune Responses.
Périodique
Cell reports
Auteur(s)
Urrutia A., Duffy D., Rouilly V., Posseme C., Djebali R., Illanes G., Libri V., Albaud B., Gentien D., Piasecka B., Hasan M., Fontes M., Quintana-Murci L., Albert M.L.
Collaborateur(s)
Milieu Intérieur Consortium
Contributeur(s)
Abel L., Alcover A., Astrom K., Bousso P., Bruhns P., Cumano A., Demangel C., Deriano L., Di Santo J., Dromer F., Eberl G., Enninga J., Fellay J., Freitas A., Gelpi O., Gomperts-Boneca I., Hercberg S., Lantz O., Leclerc C., Mouquet H., Pellegrini S., Pol S., Rogge L., Sakuntabhai A., Schwartz O., Schwikowski B., Shorte S., Soumelis V., Tangy F., Tartour E., Toubert A., Ungeheuer M.N., Quintana-Murci L., Albert M.L.
ISSN
2211-1247 (Electronic)
Statut éditorial
Publié
Date de publication
06/09/2016
Peer-reviewed
Oui
Volume
16
Numéro
10
Pages
2777-2791
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Systems approaches for the study of immune signaling pathways have been traditionally based on purified cells or cultured lines. However, in vivo responses involve the coordinated action of multiple cell types, which interact to establish an inflammatory microenvironment. We employed standardized whole-blood stimulation systems to test the hypothesis that responses to Toll-like receptor ligands or whole microbes can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, that captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. Furthermore, we used donor variability to identify shared inter-cellular pathways and trace cytokine loops involved in gene expression. This provides strategies for dimension reduction of large datasets and deconvolution of innate immune responses applicable for characterizing immunomodulatory molecules. Moreover, we provide an interactive R-Shiny application with healthy donor reference values for induced inflammatory genes.
Mots-clé
Adult, Bacteria/metabolism, Blood/metabolism, Cytokines/pharmacology, Female, Gene Expression Profiling/methods, Gene Expression Regulation/drug effects, Humans, Immunity/drug effects, Immunity/genetics, Lymphocytes/metabolism, Male, Toll-Like Receptors/metabolism, Transcription, Genetic/drug effects
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/10/2017 10:03
Dernière modification de la notice
15/07/2020 6:26
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