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

Urrutia, Alejandra (author)
Pasteur Institute,Genentech, Inc
Duffy, Darragh (author)
Pasteur Institute
Rouilly, Vincent (author)
Pasteur Institute
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Posseme, Céline (author)
Pasteur Institute
Djebali, Raouf (author)
Pasteur Institute
Illanes, Gabriel (author)
Pasteur Institute,University of the Republic
Libri, Valentina (author)
Pasteur Institute
Albaud, Benoit (author)
Curie Institute, Paris
Gentien, David (author)
Curie Institute, Paris
Piasecka, Barbara (author)
Pasteur Institute
Hasan, Milena (author)
Pasteur Institute
Fontes, Magnus (author)
Lund University,Lunds universitet,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,Pasteur Institute
Quintana-Murci, Lluis (author)
Pasteur Institute
Albert, Matthew L. (author)
Pasteur Institute
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 (creator_code:org_t)
 
Elsevier BV, 2016
2016
English 15 s.
In: Cell Reports. - : Elsevier BV. - 2211-1247. ; 16:10, s. 2777-2791
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Cell- och molekylärbiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Cell and Molecular Biology (hsv//eng)

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