Longitudinal system-based analysis of transcriptional responses to type I interferons

Pappas DJ, Coppola G, Gabatto PA, Gao F, Geschwind DH, Oksenberg JR, Baranzini SE. Longitudinal system-based analysis of transcriptional responses to type I interferons. Physiol Genomics 38: 362-371, 2009. First published June 16, 2009; doi:10.1152/physiolgenomics.00058.2009.-Type I interferons (IFNs) are pleiotropic cytokines that modulate both innate and adaptive immune responses. They have been used to treat autoimmune disorders, cancers, and viral infection and have been demonstrated to elicit differential responses within cells, despite sharing a single receptor. The molecular basis for such differential responses has remained elusive. To identify the mechanisms underlying differential type I IFN signaling, we used whole genome microarrays to measure longitudinal transcriptional events within human CD4(+) T cells treated with IFN-alpha(2b) or IFN-beta(1a). We identified differentially regulated genes, analyzed them for the enrichment of known promoter elements and pathways, and constructed a network module based on weighted gene coexpression network analysis (WGCNA). WGCNA uses advanced statistical measures to find interconnected modules of correlated genes. Overall, differential responses to IFN in CD4(+) T cells related to three dominant themes: migration, antigen presentation, and the cytotoxic response. For migration, WGCNA identified subtypespecific regulation of pre-mRNA processing factor 4 homolog B and eukaryotic translation initiation factor 4A2, which work at various levels within the cell to affect the expression of the chemokine CCL5. WGCNA also identified sterile alpha-motif domain-containing 9-like (SAMD9L) as critical in subtype-independent effects of IFN treatment. RNA interference of SAMD9L expression enhanced the migratory phenotype of activated T cells treated with IFN-beta compared with controls. Through the analysis of the dynamic transcriptional events after differential IFN treatment, we were able to identify specific signatures and to uncover novel genes that may underpin the type I IFN response.