Life-threatening influenza pneumonitis in a child with inherited IRF9 deficiency

Hernandez, Nicholas; Melki, Isabelle; Jing, Huie; Habib, Tanwir; Huang, Susie S.Y.; Danielson, Jeffrey; Kula, Tomasz; Drutman, Scott; Belkaya, Serkan; Rattina, Vimel; Lorenzo-Diaz, Lazaro; Boulai, Anais; Rose, Yoann; Kitabayashi, Naoki; Rodero, Mathieu P.; Dumaine, Cecile; Blanche, Stéphane; Lebras, Marie-Noëlle; Leung, Man Chun; Mathew, Lisa Sara; Boisson, Bertrand; Zhang, Shen-Ying; Boisson-Dupuis, Stephanie; Giliani, Silvia; Chaussabel, Damien; Notarangelo, Luigi D.; Elledge, Stephen J.; Ciancanelli, Michael J.; Abel, Laurent; Zhang, Qian; Marr, Nico; Crow, Yanick J.; Su, Helen C.; Casanova, Jean-Laurent

Total RNA from IFN-α2b-stimulated B-LCL and primary fibroblast cells was isolated (RNeasy kit; QIA GEN), and RNA integrity was assessed on an Agilent 2100 Bioanalyzer (Agilent Technologies). Poly (A)mRNA enrichment and cDNA library preparation was performed using a TruSeq Stranded mRNA Library Prep Kit (Illumina) in accordance with the manufacturer's recommendations. Paired-end sequencing was performed on a HiSeq4000 (Illumina) with 150 cycles. Quality control of the raw Fastq files was performed using FastQC (Andrews, 2010) . The samples were then aligned to the reference genome (Ensembl GRCh37) using a STAR aligner (Dobin et al., 2013) . Aligned output was then converted to BAM files using SAMtools ). The resulting BAM files were used to quantify the read counts using the HTseqcount tool (Anders et al., 2015) . The output of technical repeats (patient samples that had been stimulated in duplicate) was found to have a high correlation coefficient (not shown). Subsequent downstream analysis was performed in the R statistical programming language (Team, 2008) . Read counts of technical repeats were averaged, and IFN-α2b-responsive transcripts were identified by comparing stimulated against unstimulated conditions in the three healthy control subjects, using a minimal 1.5fold change in expression (up-regulated or down-regulated) as the cut-off. The response gene lists only those that had satisfied the filter criteria in all three controls. This resulted in a total of 1,064 and 1,576 genes that were responsive in the IFN-α2b-stimulated B-LCL and primary fibroblasts, respectively. The gene lists were then used to identify, again using a 1.5-fold change as cutoff, IFN-α2b-responsive and unresponsive genes in the cells of IRF9-, STAT1-, and STAT2-deficient patients. The overall residual responses in the patient's cells were computed by counting the responsive genes in each patient and cell type and by calculating the percentage out of the total number of response genes in each cell type. The response in the healthy control subject was set at 100%. We used MS Excel to filter for response genes that are common or unique to specific patients for subsequent analysis.