GSE49933
RNA-Seq global gene expression in lung tissue at ten time points during a 7-day time course of infection
Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here we devise a computational method, digital cell quantification (DCQ), which combines genomewide gene expression data with an immune cell compendium to infer in vivo dynamical changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during a 7-day time course of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes, and suggest a specific role for CD103+CD11b- cDCs in early stages of disease and CD8+ pDC in late stages of flu infection. Overall design: To study pathogenesis of Influenza infection, C57BL/6 mice (5 weeks) were infected intranasally with 4x103 PFU of influenza PR8 virus. We measured using RNA-Seq global gene expression in lung tissue at ten time points during a 7-day time course of infection, two infected individuals in each time point and four un-infected individuals as control. The lung organ was removed and transferred immediately into RNA Latter solution (Invitrogen).