Digital cell quantification identifies global immune cell dynamics during influenza infection

Zeev Altboum, Yael Steuerman, Eyal David, Zohar Barnett-Itzhaki, Liran Valadarsky, Hadas Keren-Shaul, Tal Meningher, Ella Mendelson, Michal Mandelboim*, Irit Gat-Viks, Ido Amit

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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 genome-wide gene expression data with an immune cell compendium to infer in vivo 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 7 days 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- DCs in early stages of disease and CD8+ pDC in late stages of flu infection.

Original languageEnglish
Article number134947
JournalMolecular Systems Biology
Volume10
Issue number2
DOIs
StatePublished - 1 Feb 2014

Keywords

  • cell quantification
  • deconvolution approach
  • dendritic cells
  • immune cell dynamics
  • influenza infection

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