Type I interferons and MAVS signaling are necessary for tissue resident memory CD8+ T cell responses to RSV infection.
Augusto VareseJoy NakawesiAna FariasFreja Cordelia Møller KirsebomMichelle PaulsenRinat NurievCecilia JohanssonPublished in: PLoS pathogens (2022)
Respiratory syncytial virus (RSV) can cause bronchiolitis and viral pneumonia in young children and the elderly. Lack of vaccines and recurrence of RSV infection indicate the difficulty in eliciting protective memory immune responses. Tissue resident memory T cells (TRM) can confer protection from pathogen re-infection and, in human experimental RSV infection, the presence of lung CD8+ TRM cells correlates with a better outcome. However, the requirements for generating and maintaining lung TRM cells during RSV infection are not fully understood. Here, we use mouse models to assess the impact of innate immune response determinants in the generation and subsequent expansion of the TRM cell pool during RSV infection. We show that CD8+ TRM cells expand independently from systemic CD8+ T cells after RSV re-infection. Re-infected MAVS and MyD88/TRIF deficient mice, lacking key components involved in innate immune recognition of RSV and induction of type I interferons (IFN-α/β), display impaired expansion of CD8+ TRM cells and reduction in antigen specific production of granzyme B and IFN-γ. IFN-α treatment of MAVS deficient mice during primary RSV infection restored TRM cell expansion upon re-challenge but failed to recover TRM cell functionality. Our data reveal how innate immunity, including the axis controlling type I IFN induction, instructs and regulates CD8+ TRM cell responses to RSV infection, suggesting possible mechanisms for therapeutic intervention.
Keyphrases
- respiratory syncytial virus
- immune response
- induced apoptosis
- respiratory tract
- single cell
- randomized controlled trial
- cell cycle arrest
- cell therapy
- working memory
- sars cov
- patient safety
- oxidative stress
- endoplasmic reticulum stress
- signaling pathway
- mesenchymal stem cells
- bone marrow
- intensive care unit
- cell death
- deep learning
- cell proliferation
- inflammatory response
- big data
- machine learning
- genome wide
- artificial intelligence
- respiratory failure
- acute respiratory distress syndrome