AllergyImmunologyPeer-reviewed journal article
Epithelial memory after respiratory viral infection results in long-lasting enhancement of antigen presentation
Piotr P. JanasiD, Wouter T’JonckiD, Matthew O. BurgessiD, Maximilian ReckiD, Caroline ChauchéiD, Matthieu VermereniD, Christopher D. LucasiD, Calum C. BainiD, Robert Scott IllingworthiD, Edward W. RobertsiD, Henry J. McSorleyiD, Jürgen SchwarzeiD
Abstract
BackgroundViral lower respiratory tract infections (LRTIs) can reduce severity of subsequent LRTIs but have also been linked to respiratory allergy development and exacerbation. Here, we show that viral LRTI can imprint lung epithelial cells (LECs), leading to long-term phenotypic and functional changes in their response to subsequent challenges. MethodsMice were infected via intranasal administration of respiratory syncytial virus (RSV). After 28 days, LECs were isolated using cold dispase digestion followed by magnetic-activated cell sorting. Epigenetic changes were assessed using CUT&RUN, while transcriptional changes were evaluated using NanoString and qPCR. Flow cytometry was employed to measure cell surface MHC levels, antigen uptake and processing rates, and OT-I proliferation. ResultsWe identified epigenetic and transcriptomic changes in murine LECs 28 days post respiratory syncytial virus (RSV) infection after recovery in genes associated with major histocompatibility complexes (MHC). Lasting upregulation of MHC-I and MHC-II was further increased following in vivo LPS stimulation. Importantly, MHC upregulation was associated with increased antigen uptake and processing, as well as increased antigen presentation to T cells. ConclusionsOur data suggest that LRTI can induce long-term upregulation of antigen-presentation by LECs, thus facilitating local T cell responses to microbial antigens and allergens, potentially enhancing immunity or in susceptible hosts respiratory allergy.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 3
- FWCI
- 1.78
- Field percentile
- top 15%
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