Mapping the epithelial–immune cell interactome upon infection in the gut and the upper airways View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-05-02

AUTHORS

Martina Poletti, Agatha Treveil, Luca Csabai, Leila Gul, Dezso Modos, Matthew Madgwick, Marton Olbei, Balazs Bohar, Alberto Valdeolivas, Denes Turei, Bram Verstockt, Sergio Triana, Theodore Alexandrov, Julio Saez-Rodriguez, Megan L. Stanifer, Steeve Boulant, Tamas Korcsmaros

ABSTRACT

Increasing evidence points towards the key role of the epithelium in the systemic and over-activated immune response to viral infection, including SARS-CoV-2 infection. Yet, how viral infection alters epithelial–immune cell interactions regulating inflammatory responses, is not well known. Available experimental approaches are insufficient to properly analyse this complex system, and computational predictions and targeted data integration are needed as an alternative approach. In this work, we propose an integrated computational biology framework that models how infection alters intracellular signalling of epithelial cells and how this change impacts the systemic immune response through modified interactions between epithelial cells and local immune cell populations. As a proof-of-concept, we focused on the role of intestinal and upper-airway epithelial infection. To characterise the modified epithelial–immune interactome, we integrated intra- and intercellular networks with single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids as well as from infected airway ciliated epithelial cells. This integrated methodology has proven useful to point out specific epithelial–immune interactions driving inflammation during disease response, and propose relevant molecular targets to guide focused experimental analysis. More... »

PAGES

15

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41540-022-00224-x

    DOI

    http://dx.doi.org/10.1038/s41540-022-00224-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1147540011

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/35501398


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