Maturation signatures of conventional dendritic cell subtypes in COVID‐19 suggest direct viral sensing

  1. Laura Marongiu
  2. Giulia Protti
  3. Fabio A. Facchini
  4. Mihai Valache
  5. Francesca Mingozzi
  6. Valeria Ranzani
  7. Anna Rita Putignano
  8. Lorenzo Salviati
  9. Valeria Bevilacqua
  10. Serena Curti
  11. Mariacristina Crosti
  12. Maria Lucia Sarnicola
  13. Mariella D'Angiò
  14. Laura Rachele Bettini
  15. Andrea Biondi
  16. Luca Nespoli
  17. Nicolò Tamini
  18. Nicola Clementi
  19. Nicasio Mancini
  20. Sergio Abrignani
  21. Roberto Spreafico
  22. Francesca Granucci

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Abstract

Growing evidence suggests that conventional dendritic cells (cDCs) undergo aberrant maturation in COVID‐19, which negatively affects T‐cell activation. The presence of effector T cells in patients with mild disease and dysfunctional T cells in severely ill patients suggests that adequate T‐cell responses limit disease severity. Understanding how cDCs cope with SARS‐CoV‐2 can help elucidate how protective immune responses are generated. Here, we report that cDC2 subtypes exhibit similar infection‐induced gene signatures, with the upregulation of IFN‐stimulated genes and IL‐6 signaling pathways. Furthermore, comparison of cDCs between patients with severe and mild disease showed severely ill patients to exhibit profound downregulation of genes encoding molecules involved in antigen presentation, such as MHCII, TAP, and costimulatory proteins, whereas we observed the opposite for proinflammatory molecules, such as complement and coagulation factors. Thus, as disease severity increases, cDC2s exhibit enhanced inflammatory properties and lose antigen presentation capacity. Moreover, DC3s showed upregulation of anti‐apoptotic genes and accumulated during infection. Direct exposure of cDC2s to the virus in vitro recapitulated the activation profile observed in vivo. Our findings suggest that SARS‐CoV‐2 interacts directly with cDC2s and implements an efficient immune escape mechanism that correlates with disease severity by downregulating crucial molecules required for T‐cell activation.

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  1. Version published to 10.1002/eji.202149298
  2. Version published to 10.1101/2021.03.03.433597v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.03.433597: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were washed twice and stained for 30 minutes on ice using the following anti-human antibodies (1:200, Becton Dickinson): anti-FcεRIα PE-Cy7, anti-CD14 PE, anti-CD1c APC-Cy7, anti-Clec9 (CD370) Alexa 647, anti-CD5 BV786, anti-CD3 BV605, anti-CD19 BV605, anti-CD88 BV605, anti-CD89 BV605, anti-CD11c BV480, anti-CD163 BV421, anti-HLA-DR BUV805.
    anti-human antibodies
    suggested: (BD Biosciences Cat# 746339, RRID:AB_2743660)
    anti-FcεRIα PE-Cy7, anti-CD14 PE, anti-CD1c APC-Cy7, anti-Clec9
    suggested: None
    PE-Cy7
    suggested: (Fitzgerald Industries International Cat# 61R-CD11aaMSPE7, RRID:AB_1282980)
    anti-CD14
    suggested: (BD Biosciences Cat# 563698, RRID:AB_2744287)
    anti-CD1c APC-Cy7
    suggested: None
    anti-CD5
    suggested: (BD Biosciences Cat# 740842, RRID:AB_2740496)
    BV786, anti-CD3 BV605,
    suggested: None
    anti-CD3
    suggested: None
    anti-CD19
    suggested: (BD Biosciences Cat# 742007, RRID:AB_2871305)
    anti-CD88
    suggested: (BD Biosciences Cat# 746588, RRID:AB_2743871)
    anti-CD89
    suggested: (BD Biosciences Cat# 744376, RRID:AB_2742189)
    anti-CD11c BV480
    suggested: (BD Biosciences Cat# 565627, RRID:AB_2739309)
    anti-CD163
    suggested: (BD Biosciences Cat# 749201, RRID:AB_2873579)
    anti-HLA-DR
    suggested: (BD Biosciences Cat# 748338, RRID:AB_2872757)
    Cells were then fixed and permeabilized with cytofix/cytoperm reagent kit (Becton Dickinson) and stained with anti-IL-6 FITC antibody, according to the manufacturer’s instructions.
    anti-IL-6 FITC
    suggested: None
    Software and Algorithms
    SentencesResources
    Flow cytometric analysis: PBMCs from COVID-19 patients enrolled from the STORM cohort were extracted from peripheral blood by density gradient centrifugation using Ficoll (GE Healthcare).
    STORM
    suggested: (SToRM, RRID:SCR_006696)
    Analyses were performed with Flow jo X software.
    Flow jo
    suggested: None
    Samples were acquired with the BD FACSsymphony instrument (Becton Dickinson) and analyzed with Kaluza software.
    Kaluza
    suggested: (Kaluza, RRID:SCR_016182)
    Count matrices were downloaded from the Gene Expression Omnibus (GEO) (GSE155673).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Single-cell data processing and analysis: Data processing and analysis for all single-cell datasets was performed using the Seurat package (version 4.0) (26) in R (version 4.0.3).
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    Differential expression analysis was performed using the quasi-likelihood framework of the edgeR package (35), using each donor as the unit of independent replication.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 25 and 18. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2021.03.03.433597v1 on bioRxiv