Maturation signatures of conventional dendritic cell subtypes in COVID-19 reflect direct viral sensing

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Abstract

Growing evidence suggests that conventional dendritic cells (cDCs) undergo aberrant maturation in COVID-19 and this negatively affects T cell activation. The presence of functional effector T cells in mild patients and dysfunctional T cells in severely ill patients suggests that adequate T cell responses are needed to limit disease severity. Therefore, understanding how cDCs cope with SARS-CoV-2 infections can help elucidate the mechanism of generation of protective immune responses. Here, we report that cDC2 subtypes exhibit similar infection-induced gene signatures with the up-regulation of interferon-stimulated genes and IL-6 signaling pathways. The main difference observed between DC2s and DC3s is the up-regulation of anti-apoptotic genes in DC3s, which explains their accumulation during infection. Furthermore, comparing cDCs between severe and mild patients, we find in the former a profound down-regulation of genes encoding molecules involved in antigen presentation, such as major histocompatibility complex class II (MHCII) molecules, β 2 microglobulin, TAP and costimulatory proteins, while an opposite trend is observed for proinflammatory molecules, such as complement and coagulation factors. Therefore, as the severity of the disease increases, cDC2s enhance their inflammatory properties and lose their main function, which is the antigen presentation capacity. In vitro, direct exposure of cDC2s to the virus recapitulates the type of activation observed in vivo. Our findings provide evidence that SARS-CoV-2 can interact directly with cDC2s and, by inducing the down-regulation of crucial molecules required for T cell activation, implements an efficient immune escape mechanism that correlates with disease severity.

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  1. 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.