Imperfect innate immune antagonism renders SARS-CoV-2 vulnerable towards IFN-γ and -λ

  1. Manuel Hayn
  2. Maximilian Hirschenberger
  3. Lennart Koepke
  4. Jan H Straub
  5. Rayhane Nchioua
  6. Maria H Christensen
  7. Susanne Klute
  8. Caterina Prelli Bozzo
  9. Wasim Aftab
  10. Fabian Zech
  11. Carina Conzelmann
  12. Janis A Müller
  13. Smitha Srinivasachar Badarinarayan
  14. Christina M Stürzel
  15. Ignasi Forne
  16. Steffen Stenger
  17. Karl-Klaus Conzelmann
  18. Jan Münch
  19. Daniel Sauter
  20. Florian I Schmidt
  21. Axel Imhof
  22. Frank Kirchhoff
  23. Konstantin MJ Sparrer

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Abstract

The innate immune system constitutes a powerful barrier against viral infections. However, it may fail because successful emerging pathogens, like SARS-CoV-2, evolved strategies to counteract it. Here, we systematically assessed the impact of 29 SARS-CoV-2 proteins on viral sensing, type I, II and III interferon (IFN) signaling, autophagy and inflammasome formation. Mechanistic analyses show that autophagy and type I IFN responses are effectively counteracted at different levels. For example, Nsp14 induces loss of the IFN receptor, whereas ORF3a disturbs autophagy at the Golgi/endosome interface. Comparative analyses revealed that antagonism of type I IFN and autophagy is largely conserved, except that SARS-CoV-1 Nsp15 is more potent in counteracting type I IFN than its SARS-CoV-2 ortholog. Altogether, however, SARS-CoV-2 counteracts type I IFN responses and autophagy much more efficiently than type II and III IFN signaling. Consequently, the virus is relatively resistant against exogenous IFN-α/β and autophagy modulation but remains highly vulnerable towards IFN-γ and -λ treatment. In combination, IFN-γ and -λ act synergistically, and drastically reduce SARS-CoV-2 replication at exceedingly low doses. Our results identify ineffective type I and II antagonism as weakness of SARS-CoV-2 that may allow to devise safe and effective anti-viral therapies based on targeted innate immune activation.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.15.340612: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Proteins were stained using primary antibodies against β-actin (1:10,000, AC-15, Sigma), strep II-tag (1:1,000, NBP2-43735, Novus), strep II-tag (1:2,000, ab76949, abcam), GAPDH (1:1,000, 607902, Biolegend), pSTAT1 (1:1,000, Y701, Cell Signaling Technology), STAT1 (1:1,000, 9172S, Cell Signaling Technology), pSTAT2 (1:1,000, Y690, Cell Signaling Technology), STAT2 (1:1,000, 4594S, Cell Signaling Technology), IFNAR1 (1:1,000, ab45172, abcam), p62 (1:1,000, GP62-N, ProGen), LC3a/β (1:200
    β-actin
    suggested: (Sigma-Aldrich Cat# A5441, RRID:AB_476744)
    GAPDH
    suggested: (BioLegend Cat# 607902, RRID:AB_2734503)
    pSTAT1
    suggested: (Fluidigm Cat# 3153003, RRID:AB_2661824)
    Y701 , Cell Signaling Technology) , STAT1
    suggested: None
    9172S , Cell Signaling Technology) , pSTAT2 ( 1:1,000 , Y690 , Cell Signaling Technology) , STAT2
    suggested: None
    IFNAR1
    suggested: (Abcam Cat# ab45172, RRID:AB_775764)
    p62
    suggested: (Progen Cat# GP62-N, RRID:AB_2801426)
    GP62-N
    suggested: (Progen Cat# GP62-N, RRID:AB_2801426)
    LC3a/β
    suggested: None
    , M2, Sigma), V5-tag (1:1,000, D3H8Q, Cell Signaling Technology), SARS-CoV-2 (COVID-19) spike antibody (1:1000, 1A9, Biozol), SARS-CoV/SARS-CoV-2
    V5-tag
    suggested: (Cell Signaling Technology Cat# 13202, RRID:AB_2687461)
    The cells were stained using primary antibodies against strep II-tag (1:200, NBP2-43735, Novus) and TGN46 (1:400, AHP500GT, Bio Rad), secondary antibodies fluorescently labelled with AlexaFluor568 targeting rabbit-IgGs (1:400, A10042, Invitrogen) and AlexaFluor647 targeting sheep-IgG (1:400, A21448, Invitrogen), and DAPI (1:1,000) to stain nuclei.
    NBP2-43735
    suggested: None
    TGN46
    suggested: (Bio-Rad Cat# AHP500GT, RRID:AB_2203291)
    A10042
    suggested: (Thermo Fisher Scientific Cat# A10042, RRID:AB_2534017)
    AlexaFluor647 targeting sheep-IgG
    suggested: None
    A21448
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Cell lines and cell culture and viruses: HEK293T cells were purchased from American type culture collection (ATCC: #CRL3216).
    HEK293T
    suggested: ATCC Cat# CRL-3216, RRID:CVCL_0063)
    Generation of stable THP-1 cells: THP-1 cell liens were generated by transduction with lentivirus generated with the indicated pLVX-EF1alpha vectors (kind gift from Nevan Krogan), as well as packaging vectors psPax2 and pMD2.
    THP-1
    suggested: CLS Cat# 300356/p804_THP-1, RRID:CVCL_0006)
    Immunofluorescence: HeLa GL cells were transfected using TransIT-LT1 and grown on coverslips in 24-well plates.
    HeLa GL
    suggested: None
    Inhibition of SARS-CoV-2 by immune modulation: 300,000 Calu-3 cells were seeded in 12-well plates.
    Calu-3
    suggested: None
    The viruses were propagated by infecting 70% confluent Vero E6 in 75 cm2 cell culture flasks at a MOI of 0.003 in 3.5 ml serum-free medium containing 1 μg/ml trypsin.
    Vero E6
    suggested: None
    Proteome analysis: For the proteome analysis of infected cells, 0.6×106 Caco-2 cells were infected with SARS-CoV-2 BetaCoV/Netherlands/01/NL/2020 at an MOI of 0.5 and harvested 24 h and 48 h post infection with TM lysis buffer supplemented with 1:500 protease inhibitor.
    Caco-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Images were acquired using a Zeiss LSM710 and analyzed with Fiji ImageJ.
    Fiji
    suggested: (Fiji, RRID:SCR_002285)
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD021899.
    PRIDE
    suggested: (Pride-asap, RRID:SCR_012052)
    MaxQuant 1.6.15.0 was used to identify proteins and quantify by LFQ with the following parameters: Database, Uniprot_AUP000005640_Hsapiens_20200120.fasta supplemented with the sequences of NSP1_V5, NSP7_V5, NSP15_V5, NSP16_V5, E_V5, M_V5, N_V5, S_V5, ORF3_V5, ORF6_V5, ORF7_V5 and Spike protein from SARSCoV239; MS tol, 10ppm; MS/MS tol, 20ppm
    MaxQuant
    suggested: (MaxQuant, RRID:SCR_014485)
    GO Analysis: From the proteome of the respective samples, proteins regulated more than 4-fold compared to the vector control were extracted and submitted to PANTHER (cellular component analysis).
    PANTHER
    suggested: (PANTHER, RRID:SCR_004869)
    We used MATLAB 2019b for the half-life analysis.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)
    Statistical analysis: Statistical analyses were performed using GraphPad PRISM 8 (GraphPad Software).
    GraphPad PRISM
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: Thank you for sharing your data.

    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: We did not find any issues relating to colormaps.

    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.

  2. Version published to 10.1101/2020.10.15.340612 on bioRxiv