High titers and low fucosylation of early human anti–SARS-CoV-2 IgG promote inflammation by alveolar macrophages

  1. Willianne Hoepel
  2. Hung-Jen Chen
  3. Chiara E. Geyer
  4. Sona Allahverdiyeva
  5. Xue D. Manz
  6. Steven W. de Taeye
  7. Jurjan Aman
  8. Lynn Mes
  9. Maurice Steenhuis
  10. Guillermo R. Griffith
  11. Peter I. Bonta
  12. Philip J.M. Brouwer
  13. Tom G. Caniels
  14. Karlijn van der Straten
  15. Korneliusz Golebski
  16. René E. Jonkers
  17. Mads D. Larsen
  18. Federica Linty
  19. Jan Nouta
  20. Cindy P.A.A. van Roomen
  21. Frank E.H.P. van Baarle
  22. Cornelis M. van Drunen
  23. Gertjan Wolbink
  24. Alexander P.J. Vlaar
  25. Godelieve J. de Bree
  26. Rogier W. Sanders
  27. Lisa Willemsen
  28. Annette E. Neele
  29. Diederik van de Beek
  30. Theo Rispens
  31. Manfred Wuhrer
  32. Harm Jan Bogaard
  33. Marit J. van Gils
  34. Gestur Vidarsson
  35. Menno de Winther
  36. Jeroen den Dunnen

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Abstract

High titers and low fucosylation of human anti–spike protein IgG promote alveolar macrophage activation and inflammation.

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  1. Version published to 10.1126/scitranslmed.abf8654
  2. ScreenIT

    SciScore for 10.1101/2020.07.13.190140: (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

    Software and Algorithms
    SentencesResources
    Materials and Methods:
    Methods
    suggested: None

    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: 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.

  3. preLights

    Excerpt

    Two recent preprints indicate that Fostamatinib might help with severe COVID-19 symptoms and point to the importance of detailed examination of immune response to COVID-19 vaccines.

  4. ScreenIT

    SciScore for 10.1101/2020.07.13.190140: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementAll the subjects provided written informed consent prior to donation to Sanquin.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableThe DIVA study includes healthy male volunteers aged 18-35.Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Previously, it has been shown that the virus leading to SARS, SARS-CoV, causes severe inflammation and lung injury through IgG antibodies(9).
    antibodies(9
    suggested: None
    Notably, SARS patients that eventually died from infection displayed similar conversion of these wound-healing lung macrophages, as well as the early and high presence of neutralizing IgG antibodies.
    neutralizing IgG
    suggested: None
    Very similar to SARS, severe COVID-19 patients are characterized by an early rise and high titers of IgG antibodies(10-12) and show a similar conversion from anti- to proinflammatory lung macrophages(13).
    antibodies(10-12
    suggested: None
    Therefore, in this study we explored the hypothesis that, similar to responses in SARS, anti-Spike antibodies drive excessive inflammation in severe cases of COVID-19.
    anti-Spike
    suggested: None
    Since activation of immune cells by IgG antibodies is known to require immune complex formation by binding of IgG to its ligand(15, 16), we generated Spike-IgG immune complexes by incubating SARS-CoV-2 Spike-coated wells with diluted serum from severely ill COVID-19 patients (i.e. patients from the intensive care unit at the Amsterdam UMC) that tested positive for anti-SARSCoV-2 IgG.
    anti-SARSCoV-2 IgG
    suggested: None
    In addition to the anti-Spike antibodies from serum, we tested the effect of the recombinant anti-Spike IgG COVA1-18, which we generated previously from B cells of COVID-19 patients(22).
    anti-Spike IgG COVA1-18
    suggested: None
    To test the efficacy of our recombinant anti-Spike IgG, we stimulated macrophages with anti-Spike immune complexes made with a high concentration (mimicking a serum concentration of 100 μg/mL in our assay) of the recombinant antibody COVA1-18.
    anti-Spike IgG
    suggested: None
    These data indicate that antiSpike IgG from COVID-19 patients has an aberrant glycosylation pattern that makes these antibodies intrinsically more inflammatory than ‘common’ IgGs by increasing its capacity to induce high amounts of pro-inflammatory cytokines.
    antiSpike IgG
    suggested: None
    To determine how this antibodyinduced inflammation could be counteracted, we first set out to investigate which receptors on human macrophages are activated by the anti-SARS-CoV-2 IgG immune complexes.
    anti-SARS-CoV-2 IgG
    suggested: None
    These different effector functions of antibodies are modulated by antibody-intrinsic characteristics, such as isotype, subclass, allotype, and glycosylation(24).
    antibody-intrinsic characteristics , such as isotype , subclass , allotype ,
    suggested: None
          <div style="margin-bottom:8px">
        <div><b>glycosylation(24</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">W. Hoepel, K. Golebski, C. M. van Drunen, J. den Dunnen, Active control of mucosal tolerance and inflammation by human IgA and IgG antibodies.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>IgG</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Nat Rev Immunol 14, 94-108 (2014). D. M. Del Valle et al., An inflammatory cytokine signature helps predict COVID-19 severity and death. medRxiv, (2020). M. E. Ackerman et al., Natural variation in Fc glycosylation of HIV-specific antibodies impacts antiviral activity.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>antiviral activity .</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">T. Zohar, G. Alter, Dissecting antibody-mediated protection against SARS-CoV-2. Nat Rev Immunol, (2020). K. Golebski et al., FcgammaRIII stimulation breaks the tolerance of human nasal epithelial cells to bacteria through cross-talk with TLR4. Mucosal Immunol 12, 425-433 (2019).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Zohar , G . Alter , Dissecting antibody-mediated protection against SARS-CoV-2 . Nat Rev Immunol , ( 2020</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>TLR4</b></div>
        <div>suggested: (Thermo Fisher Scientific Cat# MA5-18186, <a href="https://scicrunch.org/resources/Any/search?q=AB_2539560">AB_2539560</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The Spike and anti-SARS-CoV-2 monoclonal antibody COVA118 were generated as described previously(22).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-SARS-CoV-2</b></div>
        <div>suggested: (Abcam Cat# ab272854, <a href="https://scicrunch.org/resources/Any/search?q=AB_2847844">AB_2847844</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To block the different FcRs, cells were pre-incubated with 20 μg/mL of the following antibodies: (anti-FcyRI (CD64; 10.1; BD Bioscience); anti-FcyRIIa (CD32a; IV.3; Stemcell Technologies); anti-FcyRIII (CD16; 3G8; BD Bioscience) and anti-FcαRI (CD89; MIP8a; Abcam)) for 30 minutes at 4°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-FcyRI</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>anti-FcyRIIa</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>anti-FcyRIII</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>anti-FcαRI</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ELISA To determine cytokine production, supernatants were harvested after 24h of stimulation and cytokines were detected using the following antibody pairs: IL-1β and IL-6 (U-CyTech Biosciences); TNF (eBioscience); and IL-8 (Invitrogen).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>IL-6</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>IL-8</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">(A) IgG1 fucosylation and galactosylation levels of total and anti-Spike specific antibodies.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-Spike specific antibodies .</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Experimental Models: Cell Lines</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To produce a COVA1-18 variant with elevated galactosylation, 293F cells were co-transfected (1% of total DNA) with a plasmid expressing Beta-1,4-Galactosyltransferase 1 (B4GALT1).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>293F</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Software and Algorithms</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Bioinformatics 25, 2078-2079 (2009). M. I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion for RNAseq data with DESeq2. Genome Biol 15, 550 (2014). D. J. McCarthy, Y. Chen, G. K. Smyth, Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>DESeq2</b></div>
        <div>suggested: (DESeq, <a href="https://scicrunch.org/resources/Any/search?q=SCR_000154">SCR_000154</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Y. Zhou et al., Metascape provides a biologist-oriented resource for the analysis of systemslevel datasets.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Metascape</b></div>
        <div>suggested: (Metascape, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016620">SCR_016620</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">S. Durinck, P. T. Spellman, E. Birney, W. Huber, Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>R/Bioconductor</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">PAECs were pre-incubated for 24h with supernatant of alveolar macrophage-like monocytederived macrophages stimulated for 6h as described above with PolyIC, or in combination with patients serum before flow experiments were performed.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>PolyIC</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Platelet adhesion was quantified in ImageJ by determining the area covered by platelets per Field of View (FOV).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>ImageJ</b></div>
        <div>suggested: (ImageJ, <a href="https://scicrunch.org/resources/Any/search?q=SCR_003070">SCR_003070</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Raw FASTQ files were aligned to the human genome GRCh38 by STAR (v2.5.2b) with default settings(44).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>STAR</b></div>
        <div>suggested: (STAR, <a href="https://scicrunch.org/resources/Any/search?q=SCR_015899">SCR_015899</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Indexed Binary alignment map (BAM) files were generated and filtered on MAPQ>15 with SAMTools (v1.3.1)(45)</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>SAMTools</b></div>
        <div>suggested: (Samtools, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002105">SCR_002105</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Fluorescence was measured with CytoFLEX Flow Cytometer and analyzed with FlowJo software version 7.6.5 (FlowJo, LLC, Ashland, OR)</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>FlowJo</b></div>
        <div>suggested: (FlowJo, <a href="https://scicrunch.org/resources/Any/search?q=SCR_008520">SCR_008520</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The RNAseq data were deposited on Gene Expression Omnibus.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Gene Expression Omnibus</b></div>
        <div>suggested: (Gene Expression Omnibus (GEO), <a href="https://scicrunch.org/resources/Any/search?q=SCR_005012">SCR_005012</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analysis Statistical significance of the data was performed in Graphpad Prism version 8 (GraphPad Software).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Graphpad Prism</b></div>
        <div>suggested: (GraphPad Prism, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002798">SCR_002798</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>GraphPad</b></div>
        <div>suggested: (GraphPad Prism, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002798">SCR_002798</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Differential expression was assessed using the Bioconductor package edgeR (v3.28.1)(47).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>edgeR</b></div>
        <div>suggested: (edgeR, <a href="https://scicrunch.org/resources/Any/search?q=SCR_012802">SCR_012802</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For heatmaps, normalized expression values (count per million, CPM) of each gene were calculated and plotted using pheatmap (v1.0.12) with values scaled by gene.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>pheatmap</b></div>
        <div>suggested: (pheatmap, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016418">SCR_016418</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Gene set enrichment analysis (GSEA) was performed with Bioconductor package fgsea (v1.12.0)(49) with genes ranked by effect size (Cohen’s d) with respect to the “R406+serum+spike+PolyIC vs serum+spike+PolyIC” against the curated gene sets obtained from gene ontology (GO) by Bioconductor package biomaRt (v2.42.1)(50).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Bioconductor</b></div>
        <div>suggested: (Bioconductor, <a href="https://scicrunch.org/resources/Any/search?q=SCR_006442">SCR_006442</a>)</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>biomaRt</b></div>
        <div>suggested: (BioMart Project, <a href="https://scicrunch.org/resources/Any/search?q=SCR_002987">SCR_002987</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">(B) Gene set enrichment analysis (GSEA) of curated gene sets suppressed by R406: Fc-gamma receptor signaling pathway (GO:0038094), glycolytic process (GO:0006096), platelet activation (GO:0030168), response to type I interferon (GO:0034340).</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Gene set enrichment analysis</b></div>
        <div>suggested: (Gene Set Enrichment Analysis, <a href="https://scicrunch.org/resources/Any/search?q=SCR_003199">SCR_003199</a>)</div>
      </div>
    </td></tr></table>

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  5. Version published to 10.1101/2020.07.13.190140v1 on bioRxiv