SARS-CoV-2–triggered neutrophil extracellular traps mediate COVID-19 pathology

  1. Flavio Protasio Veras
  2. Marjorie Cornejo Pontelli
  3. Camila Meirelles Silva
  4. Juliana E. Toller-Kawahisa
  5. Mikhael de Lima
  6. Daniele Carvalho Nascimento
  7. Ayda Henriques Schneider
  8. Diego Caetité
  9. Lucas Alves Tavares
  10. Isadora M. Paiva
  11. Roberta Rosales
  12. David Colón
  13. Ronaldo Martins
  14. Italo Araujo Castro
  15. Glaucia M. Almeida
  16. Maria Isabel Fernandes Lopes
  17. Maíra Nilson Benatti
  18. Letícia Pastorelli Bonjorno
  19. Marcela Cavichioli Giannini
  20. Rodrigo Luppino-Assad
  21. Sérgio Luna Almeida
  22. Fernando Vilar
  23. Rodrigo Santana
  24. Valdes R. Bollela
  25. Maria Auxiliadora-Martins
  26. Marcos Borges
  27. Carlos Henrique Miranda
  28. Antônio Pazin-Filho
  29. Luis Lamberti P. da Silva
  30. Larissa Dias Cunha
  31. Dario S. Zamboni
  32. Felipe Dal-Pizzol
  33. Luiz O. Leiria
  34. Li Siyuan
  35. Sabrina Batah
  36. Alexandre Fabro
  37. Thais Mauad
  38. Marisa Dolhnikoff
  39. Amaro Duarte-Neto
  40. Paulo Saldiva
  41. Thiago Mattar Cunha
  42. José Carlos Alves-Filho
  43. Eurico Arruda
  44. Paulo Louzada-Junior
  45. Renê Donizeti Oliveira
  46. Fernando Queiroz Cunha

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Abstract

Severe COVID-19 patients develop acute respiratory distress syndrome that may progress to cytokine storm syndrome, organ dysfunction, and death. Considering that neutrophil extracellular traps (NETs) have been described as important mediators of tissue damage in inflammatory diseases, we investigated whether NETs would be involved in COVID-19 pathophysiology. A cohort of 32 hospitalized patients with a confirmed diagnosis of COVID-19 and healthy controls were enrolled. The concentration of NETs was augmented in plasma, tracheal aspirate, and lung autopsies tissues from COVID-19 patients, and their neutrophils released higher levels of NETs. Notably, we found that viable SARS-CoV-2 can directly induce the release of NETs by healthy neutrophils. Mechanistically, NETs triggered by SARS-CoV-2 depend on angiotensin-converting enzyme 2, serine protease, virus replication, and PAD-4. Finally, NETs released by SARS-CoV-2–activated neutrophils promote lung epithelial cell death in vitro. These results unravel a possible detrimental role of NETs in the pathophysiology of COVID-19. Therefore, the inhibition of NETs represents a potential therapeutic target for COVID-19.

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  1. Version published to 10.1084/jem.20201129
  2. ScreenIT

    SciScore for 10.1101/2020.06.08.20125823: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: The COVID19-HC-FMUSP autopsy study was approved by the HC-FMUSP Ethical Committee (protocol #3951.904) and performed at the “ Image Platform in the Autopsy Room” (https://pisa.hc.fm.usp.br/).
    IRB: Study approval: The procedures followed in the study were approved by the National Ethics Committee, Brazil (CONEP, CAAE: 30248420.9.0000.5440).
    Consent: Written informed consent was obtained from recruited patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Quantification of NETs: Briefly, plasma or supernatant from neutrophils culture was incubated overnight in a plate pre-coated with anti-MPO antibody (Thermo Fisher Scientific, cat. PA5-16672).
    anti-MPO
    suggested: None
    Immunostaining and confocal microscopy: Samples were fixed and stained with the following antibodies: rabbit anti-histone H3 (H3Cit, Abcam, cat. ab5103, 1:500), mouse anti-myeloperoxidase (MPO, 2C7, Abcam, cat. ab25989, 1:500), rabbit anti-Cytokeratin 17 (Abcam, ab53707, 1:400).
    anti-histone H3 ( H3Cit
    suggested: None
    anti-myeloperoxidase ( MPO
    suggested: (Antibodies-Online Cat# ABIN235893, RRID:AB_10764910)
    anti-Cytokeratin 17 ( Abcam ,
    suggested: None
    The samples were washed in PBS and incubated with secondary antibodies Donkey anti-Mouse IgG AlexaFluor 647 (Thermo Fisher Scientific, cat.
    anti-Mouse IgG
    suggested: None
    Flow cytometry: Briefly, whole blood leukocytes were stained with Fixable Viability Dye eFluor™ 780 (eBioscience, cat. 65-0865-14, 1:3,000) and monoclonal antibodies specific for CD14 (M5E2, BD, cat. 557153, 1:50), CD19 (HIB19, Biolegend, cat. 302212, 1:200), CD15 (W6D3, BD, cat. 563141, 1:200) and CD16 (ebioCB16(CB16), eBioscience, cat. 12-0168-42, 1:200) for 30 min at 4°C.
    CD14
    suggested: (BD Biosciences Cat# 557153, RRID:AB_396589)
    CD19
    suggested: (Miltenyi Biotec Cat# 130-094-531, RRID:AB_2721154)
    HIB19
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD15
    suggested: (BD Biosciences Cat# 563141, RRID:AB_2738025)
    CD16
    suggested: (Thermo Fisher Scientific Cat# 12-0168-42, RRID:AB_11043421)
    CB16
    suggested: (Thermo Fisher Scientific Cat# 12-0168-42, RRID:AB_11043421)
    Experimental Models: Cell Lines
    SentencesResources
    Stocks were amplified in Vero E6 cell line monolayers maintained in Dulbecco’s Modified Eagle’s (DMEM, Corning, cat. 15-013-CVR).
    Vero E6
    suggested: None
    The A549 cells were also co-cultured with neutrophils from COVID-19 patients or with purified NETs (10ng/mL) pretreated, or not, with rhDNase (0.5 mg/mL, Roche, 2h at 37°C).
    A549
    suggested: None
    Software and Algorithms
    SentencesResources
    The data were performed with Fiji/ImageJ software.
    Fiji/ImageJ
    suggested: None
    We used the adapted plugin Simple Neurite Tracer from Fiji by ImageJ.
    Fiji
    suggested: (Fiji, RRID:SCR_002285)
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    All data were collected on FACSVerse flow cytometers (BD Biosciences) for further analysis using FlowJo (TreeStar) software.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical analyses and graph plots were performed with GraphPad Prism 8.4.2 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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 24 and 23. 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.

  3. Version published to 10.1101/2020.06.08.20125823v1 on medRxiv