A diabetic milieu increases cellular susceptibility to SARS-CoV-2 infections in engineered human kidney organoids and diabetic patients

  1. Elena Garreta
  2. Patricia Prado
  3. Megan Stanifer
  4. Vanessa Monteil
  5. Carmen Hurtado del Pozo
  6. Asier Ullate-Agote
  7. Amaia Vilas-Zornoza
  8. Juan Pablo Romero
  9. Gustav Jonsson
  10. Roger Oria
  11. Alexandra Leopoldi
  12. Astrid Hagelkruys
  13. Daniel Moya-Rull
  14. Federico González
  15. Andrés Marco
  16. Carolina Tarantino
  17. Pere Domingo-Pedrol
  18. Omar HasanAli
  19. Pedro Ventura-Aguiar
  20. Josep María Campistol
  21. Felipe Prosper
  22. Ali Mirazimi
  23. Steeve Boulant
  24. Josef M. Penninger
  25. Nuria Montserrat

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Abstract

SARS-CoV-2 infections lead to a high risk of hospitalization and mortality in diabetic patients. Why diabetic individuals are more prone to develop severe COVID-19 remains unclear. Here, we established a novel human kidney organoid model that mimics early hallmarks of diabetic nephropathy. High oscillatory glucose exposure resulted in metabolic changes, expansion of extracellular membrane components, gene expression changes determined by scRNAseq, and marked upregulation of angiotensin-converting enzyme 2 (ACE2). Upon SARS-CoV-2 infection, hyperglycemic conditions lead to markedly higher viral loads in kidney organoids compared to normoglycemia. Genetic deletion of ACE2, but not of the candidate receptor BSG/CD147, in kidney organoids demonstrated the essential role of ACE2 in SARS-CoV-2 infections and completely prevented SARS-CoV-2 infection in the diabetogenic microenvironment. These data introduce a novel organoid model for diabetic kidney disease and show that diabetic-induced ACE2 licenses the diabetic kidney to enhanced SARS-CoV-2 replication.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.13.456228: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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: We detected the following sentences addressing limitations in the study:
    Limitations of the Study: Future work will be needed to address limitations of our study. (1) Utilizing more complex culture systems, including the assembly of a vascular component to kidney organoids, would help to further explore the impact of a high oscillatory glucose regimen in a more physiologically relevant context. (2) The design of our studies focused on the early stages of infection. As such, we cannot make any predictions with respect to the observed changes at later stages of the disease process. In this regard, inflammation represents a complex network of pathways which are influenced by external processes which currently cannot be simulated in our model. (3) We did not study pancreatic organoids, and the pancreas is one of the major metabolic organs that could explain later complications of COVID-19.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.08.13.456228v1 on bioRxiv