ACE2 and SARS-CoV-2 Expression in the Normal and COVID-19 Pancreas

  1. Irina Kusmartseva
  2. Wenting Wu
  3. Farooq Syed
  4. Verena Van Der Heide
  5. Marda Jorgensen
  6. Paul Joseph
  7. Xiaohan Tang
  8. Eduardo Candelario-Jalil
  9. Changjun Yang
  10. Harry Nick
  11. Jack L. Harbert
  12. Amanda Posgai
  13. Richard Lloyd
  14. Sirlene Cechin
  15. Alberto Pugliese
  16. Martha Campbell-Thompson
  17. Richard S. Vander Heide
  18. Carmella Evans-Molina
  19. Dirk Homann
  20. Mark A. Atkinson

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Abstract

Diabetes is associated with increased mortality from Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Given literature suggesting a potential association between SARS-CoV-2 infection and diabetes induction, we examined pancreatic expression of the key molecule for SARS-CoV-2 infection of cells, angiotensin-converting enzyme-2 (ACE2). Specifically, we analyzed five public scRNAseq pancreas datasets and performed fluorescence in situ hybridization, Western blotting, and immunolocalization for ACE2 with extensive reagent validation on normal human pancreatic tissues across the lifespan, as well as those from coronavirus disease 2019 (COVID-19) patients. These in silico and ex vivo analyses demonstrated pancreatic expression of ACE2 is prominent in pancreatic ductal epithelium and the microvasculature, with rare endocrine cell expression of this molecule. Pancreata from COVID-19 patients demonstrated multiple thrombotic lesions with SARS-CoV-2 nucleocapsid protein expression primarily limited to ducts. SARS-CoV-2 infection of pancreatic endocrine cells, via ACE2, appears an unlikely central pathogenic feature of COVID-19 as it relates to diabetes.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.31.270736: (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
    The following morning, slides were washed with 1X PBS and PBS containing 2% FBS for 5 minutes and probed using either Alexa Fluor (AF)-488 goat anti-guinea pig IgG (1:500 dilution, Invitrogen, Carlsbad, CA) or AF-488 donkey anti-mouse IgG (1:1,000 dilution, Invitrogen) secondary antibodies.
    anti-guinea pig IgG
    suggested: None
    AF-488 donkey anti-mouse IgG
    suggested: None
    mouse monoclonal anti-ACE2 (1:1,000 dilution, R&D Systems), goat polyclonal anti-ACE2 (1:500 dilution, R&D Systems)) and mouse monoclonal anti-β-actin (1:10,000 dilution; Sigma-Aldrich, St. Louis, MO) in Intercept™ Antibody Diluent (LI-COR Biosciences).
    anti-β-actin
    suggested: (Sigma-Aldrich Cat# A5441, RRID:AB_476744)
    The membranes were then washed with Tris-buffered saline containing 0.1% Tween 20 (TBST) three times at 5 minute intervals, incubated with secondary antibodies (IRDye 800CW goat anti-rabbit IgG (1:30,000 dilution)
    anti-rabbit IgG
    suggested: None
    S2D) and for SARS-CoV-2 NP single stained lung and pancreas sections (Fig. 4E-F and Fig. S4), slides were incubated overnight at 4°C with one of four primary antibodies against ACE2 (rabbit monoclonal anti-ACE2, 1:200 dilution (Abcam); rabbit polyclonal anti-ACE2, 1:2,000 dilution (Abcam); mouse monoclonal anti-human ACE2, 1:100 dilution, (R&D Systems); goat polyclonal anti-ACE2, 1:100 dilution, (R&D Systems)) or a primary antibody against SARS-CoV-2 NP (mouse monoclonal anti-SARS-CoV-2 NP, 1:50 dilution, Invitrogen).
    S4
    suggested: None
    anti-human ACE2
    suggested: None
    anti-SARS-CoV-2 NP
    suggested: None
    S2E) the primary antibody (monoclonal rabbit anti-ACE2, 1:100 dilution (Abcam, Cambridge, MA)) was incubated with 1mg/mL ACE2 peptide (Abcam) for one hour at RT, before applying to pancreas slides for overnight incubation at 4°C.
    anti-ACE2
    suggested: (Enzo Life Sciences Cat# ALX-804-722-C100, RRID:AB_11180102)
    After washing, slides were again blocked with Background Sniper, washed, and incubated with the second primary antibody (rabbit monoclonal anti-insulin, 1:2,000 dilution (Abcam)) for 30 minutes at RT.
    anti-insulin
    suggested: None
    , blocked slides were incubated for 20 minutes at RT with a primary antibody cocktail (mouse monoclonal anti-glucagon, 1:1,000 dilution (Abcam) plus rabbit monoclonal anti-ACE2, 1:200 dilution (Abcam)), then washed and incubated with MACH 2 Double Stain Kit 1 (BioCare Medical) for 20 minutes at RT.
    anti-glucagon
    suggested: None
    Slides were incubated overnight at 4°C with primary antibodies: a) monoclonal rabbit anti-ACE2 (1:100 dilution; Abcam) (Fig. 3C-E)
    3C-E
    suggested: None
    , monoclonal rabbit anti-ACE2 (1:100 dilution; Abcam), polyclonal guinea pig anti-insulin RTU antibody (undiluted; Agilent), and monoclonal mouse anti-glucagon (dilution; 1:20,000 Abcam) (Fig. 3F) or b) monoclonal rabbit anti-ACE2 (1:100 dilution; Abcam) and monoclonal mouse anti-CD34 (dilution 1:1,000; Novus Biologicals, Centennial, CO) (Fig.
    anti-insulin RTU
    suggested: None
    anti-CD34
    suggested: None
    Slides were washed, then incubated for 45 minutes at RT in the dark with secondary antibodies: a) goat anti-rabbit IgG-AF555, goat anti-mouse IgG-AF488, and goat anti-guinea pig IgG-AF647, or b) goat anti-rabbit IgG-AF594 and goat anti-mouse IgG-AF488 (all from Invitrogen).
    anti-rabbit IgG-AF555
    suggested: (SouthernBiotech Cat# 4030-32, RRID:AB_2795940)
    anti-mouse IgG-AF488
    suggested: None
    anti-guinea pig IgG-AF647
    suggested: None
    Software and Algorithms
    SentencesResources
    These included four datasets from the Gene Expression Omnibus (GEO) Repository: GSE84133 (inDrop) (Baron et al., 2016), GSE81076 (Celseq) (Grün et al., 2016), GSE85241 (CelSeq2) (Muraro et al., 2016), and GSE86469 (Fluidigm C1) (Lawlor et al., 2017).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    In addition, we analyzed an ArrayExpress database under the accession number E-MTAB-5061 (SMART-Seq2) (Segerstolpe et al., 2016).
    ArrayExpress
    suggested: (ArrayExpress, RRID:SCR_002964)
    Following protein transfer, membranes were scanned with the Gel DOC™ EZ imager, and total protein staining was visualized and quantified using Image Lab software version 5.2.1 (
    Image Lab
    suggested: (Image Lab Software, RRID:SCR_014210)
    Immunoreactive bands were visualized and densitometrically analyzed using Odyssey infrared scanner and Image Studio software version 3.1 (LI-COR Biosciences) (Fig. 2B and Fig. S2B).
    Image Studio
    suggested: (Image Studio Lite, RRID:SCR_013715)
    , monoclonal rabbit anti-ACE2 (1:100 dilution; Abcam), polyclonal guinea pig anti-insulin RTU antibody (undiluted; Agilent), and monoclonal mouse anti-glucagon (dilution; 1:20,000 Abcam) (Fig. 3F) or b) monoclonal rabbit anti-ACE2 (1:100 dilution; Abcam) and monoclonal mouse anti-CD34 (dilution 1:1,000; Novus Biologicals, Centennial, CO) (Fig.
    Agilent
    suggested: (Agilent Bravo NGS, RRID:SCR_019473)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations of Study: In theoretical conflict with our efforts, Yang et al. reported ACE2 protein expression in endocrine cells of isolated human islets and demonstrated their susceptibility to infection with SARS-CoV-2 (Yang et al., 2020). With both public scRNAseq data and our in situ smFISH experiments documenting the presence of ACE2 mRNA in small subsets of pancreatic endocrine cells, it remains unclear whether this forms an extremely limited basis for susceptibility to SARS-CoV-2 infection. However, it remains unknown whether the process of islet isolation may influence endocrine cell ACE2 expression or whether viral dosage might influence their ability to undergo SARS-CoV-2 infection ex vivo. Contrasting epidemiological reports from the United Kingdom and Germany (Tittel et al., 2020; Unsworth et al., 2020) not only underscore the requirement for data on diabetes incidence and SARS-CoV-2 infection rates in defined populations over time, but also raise the need for studying pancreatic tissues from a variety of geographic populations.

    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.

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  2. Version published to 10.1101/2020.08.31.270736v1 on bioRxiv