COVID-19 lung disease shares driver AT2 cytopathic features with Idiopathic pulmonary fibrosis

  1. Saptarshi Sinha
  2. Vanessa Castillo
  3. Celia R. Espinoza
  4. Courtney Tindle
  5. Ayden G. Fonseca
  6. Jennifer M. Dan
  7. Gajanan D. Katkar
  8. Soumita Das
  9. Debashis Sahoo
  10. Pradipta Ghosh

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Abstract

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  1. Version published to 10.1016/j.ebiom.2022.104185
  2. Version published to 10.1101/2021.11.28.470269v4 on bioRxiv
  3. Version published to 10.1101/2021.11.28.470269v3 on bioRxiv
  4. Version published to 10.1101/2021.11.28.470269v2 on bioRxiv
  5. ScreenIT

    SciScore for 10.1101/2021.11.28.470269: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: At the time of enrollment, all COVID-19 donors provided written informed consent to participate in the present and future studies.
    Field Sample Permit: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328.
    IACUC: Animal studies were approved and performed in accordance with Scripps Research IACUC Protocol #20-000328.
    Sex as a biological variablenot detected.
    RandomizationIHC Quantification: IHC images were randomly sampled at different 300x300 pixel regions of interest (ROI).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    We chose three different groups of samples: uninfected control, SARS-CoV-2 challenge after Den3 (antibody to dengue virus), and SARS-CoV-2 challenge after Anti-CoV2 (CC12.2; a potent SARS-CoV-2 neutralizing antibodies)28. Immunohistochemistry: COVID-19 samples were inactivated by storing in 10% formalin for 2 days and then transferred to zinc-formalin solution for another 3 days.
    Anti-CoV2
    suggested: None
    antibodies)28
    suggested: None
    Tissues were then incubated with the following antibodies: rabbit GRP78/ BIP polyclonal antibody (1:500 dilution; proteintech®, Rosemont, IL, USA; catalog# 11587-1-AP), rabbit p53 polyclonal antibody (1:200 dilution ; proteintech®, Rosemont, IL, USA; catalog# 21891-1-AP), rabbit Cytokeratin 8 polyclonal antibody (1:2000 dilution; proteintech®, Rosemont, IL, USA; catalog# 10384-1-AP), and rabbit Claudin 4-specific polyclonal antibody (1:200 dilution, proteintech®, Rosemont, IL, USA; catalog# 16195-1-AP) for 1.5 hours at room temperature in a humidified chamber then rinsed with TBS twice for 3 minutes each.
    p53
    suggested: (Proteintech Cat# 21891-1-AP, RRID:AB_10896826)
    Cytokeratin
    suggested: (Proteintech Cat# 10384-1-AP, RRID:AB_10638912)
    Sections were incubated with horse anti-rabbit (Vector Laboratories, Burlingame, USA; catalog# MP-7401) secondary antibodies for 30 minutes at room temperature in a humidified chamber and then washed with TBS or TBST 3x, 5 minutes each.
    anti-rabbit
    suggested: (Vector Laboratories Cat# MP-7401, RRID:AB_2336529)
    Software and Algorithms
    SentencesResources
    The nodes between the seed nodes were fetched using the connecting shortest paths and their components from the human protein interaction dataset of the STRING database19.
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Standard t-tests were performed using python scipy.stats.ttest_ind package (version 0.19.0) with Welch’s Two Sample t-test (unpaired, unequalvariance (equal_var=False), and unequal sample size) parameters.
    scipy
    suggested: (SciPy, RRID:SCR_008058)
    Pathway analysis of gene lists were carried out via the Reactome database and CluGo algorithm.
    Reactome
    suggested: (Reactome, RRID:SCR_003485)
    Violin, Swarm and Bubble plots are created using python seaborn package version 0.10.1.
    python
    suggested: (IPython, RRID:SCR_001658)
    seaborn
    suggested: (seaborn, RRID:SCR_018132)
    The raw data and processed data were deposited in Gene Expression Omnibus under accession no. GSE157057.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Detailed methods (text) Figures 2 Tables 0 Supplemental datasheets– 1-5: Supplemental Information 1: Excel datasheet with a list of transcriptomic datasets that were used in this work.
    Excel
    suggested: None

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    As for the limitations of this study, it remains unclear how to model progressive lung fibrosis in vitro and hence, no attempt was made to do so. Our results suggest that AT2 cells alone may be insufficient for such modeling because a specific host immune response that is carried in the PBMCs is a clear determinant as to who progresses and who does not. Although AT2-specific modulation of ER-stress pathway and SARS-CoV-challenged (treated vs untreated) hamsters were used to go beyond association and establish causation, our study did not attempt to inhibit/reverse fibrosis in COVID-19 by acting on any profibrogenic cellular pathway/process. Development of novel chemical matter/biologicals and validation of the therapeutic efficacy of such agents will take time, but if successful, our findings show that their benefits will likely transcend beyond PCLD into IPF and other fibrotic lung conditions such as IPF. In conclusion, this transdisciplinary work provides insights into the pathogenesis of PCLD, formally defines the fibrogenic processes in the lung, and rigorously validates high value gene signatures or even targets (i.e., IL15, senescence pathways, etc.) to track and manipulate the same. The insights, tools, computationally vetted disease models and biomarkers (prognostic gene signatures) identified here are likely to spur the development of therapies for patients with fibrotic interstitial lung disease of diverse causes, including IPF, all of whom have limited or no good t...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT0440557080Trial number did not resolve on clinicaltrials.gov. Is the number correct?NA
    NCT04856111RecruitingPirfenidone vs. Nintedanib for Fibrotic Lung Disease After C…
    NCT04653831RecruitingTreatment With Pirfenidone for COVID-19 Related Severe ARDS

    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.

  6. Version published to 10.1101/2021.11.28.470269v1 on bioRxiv