A mass spectrometry-based targeted assay for detection of SARS-CoV-2 antigen from clinical specimens

  1. Santosh Renuse
  2. Patrick M. Vanderboom
  3. Anthony D. Maus
  4. Jennifer V. Kemp
  5. Kari M. Gurtner
  6. Anil K. Madugundu
  7. Sandip Chavan
  8. Jane A. Peterson
  9. Benjamin J. Madden
  10. Kiran K. Mangalaparthi
  11. Dong-Gi Mun
  12. Smrita Singh
  13. Benjamin R. Kipp
  14. Surendra Dasari
  15. Ravinder J. Singh
  16. Stefan K. Grebe
  17. Akhilesh Pandey

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Abstract

No abstract available

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  1. Version published to 10.1016/j.ebiom.2021.103465
  2. ScreenIT

    SciScore for 10.1101/2020.08.05.20168948: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: COVID-19 specimen collection and handling: All samples were collected after informed consent and approval by the institutional review board.
    IRB: COVID-19 specimen collection and handling: All samples were collected after informed consent and approval by the institutional review board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-nucleocapsid antibody-based enrichment of nucleocapsid protein and in-solution trypsin digestion: In order to improve the sensitivity of the detection, we evaluated a number of antibodies as shown in Table S3.
    Anti-nucleocapsid antibody-based enrichment of nucleocapsid protein
    suggested: None
    Software and Algorithms
    SentencesResources
    Mass spectrometry data analysis of untargeted LC-MS/MS data: The raw mass spectrometry data were searched using Andromeda in MaxQuant software suite (version 1.6.7.0) (30) against a combined protein database of SARS-CoV-2 proteins, SARS-CoV proteins, common coronaviruses (OC43, HKU1, NL63 and L229E) and UniProt human protein database, African green monkey (Chlorocebus aethiops) database (in case of irradiated virus MS data) including common MS contaminants.
    MaxQuant
    suggested: (MaxQuant, RRID:SCR_014485)
    Data analysis of targeted LC-MS/MS data: The PRM data were processed using the Skyline software package (31).
    Skyline
    suggested: (Skyline, RRID:SCR_014080)

    Results from OddPub: Thank you for sharing your data.

    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. Version published to 10.1101/2020.08.05.20168948v1 on medRxiv