Structural and functional characterization of SARS-CoV-2 RBD domains produced in mammalian cells

  1. Christoph Gstöttner
  2. Tao Zhang
  3. Anja Resemann
  4. Sophia Ruben
  5. Stuart Pengelley
  6. Detlev Suckau
  7. Tim Welsink
  8. Manfred Wuhrer
  9. Elena Domínguez-Vega

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Abstract

As the SARS-CoV-2 pandemic is still ongoing and dramatically influences our life, the need for recombinant proteins for diagnostics, vaccine development, and research is very high. The spike (S) protein, and particularly its receptor binding domain (RBD), mediates the interaction with the ACE2 receptor on host cells and may be modulated by its structural features. Therefore, well characterized recombinant RBDs are essential. We have performed an in-depth structural and functional characterization of RBDs expressed in Chinese hamster ovary (CHO) and human embryonic kidney (HEK293) cells. To structurally characterize the native RBDs (comprising N - and O -glycans and additional posttranslational modifications) a multilevel mass spectrometric approach was employed. Released glycan and glycopeptide analysis were integrated with intact mass analysis, glycan-enzymatic dissection and top-down sequencing for comprehensive annotation of RBD proteoforms. The data showed distinct glycosylation for CHO- and HEK293-RBD with the latter exhibiting antenna fucosylation, higher level of sialylation and a combination of core 1 and core 2 type O -glycans. Additionally, from both putative O -glycosylation sites, we could confirm that O -glycosylation was exclusively present at T323, which was previously unknown. For both RBDs, the binding to SARS-CoV-2 antibodies of positive patients and affinity to ACE2 receptor was addressed showing comparable results. This work not only offers insights into RBD structural and functional features but also provides a workflow for characterization of new RBDs and batch-to-batch comparison.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.23.432424: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Recombinant RBDs (Wuhan-Hu-1-isolate (MN908947)), either transiently expressed in HEK293 or stably expressed in CHO cells, were used (InVivo Biotech Services, Henningsdorf, Germany).
    CHO
    suggested: CLS Cat# 603479/p746_CHO, RRID:CVCL_0213)
    Software and Algorithms
    SentencesResources
    The spectra were processed in FlexAnalysis (Compass for flexSeries 2.0) using a smoothing step (5 cycles 0.15 Da) and baseline subtraction (TopHat).
    TopHat
    suggested: (TopHat, RRID:SCR_013035)
    Peaks were picked using the SNAP2 algorithm up to 5,000 Da and the SNAP algorithm up to 10,000 Da.
    SNAP
    suggested: (SNAP, RRID:SCR_007936)
    For interpretation and annotation of ISD spectra BioTools 3.2 SR7 was used (Bruker).
    BioTools
    suggested: (MSU Mass Spectrometry Facility, RRID:SCR_012482)
    Glycan structures were assigned on the basis of the known MS/MS fragmentation patterns in negative-ion mode [24–26], elution order, and general glycobiological knowledge, with help of Glycoworkbench [27] and Glycomod software [28].
    Glycomod
    suggested: (GlycoMod, RRID:SCR_001602)
    In order to determine the linear correlation between the absorption values, the Pearson correlation was calculated using GraphPad Prism 9.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad Prism 9 was used to plot log(dose) response curves (variable slope, four parameters) and to compute nonlinear fits which were utilized to calculate the half-maximal concentrations (EC50).
    GraphPad
    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: 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.

  2. Version published to 10.1101/2021.02.23.432424 on bioRxiv