A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies

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Abstract

Antibody engineering technologies face increasing demands for speed, reliability and scale. We develop CeVICA, a cell-free nanobody engineering platform that uses ribosome display for in vitro selection of nanobodies from a library of 10 11 randomized sequences. We apply CeVICA to engineer nanobodies against the Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein and identify >800 binder families using a computational pipeline based on CDR-directed clustering. Among 38 experimentally-tested families, 30 are true RBD binders and 11 inhibit SARS-CoV-2 pseudotyped virus infection. Affinity maturation and multivalency engineering increase nanobody binding affinity and yield a virus neutralizer with picomolar IC50. Furthermore, the capability of CeVICA for comprehensive binder prediction allows us to validate the fitness of our nanobody library. CeVICA offers an integrated solution for rapid generation of divergent synthetic nanobodies with tunable affinities in vitro and may serve as the basis for automated and highly parallel nanobody engineering.

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  1. SciScore for 10.1101/2020.10.29.361287: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationCDR2 was randomized in stage one, PCR templates at this stage were equal molar mixtures of plasmids carrying DNA encoding frames, including three frame1 versions, one frame2, three frame3 versions and one frame4.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    ) with anti-Flag antibody (Sigma-Aldrich, F1804), then incubating antibody-coated beads with cell lysate or cell media containing 3xFlag tagged target proteins at 4°C for 2 hours.
    anti-Flag
    suggested: (Sigma-Aldrich Cat# F1804, RRID:AB_262044)
    F1804
    suggested: None
    For anti-Myc selection, magnetic beads were coated by anti-Myc antibody (ThermoFisher Scientific, 13-2500) only.
    anti-Myc
    suggested: None
    Plates were washed three times with wash buffer, HRP conjugated anti-His tag secondary antibody (BioLegend, 652503) diluted 1:2000 in blocking buffer was then added to the plates and incubated at RT for 1 hour.
    anti-His tag secondary antibody ( BioLegend , 652503
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    HEK293T ACE2 were a kind gift of Michael Farzan.
    HEK293T ACE2
    suggested: RRID:CVCL_YZ65)
    Plates were washed once with PBST (PBS, ThermoFisher Scientific, with 0.02% TritonX-100), a 1:1 mixture of HEK293T cell culture media containing secreted RBD-3xFlag and blocking buffer (PBST with 1% nonfat dry milk) was added to the plates and incubated at RT for 1 hour.
    HEK293T
    suggested: NCBI_Iran Cat# C498, RRID:CVCL_0063)
    Medium was then removed from HEK293T ACE2/TMPRSS2 cells and replaced with 150 μl of the VHH + pseudotyped lentivirus solution.
    HEK293T ACE2/TMPRSS2
    suggested: None
    Recombinant DNA
    SentencesResources
    psPAX2 and pCMV-VSV-G were previously described 20. pTRIP-SFFV-EGFP-NLS was previously described 21 (a gift from Nicolas Manel; Addgene plasmid # 86677; http://n2t.net/addgene:86677; RRID:Addgene_86677). cDNA for human TMPRSS2 and Hygromycin resistance gene was obtained by synthesis (IDT).
    detected: RRID:Addgene_86677)
    Software and Algorithms
    SentencesResources
    CDR-directed clustering analysis: Computational analysis for CDR-directed clustering was performed using custom python scripts.
    python
    suggested: (IPython, RRID:SCR_001658)
    Percentage GFP was quantified on a Cytoflex LX (Beckman Coulter) and data were analyzed with FlowJo.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    Results from OddPub: Thank you for sharing your code.


    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.