Multivariate mining of an alpaca immune repertoire identifies potent cross-neutralizing SARS-CoV-2 nanobodies

This article has been Reviewed by the following groups

Read the full article

Abstract

Conventional approaches to isolate and characterize nanobodies are laborious. We combine phage display, multivariate enrichment, next-generation sequencing, and a streamlined screening strategy to identify numerous anti–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nanobodies. We characterize their potency and specificity using neutralization assays and hydrogen/deuterium exchange mass spectrometry (HDX-MS). The most potent nanobodies bind to the receptor binding motif of the receptor binding domain (RBD), and we identify two exceptionally potent members of this category (with monomeric half-maximal inhibitory concentrations around 13 and 16 ng/ml). Other nanobodies bind to a more conserved epitope on the side of the RBD and are able to potently neutralize the SARS-CoV-2 founder virus (42 ng/ml), the Beta variant (B.1.351/501Y.V2) (35 ng/ml), and also cross-neutralize the more distantly related SARS-CoV-1 (0.46 μg/ml). The approach presented here is well suited for the screening of phage libraries to identify functional nanobodies for various biomedical and biochemical applications.

Article activity feed

  1. SciScore for 10.1101/2021.07.25.453673: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Neutralization assay: Pseudoviruses were generated by co-transfection of HEK293T cells with plasmids encoding firefly luciferase, a lentiviral packaging plasmid (Addgene cat8455), and a plasmid encoding the spike protein (with a C-terminal truncation) from either SARS-CoV (Addgene cat 170447), SARS-CoV-2 53, or SARS-CoV-2 B.
    HEK293T
    suggested: None
    Pseudotyped viruses (PSV) sufficient to generate 100 000 relative light units (RLU) were incubated with serial dilutions of nanobody for 60 min at 37 °C. 15 000 HEK293T-hACE2 cells were then added to each well, and the plates were incubated for 48 h at 37 °C.
    HEK293T-hACE2
    suggested: RRID:CVCL_A7UK)
    Experimental Models: Organisms/Strains
    SentencesResources
    SARS-CoV-2 challenge experiments: K18-hACE2 transgenic mice were purchased from Jackson laboratories and maintained as a hemizygous line.
    K18-hACE2
    suggested: RRID:IMSR_GPT:T037657)
    Recombinant DNA
    SentencesResources
    Nanobodies were cloned in the pHEN plasmid with a C-terminal sortase motif (LPETG) and a 6xHIS tag.
    pHEN
    suggested: None
    Cloning and expression of candidates: Selected nanobody sequences were ordered as eBlocks from Integrated DNA technologies (IDT) with 20 bp overhangs for Gibson assembly into a pHEN6 plasmid digested with PstI and BstEII restriction enzymes.
    pHEN6
    suggested: None
    Software and Algorithms
    SentencesResources
    Neutralizing antibody ID50 titers were calculated in Prism 9 (GraphPad Software) by fitting a four-parameter logistic curve bounded between 0 and 100, and interpolating the concentration/dilution where RLUs were reduced by 50% relative to control wells in the absence of nanobody.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Fluorescence was quantified using a BD FACSCelesta and the FlowJo software package.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    The mass spectrometry and HDExaminer analysis files have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (REF ID:30395289).
    PRIDE
    suggested: (Pride-asap, RRID:SCR_012052)
    S4) was quantified using ImageJ and an E4 homodimer as a reference.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)

    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.

    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.