1. Evaluation Summary:

    This study describes reduced antibody cross-reactivity between the SARS-CoV-2 B.1.1.7 variant and the parental strain or the B.1.351 variant. Asymmetric antibody responses and reduced neutralizing antibodies against heterogeneous variants have been demonstrated in multiple studies. The current study reports reduction of B.1.1.7 COVID-19 sera against the SARS-CoV-2 parental strain and B.1.351. This observation is interesting and could be useful for future vaccine development. The work is of interest to virologists and infectious disease specialists.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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  2. Reviewer #1 (Public Review):

    Faulkner et al., has described asymmetric antibody response in SARS-CoV-2 alpha (B.1.1.7) patient sera on parental Wuhan-hu-1 or G614 variant and Beta (B.1.351) variant. This work is highly significant and the information could be very useful for next-generation vaccine development. One of the limitations of the current study is SARS-CoV delta variant (B.1.617.2) is not included, which I think will be highly relevant due to the high transmissibility of the delta variant around the world.

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  3. Reviewer #2 (Public Review):

    The authors’ study compares neutralisation as well as antibody binding of serum collected from individuals infected with either WT or B.1.1.7 SARS-Cov2 variants. They assess these Ab responses against WT, B.1.1.7 and B.1.351 variants in in vitro assays, ultimately concluding that infection with B.1.1.7 leads to a lower cross-reactive neutralisation than WT because sera from WT maintain neutralisation against B.1.1.7 virus but sera from B.1.1.7 loose neutralisation to WT. The authors provide interesting data on an important question, and a robust analysis of the data. They consider the limitations of the data acquisition process and perform analysis to control for the different sources of the WT and B.1.1.7 sera samples, by matching, disease type (i.e. asymptomatic disease versus symptomatic) and timing of sera collection. However, there is one main point of interpretation that requires a bit more discussion, as it appears possible to interpret the data in the opposite way regarding the authors main conclusion.

    In sup. Fig S9 the authors present their most controlled (like-for-like) comparison of sera from WT and B.1.1.7 infected individuals. They conclude that B.1.1.7 infection leads to nAbs with lower cross reactivity. But this is only true for the fold drop. If you look at the absolute level of nAbs in these two groups, it seems to indicate the opposite conclusion is plausible.

    That is, if you get an asymptomatic B.1.1.7 infection it seems you may have a higher neutralisation against B.1.1.7 and WT (and even B.1.351) compared with someone who receives an asymptomatic WT infection. This would seem to indicate that a B.1.1.7 infection leads to a higher overall response including a higher cross-reactive response. This interpretation is the opposite of the authors, and the difference is whether you consider absolute level or fold-drop as the better measure of cross-reactivity. It may be that B.1.1.7 infections tend to be asymptomatic with higher viral loads and so lead to higher overall Ab responses with asymptomatic infection.

    It is not clear which of these two opposite interpretations of the data is the "correct" interpretation and the authors approach is very reasonable - it's just not clear which is the most meaningful at this stage. Therefore, the authors should include some discussion that another interpretation is possible when looking at the absolute level of nAbs in B.1.1.7 infected individuals and offer a balanced justification for why they favour the interpretation that B.1.1.7 leads to lower cross-reactivity instead of higher cross reactivity.

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  4. Reviewer #3 (Public Review):

    In this manuscript, Faulkner et al. determine the binding and neutralisation of sera from D614G and B.1.1.7 infected patients against circulating SARS-CoV-2 variants of concern. They show that antibodies arising from B.1.1.7 infection have reduced binding and neutralisation against the parental strain. Additionally, in contrast, the antibodies elicited by patients infected with the D614G strain retained binding to B.1.1.7 spike and a less pronounced decrease in neutralisation. Both cohorts had a significant decrease in neutralisation to the South African B.1.351 variant.

    I think this work is well designed, executed, clearly written and well organised. The findings are important and may help inform the design of future SARS-CoV-2 vaccines.

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  5. SciScore for 10.1101/2021.03.01.433314: (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 AuthenticationContamination: Cells lines and plasmids: HEK293T cells were obtained from the Cell Services facility at The Francis Crick Institute, verified as mycoplasma-free and validated by DNA fingerprinting.

    Table 2: Resources

    Antibodies
    SentencesResources
    , APC anti-IgM (clone MHM-88, Biolegend) and PE anti-IgA (clone IS11-8E10, Miltenyi Biotech) for 30 min (all antibodies diluted 1:200 in FACS buffer).
    anti-IgM
    suggested: None
    anti-IgA
    suggested: None
    Assay plates were then transferred out of CL3 and fixing solution washed off, cells blocked and permeabilised with a 3% BSA/0.2% Triton- X100/PBS solution, and finally immunostained with DAPI and a 488-conjugated anti-nucleoprotein monoclonal antibody (produced in-house).
    anti-nucleoprotein
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Vero E6 and Vero V1 cells were kindly provided by Dr Björn Meyer, Institut Pasteur, Paris, France, and Professor Steve Goodbourn, St. George’s, University of London, London, UK, respectively.
    Vero V1
    suggested: None
    Similarly, HEK293T cells were transfected with expression plasmids (pcDNA3) encoding the B.1.1.7 spike variant (D614G, Δ69-70, Δ144, N501Y, A570D, P681H, T716I, S982A and D1118H) or the B.1.351 spike variant (D614G, L18F, D80A, D215G, Δ242-244, R246I, K417N, E484K, N501Y, A701V) (both synthesised and cloned by GenScript).
    HEK293T
    suggested: None
    Next, the diluted serum plates were stamped into duplicate 384-well imaging plates (Greiner 781091) pre-seeded the day before with 3,000 Vero E6 cells per well, with each of the 4 dilutions into a different quadrant of the final assay plates to achieve a final working dilution of samples at 1:40, 1:160, 1:640, and 1:2560.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Genomes were assembled using an in-house pipeline18 and aligned to a selection of publicly available SARS-CoV-2 genomes19 using the MAFFT alignment software20.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Phylogenetic trees were generated from multiple sequence alignments using IQ-TREE21 and FigTree (http://tree.bio.ed.ac.uk/software/figtree), with lineages assigned (including B.1.1.7 calls) using pangolin (http://github.com/cov-lineages/pangolin), and confirmed by manual inspection of alignments.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)
    Samples were run on a Ze5 analyzer (Bio-Rad) running Bio-Rad Everest software v2.4 or an LSR Fortessa with a high-throughput sampler (BD Biosciences) running BD FACSDiva software v8.0, and analyzed using FlowJo v10
    Bio-Rad Everest
    suggested: None
    BD FACSDiva
    suggested: (BD FACSDiva Software, RRID:SCR_001456)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical analyses: Data were analysed and plotted in SigmaPlot v14.0 (Systat Software).
    SigmaPlot
    suggested: (SigmaPlot, RRID:SCR_003210)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 11. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.


    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.

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