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  1. Author Response:

    Reviewer #1 (Public Review):

    I think that it is important for the authors to consider that for most (if not all) SARS-CoV-2 variants, increased transmissibility of the virus has not been directly demonstrated. While it is clear that numerous variants have emerged and will continue to emerge, the rapid upsurge of cases with a variant may be related to many factors (e.g. host susceptibility due to immunity or genetic factors, virus seeding events, predominant replication in particular age cohorts, ...) that cannot simply be captured as "transmissibility of the virus". Even for B.1.1.7 and D614G mutants, the direct evidence of increased transmissibility in humans is extremely limited if available at all. Most studies erroneously simply take the increasing occurrence of particular lineages or mutations in sequence databases as a measure of increased "transmissibility", which should be avoided, also in the present manuscript. Increased transmissibility can only be derived from field studies where transmission is measured directly.

    We thank the reviewer for pointing out that this is a controversial area. We have adjusted the text throughout to accommodate the fact that the published evidence of increased transmissibility/infectivity is not definitive.

    On several occasions in the manuscript (e.g. page 3, page 4 L58-59, page 9 in submitted version), the authors seem to suggest that changes that lead to increased "transmission" or binding affinity and changes that lead to immune escape are mutually exclusive. But the opposite might be true. Viruses may escape from antibody-mediated immunity by amino acid substitutions in linear or structural antibody-binding epitopes. However, viruses may also escape from antibody-mediated immunity through altered protein density on virion surfaces (e.g. less Spike) and/or altered affinity, making it harder for antibody to inhibit virus attachment. As an example, increased affinity may facilitate virus replication with less dense Spike protein, allowing more effective antibody escape. Lower affinity but more dense coverage of Spike may reduce accessibility of critical virus parts by antibodies. Several viruses are known to escape from antibody-mediated neutralization through changes in affinity/avidity.

    We agree with this point and have modified the text to avoid implying that increased transmissibility and antibody escape are mutually exclusive.

    In relation to the previous point, it is important that authors mention some limitations of the present work in the discussion. SARS-CoV-2 virion attachment to cells is not just a matter of spike protein binding and certainly not of a monomeric RBD. Escape from antibodies and effects on affinity are heavily influenced by the entire (trimeric) spike protein, including its N-terminal domains. Such components are not taken into account in the present experimental designs, and this should be discussed, as e.g. the NTD can be important in attachment and antibody-mediated neutralization.

    We thank the reviewer for this suggestion. We have added an appropriate caveat to the Discussion.

    The authors suggest that the pandemic virus as it spread across the globe initially did not have "optimized" affinity. However, in the first months of the pandemic, there was relatively limited variation in spike protein sequences. The major variants emerged only later and mostly in areas where population immunity was building up. Again, this begs the question whether natural selection is occurring as a consequence of receptor affinity or immune escape?

    We thank the reviewer for making this point. However, we do not think it is that surprising that it took a few months for the first Spike variants to be detected, for the following reasons. Firstly, the number of infections would have been relatively low early in the pandemic and SARS-CoV-2 replicates with a comparatively low error rate for an RNA virus. Secondly, the introduction of strict non-pharmacological measures (social-distancing etc), which would have increased the selective pressure on the virus, was somewhat delayed. Thirdly, it would take some time for any variant that emerged by chance to expand sufficiently to be detected by sequencing. While there is evidence suggestive of broader immunity in populations were the Beta and Gamma variants emerged, which we cite, we are not aware of evidence of widespread immunity in populations where the D614G, S477N and Alpha variants first emerged.

    Reviewer #2 (Public Review):

    Barton and colleagues investigated the effect of common SARS-CoV-2 RBD mutations and two ACE2 mutations on the RBD/ACE2 interaction. They concluded that the N501Y, E484K and S477N increased receptor binding while the K417N/T had the opposite effect. Double and triple mutants were also included. The ACE2 mutations (that are rare in the human population) also increased binding to most RBD mutants. The study is well-performed and written clearly.

    The primary conclusions of the manuscript were supported by the results. However, the interpretation was too speculative. In the abstract (lines 14-17), the authors suggest that the 501 and 477 mutations enhance transmission solely based on data on the RBD-ACE2 interaction. It is unknown whether increased affinity to ACE2 is beneficial for transmission. In addition, increased RBD affinity to ACE2 does not mean that the whole spike or virus particle also binds stronger to ACE2. Lastly, increasing ACE2 affinity does not necessarily increase binding to cells (for example S1A binding to sugars or spike abundance can also influence this).

    We agree that it would be inappropriate to assume, based on our affinity/kinetic studies alone, that 501 and 477 enhance transmission. That is why the relevant sentence in the abstract starts with the phrase, “Taken together with other studies”. We summarises the evidence from these other studies in the Discussion. We acknowledge that we have not examined the effects of the mutations on binding of the whole Spike protein to ACE2 or viruses to cells, and have added a suitable caveats to the Discussion.

    The overall impact on the field will be limited as there is substantial overlap with already published studies. The observation that the N501Y and E484K increase receptor binding while the K417N/T mutations decrease binding was already made prior by Laffeber et al (2021; J Mol Biol). Laffeber et al also investigated double and triple mutants and came to similar conclusions. Liu et al (2021) confirmed that the N501Y increases binding whereas the K417N/T have opposing effects (Liu et al., 2021 mAbs). The observation that the Y501N increases ACE2 affinity has been made by several groups (e.g. Liu et al 2021 Cell research; Starr et al 2020 Cell).

    We thank the reviewer for highlighting these addition studies, two of which are very recent. We have now cited these studies.

    Starr et all 2020 was a high throughput study in which the affinity measurements were semi-quantitative, and no kinetic analysis was performed. Liu et al (2021) and Laffeber et al (2021) were performed at 25 C and without rigorous controls for mass-transport and protein aggregation. Liu et al (2021) did not report kinetic measurements. Their results are broadly consistent with ours but their affinity and kinetic measurments are ~ 10 fold different. While we accept that some of the measurements of the effects of mutations have been made before, our measurements of affinity and especially kinetics are performed more rigorously than in previous studies and, for the first time, at a physiological temperature (37 C). Thus, the affinity and kinetic data that we have obtained for single and combinations variants are more definitive. As noted in our Discussion there is a wide variation in reported binding affinities and kinetics in previously published studies. We think the comprehensive data that we report here, the same robust method to measure binding properties of all these variants, adds significant value.

    Reviewer #3 (Public Review):

    [...] 1) The ACE2 receptor exists naturally as a dimeric form and the RBD is a component of the SARS-CoV-2 spike trimer. The assay format here was monomeric RBD binding against monomeric ACE2 throughout this study. While the measurements are indeed carefully executed and under more physiological conditions than many other reported studies, the authors should discuss potential avidity effects, the consequences of mutations on the accessibility of the RBD in VOC versus wildtype, and impact of other domains such as the NTD, in the context of their monomeric ACE2 measurements with isolated RBD here.

    We thank the reviewer for raising this issue. We have added a section to the Discussion addressing these important points.

    1. As shown in Figure S2, RBD WT, K417N, K417T, KN/EK, KT/EK, and S477N, the ~30kDa monomeric proteins were flanked by additional ~60kDa bands (which correspond to the smaller peaks to the left of the main peaks) some of which bleed through to the main fraction to different extents, whereas RBDs SA, UK1, UK2, BR, and E484K, do not seem to have as much or any of these extra species. Can the authors comment on whether these contaminants are RBD-dimers as observed before (Dai et al. 2020)? If yes, would such dimers affect the affinity and kinetics?

    We thank the reviewer for pointing out these larger ~60 kDa bands in some RBD preps. We think that it is unlikely that these are RBD dimers as these are reducing gels. The strictly monophasic kinetics of all RBD preps, also argues against this being an RBD dimer. We have confirmed by densitometry that the larger band comprises less that 5% of the protein in all the preparations. This will have only a minor effect on estimated of RBD concentration. We have added this information to the Figure S2 legend.

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  2. Evaluation Summary:

    This manuscript is of interest to virologists working on SARS-CoV-2, as well as biochemists and biophysicists who perform binding experiments with surface plasmon resonance (SPR), as it provides detailed affinity and kinetics analysis of the effect of mutations in variants of concern in the SARS-CoV-2 receptor binding domain with receptor ACE2 and two 'common' mutations in ACE2.

    (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. Reviewer #1 agreed to share their name with the authors.)

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  3. Reviewer #1 (Public Review):

    I think that it is important for the authors to consider that for most (if not all) SARS-CoV-2 variants, increased transmissibility of the virus has not been directly demonstrated. While it is clear that numerous variants have emerged and will continue to emerge, the rapid upsurge of cases with a variant may be related to many factors (e.g. host susceptibility due to immunity or genetic factors, virus seeding events, predominant replication in particular age cohorts, ...) that cannot simply be captured as "transmissibility of the virus". Even for B.1.1.7 and D614G mutants, the direct evidence of increased transmissibility in humans is extremely limited if available at all. Most studies erroneously simply take the increasing occurrence of particular lineages or mutations in sequence databases as a measure of increased "transmissibility", which should be avoided, also in the present manuscript. Increased transmissibility can only be derived from field studies where transmission is measured directly.

    On several occasions in the manuscript (e.g. page 3, page 4 L58-59, page 9 in submitted version), the authors seem to suggest that changes that lead to increased "transmission" or binding affinity and changes that lead to immune escape are mutually exclusive. But the opposite might be true. Viruses may escape from antibody-mediated immunity by amino acid substitutions in linear or structural antibody-binding epitopes. However, viruses may also escape from antibody-mediated immunity through altered protein density on virion surfaces (e.g. less Spike) and/or altered affinity, making it harder for antibody to inhibit virus attachment. As an example, increased affinity may facilitate virus replication with less dense Spike protein, allowing more effective antibody escape. Lower affinity but more dense coverage of Spike may reduce accessibility of critical virus parts by antibodies. Several viruses are known to escape from antibody-mediated neutralization through changes in affinity/avidity.

    In relation to the previous point, it is important that authors mention some limitations of the present work in the discussion. SARS-CoV-2 virion attachment to cells is not just a matter of spike protein binding and certainly not of a monomeric RBD. Escape from antibodies and effects on affinity are heavily influenced by the entire (trimeric) spike protein, including its N-terminal domains. Such components are not taken into account in the present experimental designs, and this should be discussed, as e.g. the NTD can be important in attachment and antibody-mediated neutralization.

    The authors suggest that the pandemic virus as it spread across the globe initially did not have "optimized" affinity. However, in the first months of the pandemic, there was relatively limited variation in spike protein sequences. The major variants emerged only later and mostly in areas where population immunity was building up. Again, this begs the question whether natural selection is occurring as a consequence of receptor affinity or immune escape?

    Read the original source
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  4. Reviewer #2 (Public Review):

    Barton and colleagues investigated the effect of common SARS-CoV-2 RBD mutations and two ACE2 mutations on the RBD/ACE2 interaction. They concluded that the N501Y, E484K and S477N increased receptor binding while the K417N/T had the opposite effect. Double and triple mutants were also included. The ACE2 mutations (that are rare in the human population) also increased binding to most RBD mutants. The study is well-performed and written clearly.

    The primary conclusions of the manuscript were supported by the results. However, the interpretation was too speculative. In the abstract (lines 14-17), the authors suggest that the 501 and 477 mutations enhance transmission solely based on data on the RBD-ACE2 interaction. It is unknown whether increased affinity to ACE2 is beneficial for transmission. In addition, increased RBD affinity to ACE2 does not mean that the whole spike or virus particle also binds stronger to ACE2. Lastly, increasing ACE2 affinity does not necessarily increase binding to cells (for example S1A binding to sugars or spike abundance can also influence this).

    The overall impact on the field will be limited as there is substantial overlap with already published studies. The observation that the N501Y and E484K increase receptor binding while the K417N/T mutations decrease binding was already made prior by Laffeber et al (2021; J Mol Biol). Laffeber et al also investigated double and triple mutants and came to similar conclusions. Liu et al (2021) confirmed that the N501Y increases binding whereas the K417N/T have opposing effects (Liu et al., 2021 mAbs). The observation that the Y501N increases ACE2 affinity has been made by several groups (e.g. Liu et al 2021 Cell research; Starr et al 2020 Cell)

    The S477N and ACE2 mutations on the ACE2-RBD interaction were not investigated prior. In addition, the authors indicate correctly that they performed the SPR experiments at 37 degrees Celsius, whereas others did SPR experiments at room temperature.

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  5. Reviewer #3 (Public Review):

    Barton et al. performed detailed measurements and analysis of the binding of the SARS-CoV-2 receptor-binding domain (RBD) and mutations in currently circulating variants of concern (VOC) against the human receptor ACE2 using SPR. K417N/T that occurs in VOCs B.1.351 and P.1 was shown to decrease binding to ACE2, where N501Y (found in B.1.351, P.1, and B.1.1.7) increased binding. S477N and E484K exhibited more modest effects on binding to ACE2. The gain of binding by N501Y and E484K was found to make up for loss of binding caused by K417N/T in B.1.351 and P.1, respectively. Some of these effects have been noted in other publications. The authors also showed that two natural variants of human ACE2 (S19P and K26R), which are found in samples in the gnomAD database (0.4% and 0.03% respectively), also affected bind to SARS-CoV-2 RBDs. The authors then discussed possible causes of the variations of the relatively wide range of affinity values cited in the literature, including measurement at non-physiological temperature, mass-transport limitations and rebinding, and protein aggregation. These are all good points that should be taking into account in assessing absolute versus relative binding. The strengths of this paper are the comprehensive and careful analyses of wildtype and mutant SARS-CoV-2 RBD and ACE2 in one study. Points to be further considered include:

    1. The ACE2 receptor exists naturally as a dimeric form and the RBD is a component of the SARS-CoV-2 spike trimer. The assay format here was monomeric RBD binding against monomeric ACE2 throughout this study. While the measurements are indeed carefully executed and under more physiological conditions than many other reported studies, the authors should discuss potential avidity effects, the consequences of mutations on the accessibility of the RBD in VOC versus wildtype, and impact of other domains such as the NTD, in the context of their monomeric ACE2 measurements with isolated RBD here.

    2. As shown in Figure S2, RBD WT, K417N, K417T, KN/EK, KT/EK, and S477N, the ~30kDa monomeric proteins were flanked by additional ~60kDa bands (which correspond to the smaller peaks to the left of the main peaks) some of which bleed through to the main fraction to different extents, whereas RBDs SA, UK1, UK2, BR, and E484K, do not seem to have as much or any of these extra species. Can the authors comment on whether these contaminants are RBD-dimers as observed before (Dai et al. 2020)? If yes, would such dimers affect the affinity and kinetics?

    Reference:

    Dai, Lianpan, et al. (2020). A universal design of betacoronavirus vaccines against COVID-19, MERS, and SARS. Cell 182: 722-733.e11.

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  6. SciScore for 10.1101/2021.05.18.444646: (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
    HEK293F cell transfection: Cells were grown in FreeStyle™ 293 Expression Medium (12338018) in a 37 °C incubator with 8% CO2 on a shaking platform at 130 rpm.
    HEK293F
    suggested: None
    Software and Algorithms
    SentencesResources
    Data analysis: Double referenced binding data was fitted using GraphPad Prism.
    GraphPad Prism
    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.

    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.

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