Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants
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Abstract
The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2’ cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.
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SciScore for 10.1101/2022.01.24.477469: (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
Antibodies Sentences Resources To design antigens that can elicit the desired polyclonal response, we first generated a list of mutations (with respect to the wildtype Wuhan SARS-CoV-2 sequence) that satisfied the following criteria: The procedure outlined above resulted in a set of mutations that were in variable residues and would likely abrogate binding to neutralizing class 1 and 2 antibodies circulating in vaccinated and naturally infected persons, and did not diminish ACE2 binding or decrease spike stability and so would likely be viable viruses. neutralizing class 1 and 2suggested: NoneAmong these, 3 mutations (K417T, K417N, … SciScore for 10.1101/2022.01.24.477469: (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
Antibodies Sentences Resources To design antigens that can elicit the desired polyclonal response, we first generated a list of mutations (with respect to the wildtype Wuhan SARS-CoV-2 sequence) that satisfied the following criteria: The procedure outlined above resulted in a set of mutations that were in variable residues and would likely abrogate binding to neutralizing class 1 and 2 antibodies circulating in vaccinated and naturally infected persons, and did not diminish ACE2 binding or decrease spike stability and so would likely be viable viruses. neutralizing class 1 and 2suggested: NoneAmong these, 3 mutations (K417T, K417N, and T478K) were the most prevalent mutations that also escape antibodies, but they were not among the 34 mutations with the largest escape fractions from deep mutational scanning. K417Nsuggested: NoneIn order to choose residues that were consistently part of the class 1 or class 2 epitope, only residues that were bound by 3 or more class 1 or class 2 antibodies were included. more class 1 or class 2suggested: NoneSoftware and Algorithms Sentences Resources 2.1.2 Biochemical conservation fraction: For each coronavirus, a set of several hundred spike sequences were gathered (a complete list of sequences is available at https://github.com/ericzwang/sars2-vaccine/tree/main/data/aligned-cov-sequences.gz) and aligned to the PDB structure’s sequence using the ClustalW algorithm in MEGAX (Thompson et al. (1994); Kumar et al. (2018)). ClustalWsuggested: (ClustalW, RRID:SCR_017277)The model was implemented using Keras version 2.4.0 (Gulli and Pal (2017)) with the TensorFlow version 2.3.1 backend (Abadi et al. (2015)). TensorFlowsuggested: (tensorflow, RRID:SCR_016345)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Also, our AM model weights all residues equally in order to calculate the binding free energy, which is a limitation of the model. In actuality, certain residues easily abrogate antibody binding upon mutation (specifically, class 1 and 2 antibodies elicited from exposure to the WT sequence), and these escape mutations are the ones included in our designed antigens. Thus, our cocktail vaccine should protect against WT escape mutations. The mutations required to evade antibodies generated by our designed vaccine would be complementary to these WT escape mutations. It may be possible that an individual with a previous exposure to the WT sequence could have protection against the mutations that escape our cocktail vaccine. A recent study created chimeric spike mRNA vaccines, in which the mRNA sequence contains segments from multiple sarbecoviruses, which induced higher neutralizing titers against various sarbecoviruses compared to the WT SARS-CoV-2 sequence (Martinez et al. (2021)). However, the chimeras induced lower neutralizing titers against SARS-CoV-2 variants of concern than the WT SARS-CoV-2 sequence. This is not surprising because the chimeras are designed using sarbecoviruses, which are more mutated from the variants of concern than WT SARS-CoV-2 is. If one aims to protect against just SARS-CoV-2 variants, the chimeric vaccine is not better than the WT SARS-CoV-2 vaccine. Our designed antigens are predicted to generate higher titers against SARS-CoV-2 variants than the W...
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.
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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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