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  1. Article ; Online: Deep generative models predict SARS-CoV-2 Spike infectivity and foreshadow neutralizing antibody escape

    Youssef, Noor / Ghantous, Fadi / Gurev, Sarah / Brock, Kelly / Jaimes, Javier A. / Dauphin, Ann / Yurkovetskiy, Leonid / Soto, Daria / Estanboulieh, Ralph / Kotzen, Ben / Bosso, Matteo / Lemieux, Jacob / Luban, Jeremy / Seaman, Michael S. / Marks, Debora S.

    bioRxiv

    Abstract: Recurrent waves of SARS-CoV-2 infection, driven by the periodic emergence of new viral variants, highlight the need for vaccines and therapeutics that remain effective against future strains. Yet, our ability to proactively evaluate such therapeutics is ... ...

    Abstract Recurrent waves of SARS-CoV-2 infection, driven by the periodic emergence of new viral variants, highlight the need for vaccines and therapeutics that remain effective against future strains. Yet, our ability to proactively evaluate such therapeutics is limited to assessing their effectiveness against previous or circulating variants, which may differ significantly in their antibody escape from future viral evolution. To address this challenge, we developed deep learning methods to predict the effect of mutations on fitness and escape from neutralizing antibodies and used this information to engineer a set of 68 unique SARS-CoV-2 Spike proteins. The designed constructs, which incorporated novel combinations of up to 46 mutations relative to the ancestral strain, were infectious and evaded neutralization by nine well-characterized panels of human polyclonal anti-SARS-CoV-2 immune sera. Designed constructs on previous SARS-CoV-2 strains anticipated the antibody neutralization escape of variants seen subsequently during the COVID-19 pandemic. We demonstrate that designed Spike constructs using data available at the time of the implementation of the 2022 bivalent mRNA booster vaccine foretold the level of neutralizing antibody escape observed in the most recently emerging variants. Our approach provides extensive datasets of antigenically diverse escape variants to evaluate the protective ability of vaccines and therapeutics to inhibit future variants. This approach is generalizable to other viral pathogen
    Keywords covid19
    Language English
    Publishing date 2023-10-10
    Publisher Cold Spring Harbor Laboratory
    Document type Article ; Online
    DOI 10.1101/2023.10.08.561389
    Database COVID19

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  2. Article ; Online: Deep generative models predict SARS-CoV-2 Spike infectivity and foreshadow neutralizing antibody escape

    Youssef, Noor A / Ghantous, Fadi / Gurev, Sarah / Brock, Kelly / Jaimes, Javier A. / Dauphin, Ann / Yurkovetskiy, Leonid / Soto, Daria / Estaboulieh, Ralph / Kotzen, Ben / Bosso, Matteo / Lemieux, Jacob / Luban, Jeremy A. / Seaman, Michael / Marks, Debora

    bioRxiv

    Abstract: Recurrent waves of SARS-CoV-2 infection, driven by the periodic emergence of new viral variants, highlight the need for vaccines and therapeutics that remain effective against future strains. Yet, our ability to proactively evaluate such therapeutics is ... ...

    Abstract Recurrent waves of SARS-CoV-2 infection, driven by the periodic emergence of new viral variants, highlight the need for vaccines and therapeutics that remain effective against future strains. Yet, our ability to proactively evaluate such therapeutics is limited to assessing their effectiveness against previous or circulating variants, which may differ significantly in their antibody escape from future viral evolution. To address this challenge, we developed deep learning methods to predict the effect of mutations on fitness and escape from neutralizing antibodies and used this information to engineer a set of 68 unique SARS-CoV-2 Spike proteins. The designed constructs, which incorporated novel combinations of up to 46 mutations relative to the ancestral strain, were infectious and evaded neutralization by nine well-characterized panels of human polyclonal anti-SARS-CoV-2 immune sera. Designed constructs on previous SARS-CoV-2 strains anticipated the antibody neutralization escape of variants seen subsequently during the COVID-19 pandemic. We demonstrate that designed Spike constructs using data available at the time of the implementation of the 2022 bivalent mRNA booster vaccine foretold the level of neutralizing antibody escape observed in the most recently emerging variants. Our approach provides extensive datasets of antigenically diverse escape variants to evaluate the protective ability of vaccines and therapeutics to inhibit future variants. This approach is generalizable to other viral pathogen
    Keywords covid19
    Language English
    Publishing date 2023-10-10
    Publisher Cold Spring Harbor Laboratory
    Document type Article ; Online
    DOI 10.1101/2023.10.08.561389
    Database COVID19

    Full text online

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article: The 2022 RSV surge was driven by multiple viral lineages.

    Adams, Gordon / Moreno, Gage K / Petros, Brittany A / Uddin, Rockib / Levine, Zoe / Kotzen, Ben / Messer, Katelyn / Dobbins, Sabrina T / DeRuff, Katherine C / Loreth, Christine / Brock-Fisher, Taylor / Schaffner, Stephen F / Chaluvadi, Sushma / Kanjilal, Sanjat / Luban, Jeremy / Ozonoff, Al / Park, Daniel / Turbett, Sarah / Siddle, Katherine J /
    MacInnis, Bronwyn L / Sabeti, Pardis / Lemieux, Jacob

    medRxiv : the preprint server for health sciences

    2023  

    Abstract: The US experienced an early and severe respiratory syncytial virus (RSV) surge in autumn 2022. Despite the pressure this has put on hospitals and care centers, the factors promoting the surge in cases are unknown. To investigate whether viral ... ...

    Abstract The US experienced an early and severe respiratory syncytial virus (RSV) surge in autumn 2022. Despite the pressure this has put on hospitals and care centers, the factors promoting the surge in cases are unknown. To investigate whether viral characteristics contributed to the extent or severity of the surge, we sequenced 105 RSV-positive specimens from symptomatic patients diagnosed with RSV who presented to the Massachusetts General Hospital (MGH) and its outpatient practices in the Greater Boston Area. Genomic analysis of the resulting 77 genomes (54 with >80% coverage, and 23 with >5% coverage) demonstrated that the surge was driven by multiple lineages of RSV-A (91%; 70/77) and RSV-B (9%; 7/77). Phylogenetic analysis of all US RSV-A revealed 12 clades, 4 of which contained Massachusetts and Washington genomes. These clades individually had times to most recent common ancestor (tMRCA) between 2014 and 2017, and together had a tMRCA of 2009, suggesting that they emerged well before the COVID-19 pandemic. Similarly, the RSV-B genomes had a tMRCA between 2016 and 2019. We found that the RSV-A and RSV-B genomes in our sample did not differ statistically from the estimated clock rate of the larger phylogenetic tree (10.6 and 12.4 substitutions per year, respectively). In summary, the polyphyletic nature of viral genomes sequenced in the US during the autumn 2022 surge is inconsistent with the emergence of a single, highly transmissible causal RSV lineage.
    Language English
    Publishing date 2023-01-05
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.01.04.23284195
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Article ; Online: Viral Lineages in the 2022 RSV Surge in the United States.

    Adams, Gordon / Moreno, Gage K / Petros, Brittany A / Uddin, Rockib / Levine, Zoe / Kotzen, Ben / Messer, Katelyn S / Dobbins, Sabrina T / DeRuff, Katherine C / Loreth, Christine M / Brock-Fisher, Taylor / Schaffner, Stephen F / Chaluvadi, Sushma / Kanjilal, Sanjat / Luban, Jeremy / Ozonoff, Al / Park, Daniel J / Turbett, Sarah E / Siddle, Katherine J /
    MacInnis, Bronwyn L / Sabeti, Pardis C / Lemieux, Jacob E

    The New England journal of medicine

    2023  Volume 388, Issue 14, Page(s) 1335–1337

    MeSH term(s) Humans ; Infant ; Respiratory Syncytial Virus Infections/epidemiology ; Respiratory Syncytial Virus Infections/genetics ; Respiratory Syncytial Virus Infections/virology ; Seasons ; United States/epidemiology ; Disease Outbreaks ; Respiratory Syncytial Viruses/genetics
    Language English
    Publishing date 2023-02-22
    Publishing country United States
    Document type Letter
    ZDB-ID 207154-x
    ISSN 1533-4406 ; 0028-4793
    ISSN (online) 1533-4406
    ISSN 0028-4793
    DOI 10.1056/NEJMc2216153
    Database MEDical Literature Analysis and Retrieval System OnLINE

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