13
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      SARS-CoV-2 Omicron sublineages exhibit distinct antibody escape patterns

      brief-report

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          SARS-CoV-2 neutralizing antibodies play a critical role in COVID-19 prevention and treatment but are challenged by viral evolution and the emergence of novel escape variants. Importantly, the recently identified Omicron sublineages BA.2.12.1 and BA.4/5 are rapidly becoming predominant in various countries. By determining polyclonal serum activity of 50 convalescent or vaccinated individuals against BA.1, BA.1.1, BA.2, BA.2.12.1, and BA.4/5, we reveal a further reduction of BA.4/5 susceptibility to vaccinee sera. Most notably, delineation of sensitivity to an extended 163-antibody panel demonstrates pronounced antigenic differences with distinct escape patterns among Omicron sublineages. Antigenic distance and/or higher resistance may therefore favor immune escape-mediated BA.4/5 expansion after the first Omicron wave. Finally, while most clinical-stage monoclonal antibodies are inactive against Omicron sublineages, we identify promising antibodies with high pan-SARS-CoV-2 neutralizing potency. Our study provides a detailed understanding of Omicron sublineage antibody escape that can inform on effective strategies against COVID-19.

          Graphical abstract

          Abstract

          Gruell and Vanshylla et al. study the immune escape properties of emerging Omicron sublineages including BA.2.12.1 and BA.4/5. Antigenic profiling using a large panel of monoclonal antibodies revealed distinct viral escape patterns. While most clinical antibodies lose activity against Omicron, highly potent SARS-CoV-2 antibodies with retained pan-Omicron activity were identified.

          Related collections

          Most cited references83

          • Record: found
          • Abstract: found
          • Article: not found

          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

            K Katoh (2002)
            A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              UCSF ChimeraX : Structure visualization for researchers, educators, and developers

              UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.
                Bookmark

                Author and article information

                Journal
                Cell Host Microbe
                Cell Host Microbe
                Cell Host & Microbe
                Elsevier Inc.
                1931-3128
                1934-6069
                7 July 2022
                7 July 2022
                Affiliations
                [1 ]Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
                [2 ]Department of Infectious Diseases and Respiratory Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, 13353 Berlin, Germany
                [3 ]Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, 50937 Germany
                [4 ]Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine and Department of Medicine I, University Medical Center Hamburg-Eppendorf, 20359 Hamburg, Germany
                [5 ]German Center for Infection Research (DZIF), Partner site Bonn-Cologne, 50937 Cologne, Germany
                [6 ]Center for Molecular Medicine Cologne (CMMC), University of Cologne, 50931 Cologne, Germany
                Author notes
                []Corresponding author
                [7]

                These authors contributed equally

                [8]

                Lead contact

                Article
                S1931-3128(22)00318-3
                10.1016/j.chom.2022.07.002
                9260412
                35921836
                c8ef1ad2-921a-4b93-bad3-63bb1fc8f74b
                © 2022 Elsevier Inc.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 11 March 2022
                : 2 June 2022
                : 30 June 2022
                Categories
                Short Article

                Microbiology & Virology
                sars-cov-2,omicron,sublineages,ba.4,ba.5,ba.2.12.1,neutralizing antibodies,immune escape,resistance

                Comments

                Comment on this article