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      Distinct antibody repertoires against endemic human coronaviruses in children and adults

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      1 , 1 , 1 , 1 , 1 , 2 , 2 , 3 , 4 , 2 , 2 , 3 , 4 , 2 , 3 , 4 , 2 , 3 , 4 , 5 , 6 , 5 , 6 , 6 , 7 , 8 , 9 , 8 , 10 , 11 , 12 , 13 , 2 , 3 , 4 , 2 , 3 , 4 , 14 , 7 , 15 , 1 , 16 ,
      JCI Insight
      American Society for Clinical Investigation
      Immunology, Infectious disease, Immunoglobulins

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          Abstract

          Four endemic human coronaviruses (HCoVs) are commonly associated with acute respiratory infection in humans. B cell responses to these “common cold” viruses remain incompletely understood. Here we report a comprehensive analysis of CoV-specific antibody repertoires in 231 children and 1168 adults using phage immunoprecipitation sequencing. Seroprevalence of antibodies against endemic HCoVs ranged between approximately 4% and 27% depending on the species and cohort. We identified at least 136 novel linear B cell epitopes. Antibody repertoires against endemic HCoVs were qualitatively different between children and adults in that anti-HCoV IgG specificities more frequently found among children targeted functionally important and structurally conserved regions of the spike, nucleocapsid, and matrix proteins. Moreover, antibody specificities targeting the highly conserved fusion peptide region and S2′ cleavage site of the spike protein were broadly cross-reactive with peptides of epidemic human and nonhuman coronaviruses. In contrast, an acidic tandem repeat in the N-terminal region of the Nsp3 subdomain of the HCoV-HKU1 polyprotein was the predominant target of antibody responses in adult donors. Our findings shed light on the dominant species-specific and pan-CoV target sites of human antibody responses to coronavirus infection, thereby providing important insights for the development of prophylactic or therapeutic monoclonal antibodies and vaccine design.

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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              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.
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                Author and article information

                Contributors
                Journal
                JCI Insight
                JCI Insight
                JCI Insight
                JCI Insight
                American Society for Clinical Investigation
                2379-3708
                22 February 2021
                22 February 2021
                22 February 2021
                : 6
                : 4
                : e144499
                Affiliations
                [1 ]Research Branch, Sidra Medicine, Doha, Qatar.
                [2 ]St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, New York, USA.
                [3 ]Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, Paris, France.
                [4 ]University of Paris, Imagine Institute, Paris, France.
                [5 ]College of Health Sciences, QU Health, Qatar University, Doha, Qatar.
                [6 ]Biomedical Research Center, Qatar University, Doha, Qatar.
                [7 ]Department of Pathology, Sidra Medicine, Doha, Qatar.
                [8 ]Center of Human Genetics,
                [9 ]Department of Internal Medicine, and
                [10 ]Fonds de la Recherche Scientifique (FNRS) and Center of Human Genetics, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.
                [11 ]Department of Pediatric Pulmonology and Immunology, Department of Pediatrics and Internal Medicine, Center for Primary Immunodeficiencies Ghent, Jeffrey Modell Foundation Diagnostic and Research Center, Ghent University Hospital, Belgium.
                [12 ]Laboratory for Inborn Errors of Immunity, Department of Microbiology, Immunology and Transplantation, and Department of Pediatrics, University Hospitals Leuven, KU Leuven, Belgium.
                [13 ]Department of Pediatrics, University Hospitals Leuven, KU Leuven, Belgium.
                [14 ]Howard Hughes Medical Institute, New York, New York, USA.
                [15 ]Weill Cornell Medical College in Qatar, Doha, Qatar.
                [16 ]College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar.
                Author notes
                Address correspondence to: Nico Marr, Sidra Medicine, Research Branch, Al Gharrafa Street, Ar-Rayyan, PO Box 26999, Doha, Qatar. Phone: 974.4003.7568; E-mail: nmarr@ 123456sidra.org .
                Author information
                http://orcid.org/0000-0002-7917-8965
                http://orcid.org/0000-0003-4586-4067
                http://orcid.org/0000-0001-6451-7357
                http://orcid.org/0000-0002-9040-3289
                http://orcid.org/0000-0002-5926-8437
                http://orcid.org/0000-0001-7209-6257
                http://orcid.org/0000-0001-9252-1038
                http://orcid.org/0000-0002-7621-0130
                http://orcid.org/0000-0001-8682-5967
                http://orcid.org/0000-0002-2730-7673
                http://orcid.org/0000-0003-2845-6758
                http://orcid.org/0000-0001-7016-6493
                http://orcid.org/0000-0002-7782-4169
                http://orcid.org/0000-0002-4658-7949
                http://orcid.org/0000-0002-1927-7072
                Article
                144499
                10.1172/jci.insight.144499
                7934927
                33497357
                bb03c3e4-669b-4559-8b1f-a0448b0cd2f3
                © 2021 Khan et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 September 2020
                : 13 January 2021
                Funding
                Funded by: Qatar National Research Fund
                Award ID: PPM1-1220-150017
                Funded by: Sidra Medicine
                Award ID: SDR400127
                Categories
                Research Article

                immunology,infectious disease,immunoglobulins
                immunology, infectious disease, immunoglobulins

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