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      Live-attenuated vaccine sCPD9 elicits superior mucosal and systemic immunity to SARS-CoV-2 variants in hamsters

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      1 , 1 , 2 , 1 , 3 , 4 , 1 , 5 , 5 , 5 , 2 , 2 , 6 , 7 , 6 , 7 , 8 , 8 , 8 , 9 , 1 , 10 , 11 , 2 , 2 , 12 , 12 , 6 , 13 , 6 , 13 , 6 , 7 , 14 , 3 , 15 , 1 , 5 , 16 , 2 , 17 , 4 , 2 , 2 ,
      Nature Microbiology
      Nature Publishing Group UK
      Live attenuated vaccines, SARS-CoV-2, Mucosal immunology

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          Abstract

          Vaccines play a critical role in combating the COVID-19 pandemic. Future control of the pandemic requires improved vaccines with high efficacy against newly emerging SARS-CoV-2 variants and the ability to reduce virus transmission. Here we compare immune responses and preclinical efficacy of the mRNA vaccine BNT162b2, the adenovirus-vectored spike vaccine Ad2-spike and the live-attenuated virus vaccine candidate sCPD9 in Syrian hamsters, using both homogeneous and heterologous vaccination regimens. Comparative vaccine efficacy was assessed by employing readouts from virus titrations to single-cell RNA sequencing. Our results show that sCPD9 vaccination elicited the most robust immunity, including rapid viral clearance, reduced tissue damage, fast differentiation of pre-plasmablasts, strong systemic and mucosal humoral responses, and rapid recall of memory T cells from lung tissue after challenge with heterologous SARS-CoV-2. Overall, our results demonstrate that live-attenuated vaccines offer advantages over currently available COVID-19 vaccines.

          Abstract

          Comparison of mucosal and systemic immunity after vaccination with the live-attenuated vaccine sCPD9, mRNA vaccine BNT162b2 or an adenovirus-vectored vaccine following SARS-CoV-2 challenge in hamsters.

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          Most cited references58

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          Comprehensive Integration of Single-Cell Data

          Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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            Integrated analysis of multimodal single-cell data

            Summary The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce “weighted-nearest neighbor” analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.
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              Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR

              Background The ongoing outbreak of the recently emerged novel coronavirus (2019-nCoV) poses a challenge for public health laboratories as virus isolates are unavailable while there is growing evidence that the outbreak is more widespread than initially thought, and international spread through travellers does already occur. Aim We aimed to develop and deploy robust diagnostic methodology for use in public health laboratory settings without having virus material available. Methods Here we present a validated diagnostic workflow for 2019-nCoV, its design relying on close genetic relatedness of 2019-nCoV with SARS coronavirus, making use of synthetic nucleic acid technology. Results The workflow reliably detects 2019-nCoV, and further discriminates 2019-nCoV from SARS-CoV. Through coordination between academic and public laboratories, we confirmed assay exclusivity based on 297 original clinical specimens containing a full spectrum of human respiratory viruses. Control material is made available through European Virus Archive – Global (EVAg), a European Union infrastructure project. Conclusion The present study demonstrates the enormous response capacity achieved through coordination of academic and public laboratories in national and European research networks.
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                Author and article information

                Contributors
                trimpert.jakob@fu-berlin.de
                Journal
                Nat Microbiol
                Nat Microbiol
                Nature Microbiology
                Nature Publishing Group UK (London )
                2058-5276
                3 April 2023
                3 April 2023
                2023
                : 8
                : 5
                : 860-874
                Affiliations
                [1 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Department of Infectious Diseases, Respiratory Medicine and Critical Care, , Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, ; Berlin, Germany
                [2 ]GRID grid.14095.39, ISNI 0000 0000 9116 4836, Institut für Virologie, , Freie Universität Berlin, ; Berlin, Germany
                [3 ]GRID grid.7468.d, ISNI 0000 0001 2248 7639, Institute of Pathology Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Institute for Biology, IRI Life Sciences, , Humboldt-Universität zu Berlin, ; Berlin, Germany
                [4 ]GRID grid.419491.0, ISNI 0000 0001 1014 0849, Berlin Institute for Medical Systems Biology (BIMSB), , Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), ; Berlin, Germany
                [5 ]GRID grid.14095.39, ISNI 0000 0000 9116 4836, Institut für Tierpathologie, , Freie Universität Berlin, ; Berlin, Germany
                [6 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Institute of Virology, , Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, ; Berlin, Germany
                [7 ]GRID grid.484013.a, ISNI 0000 0004 6879 971X, Berlin Institute of Health (BIH), ; Berlin, Germany
                [8 ]GRID grid.425396.f, ISNI 0000 0001 1019 0926, Product Testing of IVMPs, Division of Veterinary Medicines, , Paul-Ehrlich-Institut, ; Langen, Germany
                [9 ]GRID grid.452463.2, German Center for Infection Research (DZIF), partner site Gießen-Marburg-Langen, ; Giessen, Germany
                [10 ]GRID grid.440833.8, ISNI 0000 0004 0642 9705, Faculty of Medicine, , Cyprus International University, ; Nicosia, Cyprus
                [11 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Institute of Physiology, , Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, ; Berlin, Germany
                [12 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Department of Gynecology, , Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, ; Berlin, Germany
                [13 ]GRID grid.452463.2, German Center for Infection Research (DZIF), partner site Charité, ; Berlin, Germany
                [14 ]GRID grid.7468.d, ISNI 0000 0001 2248 7639, Berlin Institute for Medical Systems Biology (BIMSB) Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), and Institute for Biology, , Humboldt-Universität zu Berlin, ; Berlin, Germany
                [15 ]GRID grid.190737.b, ISNI 0000 0001 0154 0904, School of Life Sciences, , Chongqing University, ; Chongqing, China
                [16 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Berlin Institute of Health at Charité, , Universitätsmedizin Berlin, ; Berlin, Germany
                [17 ]GRID grid.35030.35, ISNI 0000 0004 1792 6846, Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, , City University of Hong Kong, ; Kowloon, Hong Kong China
                Author information
                http://orcid.org/0000-0003-1973-3119
                http://orcid.org/0000-0001-8147-0351
                http://orcid.org/0000-0002-8132-7237
                http://orcid.org/0000-0002-4257-8690
                http://orcid.org/0000-0002-5822-4168
                http://orcid.org/0000-0003-2077-3716
                http://orcid.org/0000-0001-7311-3477
                http://orcid.org/0000-0002-9670-5640
                http://orcid.org/0000-0003-3700-1691
                http://orcid.org/0000-0002-7962-2165
                http://orcid.org/0000-0001-7066-0184
                http://orcid.org/0000-0002-7069-5018
                http://orcid.org/0000-0002-1616-4005
                http://orcid.org/0000-0002-1897-6365
                http://orcid.org/0000-0001-7923-0519
                http://orcid.org/0000-0002-3959-004X
                http://orcid.org/0000-0002-1075-8734
                http://orcid.org/0000-0002-0171-7447
                http://orcid.org/0000-0002-4502-0393
                http://orcid.org/0000-0002-0186-5271
                http://orcid.org/0000-0002-9884-1806
                http://orcid.org/0000-0003-1616-0810
                Article
                1352
                10.1038/s41564-023-01352-8
                10159847
                37012419
                d14f3b3f-c0d5-4905-9457-687eb0360eda
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 June 2022
                : 1 March 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: SFB 1449–431232613
                Award ID: SFB TR84
                Award ID: SFB 1449–431232613
                Award ID: SFB TR84
                Award ID: OS 143/16-1
                Award ID: SFB TR84
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research);
                Award ID: 16GW0247
                Award ID: 01ZX1604B
                Award ID: 01ZX1906A
                Award ID: 16GW0247
                Award ID: Organo-Strat 01KX2021
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003107, Bundesministerium für Gesundheit (Federal Ministry of Health, Germany);
                Award ID: CHARIS 6a
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100009318, Helmholtz Association;
                Award ID: KA1-Co-02
                Award ID: KA1-Co-02
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100006188, Einstein Stiftung Berlin (Einstein Foundation Berlin);
                Award ID: EZ-2020-597 FU
                Award Recipient :
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                © Springer Nature Limited 2023

                live attenuated vaccines,sars-cov-2,mucosal immunology

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