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      Convergent CDR3 homology amongst Spike-specific antibody responses in convalescent COVID-19 subjects receiving the BNT162b2 vaccine

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          Abstract

          Convalescent coronavirus disease 2019 (COVID-19) subjects who receive BNT162b2 develop robust antibody responses against SARS-CoV-2. However, our understanding of the clonal B cell response pre- and post-vaccination in such individuals is limited. Here we characterized B cell phenotypes and the BCR repertoire after BNT162b2 immunization in two convalescent COVID-19 subjects. BNT162b2 stimulated many B cell clones that were under-represented during SARS-CoV-2 infection. In addition, the vaccine generated B cell clusters with >65% similarity in CDR3 V H and V L region consensus sequences both within and between subjects. This result suggests that the CDR3 region plays a dominant role adjacent to heavy and light chain V/J pairing in the recognition of the SARS-CoV-2 spike protein. Antigen-specific B cell populations with homology to published SARS-CoV-2 antibody sequences from the CoV-AbDab database were observed in both subjects. These results point towards the development of convergent antibody responses against the virus in different individuals.

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          STAR: ultrafast universal RNA-seq aligner.

          Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)
          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine

            Fernando P Polack, Stephen J. Thomas, Nicholas R.E. Kitchin … (2023)
            Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (Covid-19) have afflicted tens of millions of people in a worldwide pandemic. Safe and effective vaccines are needed urgently. Methods In an ongoing multinational, placebo-controlled, observer-blinded, pivotal efficacy trial, we randomly assigned persons 16 years of age or older in a 1:1 ratio to receive two doses, 21 days apart, of either placebo or the BNT162b2 vaccine candidate (30 μg per dose). BNT162b2 is a lipid nanoparticle–formulated, nucleoside-modified RNA vaccine that encodes a prefusion stabilized, membrane-anchored SARS-CoV-2 full-length spike protein. The primary end points were efficacy of the vaccine against laboratory-confirmed Covid-19 and safety. Results A total of 43,548 participants underwent randomization, of whom 43,448 received injections: 21,720 with BNT162b2 and 21,728 with placebo. There were 8 cases of Covid-19 with onset at least 7 days after the second dose among participants assigned to receive BNT162b2 and 162 cases among those assigned to placebo; BNT162b2 was 95% effective in preventing Covid-19 (95% credible interval, 90.3 to 97.6). Similar vaccine efficacy (generally 90 to 100%) was observed across subgroups defined by age, sex, race, ethnicity, baseline body-mass index, and the presence of coexisting conditions. Among 10 cases of severe Covid-19 with onset after the first dose, 9 occurred in placebo recipients and 1 in a BNT162b2 recipient. The safety profile of BNT162b2 was characterized by short-term, mild-to-moderate pain at the injection site, fatigue, and headache. The incidence of serious adverse events was low and was similar in the vaccine and placebo groups. Conclusions A two-dose regimen of BNT162b2 conferred 95% protection against Covid-19 in persons 16 years of age or older. Safety over a median of 2 months was similar to that of other viral vaccines. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
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              Comprehensive Integration of Single-Cell Data

              Tim Stuart, Andrew Butler, Paul Hoffman … (2019)
              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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                Author and article information

                Journal
                Journal ID (nlm-ta): Clin Immunol
                Journal ID (iso-abbrev): Clin Immunol
                Title: Clinical Immunology (Orlando, Fla.)
                Publisher: Published by Elsevier Inc.
                ISSN (Print): 1521-6616
                ISSN (Electronic): 1521-7035
                Publication date PMC-release: 5 March 2022
                Publication date (Electronic): 5 March 2022
                Electronic Location Identifier: 108963
                Affiliations
                [a ]Department of Immunology, University of Toronto, Toronto, Ontario, Canada
                [b ]Department of Laboratory Medicine, University of Toronto, Toronto, Ontario, Canada
                [c ]Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
                [d ]Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
                [e ]Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada
                [f ]dYcode Bio, Toronto, Ontario, Canada
                [g ]Department of Medicine, University of Toronto; Toronto, ON, Canada
                [h ]Keenan Research Centre for Biomedical Science of St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
                Author notes
                [* ]Correspondence to: M. Ostrowski, Department of Laboratory Medicine, University of Toronto, Medical Sciences Building 6271, Toronto M5S1A8, Canada.
                [** ]Correspondence to: A. Martin, Department of Immunology, University of Toronto, Medical Sciences Building 7302, Toronto M5S1A8, Canada.
                Article
                Publisher Item ID: S1521-6616(22)00043-2 Publisher ID: 108963
                DOI: 10.1016/j.clim.2022.108963
                PMC ID: 8897198
                PubMed ID: 35259543
                SO-VID: a4a70205-0369-404b-a365-e222869e4979
                Copyright © © 2022 Published by Elsevier Inc.
                License:

                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
                Date received : 30 December 2021
                Date revision received : 25 February 2022
                Date accepted : 1 March 2022
                Categories
                Subject: Article

                ScienceOpen disciplines: Immunology
                Keywords: sars cov2,covid19,b cells,antibodies
                Data availability:
                ScienceOpen disciplines: Immunology
                Keywords: sars cov2, covid19, b cells, antibodies

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