For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
12
views
116
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      396
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Preservation of memory B cell homeostasis in an individual producing broadly neutralising antibodies against HIV-1

      Preprint
      research-article

      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

          Immunological determinants favouring emergence of broadly neutralising antibodies are crucial to the development of HIV-1 vaccination strategies. Here, we combined RNAseq and B cell cloning approaches to isolate a broadly neutralising antibody (bnAb) ELC07 from an individual living with untreated HIV-1. Using single particle cryogenic electron microscopy (cryo-EM), we show that the antibody recognises a conformational epitope at the gp120-gp41 interface. ELC07 binds the closed state of the viral glycoprotein causing considerable perturbations to the gp41 trimer core structure. Phenotypic analysis of memory B cell subsets from the ELC07 bnAb donor revealed a lack of expected HIV-1-associated dysfunction, specifically no increase in CD21 −/CD27 − cells was observed whilst the resting memory (CD21 +/CD27 +) population appeared preserved despite uncontrolled HIV-1 viraemia. Moreover, single cell transcriptomes of memory B cells from this bnAb donor showed a resting memory phenotype irrespective of the epitope they targeted or their ability to neutralise diverse strains of HIV-1. Strikingly, single memory B cells from the ELC07 bnAb donor were transcriptionally similar to memory B cells from HIV-negative individuals. Our results demonstrate that potent bnAbs can arise without the HIV-1-induced dysregulation of the memory B cell compartment and suggest that sufficient levels of antigenic stimulation with a strategically designed immunogen could be effective in HIV-negative vaccine recipients.

          Related collections

          Most cited references116

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

          UCSF Chimera--a visualization system for exploratory research and analysis.

          Eric F. Pettersen, Thomas Goddard, Conrad Huang … (2004)
          The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
          Article 0 comments Cited 7937 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

            Bo Li, Colin Dewey (2011)
            Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
            Article 0 comments Cited 4592 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

              Ali Punjani, John Rubinstein, David J. Fleet … (2017)
              A software tool, cryoSPARC, addresses the speed bottleneck in cryo-EM image processing, enabling automated macromolecular structure determination in hours on a desktop computer without requiring a starting model.
              Article 0 comments Cited 2678 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): bioRxiv
                Journal ID (publisher-id): BIORXIV
                Title: bioRxiv
                Publisher: Cold Spring Harbor Laboratory
                Publication date (Electronic): 06 February 2024
                Electronic Location Identifier: 2024.02.05.578789
                Affiliations
                [1 ]Institute of Immunity and Transplantation, Division of Infection and Immunity, University College London, London, UK;
                [2 ]Molecular Immunity Unit, Department of Medicine, Medical Research Council Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK;
                [3 ]Cambridge University Hospitals NHS Foundation Trust, and NIHR Cambridge Biomedical Research Centre, Cambridge, UK
                [4 ]Chromatin Structure and Mobile DNA Laboratory, The Francis Crick Institute, London, UK;
                [5 ]Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, UK;
                [6 ]Cellular Genetics, Wellcome Sanger Institute, Cambridge, UK
                [7 ]Ian Frazer Centre for Children’s Immunotherapy Research, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia
                [8 ]Structural Biology Science Technology Platform, The Francis Crick Institute, London, UK
                [9 ]SHARE collaborative, Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK;
                [10 ]Homerton University Hospital NHS Foundation, London, UK;
                [11 ]Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), Cambridge, UK;
                [12 ]Department of Medicine, University of Cambridge, Cambridge, UK;
                [13 ]Department of Infectious Diseases, School of Immunology & Microbial Sciences, King’s College London, London, UK;
                [14 ]Department of Infectious Disease, St-Mary’s Campus, Imperial College London, London, UK;
                Author notes
                [**]

                equal contribution

                Author contributions

                L.E.M conceptualised the project. S.G, L.M, J.H, C.P, J.M.G, A.F, E.T, C.R-S, A.N, C.R, Y.A, D.F, K.J.D, L.E.M, P.C performed experimental work. S.G, L.M, O.S, Z.K.T, M.C designed and performed bioinformatic analysis. C.O, J.D, J.A, R.K.G, A.M recruited participants. S.G, L.M, O.S, P.C and L.E.M wrote the original manuscript. S.G, L.M, J.H, J.M.G, C.R-S, D.F, K.J.D, C.O, P.C, A.M, M.C and L.E.M reviewed and edited the manuscript. L.E.M, A.M and P.C acquired funding and supervised the project.

                [§ ]Corresponding author
                Author information
                http://orcid.org/0000-0001-9751-1808
                http://orcid.org/0000-0002-0634-538X
                http://orcid.org/0000-0001-9503-7946
                Article
                DOI: 10.1101/2024.02.05.578789
                PMC ID: 10871235
                PubMed ID: 38370662
                SO-VID: baa23f39-8800-4428-b147-02b85577e7b9
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

                History
                Funding
                This study was supported by the European Research Council (ERC) under the European Union’s 1053 Horizon 2020 research and innovation programme (Grant Agreement No. 757601). L.E.M is supported by a Career Development Award (MR/R008698/1). E.T is supported by an MRC studentship (MR/N013867/1). The work in Peter Cherepanov’s laboratory was funded by the US National Institutes of Health grant U54AI170791 and the Francis Crick Institute, which receives its core funding from Cancer Research UK (CC2058), the UK Medical Research Council (CC2058), and the Wellcome Trust (CC2058). A.M and J.M.G are supported by The Rosetrees Trust (CF1\100003). For Open Access, the author has applied for a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
                Categories
                Subject: Article

                Data availability:

                Comments

                Comment on this article