Dataset Information

De novo identification of VRC01 class HIV-1-neutralizing antibodies by next-generation sequencing of B-cell transcripts.

ABSTRACT: Next-generation sequencing of antibody transcripts provides a wealth of data, but the ability to identify function-specific antibodies solely on the basis of sequence has remained elusive. We previously characterized the VRC01 class of antibodies, which target the CD4-binding site on gp120, appear in multiple donors, and broadly neutralize HIV-1. Antibodies of this class have developmental commonalities, but typically share only ?50% amino acid sequence identity among different donors. Here we apply next-generation sequencing to identify VRC01 class antibodies in a new donor, C38, directly from B cell transcript sequences. We first tested a lineage rank approach, but this was unsuccessful, likely because VRC01 class antibody sequences were not highly prevalent in this donor. We next identified VRC01 class heavy chains through a phylogenetic analysis that included thousands of sequences from C38 and a few known VRC01 class sequences from other donors. This "cross-donor analysis" yielded heavy chains with little sequence homology to previously identified VRC01 class heavy chains. Nonetheless, when reconstituted with the light chain from VRC01, half of the heavy chain chimeric antibodies showed substantial neutralization potency and breadth. We then identified VRC01 class light chains through a five-amino-acid sequence motif necessary for VRC01 light chain recognition. From over a million light chain sequences, we identified 13 candidate VRC01 class members. Pairing of these light chains with the phylogenetically identified C38 heavy chains yielded functional antibodies that effectively neutralized HIV-1. Bioinformatics analysis can thus directly identify functional HIV-1-neutralizing antibodies of the VRC01 class from a sequenced antibody repertoire.

SUBMITTER: Zhu J

PROVIDER: S-EPMC3808619 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Publications

De novo identification of VRC01 class HIV-1-neutralizing antibodies by next-generation sequencing of B-cell transcripts.

Zhu Jiang J Wu Xueling X Zhang Baoshan B McKee Krisha K O'Dell Sijy S Soto Cinque C Zhou Tongqing T Casazza Joseph P JP Mullikin James C JC Kwong Peter D PD Mascola John R JR Shapiro Lawrence L

Proceedings of the National Academy of Sciences of the United States of America 20131008 43

Next-generation sequencing of antibody transcripts provides a wealth of data, but the ability to identify function-specific antibodies solely on the basis of sequence has remained elusive. We previously characterized the VRC01 class of antibodies, which target the CD4-binding site on gp120, appear in multiple donors, and broadly neutralize HIV-1. Antibodies of this class have developmental commonalities, but typically share only ∼50% amino acid sequence identity among different donors. Here we a ...[more]

PMID: 24106303

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Project description:BACKGROUND:A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57-74, 2012; Nat 507:462-70, 2014; Nat 507:455-61, 2014; Nat 518:317-30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. RESULTS:We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563-5, 2007; Nat Protoc 5:323-34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. CONCLUSIONS:TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au .

Dataset Information

De novo identification of VRC01 class HIV-1-neutralizing antibodies by next-generation sequencing of B-cell transcripts.

Publications

De novo identification of VRC01 class HIV-1-neutralizing antibodies by next-generation sequencing of B-cell transcripts.

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