Toward a more accurate view of human B-cell repertoire by next-generation sequencing, unbiased repertoire capture and single-molecule barcoding.

TitleToward a more accurate view of human B-cell repertoire by next-generation sequencing, unbiased repertoire capture and single-molecule barcoding.
Publication TypeJournal Article
Year of Publication2014
AuthorsHe L, Sok D, Azadnia P, Hsueh J, Landais E, Simek M, Koff WC, Poignard P, Burton DR, Zhu J
JournalSci Rep
Volume4
Pagination6778
Date Published10/27/2014
ISSN2045-2322
Abstract

B-cell repertoire analysis using next-generation sequencing has become a valuable tool for interrogating the genetic record of humoral response to infection. However, key obstacles such as low throughput, short read length, high error rate, and undetermined bias of multiplex PCR method have hindered broader application of this technology. In this study, we report several technical advances in antibody repertoire sequencing. We first demonstrated the ability to sequence antibody variable domains using the Ion Torrent PGM platform. As a test case, we analyzed the PGT121 class of antibodies from IAVI donor 17, an HIV-1-infected individual. We then obtained "unbiased" antibody repertoires by sequencing the 5'-RACE PCR products of B-cell transcripts from IAVI donor 17 and two HIV-1-uninfected individuals. We also quantified the bias of previously published gene-specific primers by comparing the repertoires generated by 5'-RACE PCR and multiplex PCR. We further developed a single-molecule barcoding strategy to reduce PCR-based amplification noise. Lastly, we evaluated several new PGM technologies in the context of antibody sequencing. We expect that, based upon long-read and high-fidelity next-generation sequencing technologies, the unbiased analysis will provide a more accurate view of the overall antibody repertoire while the barcoding strategy will facilitate high-resolution analysis of individual antibody families.

DOI10.1038/srep06778
Alternate JournalSci Rep
PubMed ID25345460
Grant ListUM1 AI100663 / AI / NIAID NIH HHS / United States
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