Bioinformatic Analysis of Natively Paired VH:VL Antibody Repertoires for Antibody Discovery
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nihms-2079241.pdf
Description
Accepted version
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780.16 KB
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Adobe PDF
Checksum (MD5)
ca7e396a0ac23a722ae6cbba4b64ab14
Author(s)
Fahad, Ahmed S
Madan, Bharat
DeKosky, Brandon J
Date Issued
November 9, 2022
Journal
Methods in Molecular Biology
Publisher
Springer US
Citation
Fahad, A.S., Madan, B., DeKosky, B.J. (2023). Bioinformatic Analysis of Natively Paired VH:VL Antibody Repertoires for Antibody Discovery. In: Tsumoto, K., Kuroda, D. (eds) Computer-Aided Antibody Design. Methods in Molecular Biology, vol 2552. Humana, New York, NY.
Version
Author's final manuscript
Abstract
Next-generation DNA sequencing (NGS) of human antibody repertoires has been extensively implemented to discover novel antibody drugs, to analyze B-cell developmental features, and to investigate antibody responses to infectious diseases and vaccination. Because the antibody repertoire encoded by human B cells is highly diverse, NGS analyses of antibody genes have provided a new window into understanding antibody responses for basic immunology, biopharmaceutical drug discovery, and immunotherapy. However, many antibody discovery protocols analyze the heavy and light chains separately due to the short-read nature of most NGS technologies, whereas paired heavy and light chain data are required for complete antibody characterization. Here, we describe a computational workflow to process millions of paired antibody heavy and light chain DNA sequence reads using the Illumina MiSeq 2x300 NGS platform. In this workflow, we describe raw NGS read processing and initial quality filtering, the annotation and assembly of antibody clonotypes relating to paired heavy and light chain antibody lineages, and the generation of complete heavy+light consensus sequences for the downstream cloning and expression of human antibody proteins.
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/978-1-0716-2609-2_25
