1. Structural Biology and Molecular Biophysics
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Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves

  1. Rhys M Adams
  2. Thierry Mora  Is a corresponding author
  3. Aleksandra M Walczak  Is a corresponding author
  4. Justin B Kinney  Is a corresponding author
  1. École Normale Supérieure, France
  2. Cold Spring Harbor Laboratory, United States
Research Article
  • Cited 36
  • Views 4,406
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Cite this article as: eLife 2016;5:e23156 doi: 10.7554/eLife.23156

Abstract

Despite the central role that antibodies play in the adaptive immune system and in biotechnology, much remains unknown about the quantitative relationship between an antibody's amino acid sequence and its antigen binding affinity. Here we describe a new experimental approach, called Tite-Seq, that is capable of measuring binding titration curves and corresponding affinities for thousands of variant antibodies in parallel. The measurement of titration curves eliminates the confounding effects of antibody expression and stability that arise in standard deep mutational scanning assays. We demonstrate Tite-Seq on the CDR1H and CDR3H regions of a well-studied scFv antibody. Our data shed light on the structural basis for antigen binding affinity and suggests a role for secondary CDR loops in establishing antibody stability. Tite-Seq fills a large gap in the ability to measure critical aspects of the adaptive immune system, and can be readily used for studying sequence-affinity landscapes in other protein systems.

Data availability

The following data sets were generated
    1. Adams RM
    2. Kinney JB
    3. Mora T
    4. Walczak AM
    (2016) Saccharomyces cerevisiae high-throughput titration curves
    Publicly available at the NCBI BioProject database (accession no: PRJNA344711).

Article and author information

Author details

  1. Rhys M Adams

    Laboratoire de Physique Théorique, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Thierry Mora

    Laboratoire de Physique Statistique, École Normale Supérieure, Paris, France
    For correspondence
    tmora@lps.ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5456-9361
  3. Aleksandra M Walczak

    Laboratoire de Physique Théorique, École Normale Supérieure, Paris, France
    For correspondence
    awalczak@lpt.ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2686-5702
  4. Justin B Kinney

    Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    For correspondence
    jkinney@cshl.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

European Research Council (StG n. 306312)

  • Rhys M Adams
  • Thierry Mora
  • Aleksandra M Walczak

Simons Center for Quantitative Biology

  • Justin B Kinney

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Jesse D Bloom, Fred Hutchinson Cancer Research Center, United States

Publication history

  1. Received: November 10, 2016
  2. Accepted: December 27, 2016
  3. Accepted Manuscript published: December 30, 2016 (version 1)
  4. Accepted Manuscript updated: January 3, 2017 (version 2)
  5. Version of Record published: January 26, 2017 (version 3)

Copyright

© 2016, Adams et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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