Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves

Abstract
Data availability
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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).

https://www.ncbi.nlm.nih.gov/bioproject/344711

Article and author information

Author details

Rhys M Adams

Laboratoire de Physique Théorique, École Normale Supérieure, Paris, France

Competing interests
The authors declare that no competing interests exist.
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.

"This ORCID iD identifies the author of this article:" 0000-0002-5456-9361
Aleksandra M Walczak

Laboratoire de Physique Théorique, École Normale Supérieure, Paris, France

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-2686-5702
Justin B Kinney

Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, United States

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.

Copyright

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.