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PreprintCited by 24Monoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approachesChemical Synthesis and Analysis

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

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Petersen, Brian M., Kirby, Monica B., Chrispens, Karson M., Irvin, Olivia M., Strawn, Isabell K., Haas, Cyrus M., Walker, Alexis M., Baumer, Zachary T., Ulmer, Sophia A., Ayala, Edgardo, Rhodes, Emily R., Guthmiller, Jenna J., Steiner, Paul J., Whitehead, Timothy A.·2024·Nature Communications
DOI 10.1101/2024.01.16.575852PMC PMC11087541

Preprint — published as 10.1038/s41467-024-48072-z · Paper page

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Abstract

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines m ultiple a nti g ens and m ultiple a ntibodies and determines quantitative biophysical parameters using deep seq uencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of ten different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

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Authors
Petersen, B. M., Kirby, M. B., Chrispens, K. M., Irvin, O. M., Strawn, I. K., Haas, C. M., Walker, A. M., Baumer, Z. T., Ulmer, S. A., Ayala, E., Rhodes, E. R., Guthmiller, J. J., Steiner, P. J., & Whitehead, T. A.
Affiliations
  • University of Colorado Boulder (US)
  • University of Colorado Anschutz (US)
Corresponding author
Whitehead, Timothy A.
ORCID
Venue
Nature Communications
Publisher
openRxiv
Published
2024-01-17
Volume
15
Issue
1
Pages
3974-3974
ISSN
2041-1723 (ISSN-L)
DOI
10.1101/2024.01.16.575852
PMC
PMC11087541
OpenAlex
W4396815173
Cited by
24
References
1
Citations by year
2026: 15 · 2025: 7 · 2024: 2
FWCI
6.11
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Science Foundation (2040434, 2244288, 2201538)
  • Division of Intramural Research, National Institute of Allergy and Infectious Diseases (5R01AI141452-05)
  • Colorado State University (2201538)
  • Rush University
  • National Institutes of Health
  • University of Colorado Boulder (2201538)
  • National Institute of Allergy and Infectious Diseases (R01AI141452, R00AI159136)
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
Keywords
mutation scanning, sequence-function relationships, antibody engineering, broadly neutralizing antibodies, binding affinity measurement, deep sequencing

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