Published November 10, 2020 | Version v1
Journal article Open

Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of cdr loops

Description

Antibodies are critical components of adaptive immunity, binding with high affinity to pathogenic epitopes. Antibodies undergo rigorous selection to achieve this high affinity, yet some maintain an additional basal level of low affinity, broad reactivity to diverse epitopes, a phenomenon termed "polyreactivity". While polyreactivity has been observed in antibodies isolated from various immunological niches, the biophysical properties that allow for promiscuity in a protein selected for high affinity binding to a single target remain unclear. Using a database of over 1,000 polyreactive and non-polyreactive antibody sequences, we created a bioinformatic pipeline to isolate key determinants of polyreactivity. These determinants, which include an increase in inter-loop crosstalk and a propensity for a neutral binding surface, are sufficient to generate a classifier able to identify polyreactive antibodies with over 75% accuracy. The framework from which this classifier was built is generalizable, and represents a powerful, automated pipeline for future immune repertoire analysis.

Data availability

All data generated and all code used for analysis in this study has been published on GitHub at http://github.com/ctboughter/AIMS (copy archived at https://archive.softwareheritage.org/swh:1:rev:f6c855ef4a7ce63f72dba6b34e9d0e9edd9200ce/).

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Additional details

Identifiers

DOI
10.7554/eLife.61393
Other
oai:uchicago.tind.io:9862

Funding

National Institute of Biomedical Imaging and Bioengineering
EB009412
National Institute of Allergy and Infectious Diseases
AI147954
National Institute of Allergy and Infectious Diseases
AI115471
National Science Foundation
MCB-1517221
National Institute of Allergy and Infectious Diseases
AI125250

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Biochemistry and Molecular Biology, Biophysical Sciences, Immunology, Medicine, Pathology