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Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops
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 ‘pol...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755423/ https://www.ncbi.nlm.nih.gov/pubmed/33169668 http://dx.doi.org/10.7554/eLife.61393 |
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author | Boughter, Christopher T Borowska, Marta T Guthmiller, Jenna J Bendelac, Albert Wilson, Patrick C Roux, Benoit Adams, Erin J |
author_facet | Boughter, Christopher T Borowska, Marta T Guthmiller, Jenna J Bendelac, Albert Wilson, Patrick C Roux, Benoit Adams, Erin J |
author_sort | Boughter, Christopher T |
collection | PubMed |
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 1000 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. |
format | Online Article Text |
id | pubmed-7755423 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-77554232020-12-28 Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops Boughter, Christopher T Borowska, Marta T Guthmiller, Jenna J Bendelac, Albert Wilson, Patrick C Roux, Benoit Adams, Erin J eLife Immunology and Inflammation 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 1000 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. eLife Sciences Publications, Ltd 2020-11-10 /pmc/articles/PMC7755423/ /pubmed/33169668 http://dx.doi.org/10.7554/eLife.61393 Text en © 2020, Boughter et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Immunology and Inflammation Boughter, Christopher T Borowska, Marta T Guthmiller, Jenna J Bendelac, Albert Wilson, Patrick C Roux, Benoit Adams, Erin J Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title | Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title_full | Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title_fullStr | Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title_full_unstemmed | Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title_short | Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops |
title_sort | biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of cdr loops |
topic | Immunology and Inflammation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755423/ https://www.ncbi.nlm.nih.gov/pubmed/33169668 http://dx.doi.org/10.7554/eLife.61393 |
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