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A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies

Antibody engineering technologies face increasing demands for speed, reliability and scale. We develop CeVICA, a cell-free nanobody engineering platform that uses ribosome display for in vitro selection of nanobodies from a library of 10(11) randomized sequences. We apply CeVICA to engineer nanobodi...

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Autores principales: Chen, Xun, Gentili, Matteo, Hacohen, Nir, Regev, Aviv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448731/
https://www.ncbi.nlm.nih.gov/pubmed/34535642
http://dx.doi.org/10.1038/s41467-021-25777-z
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author Chen, Xun
Gentili, Matteo
Hacohen, Nir
Regev, Aviv
author_facet Chen, Xun
Gentili, Matteo
Hacohen, Nir
Regev, Aviv
author_sort Chen, Xun
collection PubMed
description Antibody engineering technologies face increasing demands for speed, reliability and scale. We develop CeVICA, a cell-free nanobody engineering platform that uses ribosome display for in vitro selection of nanobodies from a library of 10(11) randomized sequences. We apply CeVICA to engineer nanobodies against the Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein and identify >800 binder families using a computational pipeline based on CDR-directed clustering. Among 38 experimentally-tested families, 30 are true RBD binders and 11 inhibit SARS-CoV-2 pseudotyped virus infection. Affinity maturation and multivalency engineering increase nanobody binding affinity and yield a virus neutralizer with picomolar IC50. Furthermore, the capability of CeVICA for comprehensive binder prediction allows us to validate the fitness of our nanobody library. CeVICA offers an integrated solution for rapid generation of divergent synthetic nanobodies with tunable affinities in vitro and may serve as the basis for automated and highly parallel nanobody engineering.
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spelling pubmed-84487312021-10-04 A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies Chen, Xun Gentili, Matteo Hacohen, Nir Regev, Aviv Nat Commun Article Antibody engineering technologies face increasing demands for speed, reliability and scale. We develop CeVICA, a cell-free nanobody engineering platform that uses ribosome display for in vitro selection of nanobodies from a library of 10(11) randomized sequences. We apply CeVICA to engineer nanobodies against the Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein and identify >800 binder families using a computational pipeline based on CDR-directed clustering. Among 38 experimentally-tested families, 30 are true RBD binders and 11 inhibit SARS-CoV-2 pseudotyped virus infection. Affinity maturation and multivalency engineering increase nanobody binding affinity and yield a virus neutralizer with picomolar IC50. Furthermore, the capability of CeVICA for comprehensive binder prediction allows us to validate the fitness of our nanobody library. CeVICA offers an integrated solution for rapid generation of divergent synthetic nanobodies with tunable affinities in vitro and may serve as the basis for automated and highly parallel nanobody engineering. Nature Publishing Group UK 2021-09-17 /pmc/articles/PMC8448731/ /pubmed/34535642 http://dx.doi.org/10.1038/s41467-021-25777-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chen, Xun
Gentili, Matteo
Hacohen, Nir
Regev, Aviv
A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title_full A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title_fullStr A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title_full_unstemmed A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title_short A cell-free nanobody engineering platform rapidly generates SARS-CoV-2 neutralizing nanobodies
title_sort cell-free nanobody engineering platform rapidly generates sars-cov-2 neutralizing nanobodies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448731/
https://www.ncbi.nlm.nih.gov/pubmed/34535642
http://dx.doi.org/10.1038/s41467-021-25777-z
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