A robust pipeline for rapid production of versatile nanobody repertoires
| Autor: | Sarah Keegan, Marlene Oeffinger, David Fenyö, Michel C. Nussenzweig, Peter C. Fridy, Brian T. Chait, Mary K Thompson, Johannes F. Scheid, Yinyin Li, Michael P. Rout, Ilona Nudelman |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Green Fluorescent Proteins
Computational biology Biology Proteomics Biochemistry Epitope Article law.invention 03 medical and health sciences Epitopes 0302 clinical medicine Antigen law Animals Lymphocytes Molecular Biology 030304 developmental biology Gene Library 0303 health sciences Extramural Cell Biology Single-Domain Antibodies Molecular biology Recombinant Proteins Luminescent Proteins Spectrometry Mass Matrix-Assisted Laser Desorption-Ionization Recombinant DNA Immunization mCherry Camelids New World 030217 neurology & neurosurgery Biotechnology |
| Zdroj: | Nature methods |
| ISSN: | 1548-7105 1548-7091 |
| Popis: | Nanobodies are single domain antibodies derived from the variable regions of Camelidae atypical immunoglobulins. They show great promise as high affinity reagents for research, diagnostics and therapeutics due to their high specificity, small size (~15 kDa) and straightforward bacterial expression. However, identification of repertoires with sufficiently high affinity has proven time consuming and difficult, hampering nanobody implementation. Here, we present a rapid, straightforward approach that generates large repertoires of readily expressible recombinant nanobodies with high affinities and specificities against a given antigen. We demonstrate the efficacy of this approach through the production of large repertoires of nanobodies against two antigens, GFP and mCherry, with Kd values into the sub-nanomolar range. After mapping diverse epitopes on GFP, we were also able to design ultra-high affinity dimeric nanobodies with Kds down to ~30 pM. The approach presented is well-suited for the routine production of high affinity capture reagents for various biomedical applications. |
| Databáze: | OpenAIRE |
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