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Quantitative flow cytometric selection of tau conformational nanobodies specific for pathological aggregates
- Source :
- Frontiers in Immunology, Vol 14 (2023)
- Publication Year :
- 2023
- Publisher :
- Frontiers Media S.A., 2023.
-
Abstract
- Single-domain antibodies, also known as nanobodies, are broadly important for studying the structure and conformational states of several classes of proteins, including membrane proteins, enzymes, and amyloidogenic proteins. Conformational nanobodies specific for aggregated conformations of amyloidogenic proteins are particularly needed to better target and study aggregates associated with a growing class of associated diseases, especially neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. However, there are few reported nanobodies with both conformational and sequence specificity for amyloid aggregates, especially for large and complex proteins such as the tau protein associated with Alzheimer’s disease, due to difficulties in selecting nanobodies that bind to complex aggregated proteins. Here, we report the selection of conformational nanobodies that selectively recognize aggregated (fibrillar) tau relative to soluble (monomeric) tau. Notably, we demonstrate that these nanobodies can be directly isolated from immune libraries using quantitative flow cytometric sorting of yeast-displayed libraries against tau aggregates conjugated to quantum dots, and this process eliminates the need for secondary nanobody screening. The isolated nanobodies demonstrate conformational specificity for tau aggregates in brain samples from both a transgenic mouse model and human tauopathies. We expect that our facile approach will be broadly useful for isolating conformational nanobodies against diverse amyloid aggregates and other complex antigens.
Details
- Language :
- English
- ISSN :
- 16643224
- Volume :
- 14
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Immunology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.744b44e777364c28a6fe9024584e8b23
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fimmu.2023.1164080