Quantitative flow cytometric selection of tau conformational nanobodies specific for pathological aggregates

Frontiers in Immunology

Immunology

Emily K. Makowski¹  Jennifer M. Zupancic²  Matthew D. Smith²  Michael J. Lucas³  Peter M. Tessier⁴  Mary E. Skinner⁵  Henry L. Paulson⁶  Sean P. Ferris⁷  Hanna Trzeciakiewicz⁸  Ravi S. Kane⁹  Nikki McArthur⁹ 

[1] Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States;Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, United States;Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, United States;Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States;Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, United States;Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States;Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, United States;Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, United States;Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States;Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, United States;Protein Folding Disease Initiative, University of Michigan, Ann Arbor, MI, United States;Michigan Alzheimer’s Disease Center, University of Michigan, Ann Arbor, MI, United States;Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States;Department of Neurology, University of Michigan, Ann Arbor, MI, United States;Department of Neurology, University of Michigan, Ann Arbor, MI, United States;Protein Folding Disease Initiative, University of Michigan, Ann Arbor, MI, United States;Michigan Alzheimer’s Disease Center, University of Michigan, Ann Arbor, MI, United States;Department of Pathology, University of Michigan, Ann Arbor, MI, United States;Department of Translational Neuroscience, Michigan State University, Grand Rapids, MI, United States;School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, United States;

关键词: VH;    single-domain antibody (sdAb);    protein aggregation;    fibril;    tauopathy;    Alzheimer’s disease;    neurodegenerative disease;   

DOI  :  10.3389/fimmu.2023.1164080

 received in 2023-02-12, accepted in 2023-05-15,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Zupancic, Smith, Trzeciakiewicz, Skinner, Ferris, Makowski, Lucas, McArthur, Kane, Paulson and Tessier