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Extending the functional characteristics of naturally occurring autoantibodies against β-Amyloid, Prion Protein and α-Synuclein. PLoS One 2018; 13:e0202954. [PMID: 30157279 PMCID: PMC6114858 DOI: 10.1371/journal.pone.0202954] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Accepted: 08/13/2018] [Indexed: 12/21/2022] Open
Abstract
Background Abnormal aggregation of proteins induces neuronal cell loss in neurodegenerative disorders such as Alzheimer’s Disease, Creutzfeldt-Jakob Disease and Parkinson’s Disease. Specific stimuli initialize conformational changes in physiological proteins, causing intra- or extracellular protein aggregation. We and other groups have identified naturally occurring autoantibodies (nAbs) as part of the human antibody pool that are able to prevent peptide fibrillation. These nAbs show a rescue effect following exposure of toxic aggregates on neurons, and they support microglial uptake of aggregated peptides. Objective Identification of a putative common epitope among the relevant proteins β-Amyloid, α-Synuclein and Prion Protein for the respective nAbs. Material and methods Binding affinity between the aforementioned proteins and nAbs was tested by Dot Blot, ELISA and SPR-technology. Furthermore, the functionality of the protein-nAbs-complexes was studied in Thioflavin-T assays and microglial uptake experiments to study dependent inhibition of protein aggregation and enhancement of Fcγ mediated uptake by microglial cells. Results β-Amyloid and Prion Protein fragment showed considerable binding affinity and functional efficacy for all applied nAbs. Thereby, no significant difference within the different nAbs was detected. In contrast, α-Synuclein was bound exclusively by nAbs-α-Synuclein, which was reproduced in all binding studies. Surprisingly, functional assays with α-Synuclein revealed no significant effect of nAbs in comparison to IVIg treatment. However, all applied nAbs as well as IVIg show a minimal functionality on the microglial uptake of α-Synuclein. Conclusion nAbs-Aβ, nAbs-PrP possibly display comparable affinity to the same structural epitope within Aβ and PrP106-126 A117V whereas the epitope recognized by nAbs-α-Syn is only present in α-Syn. The structural similarity of Aβ and PrP fragment promotes the outline for an efficient antibody for the treatment of several neurodegenerative disorders and extend the functional characteristics of the investigated nAbs.
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Luštrek M, Lorenz P, Kreutzer M, Qian Z, Steinbeck F, Wu D, Born N, Ziems B, Hecker M, Blank M, Shoenfeld Y, Cao Z, Glocker MO, Li Y, Fuellen G, Thiesen HJ. Epitope predictions indicate the presence of two distinct types of epitope-antibody-reactivities determined by epitope profiling of intravenous immunoglobulins. PLoS One 2013; 8:e78605. [PMID: 24244326 PMCID: PMC3823795 DOI: 10.1371/journal.pone.0078605] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Accepted: 09/20/2013] [Indexed: 01/23/2023] Open
Abstract
Epitope-antibody-reactivities (EAR) of intravenous immunoglobulins (IVIGs) determined for 75,534 peptides by microarray analysis demonstrate that roughly 9% of peptides derived from 870 different human protein sequences react with antibodies present in IVIG. Computational prediction of linear B cell epitopes was conducted using machine learning with an ensemble of classifiers in combination with position weight matrix (PWM) analysis. Machine learning slightly outperformed PWM with area under the curve (AUC) of 0.884 vs. 0.849. Two different types of epitope-antibody recognition-modes (Type I EAR and Type II EAR) were found. Peptides of Type I EAR are high in tyrosine, tryptophan and phenylalanine, and low in asparagine, glutamine and glutamic acid residues, whereas for peptides of Type II EAR it is the other way around. Representative crystal structures present in the Protein Data Bank (PDB) of Type I EAR are PDB 1TZI and PDB 2DD8, while PDB 2FD6 and 2J4W are typical for Type II EAR. Type I EAR peptides share predicted propensities for being presented by MHC class I and class II complexes. The latter interaction possibly favors T cell-dependent antibody responses including IgG class switching. Peptides of Type II EAR are predicted not to be preferentially presented by MHC complexes, thus implying the involvement of T cell-independent IgG class switch mechanisms. The high extent of IgG immunoglobulin reactivity with human peptides implies that circulating IgG molecules are prone to bind to human protein/peptide structures under non-pathological, non-inflammatory conditions. A webserver for predicting EAR of peptide sequences is available at www.sysmed-immun.eu/EAR.
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Affiliation(s)
- Mitja Luštrek
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Universitätsmedizin, University of Rostock, Rostock, Germany
- Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia
| | - Peter Lorenz
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
| | - Michael Kreutzer
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
| | - Zilliang Qian
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
- Shanghai Institute for Biological Sciences, Shanghai, China
| | - Felix Steinbeck
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
| | - Di Wu
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
- Shanghai Institute for Biological Sciences, Shanghai, China
| | - Nadine Born
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
| | - Bjoern Ziems
- Gesellschaft für Individualisierte Medizin GmbH, Rostock, Germany
| | - Michael Hecker
- Steinbeis Transfer Center for Proteome Analysis, Rostock, Germany
| | - Miri Blank
- The Zabludovicz Center for Autoimmune Diseases, Sheba Medical Center, Ramat-Gan, Israel
| | - Yehuda Shoenfeld
- The Zabludovicz Center for Autoimmune Diseases, Sheba Medical Center, Ramat-Gan, Israel
| | - Zhiwei Cao
- School of Life Sciences and Technology, Tongji University, Shanghai, China
| | | | - Yixue Li
- Shanghai Institute for Biological Sciences, Shanghai, China
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Universitätsmedizin, University of Rostock, Rostock, Germany
| | - Hans-Jürgen Thiesen
- Institute of Immunology, Universitätsmedizin Rostock, University of Rostock, Rostock, Germany
- * E-mail:
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