Details

Autor(en) / Beteiligte

• Wu, Rongrong
• Wang, Zengkai
• Jia, Zili
• Li, Chenglong
• Wang, Jie
• Liu, Lei
• Dong, Mingdong

Titel

Identification of hybrid amyloid strains assembled from amyloid-β and human islet amyloid polypeptide

Ist Teil von

• Nanotechnology, 2023-12, Vol.34 (50), p.505101

Ort / Verlag

IOP Publishing

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Abstract Cross-fibrillation of amyloid- β (A β ) peptides and human islet amyloid polypeptides (hIAPP) has revealed a close correlation between Alzheimer’s disease and type 2 diabetes (T2D). Importantly, different amyloid strains are likely to lead to the clinical pathological heterogeneity of degenerative diseases due to toxicity. However, given the complicated cross-interactions between different amyloid peptides, it is still challenging to identify the polymorphism of the hybrid amyloid strains and reveal mechanistic insights into aggregation, but highly anticipated due to their significance. In this study, we investigated the cross-fibrillation of A β peptides and different hIAPP species (monomers, oligomers, and fibrils) using combined experimental and simulation approaches. Cross-seeding and propagation of different amyloid peptides monitored by experimental techniques proved that the three species of hIAPP aggregates have successively enhanced A β fibrillation, especially for hIAPP fibrils. Moreover, the polymorphism of these morphologically similar hybrid amyloid strains could be distinguished by testing their mechanical properties using quantitative nanomechanical mapping, where the assemblies of A β -hIAPP fibrils exhibited the high Young’s modulus. Furthermore, the enhanced internal molecular interactions and β -sheet structural transformation were proved by exploring the conformational ensembles of A β -hIAPP heterodimer and A β -hIAPP decamer using molecular dynamic simulations. Our findings pave the way for identifying different hybrid amyloid strains by quantitative nanomechanical mapping and molecular dynamic simulations, which is important not only for the precise classification of neurodegenerative disease subtypes but also for future molecular diagnosis and therapeutic treatment of multiple interrelated degenerative diseases.