Liquid Crystal Enabled Early Stage Detection of Beta Amyloid Formation on Lipid Monolayers
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Liquid crystals (LCs) can serve as sensitive reporters of interfacial events, and this property has been used for sensing of synthetic or biological toxins. Here it is demonstrated that LCs can distinguish distinct molecular motifs and exhibit a specific response to beta-sheet structures. That property is used to detect the formation of highly toxic protofibrils involved in neurodegenerative diseases, where it is crucial to develop methods that probe the early-stage aggregation of amyloidogenic peptides in the vicinity of biological membranes. In the proposed method, the amyloid fibrils formed at the lipid-decorated LC interface can change the orientation of LCs and form elongated and branched structures that are amplified by the mesogenic medium; however, nonamyloidogenic peptides form ellipsoidal domains of tilted LCs. Moreover, a theoretical and computational analysis is used to reveal the underlying structure of the LC, thereby providing a detailed molecular-level view of the interactions and mechanisms responsible for such motifs. The corresponding signatures can be detected at nanomolar concentrations of peptide by polarized light microscopy and much earlier than the ones that can be identified by fluorescence-based techniques. As such, it offers the potential for early diagnoses of neurodegenerative diseases and for facile testing of inhibitors of amyloid formation. Liquid-crystal-based sensors exhibit unique responses to peptides that aggregate at membrane interfaces. β-sheet forming peptides, such as human islet amyloid polypeptide, aggregate into fibrils at lipid-decorated liquid crystal interfaces, giving rise to branch-like structures. By contrast, rat islet amyloid polypeptide molecules, which possess α-helical character, exhibit weak protein-lipid interactions and form circular domains. © 2015 WILEY-VCH Verlag GmbH %26 Co. KGaA, Weinheim.
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Liquid crystals (LCs) can serve as sensitive reporters of interfacial events, and this property has been used for sensing of synthetic or biological toxins. Here it is demonstrated that LCs can distinguish distinct molecular motifs and exhibit a specific response to beta-sheet structures. That property is used to detect the formation of highly toxic protofibrils involved in neurodegenerative diseases, where it is crucial to develop methods that probe the early-stage aggregation of amyloidogenic peptides in the vicinity of biological membranes. In the proposed method, the amyloid fibrils formed at the lipid-decorated LC interface can change the orientation of LCs and form elongated and branched structures that are amplified by the mesogenic medium; however, nonamyloidogenic peptides form ellipsoidal domains of tilted LCs. Moreover, a theoretical and computational analysis is used to reveal the underlying structure of the LC, thereby providing a detailed molecular-level view of the interactions and mechanisms responsible for such motifs. The corresponding signatures can be detected at nanomolar concentrations of peptide by polarized light microscopy and much earlier than the ones that can be identified by fluorescence-based techniques. As such, it offers the potential for early diagnoses of neurodegenerative diseases and for facile testing of inhibitors of amyloid formation. Liquid-crystal-based sensors exhibit unique responses to peptides that aggregate at membrane interfaces. β-sheet forming peptides, such as human islet amyloid polypeptide, aggregate into fibrils at lipid-decorated liquid crystal interfaces, giving rise to branch-like structures. By contrast, rat islet amyloid polypeptide molecules, which possess α-helical character, exhibit weak protein-lipid interactions and form circular domains. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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beta amyloid; early stage detection; liquid crystals; neurodegenerative diseases; sensors Biological membranes; Cytology; Diagnosis; Glycoproteins; Liquid crystals; Liquids; Peptides; Proteins; Sensors; Amyloid formation; Amyloidogenic peptides; Beta amyloids; Biological toxins; Branched structures; Computational analysis; Liquid crystals (LCs); Nanomolar concentration; Neurodegenerative diseases
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