Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/168768
Title: A nanobar-supported lipid bilayer system for the study of membrane curvature sensing proteins in vitro
Authors: Miao, Xinwen
Wu, Jiawei
Zhao, Wenting
Keywords: Science::Chemistry
Issue Date: 2022
Source: Miao, X., Wu, J. & Zhao, W. (2022). A nanobar-supported lipid bilayer system for the study of membrane curvature sensing proteins in vitro. Journal of Visualized Experiments (JoVE), November 2022(189), e64340-. https://dx.doi.org/10.3791/64340
Project: RG112/20 
RG95/21 
MOE-T2EP30220-0009 
NTU-SUG 
Journal: Journal of Visualized Experiments (JoVE) 
Abstract: Membrane curvature plays important roles in various essential processes of cells, such as cell migration, cell division, and vesicle trafficking. It is not only passively generated by cellular activities, but also actively regulates protein interactions and is involved in many intracellular signaling. Thus, it is of great value to examine the role of membrane curvature in regulating the distribution and dynamics of proteins and lipids. Recently, many techniques have been developed to study the relationship between the curved membrane and protein in vitro. Compared to traditional techniques, the newly developed nanobar-supported lipid bilayer (SLB) offers both high-throughput and better accuracy in membrane curvature generation by forming a continuous lipid bilayer on patterned arrays of nanobars with a pre-defined membrane curvature and local flat control. Both the lipid fluidity and protein sensitivity to curved membranes can be quantitatively characterized using fluorescence microscopy imaging. Here, a detailed procedure on how to form a SLB on fabricated glass surfaces containing nanobar arrays and the characterization of curvature-sensitive proteins on such SLB are introduced. In addition, protocols for nanochip reusing and image processing are covered. Beyond the nanobar-SLB, this protocol is readily applicable to all types of nanostructured glass chips for curvature sensing studies.
URI: https://hdl.handle.net/10356/168768
ISSN: 1940-087X
DOI: 10.3791/64340
Schools: School of Chemistry, Chemical Engineering and Biotechnology 
Research Centres: Institute for Digital Molecular Analytics and Science
Rights: © 2022 JoVE Journal of Visualized Experiments. All rights reserved. This paper was published in Journal of Visualized Experiments (JoVE) and is made available with permission of JoVE Journal of Visualized Experiments.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CCEB Journal Articles

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