Atomic Force Microscopy in the Study of Protein Self-Assembly

原子力显微镜 脂质双层 生物物理学 蛋白质聚集 膜曲率 化学 淀粉样蛋白(真菌学) 生物膜 自组装 膜蛋白 显微镜 纳米技术 结晶学 材料科学 生物 生物化学 物理 光学 无机化学
作者
Natalia V. Kuzmina,Evgeniy V. Dubrovin,Olga Nikolaevna Koroleva,В. Л. Друца,Joshua Zimmerberg,Oleg V. Batishchev
出处
期刊:Biophysical Journal [Elsevier BV]
卷期号:118 (3): 200a-200a
标识
DOI:10.1016/j.bpj.2019.11.1203
摘要

Atomic force microscopy (AFM) is a high-resolution technique, allowing one to study native biological objects under non-destructive conditions. AFM is appropriate for investigating the morphology of biological objects at nanometer scales, to elucidate their physico-chemical properties, as well as to reveal conditions and characteristics of their self-assembly or interaction with other substances (e.g., lipid membranes). Amyloid aggregation, until recently, was associated with human diseases, such as diabetes and neurodegenerative Alzheimer's, Parkinson's, and Huntington's diseases. However, currently a growing number of scientists believe that any protein under certain conditions can self-assemble into highly-ordered amyloid forms, having a cross-β-structure. For example, in our group conditions were first found for the amyloid aggregation of the bacterial E. coli RNA polymerase sigma(70) subunit. Here we show the features of HIV-1 Gag protein scaffold self-assembly: the impact on this process of environmental pH, as well the influence of membrane curvature and the presence of certain lipids. We introduced a novel approach to investigate differential protein aggregate sorting based on sensing to membrane curvature by exploiting the ripple phase of supported lipid bilayers. This system allows creation of membrane surfaces with different curvature distributions. It is useful to test the propensity of relevant biological objects to adsorb to different curved regions at a broad range of temperatures. This work was supported by the Russian Foundation of Basic Research (grants #18-34-00623 – amyloid aggregation and #17-54-30022 – HIV-1 Gag self-assembly).
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