Department of Chemistry, Faculty of Science, University of Copenhagen, Frederiksberg C, 1871, Denmark.
Department of Physics and Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Commun Biol. 2022 Aug 20;5(1):850. doi: 10.1038/s42003-022-03810-1.
Protein misfolding in the form of fibrils or spherulites is involved in a spectrum of pathological abnormalities. Our current understanding of protein aggregation mechanisms has primarily relied on the use of spectrometric methods to determine the average growth rates and diffraction-limited microscopes with low temporal resolution to observe the large-scale morphologies of intermediates. We developed a REal-time kinetics via binding and Photobleaching LOcalization Microscopy (REPLOM) super-resolution method to directly observe and quantify the existence and abundance of diverse aggregate morphologies of human insulin, below the diffraction limit and extract their heterogeneous growth kinetics. Our results revealed that even the growth of microscopically identical aggregates, e.g., amyloid spherulites, may follow distinct pathways. Specifically, spherulites do not exclusively grow isotropically but, surprisingly, may also grow anisotropically, following similar pathways as reported for minerals and polymers. Combining our technique with machine learning approaches, we associated growth rates to specific morphological transitions and provided energy barriers and the energy landscape at the level of single aggregate morphology. Our unifying framework for the detection and analysis of spherulite growth can be extended to other self-assembled systems characterized by a high degree of heterogeneity, disentangling the broad spectrum of diverse morphologies at the single-molecule level.
蛋白质以纤维或球晶的形式错误折叠与一系列病理异常有关。我们对蛋白质聚集机制的现有理解主要依赖于使用光谱方法来确定平均增长率和具有低时间分辨率的衍射受限显微镜来观察中间体的大尺度形态。我们开发了一种通过结合和光漂白定位显微镜(REPLOM)超分辨率方法的实时动力学(REal-time kinetics via binding and Photobleaching LOcalization Microscopy,REPLOM),以直接观察和量化人胰岛素的各种聚集体形态的存在和丰度,这些形态低于衍射极限,并提取它们的异质生长动力学。我们的结果表明,即使是微观上相同的聚集体(例如淀粉样纤维球)的生长也可能遵循不同的途径。具体来说,球晶不仅可以各向同性地生长,而且令人惊讶的是,还可以各向异性地生长,遵循与矿物质和聚合物报道的类似途径。我们将这项技术与机器学习方法相结合,将生长速率与特定的形态转变相关联,并提供了单个聚集体形态水平的能量障碍和能量景观。我们用于检测和分析球晶生长的统一框架可以扩展到其他具有高度异质性的自组装系统,在单分子水平上解析出广泛的不同形态。