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.

原纤维或球晶形式的蛋白质错误折叠涉及一系列病理异常。我们目前对蛋白质聚集机制的理解主要依赖于使用光谱方法来确定平均生长速率和使用具有低时间分辨率的衍射极限显微镜来观察中间体的大规模形态。我们通过结合和光漂白定位显微镜 (REPLOM) 超分辨率方法开发了一种实时动力学，以直接观察和量化人胰岛素的不同聚集形态的存在和丰度，低于衍射极限并提取它们的异质生长动力学。我们的研究结果表明，即使是显微镜下相同的聚集体（例如淀粉样蛋白球晶）的生长也可能遵循不同的途径。具体来说，球晶并不完全是各向同性生长的，但令人惊讶的是，它们也可能是各向异性生长，遵循与矿物和聚合物报道的类似途径。将我们的技术与机器学习方法相结合，我们将增长率与特定的形态转变联系起来，并在单一聚合形态水平上提供了能量屏障和能量景观。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以高度异质性为特征的自组装系统，在单分子水平上解开广泛的不同形态。将我们的技术与机器学习方法相结合，我们将增长率与特定的形态转变联系起来，并在单一聚合形态水平上提供了能量屏障和能量景观。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以高度异质性为特征的自组装系统，在单分子水平上解开广泛的不同形态。将我们的技术与机器学习方法相结合，我们将增长率与特定的形态转变联系起来，并在单一聚合形态水平上提供了能量屏障和能量景观。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以高度异质性为特征的自组装系统，在单分子水平上解开广泛的不同形态。