A multi-scale data-driven model of the Abeta pore function and Ca2+ toxicity in Alzheimer's disease

阿尔茨海默病(AD)是一种慢性神经退行性疾病，会导致广泛的认知功能进行性恶化，最终导致死亡。三种淀粉样β蛋白(Aβ)多肽Aβ40、Aβ42和Aβ43被认为是AD发病的关键因素。最近的研究结果表明，A-β寡聚体在细胞外和细胞内的聚集而不是大的不溶性聚集体是可能的致病因素，它们的毒性是通过在质膜(PM)形成有毒的钙通透孔而导致胞内钙离子不受控制的升高来调节的。然而，关于不同Aβ孔类型的功能以及PM的哪一小叶更容易形成孔的详细信息尚不清楚。这些孔在其功能特性上表现出显著的多样性和随时间的变化。此外，由于这三种多肽导致的毛孔之间的药理比较缺乏。Aβ毛孔的高度异质性和动态性对通过传统的单通道方法研究其致病机制提出了极大的挑战。我们的目标是利用多尺度数据驱动的建模和具有单通道水平分辨率的先进成像技术来填补AD中β介导的钙信号中断的理解中的关键空白。使用我们的光学膜片钳技术，我们将监测和比较成百上千个由胞外和胞内Aβ寡聚体形成的Aβ孔的门控特性和随时间的演化。我们将测量和比较三种Aβ孔类型的电导特性、门控动力学和随时间的演变。我们建议在相同条件下对Aβ40、Aβ42和Aβ43孔进行平行实验，以：(1)阐明和比较它们在包括锌、铝和铜在内的各种调节剂存在下的功能，(2)比较Aβ孔阻滞剂如Na7和贝沙罗汀的作用，(3)包括姜黄素、油菜素和白藜芦醇在内的天然酚如何影响它们的形成和进化，以及(4)包括胆固醇和磷脂酰丝氨酸在内的膜成分的变化如何影响Aβ孔的功能。在实验数据的逐步推动下，我们将为每种孔类型的不同变体(基于峰值渗透率)开发特定的模型，然后将这些模型结合到一个统一的模型中，该模型包含每种Aβ孔类型的快速(毫秒)门控动力学和缓慢(数十分钟和数小时)演变。我们将把调节器和PM组件的作用融入到每个模型中，并测试不同调节器的同时存在如何影响不同细胞膜中β孔的行为？我们将使用这些模型进行长时间的模拟(数小时或数天)，以更好地了解毛孔是如何演变的，以及当它们被插入PM和不同细胞内细胞器(包括内质网、线粒体和溶酶体)的膜中时，它们是如何随时间、空间排列、运动性和Aβ40、Aβ42和Aβ43的比率而对整体钙毒性做出贡献的。

Alzheimer's disease (AD) is a chronic neurodegenerative disorder that leads to progressive deterioration in a broad range of cognitive functions and finally death. Three amyloid beta (Aβ) peptides, Aβ40, Aβ42, and Aβ43 have been implicated as a key factors in the pathogenesis of AD. Recent findings indicate that extra- and intracellular accumulations of oligomeric forms of Aβ rather than large insoluble aggregates are the likely pathological culprits, and that their toxicity is mediated through uncontrolled elevation of cytosolic Ca2+ by formation of toxic Ca2+-permeable pores in the plasma membrane (PM). Yet, detailed information about the function of different Aβ pore types and which leaflet of the PM is more susceptible to pore formation are lacking. These pores have shown significant diversity and time dependent changes in their functional properties. Moreover, pharmacological comparisons between pores due to the three types of peptides are lacking. The highly heterogeneous and dynamic nature of Aβ pores poses extreme challenges in investigating their pathogenic mechanisms through traditional single channel approaches. Our goal is to fill a critical void in the understanding of Aβ-mediated Ca2+ signaling disruptions in AD using multi-scale data-driven modeling in conjunction with advanced imaging techniques having a resolution down to single channel level. Using our optical patch clamp technique, we will monitor and compare the gating properties and time- dependent evolution of hundreds of Aβ pores formed by extra- and intracellular Aβ oligomers. We will measure and compare the conductance properties, gating kinetics, and time-dependent evolution of the three Aβ pore types. We propose to perform parallel experiments on Aβ40, Aβ42, and Aβ43 pores in identical conditions to: (1) elucidate and compare their function in the presence of various modulators including Zinc, Aluminum, and Copper, (2) compare the effects of Aβ pore blockers such as NA7 and Bexarotene, (3) how natural phenols including Curcumin, Oleuropein, and Resveratrol affect their formation and evolution, and (4) how changes in membrane components including cholesterol and phosphatidylserine affect the function of Aβ pores. Driven progressively by experimental data, we will develop specific models for different variants (based on peak permeability) of each pore type, followed by combining these models into a unified model encompassing both the fast (milliseconds) gating kinetics and slow (tens of minutes and hours) evolution of each Aβ pore type. We will incorporate the effect of modulators and PM components into each model and test how the concurrent presence of different modulators affect Aβ pores' behavior in different cell membranes? We will use these models to perform long simulations (many hours or days) to better understand how pores evolve and how they contribute to overall Ca2+ toxicity as a function of time, spatial arrangement, motility, and ratio of Aβ40, Aβ42, and Aβ43 when inserted into PM and membranes of different intracellular organelles including ER, mitochondria, and lysosomes.