蛋白质聚集的波动:神经退行性疾病早期诊断的临床前筛查设计

G. Costantini, Z. Budrikis, A. Taloni, Alexander K. Buell, S. Zapperi, C. Porta
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引用次数: 0

摘要

自催化纤维成核最近被认为是神经退行性疾病传播的一个决定性因素,但同样的过程也可以用于在诊断环境中扩增微量的蛋白质聚集体。微流体技术的最新进展允许分析微米级样品中的蛋白质聚集,可能使这种诊断方法成为可能,但迄今为止缺乏分析和解释这些数据的理论基础。在这里,我们通过计算研究了小体积蛋白质聚集的开始,并表明该过程受内在波动的支配,其体积相关分布我们也从理论上估计了。基于这些结果,我们开发了一种策略来量化与含有样本的聚合体检测相关的硅统计误差。我们的工作为预测无症状受试者的蛋白质聚集开辟了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fluctuations in protein aggregation: Design of preclinical screening for early diagnosis of neurodegenerative disease
Autocatalytic fibril nucleation has recently been proposed to be a determining factor for the spread of neurodegenerative diseases, but the same process could also be exploited to amplify minute quantities of protein aggregates in a diagnostic context. Recent advances in microfluidic technology allow analysis of protein aggregation in micron-scale samples potentially enabling such diagnostic approaches, but the theoretical foundations for the analysis and interpretation of such data are so far lacking. Here we study computationally the onset of protein aggregation in small volumes and show that the process is ruled by intrinsic fluctuations whose volume dependent distribution we also estimate theoretically. Based on these results, we develop a strategy to quantify in silico the statistical errors associated with the detection of aggregate containing samples. Our work opens a new perspective on the forecasting of protein aggregation in asymptomatic subjects.
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