Single-molecule mass photometry to probe the competition between protein aggregation and native folding

蛋白质折叠成正确功能所需的复杂结构。这些结构涉及沮丧的互动，不能总是得到满足，允许替代结构，导致功能障碍的形成。事实上，许多疾病都与这种错误折叠蛋白质的聚集有关。了解聚集如何与天然折叠竞争将产生关键的见解折叠是如何出错的，并改进设计新蛋白质的原则。我们将使用干涉光散射来测量溶液中单个蛋白质的质量来探测聚集。因为这种方法对单分子敏感，它可以监测聚集的最早步骤--覆盖聚集级联的所有阶段的异质混合物中的小寡聚体;因为它是无标记的，聚集可以被探测，而不会受到通常用于检测的荧光染料的任何偏倚。我们将使用单分子（SM）质量光度法来区分不同大小的低聚物（二聚体，三聚体，）和目录的形成/增长率，第一次获得一个公正的，定量测量的每一个国家的聚集级联比较的物理模型。我们将探讨两个具体目标：**1。当条件改变时，蛋白质如何从天然转变为聚合。我们将以tau蛋白为例：它通常有助于稳定神经元中的微管，但在阿尔茨海默病和其他痴呆症中会发生聚集。我们将比较正常和患病条件下低聚物的形成/生长速率，拟合微观模型以推断驱动行为变化的机制。2.进化如何塑造自然折叠和聚集之间的竞争。进化被认为是选择平滑的能量景观，允许快速形成最小挫折的结构。为了研究这个问题，我们将（A）比较来自不同进化时期的祖先蛋白质的聚集，重点是PrP，一种聚集引起疾病的蛋白质，我们已经重建了大约3.5亿年前的序列;和（B）测量通过计算设计的蛋白质的聚集，它们没有经历进化选择，并且经常倾向于聚集，即使从头设计越来越可靠。在每种情况下，我们将比较通过SM质量光度法测量的低聚物的形成/生长速率与我们使用SM力光谱测量的天然折叠的性质，如稳定性，势垒高度和景观粗糙度，以确定与聚集倾向差异相关的折叠中的物理变化。这样的研究与SM的灵敏度，不可能，直到最近的SM质量光度法的发展，提出了一个及时的和特殊的机会，取得重大进展，几十年的问题与生物学，物理学，化学和医学。如果没有这些仪器，我们将无法追求如此令人兴奋的科学。

Proteins fold into complex structures that are required for correct function. These structures involve frustrated' interactions that can't always be satisfied, allowing alternative structures that cause dysfunction to form. Indeed, many diseases are linked to aggregates of such misfolded proteins. Understanding how aggregation competes with native folding will yield key insights into how folding goes wrong and improved principles for designing new proteins. We will probe aggregation using interferometric light scattering to measure the mass of single proteins in solution. Because this method is sensitive to single molecules, it can monitor the earliest steps of aggregationsmall oligomerswithin a heterogeneous mixture covering all stages of the aggregation cascade; because it is label-free, aggregation can be probed without any bias from the fluorescent dyes normally used for detection. We will use single-molecule (SM) mass photometry to distinguish oligomers of different size (dimer, trimer,) and catalog their formation/growth rates, obtaining for the first time an unbiased, quantitative measure of each state in the aggregation cascade for comparison to physical models. We will probe 2 specific aims:***1. How proteins switch from native to aggregated when conditions change. We will focus on the tau protein as an example: it normally helps stabilize microtubules in neurons, but switches to aggregate in Alzheimer's disease and other dementias. We will compare the formation/growth rates of oligomers under normal and diseased conditions, fitting to microscopic models to deduce the mechanism driving the change in behaviour.***2. How evolution shapes the competition between native folding and aggregation. Evolution is thought to select for smooth energy landscapes that allow rapid formation of minimally frustrated structures. To study this question, we will (A) compare aggregation of ancestral proteins from different evolutionary periods, focusing on PrP, a protein that aggregates to cause disease and whose sequence we have reconstructed back to ~350 million years ago; and (B) measure aggregation of proteins designed computationally, which have not undergone evolutionary selection and are often prone to aggregation even though de novo design is increasingly reliable. In each case, we will compare the formation/growth rate of oligomers measured by SM mass photometry to properties of the native folding like stability, barrier height, and landscape roughness that we are measure using SM force spectroscopy, to identify the physical changes in the folding related to differences in aggregation-propensity.***Such studies of aggregation with SM sensitivity, not possible until the recent development of SM mass photometry, present a timely and exceptional opportunity to make significant advances in a decades-old problem with relevance to biology, physics, chemistry, and medicine. Without this instrumentation, we will not be able to pursue such exciting science.