Selective Nanobrush Sensors (SNS) for Label-free Diagnosis of Neurodegenerative Disorders

阿尔茨海默氏症和帕金森氏症是主要的神经系统疾病，具有巨大的经济、社会和个人负担。迄今为止，没有实验室诊断测试可以在可观察到的临床表现之前识别这些神经系统疾病。与这些疾病相关的生物标志物和关键蛋白质正在出现，但现有的检测方法由于缺乏灵敏度和特异性以及临床样品中的低丰度而繁琐。有一个适应性强的技术，能够区分和监测生物标志物，产生一个根本性的转变，在诊断，并使更好地理解有巨大的需求。在这两种疾病中，小可溶性蛋白质聚集体，如淀粉样蛋白β或α突触核蛋白已被确定为药物和诊断开发的重要目标。然而，这些小聚集体的检测非常具有挑战性，因为它们可能具有不均匀的大小，超低浓度（皮摩尔），并且仅占临床样品中总浓度的一小部分（低于1%）。该项目将物理科学，生命科学和纳米医学结合起来，旨在开发具有强大，可调和选择性识别化学的无标记单分子传感器，以克服这些限制。这将通过使用我们称之为“智能纳米刷传感器”（SNS）来实现，该传感器基于用适体纳米刷（合成的短单链核酸特异性结合目标分析物）功能化的纳米孔和一种新的电子检测模式。我们的目标是专注于提供一种技术来区分，无标记，淀粉样蛋白β或α突触核蛋白寡聚体亚群及其在复杂介质中的浓度，并最终从AD和PD患者获得的脑脊液样本，这些新型传感器将填补广泛的技术空白，目前阻碍了临床样本中小蛋白及其聚集体的生物标志物分析。它将能够准确区分分析物群体及其大小、形状和浓度。所开发的技术可以提供识别疾病标志物的变革性方法，并可以为广泛的技术铺平道路，不仅可以研究神经退行性疾病的发病机制，还可以研究由蛋白质错误折叠和聚集引起的疾病（例如与p53聚集相关的癌症）。我们设想传感器设计从化学实验室逐步发展到能够监测早期预后和疾病进展的分子变化的体外生物标志物诊断。

Alzheimer's, and Parkinson's are major neurological diseases, with a large economic, societal and personal burden. To date, there is no laboratory diagnostic test that can identify these neurological disorders ahead of observable clinical manifestations. There are emerging biomarkers and key proteins linked to these diseases, but existing detection methods are cumbersome due to lack of sensitivity and specificity, and low-abundance in clinical samples. There is an enormous need for adaptable technology capable of discriminating and monitoring biomarkers, to generate a fundamental transformation in diagnostics, and enabling a better understanding.In both diseases, small soluble protein aggregates such as amyloid beta or alpha synuclein have been identified as important targets for the development of drugs and diagnostics. These small aggregates, however, are exceptionally challenging to detect as they can have heterogeneous sizes, ultra-low concentrations (picomolar) and comprise only a small fraction (lower than 1%) of the total concentration in a clinical sample. This project unites physical sciences, life sciences, and nanomedicine with the aim of developing label-free single-molecule sensors with robust, tuneable and selective recognition chemistry that overcome these limitations. This will be achieved by using what we dub a "smart nanobrush sensor" (SNS), based on nanopores functionalised with aptamer nanobrushes (short single-stranded nucleic acids synthesised specifically bind the target analytes) and a novel mode of electronic detection. Our aims are to focus on delivering a technology to discriminate, label-free, amyloid beta or alpha synuclein oligomer subpopulations and their concentrations in complex media, and ultimately, cerebrospinal fluid samples obtained from AD and PD patients.These novel sensors will close a wide technological gap that is currently holding back the biomarker analysis of small proteins and their aggregates in clinical samples. It will enable accurate discrimination of analyte populations, as well as their size, shape and concentration. The developed technology can provide transformative methods to identify disease markers and can pave the way for a broad range of techniques to study pathogenesis not only in neurodegenerative diseases, but also in diseases caused by protein misfolding and aggregation (e.g. cancers linked to p53 aggregation). We envisage a stepwise progression in sensor design from the chemical laboratory, to in vitro biomarker diagnostics capable of monitoring molecular changes for early stage prognosis and disease progression.