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

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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.