Funded Studies
Study Rationale: Parkinson’s disease (PD) is associated with an accumulation of alpha-synuclein aggregates in the brain; however, the current methods used to identify these aggregates in biological samples do not provide quantitative information. In contrast, nanopore sensors allow us to detect protein aggregates at the level of single molecules. We propose to design a novel analytical method for quantifying alpha-synuclein clusters based on nanopore technology. Using a tiny hollow device called a nanopipette and a small sample volume to enhance aggregation, we expect to be able to quantify alpha-synuclein at concentrations of fewer than 1000 copies per sample.
Hypothesis: We hypothesize that the use of a nanopipette will allow the detection of alpha-synuclein at an early stage of aggregation, that aggregation will be amplified by “seeding” the sample with pre-formed aggregates, and that aggregation is accelerated in a small volume.
Study Design: To begin, we will optimize and calibrate our nanopipettes to determine the best experimental conditions for characterizing the size and shape of protein aggregates. We will produce alpha-synuclein aggregates and investigate the dynamics of their movement through the nanopipette. Next, we will investigate the dynamics of alpha-synuclein aggregation in the presence of pre-formed aggregates as seeds. We will correlate the initial seed concentration to the speed and composition of aggregate formation. Finally, we will scale up our technique to allow seeding experiments to be conducted in parallel, which should improve the accuracy of our nanopipette sensor.
Impact on Diagnosis/Treatment of Parkinson’s disease: Our project aims to quantify alpha-synuclein aggregates in less than two hours with a detection limit of about 1000 aggregates per sample. We expect this approach can be used as a method for the early diagnosis of PD.
Next Steps for Development: The next steps will involve validating our technique to measure alpha-synuclein aggregates in cerebrospinal fluid and other biological fluids and developing a device that can be used in clinical diagnosis.