Single‐Molecule Counting Coupled to Rapid Amplification Enables Detection of α‐Synuclein Aggregates in Cerebrospinal Fluid of Parkinson's Disease Patients

Intelligent Identification of Cerebrospinal Fluid for the Diagnosis of Parkinson's Disease

Cerebrospinal fluid (CSF) biomarkers are more sensitive than the Movement Disorder Society (MDS) criteria for detecting prodromal Parkinson's disease (PD). Early detection of PD provides the best chance for successful implementation of disease-modifying treatments, making it crucial to effectively identify CSF extracted from PD patients or normal individuals. In this study, an intelligent sensor array was built by using three metal-organic frameworks (MOFs) that exhibited varying catalytic kinetics after reacting with potential protein markers. Machine learning algorithms were used to process fingerprint response patterns, allowing for qualitative and quantitative assessment of the proteins. The results were robust and capable of discriminating between PD and non-PD patients via CSF detection. The k-nearest neighbor regression algorithm was used to predict MDS scores with a minimum mean square error of 38.88. The intelligent MOF sensor array is expected to promote the detection of CSF biomarkers due to its ability to identify multiple targets and could be used in conjunction with MDS criteria and other techniques to diagnose PD more sensitively and selectively.

Single-Molecule Two-Color Coincidence Detection of Unlabeled alpha-Synuclein Aggregates

Protein misfolding and aggregation into oligomeric and fibrillar structures is a common feature of many neurogenerative disorders. Single-molecule techniques have enabled characterization of these lowly abundant, highly heterogeneous protein aggregates, previously inaccessible using ensemble averaging techniques. However, they usually rely on the use of recombinantly-expressed labeled protein, or on the addition of amyloid stains that are not protein-specific. To circumvent these challenges, we have made use of a high affinity antibody labeled with orthogonal fluorophores combined with fast-flow microfluidics and single-molecule confocal microscopy to specifically detect α-synuclein, the protein associated with Parkinson's disease. We used this approach to determine the number and size of α-synuclein aggregates down to picomolar concentrations in biologically relevant samples.

Single-Molecule Two-Color Coincidence Detection of Unlabeled alpha-Synuclein Aggregates

Protein misfolding and aggregation into oligomeric and fibrillar structures is a common feature of many neurogenerative disorders. Single-molecule techniques have enabled characterization of these lowly abundant, highly heterogeneous protein aggregates, previously inaccessible using ensemble averaging techniques. However, they usually rely on the use of recombinantly-expressed labeled protein, or on the addition of amyloid stains that are not protein-specific. To circumvent these challenges, we have made use of a high affinity antibody labeled with orthogonal fluorophores combined with fast-flow microfluidics and single-molecule confocal microscopy to specifically detect α-synuclein, the protein associated with Parkinson's disease. We used this approach to determine the number and size of α-synuclein aggregates down to picomolar concentrations in biologically relevant samples.

Hippocampal Reduction of α-Synuclein via RNA Interference Improves Neuropathology in Alzheimer's Disease Mice

BACKGROUND

Alzheimer's disease (AD) cases are often characterized by the pathological accumulation of α-synuclein (α-syn) in addition to amyloid-β (Aβ) and tau hallmarks. The role of α-syn has been extensively studied in synucleinopathy disorders, but less so in AD. Recent studies have shown that α-syn may also play a role in AD and its downregulation may be protective against the toxic effects of Aβ accumulation.

OBJECTIVE

We hypothesized that selectively knocking down α-syn via RNA interference improves the neuropathological and biochemical findings in AD mice.

METHODS

Here we used amyloid precursor protein transgenic (APP-Tg) mice to model AD and explore pathologic and behavioral phenotypes with knockdown of α-syn using RNA interference. We selectively reduced α-syn levels by stereotaxic bilateral injection of either LV-shRNA α-syn or LV-shRNA-luc (control) into the hippocampus of AD mice.

RESULTS

We found that downregulation of α-syn results in significant reduction in the number of Aβ plaques. In addition, mice treated with LV-shRNA α-syn had amelioration of abnormal microglial activation (Iba1) and astrocytosis (GFAP) phenotypes in AD mice.

CONCLUSION

Our data suggests a novel link between Aβ and α-syn pathology as well as a new therapeutic angle for targeting AD.

Single Molecule Fingerprinting Reveals Different Amplification Properties of α-Synuclein Oligomers and Preformed Fibrils in Seeding Assay

The quantification of α-synuclein aggregates has emerged as a promising biomarker for synucleinopathies. Assays that amplify and detect such aggregates have revealed the presence of seeding-competent species in biosamples of patients diagnosed with Parkinson's disease. However, multiple species, such as oligomers and amyloid fibrils, are formed during the aggregation of α-synuclein; these species are likely to coexist in biological samples, and thus it remains unclear which species(s) are contributing to the signal detected in seeding assays. To identify individual contributions to the amplification process, recombinant oligomers and preformed fibrils were produced and purified to characterize their individual biochemical and seeding potential. Here, we used single molecule spectroscopy to track the formation and purification of oligomers and fibrils at the single particle level and compare their respective seeding potential in an amplification assay. Single molecule detection validates that size-exclusion chromatography efficiently separates oligomers from fibrils. Oligomers were found to be seeding-competent, but our results reveal that their seeding behavior is very different compared to that of preformed fibrils, in our amplification assay. Overall, our data suggest that even a low number of preformed fibrils present in biosamples is likely to dominate the response in seeding assays.