Derrick Lau, Yuan Tang, Vijaya Kenche, Thomas Copie, Daryan Kempe, Eve Jary, Noah J Graves, Maté Biro, Colin L Masters, Nicolas Dzamko, Yann Gambin, Emma Sierecki
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引用次数: 0
Abstract
α-Synuclein (αSyn) aggregates, detected in the biofluids of patients with Parkinson's disease (PD), have the ability to catalyze their own aggregation, leading to an increase in the number and size of aggregates. This self-templated amplification is used by newly developed assays to diagnose Parkinson's disease and turns the presence of αSyn aggregates into a biomarker of the disease. It has become evident that αSyn can form fibrils with slightly different structures, called "strains" or polymorphs, but little is known about their differential reactivity in diagnostic assays. Here, we compared the properties of two well-described αSyn polymorphs. Using single-molecule techniques, we observed that one of the polymorphs had an increased tendency to undergo secondary nucleation and we showed that this could explain the differences in reactivity observed in in vitro seed amplification assay and cellular assays. Simulations and high-resolution microscopy suggest that a 100-fold difference in the apparent rate of growth can be generated by a surprisingly low number of secondary nucleation "points" (1 every 2000 monomers added by elongation). When both strains are present in the same seeded reaction, secondary nucleation displaces proportions dramatically and causes a single strain to dominate the reaction as the major end product.
期刊介绍:
ACS Chemical Neuroscience publishes high-quality research articles and reviews that showcase chemical, quantitative biological, biophysical and bioengineering approaches to the understanding of the nervous system and to the development of new treatments for neurological disorders. Research in the journal focuses on aspects of chemical neurobiology and bio-neurochemistry such as the following:
Neurotransmitters and receptors
Neuropharmaceuticals and therapeutics
Neural development—Plasticity, and degeneration
Chemical, physical, and computational methods in neuroscience
Neuronal diseases—basis, detection, and treatment
Mechanism of aging, learning, memory and behavior
Pain and sensory processing
Neurotoxins
Neuroscience-inspired bioengineering
Development of methods in chemical neurobiology
Neuroimaging agents and technologies
Animal models for central nervous system diseases
Behavioral research