The phenomenon of protein aggregation and amyloid formation has become the subject of rapidly increasing research activities across a wide range of scientific disciplines. Such activities have been stimulated by the association of amyloid deposition with a range of debilitating medical disorders, from Alzheimer's disease to type II diabetes, many of which are major threats to human health and welfare in the modern world. It has become clear, however, that the ability to form the amyloid state is more general than previously imagined, and that its study can provide unique insights into the nature of the functional forms of peptides and proteins, as well as understanding the means by which protein homeostasis can be maintained and protein metastasis avoided.

The generation of toxic oligomers during the aggregation of the amyloid-β (Aβ) peptide Aβ42 into amyloid fibrils and plaques has emerged as a central feature of the onset and progression of Alzheimer's disease, but the molecular pathways that control pathological aggregation have proved challenging to identify. Here, we use a combination of kinetic studies, selective radiolabeling experiments, and cell viability assays to detect directly the rates of formation of both fibrils and oligomers and the resulting cytotoxic effects. Our results show that once a small but critical concentration of amyloid fibrils has accumulated, the toxic oligomeric species are predominantly formed from monomeric peptide molecules through a fibril-catalyzed secondary nucleation reaction, rather than through a classical mechanism of homogeneous primary nucleation. This catalytic mechanism couples together the growth of insoluble amyloid fibrils and the generation of diffusible oligomeric aggregates that are implicated as neurotoxic agents in Alzheimer's disease. These results reveal that the aggregation of Aβ42 is promoted by a positive feedback loop that originates from the interactions between the monomeric and fibrillar forms of this peptide. Our findings bring together the main molecular species implicated in the Aβ aggregation cascade and suggest that perturbation of the secondary nucleation pathway identified in this study could be an effective strategy to control the proliferation of neurotoxic Aβ42 oligomers.

We present an analytical treatment of a set of coupled kinetic equations that governs the self-assembly of filamentous molecular structures. Application to the case of protein aggregation demonstrates that the kinetics of amyloid growth can often be dominated by secondary rather than by primary nucleation events. Our results further reveal a range of general features of the growth kinetics of fragmenting filamentous structures, including the existence of generic scaling laws that provide mechanistic information in contexts ranging from in vitro amyloid growth to the in vivo development of mammalian prion diseases.

The intrinsically disordered protein alpha-synuclein plays a key role in the pathogenesis of Parkinson's disease (PD). We show here that the native state of alpha-synuclein consists of a broad distribution of conformers with an ensemble-averaged hydrodynamic radius significantly smaller than that expected for a random coil structure. This partial condensation is driven by interactions between the highly charged C-terminus and a large hydrophobic central region of the protein sequence. We suggest that this structure could inhibit the formation of alpha-synuclein aggregates, which are thought to be the cytotoxic species responsible for neurodegeneration in PD.

The elucidation of the molecular mechanisms by which soluble proteins convert into their amyloid forms is a fundamental prerequisite for understanding and controlling disorders that are linked to protein aggregation, such as Alzheimer's and Parkinson's diseases. However, because of the complexity associated with aggregation reaction networks, the analysis of kinetic data of protein aggregation to obtain the underlying mechanisms represents a complex task. Here we describe a framework, using quantitative kinetic assays and global fitting, to determine and to verify a molecular mechanism for aggregation reactions that is compatible with experimental kinetic data. We implement this approach in a web-based software, AmyloFit. Our procedure starts from the results of kinetic experiments that measure the concentration of aggregate mass as a function of time. We illustrate the approach with results from the aggregation of the β-amyloid (Aβ) peptides measured using thioflavin T, but the method is suitable for data from any similar kinetic experiment measuring the accumulation of aggregate mass as a function of time; the input data are in the form of a tab-separated text file. We also outline general experimental strategies and practical considerations for obtaining kinetic data of sufficient quality to draw detailed mechanistic conclusions, and the procedure starts with instructions for extensive data quality control. For the core part of the analysis, we provide an online platform (http://www.amylofit.ch.cam.ac.uk) that enables robust global analysis of kinetic data without the need for extensive programming or detailed mathematical knowledge. The software automates repetitive tasks and guides users through the key steps of kinetic analysis: determination of constraints to be placed on the aggregation mechanism based on the concentration dependence of the aggregation reaction, choosing from several fundamental models describing assembly into linear aggregates and fitting the chosen models using an advanced minimization algorithm to yield the reaction orders and rate constants. Finally, we outline how to use this approach to investigate which targets potential inhibitors of amyloid formation bind to and where in the reaction mechanism they act. The protocol, from processing data to determining mechanisms, can be completed in <1 d.