The role of clearance mechanisms in the kinetics of pathological protein aggregation involved in neurodegenerative diseases.

The deposition of pathological protein aggregates in the brain plays a central role in cognitive decline and structural damage associated with neurodegenerative diseases. In Alzheimer's disease, the formation of amyloid-β plaques and neurofibrillary tangles of the tau protein is associated with the appearance of symptoms and pathology. Detailed models for the specific mechanisms of aggregate formation, such as nucleation and elongation, exist for aggregation in vitro where the total protein mass is conserved. However, in vivo, an additional class of mechanisms that clear pathological species is present and is believed to play an essential role in limiting the formation of aggregates and preventing or delaying the emergence of disease. A key unanswered question in the field of neuro-degeneration is how these clearance mechanisms can be modeled and how alterations in the processes of clearance or aggregation affect the stability of the system toward aggregation. Here, we generalize classical models of protein aggregation to take into account both production of monomers and the clearance of protein aggregates. We show that, depending on the specifics of the clearance process, a critical clearance value emerges above which accumulation of aggregates does not take place. Our results show that a sudden switch from a healthy to a disease state can be caused by small variations in the efficiency of the clearance process and provide a mathematical framework to explore the detailed effects of different mechanisms of clearance on the accumulation of aggregates

Kinetic profiling of therapeutic strategies for inhibiting the formation of amyloid oligomers

Protein self-assembly into amyloid fibrils underlies several neurodegenerative conditions, including Alzheimer's and Parkinson's diseases. It has become apparent that the small oligomers formed during this process constitute neurotoxic molecular species associated with amyloid aggregation. Targeting the formation of oligomers represents therefore a possible therapeutic avenue to combat these diseases. However, it remains challenging to establish which microscopic steps should be targeted to suppress most effectively the generation of oligomeric aggregates. Recently, we have developed a kinetic model of oligomer dynamics during amyloid aggregation. Here, we use this approach to derive explicit scaling relationships that reveal how key features of the time evolution of oligomers, including oligomer peak concentration and life-time, are controlled by the different rate parameters. We discuss the therapeutic implications of our framework by predicting changes in oligomer concentrations when the rates of the individual microscopic events are varied. Our results identify the kinetic parameters that control most effectively the generation of oligomers, thus opening the way for the systematic rational design of therapeutic strategies against amyloid-related diseases

Biomimetic peptide self-assembly for functional materials

Biomolecular systems have evolved to form a rich variety of supramolecular materials and machinery fundamental to cellular function. The assembly of these structures commonly involves interactions between specific molecular building blocks, a strategy that can also be replicated in an artificial setting to prepare functional materials. The self20 assembly of synthetic biomimetic peptides allows us to explore chemical and sequence space beyond that used routinely by biology. In this Review, we discuss recent conceptual and experimental advances in self-assembly of artificial peptidic materials. In particular, we explore how naturally-occurring structures and phenomena have inspired the development of functional biomimetic materials that we can harness for potential interactions with biological systems. As our fundamental understanding of peptide self-assembly evolves, increasingly sophisticated materials and applications emerge and lead to the development of a new set of building blocks and assembly principles relevant to materials science, molecular biology, nanotechnology and precision medicine

Identification and nanomechanical characterization of the fundamental single-strand protofilaments of amyloid α-synuclein fibrils.

The formation and spreading of amyloid aggregates from the presynaptic protein α-synuclein in the brain play central roles in the pathogenesis of Parkinson's disease. Here, we use high-resolution atomic force microscopy to investigate the early oligomerization events of α-synuclein with single monomer angstrom resolution. We identify, visualize, and characterize directly the smallest elementary unit in the hierarchical assembly of amyloid fibrils, termed here single-strand protofilaments. We show that protofilaments form from the direct molecular assembly of unfolded monomeric α-synuclein polypeptide chains. To unravel protofilaments' internal structure and elastic properties, we manipulated nanomechanically these species by atomic force spectroscopy. The single-molecule scale identification and characterization of the fundamental unit of amyloid assemblies provide insights into early events underlying their formation and shed light on opportunities for therapeutic intervention at the early stages of aberrant protein self-assembly

An Environmentally Sensitive Fluorescent Dye as a Multidimensional Probe of Amyloid Formation

We have explored amyloid formation using poly(amino acid) model systems in which differences in peptide secondary structure and hydrophobicity can be introduced in a controlled manner. We show that an environmentally sensitive fluorescent dye, dapoxyl, is able to identify β-sheet structure and hydrophobic surfaces, structural features likely to be related to toxicity, as a result of changes in its excitation and emission profiles and its relative quantum yield. These results show that dapoxyl is a multidimensional probe of the time dependence of amyloid aggregation, which provides information about the presence and nature of metastable aggregation intermediates that is inaccessible to the conventional probes that rely on changes in quantum yield alone.The authors acknowledge the European Research Council (ERC), Biotechnology and Biological Sciences Research Council (BBSRC), Wellcome Trust, and Winston Churchill Foundation for financial support

Particle-Based Monte-Carlo Simulations of Steady-State Mass Transport at Intermediate Péclet Numbers

Conventional approaches for simulating steady-state distributions of dilute particles under diffusive and advective transport involve solving the diffusion and advection equations in at least two dimensions. Here, we present an alternative computational strategy by combining a particle-based rather than a field-based approach with the initialisation of particles in proportion to their flux. This method allows accurate prediction of the steady state and is applicable even at intermediate and high Péclet numbers (Pe>1) swhere traditional particle-based Monte-Carlo methods starting from randomly initialised particle distributions fail. We demonstrate that generating a flux of particles according to a predetermined density and velocity distribution at a single fixed time and initial location allows for accurate simulation of mass transport under flow. Specifically, upon initialisation in proportion to their flux, these particles are propagated individually and detected by summing up their Monte-Carlo trajectories in predefined detection regions. We demonstrate quantitative agreement of the predicted concentration profiles with the results of experiments performed with fluorescent particles in microfluidic channels under continuous flow. This approach is computationally advantageous and readily allows non-trivial initial distributions to be considered. In particular, this method is highly suitable for simulating advective and diffusive transport in microfluidic devices, for instance in the context of diffusive sizing.Financial support from the Biotechnology and Biological Sciences Research Council (BBSRC), the European Research Council (ERC), the Frances and Augustus Newman Foundation as well as the Swiss National Science Foundation is gratefully acknowledged

Quantifying Measurement Fluctuations from Stochastic Surface Processes on Sensors with Heterogeneous Sensitivity

Recent advances in micro- and nanotechnology have enabled the development of ultrasensitive sensors capable of detecting small numbers of species. In general, however, the response induced by the random adsorption of a small number of objects onto the surface of such sensors results in significant fluctuations due to the heterogeneous sensitivity inherent to many such sensors coupled to statistical fluctuations in the particle number. At present, this issue is addressed by considering either the limit of very large numbers of analytes, where fluctuations vanish, or the converse limit, where the sensor response is governed by individual analytes. Many cases of practical interest, however, fall between these two limits and remain challenging to analyze. Here, we address this limitation by deriving a general theoretical framework for quantifying measurement variations on mechanical resonators resulting from statistical-number fluctuations of analyte species. Our results provide insights into the stochastic processes in the sensing environment and offer opportunities to improve the performance of mechanical-resonator-based sensors. This metric can be used, among others, to aid in the design of robust sensor platforms to reach ultrahigh-resolution measurements using an array of sensors. These concepts, illustrated here in the context of biosensing, are general and can therefore be adapted and extended to other sensors with heterogeneous sensitivity.We acknowledge funding from the W. D. Armstrong fund, Biotechnology and Biological Sciences Research Council, Newman Foundation, St. John’s College–University of Cambridge, and European Research Council.This is the author accepted manuscript. The final version is available from the American Physical Society via http://dx.doi.org/10.1103/PhysRevApplied.5.06401

Extrinsic Amyloid-Binding Dyes for Detection of Individual Protein Aggregates in Solution

Protein aggregation is a key molecular feature underlying a wide array of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. To understand protein aggregation in molecular detail, it is crucial to be able to characterize the array of heterogeneous aggregates that are formed during the aggregation process. We present here a high-throughput method to detect single protein aggregates, in solution, from a label-free aggregation reaction, and we demonstrate the approach with the protein associated with Parkinson's disease, α-synuclein. The method combines single-molecule confocal microscopy with a range of amyloid-binding extrinsic dyes, including thioflavin T and pentameric formylthiophene acetic acid, and we show that we can observe aggregates at low picomolar concentrations. The detection of individual aggregates allows us to quantify their numbers. Furthermore, we show that this approach also allows us to gain structural insights from the emission intensity of the extrinsic dyes that are bound to aggregates. By analyzing the time evolution of the aggregate populations on a single-molecule level, we then estimate the fragmentation rate of aggregates, a key process that underlies the multiplication of pathological aggregates. We additionally demonstrate that the method permits the detection of these aggregates in biological samples. The capability to detect individual protein aggregates in solution opens up a range of new applications, including exploiting the potential of this method for high-throughput screening of human biofluids for disease diagnosis and early detection

Amyloid formation: interface influence

The causes of pathological conditions such as Alzheimer’s and Parkinson’s diseases are becoming better understood. Proteins that misfold from their native structure to form aggregates of β-sheet fibrils — termed amyloid — are known1,2 to be implicated in these ‘amyloid diseases’. Understanding the early steps of fibril formation is critical, and the conditions, mechanism and kinetics of protein and peptide aggregation are being widely investigated through a variety of in vitro studies. Kinetic aspects of the dispersion of the protein or peptide in solution are thought to influence the fibrillization process by mass-transfer effects. In addition, mixing also leads to shear forces, which can influence fibril growth by perturbing the equilibrium between the isolated and aggregated proteins, causing existing fibrils to fragment and create new nuclei3. Writing in the Journal of the American Chemical Society, David Talaga and co-workers have now highlighted4 an additional factor that can influence the fibrillization of amyloid-forming proteins — the presence of hydrophobic interfaces

Autocatalytic amplification of Alzheimer-associated Aβ42 peptide aggregation in human cerebrospinal fluid

Alzheimer’s disease is linked to amyloid β (Aβ) peptide aggregation in the brain, and a detailed understanding of the molecular mechanism of Aβ aggregation may lead to improved diagnostics and therapeutics. While previous studies have been performed in pure buffer, we approach the mechanism in vivo using cerebrospinal fluid (CSF). We investigated the aggregation mechanism of Aβ42 in human CSF through kinetic experiments at several Aβ42 monomer concentrations (0.8–10 µM). The data were subjected to global kinetic analysis and found consistent with an aggregation mechanism involving secondary nucleation of monomers on the fibril surface. A mechanism only including primary nucleation was ruled out. We find that the aggregation process is composed of the same microscopic steps in CSF as in pure buffer, but the rate constant of secondary nucleation is decreased. Most importantly, the autocatalytic amplification of aggregate number through catalysis on the fibril surface is prevalent also in CSF