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

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

Dynamics of oligomer populations formed during the aggregation of Alzheimer's Aβ42 peptide

Oligomeric species populated during the aggregation of the Aβ42 peptide have been identified as potent cytotoxins linked to Alzheimer’s disease, but the fundamental molecular pathways that control their dynamics have yet to be elucidated. By developing a general approach that combines theory, experiment and simulation, we reveal, in molecular detail, the mechanisms of Aβ42 oligomer dynamics during amyloid fibril formation. Even though all mature amyloid fibrils must originate as oligomers, we found that most Aβ42 oligomers dissociate into their monomeric precursors without forming new fibrils. Only a minority of oligomers converts into fibrillar structures. Moreover, the heterogeneous ensemble of oligomeric species interconverts on timescales comparable to those of aggregation. Our results identify fundamentally new steps that could be targeted by therapeutic interventions designed to combat protein misfolding diseases

Distinct thermodynamic signatures of oligomer generation in the aggregation of the amyloid-beta peptide

Mapping free-energy landscapes has proved to be a powerful tool for studying reaction mechanisms. Many complex biomolecular assembly processes, however, have remained challenging to access using this approach, including the aggregation of peptides and proteins into amyloid fibrils implicated in a range of disorders. Here, we generalize the strategy used to probe free-energy landscapes in protein folding to determine the activation energies and entropies that characterize each of the molecular steps in the aggregation of the amyloid-β peptide (Aβ42), which is associated with Alzheimer’s disease. Our results reveal that interactions between monomeric Aβ42 and amyloid fibrils during fibril-dependent secondary nucleation fundamentally reverse the thermodynamic signature of this process relative to primary nucleation, even though both processes generate aggregates from soluble peptides. By mapping the energetic and entropic contributions along the reaction trajectories, we show that the catalytic efficiency of Aβ42 fibril surfaces results from the enthalpic stabilization of adsorbing peptides in conformations amenable to nucleation, resulting in a dramatic lowering of the activation energy for nucleation

Cholesterol catalyses Aβ42 aggregation through a heterogeneous nucleation pathway in the presence of lipid membranes.

Alzheimer's disease is a neurodegenerative disorder associated with the aberrant aggregation of the amyloid-β peptide. Although increasing evidence implicates cholesterol in the pathogenesis of Alzheimer's disease, the detailed mechanistic link between this lipid molecule and the disease process remains to be fully established. To address this problem, we adopt a kinetics-based strategy that reveals a specific catalytic role of cholesterol in the aggregation of Aβ42 (the 42-residue form of the amyloid-β peptide). More specifically, we demonstrate that lipid membranes containing cholesterol promote Aβ42 aggregation by enhancing its primary nucleation rate by up to 20-fold through a heterogeneous nucleation pathway. We further show that this process occurs as a result of cooperativity in the interaction of multiple cholesterol molecules with Aβ42. These results identify a specific microscopic pathway by which cholesterol dramatically enhances the onset of Aβ42 aggregation, thereby helping rationalize the link between Alzheimer's disease and the impairment of cholesterol homeostasis

Deformable and robust core-shell protein microcapsules templated by liquid-liquid phase-separated microdroplets

Microcapsules are a key class of microscale materials with applications in areas ranging from personal care to biomedicine, and with increasing potential to act as extracellular matrix (ECM) models of hollow organs, tissues, or biomolecular condensates. Such capsules are conventionally generated from non-ECM materials including synthetic polymers. Here, robust microcapsules with controllable shell thickness from physically- and enzymatically-crosslinked gelatin are fabricated, and a core–shell architecture is achieved by exploiting a liquid–liquid phase-separated aqueous system in a one-step microfluidic process. Microfluidic mechanical testing reveals that the mechanical robustness of thicker-shell capsules could be controlled through modulation of the shell thickness. Furthermore, the microcapsules demonstrate environmentally-responsive deformation, including buckling driven by osmosis and external mechanical forces. A sequential release of cargo species is obtained through the degradation of the capsules. Stability measurements show the capsules are stable at 37 °C for more than 2 weeks. Finally, through gel–sol transition, microgels function as precursors for the formation of all-aqueous liquid–liquid phase-separated systems that are two-phase or multiphase. These smart capsules that can undergo phase transition are promising models of hollow biostructures, microscale drug carriers, and building blocks or compartments for active soft materials and robots

Physical determinants of amyloid assembly in biofilm formation

A wide range of bacterial pathogens have been shown to form biofilms, which significantly increase their resistance to environmental stresses, such as antibiotics, and are thus of central importance in the context of bacterial diseases. One of the major structural components of these bacterial biofilms are amyloid fibrils, yet the mechanism of fibril assembly and its importance for biofilm formation are currently not fully understood. By studying fibril formation in vitro, in a model system of two common but unrelated biofilm-forming proteins, FapC from Pseudomonas fluorescens and CsgA from Escherichia coli, we found that the two proteins have a common aggregation mechanism. In both systems, fibril formation proceeds via nucleated growth of linear fibrils exhibiting similar measured rates of elongation, with negligible fibril self-replication. These similarities between two unrelated systems suggest that convergent evolution plays a key role in tuning the assembly kinetics of functional amyloid fibrils and indicates that only a narrow window of mechanisms and assembly rates allows for successful biofilm formation. Thus, the amyloid assembly reaction is likely to represent a means for controlling biofilm formation, both by the organism and by possible inhibitory drugs.IMPORTANCE Biofilms are generated by bacteria, embedded in the formed extracellular matrix. The biofilm's function is to improve the survival of a bacterial colony through, for example, increased resistance to antibiotics or other environmental stresses. Proteins secreted by the bacteria act as a major structural component of this extracellular matrix, as they self-assemble into highly stable amyloid fibrils, making the biofilm very difficult to degrade by physical and chemical means once formed. By studying the self-assembly mechanism of the fibrils from their monomeric precursors in two unrelated bacteria, our experimental and theoretical approaches shed light on the mechanism of functional amyloid assembly in the context of biofilm formation. Our results suggest that fibril formation may be a rate-limiting step in biofilm formation, which in turn has implications on the protein self-assembly reaction as a target for potential antibiotic drugs

Geometric localization in supported elastic struts

\u3cp\u3eLocalized deformation patterns are a common motif in morphogenesis and are increasingly finding applications in materials science and engineering, in such instances as mechanical memories. Here, we describe the emergence of spatially localized deformations in a minimal mechanical system by exploring the impact of growth and shear on the conformation of a semi-flexible filament connected to a pliable shearable substrate. We combine numerical simulations of a discrete rod model with theoretical analysis of the differential equations recovered in the continuum limit to quantify (in the form of scaling laws) how geometry, mechanics and growth act together to give rise to such localized structures in this system. We find that spatially localized deformations along the filament emerge for intermediate shear modulus and increasing growth. Finally, we use experiments on a 3D-printed multi-material model system to demonstrate that external control of the amount of shear and growth may be used to regulate the spatial extent of the localized strain texture.\u3c/p\u3

Kinetic analysis of amyloid formation

The formation of amyloid fibrils is a central phenomenon in the progressive pathology of many neurodegenerative diseases, as well as in the fabrication of functional materials. Several different molecular processes acting in concert are responsible for the formation of amyloid fibrils from monomeric protein in solution. Here, we describe a method to determine which microscopic processes drive the overall formation of fibrils by using chemical kinetics in combination with systematic experimental datasets analysed in a global manner. We outline general concepts for obtaining suitable kinetic data and detail the key stages of data analysis, from quality control to the verification of a specific mechanism of aggregation

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