Dissecting the kinetic process of amyloid fiber formation through asymptotic analysis

Gallium nanoparticles as novel inhibitors of Aβ40 aggregation

Alzheimer's disease (AD) has been consistently related to the formation of senile amyloid plaques mainly composed of amyloid β (Aβ) peptides. The toxicity of Aβ aggregates has been indicated to be responsible for AD pathology. One scenario to decrease Aβ toxicity is the development of effective inhibitors against Aβ amyloid formation. In this study, we investigate the effect of gallium nitride nanoparticles (GaN NPs) as inhibitors of Aβ40 amyloid formation using a combination of biophysical approaches. Our results show that the lag phase of Aβ40 aggregation kinetics is significantly retarded by GaN NPs in a concentration dependent manner, implying the activity of GaN NPs in interfering with the formation of the crucial nucleus during Aβ aggregation. Our results also show that GaN NPs can reduce the amyloid fibril elongation rate in the course of the aggregation kinetics. It is speculated that the high polarization characteristics of GaN NPs may provoke a strong interaction between the particles and Aβ40 peptide and in this way decrease self-association of the peptide monomers to form amyloids.

Mechanisms of Heparin-Induced Tau Aggregation Revealed by a Single Nanopore

Protein aggregation is involved in many diseases, including Parkinson's and Alzheimer's. The latter is characterized by intraneuronal deposition of amyloid aggregates composed of the tau protein. Although large and insoluble aggregates are typically found in affected brains, intermediate soluble oligomers are thought to represent crucial species for toxicity and spreading. Nanopore sensors constitute an emerging technology that allows the detection of the size and populations of molecular assembly present in a sample. Here, we employed conical nanopores to obtain the particle distributions during tau aggregation. We identified three distinct populations, monomers, oligomers, and fibrils, which we could quantify along the aggregation process. By comparing tau wild type with a mutant carrying the disease-associated P301L mutation, we showed that the latter mutation promotes the formation of oligomers. We furthermore highlighted that the P301L mutation promotes fibril breakage. This work demonstrates that conical nanopore is a powerful tool to measure and quantify transient protein aggregate intermediates.

Prediction of amyloid aggregation rates by machine learning and feature selection

A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protein aggregation rate, a feedforward fully connected neural network (FCN) with one hidden layer is trained on a dataset composed of 21 different kinds of amyloid proteins and tested on 4 rest proteins. FCN shows a much better performance than traditional algorithms, such as multivariable linear regression and support vector regression, with an average accuracy higher than 90%. Furthermore, by the correlation analysis and the principal component analysis, seven key features, folding energy, HP patterns for helix, sheet and helices cross membrane, pH, ionic strength, and protein concentration, are shown to constitute a minimum feature set for characterizing the amyloid aggregation kinetics.

Measurement of Tau Filament Fragmentation Provides Insights into Prion-like Spreading

The ordered assembly of amyloidogenic proteins causes a wide spectrum of common neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. These diseases share common features with prion diseases, in which misfolded proteins can self-replicate and transmit disease across different hosts. Deciphering the molecular mechanisms that underlie the amplification of aggregates is fundamental for understanding how pathological deposits can spread through the brain and drive disease. Here, we used single-molecule microscopy to study the assembly and replication of tau at the single aggregate level. We found that tau aggregates have an intrinsic ability to amplify by filament fragmentation, and determined the doubling times for this replication process by kinetic modeling. We then simulated the spreading time for aggregates through the brain and found this to be in good agreement with both the observed time frame for spreading of pathological tau deposits in Alzheimer's disease and in experimental models of tauopathies. With this work we begin to understand the physical parameters that govern the spreading rates of tau and other amyloids through the human brain.

Growth-incompetent monomers of human calcitonin lead to a noncanonical direct relationship between peptide concentration and aggregation lag time

The role of the peptide hormone calcitonin in skeletal protection has led to its use as a therapeutic for osteoporosis. However, calcitonin aggregation into amyloid fibrils limits its therapeutic efficacy, necessitating a modification of calcitonin's aggregation kinetics. Here, we report a direct relationship between human calcitonin (hCT) concentration and aggregation lag time. This kinetic trend was contrary to the conventional understanding of amyloid aggregation and persisted over a range of aggregation conditions, as confirmed by thioflavin-T kinetics assays, CD spectroscopy, and transmission EM. Dynamic light scattering, 1H NMR experiments, and seeded thioflavin-T assay results indicated that differences in initial peptide species contribute to this trend more than variations in the primary nucleus formation rate. On the basis of kinetics modeling results, we propose a mechanism whereby a structural conversion of hCT monomers is needed before incorporation into the fibril. Our kinetic mechanism recapitulates the experimentally observed relationship between peptide concentration and lag time and represents a novel mechanism in amyloid aggregation. Interestingly, hCT at low pH and salmon calcitonin (sCT) exhibited the canonical inverse relationship between concentration and lag time. Comparative studies of hCT and sCT with molecular dynamics simulations and CD indicated an increased α-helical structure in sCT and low-pH hCT monomers compared with neutral-pH hCT, suggesting that α-helical monomers represent a growth-competent species, whereas unstructured random coil monomers represent a growth-incompetent species. Our finding that initial monomer concentration is positively correlated with lag time in hCT aggregation could help inform future efforts for improving therapeutic applications of CT.

Nanoscale Control of Amyloid Self-Assembly Using Protein Phase Transfer by Host-Guest Chemistry

Amyloid fibrils have recently been highlighted for their diverse applications as functional nanomaterials in modern chemistry. However, tight control to obtain a targeted fibril length with low heterogeneity has not been achieved because of the complicated nature of amyloid fibrillation. Herein, we demonstrate that fibril assemblies can be homogeneously manipulated with desired lengths from ~40 nm to ~10 μm by a phase transfer of amyloid proteins based on host-guest chemistry. We suggest that host-guest interactions with cucurbit[6]uril induce a phase transfer of amyloid proteins (human insulin, human islet amyloid polypeptide, hen egg lysozyme, and amyloid-β 1–40 & 1–42) from the soluble state to insoluble state when the amount of cucurbit[6]uril exceeds its solubility limit in solution. The phase transfer of the proteins kinetically delays the nucleation of amyloid proteins, while the nuclei formed in the early stage are homogeneously assembled to fibrils. Consequently, supramolecular assemblies of amyloid proteins with heterogeneous kinetics can be controlled by protein phase transfer based on host-guest interactions.

Probing the sources of the apparent irreproducibility of amyloid formation: drastic changes in kinetics and a switch in mechanism due to micellelike oligomer formation at critical concentrations of IAPP

The aggregation of amyloidogenic proteins is infamous for being highly chaotic, with small variations in conditions sometimes leading to large changes in aggregation rates. Using the amyloidogenic protein IAPP (islet amyloid polypeptide protein, also known as amylin) as an example, we show that a part of this phenomenon may be related to the formation of micellelike oligomers at specific critical concentrations and temperatures. We show that pyrene fluorescence can sensitively detect micellelike oligomer formation by IAPP and discriminate between micellelike oligomers from fibers and monomers, making pyrene one of the few chemical probes specific to a prefibrillar oligomer. We further show that oligomers of this type reversibly form at critical concentrations in the low micromolar range and at specific critical temperatures. Micellelike oligomer formation has several consequences for amyloid formation by IAPP. First, the kinetics of fiber formation increase substantially as the critical concentration is approached but are nearly independent of concentration below it, suggesting a direct role for the oligomers in fiber formation. Second, the critical concentration is strongly correlated with the propensity to form amyloid: higher critical concentrations are observed for both IAPP variants with lower amyloidogenicity and for native IAPP at acidic pH in which aggregation is greatly slowed. Furthermore, using the DEST NMR technique, we show that the pathway of amyloid formation switches as the critical point is approached, with self-interactions primarily near the N-terminus below the critical temperature and near the central region above the critical temperature, reconciling two apparently conflicting views of the initiation of IAPP aggregation.

Modelling amyloid fibril formation kinetics: mechanisms of nucleation and growth

Amyloid and amyloid-like fibrils are self-assembling protein nanostructures, of interest for their robust material properties and inherent biological compatibility as well as their putative role in a number of debilitating mammalian disorders. Understanding fibril formation is essential to the development of strategies to control, manipulate or prevent fibril growth. As such, this area of research has attracted significant attention over the last half century. This review describes a number of different models that have been formulated to describe the kinetics of fibril assembly. We describe the macroscopic implications of mechanisms in which secondary processes such as secondary nucleation, fragmentation or branching dominate the assembly pathway, compared to mechanisms dominated by the influence of primary nucleation. We further describe how experimental data can be analysed with respect to the predictions of kinetic models.

Statistical mechanical treatments of protein amyloid formation

Protein aggregation is an important field of investigation because it is closely related to the problem of neurodegenerative diseases, to the development of biomaterials, and to the growth of cellular structures such as cyto-skeleton. Self-aggregation of protein amyloids, for example, is a complicated process involving many species and levels of structures. This complexity, however, can be dealt with using statistical mechanical tools, such as free energies, partition functions, and transfer matrices. In this article, we review general strategies for studying protein aggregation using statistical mechanical approaches and show that canonical and grand canonical ensembles can be used in such approaches. The grand canonical approach is particularly convenient since competing pathways of assembly and dis-assembly can be considered simultaneously. Another advantage of using statistical mechanics is that numerically exact solutions can be obtained for all of the thermodynamic properties of fibrils, such as the amount of fibrils formed, as a function of initial protein concentration. Furthermore, statistical mechanics models can be used to fit experimental data when they are available for comparison.

Simple moment-closure model for the self-assembly of breakable amyloid filaments

In this work, we derive a simple mathematical model from mass-action equations for amyloid fiber formation that takes into account the primary nucleation, elongation, and length-dependent fragmentation. The derivation is based on the principle of minimum free energy under certain constraints and is mathematically related to the partial equilibrium approximation. Direct numerical comparisons confirm the usefulness of our simple model. We further explore its basic kinetic and equilibrium properties, and show that the current model is a straightforward generalization of that with constant fragmentation rates.

A necessary condition for coexistence of autocatalytic replicators in a prebiotic environment

A necessary, but not sufficient, mathematical condition for the coexistence of short replicating species is presented here. The mathematical condition is obtained for a prebiotic environment, simulated as a fed-batch reactor, which combines monomer recycling, variable reaction order and a fixed monomer inlet flow with two replicator types and two monomer types. An extensive exploration of the parameter space in the model validates the robustness and efficiency of the mathematical condition, with nearly 1.7% of parameter sets meeting the condition and half of those exhibiting sustained coexistence. The results show that it is possible to generate a condition of coexistence, where two replicators sustain a linear growth simultaneously for a wide variety of chemistries, under an appropriate environment. The presence of multiple monomer types is critical to sustaining the coexistence of multiple replicator types.

A variational model for oligomer-formation process of GNNQQNY peptide from yeast prion protein Sup35

Many human neurodegenerative diseases are associated with the aggregation of insoluble amyloid-like fibrous proteins. However, the processes by which the randomly diffused monomer peptides aggregate into the highly regulated amyloid fibril structures are largely unknown. We proposed a residue-level coarse-grained variational model for the investigation of the aggregation pathway for a small assembly of amyloid proteins, the peptide GNNQQNY from yeast prion protein Sup35. By examining the free energy surface, we identified the residue-level sequential pathways for double parallel and antiparallel β-peptides, which show that the central dry polar zipper structure is the major folding core in both cases. The critical nucleus size is determined to be three peptides for the homogeneous nucleation process, whereas the zig-zag growth pattern appears most favorably for heterogeneous nucleation. Consistent with the dock-and-lock mechanism, the aggregation process of free peptides to the fibril core was found to be highly cooperative. The quantitative validation with the computational simulations and experimental data demonstrated the usefulness of the proposed model in understanding the general mechanism of the amyloid fibril system.