Molecular mechanism of α-synuclein aggregation on lipid membranes revealed

The central hallmark of Parkinson's disease pathology is the aggregation of the α-synuclein protein, which, in its healthy form, is associated with lipid membranes. Purified monomeric α-synuclein is relatively stable in vitro, but its aggregation can be triggered by the presence of lipid vesicles. Despite this central importance of lipids in the context of α-synuclein aggregation, their detailed mechanistic role in this process has not been established to date. Here, we use chemical kinetics to develop a mechanistic model that is able to globally describe the aggregation behaviour of α-synuclein in the presence of DMPS lipid vesicles, across a range of lipid and protein concentrations. Through the application of our kinetic model to experimental data, we find that the reaction is a co-aggregation process involving both protein and lipids and that lipids promote aggregation as much by enabling fibril elongation as by enabling their initial formation. Moreover, we find that the primary nucleation of lipid-protein co-aggregates takes place not on the surface of lipid vesicles in bulk solution but at the air-water and/or plate interfaces, where lipids and proteins are likely adsorbed. Our model forms the basis for mechanistic insights, also in other lipid-protein co-aggregation systems, which will be crucial in the rational design of drugs that inhibit aggregate formation and act at the key points in the α-synuclein aggregation cascade.

A solid beta-sheet structure is formed at the surface of FUS droplets during aging

Phase transitions are important to understand cell dynamics, and the maturation of liquid droplets is relevant to neurodegenerative disorders. We combined NMR and Raman spectroscopies with microscopy to follow, over a period of days to months, droplet maturation of the protein fused in sarcoma (FUS). Our study reveals that the surface of the droplets plays a critical role in this process, while RNA binding prevents it. The maturation kinetics are faster in an agarose-stabilized biphasic sample compared with a monophasic condensed sample, owing to the larger surface-to-volume ratio. In addition, Raman spectroscopy reports structural differences upon maturation between the inside and the surface of droplets, which is comprised of β-sheet content, as revealed by solid-state NMR. In agreement with these observations, a solid crust-like shell is observed at the surface using microaspiration. Ultimately, matured droplets were converted into fibrils involving the prion-like domain as well as the first RGG motif.

Self-replication of Aβ42 aggregates occurs on small and isolated fibril sites

Self-replication of amyloid fibrils via secondary nucleation is an intriguing physicochemical phenomenon in which existing fibrils catalyze the formation of their own copies. The molecular events behind this fibril surface-mediated process remain largely inaccessible to current structural and imaging techniques. Using statistical mechanics, computer modeling, and chemical kinetics, we show that the catalytic structure of the fibril surface can be inferred from the aggregation behavior in the presence and absence of a fibril-binding inhibitor. We apply our approach to the case of Alzheimer's A[Formula: see text] amyloid fibrils formed in the presence of proSP-C Brichos inhibitors. We find that self-replication of A[Formula: see text] fibrils occurs on small catalytic sites on the fibril surface, which are far apart from each other, and each of which can be covered by a single Brichos inhibitor.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

Aggregation controlled by condensate rheology

Biomolecular condensates in living cells can exhibit a complex rheology, including viscoelastic and glassy behavior. This rheological behavior of condensates was suggested to regulate polymerization of cytoskeletal filaments and aggregation of amyloid fibrils. Here, we theoretically investigate how the rheological properties of condensates can control the formation of linear aggregates. To this end, we propose a kinetic theory for linear aggregation in coexisting phases, which accounts for the aggregate size distribution and the exchange of aggregates between inside and outside of condensates. The rheology of condensates is accounted in our model via aggregate mobilities that depend on aggregate size. We show that condensate rheology determines whether aggregates of all sizes or dominantly small aggregates are exchanged between condensate inside and outside on the timescale of aggregation. As a result, the ratio of aggregate numbers inside to outside of condensates differs significantly. Strikingly, we also find that weak variations in the rheological properties of condensates can lead to a switch-like change of the number of aggregates. These results suggest a possible physical mechanism for how living cells could control linear aggregation in a switch-like fashion through variations in condensate rheology.

Analytical Solution to the Flory-Huggins Model

A self-consistent analytical solution for binodal concentrations of the two-component Flory-Huggins phase separation model is derived. We show that this form extends the validity of the Ginzburg-Landau expansion away from the critical point to cover the whole phase space. Furthermore, this analytical solution reveals an exponential scaling law of the dilute phase binodal concentration as a function of the interaction strength and chain length. We demonstrate explicitly the power of this approach by fitting experimental protein liquid-liquid phase separation boundaries to determine the effective chain length and solute-solvent interaction energies. Moreover, we demonstrate that this strategy allows us to resolve differences in interaction energy contributions of individual amino acids. This analytical framework can serve as a new way to decode the protein sequence grammar for liquid-liquid phase separation.

Uncovering the universality of self-replication in protein aggregation and its link to disease

Fibrillar protein aggregates are a hallmark of a range of human disorders, from prion diseases to dementias, but are also encountered in several functional contexts. Yet, the fundamental links between protein assembly mechanisms and their functional or pathological roles have remained elusive. Here, we analyze the aggregation kinetics of a large set of proteins that self-assemble by a nucleated-growth mechanism, from those associated with disease, over those whose aggregates fulfill functional roles in biology, to those that aggregate only under artificial conditions. We find that, essentially, all such systems, regardless of their biological role, are capable of self-replication. However, for aggregates that have evolved to fulfill a structural role, the rate of self-replication is too low to be significant on the biologically relevant time scale. By contrast, all disease-related proteins are able to self-replicate quickly compared to the time scale of the associated disease. Our findings establish the ubiquity of self-replication and point to its potential importance across aggregation-related disorders.

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 lifetime, 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 a new path for the systematic rational design of therapeutic strategies against amyloid-related diseases.

Feedback control of protein aggregation

The self-assembly of peptides and proteins into amyloid fibrils plays a causative role in a wide range of increasingly common and currently incurable diseases. The molecular mechanisms underlying this process have recently been discovered, prompting the development of drugs that inhibit specific reaction steps as possible treatments for some of these disorders. A crucial part of treatment design is to determine how much drug to give and when to give it, informed by its efficacy and intrinsic toxicity. Since amyloid formation does not proceed at the same pace in different individuals, it is also important that treatment design is informed by local measurements of the extent of protein aggregation. Here, we use stochastic optimal control theory to determine treatment regimens for inhibitory drugs targeting several key reaction steps in protein aggregation, explicitly taking into account variability in the reaction kinetics. We demonstrate how these regimens may be updated "on the fly" as new measurements of the protein aggregate concentration become available, in principle, enabling treatments to be tailored to the individual. We find that treatment timing, duration, and drug dosage all depend strongly on the particular reaction step being targeted. Moreover, for some kinds of inhibitory drugs, the optimal regimen exhibits high sensitivity to stochastic fluctuations. Feedback controls tailored to the individual may therefore substantially increase the effectiveness of future treatments.

Scaling analysis reveals the mechanism and rates of prion replication in vivo

Prions consist of pathological aggregates of cellular prion protein and have the ability to replicate, causing neurodegenerative diseases, a phenomenon mirrored in many other diseases connected to protein aggregation, including Alzheimer's and Parkinson's diseases. However, despite their key importance in disease, the individual processes governing this formation of pathogenic aggregates, as well as their rates, have remained challenging to elucidate in vivo. Here we bring together a mathematical framework with kinetics of the accumulation of prions in mice and microfluidic measurements of aggregate size to dissect the overall aggregation reaction into its constituent processes and quantify the reaction rates in mice. Taken together, the data show that multiplication of prions in vivo is slower than in in vitro experiments, but efficient when compared with other amyloid systems, and displays scaling behavior characteristic of aggregate fragmentation. These results provide a framework for the determination of the mechanisms of disease-associated aggregation processes within living organisms.

Screening of small molecules using the inhibition of oligomer formation in α-synuclein aggregation as a selection parameter

The aggregation of α-synuclein is a central event in Parkinsons's disease and related synucleinopathies. Since pharmacologically targeting this process, however, has not yet resulted in approved disease-modifying treatments, there is an unmet need of developing novel methods of drug discovery. In this context, the use of chemical kinetics has recently enabled accurate quantifications of the microscopic steps leading to the proliferation of protein misfolded oligomers. As these species are highly neurotoxic, effective therapeutic strategies may be aimed at reducing their numbers. Here, we exploit this quantitative approach to develop a screening strategy that uses the reactive flux toward α-synuclein oligomers as a selection parameter. Using this approach, we evaluate the efficacy of a library of flavone derivatives, identifying apigenin as a compound that simultaneously delays and reduces the formation of α-synuclein oligomers. These results demonstrate a compound selection strategy based on the inhibition of the formation of α-synuclein oligomers, which may be key in identifying small molecules in drug discovery pipelines for diseases associated with α-synuclein aggregation.

Small-molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer's disease

Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that modifies the properties of their monomeric states. Here, we identify a small molecule (10074-G5) capable of binding and sequestering the intrinsically disordered amyloid-β (Aβ) peptide in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aβ and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterize this interaction using biophysical experiments and integrative structural ensemble determination methods. We observe that this molecule increases the conformational entropy of monomeric Aβ while decreasing its hydrophobic surface area. We also show that it rescues a Caenorhabditis elegans model of Aβ-associated toxicity, consistent with the mechanism of action identified from the in silico and in vitro studies. These results illustrate the strategy of stabilizing the monomeric states of disordered proteins with small molecules to alter their behavior for therapeutic purposes.

Mechanical basis for fibrillar bundle morphology

Understanding the morphology of self-assembled fibrillar bundles and aggregates is relevant to a range of problems in molecular biology, supramolecular chemistry and materials science. Here, we propose a coarse-grained approach that averages over specific molecular details and yields an effective mechanical theory for the spatial complexity of self-assembling fibrillar structures that arises due to the competing effects of (the bending and twisting) elasticity of individual filaments and the adhesive interactions between them. We show that our theoretical framework accounting for this allows us to capture a number of diverse fibril morphologies observed in natural and synthetic systems, ranging from Filopodia to multi-walled carbon nanotubes, and leads to a phase diagram of possible fibril shapes. We also show how the extreme sensitivity of these morphologies can lead to spatially chaotic structures. Together, these results suggest a common mechanical basis for mesoscale fibril morphology as a function of the nanoscale mechanical properties of its filamentous constituents.

Thermodynamic and kinetic design principles for amyloid-aggregation inhibitors

Understanding the mechanism of action of compounds capable of inhibiting amyloid-fibril formation is critical to the development of potential therapeutics against protein-misfolding diseases. A fundamental challenge for progress is the range of possible target species and the disparate timescales involved, since the aggregating proteins are simultaneously the reactants, products, intermediates, and catalysts of the reaction. It is a complex problem, therefore, to choose the states of the aggregating proteins that should be bound by the compounds to achieve the most potent inhibition. We present here a comprehensive kinetic theory of amyloid-aggregation inhibition that reveals the fundamental thermodynamic and kinetic signatures characterizing effective inhibitors by identifying quantitative relationships between the aggregation and binding rate constants. These results provide general physical laws to guide the design and optimization of inhibitors of amyloid-fibril formation, revealing in particular the important role of on-rates in the binding of the inhibitors.

A rationally designed bicyclic peptide remodels Aβ42 aggregation in vitro and reduces its toxicity in a worm model of Alzheimer's disease

Bicyclic peptides have great therapeutic potential since they can bridge the gap between small molecules and antibodies by combining a low molecular weight of about 2 kDa with an antibody-like binding specificity. Here we apply a recently developed in silico rational design strategy to produce a bicyclic peptide to target the C-terminal region (residues 31–42) of the 42-residue form of the amyloid β peptide (Aβ42), a protein fragment whose aggregation into amyloid plaques is linked with Alzheimer’s disease. We show that this bicyclic peptide is able to remodel the aggregation process of Aβ42 in vitro and to reduce its associated toxicity in vivo in a C. elegans worm model expressing Aβ42. These results provide an initial example of a computational approach to design bicyclic peptides to target specific epitopes on disordered proteins.

The catalytic nature of protein aggregation

The formation of amyloid fibrils from soluble peptide is a hallmark of many neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Characterization of the microscopic reaction processes that underlie these phenomena have yielded insights into the progression of such diseases and may inform rational approaches for the design of drugs to halt them. Experimental evidence suggests that most of these reaction processes are intrinsically catalytic in nature and may display enzymelike saturation effects under conditions typical of biological systems, yet a unified modeling framework accounting for these saturation effects is still lacking. In this paper, we therefore present a universal kinetic model for biofilament formation in which every fundamental process in the reaction network can be catalytic. The single closed-form expression derived is capable of describing with high accuracy a wide range of mechanisms of biofilament formation and providing the first integrated rate law of a system in which multiple reaction processes are saturated. Moreover, its unprecedented mathematical simplicity permits us to very clearly interpret the effects of increasing saturation on the overall kinetics. The effectiveness of the model is illustrated by fitting it to the data of in vitro Aβ40 aggregation. Remarkably, we find that primary nucleation becomes saturated, demonstrating that it must be heterogeneous, occurring at interfaces and not in solution.

Identification of on- and off-pathway oligomers in amyloid fibril formation

A general non-binary definition for on- and off-pathway intermediates is developed, enabling comparison of amyloid oligomers' contributions to fibril formation.

The misfolding and aberrant aggregation of proteins into fibrillar structures is a key factor in some of the most prevalent human diseases, including diabetes and dementia. Low molecular weight oligomers are thought to be a central factor in the pathology of these diseases, as well as critical intermediates in the fibril formation process, and as such have received much recent attention. Moreover, on-pathway oligomeric intermediates are potential targets for therapeutic strategies aimed at interrupting the fibril formation process. However, a consistent framework for distinguishing on-pathway from off-pathway oligomers has hitherto been lacking and, in particular, no consensus definition of on- and off-pathway oligomers is available. In this paper, we argue that a non-binary definition of oligomers' contribution to fibril-forming pathways may be more informative and we suggest a quantitative framework, in which each oligomeric species is assigned a value between 0 and 1 describing its relative contribution to the formation of fibrils. First, we clarify the distinction between oligomers and fibrils, and then we use the formalism of reaction networks to develop a general definition for on-pathway oligomers, that yields meaningful classifications in the context of amyloid formation. By applying these concepts to Monte Carlo simulations of a minimal aggregating system, and by revisiting several previous studies of amyloid oligomers in light of our new framework, we demonstrate how to perform these classifications in practice. For each oligomeric species we obtain the degree to which it is on-pathway, highlighting the most effective pharmaceutical targets for the inhibition of amyloid fibril formation.

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.

Universality of filamentous aggregation phenomena

We use perturbative renormalization group theory to study the kinetics of protein aggregation phenomena in a unified manner across multiple timescales. Using this approach, we find that, irrespective of the specific molecular details or experimental conditions, filamentous assembly systems display universal behavior in time. Moreover, we show that the universality classes for protein aggregation correspond to simple autocatalytic processes and that the diversity of behavior in these systems is determined solely by the reaction order for secondary nucleation with respect to the protein concentration, which labels all possible universality classes. We validate these predictions on experimental data for the aggregation of several different proteins at several different initial concentrations, which by appropriate coordinate transformations we are able to collapse onto universal kinetic growth curves. These results establish the power of the perturbative renormalization group in distilling the ultimately simple temporal behavior of complex protein aggregation systems, creating the possibility to study the kinetics of general self-assembly phenomena in a unified fashion.

Geometric localization in supported elastic struts

Localized 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.

Quantifying Co-Oligomer Formation by α-Synuclein

Small oligomers of the protein α-synuclein (αS) are highly cytotoxic species associated with Parkinson's disease (PD). In addition, αS can form co-aggregates with its mutational variants and with other proteins such as amyloid-β (Aβ) and tau, which are implicated in Alzheimer's disease. The processes of self-oligomerization and co-oligomerization of αS are, however, challenging to study quantitatively. Here, we have utilized single-molecule techniques to measure the equilibrium populations of oligomers formed in vitro by mixtures of wild-type αS with its mutational variants and with Aβ40, Aβ42, and a fragment of tau. Using a statistical mechanical model, we find that co-oligomer formation is generally more favorable than self-oligomer formation at equilibrium. Furthermore, self-oligomers more potently disrupt lipid membranes than do co-oligomers. However, this difference is sometimes outweighed by the greater formation propensity of co-oligomers when multiple proteins coexist. Our results suggest that co-oligomer formation may be important in PD and related neurodegenerative diseases.

Statistical Mechanics of Globular Oligomer Formation by Protein Molecules

The misfolding and aggregation of proteins into linear fibrils is widespread in human biology, for example, in connection with amyloid formation and the pathology of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. The oligomeric species that are formed in the early stages of protein aggregation are of great interest, having been linked with the cellular toxicity associated with these conditions. However, these species are not characterized in any detail experimentally, and their properties are not well understood. Many of these species have been found to have approximately spherical morphology and to be held together by hydrophobic interactions. We present here an analytical statistical mechanical model of globular oligomer formation from simple idealized amphiphilic protein monomers and show that this correlates well with Monte Carlo simulations of oligomer formation. We identify the controlling parameters of the model, which are closely related to simple quantities that may be fitted directly from experiment. We predict that globular oligomers are unlikely to form at equilibrium in many polypeptide systems but instead form transiently in the early stages of amyloid formation. We contrast the globular model of oligomer formation to a well-established model of linear oligomer formation, highlighting how the differing ensemble properties of linear and globular oligomers offer a potential strategy for characterizing oligomers from experimental measurements.

Secondary nucleation in amyloid formation

Nucleation of new peptide and protein aggregates on the surfaces of amyloid fibrils of the same peptide or protein has emerged in the past two decades as a major pathway for both the generation of molecular species responsible for cellular toxicity and for the autocatalytic proliferation of peptide and protein aggregates. A key question in current research is the molecular mechanism and driving forces governing such processes, known as secondary nucleation. In this context, the analogies with other self-assembling systems for which monomer-dependent secondary nucleation has been studied for more than a century provide a valuable source of inspiration. Here, we present a short overview of this background and then review recent results regarding secondary nucleation of amyloid-forming peptides and proteins, focusing in particular on the amyloid β peptide (Aβ) from Alzheimer's disease, with some examples regarding α-synuclein from Parkinson's disease. Monomer-dependent secondary nucleation of Aβ was discovered using a combination of kinetic experiments, global analysis, seeding experiments and selective isotope-enrichment, which pinpoint the monomer as the origin of new aggregates in a fibril-catalyzed reaction. Insights into driving forces are gained from variations of solution conditions, temperature and peptide sequence. Selective inhibition of secondary nucleation is explored as an effective means to limit oligomer production and toxicity. We also review experiments aimed at finding interaction partners of oligomers generated by secondary nucleation in an ongoing aggregation process. At the end of this feature article we bring forward outstanding questions and testable mechanistic hypotheses regarding monomer-dependent secondary nucleation in amyloid formation.

Self-Assembly-Mediated Release of Peptide Nanoparticles through Jets Across Microdroplet Interfaces

The release of nanoscale structures from microcapsules, triggered by changes in the capsule in response to external stimuli, has significant potential for active component delivery. Here, we describe an orthogonal strategy for controlling molecular species' release across oil/water interfaces by modulating their intrinsic self-assembly state. We show that although the soluble peptide Boc-FF can be stably encapsulated for days, its self-assembly into nanostructures triggers jet-like release within seconds. Moreover, we exploit this self-assembly-mediated release to deliver other molecular species that are transported as cargo. These results demonstrate the role of self-assembly in modulating the transport of peptides across interfaces.

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.

Budding-like division of all-aqueous emulsion droplets modulated by networks of protein nanofibrils

Networks of natural protein nanofibrils, such as cytoskeletal filaments, control the shape and the division of cells, yet mimicking this functionality in a synthetic setting has proved challenging. Here, we demonstrate that artificial networks of protein nanofibrils can induce controlled deformation and division of all-aqueous emulsion droplets with budding-like morphologies. We show that this process is driven by the difference in the immersional wetting energy of the nanofibril network, and that both the size and the number of the daughter droplets formed during division can be controlled by modulating the fibril concentration and the chemical properties of the fibril network. Our results demonstrate a route for achieving biomimetic division with synthetic self-assembling fibrils and offer an engineered approach to regulate the morphology of protein gels.

Cooperative Assembly of Hsp70 Subdomain Clusters

Many molecular chaperones exist as oligomeric complexes in their functional states, yet the physical determinants underlying such self-assembly behavior, as well as the role of oligomerization in the activity of molecular chaperones in inhibiting protein aggregation, have proven to be difficult to define. Here, we demonstrate direct measurements under native conditions of the changes in the average oligomer populations of a chaperone system as a function of concentration and time and thus determine the thermodynamic and kinetic parameters governing the self-assembly process. We access this self-assembly behavior in real time under native-like conditions by monitoring the changes in the micrometer-scale diffusion of the different complexes in time and space using a microfluidic platform. Using this approach, we find that the oligomerization mechanism of the Hsp70 subdomain occurs in a cooperative manner and involves structural constraints that limit the size of the species formed beyond the limits imposed by mass balance. These results illustrate the ability of microfluidic methods to probe polydisperse protein self-assembly in real time in solution and to shed light on the nature and dynamics of oligomerization processes.

Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation

Understanding how normally soluble peptides and proteins aggregate to form amyloid fibrils is central to many areas of modern biomolecular science, ranging from the development of functional biomaterials to the design of rational therapeutic strategies against increasingly prevalent medical conditions such as Alzheimer's and Parkinson's diseases. As such, there is a great need to develop models to mechanistically describe how amyloid fibrils are formed from precursor peptides and proteins. Here we review and discuss how ideas and concepts from chemical reaction kinetics can help to achieve this objective. In particular, we show how a combination of theory, experiments, and computer simulations, based on chemical kinetics, provides a general formalism for uncovering, at the molecular level, the mechanistic steps that underlie the phenomenon of amyloid fibril formation.

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

Mapping 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 various disorders. Here we generalize the strategy used to probe energy landscapes in protein folding to determine the activation energies and entropies that characterise 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 Aβ and amyloid fibrils during fibril-dependent 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 reactive trajectories, we show that the catalytic efficiency of Aβ42 fibril surfaces results from the enthalpic stabilisation of adsorbing peptides in conformations amenable to nucleation, driving a dramatic lowering of the activation energy barrier for nucleation.

Direct Observation of Oligomerization by Single Molecule Fluorescence Reveals a Multistep Aggregation Mechanism for the Yeast Prion Protein Ure2

The self-assembly of polypeptides into amyloid structures is associated with a range of increasingly prevalent neurodegenerative diseases as well as with a select set of functional processes in biology. The phenomenon of self-assembly results in species with dramatically different sizes, from small oligomers to large fibrils; however, the kinetic relationship between these species is challenging to characterize. In the case of prion aggregates, these structures can self-replicate and act as infectious agents. Here we use single molecule spectroscopy to obtain quantitative information on the oligomer populations formed during aggregation of the yeast prion protein Ure2. Global analysis of the aggregation kinetics reveals the molecular mechanism underlying oligomer formation and depletion. Quantitative characterization indicates that the majority of Ure2 oligomers are relatively short-lived, and their rate of dissociation is much higher than their rate of conversion into growing fibrils. We identify an initial metastable oligomer, which can subsequently convert into a structurally distinct oligomer, which in turn converts into growing fibrils. We also show that fragmentation is responsible for the autocatalytic self-replication of Ure2 fibrils, but that preformed fibrils do not promote oligomer formation, indicating that secondary nucleation of the type observed for peptides and proteins associated with neurodegenerative disease does not occur at a significant rate for Ure2. These results establish a framework for elucidating the temporal and causal relationship between oligomers and larger fibrillar species in amyloid forming systems, and provide insights into why functional amyloid systems are not toxic to their host organisms.

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.

Kinetic constraints on self-assembly into closed supramolecular structures

Many biological and synthetic systems exploit self-assembly to generate highly intricate closed supramolecular architectures, ranging from self-assembling cages to viral capsids. The fundamental design principles that control the structural determinants of the resulting assemblies are increasingly well-understood, but much less is known about the kinetics of such assembly phenomena and it remains a key challenge to elucidate how these systems can be engineered to assemble in an efficient manner and avoid kinetic trapping. We show here that simple scaling laws emerge from a set of kinetic equations describing the self-assembly of identical building blocks into closed supramolecular structures and that this scaling behavior provides general rules that determine efficient assembly in these systems. Using this framework, we uncover the existence of a narrow range of parameter space that supports efficient self-assembly and reveal that nature capitalizes on this behavior to direct the reliable assembly of viral capsids on biologically relevant timescales.

Sequential Release of Proteins from Structured Multishell Microcapsules

In nature, a wide range of functional materials is based on proteins. Increasing attention is also turning to the use of proteins as artificial biomaterials in the form of films, gels, particles, and fibrils that offer great potential for applications in areas ranging from molecular medicine to materials science. To date, however, most such applications have been limited to single component materials despite the fact that their natural analogues are composed of multiple types of proteins with a variety of functionalities that are coassembled in a highly organized manner on the micrometer scale, a process that is currently challenging to achieve in the laboratory. Here, we demonstrate the fabrication of multicomponent protein microcapsules where the different components are positioned in a controlled manner. We use molecular self-assembly to generate multicomponent structures on the nanometer scale and droplet microfluidics to bring together the different components on the micrometer scale. Using this approach, we synthesize a wide range of multiprotein microcapsules containing three well-characterized proteins: glucagon, insulin, and lysozyme. The localization of each protein component in multishell microcapsules has been detected by labeling protein molecules with different fluorophores, and the final three-dimensional microcapsule structure has been resolved by using confocal microscopy together with image analysis techniques. In addition, we show that these structures can be used to tailor the release of such functional proteins in a sequential manner. Moreover, our observations demonstrate that the protein release mechanism from multishell capsules is driven by the kinetic control of mass transport of the cargo and by the dissolution of the shells. The ability to generate artificial materials that incorporate a variety of different proteins with distinct functionalities increases the breadth of the potential applications of artificial protein-based materials and provides opportunities to design more refined functional protein delivery systems.

Physical principles of filamentous protein self-assembly kinetics

The polymerization of proteins and peptides into filamentous supramolecular structures is an elementary form of self-organization of key importance to the functioning biological systems, as in the case of actin biofilaments that compose the cellular cytoskeleton. Aberrant filamentous protein self-assembly, however, is associated with undesired effects and severe clinical disorders, such as Alzheimer's and Parkinson's diseases, which, at the molecular level, are associated with the formation of certain forms of filamentous protein aggregates known as amyloids. Moreover, due to their unique physicochemical properties, protein filaments are finding extensive applications as biomaterials for nanotechnology. With all these different factors at play, the field of filamentous protein self-assembly has experienced tremendous activity in recent years. A key question in this area has been to elucidate the microscopic mechanisms through which filamentous aggregates emerge from dispersed proteins with the goal of uncovering the underlying physical principles. With the latest developments in the mathematical modeling of protein aggregation kinetics as well as the improvement of the available experimental techniques it is now possible to tackle many of these complex systems and carry out detailed analyses of the underlying microscopic steps involved in protein filament formation. In this paper, we review some classical and modern kinetic theories of protein filament formation, highlighting their use as a general strategy for quantifying the molecular-level mechanisms and transition states involved in these processes.

Dynamic microfluidic control of supramolecular peptide self-assembly

The dynamic nature of supramolecular polymers has a key role in their organization. Yet, the manipulation of their dimensions and polarity remains a challenge. Here, the minimalistic diphenylalanine building block was applied to demonstrate control of nano-assemblies growth and shrinkage using microfluidics. To fine-tune differential local environments, peptide nanotubes were confined by micron-scale pillars and subjected to monomer flows of various saturation levels to control assembly and disassembly. The small-volume device allows the rapid adjustment of conditions within the system. A simplified kinetic model was applied to calculate parameters of the growth mechanism. Direct real-time microscopy analysis revealed that different peptide derivatives show unidirectional or bidirectional axial dimension variation. Atomistic simulations show that unidirectional growth is dictated by the differences in the axial ends, as observed in the crystalline order of symmetry. This work lays foundations for the rational control of nano-materials dimensions for applications in biomedicine and material science.

The organization of supramolecular peptide polymers determines their properties; however, controlling their dimensions still remains a problem. Here, Gazit et al. show the spontaneous elongation and shortening of these polymers at an individual nano-assembly level by using a microfluidic platform.

Fabrication of fibrillosomes from droplets stabilized by protein nanofibrils at all-aqueous interfaces

All-aqueous emulsions exploit spontaneous liquid-liquid separation and due to their water-based nature are particular advantageous for the biocompatible storage and processing of biomacromolecules. However, the ultralow interfacial tensions characteristic of all-aqueous interfaces represent an inherent limitation to the use of thermally adsorbed particles to achieve emulsion stability. Here, we use protein nanofibrils to generate colloidosome-like two-dimensional crosslinked networks of nanostructures templated by all-aqueous emulsions, which we term fibrillosomes. We show that this approach not only allows us to operate below the thermal limit at ultra-low surface tensions but also yields structures that are stable even in the complete absence of an interface. Moreover, we show that the growth and multilayer deposition of fibrils allows us to control the thickness of the capsule shells. These results open up the possibility of stabilizing aqueous two-phase systems using natural proteins, and creating self-standing protein capsules without the requirement for three-phase emulsions or water/oil interfaces.

Physical determinants of the self-replication of protein fibrils

The ability of biological molecules to replicate themselves, achieved with the aid of a complex cellular machinery, is the foundation of life. However, a range of aberrant processes involve the self-replication of pathological protein structures without any additional factors. A dramatic example is the autocatalytic replication of pathological protein aggregates, including amyloid fibrils and prions, involved in neurodegenerative disorders. Here, we use computer simulations to identify the necessary requirements for the self-replication of fibrillar assemblies of proteins. We establish that a key physical determinant for this process is the affinity of proteins for the surfaces of fibrils. We find that self-replication can only take place in a very narrow regime of inter-protein interactions, implying a high level of sensitivity to system parameters and experimental conditions. We then compare our theoretical predictions with kinetic and biosensor measurements of fibrils formed from the Aβ peptide associated with Alzheimer's disease. Our results show a quantitative connection between the kinetics of self-replication and the surface coverage of fibrils by monomeric proteins. These findings reveal the fundamental physical requirements for the formation of supra-molecular structures able to replicate themselves, and shed light on mechanisms in play in the proliferation of protein aggregates in nature.

Controlling the Physical Dimensions of Peptide Nanotubes by Supramolecular Polymer Coassembly

Molecular self-assembly of peptides into ordered nanotubes is highly important for various technological applications. Very short peptide building blocks, as short as dipeptides, can form assemblies with unique mechanical, optical, piezoelectric, and semiconductive properties. Yet, the control over nanotube length in solution has remained challenging, due to the inherent sequential self-assembly mechanism. Here, in line with polymer chemistry paradigms, we applied a supramolecular polymer coassembly methodology to modulate peptide nanotube elongation. Utilizing this approach, we achieved a narrow, controllable nanotube length distribution by adjusting the molecular ratio of the diphenylalanine assembly unit and its end-capped analogue. Kinetic analysis suggested a slower coassembly organization process as compared to the self-assembly dynamics of each of the building blocks separately. This is consistent with a hierarchal arrangement of the peptide moieties within the coassemblies. Mass spectrometry analysis demonstrated the bimolecular composition of the coassembled nanostructures. Moreover, the peptide nanotubes' length distribution, as determined by electron microscopy, was shown to fit a fragmentation kinetics model. Our results reveal a simple and efficient mechanism for the control of nanotube sizes through the coassembly of peptide entities at various ratios, allowing for the desired end-product formation. This dynamic size control offers tools for molecular engineering at the nanoscale exploiting the advantages of molecular coassembly.

Synthesis of Nonequilibrium Supramolecular Peptide Polymers on a Microfluidic Platform

The self-assembly of peptides and peptide mimetics into supramolecular polymers has been established in recent years as a route to biocompatible nanomaterials with novel mechanical, optical, and electronic properties. The morphologies of the resulting polymers are usually dictated by the strengths as well as lifetimes of the noncovalent bonds that lead to the formation of the structures. Together with an often incomplete understanding of the assembly mechanisms, these factors limit the control over the formation of polymers with tailored structures. Here, we have developed a microfluidic flow reactor to measure growth rates directly and accurately on the axial and radial faces of crystalline peptide supramolecular polymers. We show that the structures grow through two-dimensional nucleation mechanisms, with rates that depend exponentially on the concentration of soluble peptide. Using these mechanistic insights into the growth behavior of the axial and radial faces, we have been able to tune the aspect ratio of populations of dipeptide assemblies. These results demonstrate a general strategy to control kinetically self-assembly beyond thermodynamic products governed by the intrinsic properties of the building blocks in order to attain the required morphology and function.

Quantitative analysis of co-oligomer formation by amyloid-beta peptide isoforms

Multiple isoforms of aggregation-prone proteins are present under physiological conditions and have the propensity to assemble into co-oligomers with different properties from self-oligomers, but this process has not been quantitatively studied to date. We have investigated the amyloid-β (Aβ) peptide, associated with Alzheimer’s disease, and the aggregation of its two major isoforms, Aβ40 and Aβ42, using a statistical mechanical modelling approach in combination with in vitro single-molecule fluorescence measurements. We find that at low concentrations of Aβ, corresponding to its physiological abundance, there is little free energy penalty in forming co-oligomers, suggesting that the formation of both self-oligomers and co-oligomers is possible under these conditions. Our model is used to predict the oligomer concentration and size at physiological concentrations of Aβ and suggests the mechanisms by which the ratio of Aβ42 to Aβ40 can affect cell toxicity. An increased ratio of Aβ42 to Aβ40 raises the fraction of oligomers containing Aβ42, which can increase the hydrophobicity of the oligomers and thus promote deleterious binding to the cell membrane and increase neuronal damage. Our results suggest that co-oligomers are a common form of aggregate when Aβ isoforms are present in solution and may potentially play a significant role in Alzheimer’s disease.

Fluctuations in the Kinetics of Linear Protein Self-Assembly

Biological systems are characterized by compartmentalization from the subcellular to the tissue level, and thus reactions in small volumes are ubiquitous in living systems. Under such conditions, statistical number fluctuations, which are commonly negligible in bulk reactions, can become dominant and lead to stochastic behavior. We present here a stochastic model of protein filament formation in small volumes. We show that two principal regimes emerge for the system behavior, a small fluctuation regime close to bulk behavior and a large fluctuation regime characterized by single rare events. Our analysis shows that in both regimes the reaction lag-time scales inversely with the system volume, unlike in bulk. Finally, we use our stochastic model to connect data from small-volume microdroplet experiments of amyloid formation to bulk aggregation rates, and show that digital analysis of an ensemble of protein aggregation reactions taking place under microconfinement provides an accurate measure of the rate of primary nucleation of protein aggregates, a process that has been challenging to quantify from conventional bulk experiments.

Dynamics of protein aggregation and oligomer formation governed by secondary nucleation

The formation of aggregates in many protein systems can be significantly accelerated by secondary nucleation, a process where existing assemblies catalyse the nucleation of new species. In particular, secondary nucleation has emerged as a central process controlling the proliferation of many filamentous protein structures, including molecular species related to diseases such as sickle cell anemia and a range of neurodegenerative conditions. Increasing evidence suggests that the physical size of protein filaments plays a key role in determining their potential for deleterious interactions with living cells, with smaller aggregates of misfolded proteins, oligomers, being particularly toxic. It is thus crucial to progress towards an understanding of the factors that control the sizes of protein aggregates. However, the influence of secondary nucleation on the time evolution of aggregate size distributions has been challenging to quantify. This difficulty originates in large part from the fact that secondary nucleation couples the dynamics of species distant in size space. Here, we approach this problem by presenting an analytical treatment of the master equation describing the growth kinetics of linear protein structures proliferating through secondary nucleation and provide closed-form expressions for the temporal evolution of the resulting aggregate size distribution. We show how the availability of analytical solutions for the full filament distribution allows us to identify the key physical parameters that control the sizes of growing protein filaments. Furthermore, we use these results to probe the dynamics of the populations of small oligomeric species as they are formed through secondary nucleation and discuss the implications of our work for understanding the factors that promote or curtail the production of these species with a potentially high deleterious biological activity.

Hamiltonian Dynamics of Protein Filament Formation

We establish the Hamiltonian structure of the rate equations describing the formation of protein filaments. We then show that this formalism provides a unified view of the behavior of a range of biological self-assembling systems as diverse as actin, prions, and amyloidogenic polypeptides. We further demonstrate that the time-translation symmetry of the resulting Hamiltonian leads to previously unsuggested conservation laws that connect the number and mass concentrations of fibrils and allow linear growth phenomena to be equated with autocatalytic growth processes. We finally show how these results reveal simple rate laws that provide the basis for interpreting experimental data in terms of specific mechanisms controlling the proliferation of fibrils.

Molecular mechanisms of protein aggregation from global fitting of kinetic models

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.