Mechanics and kinetics of dynamic instability.

During dynamic instability, self-assembling microtubules (MTs) stochastically alternate between phases of growth and shrinkage. This process is driven by the presence of two distinct states of MT subunits, GTP- and GDP-bound tubulin dimers, that have different structural properties. Here, we use a combination of analysis and computer simulations to study the mechanical and kinetic regulation of dynamic instability in three-dimensional (3D) self-assembling MTs. Our model quantifies how the 3D structure and kinetics of the distinct states of tubulin dimers determine the mechanical stability of MTs. We further show that dynamic instability is influenced by the presence of quenched disorder in the state of the tubulin subunit as reflected in the fraction of non-hydrolysed tubulin. Our results connect the 3D geometry, kinetics and statistical mechanics of these tubular assemblies within a single framework, and may be applicable to other self-assembled systems where these same processes are at play

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

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.We are grateful to St. John’s College, Cambridge (T. C. T. M., J. B. K.), the Schiff Foundation (A. J. D.), the EPSRC (K. L. S.), NSF Grant No. DMR-1310266 (D. A. W.), the Harvard MRSEC Grant No. DMR1420570 (D. A. W.), BBSRC (T. P. J. K.), ERC (T. C. T. M., T. P. J. K.), and Frances and Augustus Newman Foundation (T. P. J. K.) for financial support

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.The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) through the ERC grant PhysProt (agreement no 337969) (T.P.J.K., M.A.W., and T.C.T.M.). In addition, we are grateful for financial support from the Frances and Augustus Newman Foundation (T.P.J.K. and M.A.W.), the Marie Curie Fellowship scheme (P.A.), the Cambridge Commonwealth, European and International Trust (M.M.J.B.), the NIH-Oxford Cambridge Scholars Programme (M.M.J.B.), St John’s College Cambridge (T.C.T.M.), the Swiss National Science Foundation (T.C.T.M.), and the Biotechnology and Biological Sciences Research Council (T.M.). F. A. A. is supported by a Senior Research Fellowship award from the Alzheimer’s Society, UK (grant number 317, AS-SF-16-003). This work was in part supported by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases at the National Institutes of Health (M.M.J.B.) and the Centre for Misfolding Diseases, Cambridge, UK

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

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.The authors are grateful for financial support provided by Dr Tayyeb Hussain Scholarship and the ERC (669237) (M. Iljina), the Schiff Foundation (A. Dear), Alzheimer’s Research UK and Marie-Curie Individual Fellowship (S. De), a fellowship from Fondazione Caritro, Trento (BANDO 2017 PER PROGETTI DI RICERCA SVOLTI DA GIOVANI RICERCATORI POST-DOC) (L. Tosatto), the Boehringer Ingelheim Fonds and the Studienstiftung des deutschen Volkes (P. Flagmeier), the Centre for Misfolding Diseases (A. Dear, P. Flagmeier, C. Dobson, T. Knowles), the ERC (669237) and the Royal Society (D. Klenerman). We are grateful to S. Preet for the expression and purification of A90C ɑS. We thank Y. Ye for providing tau k18

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

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