Julius B. Kirkegaard

Differences in nucleation behavior underlie the contrasting aggregation kinetics of the Aβ40 and Aβ42 peptides

Significance Alzheimers disease and several related disorders are associated with the assembly of specific proteins into ordered fibrillar aggregates. In Alzheimers disease, the key component of pathological aggregates, the Aβ peptide, is produced from a precursor protein in variable lengths: Aβ40 is more abundant and Aβ42 more aggregation-prone. To shed light on the molecular basis of disease progression, the aggregation process has been studied in vitro. New theoretical models allow us to relate kinetic measurements to the rates of the individual processes underlying the aggregation reaction. We find that the loss of two residues in Aβ40 relative to Aβ42 significantly slows nucleation of aggregates in solution, thereby shifting the mechanism yet more strongly towards nucleation on the surface of fibrils. The two major forms of the amyloid-beta (Aβ) peptide found in plaques in patients suffering from Alzheimer’s disease, Aβ40 and Aβ42, only differ by two amino acids in the C-terminal region, yet they display markedly different aggregation behavior. The origins of these differences have remained challenging to connect to specific molecular-level processes underlying the aggregation reaction. In this paper we use a general strategy to apply the conventional workflow of chemical kinetics to the aggregation of the Aβ40 peptide to identify the differences between Aβ40 and Aβ42 in terms of the microscopic determinants of the aggregation reaction. Our results reveal that the major source of aggregates in the case of Aβ40 is a fibril-catalyzed nucleation process, the multistep nature of which is evident through its saturation behavior. Moreover, our results show that the significant differences in the observed behavior of the two proteins originate not simply from a uniform increase in all microscopic rates for Aβ42 compared with Aβ40, but rather are due to a shift of more than one order of magnitude in the relative importance of primary nucleation versus fibril-catalyzed secondary nucleation processes. This analysis sheds light on the microscopic determinants of the aggregation behavior of the principal forms of Aβ and outlines a general approach toward achieving an understanding at the molecular level of the aberrant deposition of insoluble peptides in neurodegenerative disorders.

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 Alzheimers and Parkinsons 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.

A natural product inhibits the initiation of α-synuclein aggregation and suppresses its toxicity

Significance Parkinson’s disease is characterized by the presence in brain tissues of aberrant aggregates primarily formed by the protein α-synuclein. It has been difficult, however, to identify compounds capable of preventing the formation of such deposits because of the complexity of the aggregation process of α-synuclein. By exploiting recently developed highly quantitative in vitro assays, we identify a compound, squalamine, that blocks α-synuclein aggregation, and characterize its mode of action. Our results show that squalamine, by competing with α-synuclein for binding lipid membranes, specifically inhibits the initiation of the aggregation process of α-synuclein and abolishes the toxicity of α-synuclein oligomers in neuronal cells and in an animal model of Parkinson’s disease. The self-assembly of α-synuclein is closely associated with Parkinson’s disease and related syndromes. We show that squalamine, a natural product with known anticancer and antiviral activity, dramatically affects α-synuclein aggregation in vitro and in vivo. We elucidate the mechanism of action of squalamine by investigating its interaction with lipid vesicles, which are known to stimulate nucleation, and find that this compound displaces α-synuclein from the surfaces of such vesicles, thereby blocking the first steps in its aggregation process. We also show that squalamine almost completely suppresses the toxicity of α-synuclein oligomers in human neuroblastoma cells by inhibiting their interactions with lipid membranes. We further examine the effects of squalamine in a Caenorhabditis elegans strain overexpressing α-synuclein, observing a dramatic reduction of α-synuclein aggregation and an almost complete elimination of muscle paralysis. These findings suggest that squalamine could be a means of therapeutic intervention in Parkinson’s disease and related conditions.

Easyworm: an open-source software tool to determine the mechanical properties of worm-like chains

BackgroundA growing spectrum of applications for natural and synthetic polymers, whether in industry or for biomedical research, demands for fast and universally applicable tools to determine the mechanical properties of very diverse polymers. To date, determining these properties is the privilege of a limited circle of biophysicists and engineers with appropriate technical skills.FindingsEasyworm is a user-friendly software suite coded in MATLAB that simplifies the image analysis of individual polymeric chains and the extraction of the mechanical properties of these chains. Easyworm contains a comprehensive set of tools that, amongst others, allow the persistence length of single chains and the Young’s modulus of elasticity to be calculated in multiple ways from images of polymers obtained by a variety of techniques (e.g. atomic force microscopy, electron, contrast-phase, or epifluorescence microscopy).ConclusionsEasyworm thus provides a simple and efficient tool for specialists and non-specialists alike to solve a common problem in (bio)polymer science. Stand-alone executables and shell scripts are provided along with source code for further development.

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.

Motility of Colonial Choanoflagellates and the Statistics of Aggregate Random Walkers

We illuminate the nature of the three-dimensional random walks of microorganisms composed of individual organisms adhered together. Such aggregate random walkers are typified by choanoflagellates, eukaryotes that are the closest living relatives of animals. In the colony-forming species Salpingoeca rosetta we show that the beating of each flagellum is stochastic and uncorrelated with others, and the vectorial sum of the flagellar propulsion manifests as stochastic helical swimming. A quantitative theory for these results is presented and species variability discussed.

Aerotaxis in the closest relatives of animals.

As the closest unicellular relatives of animals, choanoflagellates serve as useful model organisms for understanding the evolution of animal multicellularity. An important factor in animal evolution was the increasing ocean oxygen levels in the Precambrian, which are thought to have influenced the emergence of complex multicellular life. As a first step in addressing these conditions, we study here the response of the colony-forming choanoflagellate Salpingoeca rosetta to oxygen gradients. Using a microfluidic device that allows spatio-temporal variations in oxygen concentrations, we report the discovery that S. rosetta displays positive aerotaxis. Analysis of the spatial population distributions provides evidence for logarithmic sensing of oxygen, which enhances sensing in low oxygen neighborhoods. Analysis of search strategy models on the experimental colony trajectories finds that choanoflagellate aerotaxis is consistent with stochastic navigation, the statistics of which are captured using an effective continuous version based on classical run-and-tumble chemotaxis. DOI: http://dx.doi.org/10.7554/eLife.18109.001

Filter-feeding, near-field flows, and the morphologies of colonial choanoflagellates

Efficient uptake of prey and nutrients from the environment is an important component in the fitness of all microorganisms, and its dependence on size may reveal clues to the origins of evolutionary transitions to multicellularity. Because potential benefits in uptake rates must be viewed in the context of other costs and benefits of size, such as varying predation rates and the increased metabolic costs associated with larger and more complex body plans, the uptake rate itself is not necessarily that which is optimized by evolution. Uptake rates can be strongly dependent on local organism geometry and its swimming speed, providing selective pressure for particular arrangements. Here we examine these issues for choanoflagellates, filter-feeding microorganisms that are the closest relatives of the animals. We explore the different morphological variations of the choanoflagellate Salpingoeca rosetta, which can exist as a swimming cell, as a sessile thecate cell, and as colonies of cells in various shapes. In the absence of other requirements and in a homogeneously nutritious environment, we find that the optimal strategy to maximize filter-feeding by the collar of microvilli is to swim fast, which favors swimming unicells. In large external flows, the sessile thecate cell becomes advantageous. Effects of prey diffusion are discussed and also found to be to the advantage of the swimming unicell.

Massively parallel C. elegans tracking provides multi-dimensional fingerprints for phenotypic discovery

BACKGROUND The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. NEW METHOD We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. RESULTS We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimers and Parkinsons diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. COMPARISON WITH EXISTING METHODS The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. CONCLUSIONS The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism.

Multistep Inhibition of α-Synuclein Aggregation and Toxicity in Vitro and in Vivo by Trodusquemine

The aggregation of α-synuclein, an intrinsically disordered protein that is highly abundant in neurons, is closely associated with the onset and progression of Parkinsons disease. We have shown previously that the aminosterol squalamine can inhibit the lipid induced initiation process in the aggregation of α-synuclein, and we report here that the related compound trodusquemine is capable of inhibiting not only this process but also the fibril-dependent secondary pathways in the aggregation reaction. We further demonstrate that trodusquemine can effectively suppress the toxicity of α-synuclein oligomers in neuronal cells, and that its administration, even after the initial growth phase, leads to a dramatic reduction in the number of α-synuclein inclusions in a Caenorhabditis elegans model of Parkinsons disease, eliminates the related muscle paralysis, and increases lifespan. On the basis of these findings, we show that trodusquemine is able to inhibit multiple events in the aggregation process of α-synuclein and hence to provide important information about the link between such events and neurodegeneration, as it is initiated and progresses. Particularly in the light of the previously reported ability of trodusquemine to cross the blood-brain barrier and to promote tissue regeneration, the present results suggest that this compound has the potential to be an important therapeutic candidate for Parkinsons disease and related disorders.