Single-molecule fluorescence imaging and deep learning reveal highly heterogeneous aggregation of amyloid-β 42

Single-Molecule Characterization of Heterogeneous Oligomer Formation during Co-Aggregation of 40- and 42-Residue Amyloid-β

The two most abundant isoforms of amyloid-β (Aβ) are the 40- (Aβ40) and 42-residue (Aβ42) peptides. Since they coexist and there is a correlation between toxicity and the ratio of the two isoforms, quantitative characterization of their interactions is crucial for understanding the Aβ aggregation mechanism. In this work, we follow the aggregation of individual isoforms in a mixture using single-molecule FRET spectroscopy by labeling Aβ42 and Aβ40 with the donor and acceptor fluorophores, respectively. We found that there are two phases of aggregation. The first phase consists of coaggregation of Aβ42 with a small amount of Aβ40, while the second phase results mostly from aggregation of Aβ40. We also found that the aggregation of Aβ42 is slowed by Aβ40 while the aggregation of Aβ40 is accelerated by Aβ42 in a concentration-dependent manner. The formation of oligomers was monitored by incubating mixtures in a plate reader and performing a single-molecule free-diffusion experiment at several different stages of aggregation. The detailed properties of the oligomers were obtained by maximum likelihood analysis of fluorescence bursts. The FRET efficiency distribution is much broader than that of the Aβ42 oligomers, indicating the diversity in isoform composition of the oligomers. Pulsed interleaved excitation experiments estimate that the fraction of Aβ40 in the co-oligomers in a 1:1 mixture of Aβ42 and Aβ40 varies between 0 and 20%. The detected oligomers were mostly co-oligomers especially at the physiological ratio of Aβ42 and Aβ40 (1:10), suggesting the critical role of Aβ40 in oligomer formation and aggregation.

Fluorescence-Based Monitoring of Early-Stage Aggregation of Amyloid-β, Amylin Peptide, Tau, and α-Synuclein Proteins

Early-stage aggregates of amyloid-forming proteins, specifically soluble oligomers, are implicated in neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Huntington's disease. Protein aggregation is typically monitored by fluorescence using the amyloid-binding fluorophore thioflavin T (ThT). Thioflavin T interacts, however, preferentially with fibrillar amyloid structures rather than with soluble, early-stage aggregates. In contrast, the two fluorophores, aminonaphthalene 2-cyanoacrylate-spiropyran (AN-SP) and triazole-containing boron-dipyrromethene (taBODIPY), were reported to bind preferentially to early-stage aggregates of amyloidogenic proteins. The present study compares ThT with AN-SP and taBODIPY with regard to their ability to monitor early stages of aggregation of four different amyloid-forming proteins, including amyloid-β (Aβ), tau protein, amylin, and α-synuclein. The results show that the three fluorophores vary in their suitability to monitor the early aggregation of different amyloid-forming proteins. For instance, in the presence of Aβ and amylin, the fluorescence intensity of AN-SP increased at an earlier stage of aggregation than the fluorescence of ThT, albeit with only a small fluorescence increase in the case of AN-SP. In contrast, in the presence of tau and amylin, the fluorescence intensity of taBODIPY increased at an earlier stage of aggregation than the fluorescence of ThT. Finally, α-synuclein aggregation could only be monitored by ThT fluorescence; neither AN-SP nor taBODIPY showed a significant increase in fluorescence over the course of aggregation of α-synuclein. These results demonstrate the ability of AN-SP and taBODIPY to monitor the formation of early-stage aggregates from specific amyloid-forming proteins at an early stage of aggregation, although moderate increases in fluorescence intensity, relatively large uncertainties in fluorescence values, and limited solubility of both fluorophores limit their usefulness for some amyloid proteins. The capability to monitor early aggregation of some amyloid proteins, such as amylin, might accelerate the discovery of aggregation inhibitors to minimize the formation of toxic oligomeric species for potential therapeutic use.

A Perspective on How Fibrinaloid Microclots and Platelet Pathology May be Applied in Clinical Investigations

Microscopy imaging has enabled us to establish the presence of fibrin(ogen) amyloid (fibrinaloid) microclots in a range of chronic, inflammatory diseases. Microclots may also be induced by a variety of purified substances, often at very low concentrations. These molecules include bacterial inflammagens, serum amyloid A, and the S1 spike protein of severe acute respiratory syndrome coronavirus 2. Here, we explore which of the properties of these microclots might be used to contribute to differential clinical diagnoses and prognoses of the various diseases with which they may be associated. Such properties include distributions in their size and number before and after the addition of exogenous thrombin, their spectral properties, the diameter of the fibers of which they are made, their resistance to proteolysis by various proteases, their cross-seeding ability, and the concentration dependence of their ability to bind small molecules including fluorogenic amyloid stains. Measuring these microclot parameters, together with microscopy imaging itself, along with methodologies like proteomics and imaging flow cytometry, as well as more conventional assays such as those for cytokines, might open up the possibility of a much finer use of these microclot properties in generative methods for a future where personalized medicine will be standard procedures in all clotting pathology disease diagnoses.

Structure of cytotoxic amyloid oligomers generated during disaggregation

Amyloidosis is characterized by the abnormal accumulation of amyloid proteins. The causative proteins aggregate from monomers to oligomers and fibrils, among which some intermediate oligomers are considered as major toxins. Cytotoxic oligomers are generated not only by aggregation but also via fibril disaggregation. However, little is known about the structural characteristics and generation conditions of cytotoxic oligomers produced during disaggregation. Herein, we summarized the structural commonalities of cytotoxic oligomers formed under various disaggregation conditions, including the addition of heat shock proteins or small compounds. In vitro experimental data demonstrated the presence of high-molecular-weight oligomers (protofibrils or protofilaments) that exhibited a fibrous morphology and β-sheet structure. Molecular dynamics simulations indicated that the distorted β-sheet structure contributed to their metastability. The tendency of these cytotoxic oligomers to appear under mild disaggregation conditions, implied formation during the early stages of disaggregation. This review will aid researchers in exploring the characteristics of highly cytotoxic oligomers and developing drugs that target amyloid aggregates.

Fusion of amyloid beta with ferritin yields an isolated oligomeric beta-sheet-rich aggregate inside the ferritin cage

Alzheimer's disease is a severe brain condition caused by the formation of amyloid plaques composed of amyloid beta (Aβ) peptides. These peptides form oligomers, protofibrils, and fibrils before deposition into amyloid plaques. Among these intermediates, Aβ oligomers (AβOs) were found to be the most toxic and therefore an appealing target for drug development and understanding their role in the disease. However, precise isolation and characterization of AβOs have proven challenging because AβOs tend to aggregate and form heterogeneous mixtures in solution. As a solution, we genetically fused the Aβ peptide with a ferritin monomer. Such fusion allowed the encapsulation of precisely 24 Aβ peptides inside the 24-mer ferritin cage. Using high-speed atomic force microscopy (HS-AFM), we disassembled ferritin and directly visualized the Aβ core enclosed within the cage. The thioflavin-T assay (ThT) and attenuated total reflection infrared spectroscopy (ATR-IR) revealed the presence of a β-sheet structure in the encapsulated oligomeric aggregate. Gallic acid, an amyloid inhibitor, can inhibit the fluorescence of ThT bound AβOs. Our approach represents a significant advancement in the isolation and characterization of β-sheet rich AβOs and is expected to be useful for future studies of other disordered peptides such as α-synuclein and tau.

Co-translational formation of disulfides guides folding of the SARS-CoV-2 receptor binding domain

Many secreted proteins, including viral proteins, contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that the RBD can only refold reversibly if its native disulfides are present before folding. But in their absence, the RBD spontaneously misfolds into a nonnative, molten-globule-like state that is structurally incompatible with complete disulfide formation and that is highly prone to aggregation. Thus, the RBD native structure represents a metastable state on the protein's energy landscape with reduced disulfides, indicating that nonequilibrium mechanisms are needed to ensure native disulfides form before folding. Our atomistic simulations suggest that this may be achieved via co-translational folding during RBD secretion into the endoplasmic reticulum. Namely, at intermediate translation lengths, native disulfide pairs are predicted to come together with high probability, and thus, under suitable kinetic conditions, this process may lock the protein into its native state and circumvent highly aggregation-prone nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

Single-molecule FRET and molecular diffusion analysis characterize stable oligomers of amyloid-β 42 of extremely low population

Soluble oligomers produced during protein aggregation have been thought to be toxic species causing various diseases. Characterization of these oligomers is difficult because oligomers are a heterogeneous mixture, which is not readily separable, and may appear transiently during aggregation. Single-molecule spectroscopy can provide valuable information by detecting individual oligomers, but there have been various problems in determining the size and concentration of oligomers. In this work, we develop and use a method that analyzes single-molecule fluorescence burst data of freely diffusing molecules in solution based on molecular diffusion theory and maximum likelihood method. We demonstrate that the photon count rate, diffusion time, population, and Förster resonance energy transfer (FRET) efficiency can be accurately determined from simulated data and the experimental data of a known oligomerization system, the tetramerization domain of p53. We used this method to characterize the oligomers of the 42-residue amyloid-β (Aβ42) peptide. Combining peptide incubation in a plate reader and single-molecule free-diffusion experiments allows for the detection of stable oligomers appearing at various stages of aggregation. We find that the average size of these oligomers is 70-mer and their overall population is very low, less than 1 nM, in the early and middle stages of aggregation of 1 µM Aβ42 peptide. Based on their average size and long diffusion time, we predict the oligomers have a highly elongated rod-like shape.

Single-Molecule Orientation Imaging Reveals Two Distinct Binding Configurations on Amyloid Fibrils

Fluorescence readouts for an amyloid fibril sensor critically depend on its molecular interaction and local environment offered by the available structural motifs. Here we employ polarized points accumulation for imaging in nanoscale topography with intramolecular charge transfer probes transiently bound to amyloid fibrils to investigate the organization of fibril nanostructures and probe binding configurations. Besides the in-plane (θ ≈ 90°) mode for binding on the fibril surface parallel to the long fibril axis, we also observed a sizable population of over 60% out-of-plane (θ < 60°) dipoles for rotor probes experiencing a varying degree of orientational mobility. Highly confined dipoles exhibiting an out-of-plane configuration probably reflect tightly bound dipoles in the inner channel grooves, while the weakly bound ones on amyloid enjoy rotational flexibility. Our observation of an out-of-plane binding mode emphasizes the pivotal role played by the electron donor amino group toward fluorescence detection and hence the emergence of anchored probes alongside conventional groove binders.

Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages

The transition from a disordered to an assembly-competent monomeric state (N*) in amyloidogenic sequences is a crucial event in the aggregation cascade. Using a well-calibrated model for intrinsically disordered proteins (IDPs), we show that the N* states, which bear considerable resemblance to the polymorphic fibril structures found in experiments, not only appear as excitations in the free energy landscapes of Aβ40 and Aβ42, but also initiate the aggregation cascade. For Aβ42, the transitions to the different N* states are in accord with Ostwald's rule of stages, with the least stable structures forming ahead of thermodynamically favored ones. The Aβ40 and Aβ42 monomer landscapes exhibit different extents of local frustration, which we show have profound implications in dictating subsequent self-assembly. Using kinetic transition networks, we illustrate that the most favored dimerization routes proceed via N* states. We argue that Ostwald's rule also holds for the aggregation of fused in sarcoma and polyglutamine proteins.

Quantitative proteomics of tau and Aβ in detergent fractions from Alzheimer's disease brains

The two hallmarks of Alzheimer's disease (AD) are amyloid-β (Aβ) plaques and neurofibrillary tangles marked by phosphorylated tau. Increasing evidence suggests that aggregating Aβ drives tau accumulation, a process that involves synaptic degeneration leading to cognitive impairment. Conversely, there is a realization that non-fibrillar (oligomeric) forms of Aβ mediate toxicity in AD. Fibrillar (filamentous) aggregates of proteins across the spectrum of the primary and secondary tauopathies were the focus of recent structural studies with a filament structure-based nosologic classification, but less emphasis was given to non-filamentous co-aggregates of insoluble proteins in the fractions derived from post-mortem human brains. Here, we revisited sarkosyl-soluble and -insoluble extracts to characterize tau and Aβ species by quantitative targeted mass spectrometric proteomics, biochemical assays, and electron microscopy. AD brain sarkosyl-insoluble pellets were greatly enriched with Aβ₄₂ at almost equimolar levels to N-terminal truncated microtubule-binding region (MTBR) isoforms of tau with multiple site-specific post-translational modifications (PTMs). MTBR R3 and R4 tau peptides were most abundant in the sarkosyl-insoluble materials with a 10-fold higher concentration than N-terminal tau peptides. This indicates that the major proportion of the enriched tau was the aggregation-prone N-terminal and proline-rich region (PRR) of truncated mixed 4R and 3R tau with more 4R than 3R isoforms. High concentration and occupancies of site-specific phosphorylation pT₁₈₁ (~22%) and pT₂₁₇ (~16%) (key biomarkers of AD) along with other PTMs in the PRR and MTBR indicated a regional susceptibility of PTMs in aggregated tau. Immunogold labelling revealed that tau may exist in globular non-filamentous form (N-terminal intact tau) co-localized with Aβ in the sarkosyl-insoluble pellets along with tau filaments (N-truncated MTBR tau). Our results suggest a model that Aβ and tau interact forming globular aggregates, from which filamentous tau and Aβ emerge. These characterizations contribute towards unravelling the sequence of events which lead to end-stage AD changes.

Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domain

Many secreted proteins contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that, whereas RBD can refold reversibly when its disulfides are intact, their disruption causes misfolding into a nonnative molten-globule state that is highly prone to aggregation and disulfide scrambling. Thus, non-equilibrium mechanisms are needed to ensure disulfides form prior to folding in vivo. Our simulations suggest that co-translational folding may accomplish this, as native disulfide pairs are predicted to form with high probability at intermediate lengths, ultimately committing the RBD to its metastable native state and circumventing nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

Deep learning in single-molecule imaging and analysis: recent advances and prospects

Single-molecule microscopy is advantageous in characterizing heterogeneous dynamics at the molecular level. However, there are several challenges that currently hinder the wide application of single molecule imaging in bio-chemical studies, including how to perform single-molecule measurements efficiently with minimal run-to-run variations, how to analyze weak single-molecule signals efficiently and accurately without the influence of human bias, and how to extract complete information about dynamics of interest from single-molecule data. As a new class of computer algorithms that simulate the human brain to extract data features, deep learning networks excel in task parallelism and model generalization, and are well-suited for handling nonlinear functions and extracting weak features, which provide a promising approach for single-molecule experiment automation and data processing. In this perspective, we will highlight recent advances in the application of deep learning to single-molecule studies, discuss how deep learning has been used to address the challenges in the field as well as the pitfalls of existing applications, and outline the directions for future development.

Toward high-throughput oligomer detection and classification for early-stage aggregation of amyloidogenic protein

Aggregation kinetics of proteins and peptides have been studied extensively due to their significance in many human diseases, including neurodegenerative disorders, and the roles they play in some key physiological processes. However, most of these studies have been performed as bulk measurements using Thioflavin T or other fluorescence turn-on reagents as indicators of fibrillization. Such techniques are highly successful in making inferences about the nucleation and growth mechanism of fibrils, yet cannot directly measure assembly reactions at low protein concentrations which is the case for amyloid-β (Aβ) peptide under physiological conditions. In particular, the evolution from monomer to low-order oligomer in early stages of aggregation cannot be detected. Single-molecule methods allow direct access to such fundamental information. We developed a high-throughput protocol for single-molecule photobleaching experiments using an automated fluorescence microscope. Stepwise photobleaching analysis of the time profiles of individual foci allowed us to determine stoichiometry of protein oligomers and probe protein aggregation kinetics. Furthermore, we investigated the potential application of supervised machine learning with support vector machines (SVMs) as well as multilayer perceptron (MLP) artificial neural networks to classify bleaching traces into stoichiometric categories based on an ensemble of measurable quantities derivable from individual traces. Both SVM and MLP models achieved a comparable accuracy of more than 80% against simulated traces up to 19-mer, although MLP offered considerable speed advantages, thus making it suitable for application to high-throughput experimental data. We used our high-throughput method to study the aggregation of Aβ40 in the presence of metal ions and the aggregation of α-synuclein in the presence of gold nanoparticles.