Biophysical studies of protein misfolding and aggregation in in vivo models of Alzheimer's and Parkinson's diseases

ProSol-multi: Protein solubility prediction via amino acids multi-level correlation and discriminative distribution

Protein solubility prediction is useful for the careful selection of highly effective candidate proteins for drug development. In recombinant proteins synthesis, solubility prediction is valuable for optimizing key protein characteristics, including stability, functionality, and ease of purification. It contains valuable information about potential biomarkers or therapeutic targets and helps in early forecasting of neurodegenerative diseases, cancer, and cardiovascular disorders. Traditional wet-lab experimental protein solubility prediction approaches are error-prone, time-consuming, and costly. Researchers harnessed the competence of Artificial Intelligence approaches for replacing experimental approaches with computational predictors. These predictors inferred the solubility of proteins by analyzing amino acids distributions in raw protein sequences. There is still a lot of room for the development of robust computational predictors because existing predictors remain fail in extracting comprehensive discriminative distribution of amino acids. To more precisely discriminate soluble proteins from insoluble proteins, this paper presents ProSol-Multi predictor that makes use of a novel MLCDE encoder and Random Forest classifier. MLCDE encoder transforms protein sequences into informative statistical vectors by capturing amino acids multi-level correlation and discriminative distribution within raw protein sequences. The performance of proposed encoder is evaluated against 56 existing protein sequence encoding methods on a widely used protein solubility prediction benchmark dataset under two different experimental settings namely intrinsic and extrinsic. Intrinsic evaluation reveals that from all sequence encoders, proposed MLCDE encoder manages to generate non-overlapping clusters of soluble and insoluble classes. In extrinsic evaluation, 10 machine learning classifiers achieve better performance with proposed MLCDE encoder as compared to 56 existing protein sequence encoders. Moreover, across 4 public benchmark datasets, proposed ProSol-Multi predictor outshines 20 existing predictors by an average accuracy of 3%, MCC and AU-ROC of 2%. ProSol-Multi interactive web application is available at https://sds_genetic_analysis.opendfki.de/ProSol-Multi.

The supersaturation perspective on the amyloid hypothesis

Development of therapeutic interventions for Alzheimer's over the past three decades has been guided by the amyloid hypothesis, which puts Aβ deposition as the initiating event of a pathogenic cascade leading to dementia. In the current form, the amyloid hypothesis lacks a comprehensive framework that considers the complex nature of Aβ aggregation. The explanation of how Aβ deposition leads to downstream pathology, and how reducing Aβ plaque load via anti-amyloid therapy can lead to improvement in cognition remains insufficient. In this perspective we integrate the concept of Aβ supersaturation into the amyloid hypothesis, laying out a framework for the mechanistic understanding and therapeutic intervention of Alzheimer's disease. We discuss the important distinction between in vitro and in vivo patterns of Aβ aggregation, the impact of different aggregation stages on therapeutic strategies, and how future investigations could integrate this concept in order to produce a more thorough understanding and better treatment for Alzheimer's and other amyloid-related disorders.

A protein aggregation platform that distinguishes oligomers from amyloid fibrils

Deposition of aggregated proteins is a pathological feature in many neurodegenerative disorders such as Alzheimer's and Parkinson's. In addition to insoluble amyloid fibrils, protein aggregation leads to the formation of soluble oligomers, which are more toxic and pathogenic than fibrils. However, it is challenging to screen for inhibitors targeting oligomers due to the overlapping processes of oligomerization and fibrillization. Here we report a protein aggregation platform that uses intact and split TEM-1 β-lactamase proteins as reporters of protein aggregation. The intact β-lactamase fused with an amyloid protein can report the overall protein aggregation, which leads to loss of lactamase activity. On the other hand, reconstitution of active β-lactamase from the split lactamase construct requires the formation of amyloid oligomers, making the split lactamase system sensitive to oligomerization. Using Aβ, a protein that forms amyloid plaques in Alzheimer's disease, we show that the growth curves of bacterial cells expressing either intact or split lactamase-Aβ fusion proteins can report changes in the Aβ aggregation. The cell lysate lactamase activity assays show that the oligomer fraction accounts for 20% of total activity for the split lactamase-Aβ construct, but only 3% of total activity for the intact lactamase-Aβ construct, confirming the sensitivity of the split lactamase to oligomerization. The combination of the intact and split lactamase constructs allows the distinction of aggregation modulators targeting oligomerization from those targeting overall aggregation. These low-cost bacterial cell-based and biochemical assays are suitable for high-throughput screening of aggregation inhibitors targeting oligomers of various amyloid proteins.

Structural Proteomic Profiling of Cerebrospinal Fluids to Reveal Novel Conformational Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is the most common representation of dementia, with brain pathological hallmarks of protein abnormal aggregation, such as with amyloid beta and tau protein. It is well established that posttranslational modifications on tau protein, particularly phosphorylation, increase the likelihood of its aggregation and subsequent formation of neurofibrillary tangles, another hallmark of AD. As additional misfolded proteins presumably exist distinctly in AD disease states, which would serve as potential source of AD biomarkers, we used limited proteolysis-coupled with mass spectrometry (LiP-MS) to probe protein structural changes. After optimizing the LiP-MS conditions, we further applied this method to human cerebrospinal fluid specimens collected from healthy control, mild cognitive impairment (MCI), and AD subject groups to characterize proteome-wide misfolding tendencies as a result of disease progression. The fully tryptic peptides embedding LiP sites were compared with the half-tryptic peptides generated from internal cleavage of the same region to determine any structural unfolding or misfolding. We discovered hundreds of significantly up- and down-regulated peptides associated with MCI and AD indicating their potential structural changes in AD progression. Moreover, we detected 53 structurally changed regions in 12 proteins with high confidence between the healthy control and disease groups, illustrating the functional relevance of these proteins with AD progression. These newly discovered conformational biomarker candidates establish valuable future directions for exploring the molecular mechanism of designing therapeutic targets for AD.

Protein quality control and aggregation in the endoplasmic reticulum: From basic to bedside

Endoplasmic reticulum (ER) is the largest membrane-bound compartment in all cells and functions as a key regulator in protein biosynthesis, lipid metabolism, and calcium balance. Mammalian endoplasmic reticulum has evolved with an orchestrated protein quality control system to handle defective proteins and ensure endoplasmic reticulum homeostasis. Nevertheless, the accumulation and aggregation of misfolded proteins in the endoplasmic reticulum may occur during pathological conditions. The inability of endoplasmic reticulum quality control system to clear faulty proteins and aggregates from the endoplasmic reticulum results in the development of many human disorders. The efforts to comprehensively understand endoplasmic reticulum quality control network and protein aggregation will benefit the diagnostics and therapeutics of endoplasmic reticulum storage diseases. Herein, we overview recent advances in mammalian endoplasmic reticulum protein quality control system, describe protein phase transition model, and summarize the approaches to monitor protein aggregation. Moreover, we discuss the therapeutic applications of enhancing endoplasmic reticulum protein quality control pathways in endoplasmic reticulum storage diseases.

Collaboration and knowledge integration for successful brain therapeutics - lessons learned from the pandemic

Brain diseases are a major cause of death and disability worldwide and contribute significantly to years of potential life lost. Although there have been considerable advances in biological mechanisms associated with brain disorders as well as drug discovery paradigms in recent years, these have not been sufficiently translated into effective treatments. This Special Article expands on Keystone Symposia's pre- and post-pandemic panel discussions on translational neuroscience research. In the article, we discuss how lessons learned from the COVID-19 pandemic can catalyze critical progress in translational research, with efficient collaboration bridging the gap between basic discovery and clinical application. To achieve this, we must place patients at the center of the research paradigm. Furthermore, we need commitment from all collaborators to jointly mitigate the risk associated with the research process. This will require support from investors, the public sector and pharmaceutical companies to translate disease mechanisms into world-class drugs. We also discuss the role of scientific publishing in supporting these models of open innovation. Open science journals can now function as hubs to accelerate progress from discovery to treatments, in neuroscience in particular, making this process less tortuous by bringing scientists together and enabling them to exchange data, tools and knowledge effectively. As stakeholders from a broad range of scientific professions, we feel an urgency to advance brain disease therapies and encourage readers to work together in tackling this challenge.

Molecular mechanisms of amyloid formation in living systems

Fibrillar protein aggregation is a hallmark of a variety of human diseases. Examples include the deposition of amyloid-β and tau in Alzheimer's disease, and that of α-synuclein in Parkinson's disease. The molecular mechanisms by which soluble proteins form amyloid fibrils have been extensively studied in the test tube. These investigations have revealed the microscopic steps underlying amyloid formation, and the role of factors such as chaperones that modulate these processes. This perspective explores the question to what extent the mechanisms of amyloid formation elucidated in vitro apply to human disease. The answer is not yet clear, and may differ depending on the protein and the associated disease. Nevertheless, there are striking qualitative similarities between the aggregation behaviour of proteins in vitro and the development of the related diseases. Limited quantitative data obtained in model organisms such as Caenorhabditis elegans support the notion that aggregation mechanisms in vivo can be interpreted using the same biophysical principles established in vitro. These results may however be biased by the high overexpression levels typically used in animal models of protein aggregation diseases. Molecular chaperones have been found to suppress protein aggregation in animal models, but their mechanisms of action have not yet been quantitatively analysed. Several mechanisms are proposed by which the decline of protein quality control with organismal age, but also the intrinsic nature of the aggregation process may contribute to the kinetics of protein aggregation observed in human disease.

Dependence of the Nanoscale Composite Morphology of Fe3O4 Nanoparticle-Infused Lysozyme Amyloid Fibrils on Timing of Infusion: A Combined SAXS and AFM Study

Understanding the formation process and the spatial distribution of nanoparticle (NP) clusters on amyloid fibrils is an essential step for the development of NP-based methods to inhibit aggregation of amyloidal proteins or reverse the assembling trend of the proto-fibrillary complexes that prompts pathogenesis of neuro degeneration. For this, a detailed structural determination of the diverse hybrid assemblies that are forming is needed, which can be achieved by advanced X-ray scattering techniques. Using a combined solution small angle X-ray scattering (SAXS) and atomic force microscopy (AFM) approach, this study investigates the intrinsic trends of the interaction between lysozyme amyloid fibrils (LAFs) and Fe3O4 NPs before and after fibrillization at nanometer resolution. AFM images reveal that the number of NP clusters interacting with the lysozyme fibers does not increase significantly with NP volume concentration, suggesting a saturation in NP aggregation on the fibrillary surface. The data indicate that the number of non-adsorbed Fe3O4 NPs is highly dependent on the timing of NP infusion within the synthesis process. SAXS data yield access to the spatial distribution, aggregation manner and density of NP clusters on the fibrillary surfaces. Employing modern data analysis approaches, the shape and internal structural morphology of the so formed nanocomposites are revealed. The combined experimental approach suggests that while Fe3O4 NPs infusion does not prevent the fibril-formation, the variation of NP concentration and size at different stages of the fibrillization process can impose a pronounced impact on the superficial and internal structural morphologies of these nanocomposites. These findings may be applicable in devising advanced therapeutic treatments for neurodegenerative diseases and designing novel bio-inorganic magnetic devices. Our results further demonstrate that modern X-ray methods give access to the structure of-and insight into the formation process of-biological-inorganic hybrid structures in solution.

Segmental structural dynamics in Aβ42 globulomers

Aβ42 aggregation plays a central role in the pathogenesis of Alzheimer's disease. In addition to the insoluble fibrils that comprise the amyloid plaques, Aβ42 also forms soluble aggregates collectively called oligomers, which are more toxic and pathogenic than fibrils. Understanding the structure and dynamics of Aβ42 oligomers is critical for developing effective therapeutic interventions against these oligomers. Here we studied the structural dynamics of Aβ42 globulomers, a type of Aβ42 oligomers prepared in the presence of sodium dodecyl sulfate, using site-directed spin labeling. Spin labels were introduced, one at a time, at all 42 residue positions of Aβ42 sequence. Electron paramagnetic resonance spectra of spin-labeled samples reveal four structural segments based on site-dependent spin label mobility pattern. Segment-1 consists of residues 1-6, which have the highest mobility that is consistent with complete disorder. Segment-3 is the most immobilized region, including residues 31-34. Segment-2 and -4 have intermediate mobility and are composed of residues 7-30 and 35-42, respectively. Considering the inverse relationship between protein dynamics and stability, our results suggest that residues 31-34 are the most stable segment in Aβ42 oligomers. At the same time, the EPR spectral lineshape suggests that Aβ42 globulomers lack a well-packed structural core akin to that of globular proteins.

Effect of spin labelling on the aggregation kinetics of yeast prion protein Ure2

Amyloid formation is involved in a wide range of neurodegenerative diseases including Alzheimer's and prion diseases. Structural understanding of the amyloid is critical to delineate the mechanism of aggregation and its pathological spreading. Site-directed spin labelling has emerged as a powerful structural tool in the studies of amyloid structures and provided structural evidence for the parallel in-register β-sheet structure for a wide range of amyloid proteins. It is generally accepted that spin labelling does not disrupt the structure of the amyloid fibrils, the end product of protein aggregation. The effect on the rate of protein aggregation, however, has not been well characterized. Here, we employed a scanning mutagenesis approach to study the effect of spin labelling on the aggregation rate of 79 spin-labelled variants of the Ure2 prion domain. The aggregation of Ure2 protein is the basis of yeast prion [URE3]. We found that all spin-labelled Ure2 mutants aggregated within the experimental timeframe of 15 to 40 h. Among the 79 spin-labelled positions, only five residue sites (N23, N27, S33, I35 and G42) showed a dramatic delay in the aggregation rate as a result of spin labelling. These positions may be important for fibril nucleation, a rate-limiting step in aggregation. Importantly, spin labelling at most of the sites had a muted effect on Ure2 aggregation kinetics, showing a general tolerance of spin labelling in protein aggregation studies.