Biology subjects

Vendruscolo, M.

Publications and source records attributed to Vendruscolo, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Ca2+-driven PDIA6 phase separation to ensure proinsulin quality control

The endoplasmic reticulum (ER) plays key roles in protein quality control1,2 and dynamic Ca2+ storage3,4 in eukaryotic cells. However, the protein homeostasis (proteostasis) system that regulates these ER functions is still incompletely characterised. Previous study revealed the importance of oligomerization in the function PDIA1, an ER-resident disulfide isomerase and molecular chaperone, regulates oligomeric states in accordance with client folding5. This result suggests that at least some of the 20 members of other PDI family may undergo regulated self-assembly in order to optimally function. Here, we show that Ca2+ triggers the phase separation of PDIA6 into liquid-like condensates. In contrast to the condensation mechanism observed for proteins containing low-complexity domains, our results indicate that transient but specific electrostatic interactions occur between the first and the third folded thioredoxin-like domains of PDIA6. We further show that the Ca2+-driven condensation of PDIA6 recruits PDIA3 and proinsulin, thus increasing their local concentrations. This process results in the 30-fold enhancement of proinsulin folding and in the inhibition of proinsulin aggregation. Our findings shed light on a condensation-driven Ca2+-mediated proteostasis cascade in the ER by revealing how the efficiency of the protein folding process can be enhanced within quality control granules.

biochemistry↗

bioRxiv2024

Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery

Recent advances in machine learning methods for materials science have significantly enhanced accurate predictions of the properties of novel materials. Here, we explore whether these advances can be adapted to drug discovery by addressing the problem of prospective validation - the assessment of the performance of a method on out-of-distribution data. First, we tested whether k-fold n-step forward cross-validation could improve the accuracy of out-of-distribution small molecule bioactivity predictions. We found that it is more helpful than conventional random split cross-validation in describing the accuracy of a model in real-world drug discovery settings. We also analyzed discovery yield and novelty error, finding that these two metrics provide an understanding of the applicability domain of models and an assessment of their ability to predict molecules with desirable bioactivity compared to other small molecules. Based on these results, we recommend incorporating a k-fold n-step forward cross-validation and these metrics when building state-of-the-art models for bioactivity prediction in drug discovery.

bioinformatics↗

bioRxiv2024

The diversity of SNCA transcripts in neurons, and its impact on antisense oligonucleotide therapeutics

The role of the SNCA gene locus in driving Parkinsons disease (PD) through rare and common genetic variation is well-recognized, but the transcriptional diversity of SNCA in vulnerable cell types remains unclear. We performed SNCA long-read RNA sequencing in human dopaminergic neurons and show that annotated SNCA transcripts account for only 5% of expression. Rather, the majority of expression (75%) at the SNCA locus originates from transcripts with alternative 5 and 3 untranslated regions. Importantly, 10% originates from transcripts encoding open reading frames not previously annotated, which are translated and detectable in human postmortem brain. Defining the 3 untranslated regions enabled the rational design of antisense oligonucleotides targeting the majority of SNCA transcripts, leading to the effective reversal of PD pathology, including protein aggregation, mitochondrial dysfunction, and toxicity. Resolving the complexity of the SNCA transcriptional landscape impacts RNA therapies and highlights differences in protein isoforms and their contribution to disease.

neuroscience↗

bioRxiv2024

Large-scale visualisation of α-synuclein oligomers in Parkinson's disease brain tissue

Parkinsons disease (PD) is a common neurodegenerative condition characterised by the presence in the brain of large intraneuronal aggregates, known as Lewy bodies and Lewy neurites, containing fibrillar -synuclein. According to the amyloid hypothesis, these large end-stage species form from smaller soluble protein assemblies, often termed oligomers, which are proposed as early drivers of pathogenesis. To date, however, this hypothesis has remained controversial, at least in part because it has not been possible to directly visualise oligomeric aggregates in human brain tissue. Therefore, their presence, abundance and distributions have remained elusive. Here, we present ASA-PD (Advanced Sensing of Aggregates - Parkinsons Disease), an imaging method to generate large-scale -synuclein oligomer maps in post-mortem human brain tissue. We combined autofluorescence suppression with single-molecule fluorescence methods, which together, enable the detection of nanoscale -synuclein aggregates. To demonstrate the utility of this platform, we captured [~]1.2 million oligomers from the anterior cingulate cortex in human post-mortem brain samples from PD and healthy control patients. Our data revealed a specific subpopulation of nanoscale oligomers that represent an early hallmark of the proteinopathy that underlies PD. We anticipate that quantitative information about oligomer distributions provided by ASA-PD will enable mechanistic studies to reveal the pathological processes caused by -synuclein aggregation.

neuroscience↗

bioRxiv2024

Imaging Abeta aggregation by liquid-phase transmission electron microscopy

The amyloid beta peptide (A{beta}) readily aggregates into amyloid fibrils. This process has been the subject of intense investigations since it is associated with Alzheimers disease. However, it has been highly challenging to observe the microscopic steps in the aggregation reaction directly and to characterize the oligomeric assemblies formed as intermediates. To achieve this goal, we apply liquid-phase transmission electron microscopy (LTEM) in combination with all-atom molecular dynamics simulations. Our results offer an initial visualization of the dynamics of A{beta} oligomers, the formation of A{beta} protofibrils, and the presence of A{beta} oligomers on the surface of A{beta} fibrils. This work illustrates how the application of LTEM to the study of protein aggregation in solution enables the imaging of key molecular events in the aggregation process of A{beta}.

biophysics↗

bioRxiv2024

The Alzheimer's Aβ peptide forms biomolecular condensates that trigger amyloid aggregation

The onset and development of Alzheimers disease (AD) is linked to the accumulation of pathological aggregates formed from the normally monomeric amyloid-{beta} peptide within the central nervous system. These A{beta} aggregates are increasingly successfully targeted with clinical therapies, but the fundamental molecular steps that trigger the initial nucleation event leading to the conversion of monomeric A{beta} peptide into pathological aggregates remain unknown. Here we show that the A{beta} peptide can form biomolecular condensates on lipid bilayers both in molecular assays and in living cells. Our results reveal that these A{beta} condensates can significantly accelerate the primary nucleation step in the amyloid conversion cascade that leads to the formation of amyloid aggregates and plaque. We show that A{beta} condensates contain phospholipids, are intrinsically heterogenous, and are prone to undergo a liquid-to-solid transition leading to the formation amyloid fibrils. These findings uncover the liquid-liquid phase separation behaviour of the A{beta} peptide, and reveal a new molecular step very early in the amyloid-{beta} aggregation cascade that can form the basis for novel therapeutic intervention strategies. Significance statementThe hallmark of Alzheimers disease is the abnormal buildup of the normally soluble amyloid {beta} protein aggregates in the central nervous system. While the molecular mechanisms at the late stages of the amyloid {beta} aggregation cascade are well understood, the initial steps remained elusive until now. Our current study demonstrates that amyloid {beta} undergoes liquid-liquid phase separation on lipid surfaces, which triggers primary nucleation and initiates the amyloid {beta} aggregation cascade. This newly identified step in the molecular mechanism of Alzheimers disease represents a promising target for the development of alternative innovative therapeutic strategies.

biophysics↗

bioRxiv2024

Transient interactions between the fuzzy coat and the cross-β core of brain-derived Aβ42 filaments

A wide range of human disorders, including Alzheimers disease (AD), are characterised by the aberrant formation of amyloid fibrils. Amyloid fibrils are filamentous structures characterized by the presence of a highly-ordered cross-{beta} core. In many cases, this core structure is flanked by disordered regions, often referred to as fuzzy coat. The structural properties of fuzzy coats, and the way in which they interact with their environments, however, have not been described in full detail to date. Here, we generated the conformational ensembles of two brain-derived amyloid filaments of A{beta}42, corresponding respectively to familial and sporadic forms of AD. The approach that we used, called metadynamic electron microscopy metainference (MEMMI), enabled us to provide a characterization of the transient interactions between the fuzzy coat and the cross-{beta} core of the filaments. These calculations indicated that the familial AD filaments are less soluble than the sporadic AD filaments, and that the fuzzy coat contributes to increasing the solubility of both types of filament. In addition, by analyzing the deviations between the density maps from cryo-EM and from the MEMMI structural ensembles, we observed a slowing down in the diffusion of water and sodium ions near the surface of the filaments, offering insight into the hydration dynamics of amyloid fibrils. These results illustrate how the metainference approach can help analyse cryo-EM maps for the characterisation of the properties of amyloid fibrils.

biophysics↗

bioRxiv2023

Nanoscale profiling of evolving intermolecular interactions in ageing FUS condensates

In addition to the native state, proteins can form liquid-like condensates, viscoelastic condensates, such as gels, as well as solid-like condensates, such as amyloid fibrils, crystals and amorphous materials. The material properties of these condensates play important roles in their cellular functions, with aberrant liquid-to-solid phase transitions having been implicated in neurodegenerative diseases. However, the molecular changes and resultant material properties across the whole phase space of condensates are complex and yet to be fully understood. The extreme sensitivity to their environment, which enables their biological function, is also what makes protein condensates particularly challenging experimental targets. Here, we provide a characterisation of the ageing behaviour of the full-length fused in sarcoma (FUS) protein. We achieve this goal by using a microfluidic sample deposition technology to enable the application of surface-based techniques to the study of biological condensates. We first demonstrate that we maintain relevant structural features of condensates in physiologically-relevant conditions on surfaces. Then, using a combination of atomic force microscopy and vibrational spectroscopy, we characterise the spatio-temporal changes in the structure and mechanical properties of the condensates to reveal local phase transitions in individual condensates. We observe that initially dynamic, fluid-like condensates undergo a global increase in elastic response conferred by an increase in the density of cation-{pi} intermolecular interactions. Solid-like structures form first at condensate-solvent interfaces, before heterogeneously propagating throughout the aged fluid core. These solid structures are composed of heterogenous, non-amyloid {beta}-sheets, which are stabilised by hydrogen-bonding interactions not observed in the fluid state. Overall, this study identifies the molecular conformations associated with different physical states of FUS condensates, establishing a technology platform to understand the role of phase behaviour in condensate function and dysfunction.

biophysics↗

bioRxiv2023

Aggregation of the Amyloid-beta Peptide (Abeta40) within Condensates Generated through Liquid-Liquid Phase Separation

The deposition of the A{beta} peptide into amyloid fibrils is characteristic of Alzheimers disease. As it has been recently observed that the process of amyloid aggregation can take place within an intermediate liquid-like condensed phase, we investigated whether A{beta} could undergo liquid-liquid phase separation, and whether A{beta} amyloid aggregation could take place within A{beta} liquid condensates. By using a microfluidic protocol, we observed that the 40-residue form of A{beta} (A{beta}40) can undergo liquid-liquid phase separation, and that accessing a liquid intermediate state enhances primary nucleation and enables A{beta}40 to readily self-assemble into amyloid fibrils. These results prompt further studies to investigate the possible role of A{beta} condensates in the aggregation of this peptide in Alzheimers disease.

biophysics↗

bioRxiv2023

RASP: Optimal single fluorescent puncta detection in complex cellular backgrounds

Super-resolution and single-molecule microscopy are increasingly applied to complex biological systems. A major challenge of this approach is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false positive puncta that other analysis methods detect, and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art in precision and speed, using image gradients to separate Gaussian-shaped objects from background. We demonstrate RASPs power by showing it can extract spatial correlations between microglia, neurons, and -synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments with a sensitivity down to the level of the single protein.

biophysics↗

bioRxiv2023

Sequence-based drug design using transformers

Protein-ligand interactions play central roles in biological processes and are of key importance in drug design. Deep learning-based approaches are emerging as cost-effective alternatives to high-throughput experimental methods for the screening of large libraries of ligands. Here, to predict the binding affinity between proteins and small molecules, we introduce Ligand-Transformer, a deep learning framework based on the AlphaFold2 transformer architecture. We applied Ligand-Transformer to screen inhibitors targeting the mutant EGFRLTC kinase, identifying compounds with low nanomolar potency. We then used this approach to predict the conformational population shifts induced by ABL kinase inhibitors. To show the applicability of Ligand-Transformer to disordered proteins, we explored the binding of small molecules to the Alzheimers A{beta} peptide, identifying compounds that delayed its aggregation. Overall, Ligand-Transformer illustrates the potential of transformers in accurately predicting the interactions of small molecules with both ordered and disordered proteins, thus uncovering molecular mechanisms and facilitating the initial steps in drug discovery.

bioinformatics↗

bioRxiv2023

CryoENsemble - a Bayesian approach for reweighting biomolecular structural ensembles using heterogeneous cryo-EM maps

Cryogenic electron microscopy (cryo-EM) has emerged as a central tool for the determination of structures of complex biological molecules. Accurately characterising the dynamics of such systems, however, remains a challenge. To address this, we introduce cryoENsemble, a method that applies Bayesian reweighing to conformational ensembles derived from molecular dynamics simulations to improve their agreement with cryo-EM data and extract dynamics information. We illustrate the use of cryoENsemble to determine the dynamics of the ribosome-bound state of the co-translational chaperone trigger factor (TF). We also show that cryoENsemble can assist with the interpretation of low-resolution, noisy or unaccounted regions of cryo-EM maps. Notably, we are able to link an unaccounted part of the cryo-EM map to the presence of another protein (methionine aminopeptidase, or MetAP), rather than to the dynamics of TF, and model its TF-bound state. Based on these results, cryoENsemble is expected to find use for challenging heterogeneous cryo-EM maps for various biomolecular systems, especially those encompassing dynamic elements.

biophysics↗

bioRxiv2023

The αC-β4 loop controls the allosteric cooperativity between nucleotide and substrate in the catalytic subunit of protein kinase A

Allosteric cooperativity between ATP and substrates is a prominent characteristic of the cAMP-dependent catalytic subunit of protein kinase A (PKA). Not only this long-range synergistic action is involved in substrate recognition and fidelity, but it is also likely to regulate PKA association with regulatory subunits and other binding partners. To date, a complete understanding of the molecular determinants for this intramolecular mechanism is still lacking. Here, we integrated NMR-restrained molecular dynamics simulations and a Markov State Model to characterize the free energy landscape and conformational transitions of the catalytic subunit of protein kinase A (PKA-C). We found that the apoenzyme populates a broad free energy basin featuring a conformational ensemble of the active state of PKA-C (ground state) and other basins with lower populations (excited states). The first excited state corresponds to a previously characterized inactive state of PKA-C with the C helix swinging outward. The second excited state displays a disrupted hydrophobic packing around the regulatory (R) spine, with a flipped configuration of the F100 and F102 residues at the C-{beta}4 loop. To experimentally validate the second excited state, we mutated F100 into alanine (F100A) and used NMR spectroscopy to characterize the structural response of the kinase to ATP and substrate binding. While the catalytic efficiency of PKA-CF100A with a canonical peptide substrate remains unaltered, this mutation rearranges the C-{beta}4 loop conformation, interrupting the structural coupling of the two lobes and abolishing the allosteric binding cooperativity of the enzyme. The highly conserved C-{beta}4 loop emerges as a pivotal element able to control the synergistic binding between nucleotide and substrate. These results may explain how mutations or insertions near or within this motif affect the function and drug sensitivity in other homologous kinases.

biophysics↗

bioRxiv2023

Multiplexed Digital Characterisation of Misfolded Protein Oligomers via Solid-State Nanopores

Misfolded protein oligomers are of central importance in both the detection and treatment of Alzheimers and Parkinsons diseases. However, accurate high-throughput methods to identify and quantify oligomer populations are currently lacking. We present here a single-molecule approach for the detection of oligomeric species. The approach is based on the use of solid state nanopores and multiplexed DNA barcoding to identify and characterise oligomers from multiple samples. We study -synuclein oligomers in the presence of several small molecule inhibitors of -synuclein aggregation, as an illustration of the applicability of this method to assist the development of diagnostic and therapeutic methods for Parkinsons disease.

biophysics↗

bioRxiv2023

Targeted protein editing with an antibody-based system

The chemical modification of proteins is one of the major mechanisms used to regulate the properties and functions of these macromolecules in the cell. It is therefore of great interest to develop tools to exploit this type of modifications for applications in molecular biology, medicine and biotechnology. Here we present a method of using antibodies to perform post-translational covalent modifications of endogenous proteins in complex environments by exploiting proximity-driven chemistry. The method is based on the ability of antibodies to hold a weakly reactive group close to its intended site of reaction by binding the target protein on a nearby epitope. We characterise this approach by modifying the green fluorescent protein in increasingly complex environments, and illustrate its applicability by targeting the disease-associated protein beta-2 microglobulin.

biochemistry↗

bioRxiv2023

α-Synuclein oligomers form by secondary nucleation

Oligomeric species arising during aggregation of -synuclein are proposed to be a major source of toxicity in Parkinsons disease, and thus a major potential drug target. However, their mechanism of formation and role in aggregation are largely unresolved. Here we first show that, at physiological pH, -synuclein aggregates by secondary nucleation, rather than fragmentation, and that this process is enhanced by agitation. Moreover, using a combination of single molecule and bulk level techniques, we identify secondary nucleation on the surfaces of existing fibrils, rather than formation directly from monomers, as the dominant source of oligomers. Our results highlight secondary nucleation as not only the key source of oligomers, but also the main mechanism of aggregate formation, and show that these processes take place under physiologically relevant conditions.

biophysics↗

bioRxiv2023

A scale-invariant log-normal droplet size distribution below the critical concentration for protein phase separation

Many proteins have been recently shown to undergo a process of phase separation that leads to the formation of biomolecular condensates. Intriguingly, it has been observed that some of these proteins form dense droplets of sizeable dimensions already below the critical concentration, which is the concentration at which phase separation occurs. To understand this phenomenon, which is not readily compatible with classical nucleation theory, we investigated the properties of the droplet size distributions as a function of protein concentration. We found that these distributions can be described by a scale-invariant log-normal function with an average that increases progressively as the concentration approaches the critical concentration from below. The results of this scaling analysis suggest the existence of a universal behaviour independent of the sequences and structures of the proteins undergoing phase separation. While we refrain from proposing a theoretical model here, we suggest that any model of protein phase separation should predict the scaling exponents that we reported here from the fitting of experimental measurements of droplet size distributions. Furthermore, based on these observations, we show that it is possible to use the scale invariance to estimate the critical concentration for protein phase separation.

biophysics↗

bioRxiv2023

Maturation-dependent changes in the structure and seeding capacity of Aβ42 amyloid fibrils

Many proteins self-assemble to form amyloid fibrils, which are highly organized structures stabilized by a characteristic cross-{beta} network of hydrogen bonds. This process underlies a variety of human diseases, and can be exploited to develop versatile functional biomaterials. Thus, amyloid aggregation has been widely studied, shedding light on the properties of fibrils and their intermediates. A question that remains open concerns the microscopic processes that underlie the long-time behaviour of the fibrillar assemblies. Here, we use atomic force microscopy to observe that the fibrils undergo a maturation process, with an increase in both fibril length and thickness, and a change in the cross-{beta} sheet content. These changes affect the ability of the fibrils to catalyse the formation of new aggregates through secondary nucleation. The identification of these changes helps us understand the fibril maturation processes, facilitate the targeting of amyloid fibrils in drug discovery, and offer insight into the development of biocompatible and sustainable protein based materials.

biophysics↗