Mutations in Tau Protein Promote Aggregation by Favoring Extended Conformations

Water-directed pinning is key to tau prion formation

Tau forms fibrillar aggregates that are pathological hallmarks of a family of neurodegenerative diseases known as tauopathies. The synthetic replication of disease-specific fibril structures is a critical gap for developing diagnostic and therapeutic tools. This study debuts a strategy of identifying a critical and minimal folding motif in fibrils characteristic of tauopathies and generating seeding-competent fibrils from the isolated tau peptides. The 19-residue jR2R3 peptide (295 to 313) which spans the R2/R3 splice junction of tau, and includes the P301L mutation, is one such peptide that forms prion-competent fibrils. This tau fragment contains the hydrophobic VQIVYK hexapeptide that is part of the core of all known pathological tau fibril structures and an intramolecular counterstrand that stabilizes the strand-loop-strand (SLS) motif observed in 4R tauopathy fibrils. This study shows that P301L exhibits a duality of effects: it lowers the barrier for the peptide to adopt aggregation-prone conformations and enhances the local structuring of water around the mutation site to facilitate site-directed pinning and dewetting around sites 300-301 to achieve in-register stacking of tau to cross β-sheets. We solved a 3 Å cryo-EM structure of jR2R3-P301L fibrils in which each protofilament layer contains two jR2R3-P301L copies, of which one adopts a SLS fold found in 4R tauopathies and the other wraps around the SLS fold to stabilize it, reminiscent of the three- and fourfold structures observed in 4R tauopathies. These jR2R3-P301L fibrils are competent to template full-length 4R tau in a prion-like manner.

Conformational signatures induced by ubiquitin modification in the amyloid-forming tau repeat domain

Posttranslational modifications can critically affect conformational changes of amyloid-forming proteins. Ubiquitination of the microtubule-associated tau protein, an intrinsically disordered biomolecule, has been proposed to influence the formation of filamentous deposits in neurodegenerative conditions. Given the reported link between aggregation propensity and intrinsic structural preferences (e.g., transient extended structural motifs or tertiary contacts) in disordered proteins, we sought to explore the conformational landscape of ubiquitinated tau. Exploiting selective conjugation reactions, we produced single- and double-monoubiquitinated protein samples. Next, we examined the ubiquitinated species from different standpoints using NMR spectroscopy, small-angle X-ray scattering experiments, and native ion mobility-mass spectrometry (IM-MS). Moreover, we obtained atomistic representations of the conformational ensembles via scaled MD calculations, consistent with the experimental data. Modifying the repeat domain of tau with ubiquitin had a limited effect on secondary structure propensities and local mobility of distal regions. Instead, ubiquitination enhanced the compaction of the conformational ensemble, with the effect modulated by the site and the number of modifications. Native IM-MS patterns pinpointed similarities and differences between distinct tau proteoforms. It emerges that ubiquitination exerts a position-specific influence on the conformational distribution of tau molecules. This study reveals the unique conformational features of ubiquitinated forms of tau and points to their potential impact on aggregation and phase separation propensities, offering clues for a better understanding of disease-related structural alterations.

Single-point mutations in disordered proteins: Linking sequence, ensemble, and function

Mutations in genomic DNA often result in single-point missense mutations in proteins. For folded proteins, the functional effect of these missense mutations can often be understood by their impact on structure. However, missense mutations in intrinsically disordered protein regions (IDRs) remain poorly understood. In IDRs, function can depend on the structural ensemble- the collection of accessible, interchanging conformations that is encoded in their amino acid sequence. We argue that, analogously to folded proteins, single-point mutations in IDRs can alter their structural ensemble, and consequently alter their biological function. To make this argument, we first provide experimental evidence from the literature showcasing how single-point missense mutations in IDRs affect their ensemble dimensions. Then, we use genomic data from patients to show that disease-linked missense mutations occurring in IDRs can, in many cases, significantly alter IDR structural ensembles. We hope this analysis prompts further study of disease-linked, single-point mutations in IDRs.

Intrinsically Disordered Proteins Can Behave as Different Polymers across Their Conformational Ensemble

Intrinsically disordered proteins (IDPs) are macromolecules, which in contrast to well-folded proteins explore a large number of conformationally heterogeneous states. In this work, we investigate the conformational space of the disordered protein β-casein using Hamiltonian replica exchange atomistic molecular dynamics (MD) simulations in explicit water. The energy landscape contains a global minimum along with two shallow funnels. Employing static polymeric scaling laws separately for individual funnels, we find that they cannot be described by the same polymeric scaling exponent. Around the global minimum, the conformations are globular, whereas in the vicinity of local minima, we recover coil-like scaling. To elucidate the implications of structural diversity on equilibrium dynamics, we initiated standard MD simulations in the NVT ensemble with representative conformations from each funnel. Global and internal motions for different classes of trajectories show heterogeneous dynamics with globule to coil-like signatures. Thus, IDPs can behave as entirely different polymers in different regions of the conformational space.

Chemical Synthesis Reveals Pathogenic Role of N-Glycosylation in Microtubule-Associated Protein Tau

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of tau protein aggregates. In this study, we investigated the effects of N-glycosylation on tau, focusing on its impact on aggregation and phase behavior. We chemically prepared homogeneous glycoproteins with high-mannose glycans or a single N-acetylglucosamine at the confirmed glycosylation sites in K18 and 2N4R tau. Our findings reveal that N-glycosylation significantly alters biophysical properties and potentially cellular functions of tau. Small glycans promote tau aggregation and liquid-liquid phase separation (LLPS), while larger glycans reduce these effects. High mannose glycans at N410 enhance phosphorylation by GSK3β, suggesting a pathological role in AD. Functional assays demonstrate that N-glycosylation does not impact microtubule polymerization dynamics but modulates aggregation kinetics and morphology. This research underscores the importance of glycosylation in tau pathology and opens new avenues for therapeutic interventions targeting glycan processing.

Progress on the development of prediction tools for detecting disease causing mutations in proteins

Proteins are involved in a variety of functions in living organisms. The mutation of amino acid residues in a protein alters its structure, stability, binding, and function, with some mutations leading to diseases. Understanding the influence of mutations on protein structure and function help to gain deep insights on the molecular mechanism of diseases and devising therapeutic strategies. Hence, several generic and disease-specific methods have been proposed to reveal pathogenic effects on mutations. In this review, we focus on the development of prediction methods for identifying disease causing mutations in proteins. We briefly outline the existing databases for disease-causing mutations, followed by a discussion on sequence- and structure-based features used for prediction. Further, we discuss computational tools based on machine learning, deep learning and large language models for detecting disease-causing mutations. Specifically, we emphasize the advances in predicting hotspots and mutations for targets involved in cancer, neurodegenerative and infectious diseases as well as in membrane proteins. The computational resources including databases and algorithms understanding/predicting the effect of mutations will be listed. Moreover, limitations of existing methods and possible improvements will be discussed.

Weighted families of contact maps to characterize conformational ensembles of (highly-)flexible proteins

MOTIVATION

Characterizing the structure of flexible proteins, particularly within the realm of intrinsic disorder, presents a formidable challenge due to their high conformational variability. Currently, their structural representation relies on (possibly large) conformational ensembles derived from a combination of experimental and computational methods. The detailed structural analysis of these ensembles is a difficult task, for which existing tools have limited effectiveness.

RESULTS

This study proposes an innovative extension of the concept of contact maps to the ensemble framework, incorporating the intrinsic probabilistic nature of disordered proteins. Within this framework, a conformational ensemble is characterized through a weighted family of contact maps. To achieve this, conformations are first described using a refined definition of contact that appropriately accounts for the geometry of the inter-residue interactions and the sequence context. Representative structural features of the ensemble naturally emerge from the subsequent clustering of the resulting contact-based descriptors. Importantly, transiently populated structural features are readily identified within large ensembles. The performance of the method is illustrated by several use cases and compared with other existing approaches, highlighting its superiority in capturing relevant structural features of highly flexible proteins.

AVAILABILITY AND IMPLEMENTATION

An open-source implementation of the method is provided together with an easy-to-use Jupyter notebook, available at https://gitlab.laas.fr/moma/WARIO.

Interaction of full-length Tau with negatively charged lipid membranes leads to polymorphic aggregates

The Tau protein is implicated in various diseases collectively known as tauopathies, including Alzheimer's disease and frontotemporal dementia. The precise mechanism underlying Tau pathogenicity remains elusive. Recently, the role of lipids has garnered interest due to their implications in Tau aggregation, secretion, uptake, and pathogenic dysregulation. Previous investigations have highlighted critical aspects: (i) Tau's tendency to aggregate into fibers when interacting with negatively charged lipids, (ii) its ability to form structured species upon contact with anionic membranes, and (iii) the potential disruption of the membrane upon Tau binding. In this study, we examine the disease-associated P301L mutation of the 2N4R isoform of Tau and its effects on membranes composed on phosphatidylserine (PS) lipids. Aggregation studies and liposome leakage assays demonstrate Tau's ability to bind to anionic lipid vesicles, leading to membrane disruption. Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) reveals the accumulation of Tau on the membrane surface without protein insertion, structuration, or lipid removal. Plasmon waveguide resonance (PWR) demonstrates a strong binding of Tau on PS bilayers with an apparent Kd in the micromolar range, indicating the deposition of a thick protein layer. Atomic force microscopy (AFM) real-time imaging allows the observation of partial lipid solubilization and the deposition of polymorphic aggregates in the form of thick patches and fibrillary structures resembling amyloid fibers, which could grow from a combination of extracted anionic phospholipids from the membrane and Tau protein. This study deepens our understanding of full-length Tau's multifaceted interactions with lipids, shedding light on potential mechanisms leading to the formation of pathogenic Tau assemblies.

Leveraging a large language model to predict protein phase transition: A physical, multiscale, and interpretable approach

Protein phase transitions (PPTs) from the soluble state to a dense liquid phase (forming droplets via liquid-liquid phase separation) or to solid aggregates (such as amyloids) play key roles in pathological processes associated with age-related diseases such as Alzheimer's disease. Several computational frameworks are capable of separately predicting the formation of droplets or amyloid aggregates based on protein sequences, yet none have tackled the prediction of both within a unified framework. Recently, large language models (LLMs) have exhibited great success in protein structure prediction; however, they have not yet been used for PPTs. Here, we fine-tune a LLM for predicting PPTs and demonstrate its usage in evaluating how sequence variants affect PPTs, an operation useful for protein design. In addition, we show its superior performance compared to suitable classical benchmarks. Due to the "black-box" nature of the LLM, we also employ a classical random forest model along with biophysical features to facilitate interpretation. Finally, focusing on Alzheimer's disease-related proteins, we demonstrate that greater aggregation is associated with reduced gene expression in Alzheimer's disease, suggesting a natural defense mechanism.

Ensemble-based design of tau to inhibit aggregation while preserving biological activity

The microtubule-associated protein tau is implicated in neurodegenerative diseases characterized by amyloid formation. Mutations associated with frontotemporal dementia increase tau aggregation propensity and disrupt its endogenous microtubule-binding activity. The structural relationship between aggregation propensity and biological activity remains unclear. We employed a multi-disciplinary approach, including computational modeling, NMR, cross-linking mass spectrometry, and cell models to design tau sequences that stabilize its structural ensemble. Our findings reveal that substitutions near the conserved 'PGGG' beta-turn motif can modulate local conformation, more stably engaging in interactions with the 306VQIVYK311 amyloid motif to decrease aggregation in vitro and in cells. Designed tau sequences maintain microtubule binding and explain why 3R isoforms of tau exhibit reduced pathogenesis over 4R isoforms. We propose a simple mechanism to reduce the formation of pathogenic species while preserving biological function, offering insights for therapeutic strategies aimed at reducing protein misfolding in neurodegenerative diseases.