Protein structure and aggregation: a marriage of necessity ruled by aggregation gatekeepers

AggreProt: a web server for predicting and engineering aggregation prone regions in proteins

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.

Enolase of Streptococcus suis serotype 2 promotes biomolecular condensation of ribosomal protein SA for HBMECs apoptosis

BACKGROUND

Ribosomal protein SA (RPSA) of human brain microvascular endothelial cells (HBMECs) can transfer from the cytosol to the cell surface and act as a receptor for some pathogens, including Streptococcus suis serotype 2 (SS2), a zoonotic pathogen causing meningitis in pigs and humans. We previously reported that SS2 virulence factor enolase (ENO) binds to RPSA on the cell surface of HBMECs and induces apoptosis. However, the mechanism that activates RPSA translocation to the cell surface and induces ENO-mediated HBMEC apoptosis is unclear.

RESULTS

Here, we show that RPSA localization and condensation on the host cell surface depend on its internally disordered region (IDR). ENO binds to the IDR of RPSA and promotes its interaction with RPSA and vimentin (VIM), which is significantly suppressed after 1,6-Hexanediol (1,6-Hex, a widely used tool to disrupt phase separation) treatment, indicating that ENO incorporation and thus the concentration of RPSA/VIM complexes via co-condensation. Furthermore, increasing intracellular calcium ions (Ca2+) in response to SS2 infection further facilitates the liquid-like condensation of RPSA and aggravates ENO-induced HBMEC cell apoptosis.

CONCLUSIONS

Together, our study provides a previously underappreciated molecular mechanism illuminating that ENO-induced RPSA condensation activates the migration of RPSA to the bacterial cell surface and stimulates SS2-infected HBMEC death and, potentially, disease progression. This study offers a fresh avenue for investigation into the mechanism by which other harmful bacteria infect hosts via cell surfaces' RPSA.

N-glycosylation as a eukaryotic protective mechanism against protein aggregation

The tendency for proteins to form aggregates is an inherent part of every proteome and arises from the self-assembly of short protein segments called aggregation-prone regions (APRs). While posttranslational modifications (PTMs) have been implicated in modulating protein aggregation, their direct role in APRs remains poorly understood. In this study, we used a combination of proteome-wide computational analyses and biophysical techniques to investigate the potential involvement of PTMs in aggregation regulation. Our findings reveal that while most PTM types are disfavored near APRs, N-glycosylation is enriched and evolutionarily selected, especially in proteins prone to misfolding. Experimentally, we show that N-glycosylation inhibits the aggregation of peptides in vitro through steric hindrance. Moreover, mining existing proteomics data, we find that the loss of N-glycans at the flanks of APRs leads to specific protein aggregation in Neuro2a cells. Our findings indicate that, among its many molecular functions, N-glycosylation directly prevents protein aggregation in higher eukaryotes.

Development of an in vitro aggregation assay for long synthetic polypeptide, amyloidogenic gelsolin fragment AGelD187N 173-242

Aggregation of the gelsolin protein fragment is the hallmark of the hereditary systemic disease gelsolin amyloidosis. As with other protein misfolding diseases, there is an urgent need for efficient disease-modifying treatment for gelsolin amyloidosis. The formation of amyloids can be reproduced by incubating the disease-causing amyloidogenic 8 kDa polypeptide, 70-residue gelsolin protein fragment, AGelD187N 173-242, in vitro and monitoring the process by thioflavin T dye. However, for screening of potential aggregation inhibitors, the required protein amounts are large and the biotechnological production of amyloidogenic proteins has many challenges. Conversely, use of shorter synthetic regions of AGelD187N 173-242 does not mimic the in vivo aggregation kinetics of full-length fragment as they have different aggregation propensity. In this study, we present an in vitro aggregation assay for full-length AGelD187N 173-242 that has been produced by solid-phase chemical synthesis and after that monomerized carefully. Chemical synthesis allows us to produce high quantities of full-length fragment efficiently and at low cost. We demonstrate that the generated aggregates are fibrillar in nature and how the purity, terminal modification, initial aggregates and seeding affect the aggregation kinetics of a synthetic gelsolin fragment. We also present sufficient quality criteria for the initial monomerized synthetic polypeptide.

Disrupting pathologic phase transitions in neurodegeneration

Solid-like protein deposits found in aged and diseased human brains have revealed a relationship between insoluble protein accumulations and the resulting deficits in neurologic function. Clinically diverse neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, frontotemporal lobar degeneration, and amyotrophic lateral sclerosis, exhibit unique and disease-specific biochemical protein signatures and abnormal protein depositions that often correlate with disease pathogenesis. Recent evidence indicates that many pathologic proteins assemble into liquid-like protein phases through the highly coordinated process of liquid-liquid phase separation. Over the last decade, biomolecular phase transitions have emerged as a fundamental mechanism of cellular organization. Liquid-like condensates organize functionally related biomolecules within the cell, and many neuropathology-associated proteins reside within these dynamic structures. Thus, examining biomolecular phase transitions enhances our understanding of the molecular mechanisms mediating toxicity across diverse neurodegenerative diseases. This Review explores the known mechanisms contributing to aberrant protein phase transitions in neurodegenerative diseases, focusing on tau and TDP-43 proteinopathies and outlining potential therapeutic strategies to regulate these pathologic events.

Salt-Induced Dissolution of Protein Aggregates

Protein aggregation is mediated by a complex interplay of noncovalent interactions and is associated with a broad range of aspects from debilitating human diseases to the food industry and therapeutic biotechnology. Deciphering the intricate roles of noncovalent interactions is of paramount importance for the design of effective inhibitory and disaggregation strategies, which remains a formidable challenge. By using a combination of spectroscopic and microscopic tools, here we show that the surfactant-mediated protein aggregation can be modulated by an intriguing interplay of hydrophobic and electrostatic effects. Additionally, our results illuminate the unique role of salt as a potent disaggregation inducer that alters the protein-surfactant electrostatic interactions and triggers the dissolution of preformed protein aggregates resulting in restoring the native protein structure. This unusual salt-induced dissolution and refolding offers a unique approach to regulating the balance between protein self-assembly and disassembly and will offer a potent strategy to design electrostatically targeted inhibitors.

Generating Ensembles of Dynamic Misfolding Proteins

The early stages of protein misfolding and aggregation involve disordered and partially folded protein conformers that contain a high degree of dynamic disorder. These dynamic species may undergo large-scale intra-molecular motions of intrinsically disordered protein (IDP) precursors, or flexible, low affinity inter-molecular binding in oligomeric assemblies. In both cases, generating atomic level visualization of the interconverting species that captures the conformations explored and their physico-chemical properties remains hugely challenging. How specific sub-ensembles of conformers that are on-pathway to aggregation into amyloid can be identified from their aggregation-resilient counterparts within these large heterogenous pools of rapidly moving molecules represents an additional level of complexity. Here, we describe current experimental and computational approaches designed to capture the dynamic nature of the early stages of protein misfolding and aggregation, and discuss potential challenges in describing these species because of the ensemble averaging of experimental restraints that arise from motions on the millisecond timescale. We give a perspective of how machine learning methods can be used to extract aggregation-relevant sub-ensembles and provide two examples of such an approach in which specific interactions of defined species within the dynamic ensembles of α-synuclein (αSyn) and β2-microgloblulin (β2m) can be captured and investigated.