Atomic structures of low-complexity protein segments reveal kinked β sheets that assemble networks

Nascent mitochondrial proteins initiate the localized condensation of cytosolic protein aggregates on the mitochondrial surface

Eukaryotes organize cellular contents into membrane-bound organelles and membrane-less condensates, for example, protein aggregates. An unsolved question is why the ubiquitously distributed proteins throughout the cytosol give rise to spatially localized protein aggregates on the organellar surface, like mitochondria. We report that the mitochondrial import receptor Tom70 is involved in the localized condensation of protein aggregates in budding yeast and human cells. This is because misfolded cytosolic proteins do not autonomously aggregate in vivo; instead, they are recruited to the condensation sites initiated by Tom70's substrates (nascent mitochondrial proteins) on the organellar membrane using multivalent hydrophobic interactions. Knocking out Tom70 partially impairs, while overexpressing Tom70 increases the formation and association between cytosolic protein aggregates and mitochondria. In addition, ectopic targeting Tom70 and its substrates to the vacuole surface is able to redirect the localized aggregation from mitochondria to the vacuolar surface. Although other redundant mechanisms may exist, this nascent mitochondrial proteins-based initiation of protein aggregation likely explains the localized condensation of otherwise ubiquitously distributed molecules on the mitochondria. Disrupting the mitochondrial association of aggregates impairs their asymmetric retention during mitosis and reduces the mitochondrial import of misfolded proteins, suggesting a proteostasis role of the organelle-condensate interactions.

Multidimensional super-resolution microscopy unveils nanoscale surface aggregates in the aging of FUS condensates

The intracellular liquid-liquid phase separation (LLPS) of biomolecules gives rise to condensates that act as membrane-less organelles with vital functions. FUS, an RNA-binding protein, natively forms condensates through LLPS and further provides a model system for the often disease-linked liquid-to-solid transition of biomolecular condensates during aging. However, the mechanism of such maturation processes, as well as the structural and physical properties of the system, remain unclear, partly attributable to difficulties in resolving the internal structures of the micrometer-sized condensates with diffraction-limited optical microscopy. Harnessing a set of multidimensional super-resolution microscopy tools that uniquely map out local physicochemical parameters through single-molecule spectroscopy, here we uncover nanoscale heterogeneities in the aging process of FUS condensates. Through spectrally resolved single-molecule localization microscopy (SR-SMLM) with a solvatochromic dye, we unveil distinct hydrophobic nanodomains at the condensate surface. Through SMLM with a fluorogenic amyloid probe, we identify these nanodomains as amyloid aggregates. Through single-molecule displacement/diffusivity mapping (SM d M), we show that such nanoaggregates drastically impede local diffusion. Notably, upon aging or mechanical shears, these nanoaggregates progressively expand on the condensate surface, thus leading to a growing low-diffusivity shell while leaving the condensate interior diffusion-permitting. Together, beyond uncovering fascinating nanoscale structural arrangements and aging mechanisms in the single-component FUS condensates, the demonstrated synergy of multidimensional super-resolution approaches in this study opens new paths for understanding LLPS systems.

Phase separation and molecular ordering of the prion-like domain of the Arabidopsis thermosensory protein EARLY FLOWERING 3

Liquid-liquid phase separation (LLPS) is an important mechanism enabling the dynamic compartmentalization of macromolecules, including complex polymers such as proteins and nucleic acids, and occurs as a function of the physicochemical environment. In the model plant, Arabidopsis thaliana, LLPS by the protein EARLY FLOWERING3 (ELF3) occurs in a temperature-sensitive manner and controls thermoresponsive growth. ELF3 contains a largely unstructured prion-like domain (PrLD) that acts as a driver of LLPS in vivo and in vitro. The PrLD contains a poly-glutamine (polyQ) tract, whose length varies across natural Arabidopsis accessions. Here, we use a combination of biochemical, biophysical, and structural techniques to investigate the dilute and condensed phases of the ELF3 PrLD with varying polyQ lengths. We demonstrate that the dilute phase of the ELF3 PrLD forms a monodisperse higher-order oligomer that does not depend on the presence of the polyQ sequence. This species undergoes LLPS in a pH- and temperature-sensitive manner and the polyQ region of the protein tunes the initial stages of phase separation. The liquid phase rapidly undergoes aging and forms a hydrogel as shown by fluorescence and atomic force microscopies. Furthermore, we demonstrate that the hydrogel assumes a semiordered structure as determined by small-angle X-ray scattering, electron microscopy, and X-ray diffraction. These experiments demonstrate a rich structural landscape for a PrLD protein and provide a framework to describe the structural and biophysical properties of biomolecular condensates.

Targeting Biomolecular Condensation and Protein Aggregation against Cancer

Biomolecular condensates, membrane-less entities arising from liquid-liquid phase separation, hold dichotomous roles in health and disease. Alongside their physiological functions, these condensates can transition to a solid phase, producing amyloid-like structures implicated in degenerative diseases and cancer. This review thoroughly examines the dual nature of biomolecular condensates, spotlighting their role in cancer, particularly concerning the p53 tumor suppressor. Given that over half of the malignant tumors possess mutations in the TP53 gene, this topic carries profound implications for future cancer treatment strategies. Notably, p53 not only misfolds but also forms biomolecular condensates and aggregates analogous to other protein-based amyloids, thus significantly influencing cancer progression through loss-of-function, negative dominance, and gain-of-function pathways. The exact molecular mechanisms underpinning the gain-of-function in mutant p53 remain elusive. However, cofactors like nucleic acids and glycosaminoglycans are known to be critical players in this intersection between diseases. Importantly, we reveal that molecules capable of inhibiting mutant p53 aggregation can curtail tumor proliferation and migration. Hence, targeting phase transitions to solid-like amorphous and amyloid-like states of mutant p53 offers a promising direction for innovative cancer diagnostics and therapeutics.

Biomolecule-Based Coacervates with Modulated Physiological Functions

Liquid-liquid phase separation (LLPS) exists widely in living systems, and understanding the working mechanisms of the formed condensed droplets is of great significance for the prevention and treatment of diseases as well as for the development of biomimetic materials. Herein, in this Perspective we try to focus on the in vitro reconstructions of biomolecule-based coacervates and outline the associations between the functional components and droplets as well as the physiological and pathological functions associated with coacervates. Coacervates are formed by functional components through weak, multivalent interactions. The interaction strengths that determine coacervate properties such as electability and phase state, which in turn influence the functional components to limit their fluidity, stability, or diffusion coefficients, are specially discussed. At the end of this Perspective, the current challenges are summarized; progress will require our great efforts to reveal the mechanisms of action at the molecular level and then develop biomolecule-based coacervate models with complexity, integration of methods, and intellectualization.

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

The well known phenomenon of phase separation in synthetic polymers and proteins has become a major topic in biophysics because it has been invoked as a mechanism of compartment formation in cells, without the need for membranes. Most of the coacervates (or condensates) are composed of Intrinsically Disordered Proteins (IDPs) or regions that are structureless, often in interaction with RNA and DNA. One of the more intriguing IDPs is the 526-residue RNA binding protein, Fused In Sarcoma (FUS), whose monomer conformations and condensates exhibit unusual behavior that are sensitive to solution conditions. By focussing principally on the N-terminus low complexity domain (FUS-LC comprising residues 1-214) and other truncations, we rationalize the findings of solid state NMR experiments, which show that FUS-LC adopts a non-polymorphic fibril (core-1) involving residues 39-95, flanked by fuzzy coats on both the N- and C- terminal ends. An alternate structure (core-2), whose free energy is comparable to core-1, emerges only in the truncated construct (residues 110-214). Both core-1 and core-2 fibrils are stabilized by a Tyrosine ladder as well as hydrophilic interactions. The morphologies (gels, fibrils, and glass-like behavior) adopted by FUS seem to vary greatly, depending on the experimental conditions. The effect of phosphorylation is site specific and affects the stability of the fibril depending on the sites that are phosphorylated. Many of the peculiarities associated with FUS may also be shared by other IDPs, such as TDP43 and hnRNPA2. We outline a number of problems for which there is no clear molecular understanding.

Identification of Phase-Separation-Protein-Related Function Based on Gene Ontology by Using Machine Learning Methods

Phase-separation proteins (PSPs) are a class of proteins that play a role in the process of liquid-liquid phase separation, which is a mechanism that mediates the formation of membranelle compartments in cells. Identifying phase separation proteins and their associated function could provide insights into cellular biology and the development of diseases, such as neurodegenerative diseases and cancer. Here, PSPs and non-PSPs that have been experimentally validated in earlier studies were gathered as positive and negative samples. Each protein's corresponding Gene Ontology (GO) terms were extracted and used to create a 24,907-dimensional binary vector. The purpose was to extract essential GO terms that can describe essential functions of PSPs and build efficient classifiers to identify PSPs with these GO terms at the same time. To this end, the incremental feature selection computational framework and an integrated feature analysis scheme, containing categorical boosting, least absolute shrinkage and selection operator, light gradient-boosting machine, extreme gradient boosting, and permutation feature importance, were used to build efficient classifiers and identify GO terms with classification-related importance. A set of random forest (RF) classifiers with F1 scores over 0.960 were established to distinguish PSPs from non-PSPs. A number of GO terms that are crucial for distinguishing between PSPs and non-PSPs were found, including GO:0003723, which is related to a biological process involving RNA binding; GO:0016020, which is related to membrane formation; and GO:0045202, which is related to the function of synapses. This study offered recommendations for future research aimed at determining the functional roles of PSPs in cellular processes by developing efficient RF classifiers and identifying the representative GO terms related to PSPs.

Towards sequence-based principles for protein phase separation predictions

The phenomenon of protein phase separation, which underlies the formation of biomolecular condensates, has been associated with numerous cellular functions. Recent studies indicate that the amino acid sequences of most proteins may harbour not only the code for folding into the native state but also for condensing into the liquid-like droplet state and the solid-like amyloid state. Here we review the current understanding of the principles for sequence-based methods for predicting the propensity of proteins for phase separation. A guiding concept is that entropic contributions are generally more important to stabilise the droplet state than they are for the native and amyloid states. Although estimating these entropic contributions has proven difficult, we describe some progress that has been recently made in this direction. To conclude, we discuss the challenges ahead to extend sequence-based prediction methods of protein phase separation to include quantitative in vivo characterisations of this process.

Low complexity domains of the nucleocapsid protein of SARS-CoV-2 form amyloid fibrils

The self-assembly of the Nucleocapsid protein (NCAP) of SARS-CoV-2 is crucial for its function. Computational analysis of the amino acid sequence of NCAP reveals low-complexity domains (LCDs) akin to LCDs in other proteins known to self-assemble as phase separation droplets and amyloid fibrils. Previous reports have described NCAP's propensity to phase-separate. Here we show that the central LCD of NCAP is capable of both, phase separation and amyloid formation. Within this central LCD we identified three adhesive segments and determined the atomic structure of the fibrils formed by each. Those structures guided the design of G12, a peptide that interferes with the self-assembly of NCAP and demonstrates antiviral activity in SARS-CoV-2 infected cells. Our work, therefore, demonstrates the amyloid form of the central LCD of NCAP and suggests that amyloidogenic segments of NCAP could be targeted for drug development.

Rational design of phase separating peptides based on phase separating protein sequence of p53

Artificial phase-separating (PS) peptides can be used in various applications such as microreactors and drug delivery; however, the design of artificial PS peptides remains a challenge. This can be attributed to the limitation of PS-relevant residues that drive phase separation by interactions of their pairs in short peptides and the difficulty in the design involving interaction with target PS proteins. In this study, we propose a rational method to design artificial PS peptides that satisfy the requirements of liquid droplet formation and co-phase separation with target PS proteins based on the target PS protein sequence. As a proof of concept, we designed five artificial peptides from the model PS protein p53 using this method and confirmed their PS properties using differential interference contrast and fluorescence microscopy. Single-molecule fluorescent tracking demonstrated rapid diffusion of the designed peptides in their droplets compared to that of p53 in p53 droplets. In addition, size-dependent uptake of p53 oligomers was observed in the designed peptide droplets. Large oligomers were excluded from the droplet voids and localized on the droplet surface. The uptake of high-order p53 oligomers into the droplets was enhanced by the elongated linker of the designed peptides. Furthermore, we found that the designed peptide droplets recruited p53 to suppress gel-like aggregate formation. Finally, we discuss aspects that were crucial in the successful design of the artificial PS peptides.

A hybrid positive unlabeled learning framework for uncovering scaffolds across human proteome by measuring the propensity to drive phase separation

Scaffold proteins drive liquid-liquid phase separation (LLPS) to form biomolecular condensates and organize various biochemical reactions in cells. Dysregulation of scaffolds can lead to aberrant condensate assembly and various complex diseases. However, bioinformatics predictors dedicated to scaffolds are still lacking and their development suffers from an extreme imbalance between limited experimentally identified scaffolds and unlabeled candidates. Here, using the joint distribution of hybrid multimodal features, we implemented a positive unlabeled (PU) learning-based framework named PULPS that combined ProbTagging and penalty logistic regression (PLR) to profile the propensity of scaffolds. PULPS achieved the best AUC of 0.8353 and showed an area under the lift curve (AUL) of 0.8339 as an estimation of true performance. Upon reviewing recent experimentally verified scaffolds, we performed a partial recovery with 2.85% increase in AUL from 0.8339 to 0.8577. In comparison, PULPS showed a 45.7% improvement in AUL compared with PLR, whereas 8.2% superiority over other existing tools. Our study first proved that PU learning is more suitable for scaffold prediction and demonstrated the widespread existence of phase separation states. This profile also uncovered potential scaffolds that co-drive LLPS in the human proteome and generated candidates for further experiments. PULPS is free for academic research at http://pulps.zbiolab.cn.

Modulation of Mechanical Properties of Short Bioinspired Peptide Materials by Single Amino-Acid Mutations

The occurrence of modular peptide repeats in load-bearing (structural) proteins is common in nature, with distinctive peptide sequences that often remain conserved across different phylogenetic lineages. These highly conserved peptide sequences endow specific mechanical properties to the material, such as toughness or elasticity. Here, using bioinformatic tools and phylogenetic analysis, we have identified the GX8 peptide with the sequence GLYGGYGX (where X can be any residue) in a wide range of organisms. By simple mutation of the X residue, we demonstrate that GX8 can be self-assembled into various supramolecular structures, exhibiting vastly different physicochemical and viscoelastic properties, from liquid-like coacervate microdroplets to hydrogels to stiff solid materials. A combination of spectroscopic, electron microscopy, mechanical, and molecular dynamics studies is employed to obtain insights into molecular scale interactions driving self-assembly of GX8 peptides, underscoring that π-π stacking and hydrophobic interactions are the drivers of peptide self-assembly, whereas the X residue determines the extent of hydrogen bonding that regulates the macroscopic mechanical response. This study highlights the ability of single amino-acid polymorphism to tune the supramolecular assembly and bulk material properties of GX8 peptides, enabling us to cover a broad range of potential biomedical applications such as hydrogels for tissue engineering or coacervates for drug delivery.

Role of Triggers on the Structural and Functional Facets of TAR DNA-binding Protein 43

Nuclear TAR DNA-binding protein 43 (TDP-43) mitigates cellular function, but the dynamic nucleus-cytoplasm shuttling of TDP-43 is disrupted in diseases, such as Amyotrophic Lateral Sclerosis (ALS). The polymorphic nature of the TDP-43 structures in vitro and in vivo is a result of environmental factors leading to the protein pathogenesis. Once the triggers which mitigate TDP-43 biochemistry are identified, new therapies can be developed. This review aims to illustrate recent discoveries in the diversity of TDP-43 structures (amyloidogenic and non-amyloidogenic) and highlight the triggers which result in their formation.

Sequence determinants and solution conditions underlying liquid to solid phase transition

Life consists of numberless functional biomolecules that exist in various states. Besides well-dissolved phases, biomolecules especially proteins and nucleic acids can form liquid droplets through liquid-liquid phase separation (LLPS). Stronger interactions promote a solid-like state of biomolecular condensates, which are also formerly referred to as detergent-insoluble aggregates. Solid-like condensates exist in vivo physiologically and pathologically, and their formation has not been fully understood. Recently, more and more research has proven that liquid to solid phase transition (LST) is an essential way to form solid condensates. In this review, we summarized the regions in the sequence that have different impacts on phase transition and emphasized that the LST is affected by its sequence characteristics. Moreover, increasing evidence unveiled that LST is affected by various solution conditions. We discussed solution conditions like protein concentration, pH, ATP, ions, and small molecules in a solution. Methods have been established to study these solid phase components. Here, we summarized low-throughput experimental techniques and high-throughput omics methods in the study of the LST.

Formation of subcellular compartments by condensation-prone protein OsJAZ2 in Oryza sativa and Nicotiana benthamiana leaf cells

OsJAZ2 protein has a propensity to form condensates, possibly by multivalent interactions, and can be used to construct artificial compartments in plant cells. Eukaryotic cells contain various membraneless organelles, which are compartments consisting of proteinaceous condensates formed by phase separation. Such compartments are attractive for bioengineering and synthetic biology, because they can modify cellular function by the enrichment of molecules of interest and providing an orthogonal reaction system. This study reports that Oryza sativa JAZ2 protein (OsJAZ2) is an atypical jasmonate signalling regulator that can form large condensates in both the nucleus and cytosol of O. sativa cells. TIFY and Jas domains and low-complexity regions contribute to JAZ2 condensation, possibly by multivalent interaction. Fluorescence recovery after photobleaching (FRAP) analysis suggests that JAZ2 condensates form mostly gel-like or solid compartments, but can also be in a liquid-like state. Deletion of the N-terminal region or the TIFY domain of JAZ2 causes an increase in the mobile fraction of JAZ2 condensates, moderately. Moreover, JAZ2 can also form liquid-like condensates when expressed in Nicotiana benthamiana cells. The recombinant JAZ2 fused to the green fluorescent protein (GFP) forms condensate in vitro, suggesting that the intermolecular interaction of JAZ2 molecules is a driving force for condensation. These results suggest the potential use of JAZ2 condensates to construct artificial membraneless organelles in plant cells.

A New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules

Stress granules (SGs) are cytosolic biomolecular condensates that form in response to cellular stress. Weak, multivalent interactions between their protein and RNA constituents drive their rapid, dynamic assembly through phase separation coupled to percolation. Though a consensus model of SG function has yet to be determined, their perceived implication in cytoprotective processes (e.g., antiviral responses and inhibition of apoptosis) and possible role in the pathogenesis of various neurodegenerative diseases (e.g., amyotrophic lateral sclerosis and frontotemporal dementia) have drawn great interest. Consequently, new studies using numerous cell biological, genetic, and proteomic methods have been performed to unravel the mechanisms underlying SG formation, organization, and function and, with them, a more clearly defined SG proteome. Here, we provide a consensus SG proteome through literature curation and an update of the user-friendly database RNAgranuleDB to version 2.0 (http://rnagranuledb.lunenfeld.ca/). With this updated SG proteome, we use next-generation phase separation prediction tools to assess the predisposition of SG proteins for phase separation and aggregation. Next, we analyze the primary sequence features of intrinsically disordered regions (IDRs) within SG-resident proteins. Finally, we review the protein- and RNA-level determinants, including post-translational modifications (PTMs), that regulate SG composition and assembly/disassembly dynamics.

Liquid Droplet Aging and Seeded Fibril Formation of the Cytotoxic Granule Associated RNA Binding Protein TIA1 Low Complexity Domain

Protein domains biased toward a few amino acid types are vital for the formation of biomolecular condensates in living cells. These membraneless compartments are formed by molecules exhibiting a range of molecular motions and structural order. Missense mutations increase condensate persistence lifetimes or structural order, properties that are thought to underlie pathological protein aggregation. In the context of stress granules associated with neurodegenerative diseases, this process involves the rigidification of protein liquid droplets into β-strand rich protein fibrils. Here, we characterize the molecular mechanism underlying the rigidification of liquid droplets for the low complexity domain of the Cytotoxic granule associated RNA binding protein TIA1 (TIA1) stress granule protein and the influence of a disease mutation linked to neurodegenerative diseases. A seeding procedure and solid state nuclear magnetic resonance measurements show that the low complexity domain converges on a β-strand rich fibril conformation composed of 21% of the sequence. Additional solid state nuclear magnetic resonance measurements and difference spectroscopy show that aged liquid droplets of wild type and a proline-to-leucine mutant low complexity domain are composed of fibril assemblies that are conformationally heterogeneous and structurally distinct from the seeded fibril preparation. Regarding low complexity domains, our data support the functional template-driven formation of conformationally homogeneous structures, that rigidification of liquid droplets into conformationally heterogenous structures promotes pathological interactions, and that the effect of disease mutations is more nuanced than increasing thermodynamic stability or increasing β-strand structure content.

Identification of Phase Separating Proteins With Distributed Reduced Alphabet Representations of Sequences

Phase separation of proteins play key roles in cellular physiology including bacterial division, tumorigenesis etc. Consequently, understanding the molecular forces that drive phase separation has gained considerable attention and several factors including hydrophobicity, protein dynamics, etc., have been implicated in phase separation. Data-driven identification of new phase separating proteins can enable in-depth understanding of cellular physiology and may pave way towards developing novel methods of tackling disease progression. In this work, we exploit the existing wealth of data on phase separating proteins to develop sequence-based machine learning method for prediction of phase separating proteins. We use reduced alphabet schemes based on hydrophobicity and conformational similarity along with distributed representation of protein sequences and biochemical properties as input features to Support Vector Machine (SVM) and Random Forest (RF) machine learning algorithms. We used both curated and balanced dataset for building the models. RF trained on balanced dataset with hydropathy, conformational similarity embeddings and biochemical properties achieved accuracy of 97%. Our work highlights the use of conformational similarity, a feature that reflects amino acid flexibility, and hydrophobicity for predicting phase separating proteins. Use of such "interpretable" features obtained from the ever-growing knowledgebase of phase separation is likely to improve prediction performances further.

Sequence Context and Complex Hofmeister Salt Interactions Dictate Phase Separation Propensity of Resilin-like Polypeptides

Resilin is an elastic material found in insects with exceptional durability, resilience, and extensibility, making it a promising biomaterial for tissue engineering. The monomeric precursor, pro-resilin, undergoes thermo-responsive self-assembly through liquid-liquid phase separation (LLPS). Understanding the molecular details of this assembly process is critical to developing complex biomaterials. The present study investigates the interplay between the solvent, sequence syntax, structure, and dynamics in promoting LLPS of resilin-like-polypeptides (RLPs) derived from domains 1 and 3 of Drosophila melanogaster pro-resilin. NMR, UV-vis, and microscopy data demonstrate that while kosmotropic salts and low pH promote LLPS, the effects of chaotropic salts with increasing pH are more complex. Subtle variations between the repeating amino acid motifs of resilin domain 1 and domain 3 lead to significantly different salt and pH dependence of LLPS, with domain 3 sequence motifs more strongly favoring phase separation under most conditions. These findings provide new insight into the molecular drivers of RLP phase separation and the complex roles of both RLP sequence and solution composition in fine-tuning assembly conditions.

Drosophila insulator proteins exhibit in vivo liquid-liquid phase separation properties

Drosophila insulator proteins and the cohesin subunit Rad21 coalesce in vivo to form liquid-droplet condensates, suggesting that liquid–liquid phase separation mediates their function in 3D genome organization.

Mounting evidence implicates liquid–liquid phase separation (LLPS), the condensation of biomolecules into liquid-like droplets in the formation and dissolution of membraneless intracellular organelles (MLOs). Cells use MLOs or condensates for various biological processes, including emergency signaling and spatiotemporal control over steady-state biochemical reactions and heterochromatin formation. Insulator proteins are architectural elements involved in establishing independent domains of transcriptional activity within eukaryotic genomes. In Drosophila, insulator proteins form nuclear foci known as insulator bodies in response to osmotic stress. However, the mechanism through which insulator proteins assemble into bodies is yet to be investigated. Here, we identify signatures of LLPS by insulator bodies, including high disorder tendency in insulator proteins, scaffold–client–dependent assembly, extensive fusion behavior, sphericity, and sensitivity to 1,6-hexanediol. We also show that the cohesin subunit Rad21 is a component of insulator bodies, adding to the known insulator protein constituents and γH2Av. Our data suggest a concerted role of cohesin and insulator proteins in insulator body formation and under physiological conditions. We propose a mechanism whereby these architectural proteins modulate 3D genome organization through LLPS.

Sequence-Based Prediction of Protein Phase Separation: The Role of Beta-Pairing Propensity

The formation of droplets of bio-molecular condensates through liquid-liquid phase separation (LLPS) of their component proteins is a key factor in the maintenance of cellular homeostasis. Different protein properties were shown to be important in LLPS onset, making it possible to develop predictors, which try to discriminate a positive set of proteins involved in LLPS against a negative set of proteins not involved in LLPS. On the other hand, the redundancy and multivalency of the interactions driving LLPS led to the suggestion that the large conformational entropy associated with non specific side-chain interactions is also a key factor in LLPS. In this work we build a LLPS predictor which combines the ability to form pi-pi interactions, with an unrelated feature, the propensity to stabilize the β-pairing interaction mode. The cross-β structure is formed in the amyloid aggregates, which are involved in degenerative diseases and may be the final thermodynamically stable state of protein condensates. Our results show that the combination of pi-pi and β-pairing propensity yields an improved performance. They also suggest that protein sequences are more likely to be involved in phase separation if the main chain conformational entropy of the β-pairing maintained droplet state is increased. This would stabilize the droplet state against the more ordered amyloid state. Interestingly, the entropic stabilization of the droplet state appears to proceed according to different mechanisms, depending on the fraction of "droplet-driving" proteins present in the positive set.

Emerging Implications of Phase Separation in Cancer

In eukaryotic cells, biological activities are executed in distinct cellular compartments or organelles. Canonical organelles with membrane-bound structures are well understood. Cells also inherently contain versatile membrane-less organelles (MLOs) that feature liquid or gel-like bodies. A biophysical process termed liquid-liquid phase separation (LLPS) elucidates how MLOs form through dynamic biomolecule assembly. LLPS-related molecules often have multivalency, which is essential for low-affinity inter- or intra-molecule interactions to trigger phase separation. Accumulating evidence shows that LLPS concentrates and organizes desired molecules or segregates unneeded molecules in cells. Thus, MLOs have tunable functional specificity in response to environmental stimuli and metabolic processes. Aberrant LLPS is widely associated with several hallmarks of cancer, including sustained proliferative signaling, growth suppressor evasion, cell death resistance, telomere maintenance, DNA damage repair, etc. Insights into the molecular mechanisms of LLPS provide new insights into cancer therapeutics. Here, the current understanding of the emerging concepts of LLPS and its involvement in cancer are comprehensively reviewed.

Amyloid fibril formation by αS1- and β-casein implies that fibril formation is a general property of casein proteins

Caseins are a diverse family of intrinsically disordered proteins present in the milks of all mammals. A property common to two cow paralogues, α_S2- and κ-casein, is their propensity in vitro to form amyloid fibrils, the highly ordered protein aggregates associated with many age-related, including neurological, diseases. In this study, we explored whether amyloid fibril-forming propensity is a general feature of casein proteins by examining the other cow caseins (α_S1 and β) as well as β-caseins from camel and goat. Small-angle X-ray scattering measurements indicated that cow α_S1- and β-casein formed large spherical aggregates at neutral pH and 20°C. Upon incubation at 65°C, α_S1- and β-casein underwent conversion to amyloid fibrils over the course of ten days, as shown by thioflavin T binding, transmission electron microscopy, and X-ray fibre diffraction. At the lower temperature of 37°C where fibril formation was more limited, camel β-casein exhibited a greater fibril-forming propensity than its cow or goat orthologues. Limited proteolysis of cow and camel β-casein fibrils and analysis by mass spectrometry indicated a common amyloidogenic sequence in the proline, glutamine-rich, C-terminal region of β-casein. These findings highlight the persistence of amyloidogenic sequences within caseins, which likely contribute to their functional, heterotypic self-assembly; in all mammalian milks, at least two caseins coalesce to form casein micelles, implying that caseins diversified partly to avoid dysfunctional amyloid fibril formation.

A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins

How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. Forty-eight percent of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure.

Targeting phase separation on enhancers induced by transcription factor complex formations as a new strategy for treating drug-resistant cancers

The limited options for treating patients with drug-resistant cancers have emphasized the need to identify alternative treatment targets. Tumor cells have large super-enhancers (SEs) in the vicinity of important oncogenes for activation. The physical process of liquid-liquid phase separation (LLPS) contributes to the assembly of several membrane-less organelles in mammalian cells. Intrinsically disordered regions (IDRs) of proteins induce LLPS formation by developing condensates. It was discovered that key transcription factors (TFs) undergo LLPS in SEs. In addition, TFs play critical roles in the epigenetic and genetic regulation of cancer progression. Recently, we revealed the essential role of disease-specific TF collaboration changes in advanced prostate cancer (PC). OCT4 confers epigenetic changes by promoting complex formation with TFs, such as Forkhead box protein A1 (FOXA1), androgen receptor (AR) and Nuclear respiratory factor 1 (NRF1), inducing PC progression. It was demonstrated that TF collaboration through LLPS underlying transcriptional activation contributes to cancer aggressiveness and drug resistance. Moreover, the disruption of TF-mediated LLPS inhibited treatment-resistant PC tumor growth. Therefore, we propose that repression of TF collaborations involved in the LLPS of SEs could be a promising strategy for advanced cancer therapy. In this article, we summarize recent evidence highlighting the formation of LLPS on enhancers as a potent therapeutic target in advanced cancers.

Crystal structures of FNIP/FGxxFN motif-containing leucine-rich repeat proteins

The Cafeteria roenbergensis virus (Crov), Dictyostelium, and other species encode a large family of leucine-rich repeat (LRR) proteins with FGxxFN motifs. We determined the structures of two of them and observed several unique structural features that set them aside from previously characterized LRR family members. Crov588 comprises 25 regular repeats with a LxxLxFGxxFNQxIxENVLPxx consensus, forming a unique closed circular repeat structure. Novel features include a repositioning of a conserved asparagine at the middle of the repeat, a double phenylalanine spine that generates an alternate core packing arrangement, and a histidine/tyrosine ladder on the concave surface. Crov539 is smaller, comprising 12 repeats of a similar LxxLxFGxxFNQPIExVxW/LPxx consensus and forming an unusual cap-swapped dimer structure. The phenylalanine spine of Crov539 is supplemented with a tryptophan spine, while a hydrophobic isoleucine-rich patch is found on the central concave surface. We present a detailed analysis of the structures of Crov588 and Crov539 and compare them to related repeat proteins and other LRR classes.

Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it

Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-protein β-sheets. To bridge microscopic understanding between accumulation of inter-protein β-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-protein β-sheets over time. We reveal that inter-protein β-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strong β-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-protein β-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-protein β-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down.

In this work the authors propose a multiscale computational approach, integrating atomistic and coarse-grained models simulations, to study the thermodynamic and kinetic factors playing a major role in the liquid-to-solid transition of biomolecular condensates. It is revealed how the gradual accumulation of inter-protein β-sheets increases the viscosity of functional liquid-like condensates, transforming them into gel-like pathological aggregates, and it is also shown how high concentrations of RNA can decelerate such transition.

Developing Bonded Potentials for a Coarse-Grained Model of Intrinsically Disordered Proteins

Recent advances in residue-level coarse-grained (CG) computational models have enabled molecular-level insights into biological condensates of intrinsically disordered proteins (IDPs), shedding light on the sequence determinants of their phase separation. The existing CG models that treat protein chains as flexible molecules connected via harmonic bonds cannot populate common secondary-structure elements. Here, we present a CG dihedral angle potential between four neighboring beads centered at Cα atoms to faithfully capture the transient helical structures of IDPs. In order to parameterize and validate our new model, we propose Cα-based helix assignment rules based on dihedral angles that succeed in reproducing the atomistic helicity results of a polyalanine peptide and folded proteins. We then introduce sequence-dependent dihedral angle potential parameters (εd) and use experimentally available helical propensities of naturally occurring 20 amino acids to find their optimal values. The single-chain helical propensities from the CG simulations for commonly studied prion-like IDPs are in excellent agreement with the NMR-based α-helix fraction, demonstrating that the new HPS-SS model can accurately produce structural features of IDPs. Furthermore, this model can be easily implemented for large-scale assembly simulations due to its simplicity.

Molecular interactions of FG nucleoporin repeats at high resolution

Proteins that contain repeat phenylalanine-glycine (FG) residues phase separate into oncogenic transcription factor condensates in malignant leukaemias, form the permeability barrier of the nuclear pore complex and mislocalize in neurodegenerative diseases. Insights into the molecular interactions of FG-repeat nucleoporins have, however, remained largely elusive. Using a combination of NMR spectroscopy and cryoelectron microscopy, we have identified uniformly spaced segments of transient β-structure and a stable preformed α-helix recognized by messenger RNA export factors in the FG-repeat domain of human nucleoporin 98 (Nup98). In addition, we have determined at high resolution the molecular organization of reversible FG–FG interactions in amyloid fibrils formed by a highly aggregation-prone segment in Nup98. We have further demonstrated that amyloid-like aggregates of the FG-repeat domain of Nup98 have low stability and are reversible. Our results provide critical insights into the molecular interactions underlying the self-association and phase separation of FG-repeat nucleoporins in physiological and pathological cell activities.

Proteins rich in phenylalanine-glycine (FG) repeats can phase separate through FG–FG interactions. The molecular interactions of an important FG-repeat protein, nucleoporin 98, have now been studied in liquid-like transient and amyloid-like cohesive states. These interactions underlie the behaviour of FG-repeat proteins and their function in physiological and pathological cell activities.

ALS mutations in the TIA-1 prion-like domain trigger highly condensed pathogenic structures

T cell intracellular antigen-1 (TIA-1) plays a central role in stress granule (SG) formation by self-assembly via the prion-like domain (PLD). In the TIA-1 PLD, amino acid mutations associated with neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) or Welander distal myopathy (WDM), have been identified. However, how these mutations affect PLD self-assembly properties has remained elusive. In this study, we uncovered the implicit pathogenic structures caused by the mutations. NMR analysis indicated that the dynamic structures of the PLD are synergistically determined by the physicochemical properties of amino acids in units of five residues. Molecular dynamics simulations and three-dimensional electron crystallography, together with biochemical assays, revealed that the WDM mutation E384K attenuated the sticky properties, whereas the ALS mutations P362L and A381T enhanced the self-assembly by inducing β-sheet interactions and highly condensed assembly, respectively. These results suggest that the P362L and A381T mutations increase the likelihood of irreversible amyloid fibrillization after phase-separated droplet formation, and this process may lead to pathogenicity.

Stability matters, too - the thermodynamics of amyloid fibril formation

Amyloid fibrils are supramolecular homopolymers of proteins that play important roles in biological functions and disease. These objects have received an exponential increase in attention during the last few decades, due to their role in the aetiology of a range of severe disorders, most notably some of a neurodegenerative nature. While an overwhelming number of experimental studies exist that investigate how, and how fast, amyloid fibrils form and how their formation can be inhibited, a much more limited body of experimental work attempts to answer the question as to why these types of structures form (i.e. the thermodynamic driving force) and how stable they actually are. In this review, I attempt to give an overview of the types of experiments that have been performed to-date to answer these questions, and to summarise our current understanding of amyloid thermodynamics.

Advanced materials for enamel remineralization

Dental caries, a chronic and irreversible disease caused by caries-causing bacteria, has been listed as one of the three major human diseases to be prevented and treated. Therefore, it is critical to effectively stop the development of enamel caries. Remineralization treatment can control the progression of caries by inhibiting and reversing enamel demineralization at an early stage. In this process, functional materials guide the deposition of minerals on the damaged enamel, and the structure and hardness of the enamel are then restored. These remineralization materials have great potential for clinical application. In this review, advanced materials for enamel remineralization were briefly summarized, furthermore, an outlook on the perspective of remineralization materials were addressed.

Aberrant liquid-liquid phase separation and amyloid aggregation of proteins related to neurodegenerative diseases

Recent evidence has shown that the processes of liquid-liquid phase separation (LLPS) or liquid-liquid phase transitions (LLPTs) are a crucial and prevalent phenomenon that underlies the biogenesis of numerous membrane-less organelles (MLOs) and biomolecular condensates within the cells. Findings show that processes associated with LLPS play an essential role in physiology and disease. In this review, we discuss the physical and biomolecular factors that contribute to the development of LLPS, the associated functions, as well as their consequences for cell physiology and neurological disorders. Additionally, the finding of mis-regulated proteins, which have long been linked to aggregates in neuropathology, are also known to induce LLPS/LLPTs, prompting a lot of interest in understanding the connection between aberrant phase separation and disorder conditions. Moreover, the methods used in recent and ongoing studies in this field are also explored, as is the possibility that these findings will encourage new lines of inquiry into the molecular causes of neurodegenerative diseases.

Micro-electron diffraction structure of the aggregation-driving N-terminus of Drosophila neuronal protein Orb2A reveals amyloid-like β-sheets

Amyloid protein aggregation is commonly associated with progressive neurodegenerative diseases, however not all amyloid fibrils are pathogenic. The neuronal cytoplasmic polyadenylation element binding (CPEB) protein is a regulator of synaptic mRNA translation, and has been shown to form functional amyloid aggregates that stabilize long-term memory. In adult Drosophila neurons, the CPEB homolog Orb2 is expressed as two isoforms, of which the Orb2B isoform is far more abundant, but the rarer Orb2A isoform is required to initiate Orb2 aggregation. The N-terminus is a distinctive feature of the Orb2A isoform and is critical for its aggregation. Intriguingly, replacement of phenylalanine in the 5^th position of Orb2A with tyrosine (F5Y) in Drosophila impairs stabilization of long-term memory. The structure of endogenous Orb2B fibers was recently determined by cryo-EM, but the structure adopted by fibrillar Orb2A is less certain. Here we use micro-electron diffraction to determine the structure of the first nine N-terminal residues of Orb2A, at a resolution of 1.05 Å. We find that this segment (which we term M9I) forms an amyloid-like array of parallel in-register β-sheets, which interact through side chain interdigitation of aromatic and hydrophobic residues. Our structure provides an explanation for the decreased aggregation observed for the F5Y mutant, and offers a hypothesis for how the addition of a single atom (the tyrosyl oxygen) affects long-term memory. We also propose a structural model of Orb2A that integrates our structure of the M9I segment with the published Orb2B cryo-EM structure.

An Interpretable Machine-Learning Algorithm to Predict Disordered Protein Phase Separation Based on Biophysical Interactions

Protein phase separation is increasingly understood to be an important mechanism of biological organization and biomaterial formation. Intrinsically disordered protein regions (IDRs) are often significant drivers of protein phase separation. A number of protein phase-separation-prediction algorithms are available, with many being specific for particular classes of proteins and others providing results that are not amenable to the interpretation of the contributing biophysical interactions. Here, we describe LLPhyScore, a new predictor of IDR-driven phase separation, based on a broad set of physical interactions or features. LLPhyScore uses sequence-based statistics from the RCSB PDB database of folded structures for these interactions, and is trained on a manually curated set of phase-separation-driving proteins with different negative training sets including the PDB and human proteome. Competitive training for a variety of physical chemical interactions shows the greatest contribution of solvent contacts, disorder, hydrogen bonds, pi–pi contacts, and kinked beta-structures to the score, with electrostatics, cation–pi contacts, and the absence of a helical secondary structure also contributing. LLPhyScore has strong phase-separation-prediction recall statistics and enables a breakdown of the contribution from each physical feature to a sequence’s phase-separation propensity, while recognizing the interdependence of many of these features. The tool should be a valuable resource for guiding experiments and providing hypotheses for protein function in normal and pathological states, as well as for understanding how specificity emerges in defining individual biomolecular condensates.

Electron Diffraction of 3D Molecular Crystals

Electron crystallography has a storied history which rivals that of its more established X-ray-enabled counterpart. Recent advances in data collection and analysis have sparked a renaissance in the field, opening a new chapter for this venerable technique. Burgeoning interest in electron crystallography has spawned innovative methods described by various interchangeable labels (3D ED, MicroED, cRED, etc.). This Review covers concepts and findings relevant to the practicing crystallographer, with an emphasis on experiments aimed at using electron diffraction to elucidate the atomic structure of three-dimensional molecular crystals.

Natural Antimicrobial Peptides Self-assemble as α/β Chameleon Amyloids

Amyloid protein fibrils and some antimicrobial peptides (AMPs) share biophysical and structural properties. This observation suggests that ordered self-assembly can act as an AMP-regulating mechanism, and, vice versa, that human amyloids play a role in host defense against pathogens, as opposed to their common association with neurodegenerative and systemic diseases. Based on previous structural information on toxic amyloid peptides, we developed a sequence-based bioinformatics platform and, led by its predictions, experimentally identified 14 fibril-forming AMPs (ffAMPs) from living organisms, which demonstrated cross-β and cross-α amyloid properties. The results support the amyloid-antimicrobial link. The high prevalence of ffAMPs produced by amphibians and marine creatures among other species suggests that they confer unique advantageous properties in distinctive environments, potentially providing stability and adherence properties. Most of the newly identified 14 ffAMPs showed lipid-induced and/or time-dependent secondary structure transitions in the fibril form, indicating structural and functional cross-α/β chameleons. Specifically, ffAMP cytotoxicity against human cells correlated with the inherent or lipid-induced α-helical fibril structure. The findings raise hypotheses about the role of fibril secondary structure switching in regulation of processes, such as the transition between a stable storage conformation and an active state with toxicity against specific cell types.

CARs-DB: A Database of Cryptic Amyloidogenic Regions in Intrinsically Disordered Proteins

Proteome-wide analyses suggest that most globular proteins contain at least one amyloidogenic region, whereas these aggregation-prone segments are thought to be underrepresented in intrinsically disordered proteins (IDPs). In recent work, we reported that intrinsically disordered regions (IDRs) indeed sustain a significant amyloid load in the form of cryptic amyloidogenic regions (CARs). CARs are widespread in IDRs, but they are necessarily exposed to solvent, and thus they should be more polar and have a milder aggregation potential than conventional amyloid regions protected inside globular proteins. CARs are connected with IDPs function and, in particular, with the establishment of protein-protein interactions through their IDRs. However, their presence also appears associated with pathologies like cancer or Alzheimer’s disease. Given the relevance of CARs for both IDPs function and malfunction, we developed CARs-DB, a database containing precomputed predictions for all CARs present in the IDPs deposited in the DisProt database. This web tool allows for the fast and comprehensive exploration of previously unnoticed amyloidogenic regions embedded within IDRs sequences and might turn helpful in identifying disordered interacting regions. It contains >8,900 unique CARs identified in a total of 1711 IDRs. CARs-DB is freely available for users and can be accessed at http://carsdb.ppmclab.com. To validate CARs-DB, we demonstrate that two previously undescribed CARs selected from the database display full amyloidogenic potential. Overall, CARs-DB allows easy access to a previously unexplored amyloid sequence space.

De novo determination of mosquitocidal Cry11Aa and Cry11Ba structures from naturally-occurring nanocrystals

Cry11Aa and Cry11Ba are the two most potent toxins produced by mosquitocidal Bacillus thuringiensis subsp. israelensis and jegathesan, respectively. The toxins naturally crystallize within the host; however, the crystals are too small for structure determination at synchrotron sources. Therefore, we applied serial femtosecond crystallography at X-ray free electron lasers to in vivo-grown nanocrystals of these toxins. The structure of Cry11Aa was determined de novo using the single-wavelength anomalous dispersion method, which in turn enabled the determination of the Cry11Ba structure by molecular replacement. The two structures reveal a new pattern for in vivo crystallization of Cry toxins, whereby each of their three domains packs with a symmetrically identical domain, and a cleavable crystal packing motif is located within the protoxin rather than at the termini. The diversity of in vivo crystallization patterns suggests explanations for their varied levels of toxicity and rational approaches to improve these toxins for mosquito control.

The Cryo-EM structures of two amphibian antimicrobial cross-β amyloid fibrils

The amyloid-antimicrobial link hypothesis is based on antimicrobial properties found in human amyloids involved in neurodegenerative and systemic diseases, along with amyloidal structural properties found in antimicrobial peptides (AMPs). Supporting this hypothesis, we here determined the fibril structure of two AMPs from amphibians, uperin 3.5 and aurein 3.3, by cryogenic electron microscopy (cryo-EM), revealing amyloid cross-β fibrils of mated β-sheets at atomic resolution. Uperin 3.5 formed a 3-blade symmetrical propeller of nine peptides per fibril layer including tight β-sheet interfaces. This cross-β cryo-EM structure complements the cross-α fibril conformation previously determined by crystallography, substantiating a secondary structure switch mechanism of uperin 3.5. The aurein 3.3 arrangement consisted of six peptides per fibril layer, all showing kinked β-sheets allowing a rounded compactness of the fibril. The kinked β-sheets are similar to LARKS (Low-complexity, Amyloid-like, Reversible, Kinked Segments) found in human functional amyloids.

In this work the authors provide high-resolution structural support for the amyloid-antimicrobial link via functional amyloids displaying propeller-like and kinked cross-β fibrils.

Genetic variation associated with condensate dysregulation in disease

A multitude of cellular processes involve biomolecular condensates, which has led to the suggestion that diverse pathogenic mutations may dysregulate condensates. Although proof-of-concept studies have identified specific mutations that cause condensate dysregulation, the full scope of the pathological genetic variation that affects condensates is not yet known. Here, we comprehensively map pathogenic mutations to condensate-promoting protein features in putative condensate-forming proteins and find over 36,000 pathogenic mutations that plausibly contribute to condensate dysregulation in over 1,200 Mendelian diseases and 550 cancers. This resource captures mutations presently known to dysregulate condensates, and experimental tests confirm that additional pathological mutations do indeed affect condensate properties in cells. These findings suggest that condensate dysregulation may be a pervasive pathogenic mechanism underlying a broad spectrum of human diseases, provide a strategy to identify proteins and mutations involved in pathologically altered condensates, and serve as a foundation for mechanistic insights into disease and therapeutic hypotheses.

Are casein micelles extracellular condensates formed by liquid-liquid phase separation?

Casein micelles are extracellular polydisperse assemblies of unstructured casein proteins. Caseins are the major component of milk. Within casein micelles, casein molecules are stabilised by binding to calcium phosphate nanoclusters and, by acting as molecular chaperones, through multivalent interactions. In light of such interactions, we discuss whether casein micelles can be considered as extracellular condensates formed by liquid-liquid phase separation. We analyse the sequence, structure and interactions of caseins in comparison to proteins forming intracellular condensates. Furthermore, we review the similarities between caseins and small heat-shock proteins whose chaperone activity is linked to phase separation of proteins. By bringing these observations together, we describe a regulatory mechanism for protein condensates, as exemplified by casein micelles.

Liquid-liquid phase separation in tumor biology

Liquid–liquid phase separation (LLPS) is a novel principle for explaining the precise spatial and temporal regulation in living cells. LLPS compartmentalizes proteins and nucleic acids into micron-scale, liquid-like, membraneless bodies with specific functions, which were recently termed biomolecular condensates. Biomolecular condensates are executors underlying the intracellular spatiotemporal coordination of various biological activities, including chromatin organization, genomic stability, DNA damage response and repair, transcription, and signal transduction. Dysregulation of these cellular processes is a key event in the initiation and/or evolution of cancer, and emerging evidence has linked the formation and regulation of LLPS to malignant transformations in tumor biology. In this review, we comprehensively summarize the detailed mechanisms of biomolecular condensate formation and biophysical function and review the recent major advances toward elucidating the multiple mechanisms involved in cancer cell pathology driven by aberrant LLPS. In addition, we discuss the therapeutic perspectives of LLPS in cancer research and the most recently developed drug candidates targeting LLPS modulation that can be used to combat tumorigenesis.

Structure and Conservation of Amyloid Spines From the Candida albicans Als5 Adhesin

Candida Als family adhesins mediate adhesion to biological and abiotic substrates, as well as fungal cell aggregation, fungal-bacterial co-aggregation and biofilm formation. The activity of at least two family members, Als5 and Als1, is dependent on amyloid-like protein aggregation that is initiated by shear force. Each Als adhesin has a ∼300-residue N-terminal Ig-like/invasin region. The following 108-residue, low complexity, threonine-rich (T) domain unfolds under shear force to expose a critical amyloid-forming segment ³²²SNGIVIVATTRTV³³⁴ at the interface between the Ig-like/invasin domain 2 and the T domain of Candida albicans Als5. Amyloid prediction programs identified six potential amyloidogenic sequences in the Ig-like/invasin region and three others in the T domain of C. albicans Als5. Peptides derived from four of these sequences formed fibrils that bound thioflavin T, the amyloid indicator dye, and three of these revealed atomic-resolution structures of cross-β spines. These are the first atomic-level structures for fungal adhesins. One of these segments, from the T domain, revealed kinked β-sheets, similarly to LARKS (Low-complexity, Amyloid-like, Reversible, Kinked segments) found in human functional amyloids. Based on the cross-β structures in Als proteins, we use evolutionary arguments to identify functional amyloidogenic sequences in other fungal adhesins, including adhesins from Candida auris. Thus, cross-β structures are often involved in fungal pathogenesis and potentially in antifungal therapy.

Mutations linked to neurological disease enhance self-association of low-complexity protein sequences

Protein domains of low sequence complexity do not fold into stable, three-dimensional structures. Nevertheless, proteins with these sequences assist in many aspects of cell organization, including assembly of nuclear and cytoplasmic structures not surrounded by membranes. The dynamic nature of these cellular assemblies is caused by the ability of low-complexity domains (LCDs) to transiently self-associate through labile, cross-β structures. Mechanistic studies useful for the study of LCD self-association have evolved over the past decade in the form of simple assays of phase separation. Here, we have used such assays to demonstrate that the interactions responsible for LCD self-association can be dictated by labile protein structures poised close to equilibrium between the folded and unfolded states. Furthermore, missense mutations causing Charcot-Marie-Tooth disease, frontotemporal dementia, and Alzheimer's disease manifest their pathophysiology in vitro and in cultured cell systems by enhancing the stability of otherwise labile molecular structures formed upon LCD self-association.

Aging can transform single-component protein condensates into multiphase architectures

Phase-separated biomolecular condensates that contain multiple coexisting phases are widespread in vitro and in cells. Multiphase condensates emerge readily within multicomponent mixtures of biomolecules (e.g., proteins and nucleic acids) when the different components present sufficient physicochemical diversity (e.g., in intermolecular forces, structure, and chemical composition) to sustain separate coexisting phases. Because such diversity is highly coupled to the solution conditions (e.g., temperature, pH, salt, composition), it can manifest itself immediately from the nucleation and growth stages of condensate formation, develop spontaneously due to external stimuli or emerge progressively as the condensates age. Here, we investigate thermodynamic factors that can explain the progressive intrinsic transformation of single-component condensates into multiphase architectures during the nonequilibrium process of aging. We develop a multiscale model that integrates atomistic simulations of proteins, sequence-dependent coarse-grained simulations of condensates, and a minimal model of dynamically aging condensates with nonconservative intermolecular forces. Our nonequilibrium simulations of condensate aging predict that single-component condensates that are initially homogeneous and liquid like can transform into gel-core/liquid-shell or liquid-core/gel-shell multiphase condensates as they age due to gradual and irreversible enhancement of interprotein interactions. The type of multiphase architecture is determined by the aging mechanism, the molecular organization of the gel and liquid phases, and the chemical makeup of the protein. Notably, we predict that interprotein disorder to order transitions within the prion-like domains of intracellular proteins can lead to the required nonconservative enhancement of intermolecular interactions. Our study, therefore, predicts a potential mechanism by which the nonequilibrium process of aging results in single-component multiphase condensates.

Casein kinase 1δ/ε phosphorylates fused in sarcoma (FUS) and ameliorates FUS-mediated neurodegeneration

Aberrant cytoplasmic accumulation of an RNA-binding protein, fused in sarcoma (FUS), characterizes the neuropathology of subtypes of ALS and frontotemporal lobar degeneration, although the effects of post-translational modifications of FUS, especially phosphorylation, on its neurotoxicity have not been fully characterized. Here, we show that casein kinase 1δ (CK1δ) phosphorylates FUS at 10 serine/threonine residues in vitro using mass spectrometric analyses. We also show that phosphorylation by CK1δ or CK1ε significantly increased the solubility of FUS in human embryonic kidney 293 cells. In transgenic Drosophila that overexpress wt or P525L ALS-mutant human FUS in the retina or in neurons, we found coexpression of human CK1δ or its Drosophila isologue Dco in the photoreceptor neurons significantly ameliorated the observed retinal degeneration, and neuronal coexpression of human CK1δ extended fly life span. Taken together, our data suggest a novel regulatory mechanism of the assembly and toxicity of FUS through CK1δ/CK1ε-mediated phosphorylation, which could represent a potential therapeutic target in FUS proteinopathies.

Structural Mimicry in Microbial and Antimicrobial Amyloids

The remarkable variety of microbial species of human pathogens and microbiomes generates significant quantities of secreted amyloids, which are structured protein fibrils that serve diverse functions related to virulence and interactions with the host. Human amyloids are associated largely with fatal neurodegenerative and systemic aggregation diseases, and current research has put forward the hypothesis that the interspecies amyloid interactome has physiological and pathological significance. Moreover, functional and molecular-level connections between antimicrobial activity and amyloid structures suggest a neuroimmune role for amyloids that are otherwise known to be pathological. Compared to the extensive structural information that has been accumulated for human amyloids, high-resolution structures of microbial and antimicrobial amyloids are only emerging. These recent structures reveal both similarities and surprising departures from the typical amyloid motif, in accordance with their diverse activities, and advance the discovery of novel antivirulence and antimicrobial agents. In addition, the structural information has led researchers to postulate that amyloidogenic sequences are natural targets for structural mimicry, for instance in host-microbe interactions. Microbial amyloid research could ultimately be used to fight aggressive infections and possibly processes leading to autoimmune and neurodegenerative diseases.

Screening membraneless organelle participants with machine-learning models that integrate multimodal features

Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to the mechanism by which they undergo PS: PS-Self proteins can self-assemble spontaneously to form droplets, while PS-Part proteins interact with partners to undergo PS. Analysis of the amino acid composition revealed differences in the sequence pattern between the two protein groups. Existing PS predictors, when evaluated on two test protein sets, preferentially predicted self-assembling proteins. Thus, a comprehensive predictor is required. Herein, we propose that properties other than sequence composition can provide crucial information in screening PS proteins. By incorporating phosphorylation frequencies and immunofluorescence image-based droplet-forming propensity with other PS-related features, we built two independent machine-learning models to separately predict the two protein categories. Results of independent testing suggested the superiority of integrating multimodal features. We performed experimental verification on the top-scored proteins DHX9, K_i-67, and NIFK. Their PS behavior in vitro revealed the effectiveness of our models in PS prediction. Further validation on the proteome of membraneless organelles confirmed the ability of our models to identify PS-Part proteins. We implemented a web server named PhaSePred (http://predict.phasep.pro/) that incorporates our two models together with representative PS predictors. PhaSePred displays proteome-level quantiles of different features, thus profiling PS propensity and providing crucial information for identification of candidate proteins.