Emergent microenvironments of nucleoli

In higher eukaryotes, the nucleolus harbors at least three sub-phases that facilitate multiple functionalities including ribosome biogenesis. The three prominent coexisting sub-phases are the fibrillar center (FC), the dense fibrillar component (DFC), and the granular component (GC). Here, we review recent efforts in profiling sub-phase compositions that shed light on the types of physicochemical properties that emerge from compositional biases and territorial organization of specific types of macromolecules. We highlight roles played by molecular grammars which refers to protein sequence features including the substrate binding domains, the sequence features of intrinsically disordered regions, and the multivalence of these distinct types of domains / regions. We introduce the concept of a barcode of emergent physicochemical properties of nucleoli. Although our knowledge of the full barcode remains incomplete, we hope that the concept prompts investigations into undiscovered emergent properties and engenders an appreciation for how and why unique microenvironments control biochemical reactions.

Macromolecular condensation organizes nucleolar sub-phases to set up a pH gradient

Nucleoli are multicomponent condensates defined by coexisting sub-phases. We identified distinct intrinsically disordered regions (IDRs), including acidic (D/E) tracts and K-blocks interspersed by E-rich regions, as defining features of nucleolar proteins. We show that the localization preferences of nucleolar proteins are determined by their IDRs and the types of RNA or DNA binding domains they encompass. In vitro reconstitutions and studies in cells showed how condensation, which combines binding and complex coacervation of nucleolar components, contributes to nucleolar organization. D/E tracts of nucleolar proteins contribute to lowering the pH of co-condensates formed with nucleolar RNAs in vitro. In cells, this sets up a pH gradient between nucleoli and the nucleoplasm. By contrast, juxta-nucleolar bodies, which have different macromolecular compositions, featuring protein IDRs with very different charge profiles, have pH values that are equivalent to or higher than the nucleoplasm. Our findings show that distinct compositional specificities generate distinct physicochemical properties for condensates.

Metastable condensates suppress conversion to amyloid fibrils

Stress granules form via co-condensation of RNA binding proteins with prion-like low complexity domains (PLCDs) and RNA molecules released by stress-induced polysomal runoff. Homotypic interactions among PLCDs can drive amyloid fibril formation and this is enhanced by ALS-associated mutations. We find that homotypic interactions that drive condensation versus fibril formation are separable for A1-LCD, the PLCD of hnRNPA1. These separable interactions lead to condensates that are metastable versus fibrils that are globally stable. Metastable condensates suppress fibril formation, and ALS-associated mutations enhance fibril formation by weakening condensate metastability. Mutations designed to enhance A1-LCD condensate metastability restore wild-type behaviors of stress granules in cells even when ALS-associated mutations are present. This suggests that fibril formation can be suppressed by enhancing condensate metastability through condensate-driving interactions.

Dynamical control enables the formation of demixed biomolecular condensates

Cellular matter can be organized into compositionally distinct biomolecular condensates. For example, in Ashbya gossypii, the RNA-binding protein Whi3 forms distinct condensates with different RNA molecules. Using criteria derived from a physical framework for explaining how compositionally distinct condensates can form spontaneously via thermodynamic considerations, we find that condensates in vitro form mainly via heterotypic interactions in binary mixtures of Whi3 and RNA. However, within these condensates, RNA molecules become dynamically arrested. As a result, in ternary systems, simultaneous additions of Whi3 and pairs of distinct RNA molecules lead to well-mixed condensates, whereas delayed addition of an RNA component results in compositional distinctness. Therefore, compositional identities of condensates can be achieved via dynamical control, being driven, at least partially, by the dynamical arrest of RNA molecules. Finally, we show that synchronizing the production of different RNAs leads to more well-mixed, as opposed to compositionally distinct condensates in vivo.

A disordered region controls cBAF activity via condensation and partner recruitment

Intrinsically disordered regions (IDRs) represent a large percentage of overall nuclear protein content. The prevailing dogma is that IDRs engage in non-specific interactions because they are poorly constrained by evolutionary selection. Here, we demonstrate that condensate formation and heterotypic interactions are distinct and separable features of an IDR within the ARID1A/B subunits of the mSWI/SNF chromatin remodeler, cBAF, and establish distinct "sequence grammars" underlying each contribution. Condensation is driven by uniformly distributed tyrosine residues, and partner interactions are mediated by non-random blocks rich in alanine, glycine, and glutamine residues. These features concentrate a specific cBAF protein-protein interaction network and are essential for chromatin localization and activity. Importantly, human disease-associated perturbations in ARID1B IDR sequence grammars disrupt cBAF function in cells. Together, these data identify IDR contributions to chromatin remodeling and explain how phase separation provides a mechanism through which both genomic localization and functional partner recruitment are achieved.

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

Dynamical control enables the formation of demixed biomolecular condensates

Macromolecular phase separation underlies the regulated formation and dissolution of biomolecular condensates. What is unclear is how condensates of distinct and shared macromolecular compositions form and coexist within cellular milieus. Here, we use theory and computation to establish thermodynamic criteria that must be satisfied to achieve compositionally distinct condensates. We applied these criteria to an archetypal ribonucleoprotein condensate and discovered that demixing into distinct protein-RNA condensates cannot be the result of purely thermodynamic considerations. Instead, demixed, compositionally distinct condensates arise due to asynchronies in timescales that emerge from differences in long-lived protein-RNA and RNA-RNA crosslinks. This type of dynamical control is also found to be active in live cells whereby asynchronous production of molecules is required for realizing demixed protein-RNA condensates. We find that interactions that exert dynamical control provide a versatile and generalizable way to influence the compositions of coexisting condensates in live cells.

Dynamical control enables the formation of demixed biomolecular condensates

Macromolecular phase separation underlies the regulated formation and dissolution of biomolecular condensates. What is unclear is how condensates of distinct and shared macromolecular compositions form and coexist within cellular milieus. Here, we use theory and computation to establish thermodynamic criteria that must be satisfied to achieve compositionally distinct condensates. We applied these criteria to an archetypal ribonucleoprotein condensate and discovered that demixing into distinct protein-RNA condensates cannot be the result of purely thermodynamic considerations. Instead, demixed, compositionally distinct condensates arise due to asynchronies in timescales that emerge from differences in long-lived protein-RNA and RNA-RNA crosslinks. This type of dynamical control is also found to be active in live cells whereby asynchronous production of molecules is required for realizing demixed protein-RNA condensates. We find that interactions that exert dynamical control provide a versatile and generalizable way to influence the compositions of coexisting condensates in live cells.

Connecting sequence features within the disordered C-terminal linker of Bacillus subtilis FtsZ to functions and bacterial cell division

Intrinsically disordered regions (IDRs) can function as autoregulators of folded enzymes to which they are tethered. One example is the bacterial cell division protein FtsZ. This includes a folded core and a C-terminal tail (CTT) that encompasses a poorly conserved, disordered C-terminal linker (CTL) and a well-conserved 17-residue C-terminal peptide (CT17). Sites for GTPase activity of FtsZs are formed at the interface between GTP binding sites and T7 loops on cores of adjacent subunits within dimers. Here, we explore the basis of autoregulatory functions of the CTT in Bacillus subtilis FtsZ (Bs-FtsZ). Molecular simulations show that the CT17 of Bs-FtsZ makes statistically significant CTL-mediated contacts with the T7 loop. Statistical coupling analysis of more than 1,000 sequences from FtsZ orthologs reveals clear covariation of the T7 loop and the CT17 with most of the core domain, whereas the CTL is under independent selection. Despite this, we discover the conservation of nonrandom sequence patterns within CTLs across orthologs. To test how the nonrandom patterns of CTLs mediate CTT-core interactions and modulate FtsZ functionalities, we designed Bs-FtsZ variants by altering the patterning of oppositely charged residues within the CTL. Such alterations disrupt the core-CTT interactions, lead to anomalous assembly and inefficient GTP hydrolysis in vitro and protein degradation, aberrant assembly, and disruption of cell division in vivo. Our findings suggest that viable CTLs in FtsZs are likely to be IDRs that encompass nonrandom, functionally relevant sequence patterns that also preserve three-way covariation of the CT17, the T7 loop, and core domain.

Sequence grammar underlying the unfolding and phase separation of globular proteins

Aberrant phase separation of globular proteins is associated with many diseases. Here, we use a model protein system to understand how the unfolded states of globular proteins drive phase separation and the formation of unfolded protein deposits (UPODs). We find that for UPODs to form, the concentrations of unfolded molecules must be above a threshold value. Additionally, unfolded molecules must possess appropriate sequence grammars to drive phase separation. While UPODs recruit molecular chaperones, their compositional profiles are also influenced by synergistic physicochemical interactions governed by the sequence grammars of unfolded proteins and cellular proteins. Overall, the driving forces for phase separation and the compositional profiles of UPODs are governed by the sequence grammars of unfolded proteins. Our studies highlight the need for uncovering the sequence grammars of unfolded proteins that drive UPOD formation and cause gain-of-function interactions whereby proteins are aberrantly recruited into UPODs.

Competing interactions give rise to two-state behavior and switch-like transitions in charge-rich intrinsically disordered proteins

The most commonly occurring intrinsically disordered proteins (IDPs) are polyampholytes, which are defined by the duality of low net charge per residue and high fractions of charged residues. Recent experiments have uncovered nuances regarding sequence–ensemble relationships of model polyampholytic IDPs. These include differences in conformational preferences for sequences with lysine vs. arginine and the suggestion that well-mixed sequences form a range of conformations, including globules, conformations with ensemble averages that are reminiscent of ideal chains, or self-avoiding walks. Here, we explain these observations by analyzing results from atomistic simulations. We find that polyampholytic IDPs generally sample two distinct stable states, namely, globules and self-avoiding walks. Globules are favored by electrostatic attractions between oppositely charged residues, whereas self-avoiding walks are favored by favorable free energies of hydration of charged residues. We find sequence-specific temperatures of bistability at which globules and self-avoiding walks can coexist. At these temperatures, ensemble averages over coexisting states give rise to statistics that resemble ideal chains without there being an actual counterbalancing of intrachain and chain-solvent interactions. At equivalent temperatures, arginine-rich sequences tilt the preference toward globular conformations whereas lysine-rich sequences tilt the preference toward self-avoiding walks. We also identify differences between aspartate- and glutamate-containing sequences, whereby the shorter aspartate side chain engenders preferences for metastable, necklace-like conformations. Finally, although segregation of oppositely charged residues within the linear sequence maintains the overall two-state behavior, compact states are highly favored by such systems.

AlphaFold and Implications for Intrinsically Disordered Proteins

Accurate predictions of the three-dimensional structures of proteins from their amino acid sequences have come of age. AlphaFold, a deep learning-based approach to protein structure prediction, shows remarkable success in independent assessments of prediction accuracy. A significant epoch in structural bioinformatics was the structural annotation of over 98% of protein sequences in the human proteome. Interestingly, many predictions feature regions of very low confidence, and these regions largely overlap with intrinsically disordered regions (IDRs). That over 30% of regions within the proteome are disordered is congruent with estimates that have been made over the past two decades, as intense efforts have been undertaken to generalize the structure-function paradigm to include the importance of conformational heterogeneity and dynamics. With structural annotations from AlphaFold in hand, there is the temptation to draw inferences regarding the "structures" of IDRs and their interactomes. Here, we offer a cautionary note regarding the misinterpretations that might ensue and highlight efforts that provide concrete understanding of sequence-ensemble-function relationships of IDRs. This perspective is intended to emphasize the importance of IDRs in sequence-function relationships (SERs) and to highlight how one might go about extracting quantitative SERs to make sense of how IDRs function.

Mechanistic Inferences From Analysis of Measurements of Protein Phase Transitions in Live Cells

The combination of phase separation and disorder-to-order transitions can give rise to ordered, semi-crystalline fibrillar assemblies that underlie prion phenomena namely, the non-Mendelian transfer of information across cells. Recently, a method known as Distributed Amphifluoric Förster Resonance Energy Transfer (DAmFRET) was developed to study the convolution of phase separation and disorder-to-order transitions in live cells. In this assay, a protein of interest is expressed to a broad range of concentrations and the acquisition of local density and order, measured by changes in FRET, is used to map phase transitions for different proteins. The high-throughput nature of this assay affords the promise of uncovering sequence-to-phase behavior relationships in live cells. Here, we report the development of a supervised method to obtain automated and accurate classifications of phase transitions quantified using the DAmFRET assay. Systems that we classify as undergoing two-state discontinuous transitions are consistent with prion-like behaviors, although the converse is not always true. We uncover well-established and surprising new sequence features that contribute to two-state phase behavior of prion-like domains. Additionally, our method enables quantitative, comparative assessments of sequence-specific driving forces for phase transitions in live cells. Finally, we demonstrate that a modest augmentation of DAmFRET measurements, specifically time-dependent protein expression profiles, can allow one to apply classical nucleation theory to extract sequence-specific lower bounds on the probability of nucleating ordered assemblies. Taken together, our approaches lead to a useful analysis pipeline that enables the extraction of mechanistic inferences regarding phase transitions in live cells.

Polyphasic linkage and the impact of ligand binding on the regulation of biomolecular condensates

Cellular matter can be spatially and temporally organized into membraneless biomolecular condensates. The current thinking is that these condensates form and dissolve via phase transitions driven by one or more condensate-specific multivalent macromolecules known as scaffolds. Cells likely regulate condensate formation and dissolution by exerting control over the concentrations of regulatory molecules, which we refer to as ligands. Wyman and Gill introduced the framework of polyphasic linkage to explain how ligands can exert thermodynamic control over phase transitions. This review focuses on describing the concepts of polyphasic linkage and the relevance of such a mechanism for controlling condensate formation and dissolution. We describe how ligand-mediated control over scaffold phase behavior can be quantified experimentally. Further, we build on recent studies to highlight features of ligands that make them suppressors vs drivers of phase separation. Finally, we highlight areas where advances are needed to further understand ligand-mediated control of condensates in complex cellular environments. These advances include understanding the effects of networks of ligands on condensate behavior and how ligands modulate phase transitions controlled by different combinations of homotypic and heterotypic interactions among scaffold macromolecules. Insights gained from the application of polyphasic linkage concepts should be useful for designing novel pharmaceutical ligands to regulate condensates.

Ligand effects on phase separation of multivalent macromolecules

Biomolecular condensates enable spatial and temporal control over cellular processes by concentrating biomolecules into nonstoichiometric assemblies. Many condensates form via reversible phase transitions of condensate-specific multivalent macromolecules known as scaffolds. Phase transitions of scaffolds can be regulated by changing the concentrations of ligands, which are defined as nonscaffold molecules that bind to specific sites on scaffolds. Here, we use theory and computation to uncover rules that underlie ligand-mediated control over scaffold phase behavior. We use the stickers-and-spacers model wherein reversible noncovalent cross-links among stickers drive phase transitions of scaffolds, and spacers modulate the driving forces for phase transitions. We find that the modulatory effects of ligands are governed by the valence of ligands, whether they bind directly to stickers versus spacers, and the relative affinities of ligand-scaffold versus scaffold-scaffold interactions. In general, all ligands have a diluting effect on the concentration of scaffolds within condensates. Whereas monovalent ligands destabilize condensates, multivalent ligands can stabilize condensates by binding directly to spacers or destabilize condensates by binding directly to stickers. Bipartite ligands that bind to stickers and spacers can alter the structural organization of scaffold molecules within condensates even when they have a null effect on condensate stability. Our work highlights the importance of measuring dilute phase concentrations of scaffolds as a function of ligand concentration in cells. This can reveal whether ligands modulate scaffold phase behavior by enabling or suppressing phase separation at endogenous levels, thereby regulating the formation and dissolution of condensates in vivo.

Ligand effects on phase separation of multivalent macromolecules

Biomolecular condensates enable spatial and temporal control over cellular processes by concentrating biomolecules into nonstoichiometric assemblies. Many condensates form via reversible phase transitions of condensate-specific multivalent macromolecules known as scaffolds. Phase transitions of scaffolds can be regulated by changing the concentrations of ligands, which are defined as nonscaffold molecules that bind to specific sites on scaffolds. Here, we use theory and computation to uncover rules that underlie ligand-mediated control over scaffold phase behavior. We use the stickers-and-spacers model wherein reversible noncovalent cross-links among stickers drive phase transitions of scaffolds, and spacers modulate the driving forces for phase transitions. We find that the modulatory effects of ligands are governed by the valence of ligands, whether they bind directly to stickers versus spacers, and the relative affinities of ligand-scaffold versus scaffold-scaffold interactions. In general, all ligands have a diluting effect on the concentration of scaffolds within condensates. Whereas monovalent ligands destabilize condensates, multivalent ligands can stabilize condensates by binding directly to spacers or destabilize condensates by binding directly to stickers. Bipartite ligands that bind to stickers and spacers can alter the structural organization of scaffold molecules within condensates even when they have a null effect on condensate stability. Our work highlights the importance of measuring dilute phase concentrations of scaffolds as a function of ligand concentration in cells. This can reveal whether ligands modulate scaffold phase behavior by enabling or suppressing phase separation at endogenous levels, thereby regulating the formation and dissolution of condensates in vivo.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Proteomic and functional mapping of cardiac NaV1.5 channel phosphorylation sites

Phosphorylation of the voltage-gated Na⁺ (Na_V) channel Na_V1.5 regulates cardiac excitability, yet the phosphorylation sites regulating its function and the underlying mechanisms remain largely unknown. Using a systematic, quantitative phosphoproteomic approach, we analyzed Na_V1.5 channel complexes purified from nonfailing and failing mouse left ventricles, and we identified 42 phosphorylation sites on Na_V1.5. Most sites are clustered, and three of these clusters are highly phosphorylated. Analyses of phosphosilent and phosphomimetic Na_V1.5 mutants revealed the roles of three phosphosites in regulating Na_V1.5 channel expression and gating. The phosphorylated serines S664 and S667 regulate the voltage dependence of channel activation in a cumulative manner, whereas the nearby S671, the phosphorylation of which is increased in failing hearts, regulates cell surface Na_V1.5 expression and peak Na⁺ current. No additional roles could be assigned to the other clusters of phosphosites. Taken together, our results demonstrate that ventricular Na_V1.5 is highly phosphorylated and that the phosphorylation-dependent regulation of Na_V1.5 channels is highly complex, site specific, and dynamic.

Information theoretic measures for quantifying sequence-ensemble relationships of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) contribute to a multitude of functions. De novo design of IDPs should open the door to modulating functions and phenotypes controlled by these systems. Recent design efforts have focused on compositional biases and specific sequence patterns as the design features. Analysis of the impact of these designs on sequence-function relationships indicates that individual sequence/compositional parameters are insufficient for describing sequence-function relationships in IDPs. To remedy this problem, we have developed information theoretic measures for sequence–ensemble relationships (SERs) of IDPs. These measures rely on prior availability of statistically robust conformational ensembles derived from all atom simulations. We show that the measures we have developed are useful for comparing sequence-ensemble relationships even when sequence is poorly conserved. Based on our results, we propose that de novo designs of IDPs, guided by knowledge of their SERs, should provide improved insights into their sequence–ensemble–function relationships.

Predicting Conformational Properties of Intrinsically Disordered Proteins from Sequence

Intrinsically disordered proteins (IDPs) can adopt a range of conformations from globules to swollen coils. This large range of conformational preferences for different IDPs raises the question of how conformational preferences are encoded by sequence. Global compositional features of a sequence such as the fraction of charged residues and the net charge per residue engender certain conformational biases. However, more specific sequence features such as the patterning of oppositely charged residues, expansion driving residues, or residues that can undergo posttranslational modifications can also influence the conformational ensembles of an IDP. Here, we outline how to calculate important global compositional features and patterning metrics that can be used to classify IDPs into different conformational classes and predict relative changes in conformation for sequences with the same amino acid composition. Although increased effort has been devoted to determining conformational properties of IDPs in recent years, quantitative predictions of conformation directly from sequence remain difficult and often inaccurate. Thus, if quantitative predictions of conformational properties are desired, then sequence-specific simulations must be performed.

Comment on "Innovative scattering analysis shows that hydrophobic disordered proteins are expanded in water"

Editors at Science requested our input on the above discussion (comment by Best et al and response by Riback et al) because both sets of authors use our data from Fuertes et al (2017) to support their arguments. The topic of discussion pertains to the discrepant inferences drawn from SAXS versus FRET measurements regarding the dimensions of intrinsically disordered proteins (IDPs) in aqueous solvents. Using SAXS measurements on labeled and unlabeled proteins, we ruled out the labels used for FRET measurements as the cause of discrepant inferences between the two methods. Instead, we propose that FRET and SAXS provide complementary readouts because of a decoupling of size and shape fluctuations that is intrinsic to finite-sized, heteropolymeric IDPs. Accounting for this decoupling resolves the discrepant inferences between the two methods, thus making a case for the utility of both methods.

Inert and seed-competent tau monomers suggest structural origins of aggregation

Tauopathies feature progressive accumulation of tau amyloids. Pathology may begin when these amplify from a protein template, or seed, whose structure is unknown. We have purified and characterized distinct forms of tau monomer—inert (M_i) and seed-competent (M_s). Recombinant M_s triggered intracellular tau aggregation, induced tau fibrillization in vitro, and self-assembled. M_s from Alzheimer’s disease also seeded aggregation and self-assembled in vitro to form seed-competent multimers. We used crosslinking with mass spectrometry to probe structural differences in M_i vs. M_s. Crosslinks informed models of local peptide structure within the repeat domain which suggest relative inaccessibility of residues that drive aggregation (VQIINK/VQIVYK) in M_i, and exposure in M_s. Limited proteolysis supported this idea. Although tau monomer has been considered to be natively unstructured, our findings belie this assumption and suggest that initiation of pathological aggregation could begin with conversion of tau monomer from an inert to a seed-competent form.

When doctors perform autopsies to look at the brain tissue of people with Alzheimer’s disease, they find toxic buildups of certain proteins – in particular, a protein called tau – in structures called ‘aggregates’. People with more severe dementia have more tau aggregates in their brain. Aggregates form when individual proteins stick together in repetitive patterns, much like the way a single Lego block might attach to another identical one. Like all proteins, tau is built from a string of amino acids that folds into a specific shape. Normally folded tau proteins do not form aggregates. It was not clear that an individual tau protein had two distinct forms—structures associated with health (“good”) or disease (“bad”).

Mirbaha et al. have now studied the folding pattern of purified tau proteins with a sophisticated technology called mass spectrometry. This technique can measure changes in tiny amounts of protein. Some of the purified proteins had been extracted from human brains (from people with and without Alzheimer’s). To detect which of the proteins were toxic, Mirbaha et al. also grew simple human cells in a dish that were designed to react specifically to the bad forms of tau. This allowed the good and bad forms of tau to be isolated.

Mirbaha et al. discovered that in the good form of tau the parts of the protein that allow it to stick to itself are hidden, folded inside. By contrast, the bad form of tau exposes the parts that allow it to aggregate, enabling the protein to build upon itself to form a large, toxic assembly.

The shape-shifting concept established by Mirbaha et al. might apply to other proteins that form toxic aggregates. This could help us to better understand how many other neurodegenerative diseases develop and progress. Recognizing that the shapes that tau forms can be categorized as either ‘good’ or ‘bad’ may also help to develop new treatments for Alzheimer’s disease. Drugs could be designed to stabilize the good form of tau, or to help remove the bad form from the brain. Furthermore, if the shape-shift described by Mirbaha et al. can be measured early enough in patients, it may allow treatments for Alzheimer’s before people have developed any detectable symptoms.

Tadpole-like Conformations of Huntingtin Exon 1 Are Characterized by Conformational Heterogeneity that Persists regardless of Polyglutamine Length

Soluble huntingtin exon 1 (Httex1) with expanded polyglutamine (polyQ) engenders neurotoxicity in Huntington's disease. To uncover the physical basis of this toxicity, we performed structural studies of soluble Httex1 for wild-type and mutant polyQ lengths. Nuclear magnetic resonance experiments show evidence for conformational rigidity across the polyQ region. In contrast, hydrogen-deuterium exchange shows absence of backbone amide protection, suggesting negligible persistence of hydrogen bonds. The seemingly conflicting results are explained by all-atom simulations, which show that Httex1 adopts tadpole-like structures with a globular head encompassing the N-terminal amphipathic and polyQ regions and the tail encompassing the C-terminal proline-rich region. The surface area of the globular domain increases monotonically with polyQ length. This stimulates sharp increases in gain-of-function interactions in cells for expanded polyQ, and one of these interactions is with the stress-granule protein Fus. Our results highlight plausible connections between Httex1 structure and routes to neurotoxicity.

Profilin reduces aggregation and phase separation of huntingtin N-terminal fragments by preferentially binding to soluble monomers and oligomers

Huntingtin N-terminal fragments (Htt-NTFs) with expanded polyglutamine tracts form a range of neurotoxic aggregates that are associated with Huntington's disease. Here, we show that aggregation of Htt-NTFs, irrespective of polyglutamine length, yields at least three phases (designated M, S, and F) that are delineated by sharp concentration thresholds and distinct aggregate sizes and morphologies. We found that monomers and oligomers make up the soluble M phase, ∼25-nm spheres dominate in the soluble S phase, and long, linear fibrils make up the insoluble F phase. Previous studies showed that profilin, an abundant cellular protein, reduces Htt-NTF aggregation and toxicity in cells. We confirm that profilin achieves its cellular effects through direct binding to the C-terminal proline-rich region of Htt-NTFs. We show that profilin preferentially binds to Htt-NTF M-phase species and destabilizes aggregation and phase separation by shifting the concentration boundaries for phase separation to higher values through a process known as polyphasic linkage. Our experiments, aided by coarse-grained computer simulations and theoretical analysis, suggest that preferential binding of profilin to the M-phase species of Htt-NTFs is enhanced through a combination of specific interactions between profilin and polyproline segments and auxiliary interactions between profilin and polyglutamine tracts. Polyphasic linkage may be a general strategy that cells utilize to regulate phase behavior of aggregation-prone proteins. Accordingly, detailed knowledge of phase behavior and an understanding of how ligands modulate phase boundaries may pave the way for developing new therapeutics against a variety of aggregation-prone proteins.

Monomeric Huntingtin Exon 1 Has Similar Overall Structural Features for Wild-Type and Pathological Polyglutamine Lengths

Huntington's disease is caused by expansion of a polyglutamine (polyQ) domain within exon 1 of the huntingtin gene (Httex1). The prevailing hypothesis is that the monomeric Httex1 protein undergoes sharp conformational changes as the polyQ length exceeds a threshold of 36-37 residues. Here, we test this hypothesis by combining novel semi-synthesis strategies with state-of-the-art single-molecule Förster resonance energy transfer measurements on biologically relevant, monomeric Httex1 proteins of five different polyQ lengths. Our results, integrated with atomistic simulations, negate the hypothesis of a sharp, polyQ length-dependent change in the structure of monomeric Httex1. Instead, they support a continuous global compaction with increasing polyQ length that derives from increased prominence of the globular polyQ domain. Importantly, we show that monomeric Httex1 adopts tadpole-like architectures for polyQ lengths below and above the pathological threshold. Our results suggest that higher order homotypic and/or heterotypic interactions within distinct sub-populations of neurons, which are inevitable at finite cellular concentrations, are likely to be the main source of sharp polyQ length dependencies of HD.

CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences

We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences.

A coarse-grained model for polyglutamine aggregation modulated by amphipathic flanking sequences

The aggregation of proteins with expanded polyglutamine (polyQ) tracts is directly relevant to the formation of neuronal intranuclear inclusions in Huntington's disease. In vitro studies have uncovered the effects of flanking sequences as modulators of the driving forces and mechanisms of polyQ aggregation in sequence segments associated with HD. Specifically, a seventeen-residue amphipathic stretch (N17) that is directly N-terminal to the polyQ tract in huntingtin decreases the overall solubility, destabilizes nonfibrillar aggregates, and accelerates fibril formation. Published results from atomistic simulations showed that the N17 module reduces the frequency of intermolecular association. Our reanalysis of these simulation results demonstrates that the N17 module also reduces interchain entanglements between polyQ domains. These two effects, which are observed on the smallest lengthscales, are incorporated into phenomenological pair potentials and used in coarse-grained Brownian dynamics simulations to investigate their impact on large-scale aggregation. We analyze the results from Brownian dynamics simulations using the framework of diffusion-limited cluster aggregation. When entanglements prevail, which is true in the absence of N17, small spherical clusters and large linear aggregates form on distinct timescales, in accord with in vitro experiments. Conversely, when entanglements are quenched and a barrier to intermolecular associations is introduced, both of which are attributable to N17, the timescales for forming small species and large linear aggregates become similar. Therefore, the combination of a reduction of interchain entanglements through homopolymeric polyQ and barriers to intermolecular associations appears to be sufficient for providing a minimalist phenomenological rationalization of in vitro observations regarding the effects of N17 on polyQ aggregation.