Sequence-specific interactions determine viscoelasticity and aging dynamics of protein condensates

Tunable metastability of condensates reconciles their dual roles in amyloid fibril formation

Stress granules form via co-condensation of RNA-binding proteins containing prion-like low complexity domains (PLCDs) with RNA molecules. Homotypic interactions among PLCDs can drive amyloid fibril formation that is enhanced by ALS-associated mutations. We report that condensation- versus fibril-driving homotypic interactions are separable for A1-LCD, the PLCD of hnRNPA1. Separable interactions lead to thermodynamically metastable condensates and globally stable fibrils. Interiors of condensates suppress fibril formation whereas interfaces have the opposite effect. ALS-associated mutations enhance the stability of fibrils and weaken condensate metastability, thus enhancing the rate of fibril formation. We designed mutations to enhance A1-LCD condensate metastability and discovered that stress granule disassembly in cells can be restored even when the designed variants carry ALS-causing mutations. Therefore, fibril formation can be suppressed by condensate interiors that function as sinks. Condensate sink potentials are influenced by their metastability, which is tunable through separable interactions even among minority components of stress granules.

Decoupling Phase Separation and Fibrillization Preserves Activity of Biomolecular Condensates

Age-dependent transition of metastable, liquid-like protein condensates to amyloid fibrils is an emergent phenomenon of numerous neurodegeneration-linked protein systems. A key question is whether the thermodynamic forces underlying reversible phase separation and maturation to irreversible amyloids are distinct and separable. Here, we address this question using an engineered version of the microtubule-associated protein Tau, which forms biochemically active condensates. Liquid-like Tau condensates exhibit rapid aging to amyloid fibrils under quiescent, cofactor-free conditions. Tau condensate interface promotes fibril nucleation, impairing their activity to recruit tubulin and catalyze microtubule assembly. Remarkably, a small molecule metabolite, L-arginine, selectively impedes condensate-to-fibril transition without perturbing phase separation in a valence and chemistry-specific manner. By heightening the fibril nucleation barrier, L-arginine counteracts age-dependent decline in the biochemical activity of Tau condensates. These results provide a proof-of-principle demonstration that small molecule metabolites can enhance the metastability of protein condensates against a liquid-to-amyloid transition, thereby preserving condensate function.

Chemically Informed Coarse-Graining of Electrostatic Forces in Charge-Rich Biomolecular Condensates

Biomolecular condensates composed of highly charged biomolecules, such as DNA, RNA, chromatin, and nucleic-acid binding proteins, are ubiquitous in the cell nucleus. The biophysical properties of these charge-rich condensates are largely regulated by electrostatic interactions. Residue-resolution coarse-grained models that describe solvent and ions implicitly are widely used to gain mechanistic insights into the biophysical properties of condensates, offering transferability, computational efficiency, and accurate predictions for multiple systems. However, their predictive accuracy diminishes for charge-rich condensates due to the implicit treatment of solvent and ions. Here, we present Mpipi-Recharged, a residue-resolution coarse-grained model that improves the description of charge effects in biomolecular condensates containing disordered proteins, multidomain proteins, and/or disordered single-stranded RNAs. Mpipi-Recharged introduces a pair-specific asymmetric Yukawa electrostatic potential, informed by atomistic simulations. We show that this asymmetric coarse-graining of electrostatic forces captures intricate effects, such as charge blockiness, stoichiometry variations in complex coacervates, and modulation of salt concentration, without requiring explicit solvation. Mpipi-Recharged provides excellent agreement with experiments in predicting the phase behavior of highly charged condensates. Overall, Mpipi-Recharged improves the computational tools available to investigate the physicochemical mechanisms regulating biomolecular condensates, enhancing the scope of computer simulations in this field.

Decoding phase separation of prion-like domains through data-driven scaling laws

Proteins containing prion-like low complexity domains (PLDs) are common drivers of the formation of biomolecular condensates and are prone to misregulation due to amino acid mutations. Here, we exploit the accuracy of our residue-resolution coarse-grained model, Mpipi, to quantify the impact of amino acid mutations on the stability of 140 PLD mutants from six proteins (hnRNPA1, TDP43, FUS, EWSR1, RBM14, and TIA1). Our simulations reveal the existence of scaling laws that quantify the range of change in the critical solution temperature of PLDs as a function of the number and type of amino acid sequence mutations. These rules are consistent with the physicochemical properties of the mutations and extend across the entire family tested, suggesting that scaling laws can be used as tools to predict changes in the stability of PLD condensates. Our work offers a quantitative lens into how the emergent behavior of PLD solutions vary in response to physicochemical changes of single PLD molecules.

Reconciling competing models on the roles of condensates and soluble complexes in transcription factor function

Phase separation explains the exquisite spatial and temporal regulation of many biological processes, but the role of transcription factor-mediated condensates in gene regulation is contentious, requiring head-to-head comparison of competing models. Here, we focused on the prototypical yeast transcription factor Gcn4 and assessed two models for gene transcription activation, i.e., mediated via soluble complexes or transcriptional condensates. Both models rely on the ability of transcription factors and coactivators to engage in multivalent interactions. Unexpectedly, we found that propensity to form homotypic Gcn4 condensates does not correlate well with transcriptional activity. Contrary to prevailing models, binding to DNA suppresses Gcn4 phase separation. Notably, the ability of Gcn4 to form soluble complexes with coactivator subunit Med15 closely mirrored the propensity to recruit Med15 into condensates, indicating that these properties are intertwined and cautioning against interpretation of mutational data without head-to-head comparisons. However, Gcn4 variants with the highest affinity for Med15 do not function as well as expected and instead have activities that reflect their abilities to phase separate with Med15. These variants therefore indeed form cellular condensates, and those attenuate activity. Our results show that transcription factors can function as soluble complexes as well as condensates, reconciling two seemingly opposing models, and have implications for other phase-separating systems.

Decoding Biomolecular Condensate Dynamics: An Energy Landscape Approach

A significant fraction of eukaryotic proteins contain low-complexity sequence elements with unknown functions. Many of these sequences are prone to form biomolecular condensates with unique material and dynamic properties. Mutations in low-complexity regions often result in abnormal phase transitions into pathological solid-like states. Therefore, understanding how the low-complexity sequence patterns encode the material properties of condensates is crucial for uncovering the cellular functions and evolutionary forces behind the emergence of low-complexity regions in proteins. In this work, we employ an alphabet-free energy landscape framework of the stickers and spacers to dissect how the low complexity patterns of proteins encode the material properties of condensates. We find a broad phase diagram of material properties determined by distinct energy landscape features, showing that periodic repeat motifs promote elastic-dominated while random sequences are viscous-dominated properties. We find that a certain degree of sticker periodicity is necessary to maintain the fluidity of condensates, preventing them from forming glassy or solid-like states. Finally, we show that the energy landscape framework captures viscoelastic trends seen in the recent experiments on prion domains and makes predictions for systematic variation of protein condensate viscoelasticity via altering the periodicity and strength of sticker motifs.

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Molecular Drivers of Aging in Biomolecular Condensates: Desolvation, Rigidification, and Sticker Lifetimes

Biomolecular condensates are dynamic intracellular entities defined by their sequence- and composition-encoded material properties. During aging, these properties can change dramatically, potentially leading to pathological solidlike states, the mechanisms of which remain poorly understood. Recent experiments reveal that the aging of condensates involves a complex interplay of solvent depletion, strengthening of sticker links, and the formation of rigid structural segments such as beta fibrils. In this study, we use various coarse-grained models to investigate how solvent expulsion, biopolymer chain rigidity, and the lifetimes of sticker contacts influence the viscoelastic properties and aging dynamics of condensates. We find that the rigidity of the biopolymer backbone is essential for replicating the predominant elastic behavior observed in experiments. In contrast, models using fully flexible chains-an assumption common in simulations of intrinsically disordered proteins-fail to exhibit a dominant elastic regime. We also demonstrate that altering the solvent content within condensates affects the crossover between storage and loss moduli. This suggests that desolvation plays a significant role in condensate aging by promoting the transition from a viscous to an elastic state. Furthermore, the lifetime of sticker pairs profoundly influences the mature state of the condensates; short-lived stickers lead to a Maxwell fluid behavior, while longer-lived, irreversibly cross-linked stickers result in solidlike properties, consistent with the Kelvin-Voigt model. Finally, by incorporating the chain rigidification, desolvation, and sticker pair formation into a nonequilibrium dynamic aging simulation, we show the molecular mechanism of forming solid shells around the condensate surfaces observed in a recent experimental report.

Solutes unmask differences in clustering versus phase separation of FET proteins

Phase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.

Label-Free Techniques for Probing Biomolecular Condensates

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and expansive library of tools has been developed to investigate various aspects and properties, encompassing structural and compositional information, material properties, and their evolution throughout the life cycle from formation to eventual dissolution. This Review presents an overview of the expanded set of tools and methods that researchers use to probe the properties of biomolecular condensates across diverse scales of length, concentration, stiffness, and time. In particular, we review recent years' exciting development of label-free techniques and methodologies. We broadly organize the set of tools into 3 categories: (1) imaging-based techniques, such as transmitted-light microscopy (TLM) and Brillouin microscopy (BM), (2) force spectroscopy techniques, such as atomic force microscopy (AFM) and the optical tweezer (OT), and (3) microfluidic platforms and emerging technologies. We point out the tools' key opportunities, challenges, and future perspectives and analyze their correlative potential as well as compatibility with other techniques. Additionally, we review emerging techniques, namely, differential dynamic microscopy (DDM) and interferometric scattering microscopy (iSCAT), that have huge potential for future applications in studying biomolecular condensates. Finally, we highlight how some of these techniques can be translated for diagnostics and therapy purposes. We hope this Review serves as a useful guide for new researchers in this field and aids in advancing the development of new biophysical tools to study biomolecular condensates.

Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations

Material properties of phase-separated biomolecular condensates, enriched with disordered proteins, dictate many cellular functions. Contrary to the progress made in understanding the sequence-dependent phase separation of proteins, little is known about the sequence determinants of condensate material properties. Using the hydropathy scale and Martini models, we computationally decipher these relationships for charge-rich disordered protein condensates. Our computations yield dynamical, rheological, and interfacial properties of condensates that are quantitatively comparable with experimentally characterized condensates. Interestingly, we find that the material properties of model and natural proteins respond similarly to charge segregation, despite different sequence compositions. Molecular interactions within the condensates closely resemble those within the single-chain ensembles. Consequently, the material properties strongly correlate with molecular contact dynamics and single-chain structural properties. We demonstrate the potential to harness the sequence characteristics of disordered proteins for predicting and engineering the material properties of functional condensates, with insights from the dilute phase properties.

Backbone interactions and secondary structures in phase separation of disordered proteins

Intrinsically disordered proteins (IDPs) are one of the major drivers behind the formation and characteristics of biomolecular condensates. Due to their inherent flexibility, the backbones of IDPs are significantly exposed, rendering them highly influential and susceptible to biomolecular phase separation. In densely packed condensates, exposed backbones have a heightened capacity to interact with neighboring protein chains, which might lead to strong coupling between the secondary structures and phase separation and further modulate the subsequent transitions of the condensates, such as aging and fibrillization. In this mini-review, we provide an overview of backbone-mediated interactions and secondary structures within biomolecular condensates to underscore the importance of protein backbones in phase separation. We further focus on recent advances in experimental techniques and molecular dynamics simulation methods for probing and exploring the roles of backbone interactions and secondary structures in biomolecular phase separation involving IDPs.

Biomolecular condensates form spatially inhomogeneous network fluids

The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.

Active learning of the thermodynamics-dynamics trade-off in protein condensates

Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.

Stress granule formation helps to mitigate neurodegeneration

Cellular stress pathways that inhibit translation initiation lead to transient formation of cytoplasmic RNA/protein complexes known as stress granules. Many of the proteins found within stress granules and the dynamics of stress granule formation and dissolution are implicated in neurodegenerative disease. Whether stress granule formation is protective or harmful in neurodegenerative conditions is not known. To address this, we took advantage of the alphavirus protein nsP3, which selectively binds dimers of the central stress granule nucleator protein G3BP (rin in Drosophila) and markedly reduces stress granule formation without directly impacting the protein translational inhibitory pathways that trigger stress granule formation. In Drosophila and rodent neurons, reducing stress granule formation with nsP3 had modest impacts on lifespan even in the setting of serial stress pathway induction. In contrast, reducing stress granule formation in models of ataxia, amyotrophic lateral sclerosis and frontotemporal dementia largely exacerbated disease phenotypes. These data support a model whereby stress granules mitigate, rather than promote, neurodegenerative cascades.

Design of intrinsically disordered protein variants with diverse structural properties

Intrinsically disordered proteins (IDPs) perform a wide range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Designing IDPs with specific structural or functional properties has, however, been difficult, in part because determining accurate conformational ensembles of IDPs generally requires a combination of computational modelling and experiments. Motivated by recent advancements in efficient physics-based models for simulations of IDPs, we have developed a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs with different levels of compaction and that vary more than 100 fold in their propensity to undergo phase separation, even while keeping a fixed amino acid composition. We experimentally tested designs of variants of the low-complexity domain of hnRNPA1 and find high accuracy in our computational predictions, both in terms of single-chain compaction and propensity to undergo phase separation. We analyze the sequence features that determine changes in compaction and propensity to phase separate and find an overall good agreement with previous findings for naturally occurring sequences. Our general, physics-based method enables the design of disordered sequences with specified conformational properties. Our algorithm thus expands the toolbox for protein design to include also the most flexible proteins and will enable the design of proteins whose functions exploit the many properties afforded by protein disorder.

Theory and Simulation of Multiphase Coexistence in Biomolecular Mixtures

Biomolecular condensates constitute a newly recognized form of spatial organization in living cells. Although many condensates are believed to form as a result of phase separation, the physicochemical properties that determine the phase behavior of heterogeneous biomolecular mixtures are only beginning to be explored. Theory and simulation provide invaluable tools for probing the relationship between molecular determinants, such as protein and RNA sequences, and the emergence of phase-separated condensates in such complex environments. This review covers recent advances in the prediction and computational design of biomolecular mixtures that phase-separate into many coexisting phases. First, we review efforts to understand the phase behavior of mixtures with hundreds or thousands of species using theoretical models and statistical approaches. We then describe progress in developing analytical theories and coarse-grained simulation models to predict multiphase condensates with the molecular detail required to make contact with biophysical experiments. We conclude by summarizing the challenges ahead for modeling the inhomogeneous spatial organization of biomolecular mixtures in living cells.