Biomolecular Condensates are Characterized by Interphase Electric Potentials.

Biomolecular condensates form via processes that combine phase separation and reversible associations of multivalent macromolecules. Condensates can be two- or multiphase systems defined by coexisting dense and dilute phases. Here, we show that solution ions partition asymmetrically across coexisting phases defined by condensates formed by intrinsically disordered proteins or homopolymeric RNA molecules. Our findings were enabled by direct measurements of the activities of cations and anions within coexisting phases of protein and RNA condensates. Asymmetries in ion partitioning between coexisting phases vary with protein sequence, macromolecular composition, salt concentration, and ion type. The Donnan equilibrium set up by the asymmetrical partitioning of solution ions generates interphase electric potentials known as Donnan and Nernst potentials. Our measurements show that the interphase potentials of condensates are of the same order of magnitude as membrane potentials of membrane-bound organelles. Interphase potentials quantify the degree to which microenvironments of coexisting phases are different from one another. Importantly, and based on condensate-specific interphase electric potentials, we reason that condensates are akin to capacitors that store charge. Interphase potentials should lead to electric double layers at condensate interfaces, thereby explaining recent observations of condensate interfaces being electrochemically active.

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

Biomolecular condensates are viscoelastic materials. Here, we investigate the determinants of sequence-encoded and age-dependent viscoelasticity of condensates formed by the prion-like low-complexity domain of the protein hnRNP A1 and its designed variants. We find that the dominantly viscous forms of the condensates are metastable Maxwell fluids. A Rouse-Zimm model that accounts for the network-like organization of proteins within condensates reproduces the measured viscoelastic moduli. We show that the strengths of aromatic inter-sticker interactions determine sequence-specific amplitudes of elastic and viscous moduli, and the timescales over which elastic properties dominate. These condensates undergo physical ageing on sequence-specific timescales. This is driven by mutations to spacer residues that weaken the metastability of dominantly viscous phases. The ageing of condensates is accompanied by disorder-to-order transitions, leading to the formation of non-fibrillar, beta-sheet-containing, semi-crystalline, elastic, Kelvin-Voigt solids. Our results suggest that sequence grammars, which refer to amino acid identities of stickers versus spacers in prion-like low-complexity domains, have evolved to afford control over metastabilities of dominantly viscous fluid phases of condensates. This selection is likely to render barriers for conversion from metastable fluids to globally stable solids insurmountable on functionally relevant timescales.

Direct computations of viscoelastic moduli of biomolecular condensates.

Biomolecular condensates are viscoelastic materials defined by time-dependent, sequence-specific complex shear moduli. Here, we show that viscoelastic moduli can be computed directly using a generalization of the Rouse model that leverages information regarding intra- and inter-chain contacts, which we extract from equilibrium configurations of lattice-based Metropolis Monte Carlo (MMC) simulations of phase separation. The key ingredient of the generalized Rouse model is a graph Laplacian that we compute from equilibrium MMC simulations. We compute two flavors of graph Laplacians, one based on a single-chain graph that accounts only for intra-chain contacts, and the other referred to as a collective graph that accounts for inter-chain interactions. Calculations based on the single-chain graph systematically overestimate the storage and loss moduli, whereas calculations based on the collective graph reproduce the measured moduli with greater fidelity. However, in the long time, low-frequency domain, a mixture of the two graphs proves to be most accurate. In line with the theory of Rouse and contrary to recent assertions, we find that a continuous distribution of relaxation times exists in condensates. The single crossover frequency between dominantly elastic vs dominantly viscous behaviors does not imply a single relaxation time. Instead, it is influenced by the totality of the relaxation modes. Hence, our analysis affirms that viscoelastic fluid-like condensates are best described as generalized Maxwell fluids. Finally, we show that the complex shear moduli can be used to solve an inverse problem to obtain the relaxation time spectra that underlie the dynamics within condensates. This is of practical importance given advancements in passive and active microrheology measurements of condensate viscoelasticity.

Synapsin condensation is governed by sequence-encoded molecular grammars.

Multiple biomolecular condensates coexist at the pre- and post- synapse to enable vesicle dynamics and controlled neurotransmitter release in the brain. In pre-synapses, intrinsically disordered regions (IDRs) of synaptic proteins are drivers of condensation that enable clustering of synaptic vesicles (SVs). Using computational analysis, we show that the IDRs of SV proteins feature evolutionarily conserved non-random compositional biases and sequence patterns. Synapsin-1 is essential for condensation of SVs, and its C-terminal IDR has been shown to be a key driver of condensation. Focusing on this IDR, we dissected the contributions of two conserved features namely the segregation of polar and proline residues along the linear sequence, and the compositional preference for arginine over lysine. Scrambling the blocks of polar and proline residues weakens the driving forces for forming micron-scale condensates. However, the extent of clustering in subsaturated solutions remains equivalent to that of the wild-type synapsin-1. In contrast, substituting arginine with lysine significantly weakens both the driving forces for condensation and the extent of clustering in subsaturated solutions. Co-expression of the scrambled variant of synapsin-1 with synaptophysin results in a gain-of-function phenotype in cells, whereas arginine to lysine substitutions eliminate condensation. We report an emergent consequence of synapsin-1 condensation, which is the generation of interphase pH gradients realized via differential partitioning of protons between coexisting phases. This pH gradient is likely to be directly relevant for vesicular ATPase functions and the loading of neurotransmitters. Our study highlights how conserved IDR grammars serve as drivers of synapsin-1 condensation.

Dominance analysis to assess solute contributions to multicomponent phase equilibria.

Phase separation in aqueous solutions of macromolecules underlies the generation of biomolecular condensates in cells. Condensates are membraneless bodies, representing dense, macromolecule-rich phases that coexist with the dilute, macromolecule-deficient phases. In cells, condensates comprise hundreds of different macromolecular and small molecule solutes. How do different solutes contribute to the driving forces for phase separation? To answer this question, we introduce a formalism we term energy dominance analysis. This approach rests on analysis of shapes of the dilute phase boundaries, slopes of tie lines, and changes to dilute phase concentrations in response to perturbations of concentrations of different solutes. The framework is based solely on conditions for phase equilibria in systems with arbitrary numbers of macromolecules and solution components. Its practical application relies on being able to measure dilute phase concentrations of the components of interest. The dominance framework is both theoretically facile and experimentally applicable. We present the formalism that underlies dominance analysis and establish its accuracy and flexibility by deploying it to analyze phase diagrams probed in simulations and in experiments.

Biomolecular condensates can function as inherent catalysts.

We report the discovery that chemical reactions such as ATP hydrolysis can be catalyzed by condensates formed by intrinsically disordered proteins (IDPs), which themselves lack any intrinsic ability to function as enzymes. This inherent catalytic feature of condensates derives from the electrochemical environments and the electric fields at interfaces that are direct consequences of phase separation. The condensates we studied were capable of catalyzing diverse hydrolysis reactions, including hydrolysis and radical-dependent breakdown of ATP whereby ATP fully decomposes to adenine and multiple carbohydrates. This distinguishes condensates from naturally occurring ATPases, which can only catalyze the dephosphorylation of ATP. Interphase and interfacial properties of condensates can be tuned via sequence design, thus enabling control over catalysis through sequence-dependent electrochemical features of condensates. Incorporation of hydrolase-like synthetic condensates into live cells enables activation of transcriptional circuits that depend on products of hydrolysis reactions. Inherent catalytic functions of condensates, which are emergent consequences of phase separation, are likely to affect metabolic regulation in cells.

Biomolecular condensates are characterized by interphase electric potentials.

Biomolecular condensates form via processes that combine phase separation and reversible associations of multivalent macromolecules. Condensates can be two- or multi-phase systems defined by coexisting dense and dilute phases. Here, we show that solution ions can partition asymmetrically across coexisting phases defined by condensates formed by intrinsically disordered proteins or homopolymeric RNA molecules. Our findings were enabled by direct measurements of the activities of cations and anions within coexisting phases of protein and RNA condensates. Asymmetries in ion partitioning between coexisting phases vary with protein sequence, condensate type, salt concentration, and ion type. The Donnan equilibrium set up by asymmetrical partitioning of solution ions generates interphase electric potentials known as Donnan and Nernst potentials. Our measurements show that the interphase potentials of condensates are of the same order of magnitude as membrane potentials of membrane-bound organelles. Interphase potentials quantify the degree to which microenvironments of coexisting phases are different from one another. Importantly, and based on condensate-specific interphase electric potentials, which are membrane-like potentials of membraneless bodies, we reason that condensates are mesoscale capacitors that store charge. Interphase potentials lead to electric double layers at condensate interfaces. This helps explain recent observations of condensate interfaces being electrochemically active.

Direct computations of viscoelastic moduli of biomolecular condensates.

In vitro facsimiles of biomolecular condensates are formed by different types of intrinsically disordered proteins including prion-like low complexity domains (PLCDs). PLCD condensates are viscoelastic materials defined by time-dependent, sequence-specific complex shear moduli. Here, we show that viscoelastic moduli can be computed directly using a generalization of the Rouse model and information regarding intra- and inter-chain contacts that is extracted from equilibrium configurations of lattice-based Metropolis Monte Carlo (MMC) simulations. The key ingredient of the generalized Rouse model is the Zimm matrix that we compute from equilibrium MMC simulations. We compute two flavors of Zimm matrices, one referred to as the single-chain model that accounts only for intra-chain contacts, and the other referred to as a collective model, that accounts for inter-chain interactions. The single-chain model systematically overestimates the storage and loss moduli, whereas the collective model reproduces the measured moduli with greater fidelity. However, in the long time, low-frequency domain, a mixture of the two models proves to be most accurate. In line with the theory of Rouse, we find that a continuous distribution of relaxation times exists in condensates. The single crossover frequency between dominantly elastic versus dominantly viscous behaviors is influenced by the totality of the relaxation modes. Hence, our analysis suggests that viscoelastic fluid-like condensates are best described as generalized Maxwell fluids. Finally, we show that the complex shear moduli can be used to solve an inverse problem to obtain distributions of relaxation times that underlie the dynamics within condensates.

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.

A High-Avidity, Thermostable, and Low-Cost Synthetic Capture for Ultrasensitive Detection and Quantification of Viral Antigens and Aerosols.

Lateral flow assays (LFAs) are currently the most popular point-of-care diagnostics, rapidly transforming disease diagnosis from expensive doctor checkups and laboratory-based tests to potential on-the-shelf commodities. Yet, their sensitive element, a monoclonal antibody, is expensive to formulate, and their long-term storage depends on refrigeration technology that cannot be met in resource-limited areas. In this work, LCB1 affibodies (antibody mimetic miniproteins) were conjugated to bovine serum albumin (BSA) to afford a high-avidity synthetic capture (LCB1-BSA) capable of detecting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and virus like particles (VLPs). Substituting the monoclonal antibody 2B04 for LCB1-BSA (stable up to 60 °C) significantly improved the thermal stability, shelf life, and affordability of plasmonic-fluor-based LFAs (p-LFAs). Furthermore, this substitution significantly improved the sensitivity of p-LFAs toward the spike protein and VLPs with precise quantitative ability over 2 and 3 orders of magnitude, respectively. LCB1-BSA sensors could detect VLPs at 100-fold lower concentrations, and this improvement, combined with their robust nature, enabled us to develop an aerosol sampling technology to detect aerosolized viral particles. Synthetic captures like LCB1-BSA can increase the ultrasensitivity, availability, sustainability, and long-term accuracy of LFAs while also decreasing their manufacturing costs.

Intrinsic disorder: A term to define the specific physicochemical characteristic of protein conformational heterogeneity.

In his commentary in this issue of Molecular Cell,1 Struhl reasons that the term "intrinsically disordered regions" represents a vague and confusing concept for protein function. However, the term "intrinsically disordered" highlights the important physicochemical characteristic of conformational heterogeneity. Thus, "intrinsically disordered" is the counterpart to the term "folded, " with neither term having specific functional implications.

Dominance Analysis: A formalism to uncover dominant energetic contributions to biomolecular condensate formation in multicomponent systems.

Phase separation in aqueous solutions of macromolecules is thought to underlie the generation of biomolecular condensates in cells. Condensates are membraneless bodies, representing dense, macromolecule-rich phases that coexist with the dilute, macromolecule-deficient phase. In cells, condensates comprise hundreds of different macromolecular and small molecule solutes. Do all components contribute equally or very differently to the driving forces for phase separation? Currently, we lack a coherent formalism to answer this question, a gap we remedy in this work through the introduction of a formalism we term energy dominance analysis. This approach rests on model-free analysis of shapes of the dilute arms of phase boundaries, slopes of tie lines, and changes to dilute phase concentrations in response to perturbations of concentrations of different solutes. We present the formalism that underlies dominance analysis, and establish its accuracy and flexibility by deploying it to analyse phase spaces probed in silico, in vitro , and in cellulo .

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.

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.

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.

Tear down this wall: phosphorylation regulates the internal interfaces of postsynaptic condensates.

Can the fusion/fission of biomolecular condensates be regulated in cells? In a recent study, Wu et al. show that phosphorylation of a key scaffold protein that drives condensates in postsynaptic densities modulates the apparent miscibility of underlying components, thus enabling intracondensate demixing-to-mixing transitions.

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.

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.

RNAs undergo phase transitions with lower critical solution temperatures.

Co-phase separation of RNAs and RNA-binding proteins drives the biogenesis of ribonucleoprotein granules. RNAs can also undergo phase transitions in the absence of proteins. However, the physicochemical driving forces of protein-free, RNA-driven phase transitions remain unclear. Here we report that various types of RNA undergo phase separation with system-specific lower critical solution temperatures. This entropically driven phase separation is an intrinsic feature of the phosphate backbone that requires Mg2+ ions and is modulated by RNA bases. RNA-only condensates can additionally undergo enthalpically favourable percolation transitions within dense phases. This is enabled by a combination of Mg2+-dependent bridging interactions between phosphate groups and RNA-specific base stacking and base pairing. Phase separation coupled to percolation can cause dynamic arrest of RNAs within condensates and suppress the catalytic activity of an RNase P ribozyme. Our work highlights the need to incorporate RNA-driven phase transitions into models for ribonucleoprotein granule biogenesis.

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.