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We adapt the Edwards–Muthukumar theoretical framework for a single polymer chain to investigate the interplay between proton binding and counterion condensation for poly-acids. We find that changes to pH enable non-monotonic transitions between anti- and conventional polyelectrolyte behaviors. In the former, the net charge and the overall dimensions increase with increasing salt concentration, while the converse is true for conventional polyelectrolytes. The polymeric nature and local solvent polarization drive significant pKa shifts when compared to the values of reference monoacids. These pKa shifts are enhanced in semi-flexible chains. 

Biomolecular condensates formed by intrinsically disordered proteins (IDPs) are semidilute solutions. These can be approximated as solutions of blob-sized segments, which are peptide-sized motifs. We leveraged the blob picture and molecular dynamics simulations to quantify differences between interresidue interactions in model compound and peptide-based mimics of dense versus dilute phases. The all-atom molecular dynamics simulations use a polarizable forcefield. In model compound solutions, the interactions between aromatic residues are stronger than interactions between cationic and aromatic residues. This holds in dilute and dense phases. Cooperativity within dense phases enhances pairwise interactions leading to finite-sized nanoscale clusters. The results for peptidebased condensates paint a different picture. Backbone amides add valence to the associating molecules. While this enhances pairwise inter-residue interactions in dilute phases, it weakens pair interactions in dense phases, doing so in a concentration-dependent manner. Weakening of pair interactions enables fluidization characterized by short-range order and long-range disorder. The higher valence afforded by the peptide backbone generates system-spanning networks. As a result, dense phases of peptides are best described as percolated network fluids. Overall, our results show how peptide backbones enhance pairwise interactions in dilute phases while weakening these interactions to enable percolation within dense phases. 

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 in cells. We report an emergent consequence of synapsin-1 condensation, which is the generation of interphase pH gradients that is 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 studies highlight how conserved IDR grammars serve as drivers of synapsin-1 condensation. 

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. 

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. 

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. 

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. 

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.