Jeetain Mittal

Fused in sarcoma (FUS) is an RNA‐binding protein that undergoes phase separation with RNA and other cellular components, forming ribonucleoprotein (RNP) granules. While recent advances in the study of biomolecular phase separation have focused on protein–protein interactions, information on the molecular details of protein–RNA interactions within condensates remains limited. Here, we demonstrate how RNA modulates the phase separation of the low‐complexity (LC) and arginine–glycine–glycine motif (RGG1) domains of FUS—low RNA concentrations enhance protein phase separation and excess RNA disrupts it. Integrating biochemical assays, NMR spectroscopy, and molecular dynamics simulations, we show that RNA incorporates into FUS condensates, reducing condensate density, drawing in water and ions, and enhancing local and diffusional motion. Whereas RNA binding in the dispersed phase primarily involves RGG1, within the condensed phase both LC and RGG1 contribute to RNA interactions. A diverse set of interactions between amino acids and RNA moieties, including prominent glutamine contacts, contributes to FUS‐RNA co‐condensates. RNA displaces RGG‐mediated protein contacts while enhancing LC–LC interactions, providing a molecular basis for RNA‐driven condensate interaction network remodeling. Furthermore, RNA accelerates the liquid‐to‐solid transition of FUS LC‐RGG1 condensates. Together, these results provide mechanistic insight into how RNA regulates condensate assembly, dynamics, and maturation.

Fused in sarcoma (FUS) is an RNA‐binding protein that undergoes phase separation with RNA and other cellular components, forming ribonucleoprotein (RNP) granules. While recent advances in the study of biomolecular phase separation have focused on protein–protein interactions, information on the molecular details of protein–RNA interactions within condensates remains limited. Here, we demonstrate how RNA modulates the phase separation of the low‐complexity (LC) and arginine–glycine–glycine motif (RGG1) domains of FUS—low RNA concentrations enhance protein phase separation and excess RNA disrupts it. Integrating biochemical assays, NMR spectroscopy, and molecular dynamics simulations, we show that RNA incorporates into FUS condensates, reducing condensate density, drawing in water and ions, and enhancing local and diffusional motion. Whereas RNA binding in the dispersed phase primarily involves RGG1, within the condensed phase both LC and RGG1 contribute to RNA interactions. A diverse set of interactions between amino acids and RNA moieties, including prominent glutamine contacts, contributes to FUS‐RNA co‐condensates. RNA displaces RGG‐mediated protein contacts while enhancing LC–LC interactions, providing a molecular basis for RNA‐driven condensate interaction network remodeling. Furthermore, RNA accelerates the liquid‐to‐solid transition of FUS LC‐RGG1 condensates. Together, these results provide mechanistic insight into how RNA regulates condensate assembly, dynamics, and maturation.

Biomolecular condensates exhibit spontaneous electrochemical microenvironments characterized by asymmetric ion distributions and pH gradients that emerge from protein-sequence-dependent charge regulation. Despite their biological importance, mechanistic understanding of these microenvironments has been constrained by the absence of computationally tractable frameworks capable of treating proton exchange, counterion partitioning, and buffer equilibria on consistent thermodynamic footing. Here, we introduce the buffered Charge-Regulation Monte Carlo (b-CR-MC) framework, which couples grand-canonical exchange of ions and buffer species with explicit charge regulation of titratable residues. By extending the CR-MC ion-merging strategy to multicomponent reservoirs and employing the restricted primitive model, b-CR-MC achieves computational efficiency while maintaining thermodynamic rigor, achievingquantitative agreement with the more expensive generalized grand-reaction Monte Carlo approach. Applied to full-length FUS (net positive) and PGL-3 (net negative) under physiological conditions, the framework reveals sequence-dependent pH gradients: the dense phase of FUS exhibits an alkaline shift, while that of PGL-3 exhibits an acidic shift, in both cases driving the condensate interior toward the protein's isoelectric point. Slab-geometry simulations further resolve the Donnan potential and continuous ion profiles across the condensate interface, confirming the direction of these electrochemical shifts. Additionally, we identify spatially resolved buffer depletion within dense phases, establishing that dynamic charge regulation is a primary determinant rather than a secondary correction to condensate electrochemistry. By establishing a sequence-resolved, thermodynamically consistent computational platform, b-CR-MC enables quantitative prediction of how mutations and post-translational modifications reprogram condensate microenvironments across biological and pathophysiological contexts.

The dysregulation of chromatin organization has been associated with numerous forms of neurological disease. In the ANAPC7 neurodevelopmental syndrome, a disease mechanistically linked to defective proteasomal degradation, the mitotic protein Ki-67 accumulates abnormally in heterochromatin compartments. Here, we investigate Ki-67’s role in heterochromatin through in vivo examination of neurons from two relevant genetic mouse models, in vitro assays and computational studies. We find that Ki-67 modulates the size and number of heterochromatin compartments in neurons. Furthermore, we demonstrate that an engineered Ki-67 construct enhances the propensity of HP1α and nucleosome arrays to form condensates in vitro, a process that is mediated through a complex network of electrostatic interactions and is robust to relevant histone post-translational modifications. These observations suggest that Ki-67 may regulate heterochromatin through a phase separation mechanism involving additional heterochromatin components, thus providing insights into the roles of Ki-67 during both typical neurodevelopment and in disease.

Biomolecular condensates (BMCs) organize cellular biochemistry by concentrating selected molecules into dynamic membrane-free compartments. Yet the molecular parameters that determine not only whether condensates form, but also how they behave and what they do, remain poorly defined. Here we show that scaffold binding affinity (K _d ) is a quantitative determinant of condensate phase behavior, internal dynamics and biochemical output. Using a modular SUMO-SIM system in which scaffold valency was held constant while binding affinity was systematically varied, we found that affinity governs the phase boundary, resistance to chemical perturbation, and molecular mobility of condensates in vitro and in human cells. In multicomponent mixtures, the highest-affinity scaffold dominated dense-phase composition and dynamics, revealing a hierarchical rule for condensate organization. Finally, affinity-dependent changes in condensate dynamics translated into tunable enzyme activity, establishing binding energetics as an engineerable parameter for programming condensate biochemistry.

Neurons can maintain proteostasis by extruding protein aggregates and damaged organelles via large extracellular vesicles called exophers. However, the biophysical rules governing exopher cargo selection remain poorly understood. Here, we discovered that biomolecular condensates can localize to exophers and investigated whether condensate material properties-ranging from liquids to dynamically arrested gels-determine their recruitment to exophers. By reprogramming interactions in a multidomain protein, we tuned condensate properties and linked them to neuronal exopher recruitment using a multidisciplinary approach combining in vivo dynamics, in vitro material properties, and molecular dynamics simulations. Our findings reveal that gel-like condensates with slower dynamics and higher viscoelasticity localize to exophers more avidly than dynamic liquid-like condensates, demonstrating a strong correlation between condensate dynamics and exopher recruitment. This work lays the framework for investigating the biophysical determinants of exopher cargo selection, providing critical insights into the influence of proteome material state on neuronal protein quality control.

Enhancing enzyme performance without protein engineering remains a central challenge in biocatalysis. Here, we report the unusual discovery that nanoparticles densely functionalized with DNA, commonly known as spherical nucleic acids (SNAs), can bind enzymes without chemical conjugation, affinity tags, or engineered recognition motifs and substantially increase catalytic activity. Using cytochrome c as a model peroxidase, we show that noncovalent binding to SNAs increases the apparent turnover number by up to 15-fold. Mechanistic studies by varying DNA density, length, and nanoparticle core identity reveal that activity enhancement does not arise from free DNA or the nanoparticle core alone but from the three-dimensional, high-density presentation of DNA at the nanoparticle surface. Consequently, similar effects are observed when gold cores are replaced with glucose oxidase or antibody cores. Moreover, activity modulation also depends on DNA sequence, establishing sequence design as a programmable handle for tuning enzyme output. All-atom molecular dynamics simulations, binding studies, and circular dichroism further reveal that base-specific interactions reshape enzyme conformational flexibility and increase active-site accessibility. This effect generalizes beyond cytochrome c to catalase and carbonic anhydrase. Together, these findings establish SNAs as adaptable, sequence-programmable platforms for enhancing and coordinating biocatalysis and expand their functional scope into enzyme regulation.

TAR DNA binding protein 43 (TDP-43), a key protein linked to ALS pathology, undergoes phase separation and forms functional assemblies via condensation within cells. The conserved region (CR) within its C-terminal domain (CTD) mediates self-assembly through helix–helix interactions, while the flanking intrinsically disordered regions (IDRs) contribute to phase separation through transient interactions involving aromatic and hydrophobic residues. The CTD contains ten methionine residues distributed equally between these regions, making it particularly susceptible to oxidative modifications. While methionine oxidation is known to impair TDP-43 phase separation, neither the precise mechanism nor the specific contribution of methionines in the CR compared to the IDRs has been determined. Here, we combine NMR spectroscopy and molecular dynamics (MD) simulations to reveal if and how methionine oxidation in each region differentially affects CTD structure and phase separation. To assess the change of secondary structure caused by oxidation, we measured NMR random coil chemical shift values for methionine sulfoxide. Oxidation of CR methionines disrupts helical structure and directly impairs intermolecular helical association, while oxidation of IDR methionines disrupts long-range contacts. Hence, oxidation of methionines in both regions contributes to impaired phase separation, albeit through different mechanisms. These findings establish methionines as critical redox-sensitive modulators in TDP-43 phase behavior and provide molecular insights into how oxidative stress may contribute to TDP-43 dysregulation in neurodegenerative diseases.

Biomolecular condensates exhibit spontaneous electrochemical microenvironments characterized by asymmetric ion distributions and pH gradients that emerge from protein-sequence-dependent charge regulation. Despite their biological importance, mechanistic understanding of these microenvironments has been constrained by the absence of computationally tractable frameworks capable of treating proton exchange, counterion partitioning, and buffer equilibria on consistent thermodynamic footing. Here, we introduce the buffered Charge-Regulation Monte Carlo (b-CR-MC) framework, which couples grand-canonical exchange of ions and buffer species with explicit charge regulation of titratable residues. By extending the CR-MC ion-merging strategy to multicomponent reservoirs and employing the Restricted Primitive Model, b-CR-MC achieves computational efficiency while maintaining thermodynamic rigor, with quantitative agreement to the more expensive generalized G-RxMC approach. Applied to full-length FUS (net positive) and PGL-3 (net negative) under physiological conditions, the framework reveals sequence-dependent pH gradients: the dense phase of FUS exhibits an alkaline shift, while PGL-3 exhibits an acidic shift, in both cases driving the condensate interior toward the protein’s isoelectric point. Slab-geometry simulations further resolve the Donnan potential and continuous ion profiles across the condensate interface, confirming the direction and magnitude of these electrochemical shifts. Additionally, we identify spatially resolved buffer depletion within dense phases, establishing that dynamic charge regulation is a primary determinant rather than a secondary correction to condensate electrochemistry. By establishing a sequence-resolved, thermodynamically consistent computational platform, b-CR-MC enables quantitative prediction of how mutations and post-translational modifications reprogram condensate microenvironments across biological and pathophysiological contexts.

Biomolecular condensates create distinct solvation environments in which the ionization equilibria of amino acid side chains may differ markedly from those in a bulk aqueous solution. Here, we use all-atom continuous constant pH molecular dynamics simulations to investigate the changes to the pK_a values of titratable residues between the coexisting phases of biomolecular condensates. We found that protonated states are favored in the condensate, resulting in the stabilization of charged forms of cationic residues and neutral forms of anionic residues. The effect is consistent across condensates formed by five peptide sequences, suggesting that the preference for protonated states is a general feature of the condensate microenvironment. These results highlight that differences in solvation environments between coexisting phases are key determinants of charge regulation in phase-separating proteins.