Crossing boundaries of light microscopy resolution discerns novel assemblies in the nucleolus.

The nucleolus is the largest membraneless organelle and nuclear body in mammalian cells. It is primarily involved in the biogenesis of ribosomes, essential macromolecular machines responsible for synthesizing all proteins required by the cell. The assembly of ribosomes is evolutionarily conserved and accounts for the most energy-consuming cellular process needed for cell growth, proliferation, and homeostasis. Despite the significance of this process, the substructural mechanistic principles of the nucleolar function in preribosome biogenesis have only recently begun to emerge. Here, we provide a new perspective using advanced super-resolution microscopy and single-molecule MINFLUX nanoscopy on the mechanistic principles governing ribosomal RNA-seeded nucleolar formation and the resulting tripartite suborganization of the nucleolus driven, in part, by liquid-liquid phase separation. With recent advances in the cryogenic electron microscopy (cryoEM) structural analysis of ribosome biogenesis intermediates, we highlight the current understanding of the step-wise assembly of preribosomal subunits in the nucleolus. Finally, we address how novel anticancer drug candidates target early steps in ribosome biogenesis to exploit these essential dependencies for growth arrest and tumor control.

Prediction of Antibody Viscosity from Dilute Solution Measurements.

The high antibody doses required to achieve a therapeutic effect often necessitate high-concentration products that can lead to challenging viscosity issues in production and delivery. Predicting antibody viscosity in early development can play a pivotal role in reducing late-stage development costs. In recent years, numerous efforts have been made to predict antibody viscosity through dilute solution measurements. A key finding is that the entanglement of long, flexible complexes contributes to the sharp rise in antibody viscosity at the required dosing. This entanglement model establishes a connection between the two-body binding affinity and the many-body viscosity. Exploiting this insight, this study connects dilute solution measurements of self-association to high-concentration viscosity profiles to quantify the relationship between these regimes. The resulting model has exhibited success in predicting viscosity at high concentrations (around 150 mg/mL) from dilute solution measurements, with only a few outliers remaining. Our physics-based approach provides an understanding of fundamental physics, interpretable connections to experimental data, the potential to extrapolate beyond training conditions, and the capacity to effectively explain the physical mechanics behind these outliers. Conducting hypothesis-driven experiments that specifically target the viscosity and relaxation mechanisms of outlier molecules may allow us to unravel the intricacies of their behavior and, in turn, enhance the performance of our model.

Polyubiquitin ligand-induced phase transitions are optimized by spacing between ubiquitin units.

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or posttranslational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to either the UBQLN2-binding surface of Ub or the spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model based on polyphasic linkage principles that accurately described the effects of different hubs on UBQLN2 phase separation, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. The extent to which polyubiquitin hubs promote UBQLN2 phase separation is encoded in the spacings between Ub units. This spacing is modulated by chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. The spacing in naturally occurring linear polyubiquitin chains is already optimized to promote phase separation with UBQLN2. We expect our findings to extend to other condensates, emphasizing the importance of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

Architectural basis for cylindrical self-assembly governing Plk4-mediated centriole duplication in human cells.

Proper organization of intracellular assemblies is fundamental for efficient promotion of biochemical processes and optimal assembly functionality. Although advances in imaging technologies have shed light on how the centrosome is organized, how its constituent proteins are coherently architected to elicit downstream events remains poorly understood. Using multidisciplinary approaches, we showed that two long coiled-coil proteins, Cep63 and Cep152, form a heterotetrameric building block that undergoes a stepwise formation into higher molecular weight complexes, ultimately generating a cylindrical architecture around a centriole. Mutants defective in Cep63•Cep152 heterotetramer formation displayed crippled pericentriolar Cep152 organization, polo-like kinase 4 (Plk4) relocalization to the procentriole assembly site, and Plk4-mediated centriole duplication. Given that the organization of pericentriolar materials (PCM) is evolutionarily conserved, this work could serve as a model for investigating the structure and function of PCM in other species, while offering a new direction in probing the organizational defects of PCM-related human diseases.

Distinct growth regimes of α-synuclein amyloid elongation.

Addition of amyloid seeds to aggregation-prone monomers allows for amyloid fiber growth (elongation) omitting slow nucleation. We here combine Thioflavin T fluorescence (probing formation of amyloids) and solution-state NMR spectroscopy (probing disappearance of monomers) to assess elongation kinetics of the amyloidogenic protein, α-synuclein, for which aggregation is linked to Parkinson's disease. We found that both spectroscopic detection methods give similar kinetic results, which can be fitted by applying double exponential decay functions. When the origin of the two-phase behavior was analyzed by mathematical modeling, parallel paths as well as stop-and-go behavior were excluded as possible explanations. Instead, supported by previous theory, the experimental elongation data reveal distinct kinetic regimes that depend on instantaneous monomer concentration. At low monomer concentrations (toward end of experiments), amyloid growth is limited by conformational changes resulting in ß-strand alignments. At the higher monomer concentrations (initial time points of experiments), growth occurs rapidly by incorporating monomers that have not successfully completed the conformational search. The presence of a fast disordered elongation regime at high monomer concentrations agrees with coarse-grained simulations and theory but has not been detected experimentally before. Our results may be related to the wide range of amyloid folds observed.

Circuit Topology Approach for the Comparative Analysis of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) lack a stable native conformation, making it challenging to characterize their structure and dynamics. Key topological motifs with fundamental biological relevance are often hidden in the conformational noise, eluding detection. Here, we develop a circuit topology toolbox to extract conformational patterns, critical contacts, and timescales from simulated dynamics of intrinsically disordered proteins. We follow the dynamics of IDPs by providing a smart low-dimensionality representation of their three-dimensional (3D) configuration in the topology space. Such an approach allows us to quantify topological similarity in dynamic systems, therefore providing a pipeline for structural comparison of IDPs.

Decoding optimal ligand design for multicomponent condensates.

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or post-translational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules for various cellular processes. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to the UBQLN2-binding surface of Ub or deviations from the optimal spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model that accurately described the effects of different hubs on UBQLN2 phase diagrams, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. Importantly, the extent to which polyubiquitin hubs can promote UBQLN2 phase separation are encoded in the spacings between Ub units as found for naturally-occurring chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. We expect our findings to extend to other condensates necessitating the consideration of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

Spatially non-uniform condensates emerge from dynamically arrested phase separation.

The formation of biomolecular condensates through phase separation from proteins and nucleic acids is emerging as a spatial organisational principle used broadly by living cells. Many such biomolecular condensates are not, however, homogeneous fluids, but possess an internal structure consisting of distinct sub-compartments with different compositions. Notably, condensates can contain compartments that are depleted in the biopolymers that make up the condensate. Here, we show that such double-emulsion condensates emerge via dynamically arrested phase transitions. The combination of a change in composition coupled with a slow response to this change can lead to the nucleation of biopolymer-poor droplets within the polymer-rich condensate phase. Our findings demonstrate that condensates with a complex internal architecture can arise from kinetic, rather than purely thermodynamic driving forces, and provide more generally an avenue to understand and control the internal structure of condensates in vitro and in vivo.

Beneficial and detrimental effects of non-specific binding during DNA hybridization.

DNA strands have to sample numerous states to find the alignment that maximizes Watson-Crick-Franklin base pairing. This process depends strongly on sequence, which affects the stability of the native duplex as well as the prevalence of non-native inter- and intramolecular helices. We present a theory that describes DNA hybridization as a three-stage process: diffusion, registry search, and zipping. We find that non-specific binding affects each of these stages in different ways. Mis-registered intermolecular binding in the registry search stage helps DNA strands sample different alignments and accelerates the hybridization rate. Non-native intramolecular structure affects all three stages by rendering portions of the molecule inert to intermolecular association, limiting mis-registered alignments to be sampled, and impeding the zipping process. Once in-register base pairs are formed, the stability of the native structure is important to hold the molecules together long enough for non-native contacts to break.

Conformational entropy limits the transition from nucleation to elongation in amyloid aggregation.

The formation of ß-sheet-rich amyloid fibrils in Alzheimer's disease and other neurodegenerative disorders is limited by a slow nucleation event. To understand the initial formation of ß-sheets from disordered peptides, we used all-atom simulations to parameterize a lattice model that treats each amino acid as a binary variable with ß- and non-ß-sheet states. We show that translational and conformational entropy give the nascent ß-sheet an anisotropic surface tension that can be used to describe the nucleus with 2D classical nucleation theory. Since translational entropy depends on concentration, the aspect ratio of the critical ß-sheet changes with protein concentration. Our model explains the transition from the nucleation phase to elongation as the point where the ß-sheet core becomes large enough to overcome the conformational entropy cost to straighten the terminal molecule. At this point the ß-strands in the nucleus spontaneously elongate, which results in a larger binding surface to capture new molecules. These results suggest that nucleation is relatively insensitive to sequence differences in coaggregation experiments because the nucleus only involves a small portion of the peptide.

Low-dissipation self-assembly protocols of active sticky particles.

We use neuroevolutionary learning to identify time-dependent protocols for low-dissipation self-assembly in a model of generic active particles with interactions. When the time allotted for assembly is sufficiently long, low-dissipation protocols use only interparticle attractions, producing an amount of entropy that scales as the number of particles. When time is too short to allow assembly to proceed via diffusive motion, low-dissipation assembly protocols instead require particle self-propulsion, producing an amount of entropy that scales with the number of particles and the swim length required to cause assembly. Self-propulsion therefore provides an expensive but necessary mechanism for inducing assembly when time is of the essence.

How Hierarchical Interactions Make Membraneless Organelles Tick Like Clockwork.

Biomolecular condensates appear throughout the cell, serving many different biochemical functions. We argue that condensate functionality is optimized when the interactions driving condensation vary widely in affinity. Strong interactions provide structural specificity needed to encode functional properties but carry the risk of kinetic arrest, while weak interactions allow the system to remain dynamic but do not restrict the conformational ensemble enough to sustain specific functional features. To support our opinion, we describe illustrative examples of the interplay of strong and weak interactions that are found in the nucleolus, SPOP/DAXX condensates, polySUMO/polySIM condensates, chromatin, and stress granules. The common feature of these systems is a hierarchical assembly motif in which weak, transient interactions condense structurally defined functional units.

Structure-Function Properties in Disordered Condensates.

Biomolecular condensates appear throughout the cell serving a wide variety of functions. Many condensates appear to form by the assembly of multivalent molecules, which produce phase-separated networks with liquidlike properties. These networks then recruit client molecules, with the total composition providing functionality. Here we use a model system of poly-SUMO and poly-SIM proteins to understand client-network interactions and find that the structure of the network plays a strong role in defining client recruitment and thus functionality. The basic unit of assembly in this system is a zipperlike filament composed of alternating poly-SUMO and poly-SIM molecules. These filaments have defects of unsatisfied bonds that allow for both the formation of a 3D network and the recruitment of clients. The filamentous structure constrains the scaffold stoichiometries and the distribution of client recruitment sites that the network can accommodate. This results in a nonmonotonic client binding response that can be tuned independently by the client valence and binding energy. These results show how the interactions within liquid states can be disordered yet still contain structural features that provide functionality to the condensate.

Thermodynamics of Huntingtin Aggregation.

Amyloid aggregates are found in many neurodegenerative diseases, including Huntington's, Alzheimer's, and prion diseases. The precise role of the aggregates in disease progression has been difficult to elucidate because of the diversity of aggregated states they can adopt. Here, we study the formation of fibrils and oligomers by exon 1 of huntingtin protein. We show that the oligomer states are consistent with polymer micelles that are limited in size by the stretching entropy of the polyglutamine region. The model shows how the sequences flanking the amyloid core modulate aggregation behavior. The N17 region promotes aggregation through weakly attractive interactions, whereas the C38 tail opposes aggregation via steric repulsion. We also show that the energetics of cross-ß stacking by polyglutamine would produce fibrils with many alignment defects, but minor perturbations from the flanking sequences are sufficient to reduce the defects to the level observed in experiment. We conclude with a discussion of the implications of this model for other amyloid-forming molecules.

Amyloid assembly is dominated by misregistered kinetic traps on an unbiased energy landscape.

Atomistic description of protein fibril formation has been elusive due to the complexity and long time scales of the conformational search. Here, we develop a multiscale approach combining numerous atomistic simulations in explicit solvent to construct Markov State Models (MSMs) of fibril growth. The search for the in-register fully bound fibril state is modeled as a random walk on a rugged two-dimensional energy landscape defined by ß-sheet alignment and hydrogen-bonding states, whereas transitions involving states without hydrogen bonds are derived from kinetic clustering. The reversible association/dissociation of an incoming peptide and overall growth kinetics are then computed from MSM simulations. This approach is applied to derive a parameter-free, comprehensive description of fibril elongation of Aß16-22 and how it is modulated by phenylalanine-to-cyclohexylalanine (CHA) mutations. The trajectories show an aggregation mechanism in which the peptide spends most of its time trapped in misregistered ß-sheet states connected by weakly bound states twith short lifetimes. Our results recapitulate the experimental observation that mutants CHA19 and CHA1920 accelerate fibril elongation but have a relatively minor effect on the critical concentration for fibril growth. Importantly, the kinetic consequences of mutations arise from cumulative effects of perturbing the network of productive and nonproductive pathways of fibril growth. This is consistent with the expectation that nonfunctional states will not have evolved efficient folding pathways and, therefore, will require a random search of configuration space. This study highlights the importance of describing the complete energy landscape when studying the elongation mechanism and kinetics of protein fibrils.

Protein Network Structure Enables Switching between Liquid and Gel States.

Biomolecular condensates are emerging as an important organizational principle within living cells. These condensed states are formed by phase separation, yet little is known about how material properties are encoded within the constituent molecules and how the specificity for being in different phases is established. Here we use analytic theory to explain the phase behavior of the cancer-related protein SPOP and its substrate DAXX. Binary mixtures of these molecules have a phase diagram that contains dilute liquid, dense liquid, and gel states. We show that these discrete phases appear due to a competition between SPOP-DAXX and DAXX-DAXX interactions. The stronger SPOP-DAXX interactions dominate at sub-stoichiometric DAXX concentrations leading to the formation of cross-linked gels. The theory shows that the driving force for gel formation is not the binding energy, but rather the entropy of distributing DAXX molecules on the binding sites. At high DAXX concentrations the SPOP-DAXX interactions saturate, which leads to the dissolution of the gel and the appearance of a liquid phase driven by weaker DAXX-DAXX interactions. This competition between interactions allows multiple dense phases to form in a narrow region of parameter space. We propose that the molecular architecture of phase-separating proteins governs the internal structure of dense phases, their material properties and their functions. Analytical theory can reveal these properties on the long length and time scales relevant to biomolecular condensates.

Catalystlike role of impurities in speeding layer-by-layer growth.

Molecular self-assembly is usually done at low supersaturation, leading to low rates of growth, in order to allow time for binding mistakes to anneal. However, such conditions can lead to prohibitively long assembly times where growth proceeds by the slow nucleation of successive layers. Here we use a lattice model of molecular self-assembly to show that growth in this regime can be sped up by impurities, which lower the free-energy cost of layer nucleation. Under certain conditions impurities behave almost as a catalyst in that they are present at high concentration at the surface of the assembling structure, but at low concentration in the bulk of the assembled structure. Extrapolation of our numerics using simple analytic arguments suggests that this mechanism can reduce growth times by orders of magnitude in parameter regimes applicable to molecular systems.

Effects of non-pairwise repulsion on nanoparticle assembly.

Electrostatic interactions provide a convenient way to modulate interactions between nanoparticles, colloids, and biomolecules because they can be adjusted by the solution pH or salt concentration. While the presence of salt provides an easy method to control the net interparticle interaction, the nonlinearities arising from electrostatic screening make it difficult to quantify the strength of the interaction. In particular, when charged particles assemble into clusters or aggregates, nonlinear effects render the interactions strongly non-pairwise. Here, we report Brownian dynamics simulations to investigate the effect that the non-pairwise nature of electrostatic interactions has on nanoparticle assembly. We compare these simulations to a system in which the electrostatics are modeled by a strictly pairwise Yukawa potential. We find that both systems show a narrow range in parameter space where the particles form well-ordered crystals. Bordering this range are regions where the net interactions are too weak to stabilize aggregated structures or strong enough that the system becomes kinetically trapped in a gel. The non-pairwise potential differs from the pairwise system in the appearance of an amorphous state for strongly charged particles. This state appears because the many-body electrostatic interactions limit the maximum density achievable in an assembly.