Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains

Prion-like low-complexity domains (PLCDs) have distinctive sequence grammars that determine their driving forces for phase separation. Here we uncover the physicochemical underpinnings of how evolutionarily conserved compositional biases influence the phase behaviour of PLCDs. We interpret our results in the context of the stickers-and-spacers model for the phase separation of associative polymers. We find that tyrosine is a stronger sticker than phenylalanine, whereas arginine is a context-dependent auxiliary sticker. In contrast, lysine weakens sticker-sticker interactions. Increasing the net charge per residue destabilizes phase separation while also weakening the strong coupling between single-chain contraction in dilute phases and multichain interactions that give rise to phase separation. Finally, glycine and serine residues act as non-equivalent spacers, and thus make the glycine versus serine contents an important determinant of the driving forces for phase separation. The totality of our results leads to a set of rules that enable comparative estimates of composition-specific driving forces for PLCD phase separation.

Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains

Prion-like low-complexity domains (PLCDs) have distinctive sequence grammars that determine their driving forces for phase separation. Here we uncover the physicochemical underpinnings of how evolutionarily conserved compositional biases influence the phase behaviour of PLCDs. We interpret our results in the context of the stickers-and-spacers model for the phase separation of associative polymers. We find that tyrosine is a stronger sticker than phenylalanine, whereas arginine is a context-dependent auxiliary sticker. In contrast, lysine weakens sticker-sticker interactions. Increasing the net charge per residue destabilizes phase separation while also weakening the strong coupling between single-chain contraction in dilute phases and multichain interactions that give rise to phase separation. Finally, glycine and serine residues act as non-equivalent spacers, and thus make the glycine versus serine contents an important determinant of the driving forces for phase separation. The totality of our results leads to a set of rules that enable comparative estimates of composition-specific driving forces for PLCD phase separation.

A multi-step nucleation process determines the kinetics of prion-like domain phase separation

Compartmentalization by liquid-liquid phase separation (LLPS) has emerged as a ubiquitous mechanism underlying the organization of biomolecules in space and time. Here, we combine rapid-mixing time-resolved small-angle X-ray scattering (SAXS) approaches to characterize the assembly kinetics of a prototypical prion-like domain with equilibrium techniques that characterize its phase boundaries and the size distribution of clusters prior to phase separation. We find two kinetic regimes on the micro- to millisecond timescale that are distinguished by the size distribution of clusters. At the nanoscale, small complexes are formed with low affinity. After initial unfavorable complex assembly, additional monomers are added with higher affinity. At the mesoscale, assembly resembles classical homogeneous nucleation. Careful multi-pronged characterization is required for the understanding of condensate assembly mechanisms and will promote understanding of how the kinetics of biological phase separation is encoded in biomolecules.

Oncogenic signaling of RTK fusions becomes more granular

A spectrum of cancers arises from chromosomal translocations that fuse receptor tyrosine kinase domains to oligomerization domains from unrelated proteins. Tulpule et al. (2021) demonstrate that fusion proteins with the ability to assemble higher-order cytoplasmic protein granules can activate RAS signaling in a lipid membrane-independent manner.

The role of liquid-liquid phase separation in regulating enzyme activity

Liquid-liquid phase separation (LLPS) is now recognized as a common mechanism underlying regulation of enzyme activity in cells. Insights from studies in cells are complemented by in vitro studies aimed at developing a better understanding of mechanisms underlying such control. These mechanisms are often based on the influence of LLPS on the physicochemical properties of the enzyme's environment. Biochemical mechanisms underlying such regulation include the potential for concentrating reactants together, tuning reaction rates, and controlling competing metabolic pathways. LLPS is thus a powerful tool with extensive utilities at the cell's disposal, e.g. for consolidating cell survival under stress or rerouting metabolic pathways in response to the energy state of the cell. Here, we examin the evidence for how LLPS affects enzyme catalysis and begin to understand emerging concepts and expand our understanding of enzyme catalysis in living cells.

Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

Liquid-liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (i) electrostatically-mediated interactions that compact hnRNPA1 and contribute to phase separation and (ii) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

G3BP1 Is a Tunable Switch that Triggers Phase Separation to Assemble Stress Granules

The mechanisms underlying ribonucleoprotein (RNP) granule assembly, including the basis for establishing and maintaining RNP granules with distinct composition, are unknown. One prominent type of RNP granule is the stress granule (SG), a dynamic and reversible cytoplasmic assembly formed in eukaryotic cells in response to stress. Here, we show that SGs assemble through liquid-liquid phase separation (LLPS) arising from interactions distributed unevenly across a core protein-RNA interaction network. The central node of this network is G3BP1, which functions as a molecular switch that triggers RNA-dependent LLPS in response to a rise in intracellular free RNA concentrations. Moreover, we show that interplay between three distinct intrinsically disordered regions (IDRs) in G3BP1 regulates its intrinsic propensity for LLPS, and this is fine-tuned by phosphorylation within the IDRs. Further regulation of SG assembly arises through positive or negative cooperativity by extrinsic G3BP1-binding factors that strengthen or weaken, respectively, the core SG network.

Microfluidic characterization of macromolecular liquid-liquid phase separation

Liquid-liquid phase separation plays important roles in the compartmentalization of cells. Developing an understanding of how phase separation is encoded in biomacromolecules requires quantitative mapping of their phase behavior. Given that such experiments require large quantities of the biomolecule of interest, these efforts have been lagging behind the recent breadth of biological insights. Herein, we present a microfluidic phase chip that enables the measurement of saturation concentrations over at least three orders of magnitude for a broad spectrum of biomolecules and solution conditions. The phase chip consists of five units, each made of twenty individual sample chambers to allow the measurement of five sample conditions simultaneously. The analytes are slowly concentrated via evaporation of water, which is replaced by oil, until the sample undergoes phase separation into a dilute and dense phase. We show that the phase chip lowers the required sample quantity by 98% while offering six-fold better statistics in comparison to standard manual experiments that involve centrifugal separation of dilute and dense phases. We further show that the saturation concentrations measured in chips are in agreement with previously reported data for a variety of biomolecules. Concomitantly, time-dependent changes of the dense phase morphology and potential off-pathway processes, including aggregation, can be monitored microscopically. In summary, the phase chip is suited to exploring sequence-to-binodal relationships by enabling the determination of a large number of saturation concentrations at low protein cost.

How do intrinsically disordered protein regions encode a driving force for liquid-liquid phase separation?

Liquid-liquid phase separation is the mechanism underlying the formation of biomolecular condensates. Disordered protein regions often drive phase separation, but the molecular interactions mediating this phenomenon are not well understood, sometimes leading to the conflation that all disordered protein regions drive phase separation. Given the critical role of phase separation in many cellular processes, and that dysfunction of phase separation can lead to debilitating diseases, it is important that we understand the interactions and sequence properties underlying phase behavior. A conceptual framework that divides IDRs into interacting and solvating regions has proven particularly useful, and analytical instantiations and coarse-grained models can test our understanding of the driving forces against experimental phase behavior. Validated simulation paradigms enable the exploration of sequence space to help our understanding of how disordered protein regions can encode phase behavior, which IDRs may mediate phase separation in cells, and which IDRs are highly soluble.

Conformational Ensembles of an Intrinsically Disordered Protein Consistent with NMR, SAXS, and Single-Molecule FRET

Intrinsically disordered proteins (IDPs) have fluctuating heterogeneous conformations, which makes their structural characterization challenging. Although challenging, characterization of the conformational ensembles of IDPs is of great interest, since their conformational ensembles are the link between their sequences and functions. An accurate description of IDP conformational ensembles depends crucially on the amount and quality of the experimental data, how it is integrated, and if it supports a consistent structural picture. We used integrative modeling and validation to apply conformational restraints and assess agreement with the most common structural techniques for IDPs: Nuclear Magnetic Resonance (NMR) spectroscopy, Small-angle X-ray Scattering (SAXS), and single-molecule Förster Resonance Energy Transfer (smFRET). Agreement with such a diverse set of experimental data suggests that details of the generated ensembles can now be examined with a high degree of confidence. Using the disordered N-terminal region of the Sic1 protein as a test case, we examined relationships between average global polymeric descriptions and higher-moments of their distributions. To resolve apparent discrepancies between smFRET and SAXS inferences, we integrated SAXS data with NMR data and reserved the smFRET data for independent validation. Consistency with smFRET, which was not guaranteed a priori, indicates that, globally, the perturbative effects of NMR or smFRET labels on the Sic1 ensemble are minimal. Analysis of the ensembles revealed distinguishing features of Sic1, such as overall compactness and large end-to-end distance fluctuations, which are consistent with biophysical models of Sic1's ultrasensitive binding to its partner Cdc4. Our results underscore the importance of integrative modeling and validation in generating and drawing conclusions from IDP conformational ensembles.

Small-angle X-ray scattering experiments of monodisperse intrinsically disordered protein samples close to the solubility limit

The condensation of biomolecules into biomolecular condensates via liquid-liquid phase separation (LLPS) is a ubiquitous mechanism that drives cellular organization. To enable these functions, biomolecules have evolved to drive LLPS and facilitate partitioning into biomolecular condensates. Determining the molecular features of proteins that encode LLPS will provide critical insights into a plethora of biological processes. Problematically, probing biomolecular dense phases directly is often technologically difficult or impossible. By capitalizing on the symmetry between the conformational behavior of biomolecules in dilute solution and dense phases, it is possible to infer details critical to phase separation by precise measurements of the dilute phase thus circumventing complicated characterization of dense phases. The symmetry between dilute and dense phases is found in the size and shape of the conformational ensemble of a biomolecule-parameters that small-angle X-ray scattering (SAXS) is ideally suited to probe. Recent technological advances have made it possible to accurately characterize samples of intrinsically disordered protein regions at low enough concentration to avoid interference from intermolecular attraction, oligomerization or aggregation, all of which were previously roadblocks to characterizing self-assembling proteins. Herein, we describe the pitfalls inherent to measuring such samples, the experimental details required for circumventing these issues and analysis methods that place the results of SAXS measurements into the theoretical framework of LLPS.

Connecting Coil-to-Globule Transitions to Full Phase Diagrams for Intrinsically Disordered Proteins

Phase separation is thought to underlie spatial and temporal organization that is required for controlling biochemical reactions in cells. Multivalence of interaction motifs, also known as stickers, is a defining feature of proteins that drive phase separation. Intrinsically disordered proteins with stickers uniformly distributed along the linear sequence can serve as scaffold molecules that drive phase separation. The sequence-intrinsic contributions of disordered proteins to phase separation can be discerned by computing or measuring sequence-specific phase diagrams. These help to delineate the combinations of protein concentration and a suitable control parameter, such as temperature, that support phase separation. Here, we present an approach that combines detailed simulations with a numerical adaptation of an analytical Gaussian cluster theory to enable the calculation of sequence-specific phase diagrams. Our approach leverages the known equivalence between the driving forces for single-chain collapse in dilute solutions and the driving forces for phase separation in concentrated solutions. We demonstrate the application of the theory-aided computations through calculation of phase diagrams for a set of archetypal intrinsically disordered low-complexity domains. We also leverage theories to compute sequence-specific percolation lines and thereby provide a thermodynamic framework for hardening transitions that have been observed for many biomolecular condensates.

Valence and patterning of aromatic residues determine the phase behavior of prion-like domains

Prion-like domains (PLDs) can drive liquid-liquid phase separation (LLPS) in cells. Using an integrative biophysical approach that includes nuclear magnetic resonance spectroscopy, small-angle x-ray scattering, and multiscale simulations, we have uncovered sequence features that determine the overall phase behavior of PLDs. We show that the numbers (valence) of aromatic residues in PLDs determine the extent of temperature-dependent compaction of individual molecules in dilute solutions. The valence of aromatic residues also determines full binodals that quantify concentrations of PLDs within coexisting dilute and dense phases as a function of temperature. We also show that uniform patterning of aromatic residues is a sequence feature that promotes LLPS while inhibiting aggregation. Our findings lead to the development of a numerical stickers-and-spacers model that enables predictions of full binodals of PLDs from their sequences.