Biomolecular condensates form via macromolecular phase separation. Here, we report results from our characterization of synthetic condensates formed by phase separation of mixtures comprising two types of RNA molecules and the biocompatible polymer polyethylene glycol. Purine-rich RNAs are scaffolds that drive phase separation via heterotypic interactions. Conversely, pyrimidine-rich RNA molecules are adsorbents defined by weaker heterotypic interactions. They adsorb onto and wet the interfaces of coexisting phases formed by scaffolds. Lattice-based simulations reproduce the phenomenology observed in experiments and these simulations predict that scaffolds and adsorbents have different non-random orientational preferences at interfaces. Dynamics at interfaces were probed using single-molecule tracking of fluorogenic probes bound to RNA molecules. These experiments revealed dynamical anisotropy at interfaces whereby motions of probe molecules parallel to the interface are faster than motions perpendicular to the interface. Taken together, our findings have broad implications for designing synthetic condensates with tunable interfacial properties.

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. Biomolecular condensates form via phase separation of multivalent macromolecules. Phase separation is governed by solubility whereas multivalence drives percolation, also known as gelation. The authors in this work identify the distinct energy and length scales that influence phase separation versus percolation.

Macromolecular solubility is an important contributor to the driving forces for phase separation. Formally, the driving forces in a binary mixture comprising a macromolecule dissolved in a solvent can be quantified in terms of the saturation concentration, which is the threshold macromolecular concentration above which the mixture separates into coexisting dense and dilute phases. Additionally, the second virial coefficient, which measures the effective strength of solvent-mediated intermolecular interactions provides direct assessments of solvent quality. The sign and magnitude of second virial coefficients will be governed by a combination of solution conditions and the nature of the macromolecule of interest. Here, we show, using a combination of theory, simulation, and in vitro experiments, that titrations of crowders, providing they are true depletants, can be used to extract the intrinsic driving forces for macromolecular phase separation. This refers to saturation concentrations in the absence of crowders and the second virial coefficients that quantify the magnitude of the incompatibility between macromolecules and the solvent. Our results show how the depletion-mediated attractions afforded by crowders can be leveraged to obtain comparative assessments of macromolecule-specific, intrinsic driving forces for phase separation.SIGNIFICANCE:Phase separation has emerged as a process of significant relevance to sorting macromolecules into distinct compartments, thereby enabling spatial and temporal control over cellular matter. Considerable effort is being invested into uncovering the driving forces that enable the separation of macromolecular solutions into coexisting phases. At its heart, this process is governed by the balance of macromolecule-solvent, inter-macromolecule, and solvent-solvent interactions. We show that the driving forces for phase separation, including the coefficients that measure interaction strengths between macromolecules, can be extracted by titrating the concentrations of crowders that enable macromolecules to phase separate at lower concentrations. Our work paves the way to leverage specific categories of measurements for quantitative characterizations of driving forces for phase separation.

In vitro experiments often use synthetic crowders such as polyethylene glycol (PEG) to induce macromolecular phase separation. However, many questions remain unanswered regarding the effects of crowders. How do crowders influence phase separation? What information can one extract from titrations of crowder concentrations? Do systems featuring differences in sequence-specific driving forces for phase separation respond differently to crowders? And how are the compositions and physical properties of coexisting phases impacted by crowders? To answer these questions, we performed simulations using the LaSSI engine and uncovered rules for how crowders impact overall phase behaviors of associative macromolecules with sticker-and-spacer architectures.

Multivalent proteins undergo coupled segregative and associative phase transitions. Phase separation, a segregative transition, is driven by macromolecular solubility, and this leads to coexisting phases above system-specific saturation concentrations. Percolation is a continuous transition that is driven by multivalent associations among cohesive motifs. Contributions from percolation are highlighted by the formation of heterogeneous distributions of clusters in sub-saturated solutions, as was recently reported for Fused in sarcoma (FUS) and FET family proteins. Here, we show that clustering and phase separation are defined by a separation of length- and energy-scales. This is unmasked when glutamate is the primary solution anion. Glutamate is preferentially excluded from protein sites, and this enhances molecular associations. Differences between glutamate and chloride are manifest at ultra-low protein concentrations. These differences are amplified as concentrations increase, and they saturate as the micron-scale is approached. Therefore, condensate formation in supersaturated solutions and clustering in sub-saturated are governed by distinct energy and length scales. Glutamate, unlike chloride, is the dominant intracellular anion, and the separation of scales, which is masked in chloride, is unmasked in glutamate. Our work highlights how components of cellular milieus and sequence-encoded interactions contribute to amplifying distinct contributions from associative versus segregative phase transitions.

Cell-free protein synthesis is an important tool for studying gene expression and harnessing it for applications. In cells, gene expression is regulated in part by the spatial organization of transcription and translation. Unfortunately, current cell-free approaches are unable to control the organization of molecular components needed for gene expression, which limits the ability to probe and utilize its effects. Here, we show, using complementary computational and experimental approaches, that macromolecular crowding can be used to control the spatial organization and translational efficiency of gene expression in cell-sized vesicles. Computer simulations and imaging experiments reveal that, as crowding is increased, DNA plasmids become localized at the inner surface of vesicles. Ribosomes, in contrast, remain uniformly distributed, demonstrating that crowding can be used to differentially organize components of gene expression. We further carried out cell-free protein synthesis reactions in cell-sized vesicles and quantified mRNA and protein abundance. At sufficiently high levels of crowding, we observed localization of mRNA near vesicle surfaces, a decrease in translational efficiency and protein abundance, and anomalous scaling of protein abundance as a function of vesicle size. These results are consistent with high levels of crowding causing altered spatial organization and slower diffusion. Our work demonstrates a straightforward way to control the organization of gene expression in cell-sized vesicles and provides insight into the spatial regulation of gene expression in cells.

Macromolecular crowding is a feature of cellular and cell-free systems that, through depletion effects, can impact the interactions of semiflexible biopolymers with surfaces. In this work, we use computer simulations to study crowding-induced adsorption of semiflexible polymers on otherwise repulsive surfaces. Crowding particles are modeled explicitly, and we investigate the interplay between the bending stiffness of the polymer and the volume fraction and size of crowding particles. Adsorption to flat surfaces is promoted by stiffer polymers, smaller crowding particles, and larger volume fractions of crowders. We characterize transitions from non-adsorbed to partially and strongly adsorbed states as a function of bending stiffness. The crowding-induced transitions occur at smaller values of the bending stiffness as the volume fraction of crowders increases. Concomitant effects on the size and shape of the polymer are reflected by crowding- and stiffness-dependent changes to the radius of gyration. For various polymer lengths, we identify a critical crowding fraction for adsorption and analyze its scaling behavior in terms of polymer stiffness. We also consider crowding-induced adsorption in spherical confinement and identify a regime in which increasing the bending stiffness induces desorption. The results of our simulations shed light on the interplay of crowding and bending stiffness on the spatial organization of biopolymers in encapsulated cellular and cell-free systems.

Macromolecular crowding and the presence of surfaces can significantly impact the spatial organization of biopolymers. While the importance of crowding-induced depletion interactions in biology has been recognized, much remains to be understood about the effect of crowding on biopolymers such as DNA plasmids. A fundamental problem highlighted by recent experiments is to characterize the impact of crowding on polymer-polymer and polymer-surface interactions. Motivated by the need for quantitative insight, we studied flexible ring polymers in crowded environments using Langevin dynamics simulations. The simulations demonstrated that crowding can lead to compaction of isolated ring polymers and enhanced interactions between two otherwise repulsive polymers. Using umbrella sampling, we determined the potential of mean force (PMF) between two ring polymers as a function of their separation distance at different volume fractions of crowding particles, φ. An effective attraction emerged at φ ≈ 0.4, which is similar to the degree of crowding in cells. Analogous simulations showed that crowding can lead to strong adsorption of a ring polymer to a wall, with an effective attraction to the wall emerging at a smaller volume fraction of crowders (φ ≈ 0.2). Our results reveal the magnitude of depletion interactions in a biologically-inspired model and highlight how crowding can be used to tune interactions in both cellular and cell-free systems.

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting-the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increase in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA ("spatial noise") that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. These results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.

Synergistic interactions between macromolecular crowding and confinement spatially organize transcription and translation in cells. Yet, reproducing such spatial ordering in cell-free expression platforms has proven to be elusive. Here we report crowding- and confinement-driven spatial self-organization of cell-free expression that mimics expression behavior within and around the nucleoid of prokaryotes. These experiments use Ficoll-70 to approximate cellular macromolecular crowding conditions within cell-size lipid vesicles. Intriguingly, there was an abrupt change in transcriptional dynamics when crowding reached physiologically relevant levels. Imaging experiments revealed that this change in transcriptional dynamics was coincident with localization of plasmid DNA and mRNA at the vesicle wall. Computer simulations demonstrated that crowding leads to an entropically induced attraction between plasmid DNA and the wall, causing localization of DNA near the wall at sufficiently high crowding levels. The experiments demonstrate cell-like spatial organization of translation, where translational activity is controlled by chromosomally-templated positioning of mRNA. This cell-free system provides a flexible experimental platform to probe the underlying mechanisms of self-organization of membrane-less structures in cells and the spatial control of gene expression.

Cell-free gene expression using purified components or cell extracts has become an important platform for synthetic biology that is finding a growing numBer of practical applications. Unfortunately, at cell-relevant reactor volumes, cell-free expression suffers from excessive variability (noise) such that protein concentrations may vary by more than an order of magnitude across a population of identically constructed reaction chambers. Consensus opinion holds that variability in expression is due to the stochastic distribution of expression resources (DNA, RNAP, ribosomes, etc.) across the population of reaction chambers. In contrast, here we find that chamber-to-chamber variation in the expression efficiency generates the large variability in protein production. Through analysis and modeling, we show that chambers self-organize into expression centers that control expression efficiency. Chambers that organize into many centers, each having relatively few expression resources, exhibit high expression efficiency. Conversely, chambers that organize into just a few centers where each center has an abundance of resources, exhibit low expression efficiency. A particularly surprising finding is that diluting expression resources reduces the chamber-to-chamber variation in protein production. Chambers with dilute pools of expression resources exhibit higher expression efficiency and lower expression noise than those with more concentrated expression resources. In addition to demonstrating the means to tune expression noise, these results demonstrate that in cell-free systems, self-organization may exert even more influence over expression than the abundance of the molecular components of transcription and translation. These observations in cell-free platform may elucidate how self-organized, membrane-less structures emerge and function in cells.