What are the distinguishing features and size requirements of biomolecular condensates and their implications for RNA-containing condensates?

Exciting recent work has highlighted that numerous cellular compartments lack encapsulating lipid bilayers (often called "membraneless organelles"), and that their structure and function are central to the regulation of key biological processes, including transcription, RNA splicing, translation, and more. These structures have been described as "biomolecular condensates" to underscore that biomolecules can be significantly concentrated in them. Many condensates, including RNA granules and processing bodies, are enriched in proteins and nucleic acids. Biomolecular condensates exhibit a range of material states from liquid- to gel-like, with the physical process of liquid-liquid phase separation implicated in driving or contributing to their formation. To date, in vitro studies of phase separation have provided mechanistic insights into the formation and function of condensates. However, the link between the often micron-sized in vitro condensates with nanometer-sized cellular correlates has not been well established. Consequently, questions have arisen as to whether cellular structures below the optical resolution limit can be considered biomolecular condensates. Similarly, the distinction between condensates and discrete dynamic hub complexes is debated. Here we discuss the key features that define biomolecular condensates to help understand behaviors of structures containing and generating RNA.

Allosteric Modulation of Grb2 Recruitment to the Intrinsically Disordered Scaffold Protein, LAT, by Remote Site Phosphorylation.

Tyrosine phosphorylation of membrane receptors and scaffold proteins followed by recruitment of SH2 domain-containing adaptor proteins constitutes a central mechanism of intracellular signal transduction. During early T-cell receptor (TCR) activation, phosphorylation of linker for activation of T cells (LAT) leading to recruitment of adaptor proteins, including Grb2, is one prototypical example. LAT contains multiple modifiable sites, and this multivalency may provide additional layers of regulation, although this is not well understood. Here, we quantitatively analyze the effects of multivalent phosphorylation of LAT by reconstituting the initial reactions of the TCR signaling pathway on supported membranes. Results from a series of LAT constructs with combinatorial mutations of tyrosine residues reveal a previously unidentified allosteric mechanism in which the binding affinity of LAT:Grb2 depends on the phosphorylation at remote tyrosine sites. Additionally, we find that LAT:Grb2 binding affinity is altered by membrane localization. This allostery mainly regulates the kinetic on-rate, not off-rate, of LAT:Grb2 interactions. LAT is an intrinsically disordered protein, and these data suggest that phosphorylation changes the overall ensemble of configurations to modulate the accessibility of other phosphorylated sites to Grb2. Using Grb2 as a phosphorylation reporter, we further monitored LAT phosphorylation by TCR ζ chain-recruited ZAP-70, which suggests a weakly processive catalysis on membranes. Taken together, these results suggest that signal transmission through LAT is strongly gated and requires multiple phosphorylation events before efficient signal transmission is achieved.

Measurement of solubility product reveals the interplay of oligomerization and self-association for defining condensate formation.

Cellular condensates often consist of 10s to 100s of distinct interacting molecular species. Because of the complexity of these interactions, predicting the point at which they will undergo phase separation is daunting. Using experiments and computation, we therefore studied a simple model system consisting of polySH3 and polyPRM designed for pentavalent heterotypic binding. We tested whether the peak solubility product, or the product of the dilute phase concentration of each component, is a predictive parameter for the onset of phase separation. Titrating up equal total concentrations of each component showed that the maximum solubility product does approximately coincide with the threshold for phase separation in both experiments and models. However, we found that measurements of dilute phase concentration include small oligomers and monomers; therefore, a quantitative comparison of the experiments and models required inclusion of small oligomers in the model analysis. Even with the inclusion of small polyPRM and polySH3 oligomers, models did not predict experimental results. This led us to perform dynamic light scattering experiments, which revealed homotypic binding of polyPRM. Addition of this interaction to our model recapitulated the experimentally observed asymmetry. Thus, comparing experiments to simulation reveals that the solubility product can be predictive of the interactions underlying phase separation, even if small oligomers and low affinity homotypic interactions complicate the analysis.

Measurement of solubility product in a model condensate reveals the interplay of small oligomerization and self-association.

Cellular condensates often consist of 10s to 100s of distinct interacting molecular species. Because of the complexity of these interactions, predicting the point at which they will undergo phase separation into discrete compartments is daunting. Using experiments and computation, we therefore studied a simple model system consisting of 2 proteins, polySH3 and polyPRM, designed for pentavalent heterotypic binding. We tested whether the peak solubility product, the product of dilute phase monomer concentrations, is a predictive parameter for the onset of phase separation. Titrating up equal total concentrations of each component showed that the maximum solubility product does approximately coincide with the threshold for phase separation in both the experiments and models. However, we found that measurements of dilute phase concentration include contributions from small oligomers, not just monomers; therefore, a quantitative comparison of the experiments and models required inclusion of small oligomers in the model analysis. We also examined full phase diagrams where the model results were almost symmetric along the diagonal, but the experimental results were highly asymmetric. This led us to perform dynamic light scattering experiments, where we discovered a weak homotypic interaction for polyPRM; when this was added to the computational model, it was able to recapitulate the experimentally observed asymmetry. Thus, comparing experiments to simulation reveals that the solubility product can be predictive of phase separation, even if small oligomers and low affinity homotypic interactions preclude experimental measurement of monomer concentration.

There is more than one way to model an elephant. Experiment-driven modeling of the actin cytoskeleton.

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton.

Coupling of protein condensates to ordered lipid domains determines functional membrane organization.

During T cell activation, the transmembrane adaptor protein LAT (linker for activation of T cells) forms biomolecular condensates with Grb2 and Sos1, facilitating signaling. LAT has also been associated with cholesterol-rich condensed lipid domains; However, the potential coupling between protein condensation and lipid phase separation and its role in organizing T cell signaling were unknown. Here, we report that LAT/Grb2/Sos1 condensates reconstituted on model membranes can induce and template lipid domains, indicating strong coupling between lipid- and protein-based phase separation. Correspondingly, activation of T cells induces cytoplasmic protein condensates that associate with and stabilize raft-like membrane domains. Inversely, lipid domains nucleate and stabilize LAT protein condensates in both reconstituted and living systems. This coupling of lipid and protein assembly is functionally important, as uncoupling of lipid domains from cytoplasmic protein condensates abrogates T cell activation. Thus, thermodynamic coupling between protein condensates and ordered lipid domains regulates the functional organization of living membranes.

Biomolecular condensates in membrane receptor signaling.

Clustering is a prominent feature of receptors at the plasma membrane (PM). It plays an important role in signaling. Liquid-liquid phase separation (LLPS) of proteins is emerging as a novel mechanism underlying the observed clustering. Receptors/transmembrane signaling proteins can be core components essential for LLPS (such as LAT or nephrin) or clients enriched at the phase-separated condensates (for example, at the postsynaptic density or at tight junctions). Condensate formation has been shown to regulate signaling in multiple ways, including by increasing protein binding avidity and by modulating the local biochemical environment. In moving forward, it is important to study protein LLPS at the PM of living cells, its interplay with other factors underlying receptor clustering, and its signaling and functional consequences.

The role of sigma 1 receptor in organization of endoplasmic reticulum signaling microdomains.

Sigma 1 receptor (S1R) is a 223-amino-acid-long transmembrane endoplasmic reticulum (ER) protein. S1R modulates activity of multiple effector proteins and is a well-established drug target. However, signaling functions of S1R in cells are poorly understood. Here, we test the hypothesis that biological activity of S1R in cells can be explained by its ability to interact with cholesterol and to form cholesterol-enriched microdomains in the ER membrane. By performing experiments in reduced reconstitution systems, we demonstrate direct effects of cholesterol on S1R clustering. We identify a novel cholesterol-binding motif in the transmembrane region of human S1R. Mutations of this motif impair association of recombinant S1R with cholesterol beads, affect S1R clustering in vitro and disrupt S1R subcellular localization. We demonstrate that S1R-induced membrane microdomains have increased local membrane thickness and that increased local cholesterol concentration and/or membrane thickness in these microdomains can modulate signaling of inositol-requiring enzyme 1α in the ER. Further, S1R agonists cause disruption of S1R clusters, suggesting that biological activity of S1R agonists is linked to remodeling of ER membrane microdomains. Our results provide novel insights into S1R-mediated signaling mechanisms in cells.

Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma.

BACKGROUND: Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, oncocytoma is usually regarded as a benign entity. The overlapping characteristics are best explained by a common cellular origin, and the biologic differences between chRCC and oncocytoma are therefore of considerable interest in terms of carcinogenesis, diagnosis and clinical management. Previous studies have been relatively limited in terms of examining the differences between oncocytoma and chromophobe RCC. METHODS: Gene expression profiling using the Affymetrix HGU133Plus2 platform was applied on chRCC (n = 15) and oncocytoma specimens (n = 15). Supervised analysis was applied to identify a discriminatory gene signature, as well as differentially expressed genes. High throughput single-nucleotide polymorphism (SNP) genotyping was performed on independent samples (n = 14) using Affymetrix GeneChip Mapping 100 K arrays to assess correlation between expression and gene copy number. Immunohistochemical validation was performed in an independent set of tumors. RESULTS: A novel 14 probe-set signature was developed to classify the tumors internally with 93% accuracy, and this was successfully validated on an external data-set with 94% accuracy. Pathway analysis highlighted clinically relevant dysregulated pathways of c-erbB2 and mammalian target of rapamycin (mTOR) signaling in chRCC, but no significant differences in p-AKT or extracellular HER2 expression was identified on immunohistochemistry. Loss of chromosome 1p, reflected in both cytogenetic and expression analysis, is common to both entities, implying this may be an early event in histogenesis. Multiple regional areas of cytogenetic alterations and corresponding expression biases differentiating the two entities were identified. Parafibromin, aquaporin 6, and synaptogyrin 3 were novel immunohistochemical markers effectively discriminating the two pathologic entities. CONCLUSIONS: Gene expression profiles, high-throughput SNP genotyping, and pathway analysis effectively distinguish chRCC from oncocytoma. We have generated a novel transcript predictor that is able to discriminate between the two entities accurately, and which has been validated both in an internal and an independent data-set, implying generalizability. A cytogenetic alteration, loss of chromosome 1p, common to renal oncocytoma and chRCC has been identified, providing the opportunities for identifying novel tumor suppressor genes and we have identified a series of immunohistochemical markers that are clinically useful in discriminating chRCC and oncocytoma.

Dynamin regulates the dynamics and mechanical strength of the actin cytoskeleton as a multifilament actin-bundling protein.

The dynamin GTPase is known to bundle actin filaments, but the underlying molecular mechanism and physiological relevance remain unclear. Our genetic analyses revealed a function of dynamin in propelling invasive membrane protrusions during myoblast fusion in vivo. Using biochemistry, total internal reflection fluorescence microscopy, electron microscopy and cryo-electron tomography, we show that dynamin bundles actin while forming a helical structure. At its full capacity, each dynamin helix captures 12-16 actin filaments on the outer rim of the helix. GTP hydrolysis by dynamin triggers disassembly of fully assembled dynamin helices, releasing free dynamin dimers/tetramers and facilitating Arp2/3-mediated branched actin polymerization. The assembly/disassembly cycles of dynamin promote continuous actin bundling to generate mechanically stiff actin super-bundles. Super-resolution and immunogold platinum replica electron microscopy revealed dynamin along actin bundles at the fusogenic synapse. These findings implicate dynamin as a unique multifilament actin-bundling protein that regulates the dynamics and mechanical strength of the actin cytoskeletal network.

An open model of actin dendritic nucleation.

The availability of quantitative experimental data on the kinetics of actin assembly has enabled the construction of many mathematical models focused on explaining specific behaviors of this complex system. However these ad hoc models are generally not reusable or accessible by the large community of actin biologists. In this work, we present a comprehensive model that integrates and unifies much of the in vitro data on the components of the dendritic nucleation mechanism for actin dynamics. More than 300 simulations have been run based on compartmental and three-dimensional spatial versions of this model. Several key findings are highlighted, including an explanation for the sharp boundary between actin assembly and disassembly in the lamellipodia of migrating cells. Because this model, with the simulation results, is "open source", in the sense that it is publicly available and editable through the Virtual Cell database (http://vcell.org), it can be accessed, analyzed, modified, and extended.

Regulation of Transmembrane Signaling by Phase Separation.

Cell surface transmembrane receptors often form nanometer- to micrometer-scale clusters to initiate signal transduction in response to environmental cues. Extracellular ligand oligomerization, domain-domain interactions, and binding to multivalent proteins all contribute to cluster formation. Here we review the current understanding of mechanisms driving cluster formation in a series of representative receptor systems: glycosylated receptors, immune receptors, cell adhesion receptors, Wnt receptors, and receptor tyrosine kinases. We suggest that these clusters share properties of systems that undergo liquid-liquid phase separation and could be investigated in this light.

Stoichiometry controls activity of phase-separated clusters of actin signaling proteins.

Biomolecular condensates concentrate macromolecules into foci without a surrounding membrane. Many condensates appear to form through multivalent interactions that drive liquid-liquid phase separation (LLPS). LLPS increases the specific activity of actin regulatory proteins toward actin assembly by the Arp2/3 complex. We show that this increase occurs because LLPS of the Nephrin-Nck-N-WASP signaling pathway on lipid bilayers increases membrane dwell time of N-WASP and Arp2/3 complex, consequently increasing actin assembly. Dwell time varies with relative stoichiometry of the signaling proteins in the phase-separated clusters, rendering N-WASP and Arp2/3 activity stoichiometry dependent. This mechanism of controlling protein activity is enabled by the stoichiometrically undefined nature of biomolecular condensates. Such regulation should be a general feature of signaling systems that assemble through multivalent interactions and drive nonequilibrium outputs.

A composition-dependent molecular clutch between T cell signaling condensates and actin.

During T cell activation, biomolecular condensates form at the immunological synapse (IS) through multivalency-driven phase separation of LAT, Grb2, Sos1, SLP-76, Nck, and WASP. These condensates move radially at the IS, traversing successive radially-oriented and concentric actin networks. To understand this movement, we biochemically reconstituted LAT condensates with actomyosin filaments. We found that basic regions of Nck and N-WASP/WASP promote association and co-movement of LAT condensates with actin, indicating conversion of weak individual affinities to high collective affinity upon phase separation. Condensates lacking these components were propelled differently, without strong actin adhesion. In cells, LAT condensates lost Nck as radial actin transitioned to the concentric network, and engineered condensates constitutively binding actin moved aberrantly. Our data show that Nck and WASP form a clutch between LAT condensates and actin in vitro and suggest that compositional changes may enable condensate movement by distinct actin networks in different regions of the IS.

Who's In and Who's Out-Compositional Control of Biomolecular Condensates.

Biomolecular condensates are two- and three-dimensional compartments in eukaryotic cells that concentrate specific collections of molecules without an encapsulating membrane. Many condensates behave as dynamic liquids and appear to form through liquid-liquid phase separation driven by weak, multivalent interactions between macromolecules. In this review, we discuss current models and data regarding the control of condensate composition, and we describe our current understanding of the composition of representative condensates including PML nuclear bodies, P-bodies, stress granules, the nucleolus, and two-dimensional membrane localized LAT and nephrin clusters. Specific interactions, such as interactions between modular binding domains, weaker interactions between intrinsically disorder regions and nucleic acid base pairing, and nonspecific interactions, such as electrostatic interactions and hydrophobic interactions, influence condensate composition. Understanding how specific condensate composition is determined is essential to understanding condensates as biochemical entities and ultimately discerning their cellular and organismic functions.

A molecular classification of papillary renal cell carcinoma.

Despite the moderate incidence of papillary renal cell carcinoma (PRCC), there is a disproportionately limited understanding of its underlying genetic programs. There is no effective therapy for metastatic PRCC, and patients are often excluded from kidney cancer trials. A morphologic classification of PRCC into type 1 and 2 tumors has been recently proposed, but its biological relevance remains uncertain. We studied the gene expression profiles of 34 cases of PRCC using Affymetrix HGU133 Plus 2.0 arrays (54,675 probe sets) using both unsupervised and supervised analyses. Comparative genomic microarray analysis was used to infer cytogenetic aberrations, and pathways were ranked with a curated database. Expression of selected genes was validated by immunohistochemistry in 34 samples with 15 independent tumors. We identified two highly distinct molecular PRCC subclasses with morphologic correlation. The first class, with excellent survival, corresponded to three histologic subtypes: type 1, low-grade type 2, and mixed type 1/low-grade type 2 tumors. The second class, with poor survival, corresponded to high-grade type 2 tumors (n = 11). Dysregulation of G1-S and G2-M checkpoint genes were found in class 1 and 2 tumors, respectively, alongside characteristic chromosomal aberrations. We identified a seven-transcript predictor that classified samples on cross-validation with 97% accuracy. Immunohistochemistry confirmed high expression of cytokeratin 7 in class 1 tumors and of topoisomerase IIalpha in class 2 tumors. We report two molecular subclasses of PRCC, which are biologically and clinically distinct and may be readily distinguished in a clinical setting.

Reconstitution of TCR Signaling Using Supported Lipid Bilayers.

Biochemical reconstitution has served as an important tool for understanding the mechanisms of many cellular processes including DNA replication, transcription, translation, vesicle trafficking, and ubiquitin-mediated proteolysis. Here, we demonstrate that biochemical reconstitution can be applied to studying a complex signaling pathway involving as many as 12 proteins or protein complexes acting at the surface of model membranes. We show that a temporal sequence of events in activated T cells beginning with phosphorylation of the T cell receptor and culminating in the activation of actin polymerization can be replicated in vitro. Our reconstitution demonstrates the sufficiency of these proteins in producing many of the complex behaviors observed during T cell activation. The ability to manipulate all of the components, measure reaction rates, and observe molecular behaviors, including at single molecule resolution, has enabled us to gain insight into some of the important biochemical features of this signaling pathway such as microcluster formation. The same system could be adapted to study other membrane-proximal signaling pathways, including growth factor receptors, death receptors, and Eph receptors.