Membraneless Organelles Research Articles

First person – Angela Fan and Yoldas Yildiz

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Biology Open, helping researchers promote themselves alongside their papers. Angela Fan and Yoldas Yildiz are co-first authors on ‘ Ethanol induces subcellular trafficking of the RNA-binding protein, hnRNP A1, in neuronal cells in vitro, but not in the peripubertal rat brain’, published in BIO. Angela is a PhD candidate in the lab of Toni R. Pak at Loyola University Chicago Stritch School of Medicine, Maywood, IL, USA, investigating biomolecular condensates, particularly their formation mechanisms and functional roles under stress, especially in the context of pathophysiology. Yoldas is a PhD candidate in the same lab, investigating the cellular and molecular mechanisms of nuclear receptor signalling, how they change in ageing, and the downstream consequences to the transcriptome and proteome.

Enhanced condensate fluidity in modified patchy particle models.

Biomolecular condensates are formed via liquid-liquid phase separation of proteins, often together with nucleic acids, typically driven by interactions between low-affinity binding sites. The computational study of such condensates that accounts for both the droplet-scale fluid behavior and the internal structure of the condensate requires coarse-grained models. Recently, patchy particle models, representing proteins as spheres with a repulsive core and directional attractive patches, have emerged as a powerful tool. However, these simulations typically exhibit slow dynamics and often show glass-like rather than fluid condensates as required for the description of many biomolecular condensates, establishing a need for model variants with accelerated dynamics, both to speed up simulations and to better represent fluid biomolecular condensates. Here, we study several modified patchy particle models suited to simulate the formation and dynamics of biomolecular condensates. These variants incorporate flexible patches and weak isotropic attractions between cores. They significantly accelerate the system dynamics while preserving key equilibrium characteristics of the classical patchy particle model, including the phase behavior and the local structure of the condensate. These modifications thereby enable the simulation of larger, more complex systems previously inaccessible due to prohibitive relaxation times and provide a versatile tool for studying condensate dynamics.

Chromatin heterogeneity modulates nuclear condensate dynamics and phase behavior

The cell nucleus is a soft composite material with a shell-like nuclear cortex enclosing chromatin, comprised of roughly 2 meters of DNA and associated proteins. Assembling on and around chromatin are droplet-like structures known as biomolecular condensates, which form via phase separation, and facilitate vital roles in gene expression. From studies in non-living materials, the driving forces for phase separation are expected to be sensitive to the local mechanical environment, which often exhibits significant spatial heterogeneity. However, the relationship between chromatin heterogeneity and the phase equilibrium and dynamics of nuclear condensates remains unclear. Here, we investigate the interplay between chromatin organization and the formation, dynamics, and size of engineered model condensates and endogenous nuclear bodies in living cells. We demonstrate that decreasing chromatin heterogeneity with epigenetic modifying drugs correlates with decreased mobility of both endogenous and engineered condensates, and is associated with impaired condensate growth and shifts in the binodal phase boundary of engineered condensates. These findings illustrate how the cell nucleus behaves as a heterogeneous composite material with mechanically permissive chromatin micro-environments.

Enhancement of enzymatic activity by biomolecular condensates through pH buffering

Biomolecular condensates can affect enzymatic reactions by locally changing not only concentrations of molecules but also their environment. Since protein conformations can differ between the dense and dilute phase, phase separation can particularly modulate enzymes characterized by a conformation-dependent activity. Here, we generate enzymatic condensates containing a lipase from Bacillus thermocatenulatus, which exhibits an equilibrium between a closed, inactive state, and an open, active conformation. We show that the activity of the enzyme increases inside the dense phase, leading to an enhancement of the overall reaction rate in the phase-separated system. Moreover, we demonstrate that these condensates can generate a more basic environment compared to the surrounding solution, maintaining a high enzymatic activity even in a solution pH interval that would be otherwise less favorable for the lipase. We further show that the formation of two phases with distinct pH values optimizes a cascade reaction involving two enzymes with different optimal pH conditions. Our results demonstrate that, through local pH buffering, biomolecular condensates can expand the optimal pH interval for enzymatic reactions and increase their robustness towards changes in environmental parameters. These findings have implications in biology and biotechnology for biocatalytic engineering, for instance for enabling network reactions with enzymes that require distinct pH values.

Chemical Probe Discovery for DEAD-Box RNA-Binding Protein DDX21 Using Small-Molecule Microarrays.

The DEAD-box family of ATPases plays a critical role in nearly all stages of RNA metabolism, from transcription to degradation, and serves as a major regulator of biomolecular condensates. Dysregulation of DEAD-box proteins is well-established in a variety of diseases, including cancer and neurodegenerative disorders, making them attractive therapeutic targets. However, their classification as "undruggable" has historically hindered small-molecule-based modulation. In this study, we focus on DDX21, a member of the DEAD-box family involved in ribosome biogenesis and transcription regulation. As a proof of concept for targeting such RNA-binding proteins, we developed a lysate-based small-molecule microarray platform to identify compounds that directly bind DDX21. This screen led to the discovery of KI-DX-014, a small-molecule compound capable of inhibiting the interaction of DDX21 with RNA. KI-DX-014 modulated the RNA-dependent functions of DDX21, including its ATPase activity and biomolecular condensate formation. Furthermore, KI-DX-014 attenuated the DDX21-dependent release of P-TEFb from the 7SK snRNP complex in vitro, suppressed P-TEFb-dependent phosphorylation of the RNA polymerase II CTD, and induced developmental defects in zebrafish embryos. These findings reveal a previously unexploited therapeutic avenue and establish KI-DX-014 as a chemical probe for dissecting the biological functions of DDX21 in both normal physiology and disease states.

Nucleolar proteomics revealed the regulation of RNA exosome localization by MTR4.

Nucleolar proteomics revealed the regulation of RNA exosome localization by MTR4.

Nuclear p62/SQSTM1 facilitates ubiquitin-independent proteasomal degradation of BMAL1.

Brain and muscle arnt-like protein 1(BMAL1) is a critical regulator of circadian rhythm. Although transcriptional regulation of BMAL1 has been extensively studied, the mechanisms governing the stability of BMAL1 at the protein level remain unclear. p62/SQSTM1 is a crucial factor in proteostasis regulation and is involved in both autophagy and the ubiquitin-proteasome system. We demonstrated that p62 promotes proteasomal degradation of BMAL1 within the nucleus, independent of ubiquitination. Additional molecular analyses indicated that p62 functions as a receptor for the 20S proteasome, facilitating the recruitment of BMAL1 to the 20S proteasome for degradation. This mechanism is independent of recently identified p62-driven nuclear biomolecular condensates. We also revealed that remodeling the nuclear accumulation of p62 may represent a potential strategy for targeting BMAL1 to suppress tumor cell growth. In conclusion, our findings revealed a novel mechanism by which nuclear p62 regulates BMAL1 proteostasis.

Anomalous thermoresponsive phase behavior in a minimal lattice model mimicking proteins.

Proteins are known to phase separate and form biomolecular condensates that play key roles in cellular functions. Therefore, there is now a growing interest in understanding rational design principles for protein sequences that exhibit rich stimulus-responsive phase behavior. Here, we have developed a minimal lattice-gas model and employed Monte-Carlo simulations to capture rich thermoresponsive phase behavior often observed in computational and experimental studies on disordered proteins. Proteins are modeled as particles with two internal states: a ground state representing the native configuration and a degenerate excited state representing unfolded configurations. The computed phase diagrams reveal an anomalous reentrant phase separation behavior with both upper and lower critical solution temperatures, providing insights into its underlying mechanism. We also explored non-equilibrium effects, such as non-Boltzmann population distributions of native and unfolded states, and enhanced translational diffusion due to non-thermal noise on the phase separation. We find that these factors offer an additional dimension for modulating condensate morphologies. We further extended our model to study phase separation in binary protein mixtures and successfully reproduced complex phase-separated states, including wetted, partially wetted, segregative, and associative phases-observed in computational studies of these systems. This model can be easily extended to mimic proteins with multiple internal (say, partially folded) states, allowing exploration of conformation heterogeneity effects on condensate morphologies. Our findings offer important insights into designing solvent-mediated effective interactions between proteins for controlled phase separation, relevant for engineering functional condensates.

Liquid-Liquid Phase Separation in Hereditary Hearing Loss.

Hearing loss is one of the most prevalent sensory disorders affecting the human nervous system. Liquid-liquid phase separation (LLPS) is a physiological process that facilitates the reversible and dynamic assembly of biomolecular condensates. Increasing evidence suggests that LLPS plays a significant role in the pathogenesis of hereditary hearing loss. Nevertheless, there is a conspicuous lack of systematic investigations exploring the impact of LLPS abnormalities on the etiology of hereditary hearing loss. In this review, we examine the mechanisms by which dysfunctions in LLPS contribute to hereditary hearing loss, specifically focusing on its effects on mechanoelectrical transduction in hair bundles, transcriptional regulation, post-transcriptional modifications, the actin cytoskeleton, ion homeostasis within the inner ear, and energy and redox homeostasis. Furthermore, we evaluate the considerable potential of targeting LLPS as a therapeutic approach for hearing loss and propose innovative perspectives on LLPS that may guide future research initiatives in the field of auditory disorders.

Multivalency Controls the Growth and Dynamics of a Biomolecular Condensate.

Biomolecular condensates are essential for cellular organization and function, yet understanding how chemical and physical factors govern their formation and dynamics has been limited by a lack of noninvasive measurement techniques. Conventional microscopy methods often rely on fluorescent labeling and substrate immobilization, which can perturb the intrinsic properties of condensates. To overcome these challenges, we apply label-free, contact-free holographic video microscopy to study the behavior of a condensate-forming protein in vitro. This technique enables rapid, high-throughput, and precise measurements of individual condensate diameters and refractive indexes, providing unprecedented insight into size distributions and dense-phase macromolecular concentrations over time. Using this method, we investigate the kinetics of droplet growth, aging, and equilibrium dynamics in the model condensate-forming protein PopZ. By systematically varying the concentration and valence of cations, we uncover how multivalent ions influence condensate organization and dynamics, a hypothesis we further test using super-resolution microscopy. Our findings reveal that PopZ droplet growth deviates from classical models such as Smoluchowski coalescence and Ostwald ripening. Instead, we show that condensate growth is consistent with gelation at the critical overlap concentration. Holographic microscopy offers significant advantages over traditional techniques, such as differential interference contrast microscopy, delivering reproducible measurements and capturing condensate dynamics with unparalleled precision. This work highlights the power of holographic microscopy to probe the material properties and mechanistic underpinnings of biomolecular condensates, paving the way for deeper insights into their roles in synthetic systems.

Comprehensive protein datasets and benchmarking for liquid–liquid phase separation studies

BackgroundProteins self-organize in dynamic cellular environments by assembling into reversible biomolecular condensates through liquid–liquid phase separation (LLPS). These condensates can comprise single or multiple proteins, with different roles in the ensemble’s structural and functional integrity. Driver proteins form condensates autonomously, while client proteins just localize within them. Although several databases exist to catalog proteins undergoing LLPS, they often contain divergent data that impedes interoperability between these resources. Additionally, there is a lack of consensus on selecting proteins without explicit experimental association with condensates under physiological conditions (non-LLPS proteins or negative proteins). These two aspects have prevented the generation of reliable predictive models and fair benchmarks.ResultsIn this work, we use an integrated biocuration protocol to analyze information from all relevant LLPS databases and generate confident datasets of client and driver proteins. We introduce standardized negative datasets, encompassing both globular and disordered proteins. To validate our datasets, we investigate specific physicochemical traits related to LLPS across different subsets of protein sequences and benchmark them against 16 predictive algorithms. We observe significant differences not only between positive and negative instances but also among LLPS proteins themselves. The datasets from this study are available as a website at https://llpsdatasets.ppmclab.com and as a data repository at https://doi.org/10.5281/zenodo.15118996.ConclusionsOur datasets offer a reliable means for confidently assessing the specific roles of proteins in LLPS and identifying key differences in physicochemical properties underlying this process. Moreover, we describe limitations in classical and state-of-the-art predictive algorithms by providing the most comprehensive benchmark to date.Graphical

Optogenetic storage and release of protein and mRNA in live cells and animals

Cells compartmentalize biomolecules in membraneless structures called biomolecular condensates. While their roles in regulating cellular processes are increasingly understood, tools for their synthetic manipulation remain limited. Here, we introduce RELISR (Reversible Light-Induced Store and Release), an optogenetic condensate system that enables reversible storage and release of proteins or mRNAs. RELISR integrates multivalent scaffolds, optogenetic switches, and cargo-binding domains to trap cargo in the dark and release it upon blue-light exposure. We demonstrate its utility in primary neurons and show that light-triggered release of signaling proteins can modulate fibroblast morphology. Furthermore, light-induced release of cargo mRNA results in protein translation both in vitro and in live mice. RELISR thus provides a versatile platform for spatiotemporal control of protein activity and mRNA translation in complex biological systems, with broad potential for research and therapeutic applications.

Small Molecules as Regulators of Liquid-Liquid Phase Separation: Mechanisms and Strategies for New Drug Discovery.

Condensate-modifying therapeutics (c-mods), comprising low-molecular-weight compounds (~1.5 kDa) and related agents such as RNAs and metabolites like ATP, are emerging as promising drug candidates for neurodegenerative disorders, cancer, and viral infections. These compounds modulate liquid-liquid phase separation (LLPS), a biophysical process driven by intrinsically disordered regions, low-complexity domains, and multivalent non-covalent interactions (hydrogen bonds, van der Waals forces, hydrophobic, and electrostatic interactions). LLPS governs the formation of biomolecular condensates essential for gene regulation, signaling, stress responses, and cellular organization. By selectively inhibiting or promoting condensation, we show that c-mods offer strategies to manage diseases presented with aberrant phase separation. Mechanistic insights into LLPS dynamics provided by specific physicochemical features (planar structures and polarity) of c-mods open avenues for accelerating drug discovery, repurposing, and synergistic therapies. We highlight scaffolds, charged molecules, and ions that modulate LLPS. We integrate recent advances in understanding the roles of c-mods in regulating viral protein assemblies; however, the function of LLPS and its regulation in other microorganisms remains underexplored. Future directions include engineering peptide-based therapeutics, designing artificial condensates, and employing AI-driven target identification to discover novel LLPS-associated drug targets. Additionally, biomaterials and industry-led initiatives in condensate-targeted drug discovery are broadening therapeutic intervention across diverse diseases.

A plant bunyaviral protein disrupts SERRATE phase separation to modulate microRNA biogenesis during viral pathogenesis

Liquid-liquid phase separation (LLPS) regulates diverse biological functions by mediating the assembly of biomolecular condensates. However, it remains unclear how host LLPS is targeted by viruses during infection. Here we show that a plant bunyaviral protein, the disease-specific protein (SP) encoded by rice stripe virus (RSV), possesses phase separation potential through its N-terminal intrinsically disordered region 1 (IDR1). In vivo, however, SP does not form phase-separated biomolecular condensates independently but utilizes its phase separation properties to interfere with the phase separation of the SERRATE protein (SE), a key component of Dicing bodies essential for microRNA processing. By disrupting SE phase separation, SP inhibits D-body assembly and miRNA biogenesis. Our study demonstrates that a viral protein can modulate host microRNA processing by targeting LLPS, revealing a previously uncharacterized mechanism involved in viral infection strategies and miRNA biogenesis regulation in plants.

Homotypic RNA clustering accompanies a liquid-to-solid transition inside the core of multi-component biomolecular condensates.

RNA-driven condensation plays a central role in organizing and regulating ribonucleoprotein granules within cells. Disruptions to this process-such as the aberrant aggregation of repeat-expanded RNA-are associated with numerous neurological disorders. Here we study the role of biomolecular condensates in irreversible RNA aggregation. We find that physiologically relevant and disease-associated repeat RNAs spontaneously undergo an age-dependent percolation transition inside multi-component condensates to form nanoscale clusters. Homotypic RNA clusters drive the emergence of multi-phasic condensate structures, with an RNA-rich solid core surrounded by an RNA-depleted fluid shell. The timescale of RNA clustering is determined by sequence, secondary structure and repeat length. Importantly, G3BP1, the core scaffold of stress granules, introduces heterotypic buffering to homotypic RNA-RNA interactions and prevents RNA clustering in an ATP-independent manner. Our work suggests that biomolecular condensates can act as sites for RNA aggregation and highlights the chaperone-like function of RNA-binding proteins against aberrant RNA phase transitions.

Mapping and engineering RNA-driven architecture of the multiphase nucleolus.

Biomolecular condensates are key features of intracellular compartmentalization1,2. As the most prominent nuclear condensate in eukaryotes, the nucleolus is a multiphase liquid-like structure in which ribosomal RNAs (rRNAs) are transcribed and processed, undergoing multiple maturation steps to form the small (SSU) and large (LSU) ribosomal subunits3-5. However, how rRNA processing is coupled to the layered organization of the nucleolus is poorly understood owing to a lack of tools to precisely monitor and perturb nucleolar rRNAprocessing dynamics. Here we developed two complementary approaches to spatiotemporally map rRNA processing and engineer de novo nucleoli. Using sequencing in parallel with imaging, we found that rRNA processing steps are spatially segregated, with sequential maturation of rRNA required for its outward movement through nucleolar phases. By generating synthetic nucleoli in cells using an engineered rDNA plasmid system, we show that defects in SSU processing can alter the ordering of nucleolar phases, resulting in inside-out nucleoli and preventing rRNA outflux, while LSU precursors are necessary to build the outermost layer of the nucleolus. These findings demonstrate how rRNA is both a scaffold and substrate for the nucleolus, with rRNA acting as a programmable blueprint for the multiphase architecture that facilitates assembly of an essential molecular machine.

An artificial intelligence-based approach for identifying the proteins regulating liquid–liquid phase separation

Liquid–liquid phase separation (LLPS) is a biomolecular process that underpins the formation of membrane-less organelles within living cells. This phenomenon, along with the resulting condensate bodies, is increasingly recognized for its critical roles in various biological processes, such as ribonucleic acid (RNA) metabolism, chromatin rearrangement, and signal transduction. Notably, regulator proteins play a central role in the process of LLPS. They are essential for the formation, stabilization, and maintenance of the dynamic properties of LLPS, ensuring an appropriate phase separation response to cellular signals. Targeting these regulator proteins is the key to manipulating LLPS for applications in biotechnology, materials science, and medicine, including biomaterials, drug delivery, diagnostics, and synthetic biology. Given their importance, this study focused on an artificial intelligence-based approach to identify regulator proteins in LLPS. We constructed a dataset of 913 positive and 6584 negative protein sequences, and divided it into eight balanced training datasets and a test dataset. Semantic information from protein sequences was extracted using the ESM2_t36 pretrained protein language model, followed by training a multilayer perceptron classifier. The model achieved 0.78 accuracy on the test dataset, outperforming traditional sequence-based methods, one-hot encoding, and other pretrained embedding methods. SHapley Additive exPlanations (SHAP)-based interpretation revealed key biophysical patterns enriched in regulator proteins, including higher levels of charged and disordered residues. Our results show that deep contextual protein representations combined with neural network-based classifiers can accurately identify LLPS regulator proteins. This tool offers new opportunities for understanding condensate biology and designing synthetic phase-separating systems. All data and code are available at: https://github.com/bioplusAI/LLPS_regulators_pred.

AMPK alters proteasome phosphorylation status and prevents persistent proteasome condensates.

Proteasomes undergo dynamic nucleocytoplasmic translocation and phase transitions in response to glucose starvation. AMP-activated protein kinase (AMPK) is important for cytoplasmic proteasome condensate dissolution and proteasome nuclear reentry in budding yeast cells upon glucose refeeding of quiescent cells. This study demonstrates that AMPK interacts with proteasomes, and the AMPK pathway regulates proteasome phosphorylation status and condensate solubility during reversible proteasome condensate formation. AMPK and the PP1 phosphatase dynamically regulate phosphorylation of multiple proteasome subunits. Therefore, the regulation of proteasome phosphorylation by AMPK is likely to be central to proteasome biomolecular condensate formation and dissolution.

Unraveling architectural RNAs: Structural and functional blueprints of membraneless organelles and strategies for genome-scale identification.

Unraveling architectural RNAs: Structural and functional blueprints of membraneless organelles and strategies for genome-scale identification.

Small-molecule-induced liquid-liquid phase separation suppresses the carcinogenesis of β-catenin

Biomolecular condensates are droplet-like membrane-less compartments in cells that can sequester proteins. Modulating these condensates offers a promising way to durably inhibit disease-driving proteins that lack enzymatic activity and thus elude traditional drug targeting. However, many such proteins remain beyond the reach of current condensate-modulating strategies. Here we show an alternative approach: by destabilizing target proteins, we directly induce their liquid–liquid phase separation (LLPS), causing them to form condensates. Using this strategy, we develop a small molecule RQ that forces β-catenin (an oncogenic protein in liver cancer) into cytoplasmic condensates. This sequestration prevents β-catenin from entering the nucleus and activating cancer-promoting genes. In nanoparticle form (albumin-bound Abroquinone), RQ is selectively taken up by β-catenin-driven liver cancer cells and kills them while sparing normal cells. This approach suppresses β-catenin-driven tumor growth and overcomes immune evasion, demonstrating a promising paradigm for targeting previously untargetable proteins by inducing their phase separation.