Biology subjects

Espinosa, J. R.

Publications and source records attributed to Espinosa, J. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Size Control of hnRNPK-based Nucleolar Condensates by RNA-Regulated Fusion Dynamics

Nucleoli are liquid-like condensates whose size is actively conserved--they remain small, numerous, and resistant to coalescence--yet the molecular mechanisms that constrain their fusion remain poorly understood. Heterogeneous nuclear ribonucleoprotein K (hnRNPK), an RNA-binding protein implicated in nucleolar organization and cancer, interacts directly with the scaffold protein Nucleolin. Combining residue-resolution coarse-grained simulations with biochemical experiments, we find that hnRNPK and Nucleolin condense through distinct interaction networks--a localized cation-{pi}/electrostatic hotspot in hnRNPK versus broadly distributed electrostatic contacts in Nucleolin, reorganized upon co-assembly. To probe how RNAs reshape these condensates, we develop and validate, against re-entrant phase-separation experiments and AlphaLISA binding data, a nucleotide-resolution coarse-grained model for single-stranded RNA. Using this framework, we show that RNA is asymmetrically and preferentially recruited by hnRNPK over Nucleolin, an asymmetry that grows stronger when the two proteins compete for the same RNAs. This selective recruitment sustains a dynamic fission-fusion equilibrium: hnRNPK-containing condensates repeatedly fuse and split rather than coalescing into a single condensate, whereas Nucleolin-containing and ternary condensates fuse into one dominant cluster. These results reveal a molecular mechanism, grounded in sequence-encoded, RNA-controlled fusion dynamics, by which nucleolar condensates conserve a controlled, non-coalescing size despite their liquid-like character.

biophysics↗

bioRxiv2026

Prognostic stratification by LGR5 expression identifies surface-accessible, structurally ligandable and condensate-forming targets in colorectal cancer

Background: LGR5 marks colorectal cancer stem cells and is associated with poor outcome, but its expression on normal intestinal stem cells has constrained direct therapeutic targeting, and the molecular landscape of LGR5-high tumors remains incompletely defined. A transcriptional signature is not itself a set of drug targets: its constituent genes differ in whether and how they can be engaged pharmacologically, a distinction rarely applied systematically to a tumor-defined gene set. Methods: We stratified 396 colorectal tumors from The Cancer Genome Atlas by LGR5 expression and compared transcriptional, somatic mutation, and copy number profiles between LGR5-high and LGR5-low groups using non-parametric testing with combined significance and effect-size thresholds. Genome-wide CRISPR knockout data were interrogated to test genetic dependency. Each signature gene was then triaged by pharmacological tractability rather than essentiality, along three axes: surface accessibility, from surfaceome annotation and membrane topology; cavity ligandability, from pocket detection on predicted structures using three independent algorithms; and condensate propensity, from saturation concentration prediction and coarse-grained molecular dynamics simulation. Results: LGR5-high tumors displayed a coordinated program spanning Wnt signaling, stemness, and matrix remodeling, arising on an APC-mutant background with co-occurring IGF2 amplification. No constituent gene scored as a selective dependency. The three axes partitioned the signature with minimal overlap and nominated three candidates engaged by orthogonal modalities: ENPP3, a single-pass ectoenzyme presenting an accessible ectodomain and carrying clinical antibody-drug conjugate precedent; PLCB4, combining a well-defined catalytic pocket with additional predicted ligandable sites; and NKD1, accessible by neither route but undergoing RNA-stabilized homotypic phase separation, unlike SATB1 and MEX3A. Simulations further indicated that NKD1 partitions into DVL2-containing condensates and reduces DVL2-Wnt contacts, suggesting a biophysical basis for its negative-feedback role. Conclusions: LGR5 expression defines a colorectal cancer subset that is pharmacologically tractable despite the absence of genetic dependency. Triaging by modality rather than essentiality converts descriptive tumor signatures into stratified, experimentally testable therapeutic hypotheses, including condensate-directed modulation of NKD1 as a route to targets inaccessible by antibody- or pocket-based approaches.

molecular biology↗

bioRxiv2026

Compositional control of FUS condensate ageing through aggregation-prone interaction networks

Stress granules are multicomponent biomolecular condensates whose aberrant ageing has been implicated in numerous neurodegenerative diseases. Although their composition is known to influence condensate properties, the molecular principles linking composition to structural maturation remain poorly understood. Here, we perform equilibrium and non-equilibrium residue-resolution molecular dynamics simulations to determine how RNA and heterotypic protein interactions regulate the pathological hardening of multicomponent FUS-containing condensates inspired by stress-granule composition. We show that diverse compositional changes--including RNA concentration, heterotypic protein partitioning, interfacial enrichment of G3BP1, and charged peptide recruitment--reshape condensate organization through distinct molecular mechanisms. Despite these different modes of action, all converge on a common physical principle: modulation of the local clustering and persistence of contacts between low-complexity aromatic-rich kinked segments (LARKS) governs the nucleation and accumulation of long-lived intermolecular cross-{beta}-sheet structures. Intermediate RNA concentrations enhance condensate density and promote LARKS contacts, whereas high RNA levels, heterotypic interactions, and interfacial coating reduce their availability and delay ageing. Our results establish a unified molecular framework linking condensate composition, internal organization and ageing. This framework provides mechanistic insight into the regulation of multicomponent condensate material properties and suggests general design principles for modulating their pathological aggregation.

biophysics↗

bioRxiv2026

A Spectrum of Free Energy Landscape Topologies Encodes Chromatin Polymorphism and Phase Separation

Chromatin exhibits structural polymorphism, yet how such substantial structural heterogeneity is encoded in its underlying free-energy landscape remains unknown. Here we map the folding landscapes of tetra-nucleosome arrays using adaptive Markov state models constructed from near-atomistic coarse-grained simulations. We find that chromatin is not governed by a single folding funnel analogous to those of many globular proteins. Instead, it spans a continuum of free-energy landscape topologies, ranging from funnelled to rugged to flat. Remarkably, phase separation reshapes chromatins free-energy landscape by stabilising conformations that maximise intermolecular connectivity, demonstrating that the landscape is determined not only by intrinsic molecular parameters but also by the environment and intermolecular interactions. Linker DNA geometry selects among landscape regimes through geometric frustration of zig-zag nucleosome stacking. At short and intermediate linker lengths, canonical 10N bp linkers produce funnelled landscapes dominated by compact zig-zag structures, whereas 10N +5 bp linkers generate rugged landscapes with multiple competing minima. Long linkers relieve frustration and flatten the landscape into a broad entropic basin. This control operates with single-base-pair precision, such that changing linker length by one base pair is sufficient to reorganise both the thermodynamics and kinetics of chromatin folding. DNA sequence provides a second level of control by modulating linker deformability, but only when zig-zag geometric frustration is present. These results establish free-energy landscapes as a framework for understanding the physical origin of chromatin polymorphism and its coupling to phase separation.

biophysics↗

bioRxiv2026

RNA2PS: A sequence-specific coarse-grained RNA model linking structure, thermodynamics and phase separation

RNA plays a central role in the formation and regulation of biomolecular condensates, yet a quantitative understanding of how RNA sequence, structure, and thermodynamics jointly determine phase behaviour, particularly in repeat expansion RNAs, remains incomplete. Here, we introduce RNA2PS, a sequence-specific RNA coarse-grained model for phase-separation that predicts RNA structure from sequence, achieving quantitative agreement for both single-stranded conformations and duplex helical geometry relative to crystallographic PDB structures. RNA2PS represents each nucleotide by two beads that separate the phosphate-ribose backbone from the base. This representation decouples electrostatic interactions from directional base pairing, while explicitly incorporating strand polarity (5' [->] 3') and local sequence context at the trimer level. Canonical and wobble base pairing are modelled through a multi-body potential with sequence-dependent coordination. Importantly, RNA2PS captures sequence-dependent duplex stability at the nearest-neighbour level and reproduces experimental melting temperatures across a diverse set of sequences. RNA2PS shows that phase separation of trinucleotide repeat RNAs is governed by transient inter-strand duplexes that form reversible cross-links. Competition between intra- and intermolecular base pairing regulates the density of labile RNA-RNA interactions, giving rise to strong sequence- and length-dependent differences in condensation that reproduce cellular RNA foci formation. Overall, RNA2PS provides a near-quantitative predictive framework that links sequence-encoded hybridization thermodynamics to mesoscale condensation of pure RNA sequences.

biophysics↗

bioRxiv2026

Condensate-Driven Transcriptional Reprogramming Defines Core Vulnerabilities in Esophageal and Gastric Cancers

Biomolecular condensates organize key nuclear functions by compartmentalizing biomolecules, yet their contribution to gastrointestinal tumorigenesis remains poorly defined. Integrating multi-omics profiling, functional genomics, and molecular dynamics simulations, we reveal that esophageal and gastric cancers share a condensate-enriched transcriptional program driven by intrinsically disordered proteins involved in transcription, RNA processing, and replication stress. Transcriptomic analyses identify a hyperactive transcriptional state with upregulation of condensate-associated genes, including TOPBP1 and CHERP. Dependency mapping demonstrates that these proteins are essential for tumor cell viability, defining a conserved condensate core across different tumor types. Machine-learned predictions and residue-resolution coarse-grained simulations confirm that TOPBP1 and CHERP undergo phase separation through homotypic interactions mediated by intrinsically disordered regions, with saturation concentrations below 2 {micro}M, consistent with spontaneous condensate formation observed in vitro. Together, these findings establish condensate organization as a fundamental mesoscale principle in upper gastrointestinal cancers and nominate condensate scaffolds as tractable therapeutic vulnerabilities.

bioinformatics↗

bioRxiv2025

Near-atomistic simulations reveal the molecular principles that control chromatin structure and phase separation

Understanding how chromatins physicochemical properties shape its emergent organisation is central to deciphering genome function. To address this, we present OpenCGChromatin, a high-performance coarse-grained model that achieves near-atomistic simulations of chromatin systems an order of magnitude larger than previously possible, spanning biomolecular condensates and fibers tens of kilobases in length. OpenCGChromatin simulations independently predict, from physicochemical principles, the linker-DNA-dependent chromatin structures observed by cryo-ET and the relative thermodynamic stability of condensates inferred from biochemical assays. Crucially, OpenCGChromatin resolves histone-tail dynamics and interaction networks that remain inaccessible experimentally, explaining how linker-DNA length controls histone tail accessibility and the resulting multiscale structure of chromatin condensates. Extending simulations to 108-nucleosome fibers shows that acetylation disrupts chromatin compaction in a pattern-specific manner by weakening key tail-mediated interactions, with H4K16 and H3K9 emerging as the most energetically disruptive modifications. These results position OpenCGChromatin as a powerful framework for linking molecular detail to emergent chromatin organization.

biophysics↗

bioRxiv2025

Determination of nucleotide-nucleotide and nucleotide-amino acid binding interactions from all-atom potential-of-mean-force calculations

Biomolecular condensates emerge from multivalent interactions between proteins and nucleic acids and are frequently modeled using coarse-grained molecular dynamics simulations. The parametrization of these models critically depends on atomistic data describing the underlying molecular interactions. In this work, we employ all-atom molecular dynamics simulations and potential-of-mean-force (PMF) calculations to investigate the interaction landscape between RNA nucleotides and protein amino acids. We begin by characterizing nucleotide-nucleotide binding modes through canonical base-pairing analysis, observing notable agreement in the predictions from both AMBER03ws and CHARMM36 force fields. Further rationalization of different nucleotide-nucleotide interaction modes involves the calculation of PMFs for ribose-ribose, phosphate-phosphate, and RNA tertiary interactions such as G-quadruplex formation. We also examine the effect of salt concentration on these interactions, finding a reduction on electrostatic self-repulsion for phosphate-phosphate binding upon increasing the ionic strength. Extending our analysis to amino acids, we first benchmark the performance of both AMBER03ws and a99SB-disp force fields for describing pairwise amino acid interactions, and then we evaluate different nucleotide-amino acid binding profiles. Our findings reveal a subset of amino acids--Lys and Arg (positively charged), Asp and Glu (negatively charged), and Gln, Ser, and Asn (polar residues)--that consistently engage with the nitrogenous bases of different nucleotides. Such binding is primarily mediated by hydrogen bonding and, in some cases, cation-{pi} interactions. Furthermore, we identify strong{pi} -{pi} stacking interactions with aromatic residues and phosphate-Arg contacts as key contributors to condensate cohesion in RNA-protein condensates. Our comprehensive analysis provides a detailed library of nucleotide-amino acid interactions, offering quantitative insights to inform coarse-grained model parametrization and deepening our understanding of condensate self-assembly, nucleic acid recognition, and phase-separation regulation at submolecular scale.

biophysics↗

bioRxiv2025

Decoding PARP1 Selectivity: Atomistic Insights for Next-Generation Cancer Inhibitors

Selective inhibition of PARP1 represents a promising strategy to improve the therapeutic index of PARP inhibitors, a class of anticancer agents that exploit defects in DNA repair pathways. While PARP inhibitors have shown remarkable clinical benefit, particularly in BRCA-mutated tumors, the lack of discrimination between PARP1 and its close homolog PARP2, often leads to hematological toxicity and limits treatment efficacy. Thus, achieving molecular selectivity for PARP1 remains a central challenge in the rational design of safer and more potent inhibitors. To explore the molecular determinants of ligand selectivity, we focus on four clinically relevant PARP inhibitors--two PARP1-selective (saruparib and NMS-P118) and two non-selective (veliparib and olaparib) inhibitors--and perform atomistic potential-of-mean-force calculations of the PARP1 catalytic binding domain in the presence of these molecules. Our simulations near-quantitatively capture the experimental relative binding preferences, demonstrating that our approach reliably reflects selectivity patterns. Based on these findings, we analyze protein-ligand contact frequencies to identify the stabilizing interaction network and contact connectivity inducing protein selectivity. The most frequent protein-inhibitor contacts are primarily mediated by tyrosine triads and electrostatic interactions, showing a cooperative complex network of intermolecular contacts which strongly relies on protein multivalency. To dissect the decisive role of individual residues across the binding site, we also perform targeted mutagenesis of the PARP1 catalytic pocket in complex with saruparib, replacing several active-site amino acids by glycines. Progressively increasing the number of mutations markedly reduces binding stability, with distinct residue combinations exerting two primary effects: destabilization of the final bound state and the emergence of energetic barriers along the ligand association pathway. Together, our results provide a coherent mechanistic framework for understanding PARP1 selectivity and informs the rational design of next-generation inhibitors with improved efficacy and safety.

molecular biology↗

bioRxiv2025

An electrostatic repulsion model of centromere organisation

During cell division, chromosomes reorganise into compact bodies in which centromeres localise precisely at the chromatin surface1-4 to enable kinetochore-microtubule interactions essential for genome segregation5-8. The physical principles guiding this centromere positioning remain unknown. Here, we reveal that human core centromeres are directed to the chromatin surface by repulsion of centromere-associated proteins - independent of condensin-mediated loop extrusion and microtubule engagement. Using cellular perturbations, biochemical reconstitution, and multiscale molecular dynamics simulations, we show that chromatin surface localisation emerges from repulsion between condensed chromatin and both the kinetochore and the highly negatively charged centromere protein, CENP-B. Together, these elements form a centromeric region composed of two domains with opposing affinities, one favouring integration within the mitotic chromosome and the other favouring exposure to the surrounding cytoplasm, thereby driving surface positioning. Tethering synthetic negatively charged proteins to chromatin was sufficient to recapitulate this surface localisation in cells and in vitro, indicating that electrostatic repulsion is a key determinant of surface localisation. These findings demonstrate that centromere layering is not hardwired by chromatin folding patterns but instead emerges from phase separation in chromatin. Our work uncovers electrostatic polarity as a general and programmable mechanism to spatially organise chromatin.

cell biology↗

bioRxiv2025

Molecular insights on the mechanism of α1-antitrypsin condensate formation and maturation

The deficiency of 1-antitrypsin protein is a genetic disorder characterized by the accumulation of misfolded protein aggregates within hepatocytes, leading to liver dysfunction. In the lung, it is found in macrophages, bronchial and epithelial alveolar cells type 2, leading to pulmonary emphysema. Despite extensive research, the precise mechanism underlying the formation of 1-antitrypsin inclusion bodies remain elusive. In this study, we combine equilibrium and non-equilibrium molecular dynamics simulations to elucidate the intricate process of 1-antitrypsin condensate formation and maturation. Our mechanistic model explains cluster accumulation--specifically the onset of this pathogenesis--through the emergence of phase-separated liquid-like protein droplets, which subsequently undergo inter-protein {beta}-sheet transitions between misfolded variants, resulting in solid-like clusters. We find that this mechanism only applies to the misfolded variant, Z-1-antitrypsin, which phase-separates driven by its disordered C-terminus. In contrast, the native protein, M-1-antitrypsin, shows much lower propensity to phase-separate and later form kinetically trapped aggregates. Furthermore, we explore how Z-1-antitrypsin exhibits an increased capacity to form condensates near external walls with different types of interactions. Such conditions can be similar to those found within the endoplasmic reticulum membrane, where phase separation and hardening take place. Overall, our results shed light on the molecular basis of 1-antitrypsin-related disorders and provide valuable microscopic insights for the development of therapeutic strategies targeting protein misfolding and aggregation-related disorders. Author summaryAlpha-1 antitrypsin deficiency is a genetic disorder that can cause liver and lung disease. It occurs when the protein 1-antitrypsin folds incorrectly and accumulates in harmful clumps inside cells. Exactly how these clumps form has been unclear. In this study, we used computer simulations to reveal the steps behind this process. We found that the faulty version of the protein first collects into liquid-like droplets that later harden into solid clusters. This behavior is driven by a flexible tail region of the misfolded protein. In contrast, the normal version is far less likely to clump. Our findings provide new insight into disease onset and may guide the development of therapies.

biophysics↗

bioRxiv2024

Capturing single-molecule properties does not ensure accurate prediction of biomolecular phase diagrams

Intracellular liquid-liquid phase separation of proteins and nucleic acids represents a fundamental mechanism by which cells organise their components into biomolecular condensates that perform multiple biological tasks. Computer simulations provide powerful tools to investigate biomolecular phase separation, offering microscopic insights into the physicochemical principles that regulate these systems. In this study, we investigate the phase behaviour of the low-complexity domain (LCD) of hnRNPA1 and several mutants via Molecular Dynamics simulations. We systematically compare the performance of five state-of-the-art residue-resolution coarse-grained protein models: HPS, HPS-cation-{pi}, CALVADOS2, Mpipi, and Mpipi-Recharged. Our evaluation focuses on how well these models reproduce experimental coexistence densities and single-protein radii of gyration for the LCD-hnRNPA1 set of mutants. While most models yield similar intramolecular contact maps and reasonable estimates of the single-protein radius of gyration compared to in vitro measurements, only Mpipi-Recharged, Mpipi, and CALVADOS2 accurately predict phase diagrams that align with experimental data. This suggests that force field parameterizations optimized solely to reproduce single-protein properties may not always capture the phase behaviour of protein solutions. Additionally, our findings reveal that some residue-resolution coarse-grained models can lead to significant discrepancies in predicting the roles of individual intermolecular interactions, even for relatively simple intrinsically disordered proteins like the low-complexity domain of hnRNPA1. Our work highlights the importance of balancing both single-molecule and collective properties of proteins to accurately predict condensate formation and material properties.

biophysics↗

bioRxiv2024

Chemically-informed coarse-graining of electrostatic forces in charge-richbiomolecular condensates

Biomolecular condensates composed of highly charged biomolecules like DNA, RNA, chromatin, and nucleic-acid binding proteins are ubiquitous in the cell nucleus. The biophysical properties of these charge-rich condensates are largely regulated by electrostatic interactions. Residue-resolution coarse-grained models that describe solvent and ions implicitly are widely used to gain mechanistic insights into the biophysical properties of condensates, offering transferability, computational efficiency, and accurate predictions for many systems. However, their predictive accuracy diminishes for charge-rich condensates due to the implicit treatment of solvent and ions. Here, we present the Mpipi-Recharged model, a residue-resolution coarse-grained model that improves the description of charge effects in biomolecular condensates containing disordered proteins, multi-domain proteins, and/or disordered RNAs. Mpipi-Recharged maintains the computational efficiency of its predecessor--the Mpipi model--by still treating solvent and ions implicitly, but improves its accuracy by incorporating a pair-specific asymmetric electrostatic potential informed by atomistic simulations in explicit solvent and ions. We show that such asymmetric coarse-graining of electrostatic forces is needed to recapitulate the stronger mean-field impact of associative interactions between opposite-charge pairs over the repulsion among equally charged pairs revealed by our atomistic simulations. Mpipi-Recharged shows excellent agreement with the experimental phase behavior of highly charged systems, capturing subtle effects challenging to model without explicit solvation, such as the impact of charge blockiness, stoichiometry changes, and salt concentration variation. By offering improved predictions for charge-rich biomolecular condensates, Mpipi-Recharged extends the computational tools available to investigate the physicochemical mechanisms regulating biomolecular condensates.

biophysics↗

bioRxiv2022

Reordering of aromatic-rich segments in FUS inhibits ageing of FUS-RNA condensates

Maturation of functional liquid-like biomolecular condensates into solid-like aggregates has been linked to the onset of several neurodegenerative disorders. Low-complexity aromatic-rich kinked segments (LARKS) contained in numerous RNA-binding proteins can promote aggregation by forming inter-protein {beta}-sheet fibrils that accumulate over time and ultimately drive the liquid-to-solid transition of the condensates. Here, we combine atomistic molecular dynamics simulations with sequence-dependent coarse-grained models of various resolutions to investigate the role of LARKS abundance and position within the amino acid sequence in the maturation of condensates. Remarkably, proteins with tail-located LARKS display much higher viscosity over time than those in which the LARKS are placed towards the center. Yet, at very long timescales, proteins with a single LARKS--independently of its location--can still relax and behave as high viscous liquids. However, phase-separated condensates of proteins containing two or more LARKS become kinetically trapped due to the formation of percolated {beta}-sheet networks that display gel-like behaviour. Furthermore, as a work case example, we demonstrate how shifting the location of the LARKS-containing low-complexity domain of FUS protein towards its center effectively precludes the accumulation of {beta}-sheet fibrils in FUS-RNA condensates, maintaining functional liquid-like behaviour without ageing.

biophysics↗

bioRxiv2022

Time-dependent material properties of ageing biomolecular condensates from different viscoelasticity measurements in molecular dynamics simulations

Biomolecular condensates are important contributors to the internal organization of the cell material. While initially described as liquid-like droplets, the term biomolecular condensates is now used to describe a diversity of condensed phase assemblies with material properties extending from low to high viscous liquids, gels, and even glasses. Because the material properties of condensates are determined by the intrinsic behaviour of their molecules, characterising such properties is integral to rationalising the molecular mechanisms that dictate their functions and roles in health and disease. Here, we apply and compare three distinct computational methods to measure the viscoelasticity of biomolecular condensates in molecular simulations. These methods are the shear stress relaxation modulus integration (SSRMI), the oscillatory shear (OS) technique, and the bead tracking (BT) method. We find that, although all of these methods provide consistent results for the viscosity of the condensates, the SSRMI and OS techniques outperform the BT method in terms of computational efficiency and statistical uncertainty. We, thus, apply the SSRMI and OS techniques for a set of 12 different protein/RNA systems using a sequence-dependent high-resolution coarse-grained model. Our results reveal a strong correlation between condensate viscosity and density, as well as with protein/RNA length and the number of stickers vs. spacers in the amino-acid protein sequence. Moreover, we couple the SSRMI and the OS technique to nonequilibrium molecular dynamics simulations that mimic the progressive liquid-to-gel transition of protein condensates due to the accumulation of inter-protein {beta}-sheets. We compare the behaviour of three different protein condensates--i.e., those formed by either hnRNPA1, FUS, or TDP-43 proteins--whose liquid-to-gel transitions are associated with the onset of amyotrophic lateral sclerosis and frontotemporal dementia. We find that both SSRMI and OS techniques successfully predict the transition from functional liquid-like behaviour to kinetically arrested states once the network of inter-protein {beta}-sheets has percolated through the condensates. Overall, our work provides a comparison of different modelling rheological techniques to assess the viscosity of biomolecular condensates, a critical magnitude that provides information on the behaviour of biomolecules inside condensates.

biophysics↗

bioRxiv2022

Surfactants or scaffolds? RNAs of different lengths exhibit heterogeneous distributions and play diverse roles in RNA-protein condensates

Biomolecular condensates, thought to form via liquid-liquid phase separation of intracellular mixtures, are multicomponent systems that can include diverse types of proteins and RNAs. RNA is a critical modulator of RNA-protein condensate stability, as it induces an RNA-concentration dependent reentrant phase transition--increasing stability at low RNA concentrations and decreasing it at high concentrations. Beyond concentration, RNAs inside condensates can be heterogeneous in length, sequence, and structure. Here, we use multiscale simulations to understanding how different RNA parameters interact with one another to modulate the properties of RNA-protein condensates. To do so, we perform residue/nucleotide-resolution coarse-grained Molecular Dynamics simulations of multicomponent RNA-protein condensates containing RNAs of different lengths and concentrations, and either FUS or PR25 proteins. Our simulations reveal that RNA length regulates the reentrant phase behaviour of RNA-protein condensates: increasing RNA length sensitively rises the maximum value that the critical temperature of the mixture reaches, and the maximum concentration of RNA that the condensate can incorporate before beginning to become unstable. Strikingly, RNA of different lengths are organised heterogeneously inside condensates, which allows them to enhance condensate stability via two distinct mechanisms: shorter RNA chains accumulate at the condensates surface acting as natural biomolecular surfactants, whilst longer RNA chains concentrate inside the core to saturate their bonds and enhance the density of molecular connections in the condensate. Using a patchy particle model, we demonstrate that the combined impact of RNA length and concentration on condensate properties is dictated by the valency, binding affinity, and polymer length of the various biomolecules involved. Our results postulate that diversity on RNA parameters within condensates allows RNAs to increase condensate stability by fulfilling two different criteria: maximizing enthalpic gain and minimizing interfacial free energy; hence, RNA diversity should be considered when assessing the impact of RNA on biomolecular condensates regulation.

biophysics↗

bioRxiv2022

Solid/liquid coexistence during aging of FUS condensates

A wide range of macromolecules undergo phase separation, forming biomolecular condensates in living cells. These membraneless organelles are typically highly dynamic, formed in a reversible manner, and carry out important functions in biological systems. Crucially, however, a further liquid-to-solid transition of the condensates can lead to irreversible pathological aggregation and cellular dysfunction associated with the onset and development of neurodegenerative diseases. Despite the importance of this liquid-to-solid transition of proteins, the mechanism by which it is initiated in normally functional condensates is unknown. Here we show, by measuring the changes in structure, dynamics and mechanics in time and space, that FUS condensates do not uniformly convert to a solid gel, but rather that liquid and gel phases co-exist simultaneously within the same condensate, resulting in highly inhomogeneous structures. We introduce two new optical techniques, dynamic spatial mapping and reflective confocal dynamic speckle microscopy, and use these to further show that the liquid-to-solid transition is initiated at the interface between the dense phase within condensates and the dilute phase. These results reveal the importance of the spatiotemporal dimension of the liquid-to-solid transition and highlight the interface of biomolecular condensates as a key element in driving pathological protein aggregation.

biophysics↗

bioRxiv2022

Ageing critically transforms the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it

Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-protein {beta}-sheets. To bridge microscopic understanding between accumulation of inter-protein {beta}-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-protein {beta}-sheets over time. We reveal that inter-protein {beta}-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strong {beta}-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-protein {beta}-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-protein {beta}-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down.

biophysics↗