Stability Of Condensate Research Articles

Nonspecific Yet Selective Interactions Contribute to Small Molecule Condensate Binding.

Biomolecular condensates are essential in various cellular processes, and their misregulation has been demonstrated to underlie disease. Small molecules that modulate condensate stability and material properties offer promising therapeutic approaches, but mechanistic insights into their interactions with condensates remain largely lacking. We employ a multiscale approach to enable long-time, equilibrated all-atom simulations of various condensate-ligand systems. Systematic characterization of the ligand binding poses reveals that condensates can form diverse and heterogeneous chemical environments with one or multiple chains to bind small molecules. Unlike traditional protein-ligand interactions, these chemical environments are dominated by nonspecific hydrophobic interactions. Nevertheless, the chemical environments feature unique amino acid compositions and physicochemical properties that favor certain small molecules over others, resulting in varied ligand partitioning coefficients within condensates. Notably, different condensates share similar sets of chemical environments but at different populations. This population shift drives ligand selectivity toward specific condensates. Our approach can enhance the interpretation of experimental screening data and may assist in the rational design of small molecules targeting specific condensates.

Cosmic stability of dark matter from Pauli blocking

Why does dark matter (DM) live longer than the age of the Universe? Here we study a novel sub-eV scalar DM candidate whose stability is due to the Pauli exclusion of its fermionic decay products. We analyze the stability of the DM condensate against decays, scatterings (i.e., evaporation), and parametric resonance, delineating the viable parameter regions in which DM is cosmologically stable. In a minimal scenario in which the scalar DM decays to a pair of new exotic fermions, we find that scattering can populate an interacting thermal dark sector component to energies far above the DM mass. This self-interacting dark radiation may potentially alleviate the Hubble tensions. Furthermore, our scenario can be probed through precise measurements of the halo-mass function or the masses of dwarf spheroidal galaxies since scattering prevents the DM from becoming too dense. On the other hand, if the lightest neutrino stabilizes the DM, the cosmic neutrino background (CνB) can be significantly altered from the Lambda cold dark matter prediction and thus be probed in the future by CνB detection experiments. Published by the American Physical Society 2024

Nucleoprotein Phase-Separation Affinities Revealed via Atomistic Simulations of Short Peptide and RNA Fragments.

Liquid-liquid phase separation of proteins and nucleic acids into condensate phases is a versatile mechanism for ensuring the compartmentalization of cellular biochemistry. RNA molecules play critical roles in these condensates, particularly in transcriptional regulation and stress responses, exhibiting a wide range of thermodynamic and dynamic behaviors. However, deciphering the molecular grammar that governs the stability and dynamics of protein-RNA condensates remains challenging due to the multicomponent and heterogeneous nature of condensates. In this study, we employ atomistic simulations of 20 distinct mixtures containing minimal RNA and peptide fragments which allows us to dissect the phase-separating affinities of all 20 amino acids in the presence of RNA. Our findings elucidate chemically specific interactions, hydration profiles, and ionic effects that synergistically promote or suppress protein-RNA phase separation. We map a ternary phase diagram of interactions, identifying four distinct groups of residues that promote, maintain, suppress, and disrupt protein-RNA clusters.

Nucleoprotein phase-separation affinities revealed via atomistic simulations of short peptide and RNA fragments.

Liquid-liquid phase separation of proteins and nucleic acids into condensate phases is a versatile mechanism for ensuring compartmentalization of cellular biochemistry. RNA molecules play critical roles in these condensates, particularly in transcriptional regulation and stress responses, exhibiting a wide range of thermodynamic and dynamic behaviors. However, deciphering the molecular grammar that governs the stability and dynamics of protein-RNA condensates remains challenging due to the multicomponent and heterogeneous nature of these biomolecular mixtures. In this study, we employ atomistic simulations of twenty distinct mixtures containing minimal RNA and peptide fragments to dissect the phase-separating affinities of all twenty amino acids in the presence of RNA. Our findings elucidate chemically specific interactions, hydration profiles, and ionic effects that synergistically promote or suppress protein-RNA phase separation. We map a ternary phase diagram of interactions, identifying four distinct groups of residues that promote, maintain, suppress, or disrupt protein-RNA clusters.

DNA-Origami-Armored DNA Condensates.

DNA condensates, formed by liquid-liquid phase separation (LLPS), emerge as promising soft matter assemblies for creating artificial cells. The advantages of DNA condensates are their molecular permeability through the surface due to their membrane-less structure and their fluidic property. However, they face challenges in the design of their surface, e. g., unintended fusion and less regulation of permeable molecules. Addressing them, we report surface modification of DNA condensates with DNA origami nanoparticles, employing a Pickering-emulsion strategy. We successfully constructed core-shell structures with DNA origami coatings on DNA condensates and further enhanced the condensate stability toward fusion via connecting DNA origamis by responding to DNA input strands. The 'armoring' prevented the fusion of DNA condensates, enabling the formation of multicellular-like structures of DNA condensates. Moreover, the permeability was altered through the state change from coating to armoring the DNA condensates. The armored DNA condensates have significant potential for constructing artificial cells, offering increased surface stability and selective permeability for small molecules while maintaining compartmentalized space and multicellular organization.

Ubiquitin-driven protein condensation stabilizes clathrin-mediated endocytosis.

Clathrin-mediated endocytosis is an essential cellular pathway that enables signaling and recycling of transmembrane proteins and lipids. During endocytosis, dozens of cytosolic proteins come together at the plasma membrane, assembling into a highly interconnected network that drives endocytic vesicle biogenesis. Recently, multiple groups have reported that early endocytic proteins form flexible condensates, which provide a platform for efficient assembly of endocytic vesicles. Given the importance of this network in the dynamics of endocytosis, how might cells regulate its stability? Many receptors and endocytic proteins are ubiquitylated, while early endocytic proteins such as Eps15 contain ubiquitin-interacting motifs. Therefore, we examined the influence of ubiquitin on the stability of the early endocytic protein network. In vitro, we found that recruitment of small amounts of polyubiquitin dramatically increased the stability of Eps15 condensates, suggesting that ubiquitylation could nucleate endocytic assemblies. In live-cell imaging experiments, a version of Eps15 that lacked the ubiquitin-interacting motif failed to rescue defects in endocytic initiation created by Eps15 knockout. Furthermore, fusion of Eps15 to a deubiquitylase enzyme destabilized nascent endocytic sites within minutes. In both in vitro and live-cell settings, dynamic exchange of Eps15 proteins, a measure of protein network stability, was decreased by Eps15-ubiquitin interactions and increased by loss of ubiquitin. These results collectively suggest that ubiquitylation drives assembly of the flexible protein network responsible for catalyzing endocytic events. More broadly, this work illustrates a biophysical mechanism by which ubiquitylated transmembrane proteins at the plasma membrane could regulate the efficiency of endocytic internalization.

Non-specific yet selective interactions contribute to small molecule condensate partitioning behavior.

Biomolecular condensates are essential in various cellular processes, and their mis-regulation has been demonstrated to be underly disease. Small molecules that modulate condensate stability and material properties offer promising therapeutic approaches, but mechanistic insights into their interactions with condensates remain largely lacking. We employ a multiscale approach to enable long-time, equilibrated all-atom simulations of various condensate-ligand systems. Systematic characterization of the ligand binding poses reveals that condensates can form diverse and heterogeneous chemical environments with one or multiple chains to bind small molecules. Unlike traditional protein-ligand interactions, these chemical environments are dominated by non-specific hydrophobic interactions. Nevertheless, the chemical environments feature unique amino acid compositions and physicochemical properties that favor certain small molecules over others, resulting in varied ligand partitioning coefficients within condensates. Notably, different condensates share similar sets of chemical environments but at different populations. This population shift drives ligand selectivity towards specific condensates. Our approach can enhance the interpretation of experimental screening data and may assist in the rational design of small molecules targeting specific condensates.

Microphase Separation Produces Interfacial Environment within Diblock Biomolecular Condensates.

The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.

Stability and deformation of biomolecular condensates under the action of shear flow.

Biomolecular condensates play a key role in cytoplasmic compartmentalization and cell functioning. Despite extensive research on the physico-chemical, thermodynamic, or crowding aspects of the formation and stabilization of the condensates, one less studied feature is the role of external perturbative fluid flow. In fact, in living cells, shear stress may arise from streaming or active transport processes. Here, we investigate how biomolecular condensates are deformed under different types of shear flows. We first model Couette flow perturbations via two-way coupling between the condensate dynamics and fluid flow by deploying Lattice Boltzmann Molecular Dynamics. We then show that a simplified approach where the shear flow acts as a static perturbation (one-way coupling) reproduces the main features of the condensate deformation and dynamics as a function of the shear rate. With this approach, which can be easily implemented in molecular dynamics simulations, we analyze the behavior of biomolecular condensates described through residue-based coarse-grained models, including intrinsically disordered proteins and protein/RNA mixtures. At lower shear rates, the fluid triggers the deformation of the condensate (spherical to oblated object), while at higher shear rates, it becomes extremely deformed (oblated or elongated object). At very high shear rates, the condensates are fragmented. We also compare how condensates of different sizes and composition respond to shear perturbation, and how their internal structure is altered by external flow. Finally, we consider the Poiseuille flow that realistically models the behavior in microfluidic devices in order to suggest potential experimental designs for investigating fluid perturbations in vitro.

Алгоритм оценки последствий отказа технологического трубопровода по методике API RP 581 3rd Edition (Уровень 1)

The article considers the issue of the development of an algorithm for the assessment of the consequences of failure (CoF) of the process pipeline of the gas condensate stabilization system of a hazardous production facility. The assessment of the consequences of failure is one of the main components of a risk-oriented approach to the inspection of technical devices. In accordance with the API RP 581 3rd Edition methodology, the assessment is used for equipment ranking and designed to determine the priority of inspections. Inspection, in turn, is a tool to ensure integrity, i.e., the condition of equipment that ensures its leak-tightness, which undoubtedly is a necessary condition of industrial safety. The algorithm and the detailed procedure of calculation of failure consequences consisting of 13 basic stages have been provided. As an example, the calculation of failure consequences has been conducted by the API RP 581 3rd Edition methodology (Level 1). The basic stages and the results of calculation have been compared to the calculation methodologies of technical device failure consequences effective in Russia. The results of the comparative analysis of methodologies indicate their similarity as to the application of common methods of the analysis of accident scenarios, the use of similar initial data, and the focus on the reduction of equipment failure risk. At the same time, significant differences in indices and criteria of acceptable risk level have been detected. The results of the calculation indicated the conservatism of the API 581 3rd Edition methodology (Level 1). The application of calculation of failure consequences by the API RP 581 3rd Edition methodology (Level 1) in the field of risk-oriented approach to the inspection of technical devices is possible upon its adaptation to the standards generally accepted in Russia.

Modularity of PRC1 composition and chromatin interaction define condensate properties.

Polycomb repressive complexes (PRCs) play a key role in gene repression and are indispensable for proper development. Canonical PRC1 forms condensates invitro and in cells that are proposed to contribute to the maintenance of repression. However, how chromatin and the various subunits of PRC1 contribute to condensation is largely unexplored. Using a reconstitution approach and single-molecule imaging, we demonstrate that nucleosomal arrays and PRC1 act synergistically, reducing the critical concentration required for condensation by more than 20-fold. We find that the exact combination of PHC and CBX subunits determines condensate initiation, morphology, stability, and dynamics. Particularly, PHC2's polymerization activity influences condensate dynamics by promoting the formation of distinct domains that adhere to each other but do not coalesce. Live-cell imaging confirms CBX's role in condensate initiation and highlights PHC's importance for condensate stability. We propose that PRC1 composition can modulate condensate properties, providing crucial regulatory flexibility across developmental stages.

Probing the surface charge of condensates using microelectrophoresis

Biomolecular condensates play an important role in cellular organization. Coacervates are commonly used models that mimic the physicochemical properties of biomolecular condensates. The surface of condensates plays a key role in governing molecular exchange between condensates, accumulation of species at the interface, and the stability of condensates against coalescence. However, most important surface properties, including the surface charge and zeta potential, remain poorly characterized and understood. The zeta potential of coacervates is often measured using laser doppler electrophoresis, which assumes a size-independent electrophoretic mobility. Here, we show that this assumption is incorrect for liquid-like condensates and present an alternative method to study the electrophoretic mobility of coacervates and in vitro condensate models by microelectrophoresis and single-particle tracking. Coacervates have a size-dependent electrophoretic mobility, originating from their fluid nature, from which a well-defined zeta potential is calculated. Interestingly, microelectrophoresis measurements reveal that polylysine chains are enriched at the surface of polylysine/polyaspartic acid complex coacervates, which causes the negatively charged protein ɑ-synuclein to adsorb and accumulate at the interface. Addition of ATP inverts the surface charge, displaces ɑ-synuclein from the surface and may help to suppress its interface-catalyzed aggregation. Together, these findings show how condensate surface charge can be measured and altered, making this microelectrophoresis platform combined with automated single-particle tracking a promising characterization technique for both biomolecular condensates and coacervate protocells.

Interplay between charge distribution and DNA in shaping HP1 paralog phase separation and localization

The heterochromatin protein 1 (HP1) family is a crucial component of heterochromatin with diverse functions in gene regulation, cell cycle control, and cell differentiation. In humans, there are three paralogs, HP1α, HP1β, and HP1γ, which exhibit remarkable similarities in their domain architecture and sequence properties. Nevertheless, these paralogs display distinct behaviors in liquid-liquid phase separation (LLPS), a process linked to heterochromatin formation. Here, we employ a coarse-grained simulation framework to uncover the sequence features responsible for the observed differences in LLPS. We highlight the significance of the net charge and charge patterning along the sequence in governing paralog LLPS propensities. We also show that both highly conserved folded and less-conserved disordered domains contribute to the observed differences. Furthermore, we explore the potential co-localization of different HP1 paralogs in multicomponent assemblies and the impact of DNA on this process. Importantly, our study reveals that DNA can significantly reshape the stability of a minimal condensate formed by HP1 paralogs due to competitive interactions of HP1α with HP1β and HP1γ versus DNA. In conclusion, our work highlights the physicochemical nature of interactions that govern the distinct phase-separation behaviors of HP1 paralogs and provides a molecular framework for understanding their role in chromatin organization.

Interplay between charge distribution and DNA in shaping HP1 paralog phase separation and localization.

The heterochromatin protein 1 (HP1) family is a crucial component of heterochromatin with diverse functions in gene regulation, cell cycle control, and cell differentiation. In humans, there are three paralogs, HP1α, HP1β, and HP1γ, which exhibit remarkable similarities in their domain architecture and sequence properties. Nevertheless, these paralogs display distinct behaviors in liquid-liquid phase separation (LLPS), a process linked to heterochromatin formation. Here, we employ a coarse-grained simulation framework to uncover the sequence features responsible for the observed differences in LLPS. We highlight the significance of the net charge and charge patterning along the sequence in governing paralog LLPS propensities. We also show that both highly conserved folded and less-conserved disordered domains contribute to the observed differences. Furthermore, we explore the potential co-localization of different HP1 paralogs in multicomponent assemblies and the impact of DNA on this process. Importantly, our study reveals that DNA can significantly reshape the stability of a minimal condensate formed by HP1 paralogs due to competitive interactions of HP1α with HP1β and HP1γ versus DNA. In conclusion, our work highlights the physicochemical nature of interactions that govern the distinct phase-separation behaviors of HP1 paralogs and provides a molecular framework for understanding their role in chromatin organization.

Controlling collisional loss and scattering lengths of ultracold dipolar molecules with static electric fields

Trapped samples of ultracold molecules are often short-lived because close collisions between them result in trap loss. We investigate the use of shielding with static electric fields to create repulsive barriers between polar molecules to prevent such loss. Shielding is very effective even for RbCs, with a relatively low dipole moment, and even more effective for molecules such as NaK, NaRb, and NaCs, with progressively larger dipoles. Varying the electric field allows substantial control over the scattering length, which will be crucial for the stability or collapse of molecular Bose-Einstein condensates. This arises because the dipole-dipole interaction creates a long-range attraction that is tunable with electric field. For RbCs, the scattering length is positive across the range where shielding is effective because the repulsion responsible for shielding dominates. For NaK, the scattering length can be tuned across zero to negative values. For NaRb and NaCs, the attraction is strong enough to support tetra-atomic bound states, and the scattering length passes through resonant poles where these states cross threshold. For KAg and CsAg, there are multiple bound states and multiple poles. For each molecule, we calculate the variation of the scattering length with field and comment on the possibilities for exploring new physics. Published by the American Physical Society 2024

A machine learning approach for modelling and optimization of complex systems: Application to condensate stabilizer plants

AbstractRecent advancements in supervised machine learning tools have demonstrated their ability to achieve accurate and efficient prediction results. In this paper, we leverage these tools as alternative approaches to model a specific application in the gas industry, based on operating data. The chosen application is a natural gas condensate stabilization process, in which light end components are removed to reduce condensate vapour pressure, meeting storage and transportation specifications. Here, we develop and evaluate various supervised machine learning models to predict the performance of two industrial condensate stabilizer units. By utilizing large datasets from these units and encompassing comprehensive operating data of input–output variables, we not only demonstrate the capability of these techniques to offer reliable and accurate predictions but also shed light on their potential impacts and implementations. The impacts of applying selected AI and machine learning algorithms are two‐fold. First, our research presents an innovative approach to process modelling and optimization in the gas industry, showing the potential for enhanced operational efficiency, profitability, and safety. Second, we propose a data‐driven surrogate‐based optimization framework, where the generated machine learning models can replace detailed first‐principle models, offering a streamlined method to find optimal values for variables to reduce operational energy consumption. Furthermore, we address the validation requirements of our machine learning models, ensuring their robustness and reliability in real‐world applications. By incorporating rigorous validation procedures, we guarantee the quality of our predictions and support their practical implementation. In conclusion, our research not only highlights the capabilities of machine learning in gas industry applications but also emphasizes their potential impacts and contributions to operational excellence. So, the presented approach can pave the way for improved performance, efficiency, and profitability in the gas industry.

Active learning of the thermodynamics-dynamics trade-off in protein condensates.

Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.

Improvement of operating conditions and composition of streams in gas condensate stabilization unit with the aim of reducing flare gas in Sarkhon and Qeshm gas plant

The gas condensate is one of the most valuable products of gas refineries. In unit 700 of the Sarkhon gas refinery, first, the gas condensate is separated from the feed. Then, the vapor pressure of the gas condensate is stabilized by de-ethanizer and de-butanizer towers. The H-701 and H-702 furnaces act as reboilers of the towers. In this research, unit 700 is simulated by HYSYS software. The product of this unit is examined to achieve desirable conditions. In addition, the best conditions are obtained to reduce the gas loss in this unit. The desirable conditions are introduced according to the operational problems of this unit. In this study, the environmental and economic loss due to the loss of hydrocarbons from the de-butanizer tower is identified. Results of this research show that the best operating temperature and pressure of the first feed are 40 °C and 29 bar, respectively. Also, the best temperature and pressure of the second feed are 20 °C and 28 bar, respectively. Also, the best temperature and pressure of the output stream from the S-701 as a feed of the T-701 are 34.35 °C and 22.51 bar, respectively.

Ion binding with charge inversion combined with screening modulates DEAD box helicase phase transitions

Membraneless organelles, or biomolecular condensates, enable cells to compartmentalize material and processes into unique biochemical environments. While specific, attractive molecular interactions are known to stabilize biomolecular condensates, repulsive interactions, and the balance between these opposing forces, are largely unexplored. Here, we demonstrate that repulsive and attractive electrostatic interactions regulate condensate stability, internal mobility, interfaces, and selective partitioning of molecules both invitro and in cells. We find that signaling ions, such as calcium, alter repulsions between model Ddx3 and Ddx4 condensate proteins by directly binding to negatively charged amino acid sidechains and effectively inverting their charge, in a manner fundamentally dissimilar to electrostatic screening. Using a polymerization model combined with generalized stickers and spacers, we accurately quantify and predict condensate stability over a wide range of pH, salt concentrations, and amino acid sequences. Our model provides a general quantitative treatment for understanding how charge and ions reversibly control condensate stability.

Sulfur melt in Golovnin Caldera, Kunashir Island, Russia

The paper considers the formation of native sulfur and sulfides in the bottom sediments of volcanic lakes in the Golovnin Caldera. Our observations and microstructure studies indicate the presence of sulfur melt at the bottom of Kipyaschee Lake. Drops of this melt are carried to the surface of the lake as part of a light gray foam. The significant differences of sulfur spherules in the concentration of sulfide mineralization, in its composition, as well as in the presence or absence of numerous opal inclusions are most simply explained by the capture of droplets in various parts of the sulfur melt and their subsequent movement by a gas stream passing through the melt. The effusions of sulfur melt in 1979 are direct evidence of its existence. Molecular chemical modeling shows that the stability of sulfur condensate in the bottom sediments is controlled by two thermobaric surfaces. The upper is controlled by the beginning of water condensation and a wave of acidity, the lower by the beginning of sulfur condensation. Both surfaces are a consequence of the cooling effect of lake water, and when bottom sediments accumulate, they move following changes in the surface of the lake bottom. Elemental sulfur condensate is formed between these surfaces as a result of forced cooling of endogenous gas flows. This process is most active in crater depressions at the bottom of Golovnin Caldera lakes, where sulfidization of the sulfur melt occurs simultaneously with the condensation of sulfur itself. Gravitational deposition of sulfides in the sulfur melt leads to their enrichment of the root parts of crater depressions, where pyrite ore bodies are formed in real time.