Influence of Nonspecific Interactions on Protein Associations: Implications for Biochemistry In Vivo.

The cellular interior is composed of a variety of microenvironments defined by distinct local compositions and composition-dependent intermolecular interactions. We review the various types of nonspecific interactions between proteins and between proteins and other macromolecules and supramolecular structures that influence the state of association and functional properties of a given protein existing within a particular microenvironment at a particular point in time. The present state of knowledge is summarized, and suggestions for fruitful directions of research are offered.

Enhanced DNA repair through droplet formation and p53 oscillations.

Living organisms are constantly exposed to DNA damage, and optimal repair is therefore crucial. A characteristic hallmark of the response is the formation of sub-compartments around the site of damage, known as foci. Following multiple DNA breaks, the transcription factor p53 exhibits oscillations in its nuclear concentration, but how this dynamics can affect the repair remains unknown. Here, we formulate a theory for foci formation through droplet condensation and discover how oscillations in p53, with its specific periodicity and amplitude, optimize the repair process by preventing Ostwald ripening and distributing protein material in space and time. Based on the theory predictions, we reveal experimentally that the oscillatory dynamics of p53 does enhance the repair efficiency. These results connect the dynamical signaling of p53 with the microscopic repair process and create a new paradigm for the interplay of complex dynamics and phase transitions in biology.

A Solid-State Conceptualization of Information Transfer from Gene to Message to Protein.

In this review, we describe speculative ideas and early stage research concerning the flow of genetic information from the nuclear residence of genes to the disparate, cytoplasmic sites of protein synthesis. We propose that this process of information transfer is meticulously guided by transient structures formed from protein segments of low sequence complexity/intrinsic disorder. These low complexity domains are ubiquitously associated with regulatory proteins that control gene expression and RNA biogenesis, but they are also found in the central channel of nuclear pores, the nexus points of intermediate filament assembly, and the locations of action of other well-studied cellular proteins and pathways. Upon being organized into localized cellular positions via mechanisms utilizing properly folded protein domains, thereby facilitating elevated local concentration, certain low complexity domains adopt cross-ß interactions that are both structurally specific and labile to disassembly. These weakly tethered assemblies, we propose, are built to relay the passage of genetic information from one site to another within a cell, ensuring that the process is of extreme fidelity.

The Eukaryotic CO2-Concentrating Organelle Is Liquid-like and Exhibits Dynamic Reorganization.

Approximately 30%-40% of global CO2 fixation occurs inside a non-membrane-bound organelle called the pyrenoid, which is found within the chloroplasts of most eukaryotic algae. The pyrenoid matrix is densely packed with the CO2-fixing enzyme Rubisco and is thought to be a crystalline or amorphous solid. Here, we show that the pyrenoid matrix of the unicellular alga Chlamydomonas reinhardtii is not crystalline but behaves as a liquid that dissolves and condenses during cell division. Furthermore, we show that new pyrenoids are formed both by fission and de novo assembly. Our modeling predicts the existence of a "magic number" effect associated with special, highly stable heterocomplexes that influences phase separation in liquid-like organelles. This view of the pyrenoid matrix as a phase-separated compartment provides a paradigm for understanding its structure, biogenesis, and regulation. More broadly, our findings expand our understanding of the principles that govern the architecture and inheritance of liquid-like organelles.

A central chaperone-like role for 14-3-3 proteins in human cells.

14-3-3 proteins are highly conserved regulatory proteins that interact with hundreds of structurally diverse clients and act as central hubs of signaling networks. However, how 14-3-3 paralogs differ in specificity and how they regulate client protein function are not known for most clients. Here, we map the interactomes of all human 14-3-3 paralogs and systematically characterize the effect of disrupting these interactions on client localization. The loss of 14-3-3 binding leads to the coalescence of a large fraction of clients into discrete foci in a client-specific manner, suggesting a central chaperone-like function for 14-3-3 proteins. Congruently, the engraftment of 14-3-3 binding motifs to nonclients can suppress their aggregation or phase separation. Finally, we show that 14-3-3s negatively regulate the localization of the RNA-binding protein SAMD4A to cytoplasmic granules and inhibit its activity as a translational repressor. Our work suggests that 14-3-3s have a more prominent role as chaperone-like molecules than previously thought.

Universal cold RNA phase transitions.

RNA's diversity of structures and functions impacts all life forms since primordia. We use calorimetric force spectroscopy to investigate RNA folding landscapes in previously unexplored low-temperature conditions. We find that Watson-Crick RNA hairpins, the most basic secondary structure elements, undergo a glass-like transition below [Formula: see text]C where the heat capacity abruptly changes and the RNA folds into a diversity of misfolded structures. We hypothesize that an altered RNA biochemistry, determined by sequence-independent ribose-water interactions, outweighs sequence-dependent base pairing. The ubiquitous ribose-water interactions lead to universal RNA phase transitions below TG, such as maximum stability at [Formula: see text]C where water density is maximum, and cold denaturation at [Formula: see text]C. RNA cold biochemistry may have a profound impact on RNA function and evolution.

Real-space visualization of a defect-mediated charge density wave transition.

We study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS2. By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature Tc by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance-a global property-and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

Heterotypic electrostatic interactions control complex phase separation of tau and prion into multiphasic condensates and co-aggregates.

Biomolecular condensates formed via phase separation of proteins and nucleic acids are thought to perform a wide range of critical cellular functions by maintaining spatiotemporal regulation and organizing intracellular biochemistry. However, aberrant phase transitions are implicated in a multitude of human diseases. Here, we demonstrate that two neuronal proteins, namely tau and prion, undergo complex coacervation driven by domain-specific electrostatic interactions to yield highly dynamic, mesoscopic liquid-like droplets. The acidic N-terminal segment of tau interacts electrostatically with the polybasic N-terminal intrinsically disordered segment of the prion protein (PrP). We employed a unique combination of time-resolved tools that encompass several orders of magnitude of timescales ranging from nanoseconds to seconds. These studies unveil an intriguing symphony of molecular events associated with the formation of heterotypic condensates comprising ephemeral, domain-specific, short-range electrostatic nanoclusters. Our results reveal that these heterotypic condensates can be tuned by RNA in a stoichiometry-dependent manner resulting in reversible, multiphasic, immiscible, and ternary condensates of different morphologies ranging from core-shell to nested droplets. This ternary system exhibits a typical three-regime phase behavior reminiscent of other membraneless organelles including nucleolar condensates. We also show that upon aging, tau:PrP droplets gradually convert into solid-like co-assemblies by sequestration of persistent intermolecular interactions. Our vibrational Raman results in conjunction with atomic force microscopy and multi-color fluorescence imaging reveal the presence of amorphous and amyloid-like co-aggregates upon maturation. Our findings provide mechanistic underpinnings of overlapping neuropathology involving tau and PrP and highlight a broader biological role of complex phase transitions in physiology and disease.

The spontaneous symmetry breaking in Ta2NiSe5 is structural in nature.

The excitonic insulator is an electronically driven phase of matter that emerges upon the spontaneous formation and Bose condensation of excitons. Detecting this exotic order in candidate materials is a subject of paramount importance, as the size of the excitonic gap in the band structure establishes the potential of this collective state for superfluid energy transport. However, the identification of this phase in real solids is hindered by the coexistence of a structural order parameter with the same symmetry as the excitonic order. Only a few materials are currently believed to host a dominant excitonic phase, Ta2NiSe5 being the most promising. Here, we test this scenario by using an ultrashort laser pulse to quench the broken-symmetry phase of this transition metal chalcogenide. Tracking the dynamics of the material's electronic and crystal structure after light excitation reveals spectroscopic fingerprints that are compatible only with a primary order parameter of phononic nature. We rationalize our findings through state-of-the-art calculations, confirming that the structural order accounts for most of the gap opening. Our results suggest that the spontaneous symmetry breaking in Ta2NiSe5 is mostly of structural character, hampering the possibility to realize quasi-dissipationless energy transport.

Observation of the most H2-dense filled ice under high pressure.

Hydrogen hydrates are among the basic constituents of our solar system's outer planets, some of their moons, as well Neptune-like exo-planets. The details of their high-pressure phases and their thermodynamic conditions of formation and stability are fundamental information for establishing the presence of hydrogen hydrates in the interior of those celestial bodies, for example, against the presence of the pure components (water ice and molecular hydrogen). Here, we report a synthesis path and experimental observation, by X-ray diffraction and Raman spectroscopy measurements, of the most H[Formula: see text]-dense phase of hydrogen hydrate so far reported, namely the compound 3 (or C[Formula: see text]). The detailed characterisation of this hydrogen-filled ice, based on the crystal structure of cubic ice I (ice I[Formula: see text]), is performed by comparing the experimental observations with first-principles calculations based on density functional theory and the stochastic self-consistent harmonic approximation. We observe that the extreme (up to 90 GPa and likely beyond) pressure stability of this hydrate phase is due to the close-packed geometry of the hydrogen molecules caged in the ice I[Formula: see text] skeleton.

Adaptive Monte Carlo augmented with normalizing flows.

SignificanceMonte Carlo methods, tools for sampling data from probability distributions, are widely used in the physical sciences, applied mathematics, and Bayesian statistics. Nevertheless, there are many situations in which it is computationally prohibitive to use Monte Carlo due to slow "mixing" between modes of a distribution unless hand-tuned algorithms are used to accelerate the scheme. Machine learning techniques based on generative models offer a compelling alternative to the challenge of designing efficient schemes for a specific system. Here, we formalize Monte Carlo augmented with normalizing flows and show that, with limited prior data and a physically inspired algorithm, we can substantially accelerate sampling with generative models.

Observation of two-step melting on a sphere.

Melting in two-dimensional flat space is typically two-step and via the hexatic phase. How melting proceeds on a curved surface, however, is not known. Topology mandates that crystalline particle assemblies on these surfaces harbor a finite density of defects, which itself can be ordered, like the icosahedral ordering of 5-coordinated disclination defects on a sphere. Thus, melting even on a sphere, the simplest closed surface, involves the loss of both crystalline and defect order. Probing the interplay of these two forms of order, however, requires a system in which melting can be performed in situ, and this has not been achieved hitherto. Here, by tuning interparticle interactions in situ, we report an observation of an intermediate hexatic phase during the melting of colloidal crystals on a sphere. Remarkably, we observed a precipitous drop in icosahedral defect order in the hexatic phase where the shear modulus is expected to vanish. Furthermore, unlike in flat space, where disorder can fundamentally alter the nature of the melting process, on the sphere, we observed the signature characteristics of ideal melting. Our findings have profound implications for understanding, for instance, the self-assembly and maturation dynamics of viral capsids and also phase transitions on curved surfaces.

Opinion dynamics in financial markets via random networks.

We investigate financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize individuals in a financial market according to their trading strategy, namely, whether they are noise traders or fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the decisions of fundamentalist agents. We introduce a noise parameter, q, to represent the level of anxiety and perceived uncertainty regarding market behavior, enabling the possibility of adrift financial action. We place individuals as nodes in an Erdös-Rényi random graph, where the links represent their social interactions. At any given time, individuals assume one of two possible opinion states ±1 regarding buying or selling an asset. The model exhibits fundamental qualitative and quantitative real-world market features such as the distribution of logarithmic returns with fat tails, clustered volatility, and the long-term correlation of returns. We use Student's t distributions to fit the histograms of logarithmic returns, showing a gradual shift from a leptokurtic to a mesokurtic regime depending on the fraction of fundamentalist agents. Furthermore, we compare our results with those concerning the distribution of the logarithmic returns of several real-world financial indices.

Understanding the coevolution of mask wearing and epidemics: A network perspective.

Nonpharmaceutical interventions (NPIs) such as mask wearing can be effective in mitigating the spread of infectious diseases. Therefore, understanding the behavioral dynamics of NPIs is critical for characterizing the dynamics of disease spread. Nevertheless, standard infection models tend to focus only on disease states, overlooking the dynamics of "beneficial contagions," e.g., compliance with NPIs. In this work, we investigate the concurrent spread of disease and mask-wearing behavior over multiplex networks. Our proposed framework captures both the competing and complementary relationships between the dueling contagion processes. Further, the model accounts for various behavioral mechanisms that influence mask wearing, such as peer pressure and fear of infection. Our results reveal that under the coupled disease-behavior dynamics, the attack rate of a disease-as a function of transition probability-exhibits a critical transition. Specifically, as the transmission probability exceeds a critical threshold, the attack rate decreases abruptly due to sustained mask-wearing responses. We empirically explore the causes of the critical transition and demonstrate the robustness of the observed phenomena. Our results highlight that without proper enforcement of NPIs, reductions in the disease transmission probability via other interventions may not be sufficient to reduce the final epidemic size.

Sharp, localized phase transitions in single neuronal cells.

The origin of nonlinear responses in cells has been suggested to be crucial for various cell functions including the propagation of the nervous impulse. In physics, nonlinear behavior often originates from phase transitions. Evidence for such transitions on the single-cell level, however, has so far not been provided, leaving the field unattended by the biological community. Here, we demonstrate that single cells of a human neuronal cell line display all optical features of a sharp, highly nonlinear phase transition within their membrane. The transition is reversible and does not originate from protein denaturation. Triggered by temperature and modified by pH here, a thermodynamic approach strongly suggests that similar nonlinear state changes can be induced by other variables such as calcium or mechanical stress. At least in lipid membranes, such state changes are accompanied by significant changes in permeability, enzyme activity, elastic, and electrical properties.

Phase-transforming metamaterial with magnetic interactions.

Solid-solid phase transformations can affect energy transduction and change material properties (e.g., superelasticity in shape memory alloys and soft elasticity in liquid crystal elastomers). Traditionally, phase-transforming materials are based on atomic- or molecular-level thermodynamic and kinetic mechanisms. Here, we develop elasto-magnetic metamaterials that display phase transformation behaviors due to nonlinear interactions between internal elastic structures and embedded, macroscale magnetic domains. These phase transitions, similar to those in shape memory alloys and liquid crystal elastomers, have beneficial changes in strain state and mechanical properties that can drive actuations and manage overall energy transduction. The constitutive response of the elasto-magnetic metamaterial changes as the phase transitions occur, resulting in a nonmonotonic stress-strain relation that can be harnessed to enhance or mitigate energy storage and release under high-strain-rate events, such as impulsive recoil and impact. Using a Landau free energy-based predictive model, we develop a quantitative phase map that relates the geometry and magnetic interactions to the phase transformation. Our work demonstrates how controllable phase transitions in metamaterials offer performance capabilities in energy management and programmable material properties for high-rate applications.

Synthesis and Polymorph Manipulation of FeSe2 Monolayers.

Polymorph engineering involves the manipulation of material properties through controlled structural modification and is a candidate technique for creating unique two-dimensional transition metal dichalcogenide (TMDC) nanodevices. Despite its promise, polymorph engineering of magnetic TMDC monolayers has not yet been demonstrated. Here we grow FeSe2 monolayers via molecular beam epitaxy and find that they have great promise for magnetic polymorph engineering. Using scanning tunneling microscopy (STM) and spectroscopy (STS), we find that FeSe2 monolayers predominantly display a 1T' structural polymorph at 5 K. Application of voltage pulses from an STM tip causes a local, reversible transition from the 1T' phase to the 1T phase. Density functional theory calculations suggest that this single-layer structural phase transition is accompanied by a magnetic transition from an antiferromagnetic to a ferromagnetic configuration. These results open new possibilities for creating functional magnetic devices with TMDC monolayers via polymorph engineering.

From Insulator to Superconductor: A Series of Pressure-Driven Transitions in Quasi-One-Dimensional TiS3 Nanoribbons.

Transition metal trichalcogenides (TMTCs) offer remarkable opportunities for tuning electronic states through modifications in chemical composition, temperature, and pressure. Despite considerable interest in TMTCs, there remain significant knowledge gaps concerning the evolution of their electronic properties under compression. In this study, we employ experimental and theoretical approaches to comprehensively explore the high-pressure behavior of the electronic properties of TiS3, a quasi-one-dimensional (Q1D) semiconductor, across various temperature ranges. Through high-pressure electrical resistance and magnetic measurements at elevated pressures, we uncover a distinctive sequence of phase transitions within TiS3, encompassing a transformation from an insulating state at ambient pressure to the emergence of an incipient superconducting state above 70 GPa. Our findings provide compelling evidence that superconductivity at low temperatures of ∼2.9 K is a fundamental characteristic of TiS3, shedding new light on the intriguing high-pressure electronic properties of TiS3 and underscoring the broader implications of our discoveries for TMTCs in general.

Nanoscale Operando Imaging of Electrically Driven Charge-Density Wave Phase Transitions.

Structural transformations in strongly correlated materials promise efficient and fast control of materials' properties via electrical or optical stimulation. The desired functionality of devices operating based on phase transitions, however, will also be influenced by nanoscale heterogeneity. Experimentally characterizing the relationship between microstructure and phase switching remains challenging, as nanometer resolution and high sensitivity to subtle structural modifications are required. Here, we demonstrate nanoimaging of a current-induced phase transformation in the charge-density wave (CDW) material 1T-TaS2. Combining electrical characterizations with tailored contrast enhancement, we correlate macroscopic resistance changes with the nanoscale nucleation and growth of CDW phase domains. In particular, we locally determine the transformation barrier in the presence of dislocations and strain, underlining their non-negligible impact on future functional devices. Thereby, our results demonstrate the merit of tailored contrast enhancement and beam shaping for advanced operando microscopy of quantum materials and devices.

Making the Case for Disordered Proteins and Biomolecular Condensates in Bacteria.

Intrinsically disordered proteins/regions (IDPs/IDRs) contribute to a diverse array of molecular functions in eukaryotic systems. There is also growing recognition that membraneless biomolecular condensates, many of which are organized or regulated by IDPs/IDRs, can enable spatial and temporal regulation of complex biochemical reactions in eukaryotes. Motivated by these findings, we assess if (and how) membraneless biomolecular condensates and IDPs/IDRs are functionally involved in key cellular processes and molecular functions in bacteria. We summarize the conceptual underpinnings of condensate assembly and leverage these concepts by connecting them to recent findings that implicate specific types of condensates and IDPs/IDRs in important cellular level processes and molecular functions in bacterial systems.