Browse Articles

Immiscible proteins compete for RNA binding to order condensate layers

Biomolecular condensates mediate diverse and essential cellular functions by compartmentalizing biochemical pathways. Many condensates have internal subdomains with distinct compositional identities. A major challenge lies in dissecting the multicomponent logic that relates biomolecular features to emergent condensate organization. Nuclear paraspeckles are paradigmatic examples of multidomain condensates, comprising core and shell layers with distinct compositions that are scaffolded by the lncRNA NEAT1, which spans both layers. A prevailing model of paraspeckle assembly proposes that core proteins bind directly and specifically to core-associated NEAT1 domains. Combining informatics and biochemistry, we unexpectedly find that the essential core proteins FUS and NONO bind and condense preferentially with shell-associated NEAT1 domains. The shell protein TDP-43 exhibits similar NEAT1 domain preferences on its own but forms surfactant-like shell layers around core protein-driven condensates when both are present. Together, experiments and physics-based simulations suggest that competitive RNA binding and immiscibility between core and shell proteins order paraspeckle layers. More generally, we propose that subcondensate organization can spontaneously arise from a balance of collaborative and competitive protein binding to the same domains of a lncRNA.

The speed dynamics of different sprint and acceleration exercises applied during football training

The E3 ligase HECTD4 regulates COX-2-dependent tumor progression and metastasis

E3 ubiquitin ligases mediating turnover of proteins engaged in cancer progression point to key regulatory nodes. To uncover modifiers of metastatic competency, we conducted an in vivo genome-wide CRISPR-inactivation screen using cultured breast circulating tumor cells, following intravascular seeding and lung colonization. We identified HECTD4, a previously uncharacterized gene encoding a conserved potential homologous to E6AP C-terminus domain–containing ubiquitin transferase, as a potent tumor and metastasis suppressor. We show that purified HECTD4 mediates ubiquitin conjugation in vitro, and proteomic studies combined with ubiquitin remnant profiling identify a major degradation target as the prostaglandin synthetic enzyme cyclooxygenase-2 ( COX-2 ; PTGS2 ). In addition to COX-2 itself, HECTD4 targets its regulatory kinase MKK7. In breast cancer models, HECTD4 expression is induced as cells lose adherence to the matrix, and its depletion massively increases COX-2 expression, enhancing anchorage-independent proliferation and tumorigenesis. Genetic or pharmacologic suppression of COX-2 reverses the protumorigenic and prometastatic phenotype of HECTD4-depleted cells. Thus, HECTD4 encodes an E3 ubiquitin ligase that downregulates COX-2 suppressing anchorage independence in epithelial cancer cells.

Concept learning based on improved FCM- BiLSTM for fuzzy data classification and fusion

Lattice materials with topological states optimized on demand

Topological states of matter, first discovered in quantum systems, have opened new avenues for wave manipulation beyond the quantum realm. In elastic media, realizing these topological effects requires identifying lattices that support the corresponding topological bands. However, among the vast number of theoretically predicted topological states, only a small fraction has been physically realized. To close this gap, we present a strategy capable of systematically and efficiently discovering metamaterials with desired topological state. Our approach builds on topological quantum chemistry, which systematically classifies topological states by analyzing symmetry properties at selected wavevectors. Because this method condenses the topological character into mathematical information at a small set of wavevectors, it encodes a clear and computationally efficient objective for topology optimization algorithms. We demonstrate that, for certain lattice symmetries, this classification can be further reduced to intuitive morphological features of the phonon band structure. By incorporating these band morphology constraints into topology optimization algorithms and further fabricating obtained designs, we enable the automated discovery and physical realization of metamaterials with targeted topological properties. This methodology establishes a paradigm for engineering topological elastic lattices on demand, addressing the bottleneck in material realization and paving the way for a comprehensive database of topological metamaterial configurations.

Single-cell and bulk transcriptome profiling reveals RNA-binding protein regulatory programs in cervical cancer

Detecting chirality-induced spin selectivity in chromophore-linked DNA hairpins using photogenerated radical pairs

Chirality-induced spin selectivity (CISS) results in spin polarization of electrons transmitted through chiral molecules and materials. Since CISS results in spin polarization even at room temperature, it affords the possibility of using it to develop quantum technologies that can operate under ambient conditions. We have shown previously that photo-driven hole transfer within DNA hairpins provides a facile route to generate spin-correlated radical pairs (SCRPs). To study the effect of CISS on the spin dynamics of SCRPs in DNA hairpins, we prepared a series of electron donor—chiral bridge—acceptor molecules where the chiral bridge is a B-form DNA helix consisting of 4 to 6 base pairs. Naphthalene-1,8:4,5-bis(dicarboximide) (NDI) serves as the hairpin linker chromophore and electron acceptor. Photoexcitation of NDI results in rapid hole transfer through the π-stacked purine bases of the DNA and trapping of the hole on a terminal stilbene diether (Sd) to generate the NDI •− - Sd •+ SCRP. Time-resolved electron paramagnetic resonance spectra of the SCRPs at X- (9.6 GHz), Q- (34 GHz), and W- (94 GHz) bands show that the CISS effect imparts significant triplet character to the SCRP. We do not observe a significant dependence of CISS on DNA length, likely resulting from hole delocalization over the guanine bases in the G-tract. Interestingly, we find that the CISS contribution significantly increases with magnetic field strength. These findings should be considered in any future modeling of CISS.

Chidamide and anlotinib synergistically inhibit high grade B-cell lymphomas via PI3K/AKT signaling pathway

Endocannabinoids inhibit contextual fear memory generalization via hippocampal GABAergic synaptic transmission

Memory generalization allows an organism to adapt to new conditions, but overgeneralization of fear or traumatic experiences can be detrimental to survival and contributes to the development of various mental disorders. However, the cellular and molecular mechanisms underlying fear memory generalization, especially in the hippocampus, remain largely unknown. In this study, utilizing a well-established mouse model of fear memory generalization, we investigated the role of endocannabinoids (eCBs)-mediated GABAergic synaptic inputs to hippocampal pyramidal neurons in regulating contextual fear memory generalization. Our results revealed that pharmacological or genetic blockade of CB1R in hippocampal CA1 resulted in overgeneralization of contextual fear memory but not fear memory expression. Subsequent investigations in conditional knockout mice revealed the involvement of CB1R in GABAergic neurons, but not those in glutamatergic neurons or astrocytes, in this overgeneralization. In addition, activation of GABA A receptors on pyramidal neurons was required for inducing overgeneralization via AM281, a CB1R antagonist. Neural mechanistic studies showed that eCBs/CB1R signaling regulates both the activity and plasticity of inhibitory synapses during generalization, highlighting the prominence of the disinhibition of CB1R in interneurons during this process. Subsequently, we delved into the downstream effects and found that eCB-dependent long-term potentiation (LTP) in CA1 pyramidal neurons was regulated by the aforementioned mechanisms. Our findings illustrate that the eCBs/CB1R signaling pathway modulates the balance between fear memory discrimination and generalization by controlling inhibitory inputs to hippocampal pyramidal neurons, accompanied by alterations in excitatory plasticity within this region.

Sex estimation using humerus volume in a Korean population with varying bone preservation

Structural insights into a citrate transporter that mediates aluminum tolerance in barley

HvAACT1 is a major aluminum (Al)-tolerance gene in barley, encoding a citrate transporter that belongs to the multidrug and toxic compound extrusion (MATE) family. This transporter facilitates citrate secretion from the roots, thereby detoxifying external Al ions—a major constraint of crop production on acidic soils. In this study, we present the outward-facing crystal structure of HvAACT1, providing insights into a citrate transport mechanism. The putative citrate binding site consists of three basic residues—K126 in transmembrane helix 2 (TM2), R358 in TM7, and R535 in TM12—creating substantial positive charges in the C-lobe cavity. Proton coupling for substrate transport may involve two pairs of aspartate residues in the N-lobe cavity, one of which corresponds to the essential Asp pair found in prokaryotic H + -coupled MATE transporters belonging to the DinF subfamily. Structural coupling between proton uptake in the N-lobe and citrate extrusion in the C-lobe can be enabled by an extensive, unique hydrogen-bonding network at the extracellular half of the N-lobe. Mutation-based functional analysis, structural comparisons, molecular dynamics simulation, and phylogenic analysis suggest an evolutionary link between citrate MATE transporters and the DinF MATE subfamily. Our findings provide a solid structural basis for citrate transport by HvAACT1 in barley and contribute to a broader understanding of citrate transporter structures in other plant species.

Quaternized chitosan derivatives inhibit growth and affect biofilm formation of Staphylococcus aureus

Cancer cells suppress NK cell activity by actin-driven polarization of inhibitory ligands to the immunological synapse

Natural killer (NK) cells engage target cells via the immunological synapse (IS), where inhibitory and activating signals determine whether NK cell cytotoxicity is suppressed or activated. We previously reported that cancer cells can rapidly remodel their actin cytoskeleton upon NK cell engagement, leading to F-actin accumulation at the synapse. Here, we show that this process inhibits NK cell activation as indicated by impaired MTOC and lytic granule polarization. Exploring the underlying mechanism, we demonstrate that actin remodeling drives the recruitment of inhibitory ligands, such as HLA-A, -B, and -C, to the synapse. Disrupting HLA interaction with their cognate inhibitory receptors KIRs restores NK cell activation. Using NK cells expressing inhibitory KIR receptors, matched or unmatched to HLA molecules on cancer cells, we show that synaptic F-actin accumulation and matching KIR–HLA interactions jointly suppress NK cell cytotoxicity. Our findings reveal an immune evasion strategy in which cancer cells impair NK cell activation by altering synaptic signaling through actin cytoskeleton–driven recruitment of inhibitory signals to the IS.

Dehydrotanshinone II A alleviates osteoarthritis via activating PPARγ to inhibit ferroptosis in chondrocytes

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

Effectiveness of cooling strategies for emergency personnel: a systematic review and meta-analysis

Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming

The famous model organism Saccharomyces cerevisiae is widely present in a variety of natural and human-associated habitats. Despite extensive studies of this organism, the metabolic mechanisms driving its adaptation to varying niches remain elusive. We here gathered genomic resources from 1,807 S. cerevisiae strains and assembled them into a high-quality pangenome, facilitating the comprehensive characterization of genetic diversity across isolates. Utilizing the pangenome, 1,807 strain-specific genome-scale metabolic models (ssGEMs) were generated, which performed well in quantitative predictions of cellular phenotypes, thus helping to examine the metabolic disparities among all S. cerevisiae strains. Integrative analyses of fluxomics and transcriptomics with ssGEMs showcased ubiquitous transcriptional regulation of metabolic flux in specific pathways (i.e., amino acid synthesis) at a population level. Additionally, the gene/reaction inactivation analysis through the ssGEMs refined by transcriptomics showed that S. cerevisiae strains from various ecological niches had undergone reductive evolution at both the genomic and metabolic network levels when compared to wild isolates. Finally, the compiled analysis of the pangenome, transcriptome, and metabolic fluxome revealed remarkable metabolic differences among S. cerevisiae strains originating from distinct oxygen-limited niches, including human gut and cheese environments, and identified convergent metabolic evolution, such as downregulation of oxidative phosphorylation pathways. Together, these results illustrate how yeast adapts to distinct niches modulated by genomic and metabolic reprogramming, and provide computational resources for translating yeast genotype to fitness in future studies.

REST/NRSF Preserves muscle stem cell identity by repressing alternate cell fate

Network analysis of the food-energy-water nexus in the Gulf of Mexico (America) region

The radiation and geographic expansion of primates through diverse climates

One of the most influential hypotheses about primate evolution postulates that their origin, radiation, and major dispersals were associated with exceptionally warm conditions in tropical forests at northern latitudes (henceforth the warm tropical forest hypothesis ). However, this notion has proven difficult to test given the overall uncertainty about both geographic locations and paleoclimates of ancestral species. By the resolution of both challenges, we reveal that early primates dispersed and radiated in higher latitudes, through diverse climates, including cold, arid, and temperate conditions. Contrary to expectations of the warm tropical forest hypothesis, warmer global temperatures had no effect on dispersal distances or the speciation rate. Rather, the amount of change in local temperature and precipitation substantially predicted geographic and species diversity. Our results suggest that nontropical, changeable environments exerted strong selective pressures on primates with higher dispersal ability – promoting the primate radiation and their subsequent colonization of tropical climates millions of years after their origin.