Comprehensive structure and functional adaptations of the yeast nuclear pore complex.

Nuclear pore complexes (NPCs) mediate the nucleocytoplasmic transport of macromolecules. Here we provide a structure of the isolated yeast NPC in which the inner ring is resolved by cryo-EM at sub-nanometer resolution to show how flexible connectors tie together different structural and functional layers. These connectors may be targets for phosphorylation and regulated disassembly in cells with an open mitosis. Moreover, some nucleoporin pairs and transport factors have similar interaction motifs, which suggests an evolutionary and mechanistic link between assembly and transport. We provide evidence for three major NPC variants that may foreshadow functional specializations at the nuclear periphery. Cryo-electron tomography extended these studies, providing a model of the in situ NPC with a radially expanded inner ring. Our comprehensive model reveals features of the nuclear basket and central transporter, suggests a role for the lumenal Pom152 ring in restricting dilation, and highlights structural plasticity that may be required for transport.

PD-L1 engagement on T cells promotes self-tolerance and suppression of neighboring macrophages and effector T cells in cancer.

Programmed cell death protein 1 (PD-1) ligation delimits immunogenic responses in T cells. However, the consequences of programmed cell death 1 ligand 1 (PD-L1) ligation in T cells are uncertain. We found that T cell expression of PD-L1 in cancer was regulated by tumor antigen and sterile inflammatory cues. PD-L1+ T cells exerted tumor-promoting tolerance via three distinct mechanisms: (1) binding of PD-L1 induced STAT3-dependent 'back-signaling' in CD4+ T cells, which prevented activation, reduced TH1-polarization and directed TH17-differentiation. PD-L1 signaling also induced an anergic T-bet-IFN-γ- phenotype in CD8+ T cells and was equally suppressive compared to PD-1 signaling; (2) PD-L1+ T cells restrained effector T cells via the canonical PD-L1-PD-1 axis and were sufficient to accelerate tumorigenesis, even in the absence of endogenous PD-L1; (3) PD-L1+ T cells engaged PD-1+ macrophages, inducing an alternative M2-like program, which had crippling effects on adaptive antitumor immunity. Collectively, we demonstrate that PD-L1+ T cells have diverse tolerogenic effects on tumor immunity.

Structure and Function of the Nuclear Pore Complex Cytoplasmic mRNA Export Platform.

The last steps in mRNA export and remodeling are performed by the Nup82 complex, a large conserved assembly at the cytoplasmic face of the nuclear pore complex (NPC). By integrating diverse structural data, we have determined the molecular architecture of the native Nup82 complex at subnanometer precision. The complex consists of two compositionally identical multiprotein subunits that adopt different configurations. The Nup82 complex fits into the NPC through the outer ring Nup84 complex. Our map shows that this entire 14-MDa Nup82-Nup84 complex assembly positions the cytoplasmic mRNA export factor docking sites and messenger ribonucleoprotein (mRNP) remodeling machinery right over the NPC's central channel rather than on distal cytoplasmic filaments, as previously supposed. We suggest that this configuration efficiently captures and remodels exporting mRNP particles immediately upon reaching the cytoplasmic side of the NPC.

Implications of a multiscale structure of the yeast nuclear pore complex.

Nuclear pore complexes (NPCs) direct the nucleocytoplasmic transport of macromolecules. Here, we provide a composite multiscale structure of the yeast NPC, based on improved 3D density maps from cryogenic electron microscopy and AlphaFold2 models. Key features of the inner and outer rings were integrated into a comprehensive model. We resolved flexible connectors that tie together the core scaffold, along with equatorial transmembrane complexes and a lumenal ring that anchor this channel within the pore membrane. The organization of the nuclear double outer ring reveals an architecture that may be shared with ancestral NPCs. Additional connections between the core scaffold and the central transporter suggest that under certain conditions, a degree of local organization is present at the periphery of the transport machinery. These connectors may couple conformational changes in the scaffold to the central transporter to modulate transport. Collectively, this analysis provides insights into assembly, transport, and NPC evolution.

Collective motion in hcp-Fe at Earth's inner core conditions.

Earth's inner core is predominantly composed of solid iron (Fe) and displays intriguing properties such as strong shear softening and an ultrahigh Poisson's ratio. Insofar, physical mechanisms to explain these features coherently remain highly debated. Here, we have studied longitudinal and shear wave velocities of hcp-Fe (hexagonal close-packed iron) at relevant pressure-temperature conditions of the inner core using in situ shock experiments and machine learning molecular dynamics (MLMD) simulations. Our results demonstrate that the shear wave velocity of hcp-Fe along the Hugoniot in the premelting condition, defined as T/Tm (Tm: melting temperature of iron) above 0.96, is significantly reduced by ~30%, while Poisson's ratio jumps to approximately 0.44. MLMD simulations at 230 to 330 GPa indicate that collective motion with fast diffusive atomic migration occurs in premelting hcp-Fe primarily along [100] or [010] crystallographic direction, contributing to its elastic softening and enhanced Poisson's ratio. Our study reveals that hcp-Fe atoms can diffusively migrate to neighboring positions, forming open-loop and close-loop clusters in the inner core conditions. Hcp-Fe with collective motion at the inner core conditions is thus not an ideal solid previously believed. The premelting hcp-Fe with collective motion behaves like an extremely soft solid with an ultralow shear modulus and an ultrahigh Poisson's ratio that are consistent with seismic observations of the region. Our findings indicate that premelting hcp-Fe with fast diffusive motion represents the underlying physical mechanism to help explain the unique seismic and geodynamic features of the inner core.

FANCD2 deficiency sensitizes SHH medulloblastoma to radiotherapy via ferroptosis.

Radiotherapy is one of the standard therapeutic regimens for medulloblastoma (MB). Tumor cells utilize DNA damage repair (DDR) mechanisms to survive and develop resistance during radiotherapy. It has been found that targeting DDR sensitizes tumor cells to radiotherapy in several types of cancer, but whether and how DDR pathways are involved in the MB radiotherapy response remain to be determined. Single-cell RNA sequencing was carried out on 38 MB tissues, followed by expression enrichment assays. Fanconi anemia group D2 gene (FANCD2) expression was evaluated in MB samples and public MB databases. The function of FANCD2 in MB cells was examined using cell counting assays (CCK-8), clone formation, lactate dehydrogenase activity, and in mouse orthotopic models. The FANCD2-related signaling pathway was investigated using assays of peroxidation, a malondialdehyde assay, a reduced glutathione assay, and using FerroOrange to assess intracellular iron ions (Fe2+ ). Here, we report that FANCD2 was highly expressed in the malignant sonic hedgehog (SHH) MB subtype (SHH-MB). FANCD2 played an oncogenic role and predicted worse prognosis in SHH-MB patients. Moreover, FANCD2 knockdown markedly suppressed viability, mobility, and growth of SHH-MB cells and sensitized SHH-MB cells to irradiation. Mechanistically, FANCD2 deficiency led to an accumulation of Fe2+ due to increased divalent metal transporter 1 expression and impaired glutathione peroxidase 4 activity, which further activated ferroptosis and reduced proliferation of SHH-MB cells. Using an orthotopic mouse model, we observed that radiotherapy combined with silencing FANCD2 significantly inhibited the growth of SHH-MB cell-derived tumors in vivo. Our study revealed FANCD2 as a potential therapeutic target in SHH-MB and silencing FANCD2 could sensitize SHH-MB cells to radiotherapy via inducing ferroptosis. © 2024 The Pathological Society of Great Britain and Ireland.

Intracellular infection by symbiotic bacteria requires the mitotic kinase AURORA1.

The subcellular events occurring in cells of legume plants as they form transcellular symbiotic-infection structures have been compared with those occurring in premitotic cells. Here, we demonstrate that Aurora kinase 1 (AUR1), a highly conserved mitotic regulator, is required for intracellular infection by rhizobia in Medicago truncatula. AUR1 interacts with microtubule-associated proteins of the TPXL and MAP65 families, which, respectively, activate and are phosphorylated by AUR1, and localizes with them within preinfection structures. MYB3R1, a rhizobia-induced mitotic transcription factor, directly regulates AUR1 through two closely spaced, mitosis-specific activator cis elements. Our data are consistent with a model in which the MYB3R1-AUR1 regulatory module serves to properly orient preinfection structures to direct the transcellular deposition of cell wall material for the growing infection thread, analogous to its role in cell plate formation. Our findings indicate that the eukaryotically conserved MYB3R1-TPXL-AUR1-MAP65 mitotic module was conscripted to support endosymbiotic infection in legumes.

Biomimetic Design of a Dynamic M-O-V Pyramid Electron Bridge for Enhanced Nitrogen Electroreduction.

Electrochemical nitrogen reduction reaction (eNRR) offers a sustainable route for ammonia synthesis; however, current electrocatalysts are limited in achieving optimal performance within narrow potential windows. Herein, inspired by the heliotropism of sunflowers, we present a biomimetic design of Ru-VOH electrocatalyst, featuring a dynamic Ru-O-V pyramid electron bridge for eNRR within a wide potential range. In situ spectroscopy and theoretical investigations unravel the fact that the electrons are donated from Ru to V at lower overpotentials and retrieved at higher overpotentials, maintaining a delicate balance between N2 activation and proton hydrogenation. Moreover, N2 adsorption and activation were found to be enhanced by the Ru-O-V moiety. The catalyst showcases an outstanding Faradaic efficiency of 51.48% at -0.2 V (vs RHE) with an NH3 yield rate exceeding 115 µg h-1 mg-1 across the range of -0.2 to -0.4 V (vs RHE), along with impressive durability of over 100 cycles. This dynamic M-O-V pyramid electron bridge is also applicable to other metals (M = Pt, Rh, and Pd).

Centrosymmetry-Breaking Morphotropic Phase Boundary: A Pathway to Highly Sensitive and Strong Pressure-Responsive Nonlinear Optical Switches.

The quest for high-performance piezoelectric materials has been synonymous with the pursuit of the morphotropic phase boundary (MPB), yet the full potential of MPBs remains largely untapped outside of the realm of ferroelectrics. In this study, we reveal a new class of MPB by creating continuous molecular-based solid solutions between centro- and noncentrosymmetric compounds, exemplified by (tert-butylammonium)1-x(tert-amylammonium)xFeCl4 (0 ≤ x ≤ 1), where the MPB is formed due to disorder of molecular cations. Near the MPB, we discovered an exceptionally sensitive nonlinear optical material in the centrosymmetric phase, capable of activation at pressures as low as 0.12-0.27 GPa, and producing tunable second-harmonic generation (SHG) signals from zero to 18.8 times that of KH2PO4 (KDP). Meanwhile, synchrotron diffraction experiments have unveiled a third competing phase (P212121) appearing at low pressure, forming a triple-phase point near the MPB, thereby providing insight into the mechanism underpinning the nonlinear optical (NLO) switch behavior. These findings highlight the opportunity to harness exceptional physical properties in symmetry-breaking solid solution systems by strategically designing novel MPBs.

Comparative Venom Multiomics Reveal the Molecular Mechanisms Driving Adaptation to Diverse Predator-Prey Ecosystems in Closely Related Sea Snakes.

Predator-prey arms races are ideal models for studying the natural selection and adaptive evolution that drive the formation of biological diversity. For venomous snakes, venom is a key bridge linking snakes with their prey, but whether and how venom evolves under the selection of diet remains unclear. Here, we focused on two closely related sea snakes, Hydrophis cyanocinctus and Hydrophis curtus, which show significant differences in prey preferences. Data-independent acquisition (DIA)-based proteomic analysis revealed different degrees of homogeneity in the venom composition of the two snakes, which was consistent with the differential phylogenetic diversity of their prey. By investigating the sequences and structures of three-finger toxins (3FTx), a predominant toxin family in elapid venom, we identified significant differences between the two sea snakes in the binding activity of 3FTx to receptors from different prey populations, which could explain the trophic specialization of H. cyanocinctus. Furthermore, we performed integrated multiomic profiling of the transcriptomes, microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and proteomes of the venom glands; constructed venom-related mRNA-miRNA-lncRNA networks; and identified a series of noncoding RNAs involved in the regulation of toxin gene expression in the two species. These findings are highly informative for elucidating the molecular basis and regulatory mechanisms that account for discrepant venom evolution in response to divergent diets in closely related snakes, providing valuable evidence for the study of coselection and coevolution in predator-prey ecosystems.

Fluorinated 1,7-DO2A-Based Iron(II) Complexes as Sensitive 19F MRI Molecular Probes for Visualizing Renal Dysfunction in Living Mice.

Kidney diseases have become an important global health concern due to their high incidence, inefficient diagnosis, and poor prognosis. Devising direct methods, especially imaging means, to assess renal function is the key for better understanding the mechanisms of various kidney diseases and subsequent development of effective treatment. Herein, we developed a fluorinated ferrous chelate-based sensitive probe, 1,7-DO2A-Fe(II)-F18 (Probe 1), for 19F magnetic resonance imaging (MRI). This highly fluorinated probe (containing 18 chemically equivalent 19F atoms with a fluorine content at 35 wt %) achieves a 15-time enhancement in signal intensity compared with the fluorine-containing ligand alone due to the appropriately regulated 19F relaxation times by the ferrous ion, which significantly increases imaging sensitivity and reduces acquisition time. Owing to its high aqueous solubility, biostability, and biocompatibility, this probe could be rapidly cleared by kidneys, which provides a means for monitoring renal dysfunction via 19F MRI. With this probe, we accomplish in vivo imaging of the impaired renal dysfunction caused by various kidney diseases including acute kidney injury, unilateral ureteral obstruction, and renal fibrosis at different stages. Our study illustrates the promising potential of Probe 1 for in vivo real-time visualization of kidney dysfunction, which is beneficial for the study, diagnosis, and even stratification of different kidney diseases. Furthermore, the design strategy of our probe is inspiring for the development of more high-performance 19F MRI probes for monitoring various biological processes.

Integrated phenotypic, transcriptomics and metabolomics: growth status and metabolite accumulation pattern of medicinal materials at different harvest periods of Astragalus Membranaceus Mongholicus.

BACKGROUND: Astragalus membranaceus var. mongholicus (Astragalus), acknowledged as a pivotal "One Root of Medicine and Food", boasts dual applications in both culinary and medicinal domains. The growth and metabolite accumulation of medicinal roots during the harvest period is intricately regulated by a transcriptional regulatory network. One key challenge is to accurately pinpoint the harvest date during the transition from conventional yield content of medicinal materials to high and to identify the core regulators governing such a critical transition. To solve this problem, we performed a correlation analysis of phenotypic, transcriptome, and metabolome dynamics during the harvesting of Astragalus roots. RESULTS: First, our analysis identified stage-specific expression patterns for a significant proportion of the Astragalus root genes and unraveled the chronology of events that happen at the early and later stages of root harvest. Then, the results showed that different root developmental stages can be depicted by co-expressed genes of Astragalus. Moreover, we identified the key components and transcriptional regulation processes that determine root development during harvest. Furthermore, through correlating phenotypes, transcriptomes, and metabolomes at different harvesting periods, period D (Nov.6) was identified as the critical period of yield and flavonoid content increase, which is consistent with morphological and metabolic changes. In particular, we identified a flavonoid biosynthesis metabolite, isoliquiritigenin, as a core regulator of the synthesis of associated secondary metabolites in Astragalus. Further analyses and experiments showed that HMGCR, 4CL, CHS, and SQLE, along with its associated differentially expressed genes, induced conversion of metabolism processes, including the biosynthesis of isoflavones and triterpenoid saponins substances, thus leading to the transition to higher medicinal materials yield and active ingredient content. CONCLUSIONS: The findings of this work will clarify the differences in the biosynthetic mechanism of astragaloside IV and calycosin 7-O-ß-D-glucopyranoside accumulation between the four harvesting periods, which will guide the harvesting and production of Astragalus.

N-Doping Effects On Electrocatalytic Water Splitting of Non-Noble High-Entropy Alloy Nanoparticles Prepared by Inert Gas Condensation.

The unique catalytic activities of high-entropy alloys (HEAs) emerge from the complex interaction among different elements in a single-phase solid solution. As a "green" nanofabrication technique, inert gas condensation (IGC) combined with laser source opens up a highly efficient avenue to develop HEA nanoparticles (NPs) for catalysis and energy storage. In this work, the novel N-doped non-noble HEA NPs are designed and successfully prepared by IGC. The N-doping effects of HEA NPs on oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) are systematically investigated. The results show that N-doping is conducive to improving the OER, but unfavorable for HER activity. The FeCoNiCrN NPs achieve an overpotential of 269.7 mV for OER at a current density of 10 mA cm-2 in 1.0 M KOH solution, which is among the best reported values for non-noble HEA catalysts. The effects of the differences in electronegativity, ionization energy and electron affinity energy among mixed elements in N-doped HEAs are discussed as inducing electron transfer efficiency. Combined with X-ray photoelectron spectroscopy and the extended X-ray absorption fine structure analysis, an element-design strategy in N-doped HEAs electrocatalysts is proposed to improve the intrinsic activity and ameliorate water splitting performance.

Temperature and light reverse the fertility of rice P/TGMS line ostms19 via reactive oxygen species homeostasis.

P/TGMS (Photo/thermo-sensitive genic male sterile) lines are crucial resources for two-line hybrid rice breeding. Previous studies revealed that slow development is a general mechanism for sterility-fertility conversion of P/TGMS in Arabidopsis. However, the difference in P/TGMS genes between rice and Arabidopsis suggests the presence of a distinct P/TGMS mechanism in rice. In this study, we isolated a novel P/TGMS line, ostms19, which shows sterility under high-temperature conditions and fertility under low-temperature conditions. OsTMS19 encodes a novel pentatricopeptide repeat (PPR) protein essential for pollen formation, in which a point mutation GTA(Val) to GCA(Ala) leads to ostms19 P/TGMS phenotype. It is highly expressed in the tapetum and localized to mitochondria. Under high temperature or long-day photoperiod conditions, excessive ROS accumulation in ostms19 anthers during pollen mitosis disrupts gene expression and intine formation, causing male sterility. Conversely, under low temperature or short-day photoperiod conditions, ROS can be effectively scavenged in anthers, resulting in fertility restoration. This indicates that ROS homeostasis is critical for fertility conversion. This relationship between ROS homeostasis and fertility conversion has also been observed in other tested rice P/TGMS lines. Therefore, we propose that ROS homeostasis is a general mechanism for the sterility-fertility conversion of rice P/TGMS lines.

Learning representations for gene ontology terms by jointly encoding graph structure and textual node descriptors.

Measuring the semantic similarity between Gene Ontology (GO) terms is a fundamental step in numerous functional bioinformatics applications. To fully exploit the metadata of GO terms, word embedding-based methods have been proposed recently to map GO terms to low-dimensional feature vectors. However, these representation methods commonly overlook the key information hidden in the whole GO structure and the relationship between GO terms. In this paper, we propose a novel representation model for GO terms, named GT2Vec, which jointly considers the GO graph structure obtained by graph contrastive learning and the semantic description of GO terms based on BERT encoders. Our method is evaluated on a protein similarity task on a collection of benchmark datasets. The experimental results demonstrate the effectiveness of using a joint encoding graph structure and textual node descriptors to learn vector representations for GO terms.

DataDTA: a multi-feature and dual-interaction aggregation framework for drug-target binding affinity prediction.

MOTIVATION: Accurate prediction of drug-target binding affinity (DTA) is crucial for drug discovery. The increase in the publication of large-scale DTA datasets enables the development of various computational methods for DTA prediction. Numerous deep learning-based methods have been proposed to predict affinities, some of which only utilize original sequence information or complex structures, but the effective combination of various information and protein-binding pockets have not been fully mined. Therefore, a new method that integrates available key information is urgently needed to predict DTA and accelerate the drug discovery process. RESULTS: In this study, we propose a novel deep learning-based predictor termed DataDTA to estimate the affinities of drug-target pairs. DataDTA utilizes descriptors of predicted pockets and sequences of proteins, as well as low-dimensional molecular features and SMILES strings of compounds as inputs. Specifically, the pockets were predicted from the three-dimensional structure of proteins and their descriptors were extracted as the partial input features for DTA prediction. The molecular representation of compounds based on algebraic graph features was collected to supplement the input information of targets. Furthermore, to ensure effective learning of multiscale interaction features, a dual-interaction aggregation neural network strategy was developed. DataDTA was compared with state-of-the-art methods on different datasets, and the results showed that DataDTA is a reliable prediction tool for affinities estimation. Specifically, the concordance index (CI) of DataDTA is 0.806 and the Pearson correlation coefficient (R) value is 0.814 on the test dataset, which is higher than other methods. AVAILABILITY AND IMPLEMENTATION: The codes and datasets of DataDTA are available at https://github.com/YanZhu06/DataDTA.

Phased genome assemblies reveal haplotype-specific genetic load in the critically endangered Chinese Bahaba (Teleostei, Sciaenidae).

While haplotype-specific genetic load shapes the evolutionary trajectory of natural and captive populations, mixed-haplotype assembly and genotyping hindered its characterization in diploids. Herein, we produced two phased genome assemblies of the critically endangered fish Chinese Bahaba (Bahaba taipingensis, Sciaenidae, Teleostei) and resequenced 20 whole genomes to quantify population genetic load at a haplotype level. We identified frame-shifting variants as the most deleterious type, followed by mutations in the 5'-UTR, 3'-UTR and missense mutations at conserved amino acids. Phased haplotypes revealed gene deletions and high-impact deleterious variants. We estimated ~1.12% of genes missing or interrupted per haplotype, with a significant overlap of disrupted genes (30.35%) between haplotype sets. Relative proportions of deleterious variant categories differed significantly between haplotypes. Simulations suggested that purifying selection struggled to purge slightly deleterious genetic load in captive breeding compared to genotyping interventions, and that higher inter-haplotypic variance of genetic load predicted more efficient purging by artificial selection. Combining the knowledge of haplotype-resolved genetic load with predictive modelling will be immensely useful for understanding the evolution of deleterious variants and guiding conservation planning.

Why thermal images are blurry.

The resolution of optical imaging is limited by diffraction as well as detector noise. However, thermal imaging exhibits an additional unique phenomenon of ghosting which results in blurry and low-texture images. Here, we provide a detailed view of thermal physics-driven texture and explain why it vanishes in thermal images capturing heat radiation. We show that spectral resolution in thermal imagery can help recover this texture, and we provide algorithms to recover texture close to the ground truth. We develop a simulator for complex 3D scenes and discuss the interplay of geometric textures and non-uniform temperatures which is common in real-world thermal imaging. We demonstrate the failure of traditional thermal imaging to recover ground truth in multiple scenarios while our thermal perception approach successfully recovers geometric textures. Finally, we put forth an experimentally feasible infrared Bayer-filter approach to achieve thermal perception in pitch darkness as vivid as optical imagery in broad daylight.

MEMS-based two-photon microscopy with Lissajous scanning and image reconstruction under a feed-forward control strategy.

Two-photon microscopy (TPM) based on two-dimensional micro-electro-mechanical (MEMS) system mirrors shows promising applications in biomedicine and the life sciences. To improve the imaging quality and real-time performance of TPM, this paper proposes Lissajous scanning control and image reconstruction under a feed-forward control strategy, a dual-parameter alternating drive control algorithm and segmented phase synchronization mechanism, and pipe-lined fusion-mean filtering and median filtering to suppress image noise. A 10 fps frame rate (512 × 512 pixels), a 140 µm × 140 µm field of view, and a 0.62 µm lateral resolution were achieved. The imaging capability of MEMS-based Lissajous scanning TPM was verified by ex vivo and in vivo biological tissue imaging.

The transcription factor OsSPL9 endows rice with copper deficiency resilience.

Copper (Cu) is a crucial micronutrient essential for the growth and development of plants. Rice exhibits remarkable resistance to Cu deficiency, but the underlying molecular mechanisms are not well understood. In this study, we reveal that the plant's ability to withstand Cu deficiency is orchestrated by a transcription factor known as OsSPL9. We have demonstrated that OsSPL9 functions as a central regulator of Cu homeostasis. Disrupting OsSPL9 through knockout significantly reduces the plant's tolerance to Cu deficiency. As a result, the spl9 mutants exhibit reduced Cu accumulation in their shoots when compared to wild-type plants. This reduction is linked to a disruption in the transport of Cu from older leaves to younger ones. Furthermore, we show that OsSPL9 directly binds to GTAC motifs in the promoters of key genes involved in Cu uptake and transport, as well as Cu-miRNAs, and enhances their transcription under Cu-deficient conditions. Overall, our findings shed light on the molecular basis of rice resilience to Cu deficiency stress and place the transcription factor OsSPL9 as a master regulator of this response.