Biology subjects

Liu, Z.

Publications and source records attributed to Liu, Z..

At least 325 records · Page 18Linked to original sources

bioRxiv2025

Two telomere-to-telomere, gap-free genome assemblies and comparisons revealed the conserved key genes associated with sugar accumulation in Rubus genus

For the first time, we assembled two highly continuous, completely gap-free reference genomes of the Rubus subgenus: Rubus hirsutus Thunb. Penglei (XMM) and Rubus eustephanos Focke ex Diels Dahongpao (DHP), which are widely distributed in southern China with similar phenotypic traits (Figures 1A, 1B, and Figure S1), yet ripe fruits display distinct sugar accumulation levels (Table S1), making them ideal candidates for investigating the mechanisms underlying sugar accumulation in the Rubus genus. The XMM (213.53 Mb, 28,204 genes) and DHP (218.26 Mb, 28,569 genes) genomes exhibit close evolutionary relationships, diverging approximately 3.21 Mya. Comparative genomics identified extensive synteny, interspecific structural variations (translocations, inversions, segmental duplications), and presence/absence variation (PAV). Using Hi-C interaction heatmaps and Sanger sequencing, we validated interspecific structural inversions. Additionally, we identified a sugar transporter gene (MFS1), which is present in XMM but absent in DHP. Combined analysis of the gene family expansion/contraction and transcriptome identified two conserved key genes (RhSTP13 and RhSTP7) associated with sugar accumulation in Rubus genus and displayed distinct roles through transient expression assay. To facilitate functional genomics study, we also established a comprehensive Rubus database, RubusDB, a freely accessible repository consolidating all genomic, transcriptomic and phenotypic data of Rubus genus. These findings provide a foundational framework for elucidating the genetic basis of sugar accumulation, genome diversification, and trait improvement in Rubus species. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/646780v2_fig1.gif" ALT="Figure 1"> View larger version (72K): org.highwire.dtl.DTLVardef@1baca20org.highwire.dtl.DTLVardef@2c01eaorg.highwire.dtl.DTLVardef@131dc00org.highwire.dtl.DTLVardef@62a04f_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFIGURE 1.C_FLOATNO Phenotypic characterization, de novo genome assemblies, variation, and evolution of Rubus hirsutus Thunb. Penglei (XMM) and Rubus eustephanos Focke ex Diels Dahongpao (DHP). (A) Illustration of XMM whole plants, stem, flower bud and flower, respectively. (B) Illustration of DHP whole plants, stem, flower bud and flower, respectively. (C) The chromosome karyotype analysis of XMM. Bar = 10 {micro}m. (D) Circular diagram of XMM and DHP reference genomes. (a) Chromosomes are represented by centromeres (dark red) and telomeres (blue); (b) CEN18 density; (c) CEN17 density; (d) Gene density; (e) TE density; (f) PAV density; (g) SNP density; (h) Collinear lines at the center of diagram highlight homoeologous chromosomes relationships and non-homoeologous regions. (E) Genomic alignments between XMM and DHP. Inversions, duplications and translocations are marked with orange, blue and green ribbons, respectively. (F) Identification of large inversions in chromosome 7 between XMM and DHP. The three heatmaps show the chromatin interaction matrix, including mapping Hi-C data of DHP against DHP genome (left), mapping Hi-C data of DHP against XMM genome (middle) and mapping Hi-C data of XMM against XMM genome (right). The lower panel illustrates gene alignments between XMM and DHP. (G) Synteny, structural rearrangements, monomer, and identity distribution in the 16-20 Mbp region of chromosome 6 between XMM and DHP. (H) Local genome synteny of chromosome 5, with a structural variation that is present only in XMM. The PAV region includes a gene related to sugar transporter (MFS1, XMM05G025540). (I) Gene-level matchings of MFS genes in the PAVs region between XMM and DHP. (J) Phylogenetic relationships and divergence times between raspberries and other Rosaceae species. The black numbers close to the divergence nodes indicate the divergence times and the red bars represent the 95% confidence intervals. The red and black numbers indicate expanded and contracted ortholog groups at the corresponding node. Scale bar corresponds to 10 Mya. C_FIG

genomics↗

bioRxiv2025

Regulation of airway fumarate by host and pathogen promotes S. aureus pneumonia

Staphylococcus aureus is a leading cause of healthcare-associated pneumonia, contributing significantly to morbidity and mortality worldwide. As a ubiquitous colonizer of the upper respiratory tract, S. aureus must undergo substantial metabolic adaptation to achieve persistent infection in the distinctive microenvironment of the lung. We observed that fumC, which encodes the enzyme that converts fumarate to malate, is highly conserved with low mutation rates in S. aureus isolates from chronic lung infections. Fumarate, a pro-inflammatory metabolite produced by macrophages during infection, is regulated by the host fumarate hydratase (FH) to limit inflammation. Here, we demonstrate that fumarate, which accumulates in the chronically infected lung, is detrimental to S. aureus, blocking primary metabolic pathways such as glycolysis and oxidative phosphorylation (OXPHOS). This creates a metabolic bottleneck that drives staphylococcal FH (FumC) activity for airway adaptation. FumC not only degrades fumarate but also directs its utilization into critical pathways including the tricarboxylic acid (TCA) cycle, gluconeogenesis and hexosamine synthesis to maintain metabolic fitness and form a protective biofilm. Itaconate, another abundant immunometabolite in the infected airway enhances FumC activity, in synergy with fumarate. In a mouse model of pneumonia, a {Delta}fumC mutant displays significant attenuation compared to its parent and complemented strains, particularly in fumarate- and itaconate-replete conditions. Our findings underscore the pivotal role of immunometabolites in promoting S. aureus pulmonary adaptation.

microbiology↗

bioRxiv2025

Repurposing without Reinventing the Wheel - Ensemble Models for Differential Analysis

Inspired by ensemble models in machine learning, we propose a general framework for aggregating multiple distinct base models to enhance the power of published differential association analysis (DAA) methods. We demonstrate this approach by augmenting popular DAA models with one or more biologically motivated alternatives. This creates an ensemble that bypasses the challenge of selecting an optimal model and instead combines the strengths of complementary statistical models to achieve superior performance. Our proposed ensemble learning approach is platform-agnostic and can augment any existing DAA method, providing a general and flexible framework for various downstream modeling tasks across domains and data types. We performed extensive benchmarking across both simulated and experimental datasets spanning single-cell gene expression, bulk transcriptomics, and microbiome metagenomics, where the ensemble strategy vastly outperformed non-ensemble methods, identified more differential patterns than the competing methods, and displayed good control of false positive and false discovery rates across diversified scenarios. In addition to highlighting a substantial performance boost for state-of-the-art DAA methods, this work has practical implications for mitigating the so-called reproducibility crisis in omics data science. An open-source R package implementing the ensemble strategy is publicly available at https://github.com/himelmallick/DAssemble.

bioinformatics↗

bioRxiv2025

Pathogenic potential prediction of Vibrio parahaemolyticus by using pangenome data with high performance machine learning algorithms

The presence of Vibrio parahaemolyticus (Vp) at various stages of seafood production has adversely affected public health and threatened the sustainability of the industry. To address the critical public health threats posed by this prevalent seafood-borne pathogen, this research applied advanced machine learning (ML) and deep learning (DL) algorithms to predict the pathogenic potential of Vp using pangenome data. Utilizing comprehensive pangenomic assemblies and sophisticated ML/DL models, this study achieved robust and precise pathogenic potential prediction of Vp based on source attribution, which provides a novel reliable diagnostic tool facilitating conventional serotyping and virulence gene combination approaches. Based on results, non-core regions in Vp pangenome exhibited useful signals ML models can utilize in pathogenic potential determination process. Tree-based ensemble learning methods (Random Forest and Gradient Boosting Trees) have shown the distinguished performance with AUC score 0.97 based on selected pangenome matrix. Furthermore, Convolutional Neural Network successfully predicted the pathogenic potential of isolates with slightly better performance with AUC score 0.98 based on full pangenome. Critical biological insights revealing critical pathogenic potential-associated genes were retrieved from established ML/DL models: the gene feature weight analysis from Random Forest revealed the importance of accessory genes during Vp evolution (similarly highlighted by Gram-cam analysis of Convolutional Neural Network), which provided potential guidance for future research direction.

microbiology↗

bioRxiv2025

Cytokine-driven cellular polarization in preeclampsia revealed through the "Dictionary of immune responses"

BackgroundPreeclampsia (PE) is a pregnancy-related hypertensive disorder and a leading cause of maternal and perinatal mortality. Current treatments focus primarily on symptom management, as delivery remains the only definitive cure. This underscores the urgent need for innovative therapeutic strategies. Cytokines released by placental immune cells may contribute to the progression of PE and represent promising therapeutic targets. MethodsWe conducted single-cell sequencing on placental tissues obtained via cesarean section from patients with severe PE and cases of non-infectious preterm birth. Machine learning was applied to identify critical immune cells. Immune Response Enrichment Analysis was performed on these key cells to evaluate their polarization states and cytokine responses associated with PE. Additionally, we investigated cell-cell communications, key genes, and their related functions ResultsWe identified cell type-specific alterations in PE, including an increased proportion of CD4+ T cells polarized towards an IL-1- and IL-1{beta} enriched T4-c state. Altered SPP1 signaling between macrophages and CD4+ T cells was observed, indicating immune response dysregulation. Additionally, machine learning algorithms identified four hub genes, and six small-molecule drugs were predicted to hold therapeutic potential for PE. ConclusionsThis study emphasizes the importance of further understanding CD4+ T cell dynamics in preeclampsia, providing potential insights into the principles of placental immunity and contributing to the exploration of immunotherapeutic strategies

bioinformatics↗

bioRxiv2025

AT1R and Integrin β3 Synergize to Drive Aortic Dissection via Non-Canonical Wnt/β-Catenin Signaling

Aortic dissection (AD), a life-threatening cardiovascular emergency, continues to impose high mortality due to insufficient therapeutic options, as monotherapy targeting angiotensin II type 1 receptor (AT1R) demonstrates limited clinical efficacy. Utilizing single-cell RNA sequencing, we identified integrin {beta}3 as a critical driver of AD progression, with expression levels positively correlated with disease severity. Histopathological validation in human AD specimens and a murine angiotensin II (AngII)-infusion model confirmed marked upregulation of integrin {beta}3 activation. Pharmacological blockade of integrin {beta}3 with Cyclo(-RGDfK) significantly attenuated aortic pathogenesis in vivo, reducing dissection incidence and aortic degeneration. Mechanistically, AngII-mediated AT1R activation induced formation of a receptor complex with integrin {beta}3, triggering its conformational activation. Transcriptomic profiling revealed that activated integrin {beta}3 potentiates vascular endothelial dysfunction by binding glycogen synthase kinase 3{beta} (GSK3{beta}), which stabilizes {beta}-catenin via a non-canonical Wnt signaling axis. This pathway drives endothelial barrier disruption, hallmarks of aortic wall destabilization in AD. Our findings unveil a previously unrecognized synergy between AT1R and integrin {beta}3, implicating aberrant Wnt/{beta}-catenin signaling as a nexus of endothelial injury in AD pathogenesis. These results advocate for a paradigm-shifting dual-therapeutic strategy concurrently targeting AT1R and integrin {beta}3 to restore vascular homeostasis, offering a mechanistically grounded approach to mitigate this lethal disease. This work bridges critical gaps in understanding AD pathophysiology and provides a transformative framework for precision therapeutics.

pharmacology and toxicology↗

bioRxiv2025

Divalent cations govern the activity of coronavirus nsp15

Coronavirus nsp15 is an endoribonuclease that limits the accumulation of viral dsRNA in cytosol and plays a crucial role in the evasion of host immunity. Here, we show that Co2+ or Ni2+ potently activates nsp15 of human and animal coronaviruses, including SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-229E, MHV-A59, and PEDV. Whereas Zn2+ strongly inhibits nsp15 of these coronaviruses. Cryo-EM structures of the Co2+-bound SARS-CoV-2 nsp15/dsRNA complexes reveal that Co2+ binds to the nsp15 active site and is coordinated by three catalytic residues H234, H249, K289, and the 2 hydroxyl of the flipped base from dsRNA, suggesting that Co2+ stabilizes the catalytic core and increases substrate binding. Although our data indicated that Ni2+ and Zn2+ bind to the same site as Co2+, Zn2+ lacks the catalytic capability and inhibits nsp15. These findings reveal that divalent cations govern coronavirus nsp15s activity and provide basis for new therapeutic strategies.

molecular biology↗

bioRxiv2025

Hydrogen-Induced Calcium Influx via the TRPC4-TRPC4AP Axis

BackgroundCalcium ions (Ca{superscript 2}) serve as universal intracellular messengers regulating diverse physiological processes, while dysregulated Ca{superscript 2} homeostasis triggers cytotoxicity. Molecular hydrogen (H2) exhibits protective effects against oxidative stress-related pathologies, but its mechanism of action remains incompletely understood. Transient receptor potential canonical 4 (TRPC4) channels and their associated protein TRPC4AP are critical mediators of Ca{superscript 2} influx ( [Ca{superscript 2}]i), yet their role in H2-mediated calcium signaling is unexplored. This study investigates the molecular mechanism by which H2 modulates Ca{superscript 2} dynamics through the TRPC4-TRPC4AP axis, aiming to establish its therapeutic potential for calcium-related disorders. MethodsThe study employed heterogeneous cellular models (e.g., mesenchymal stem cells, neurons, fibroblasts) and in vivo two-photon calcium imaging in C57BL/6J mice. Techniques included CRISPR-Cas9 knockout, siRNA-mediated gene silencing, molecular docking (AlphaFold 3), and protein-protein interaction analysis. Calcium flux was quantified via fluorescence imaging, while mitochondrial integrity and cytoskeletal dynamics were assessed using JC-1 staining, ATPase activity assays, and live-cell imaging. Structural validation of TRPC4-TRPC4AP binding sites utilized mutagenesis and complementation experiments. ResultsH2 selectively enhanced extracellular Ca{superscript 2} influx via TRPC4-TRPC4AP, with no cytotoxicity or mitochondrial dysfunction observed. Key arginine residues (730Arg-731Arg) in the TRPC4 CIRB domain formed hydrogen-bond networks essential for channel activation. In vivo, H2 increased neuronal Ca{superscript 2} transient frequency and amplitude in the primary motor cortex. TRPC4AP knockout abolished H2-induced Ca{superscript 2} influx, while mutagenesis of 730Arg/731Arg disrupted channel activity. H2 also promoted cytoskeletal remodeling and cell motility, dependent on TRPC4AP-mediated Ca{superscript 2} signaling. ConclusionsThis study identifies H2 as a novel calcium agonist that activates the TRPC4-TRPC4AP axis to regulate extracellular Ca{superscript 2} influx. The 730Arg-731Arg motif in TRPC4 serves as a critical H2-sensitive site, enabling dynamic calcium homeostasis without overload. These findings provide a mechanistic basis for H2-based therapies targeting calcium dysregulation in neurodegenerative, inflammatory, and metabolic diseases, while highlighting TRPC4AP as a pivotal molecular switch for gasotransmitter signaling.

biochemistry↗

bioRxiv2025

clusIBD: Robust Detection of Identity-by-descent (IBD) Segments Using Unphased Genetic Data from Poor-quality DNA Samples

Inferring relatedness through the detection of identity-by-descent (IBD) segments is widely used in many fields. However, existing methods are often powerless for poor-quality DNA samples. Here, we propose a method, clusIBD, which can robustly detect IBD segments using unphased genetic data with high genotype errors. We evaluated and compared the performance of clusIBD with IBIS, TRUFFLE, and IBDseq using simulated data, artificial poor-quality materials and ancient DNA samples. The results showed that clusIBD outperformed these state-of-the-art existing tools and may be a promising tool for kinship inference in fields such as ancient DNA analysis and criminal investigation (freely available at https://github.com/Ryan620/clusIBD/).

genetics↗

bioRxiv2025

SMART: an approach for accurate formula assignment in spatially-resolved metabolomics

Spatially-resolved metabolomics plays a critical role in unraveling tissue-specific metabolic complexities. Despite its significance, this profound technology generates thousands of features, yet accurate annotation significantly lags behind LC-MS-based approaches. To bridge this gap, we introduce SMART, an open-source platform designed for precise formula assignment in mass spectrometry imaging. SMART constructs a KnownSet database containing 2.8 million formulas linked by DBEdges derived from repositories such as HMDB, ChEMBL, PubChem, and BioEdges from KEGG biological reactant pairs. Using a multiple linear regression model, SMART extracts formula networks associated with the m/z of interest and scores potential candidates based on several criteria, including linked formulas, DBEdges/BioEdges, and ppm values. Benchmarking against reference datasets demonstrates that SMART achieves prediction accuracy rates of up to 92.4%. Applied to mass spectrometry imaging, SMART successfully annotated 986 formulas in developing mouse embryos. This robust platform enables systematic formula annotation within tissues, enhancing our understanding of metabolic heterogeneity.

bioinformatics↗

bioRxiv2025

Double stranded RNA sensing drives interferon silencing in early development

In early mammalian development, the type I interferon (IFN) response is inactive, only becoming functional after gastrulation. As a result, the totipotent and pluripotent embryonic stages remain highly susceptible to pathogens, including viruses. Here, we show that pluripotent mouse embryonic stem cells (mESCs) suppress the RIG-I-like receptor sensing pathway by silencing the expression of the dsRNA sensor MDA5. We show that this silencing is required to avoid the recognition of dsRNAs from endogenous origin, which only accumulate in mESCs. Reintroducing MDA5 results in recognition of these endogenous dsRNAs, and activation of the IFN response through IRF3. The production of IFN alters the differentiation ability of mESCs, as well as the pluripotency gene expression program, as shown by epigenetic, transcriptomic and proteomic analyses. These findings are conserved in zebrafish, where MDA5 is also expressed at later stages of development. Similarly, zebrafish lack early-stage IFN activation and premature IFN signalling results in developmental defects. Altogether, we conclude that silencing the RIG-I-like receptor pathway during early development is the widely conserved and is required to prevent aberrant immune recognition of endogenous dsRNAs, safeguarding normal development.

cell biology↗

bioRxiv2025

Multimodal brain cell atlas across the adult macaque lifespan

High-throughput single-cell omics of non-human primate tissues present a remarkable opportunity to study primate brain aging. Here, we introduce a transcriptomic and chromatin accessibility landscape of 1,985,317 cells from eight brain regions of 13 cynomolgus female monkeys spanning adult lifespan including exceptionally old individuals up to 29-years old. This dataset uncovers dynamic molecular changes in critical brain functions such as synaptic communication and axon myelination, exhibiting a high degree of cell type and brain region specificity. We identify the multicellular networks of the pons and medulla as a previously unrecognized hotspot for aging. Furthermore, comparative analyses with human neurodegeneration datasets highlight both shared and distinct mechanisms contributing to aging and disease. In addition, we uncover transcription factors implicated in monkey brain aging and pinpoint aging-regulated loci linked to longevity and neurodegeneration. This spatiotemporal atlas will advance our understanding of primate brain aging and its broader implications for health and disease.

neuroscience↗

bioRxiv2025

The stress response factor SigH mediates intrinsic resistance to multiple antibiotics in Mycobacterium abscessus

Mycobacterium abscessus (Mab) causes pulmonary diseases with limited treatment options due to its high level of intrinsic resistance to available drugs. Mab possesses complex and poorly understood drug resistance mechanisms. Identifying new drug targets and gaining a deeper understanding of drug resistance mechanisms are essential for discovering novel therapeutic alternatives. Here, we investigated the role of a putative sigma factor SigH in intrinsic multi-drug resistance in Mab. Mab SigH shares an 84% peptide sequence identity with Mycobacterium tuberculosis (Mtb) SigH, a well-known stress response protein and global transcriptional regulator. We constructed a sigH gene deletion strain of Mab ({Delta}sigH) and complemented strains by expressing either Mab sigH (CPMabsigH) or Mtb sigH (CPMtbsigH) in {Delta}sigH. The {Delta}sigH strain exhibited hypersensitivity to a broad range of antibiotics, including levofloxacin, moxifloxacin, tigecycline, tetracycline, amikacin, vancomycin, and rifabutin and all complemented strains restored the drug resistance phenotype. Additionally, {Delta}sigH showed increased sensitivity to oxidative and heat stress compared to the wild-type Mab and complemented strains. Transcriptomic analysis revealed that deletion of sigH disrupted the balance of gene expression, primarily elevating the expression of genes encoding YrbE and MCE family proteins and downregulating genes expressing ABC-type transporters, sigma and anti-sigma factors and other genes associated with antimicrobial resistance. Collectively, our findings indicate that SigH is a key regulator of global gene expression in response to environmental stresses, including antimicrobial treatment, and is crucial for the intrinsic drug resistance of Mab. SigH represents a promising target for the development of novel therapeutic strategies against Mab infections.

molecular biology↗

bioRxiv2025

Deviant functional connectivity patterns in the EEG and their potential use for dyslexia screening

Developmental dyslexia (DD) is a common learning disorder with potential neural origins. While EEG-based brain activation measures combined with machine learning have shown promise for DD screening, these approaches often lack validation on independent participants, which is a crucial step for practical application. This study developed an EEG-based screening approach and investigated the neural correlates of DD in Chinese children. EEG signals were recorded from 130 children (82 with DD, 48 typically developing) aged betweeen 7 and 11 during resting-state and working memory tasks. The EEG data were preprocessed into clean segments to compute functional connectivity (FC) matrices across four frequency bands (delta, theta, alpha, beta). The segments were split into two independent samples, ensuring independence at the participant level: Sample 1, used for training and five-fold cross validation of the convolutional neural networks, and Sample 2, used for cross-sample validation with the trained model. The beta-band FC index in the eyes-open condition achieved the highest within-sample classification accuracy (98%) and cross-sample accuracy (70%, p < .001). Discriminative FC patterns revealed that children with DD exhibited reduced temporal-parietal and central connectivity but increased frontal-central connectivity, likely reflecting compensatory mechanisms. Within the DD group, stronger FCs showed significant negative correlations with Chinese word reading accuracy and fluency. These findings suggest that EEG-based FC measures can effectively distinguish DD and reveal neural markers associated with impaired reading performance. This approach shows promise for noninvasive screening and deeper insight into the neural basis of DD, particularly in non-alphabetic language systems.

neuroscience↗

bioRxiv2025

Chewing behavior and bolus particle size of rice shape gut microbiota functionality and microbial metabolite signatures

The size of food particles and their surface area affect how accessible the substrates are to the gut microbiota. This study aimed to examine how the oral breakdown of rice influences the gut microbiota functionality, considering the oral phase, digestion, and colonic fermentation. Increasing the number of chews per bite produced more and smaller particles and increased total bolus surface area, influencing microbial activity and microbial metabolite production. Higher bile salt hydrolase activity and total short- chain fatty acid (SCFA) levels were found in large particles. Focusing on SCFAs, acetic acid was correlated with larger particle sizes. Propionic acid production was associated with a larger surface area, while butyric acid production was highly correlated to the fiber content. Untargeted lipidomics highlighted that particle size influenced numerous metabolites beyond SCFA. This study showed that food particle size could be an innovative strategy to modulate gut microbiota functionality and microbial metabolite production.

microbiology↗

bioRxiv2025

Inhibiting B-cell-mediated Immunosuppression to Enhance the Immunotherapy Efficacy in Hepatocellular Carcinoma

BackgroundImmunotherapy is efficacious in hepatocellular carcinoma (HCC), but the benefits are limited to a minority of patients. Most HCC patients show resistance to immune checkpoint blockade (ICB). Agonists of the stimulator of interferon genes (STING), potent immune stimulators, showed limited effectiveness. Using preclinical models, we studied the mechanisms of resistance to ICB and STING agonism. MethodsMurine HCA-1 and RIL-175 HCCs were orthotopically grown in mice with underlying liver fibrosis, to mimic the presentation of human HCC. Established tumors were treated with a STING agonist (BMS-986301) or anti-PD1 ICB, and mice were followed to evaluate safety and efficacy, as well as the mechanisms of treatment resistance by RNA sequencing, flow cytometry, and immunofluorescence, B-cell depletion and T-cell immunoglobulin and mucin domain 1 (TIM-1) ICB. ResultsUnbiased analyses of transcriptomic data from murine HCC tissues from ICB-treated mice showed an increased abundance of intratumoral CD8+ T cells and B cells. STING agonism alone showed efficacy in the ICB-responsive RIL-175 HCC model but more limited efficacy in the ICB-resistant HCA-1 model. STING agonism increased circulating IL-10 and intratumoral infiltration by B-cells, including TIM-1+ B cells, and promoted the formation of tertiary lymphoid structure (TLS)-like structures, especially in the peritumoral areas. Strikingly, adding B cell depletion to ICB or STING agonism treatment significantly increased survival. Interestingly, unlike ICB, STING agonism also had a pronounced anti-metastatic activity. In addition, the combination of STING agonism and TIM-1 blockade augmented B cell differentiation and antigen presentation in vitro and improved the anti-tumor effects in murine HCC in vivo. This approach decreased the number of TIM-1+ B cells in the tumor and shifted B cells to higher expression of CD86 and MHC class II, enhancing the antigen presentation capability and further boosting the antitumor efficacy of CD8+ cytotoxic T cells. ConclusionOur findings demonstrate that B cells are associated with ICB- and STING-mediated therapy resistance, and that depleting B-cells or targeting TIM-1 enhances both innate and acquired therapeutic efficacy in HCC.

cancer biology↗

bioRxiv2025

Ultrasonic Modulation of Astrocytic and Neuronal Calcium Dynamics in Mouse Cortex

BackgroundAstrocytes are abundant in the brain and their calcium signaling is reported to have an important effect on neuronal activity in both physiological and pathological conditions. Low-frequency focused ultrasound (FUS) has recently emerged as a powerful noninvasive neuromodulation approach, yet its impact on astrocyte calcium dynamics in different brain states in vivo is poorly understood. ObjectiveThis study aimed to elucidate the effects of non-thermal FUS on astrocyte calcium dynamic with in vivo cellular-resolution and cell-type-specific recording and identify whether the influences of FUS on cortical astrocytes and neurons are distinctive and state dependent. MethodsHere we combined a customized 0.521MHz FUS transducer with two-photon microscopy, allowing simultaneous single-cell resoultion imaging and FUS stimulation at intensities of 0.91 or 1.5 W/cm2 to examine astrocyte and neuronal calcium responses in somatosensory cortex of both awake and lightly anesthetized mice. Functional clustering analysis was performed to identify calcium response activated or inhibited subpopulations. ResultsIn awake mice, FUS significantly enhanced the amplitude, frequency, and temporal integral of astrocyte calcium transients, while suppressing neuronal calcium activity and reducing the proportion of activated neuronal subpopulations. In contrast, lightly anesthetized mice displayed a blunted yet increased astrocyte response and negligible neuronal modulation under FUS, suggesting that baseline suppression from anesthesia partially masks FUS effects. ConclusionsOur study demonstrated that FUS elicited distinctive, state-dependent effects on cortical astrocytes and neurons, highlighting astrocytes as previously underappreciated targets of ultrasound neuromodulation. These findings will pave the way for FUS-based therapies targeting astrocyte-neuron interactions in conditions involving abnormal brain excitability. HighlightsO_LILow duty cycle low frequency focused ultrasound induced negligible heat effects. C_LIO_LIUltrasound markedly enhanced astrocyte calcium transients in awake mice. C_LIO_LIUltrasound suppressed neuronal calcium activity in awake mice. C_LIO_LIThe effects of ultrasound on both cell types were reduced under light anesthesia. C_LI

bioengineering↗

bioRxiv2025

Ethylene modulates cell wall mechanics for root responses to compaction

Soil stresses impact crop yields, presenting global agricultural challenges. Soil compaction triggers root length reduction and radial expansion driven by the plant hormone ethylene. We report how ethylene controls cell wall properties to promote root radial expansion. We demonstrate how soil compaction stress, via ethylene, upregulates Auxin Response Factor1 in the root cortex, which represses Cellulose Synthase (CESA) genes. CESA repression drives radial expansion of root cortical cells by modifying the thickness and mechanics of their cell walls, which result in a "stiff epidermis-soft cortex" contrast. Our research thus connects ethylene signaling with root mechanics via cell wall strength, and reveals how dynamic regulation of cellulose synthesis crucially controls root growth in compacted soil.

plant biology↗