Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 397 records · Page 22Linked to original sources

bioRxiv2025

Advanced adaptive strategies in an ancestral body plan: insights from a 510-Ma-old leptomitid sponge

Sponges have thrived in diverse environmental conditions since the early Cambrian till today. However, little is known about how their adaptive capability and strategies have been shaped throughout evolutionary history. Here, we explore this question based on a new leptomitid sponge fossil from the Cambrian Stage 4. The family Leptomitidae was an abundant sponge group inhabiting Cambrian soft substrates but significantly declined thereafter. The new species exhibits a sophisticated set of morphological characteristics adaptive to a shallow siliciclastic environment, which are unprecedented among leptomitids. These include (1) a robust body wall woven by spirally twisted monaxonic spicules; (2) a thick stub-like root tuft for anchoring; (3) spicules radiating out from the sponge body to prevent clogging and sinking; and (4) the inferred capability to close the osculum against unfavourable stimuli. Nevertheless, the new fossil species maintains a leptomitid body plan which lacks modularity and morphological plasticity, the two common and critical attributes in extant sponges to enhance flexibility and resilience in changing environmental conditions. This juxtaposition of evolutionary innovation and structural conservatism offers a compelling case for further exploration of the evolutionary mechanisms that shaped early sponge lineages.

paleontology↗

bioRxiv2025

VGLL3-centered network connects placental, vascular, and immune defects in preeclampsia

Preeclampsia affects approximately 1 in 10 pregnancies, leading to severe complications and long-term health risks for both mother and offspring. While the etiology remains unclear, preeclampsia has been linked to both autoimmunity and the timing of menarche. Through human single-cell and spatial analyses, coupled with in vitro, in vivo, and ex vivo models, we demonstrate that VGLL3, a transcription co-regulator in the Hippo pathway, is upregulated in preeclamptic placentas. VGLL3 promotes immune activation, impairs trophoblast differentiation, and induces endothelial dysfunction, all of which contribute to pregnancy-related hypertension, fetal growth restriction, and offspring mortality. Our data reveal that VGLL3 acts upstream of preeclampsia-associated processes, including the production of sFLT1, a key biomarker of the disease. Notably, targeting VGLL3--either by genetic deletion in mouse placentas or through therapeutic inhibition in human placentas--protects against preeclampsia and alleviates disease pathology. These findings position VGLL3 as a promising novel therapeutic target for preeclampsia.

immunology↗

bioRxiv2025

A missense mutation in Muc2 promotes gut microbiome- and metabolome-dependent colitis-associated tumorigenesis.

Colitis-associated cancer (CAC) arises from a complex interplay between host and environmental factors, including the gut microbiome. Since ulcerative colitis (UC), a significant risk factor for CAC, is rising in prevalence worldwide, an integrative approach is essential to identify potential triggers linking inflammation to cancer. In the present study, we investigated the role of the gut microbiome using Winnie mice, a UC-like model with a relevant missense mutation in the Muc2 gene. Upon transfer from a conventional (CONV) to a specific-pathogen-free (SPF) facility, Winnie mice exhibited a more severe colitis phenotype, and notably, spontaneous CAC as early as four weeks of age, which progressively worsened over time. In contrast, CONV Winnie developed only mild colitis but with no overt signs of tumorigenesis. Notably, when rederived into germ-free (GF) conditions, SPF Winnie mice were protected from colitis or colon tumor development, indicating an essential role for the gut microbiome in the initiation and progression of CAC in these mice. Using shotgun metagenomics, metabolomics, and lipidomics, we identified a distinct pro-inflammatory microbial and metabolic signature that potentially drives the transition from colitis to CAC. Fecal microbiota transplantation (FMT), using either SPF Winnie or WT (Bl/6) donors into GF Winnie recipients, demonstrated that while colitis developed regardless of donor, only FMT from SPF Winnie donors resulted in CAC, revealing a microbiota-driven, host-specific susceptibility to tumorigenesis in Winnie mice. Our studies present a novel and relevant model of CAC, providing further evidence that the microbiome plays a key role in the pathogenesis of CAC, thereby challenging the concept of colon cancer as a strictly non-transmissible disease. Lay summaryThis study reveals a distinct metagenomic, metabolomic, and lipidomic profile associated with tumorigenesis in a murine model of ulcerative colitis, highlighting the risks of specific intestinal dysbiosis in genetically predisposed subjects. What you need to knowO_ST_ABSBackground and contextC_ST_ABSColitis-associated colorectal cancer arises from complex host-environment interactions, including gut microbiome influences, driving chronic inflammation, with the intestinal lumen environment remaining a largely unexplored potential risk factor in cancer development. New findingsWinnie mice in specific pathogen-free conditions developed severe colitis, and a novel juvenile colon dysplasia and cancer, with gut microbiome changes driving colitis-associated cancer initiation and progression. LimitationsWe identified a pro-inflammatory microbial/metabolic signature promoting colitis-to-CAC transition in Winnie mice, with FMT confirming microbiota-driven tumor susceptibility. However, further research is needed to pinpoint the key bacteria-metabolite-lipid combination driving CAC. Clinical research relevanceThis newly characterized microbiota-metabolome-based model of CAC, challenges the dogma of cancer as a non-transmittable disease, providing a foundation for developing microbiota-based strategies for CAC prevention and treatment. Basic research relevanceUnlike genetic or chemically induced models, the Winnie mouse model uniquely serves as a dual model for spontaneous colitis and juvenile CAC, offering a fast, 100% penetrant phenotype that enhances reliability, accelerates research, and provides valuable insights into IBD and CAC.

cancer biology↗

bioRxiv2025

Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models

In-silico prediction of protein mutant stability, measured by the difference in Gibbs free energy change ({Delta}{Delta}G), is fundamental for protein engineering. Current sequence-to-label methods typically employ the two-stage pipeline: (i) encoding mutant sequences using neural networks (e.g., transformers), followed by (ii) the {Delta}{Delta}G regression from the latent representations. Although these methods have demonstrated promising performance, their dependence on specialized neural network encoders significantly increases the complexity. Additionally, the requirement to individually compute latent representations for each mutant site negatively impacts computational efficiency and poses the risk of overfitting. This work proposes the Venus-MO_SCPLOWAXWELLC_SCPLOW framework, which reformulates mutation {Delta}{Delta}G prediction as a sequence-to-landscape task. In Venus-MO_SCPLOWAXWELLC_SCPLOW, mutations of a protein and their corresponding {Delta}{Delta}G values are organized into a landscape matrix, allowing our framework to learn the {Delta}{Delta}G landscape of a protein with a single forward and backward pass during training. Besides, to facilitate future works, we also curated a large-scale {Delta}{Delta}G dataset with strict controls on data leakage and redundancy to ensure robust evaluation. Venus-MO_SCPLOWAXWELLC_SCPLOW is compatible with multiple protein language models and enables these models for accurate and efficient {Delta}{Delta}G prediction. For example, when integrated with the ESM-IF, Venus-MO_SCPLOWAXWELLC_SCPLOW achieves higher accuracy than ThermoMPNN with 10x faster in inference speed (despite having 50x more parameters than ThermoMPNN). The training codes, model weights, and datasets are publicly available at https://github.com/ai4protein/Venus-MAXWELL.

bioinformatics↗

bioRxiv2025

Structural innovations and neurogenic continuity define avian brain development and evolution

Understanding how neurogenic diversity and brain architecture emerge is crucial for deciphering the mechanisms of brain plasticity and cognitive evolution. Here, we present a comprehensive single-cell and spatial transcriptomic atlas of the budgerigar brain, a highly cognitive avian species. We uncover a striking dorsoventral symmetry in excitatory neuron distribution, precisely organized along the lamina mesopallialis intermedia (LMI), a key boundary structure. Cross-species comparisons further reveal the origins of this unique avian pallial organization, offering new insight into avian brain evolution. Our study also highlights distinct developmental trajectories and asynchronous maturation patterns between telencephalic and optic tectum excitatory neurons, underscoring their contribution to innate circuit assembly. Furthermore, we identify adult neural stem cells (NSCs) with evolutionarily conserved transcriptomic signatures across avian species, emphasizing their role in brain plasticity and adaptation. These findings refine fundamental models of avian brain development and elucidate conserved principles of cognitive plasticity.

evolutionary biology↗

bioRxiv2025

Xcr1+ type 1 conventional dendritic cells are essential mediators for atherosclerosis progression

BackgroundAtherosclerosis is characterized by lipid accumulation within plaques, leading to foam cell formation and an inflammatory response within the aortic lesions. Lipid disorders have been extensively investigated, however the cellular and molecular mechanisms that trigger the inflammatory response in atherosclerotic plaques remain far from being fully understood. Xcr1+ cDC1 cells are newly identified antigen-presenting cells in activating immune cells. However, the role of cDC1 cells in the development of atherosclerosis remains highly controversial. ResultsWe first confirmed the presence of cDC1 within human atherosclerotic plaques and discovered a significant association between the increasing cDC1 numbers and atherosclerosis progression in mice. Subsequently, we established Xcr1Cre-Gfp Rosa26LSL-DTA ApoE-/- mice, a novel and complex genetic model, in which cDC1 was constitutively depleted in vivo during atherosclerosis development. Intriguingly, we observed a notable reduction in atherosclerotic lesions in hyperlipidemic mice, alongside suppressed T cell activation of both CD4+ and CD8+ subsets in the aortic plaques. Notably, aortic macrophages and serum lipid levels were not significantly changed in the cDC1-depleted mice. Single-cell RNA sequencing revealed heterogeneity of Xcr1+ cDC1 cells across the aorta and lymphoid organs under hyperlipidemic conditions. As Xcr1 is the sole receptor for Xcl1, we next explored to target Xcr1+ cDC1 cells via Xcl1 by establishing Xcl1 and ApoE deficient mice. Xcl1 knockout mice exhibited decreased atherosclerotic plaque formation and reduced aortic cDC1 accumulation, indicating that Xcl1 contributes to cDC1-mediated atherosclerotic lesion development. ConclusionsOur results reveal crucial roles of cDC1 in atherosclerosis progression and provide insights into the development of immunotherapies by targeting cDC1 through Xcl1.

immunology↗

bioRxiv2025

Ketone Bodies-mediated Cysteine Modifications Discovered by Chemical Proteomics

All the studies of ketone body-dependent post-translational modifications (PTMs), notably those mediated by ketone bodies, {beta}-hydroxybutyrate (Bhb) and acetoacetate (Acac), have focused on lysine acylations. However, given the chemically diverse and reactive nature of metabolites generated, it remains unclear whether non-lysine modifications can also happen. Here, we report the synthesis of an acetoacetate-alkyne (Acac-alkyne) chemical probe that enables efficient metabolic labeling, robust fluorescent visualization, and mass spectrometry-based identification of Acac-modified proteins. By combining chemical proteomics with open-search strategy, we showed that Acac will induce previously uncharacterized cysteine modifications in mammalian cells. Notably, cysteine S-crotonation (Ccr) is validated by employing both probe-based and standard peptide-based co-elution assays. Metabolic pathway tracing further identifies BDH1 and ECHS1 as key enzymes that generate Ccr formation. Together, these findings establish ketone metabolism as a novel source of cysteine modifications and provide an alternative mechanistic pathway to explain the profound biological effects of ketone body.

biochemistry↗

bioRxiv2025

Aptamer-Enabled Discovery and Clinical Analysis of Exosomal Surface Biomarkers in Hepatocellular Carcinoma

Exosomal membrane proteins hold promise as cancer biomarkers but face detection challenges due to low abundance and conformational sensitivity. We developed AptEx-ID, a microbead-displayed aptamer platform enabling high- throughput screening of hepatocellular carcinoma (HCC)-specific exosomal surface proteins. Aptamers, selected via competitive binding to tumor-derived versus healthy exosomes, demonstrated high affinity and specificity. Clinical validation using 50 HCC and 30 control plasma samples identified a 7-aptamer panel via machine learning, achieving 93.75% accuracy and 0.95 ROC-AUC. These aptamers further revealed HCC-associated biomarkers (e.g., IMPDH1, ASCC3, GTSE1), validated by siRNA knockdown and biophysical assays. Post-treatment monitoring showed aptamer signal reduction in responsive patients, highlighting their prognostic utility. This platform integrates biomarker discovery, diagnostics, and therapeutic monitoring, offering a robust approach for HCC management through exosomal surface proteome profiling.

molecular biology↗

bioRxiv2025

Engineering the key central metabolic enzyme to utilize a non-canonical redox cofactor

Redesigning central metabolism enzymes to utilize non-canonical cofactors that are orthogonal to NAD+ and NADP+ may allow partitioning of reducing power into a distinct redox cofactor pool that is preserved for user-desired biosynthetic tasks, without being dissipated by the complex natural metabolism in the cells. Here, we engineer Escherichia coli glyceraldehyde-3-phosphate dehydrogenase (GapA), the key enzyme in glycolysis, to utilize nicotinamide mononucleotide (NMN+) while greatly reducing its original activity with its native cofactor, NAD+. Through rational design, we identify the variant A180S with a [~]3-fold increase in NMN+ specific activity compared to that of the wildtype (WT). Next, we design a double mutant, G10R-A180S (RS), where G10R mutation hampers the catalytic efficiency for NAD+ but also decreased the activity toward NMN+. Importantly, based on the hypothesis that the role of NAD+ in coordinating oligomer interface must be recapitulated in NMN+-utilizing enzymes, we develop a triple mutant G10R-A180S-G187Q (RSQ). Rosetta modeling predicts that the new mutation G187Q bridges separate subunits across the cofactor binding pocket, which possibly affords stronger association of the GapA tetramer, the active form of this enzyme. This final GapA variant features a [~]2.8 x 104 switch of cofactor specificity from GapAs natural cofactor NAD+ to the non-canonical cofactor NMN+. Overall, this work demonstrates the engineering of a highly conserved, central metabolic enzyme for the utilization of a non-canonical redox cofactor NMN+. The design principle discovered here may be broadly applicable to many enzymes that bind cofactors using an intersubunit pocket.

molecular biology↗

bioRxiv2025

Mechanosensitive Endothelial METTL7A Regulates Internal m7G mRNA Methylation and Protects Against Atherosclerosis

BACKGROUNDInternal N7-methylguanosine (m7G) is a recently identified chemical modification of mammalian mRNA and a component of the epitranscriptome. While the epitranscriptome plays a key role in regulating RNA metabolism and cellular function, the specific contribution of internal m7G to cardiovascular health and disease remains unknown. Atherosclerosis preferentially develops at sites where disturbed blood flow activates endothelial cells, but whether internal m7G and its regulatory machinery influence endothelial mechanotransduction and atherogenesis is unclear. METHODSWe integrated epitranscriptomic profiling, human tissue analysis, genetically modified mouse models, and targeted nanomedicine approaches to investigate the role of Methyltransferase-like protein 7A (METTL7A), a putative internal m7G methyltransferase, in regulating the flow-sensitive endothelial transcriptome and atherosclerosis. Vascular endothelial cells were subjected to well-defined athero-protective and athero-prone flow waveforms in vitro and in vivo. METTL7A function was assessed using RNA sequencing (RNA-seq), liquid chromatography-tandem mass spectrometry (LC-MS/MS), crosslinking immunoprecipitation sequencing (CLIP-seq), RNA stability assays, and a CRISPR-Cas-inspired RNA targeting system (CIRTS). METTL7A expression in human coronary arteries with and without atherosclerosis was evaluated by RNA-seq and immunostaining. In vivo atherosclerosis studies were conducted in both global and endothelial-specific Mettl7a1 knockout mice. Endothelial METTL7A expression was restored using cationic polymer-based nanoparticles delivering CDH5 promoter-driven METTL7A plasmids or VCAM1-targeted lipid nanoparticles delivering N1-methylpseudouridine (m{superscript 1}{Psi})-modified METTL7A mRNA. RESULTSAthero-protective unidirectional flow significantly induced METTL7A expression, which promoted internal m7G methylation of endothelial transcripts, while other major epitranscriptomic marks and cap-associated m7G were not affected by METTL7A. METTL7A preferentially binds to AG-enriched motifs in protein-coding mRNAs and plays a key role in regulating KLF4 and NFKBIA transcripts, enhancing their internal m7G and stability and supporting vascular homeostasis. In contrast, endothelial METTL7A expression was significantly reduced by disturbed blood flow and in human atherosclerotic lesions. Global or endothelial-specific loss of METTL7A exacerbated disturbed flow-induced atherosclerosis in mice, independent of serum lipid levels. Restoration of endothelial METTL7A, via nanoparticle-mediated plasmid or m1{Psi} mRNA delivery, markedly reduced lesion formation in Mettl7a1-/- and ApoE-/- mice. CONCLUSIONSThese findings establish METTL7A as a previously unrecognized mechanosensitive methyltransferase that maintains endothelial homeostasis by stabilizing key anti-inflammatory transcripts, KLF4 and NFKBIA, through internal m7G methylation. Loss of METTL7A disrupts endothelial function and accelerates atherogenesis in response to disturbed flow. Therapeutic restoration of endothelial METTL7A, via targeted nanoparticle-mediated gene or m1{Psi} mRNA delivery, significantly lessens atherosclerosis. Collectively, these results uncover a novel epitranscriptomic mechanism governing vascular health and position METTL7A as a promising target for precision nanomedicine in atherosclerotic cardiovascular disease.

molecular biology↗

bioRxiv2025

TypeSINE: Genome-Wide Detection of SINE Retrotransposon Polymorphisms Reveals Functional Variants Linked to Body Size Variation in Pigs

The genotyping of Short Interspersed Element (SINE) retrotransposon insertion polymorphisms (RIPs) from large-scale sequencing data remains technically challenging. To overcome this limitation, we developed TypeSINE to genotype SINE-RIPs from short-read sequencing data. Analyzing 362 porcine genomes, we identified 749,835 SINE-RIPs (>85% accuracy), including 65,917 common variants (5-95% frequency). These showed uniform genomic distribution ([~]22/Mb), with 40% in introns. Population analyses based on SINE-RIPs revealed independent domestication of Asian and European pigs from local wild populations, followed by introgression. GWAS detected body size-associated regions using SINE-RIPs. We created pigRIPdb (82,227 curated SINE-RIPs) with browsing and visualization tools. The methods cross-species applicability is supported by conserved SINE evolutionary patterns, enabling polymorphism discovery of SINEs in livestock and humans. TypeSINE represents an efficient, scalable solution for genome-wide SINE-RIP analysis, advancing population genomics research. TeaserAn integrated SINE-RIP genotyping platform with companion database enables large-scale analysis of SINE evolution and population genetics in swine

bioinformatics↗

bioRxiv2025

Riemann-GNN: Causal Reasoning on Hyperbolic Riemannian Manifolds for Interpretable Drug-Disease Prediction

The high cost and low success rate of de novo drug development have driven increasing interest in drug repurposing. Computational approaches to drug repurposing leverage large-scale biomedical knowledge graphs (KGs) to identify new indications for existing drugs. However, the structural heterogeneity, relation sparsity, and limited interpretability of current models remain significant challenges. In this study, we propose Riemann-GNN, an end-to-end framework that combines hyperbolic geometry, graph neural networks (GNNs), and causal inference for interpretable drug repurposing. Riemann-GNN embeds multi-relational biomedical KGs into a hyperbolic Riemannian manifold modeled by the Poincare ball, effectively capturing the hierarchical structure of biomedical entities. On top of this geometry, we introduce a causal reasoning module that extracts disease-centric subgraphs and applies intervention-based inference using structural causal models. This module provides mechanistic explanations for predicted drug-disease associations. We evaluate our model on PrimeKG, a comprehensive biomedical KG with over 129,000 nodes and 4 million edges, achieving AUROC = 0.971, AUPRC = 0.963, and Recall@20 = 0.847, significantly outperforming several state-of-the-art baselines. In a case study on amyotrophic lateral sclerosis (ALS), Riemann-GNN identifies 20 novel candidate drugs--such as Bosutinib, Masitinib, and Tamoxifen--and provides interpretable causal paths explaining their therapeutic relevance. Several predictions without existing ALS labels in the KG are supported by literature evidence, while others suggest new hypotheses for future validation. These results demonstrate the utility of integrating hyperbolic representation learning with causal semantics for robust and explainable biomedical AI.

bioinformatics↗

bioRxiv2025

Inflamed Microglia like Macrophages in the Central Nervous System of Prodromal Parkinson's Disease

We hypothesized that prodromal Parkinsons Disease (PD), characterized by REM Sleep Behavior Disorder and hyposmia, is an inflammatory disorder initiated in the gut that evolves into a neurodegenerative process manifest as classical PD. To test this hypothesis, we performed single-cell RNAseq analysis of cerebrospinal fluid (CSF) and blood from 118 individuals, comparing healthy subjects with prodromal PD and manifest PD to patients with the central nervous system (CNS) autoimmune disease, multiple sclerosis (MS). Surprisingly, we identified increased numbers of immune cells in the CSF of patients with prodromal PD. Single-cell RNA sequencing revealed increases in CSF-specific microglia-like macrophages with enhanced JAK-STAT and TNF signaling signatures in prodromal PD. CSF macrophages exhibited similar transcriptional profiles to dural macrophages and gut muscularis macrophages from -synuclein-expressing PD model mice. Finally, shared memory T cell clones were found in humans between gut and CSF T cells. These findings uncover a myeloid-mediated TNF inflammatory process in the CNS of patients with prodromal PD, with an immunological linkage between the gut and the CNS.

immunology↗

bioRxiv2025

A Conserved Mycobacterial Nucleomodulin Hijacks the Host COMPASS Complex to Reprogram Pro-Inflammatory Transcription and Promote Intracellular Survival

Nucleomodulins are a class of effector proteins secreted by bacterial pathogens that translocate into the host cell nucleus to modulate nuclear processes. However, their target proteins and underlying molecular mechanisms remain poorly understood in mycobacteria. Herein, we identified a conserved hypothetical protein Rv1075c, designated MgdE, as a nucleomodulin that enhances mycobacterial intracellular survival. MgdE undergoes nuclear translocation via two nuclear localization signals, KRIR108-111 and RLRRPR300-305, and interacts with ASH2L and WDR5, two subunits of the host histone methyltransferase COMPASS complex. This interaction suppresses histone H3 lysine 4 (H3K4) methylation-mediated transcription of pro-inflammatory genes, including IL6 and IL1B, thereby promoting mycobacterial survival in both macrophages and mice. Our study provides the first experimental evidence that a bacterial nucleomodulin facilitates intracellular survival by directly targeting the host COMPASS complex. These findings advance our understanding of mycobacterial pathogenesis by revealing a novel mechanism that contributes to its intracellular survival strategy.

microbiology↗

bioRxiv2025

CHI3L1-Targeted Small Molecules as Glioblastoma Therapies: Virtual Screening-Based Discovery, Biophysical Validation, Pharmacokinetic Profiling, and Evaluation in Glioblastoma Spheroids

Glioblastoma (GBM) remains the most aggressive primary brain malignancy with a 10% three- year survival rate. Chitinase-3-like protein 1 (CHI3L1) has emerged as a critical factor in the progression of GBM progression, invasion, and treatment resistance. However, small molecule inhibitors targeting CHI3L1 are largely unexplored. Microscale thermophoresis (MST) investigation of the direct binding potential of reported CHI3L1 modulators (K284, G721-0282, CHI3L1-IN-1) revealed modest to undetectable direct CHI3L1 binding affinity. Herein, pharmacophore-based virtual screening of in-house library resulted in the discovery of G28 as the most potent small molecule CHI3L1 binder reported to date. The CHI3L1 binding affinity of G28 was validated using MST and surface plasmon resonance (SPR). To evaluate the GBM-modulatory potential of G28, we conducted comprehensive pharmacokinetic and 3D spheroid studies alongside established CHI3L1 modulators. G28 demonstrated outstanding bioavailability and low toxicity, addressing key limitations faced by previous CHI3L1-targeted strategies. Notably, in 3D GBM spheroid models, G28 significantly outperformed reported CHI3L1 small molecule modulators, showing the most pronounced dose-dependent reductions in spheroid weight, migration, and viability. These findings position G28 as the most promising CHI3L1-targeted small molecule to date and a compelling candidate for GBM therapeutic development.

pharmacology and toxicology↗

bioRxiv2025

Enhancing Biomedical Optical Volumetric Imaging via Self-Supervised Orthogonal Learning

Optical volumetric imaging grapples with inherent noise problems arising from photon budget constraints, light scattering, and space-bandwidth product bottlenecks, all of which degrade structural fidelity and become even more pronounced than in planar imaging. While deep learning presents potential for denoising, supervised methods are hindered by the impracticality of paired dataset, and existing self-supervised approaches fail to fully exploit the intrinsic volumetric structural redundancy inherent to optical imaging. Here, we present a self-supervised Volumetric biomedicAL Imaging Denoiser (VALID) that leverages intrinsic three-dimensional spatial coherence for highly efficient volumetric denoising through a self-supervised orthogonal learning framework. VALID demonstrates robust denoising performance across diverse imaging modalities, including two- and three-photon microscopy, light-field microscopy, and optical coherence tomography, substantially enhancing structural fidelity in deep-tissue, multimodal, and dynamic imaging scenarios. By combining computational efficiency with zero-shot adaptability, VALID establishes a transformative approach to volumetric image enhancement with structure-aware precision.

neuroscience↗

bioRxiv2025

HIV-1 Amplifies IL-8 Response Of Human Stellate Cells To Gram-Positive Microbial Products Via H4K5 Histone Acetylation

BackgroundPatients living with human immunodeficiency virus 1 (PLWH) develop accelerated liver fibrosis, but the exact mechanism remains unknown. Activation of hepatic stellate cells (HSCs)--a cornerstone of fibrosis--is influenced by various factors, including viral infection, hepatocellular injury, chronic immune activation, gut barrier dysfunction, and microbial translocation. The role of gram-positive microbial products in human immunodeficiency virus 1 (HIV-1) infection-associated liver inflammation and fibrosis remains poorly understood. This study investigates the effect of lipoteichoic acid (LTA), a major gram-positive bacterial component, on HSCs in the context of HIV-1 infection. MethodsHuman HSCs were isolated from liver tissues of both HIV-1-infected and uninfected individuals undergoing hepatic resection. Inflammatory responses of HSCs to LTA stimulation were measured ex vivo via ELISA before and after HIV-1BaL exposure. Western blotting, ChIP-qPCR and RNA-seq were used to reveal the mechanisms contributing to the IL-8 response to LTA stimulation and HIV-1BaL exposure in HSCs. ResultsLTA modestly induced interleukin-8/CXCL8 (IL-8) production in HSCs, but this response was significantly heightened following HIV-1 exposure. Increased IL-8 levels were also observed in liver tissues from HIV-1-infected patients. In vitro, IL-8 treatment of HSCs elevated -SMA and COL1A1 expression, implicating IL-8 in fibrosis progression in HIV-1 infection. Transcriptomic analysis pointed to histone acetylation as a key regulator of the IL-8 response of HSCs to LTA during HIV-1 infection. Supporting this, the histone deacetylase (HDAC) inhibitor Trichostatin A (TSA) further enhanced IL-8 expression in HIV-1-exposed HSCs. ChIP-qPCR confirmed that acetylation of histone H4K5 facilitated IL-8 promoter transactivation, sensitizing HSCs to LTA under HIV-1 influence. ConclusionsHIV-1 infection primes HSCs for an exaggerated response to LTA, driven by histone acetylation and resulting in elevated IL-8 production--potentially accelerating liver fibrosis in PLWH. Given the persistence of microbial translocation despite effective antiretroviral therapy, these findings highlight the need for targeted interventions to prevent or mitigate liver fibrosis in PLWH.

immunology↗

bioRxiv2025

Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations

Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity. GBM tumors contain neoplastic cells within a spectrum of different transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we developed a novel framework, ISOSCELES (Inferred cell Sensitivity Operating on the integration of Single-Cell Expression and L1000 Expression Signatures), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identified compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states. We validated the significance of these findings in vitro, ex vivo, and in vivo, and identified a novel combination of an OLIG2 inhibitor and Depatux-M for GBM. Our studies suggest that ISOSCELES identifies cell states sensitive and resistant to targeted therapies in GBM and that it can be applied to identify new synergistic combinations. HighlightsO_LIIntegration of GBM single-cell RNA sequencing data with L1000-derived drug response signatures facilitates clustering of tumor cells and small molecules on cell-drug connectivity. C_LIO_LICell-drug connectivity predicts the identities of drug-sensitive and resistant cell states. C_LIO_LIIn silico perturbation analysis using cell-drug connectivity predicts drug-induced changes in the cell-drug connectivity landscape in vivo. C_LIO_LIIn silico perturbation analysis to predict drug-induced changes in the tumor cell-drug connectivity landscape predicts drug combinations that synergize in vivo to extend survival. C_LI

cancer biology↗