Biology subjects

Li, Q.

Publications and source records attributed to Li, Q..

At least 217 records · Page 12Linked to original sources

bioRxiv2025

Single cell multiomic analysis of the impact of Delta-9-tetrahydrocannabinol on HIV infected CD4 T cells

Cannabis use is prevalent among individuals living with HIV in the United States, but the impact of cannabis exposure on the reservoir of latently infected cells that persists during antiretroviral therapy (ART) remains unclear. To address this gap, we analyzed the effect of {Delta}-9-tetrahydrocannabinol (THC) on primary CD4 T cells that were latently infected with HIV. We found that THC had no detectable effect on baseline or latency reversing agent (LRA) stimulated HIV expression, or on expression of an activation marker (CD38). However, using an integrated multiomic single-cell analysis of genome-wide chromatin accessibility and gene expression, we observed altered expression of several hundred genes in HIV infected CD4 T cells after THC exposure, including transcriptional downregulation of genes involved in protein translation and antiviral pathways, indicating that THC suppresses innate immune activation in infected cells. Additionally, chromatin accessibility analysis demonstrated upregulated chromatin binding activity for the transcriptional regulator CTCF, and reduced activity for members of the ETS transcription factor family in infected cells after THC exposure. These findings provide insights into the mechanisms by which cannabis use could influence the persistence of HIV within cellular reservoirs and the molecular phenotype of latently infected cells. Further elucidation of the underlying mechanisms involved in THC-mediated changes to HIV infected cells, will lead to an improved understanding of the impact of cannabis use on the HIV reservoir. ImportanceCannabis use is common among individuals living with HIV, but the long-term effects of cannabis use on the HIV reservoir are not yet studied completely. We employed advanced single-cell technologies to reveal how cannabis components, specifically THC, influence HIV-infected immune cells and their pattern of gene expression. We found that, while THC doesnt reactivate virus in latently infected cells, it alters the molecular characteristics of these infected immune cells. These findings are important because they underscore how cannabis could regulate persistent infection in people living with HIV. Understanding these cellular changes in response to THC could be helpful for successful treatment for people living with HIV.

molecular biology↗

bioRxiv2025

Widespread distribution of the BpfA-carrying bacteria involved in the bisphenol F degradation in Pseudomonadota and Actinomycetota

The global use of bisphenol F (BPF) has led to widespread environmental contamination, posing significant threats to ecosystems and human health. However, the genes involved in BPF degradation remained unknown. In this study, a novel oxidase gene, bpfA, was obtained from strain Microbacterium sp. F2 through a four-step purification strategy. BpfA is classified as a member of the 4-phenol oxidizing (4PO) subfamily and contains a conserved FAD-binding domain (Asp152 and His393) as well as a Tyr-Tyr-Arg triad (Tyr93, Tyr474, Arg475). BpfA catalyzes the conversion of BPF to 4,4-dihydroxydibenzophenone (DHBP) through a series of three consecutive reactions. In addition, BpfA exhibits catalytic activity towards 4-alkylphenols, such as vanillyl alcohol (VA), 4-n-propylguaiacol (4PG), and 4-(methoxymethyl)phenol (4MOP). BpfA homologs are widely distributed in the environment, particularly in soil. Bioinformatics-based taxonomic profiling revealed that BpfA homologs are widely distributed in metagenomes from cultivated land and forests, mainly belonging to Pseudomonadota and Actinomycetota. This study enhances our understanding of the microbial degradation mechanism of BPF, elucidates the catalytic function of the novel oxidase gene bpfA and its distribution pattern in the environment, and provides important insights into the evolutionary origin of BPF degradation genes and the targeted mining of environmental microbial resources.

microbiology↗

bioRxiv2025

RareFold: Structure prediction and design of proteins with noncanonical amino acids

Protein structure prediction and design have traditionally been confined to the 20 canonical amino acids. Expanding this chemical space to include non-canonical amino acids (ncAAs) is essential for engineering proteins with novel chemical and functional properties. However, existing methods are not designed to generalise across chemically diverse residue types. Here, we present RareFold, a deep learning architecture for structure prediction and design of proteins containing the 20 canonical amino acids and 29 ncAAs. By representing each residue as an independent token, RareFold learns context-dependent atomic interaction patterns across chemically diverse sequence spaces, enabling modelling of non-standard chemistries within a unified framework. We apply this capability in EvoBindRare, a generative framework for de novo design of linear and cyclic peptide binders with an efficient implementation that substantially reduces computational requirements compared to existing architectures. We demonstrate its performance by designing binders against Ribonuclease A, yielding novel linear and cyclic peptides incorporating ncAAs within predicted interfaces with low-micromolar affinities (KD [~]2-9 M), comparable to the native ligand (KD [~]2 M). Hydrogen-deuterium exchange mass spectrometry confirms that the designed peptides engage the target at regions consistent with predicted binding interfaces. In addition, immunogenicity profiling in human-derived organoid models shows no detectable immune activation. By extending deep learning-based protein design to non-canonical chemical spaces, RareFold enables programmable access to expanded amino acid alphabets and broadens the scope of de novo protein engineering.

bioinformatics↗

bioRxiv2025

Microbially-mediated halogenation and dehalogenation cycling of organohalides in the ocean

Microbially mediated organohalide cycling in the ocean has profound implications for global element cycles and climate, but the phylogeny, coding potential, and distribution of the halogenation-dehalogenation cycling microorganisms remain unknown. Here, we construct an organohalide-cycling database (HaloCycDB) to explore the global atlas of halogenation-dehalogenation cycling genes and microorganisms in the ocean from 1,473 marine metagenomes. FlaHase and HyDase/RDase as predominant halogenase- and dehalogenase-encoding genes account for 80.24% of all potential organohalide-cycling activities. We identify 80.91% RDase and 91.35% RDase-containing prokaryotes as unknown organohalide-cycling genes and microorganisms, respectively, which greatly expand the diversity of dehalogenation phylogeny and coding potential. Further integration of microbial cultivation with protein structure prediction and molecular docking elucidates 4 unique "microorganism-enzyme-organohalide" patterns for organohalide dehalogenation in the ocean. Our results provide the first insight into microbial halogenation-dehalogenation cycling of organohalides and associated yet-to-be-explored resources in the ocean.

ecology↗

bioRxiv2025

MALER: a web server to build, evaluate, and apply machine learning models for numerical biomedical data analysis

The explosive growth of numerical biomedical data poses a challenge in uncovering meaningful insights within from vast omics and clinical data. In recent years, machine learning has emerged as a powerful tool for processing and dissecting numerical biomedical data, making it a popular choice for addressing analytical challenges in biomedical research. Nevertheless, the intricate algorithms and complex optimization processes of machine learning model frameworks have deterred numerous non-machine learning experts. To address the need for comprehensive signatures exploration in biomedical field, we have developed Maler (http://www.inbirg.com/maler/home), a platform designed to facilitate the effortless and efficient application of machine learning models to high-dimensional biomedical data for bioscientists. Maler primarily offers four machine learning modes and a variety of machine learning algorithms to accommodate diverse analysis requirements. Simultaneously, it employs multiple feature selection methods to acquire relevant features and selects the optimal combinations of features based on machine learning models to achieve the best predictive outcomes. Maler is expected to provide a user-friendly and efficient platform for marker discovery, catering to the needs of biologists and clinical experts.

bioinformatics↗

bioRxiv2025

A synergistic generative-ranking framework for tailored design of therapeutic single-domain antibodies

Single-domain antibodies (sdAbs) have emerged as powerful therapeutic agents due to their small size, high stability, and superior tissue penetration. However, unlike conventional monoclonal antibodies (mAbs), sdAbs lack an Fc domain, limiting their functional versatility and manufacturability. To address this challenge, we developed TFDesign-sdAb, a deep learning-based generative-ranking framework that enables rational engineering of sdAbs with tailored functionalities. Our framework integrates a structure-aware diffusion model (IgGM) for large-scale candidate generation and a fine-tuned sorter (A2binder) that evaluates and prioritizes them based on predicted functionality. Unlike traditional CDR-focused approaches, TFDesign-sdAb optimizes both complementarity-determining regions (CDRs) and framework regions (FRs), allowing sdAbs to acquire new functional properties while maintaining antigen specificity. We validated our approach by conferring Protein A binding to human VHs and nanobodies that originally lacked this feature, achieving high expression rates, strong binding affinities, and successful purification via industry-standard Protein A affinity chromatography. High-resolution structural characterization (1.49 [A] and 2.0 [A]) of the redesigned sdAb-Protein A complexes revealed conserved FR-mediated binding motifs that recapitulate natural Fc-Protein A interactions, validating the accuracy of our model. Furthermore, our pipeline streamlined the antibody engineering process, achieving a 100% success rate in generating Protein A-binding sdAbs while maintaining their original antigen-binding affinity. This work demonstrates the power of AI-driven design in overcoming long-standing limitations in antibody engineering and presents a scalable, generalizable solution for enhancing sdAb functionality.

bioinformatics↗

bioRxiv2025

Glycosylation-enabled Site-specific Growth Factor Engineering for Biomaterial Functionalization

In native tissue environments, growth factors (GFs) are often physically associated with the extracellular matrix (ECM) framework. Despite the enormous potential of the chemoselective click chemistry for GF functionalization of biomaterials to recapitulate such GF-ECM association, its application is limited by the lack of a universal strategy for reliable production of clickable GFs. Here we present a novel platform technology that leverages intrinsic post-translational protein glycosylation to enable site-specific metabolic engineering of GFs with azido tags for subsequent ECM hydrogel conjugation. Using Vascular Endothelial Growth Factor as a model, we demonstrated efficient, glycosylation-dependent azido incorporation during its recombinant expression with preserved bioactivity. We further expanded the utility of this strategy to non-glycosylated proteins through engineered N-linked glycosylation via the incorporation of a signal peptide that directs newly synthesized proteins to the secretory pathway where glycosylation takes place along with a sequon for glycan attachment. The resulting GF with site-specific azido incorporation can be effectively immobilized within dibenzocyclooctyne-bearing ECM hydrogel via the copper-free click chemistry, exhibiting sustained GF retention and delivering augmented angiogenic responses. Our approach thereby offers an unprecedented opportunity to streamline recombinant protein engineering for biomaterial functionalization in tissue engineering and regenerative medicine applications.

bioengineering↗

bioRxiv2025

FASN Inactivation-induced Progranulin (GRN) Expression Promotes Lysosome-dependent Cell Death to Suppress Leukemogenesis

Cancer cells rely on lipogenesis in addition to exogenous lipid uptake, and fatty acid synthase (FASN) is aberrantly overexpressed in myeloid leukemia. However, the precise role of FASN in leukemogenesis in vivo remains elusive. Here, we demonstrated that FASN is essential for leukemogenesis. Ablation of FASN impeded leukemic cell growth, survival, clonogenicity in vitro, and the leukemic burden in vivo. Conditional knockout of FASN barely affected hematopoiesis but significantly attenuated the leukemic progression of MLL-AF9 transplants. By screening a library of platensimycin derivatives, we identified compound MS-C19 as a potent FASN inhibitor. Pharmacological targeting of FASN by MS-C19 suppressed leukemic cell growth and clonogenicity in clinical AML blasts. Mechanistically, both MS-C19 treatment and FASN deficiency triggered the activation of lysosomal and inflammatory gene expression. Loss of FASN led to lysosomal membrane permeabilization and subsequent lysosome-associated cell death, but not lysosome biogenesis. We further identified that GRN, a lysosomal and neuroinflammatory gene, was potently transcribed by TFEB upon FASN loss. Depletion of GRN significantly reversed the inhibitory effects caused by FASN knockdown. Our work demonstrates that FASN is a therapeutic target for myeloid leukemia, and inactivation of FASN by the lead compound MS-C19 provides an alternative approach for leukemic intervention. Key PointsO_LIGenetic ablation of FASN induces apoptosis, impedes leukemia cell growth, and improves the survival of leukemic xenografts. C_LIO_LITargeting FASN by the compound MS-C19, a derivative of the natural microbe antibiotic platensimycin, reduces the cell survival of leukemic cell lines, the clinical leukemic blasts, and MLL-AF9 transformed murine leukemic cells. C_LIO_LIFASN inhibition induces lysosome-dependent cell death that relies on Progranulin (GRN) expression. C_LI

cancer biology↗

bioRxiv2025

Linking Brain Entropy to Molecular and Cellular Architecture in Psychosis

Brain entropy reflects the complexity of intrinsic activity and has been linked to both cognitive function and psychiatric disorders. Yet its connection to the brains neurochemical and cellular architecture remains poorly understood. By integrating molecular imaging with neuroimaging datasets, we show that the spatial distribution of cell types, neurotransmitter systems, and mitochondrial phenotypes is systematically related to brain entropy. We observed significant differences in entropy correlations: between healthy controls and individuals with schizophrenia for the mu-opioid and dopamine D1 receptors, and between controls and individuals with bipolar disorder for the norepinephrine transporter (NAT) and N-methyl-D-aspartate (NMDA) receptor. No significant differences emerged between schizophrenia and bipolar disorder in the neurotransmitter domain. At the cellular and metabolic level, both control-schizophrenia and control-bipolar comparisons revealed widespread alterations involving most mitochondrial markers, glial cells, and inhibitory neurons. These patterns point to disruptions in energy metabolism, neuroinflammatory processes, and inhibitory regulation within the clinical groups. Overall, the findings indicate that brain entropy is not randomly distributed but is closely tied to specific neurochemical systems and cellular features. This systems-level view helps explain how the complexity of brain activity arises from molecular architecture, and how it is altered in psychiatric disorders. It also provides a biological foundation for understanding brain entropy in the context of psychosis.

neuroscience↗

bioRxiv2025

APPLE-MS: A affinity purification-mass spectrometry method assisted by PafA-mediated proximity labeling

While affinity purification-mass spectrometry (AP-MS) has significantly advanced protein-protein interaction (PPI) studies, its limitations in detecting weak, transient, and membrane-associated interactions remain. To address these challenges, we introduced an innovative proteomic method termed Affinity Purification coupled Proximity LabEling-Mass Spectrometry (APPLE-MS), which combines the high specificity of Twin-Strep-tag enrichment with PafA-mediated proximity labeling. This method achieves unprecedented sensitivity while maintaining high specificity (4.07-fold over AP-MS). APPLE-MS also revealed the dynamic mitochondrial interactome of SARS-CoV-2 ORF9B during antiviral responses, while endogenous PIN1 profiling uncovered novel roles in DNA replication. Notably, APPLE-MS enabled in situ mapping of GLP-1 receptor complexes, demonstrating its unique capabilities for membrane PPI studies. This versatile method advances interactome research by providing comprehensive, physiologically relevant PPI networks, opening new opportunities for mechanistic discovery and therapeutic targeting. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/652320v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@aaf55borg.highwire.dtl.DTLVardef@1d25af1org.highwire.dtl.DTLVardef@150c1acorg.highwire.dtl.DTLVardef@db0d1c_HPS_FORMAT_FIGEXP M_FIG C_FIG MOTIVATION - Cell Reports Methods onlyAffinity purification-mass spectrometry (AP-MS) has become a widely used method for capturing high-affinity protein-protein interactions (PPIs). However, it still faces several limitations, including high levels of non-specific binding, challenges in detecting weak interactions, and limited ability to identify PPIs at the cell surface in situ. To overcome these challenges, we introduce a modular AP-MS method enhanced by PafA-mediated proximity labeling, which improves both the specificity and sensitivity of PPI detection in a single, streamlined workflow. SIGNIFICANCE - Cell Chemical Biology onlyProximity labeling is a powerful tool in chemical biology, providing critical support for studying protein function, cell signaling, and disease mechanisms by chemically labeling and capturing biomolecular interactions. In this study, we introduce a modular affinity purification-mass spectrometry (AP-MS) method that integrates proximity labeling. This method leverages the proximity-dependent enzymatic activity of PafA to covalently attach PupE to nearby proteins, in combination with the high-affinity interaction between Twin-Strep-tag and streptavidin to achieve efficient binding. This innovative approach enables precise identification of protein-protein interactions (PPIs), offering a powerful tool for capturing weak and transient interactions that are often missed by traditional AP-MS techniques. By enhancing both the specificity and efficiency of protein labeling, our work provides a robust chemical biology strategy to elucidate complex protein interactions, which are essential for understanding cellular processes and developing targeted therapeutic strategies, offering new insights into protein function and interaction dynamics in both health and disease.

biochemistry↗

bioRxiv2025

Resolving Inflammation: The Impact of Antiretroviral Therapy on Macrophage Traffic In and Out of the CNS.

The effect of antiretroviral therapy (ART) and therapy interruption on myeloid cell traffic out of the central nervous system (CNS) with human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV) infection are understudied. Using intracisternal (i.c.) injection of dual-colored fluorescent superparamagnetic iron oxide nanoparticles (SPION) in SIV-infected macaques early (12-14 dpi) and late (30 days before sacrifice) we studied CNS macrophage viral infection, turnover, and traffic out. SPION are preferentially taken up by perivascular, meningeal, and choroid plexus macrophages. In non-infected macaques, SPION+ macrophages can traffic out of the CNS to the periphery (deep cervical lymph node (dcLN), spleen, and dorsal root ganglia (DRG)), but accumulate in the CNS with SIV infection. ART reduces the accumulation of CNS SPION+ perivascular macrophages but not meningeal or choroid plexus macrophages. ART interruption does not affect the number of SPION+ perivascular and choroid plexus but the number of SPION+ meningeal macrophages increase. ART eliminates SIV-RNA perivascular macrophages, but few scattered RNA+ macrophages in the meninges and choroid plexus remain. With ART interruption, perivascular macrophages remain SIV-but scattered SIV+ meningeal and choroid plexus macrophages exist. In non-infected animals SPION+ macrophages traffic to dcLN, spleen, and DRG at a rate that is decreased with SIV infection and AIDS. SIV- RNA+ SPION+ macrophages that traffic out of the CNS are eliminated by ART and do not rebound with ART interruption. Using two different colored SPION to study the establishment of CNS SIV viral reservoirs, we find greater numbers of early SPION+ macrophages within and outside of the CNS with SIVE, ART, and ART interruption. These data are consistent with SIV-infected perivascular macrophages establishing an early viral reservoir, and continual viral seeding of the meninges and choroid plexus during infection. These findings are consistent with ART reducing traffic of infected macrophages out of the CNS, clearing the CNS perivascular macrophage viral reservoir but not SIV-RNA+ macrophages in meninges and choroid plexus that can rebound with ART interruption.

immunology↗

bioRxiv2025

Identification of immune-mitophagy related gene in PD based on single-cell sequencing and Mendelian randomization

Parkinsons disease (PD) involves dysregulated mitophagy and immuneresponses, though the underlying mechanisms remain unclear. To identify key genes linking these pathways, we integrated single-cell RNA sequencing (GSE157783) with Mendelian randomization(MR) analysis, screening mitophagy-related genes (MRGs) and immune-related genes (IRGs). Differential expression analysis across PD cell subpopulations, combined with MR, revealed four causal genes: SLC11A1and DDX17(protective) and MRAS and PDIA3(risk). These genes were enriched in antigen presentation and calcium signaling pathways and exhibited dynamic expression in astrocytes and microglia during differentiation. Subsequent protein-protein interaction(PPI) network, regulatory (SCENIC), and drug-target analyses further characterized their roles. Validation in MPTP-induced PD mice confirmed behavioral deficits and altered expression of these genes, supporting their functional relevance. Our findings highlight SLC11A1, DDX17, MRAS, and PDIA3 as critical mitophagy-immune hubs in PD, offering mechanistic insights and therapeutic targets. Author SummaryPD is a neurodegenerative disorder linked to mitochondrial dysfunction (mitophagy) and immune dysregulation, yet the interplay between these mechanisms remains poorly understood. Using integrative single-cell sequencing and MR analyses, we identified four key genes-SLC11A1, DDX17, MRAS, and PDIA3-that bridge immune and mitophagy pathways in PD pathogenesis. These genes exhibit causal relationships with PD risk, offering novel insights into diagnostic and therapeutic strategies.

genetics↗

bioRxiv2025

Identification of the role of SEL1L in platelet function through a multi-species genetic investigation

SEL1L is a well-known protein in the endoplasmic reticulum associated degradation (ERAD) pathway. While it is known to be expressed in platelets, SEL1L has never been shown to play an active role. Here we find evidence that SEL1L regulates platelet function. We first identified SEL1L through the study of Atypical Equine Thrombasthenia (AET), an autosomal recessive platelet disorder found in Thoroughbred horses. A missense variant in SEL1L (c.1810A>G p.Ile604Val) was found in AET-affected horses, which we show is associated with decreased protein expression. SEL1L is intracellular in equine platelets and localizes to the surface upon activation with thrombin. Platelets from homozygous horses exhibit significant decreases in spreading on immobilized collagen. Human megakaryocytes were found to have two SEL1L protein isoforms that increase in expression during megakaryopoiesis, although only one is delivered to mature platelets. Studies using inducible mouse and constitutive zebrafish knockouts demonstrate that SEL1L is necessary for efficient platelet or thrombocyte (fish equivalent) adhesion to sites of endothelial injury. These data reveal a previously undescribed and conserved role for the ERAD pathway in the etiology of AET and platelet function, which may play a role in human platelet disorders as well. Brief SummaryUsing a multi-species approach, SEL1L was determined to have a role in platelet function, specifically in helping platelets properly adhere to sites of injury,

genetics↗

bioRxiv2025

Single-Shot Design of a Cyclic Peptide Inhibitor of HIV-1 Membrane Fusion with EvoBind

HIV evades the immune system through rapid mutation of its surface proteins, particularly the envelope glycoprotein. However, the core mechanism of viral entry, CD4 binding and co-receptor engagement remains conserved. While therapies such as Lenacapavir represent important advances, the continued emergence of resistant strains will demand new and more adaptable treatment strategies. This challenge is not unique to HIV; future pandemics will likely present similar pressures, highlighting the need for drug design methods that are not only effective but also fast and scalable. Recent advances in protein structure prediction have transformed the landscape of therapeutic design, enabling the accurate modelling of target structures from sequence alone and now facilitating the development of novel therapeutics without prior structural data. EvoBind leverages these advances to rapidly generate cyclic peptide binders in a single design round, using only the amino acid sequence of a target protein. Cyclic peptides offer several advantages over traditional linear protein molecules, including increased stability, while their small size improves oral bioavailability and enables access to challenging binding sites. Here, we demonstrate the use of EvoBind to generate cyclic peptide binders against the HIV envelope protein gp41, which is essential for viral-host membrane fusion. Cell-based assays confirm potent inhibition of two different HIV-1 strains with no detectable toxicity. The combination of artificial intelligence-guided design and streamlined experimental validation can significantly accelerate therapeutic development, reduce costs, and provide timely solutions to the challenges posed by viral evolution and emerging global health threats.

pharmacology and toxicology↗

bioRxiv2025

NOTCH1 Acts as a Tumor Suppressor That Induces Early Differentiation in Head and Neck Cancer

We identified frequent inactivating notch1 mutations in HNSCC over a decade ago, indicating its role as a tumor suppressor--unlike its oncogenic function in leukemias and salivary gland tumors. However, there has been much debate in the literature regarding a possible oncogenic role in HNSCC as well, based on reports that notch1 signaling drives tumor growth and a cancer stem cell phenotype in some HNSCC tumor lines and patient samples. Clarifying whether NOTCH1 occasionally functions as an oncogenic driver in HNSCC is crucial to the prognosis and personalized therapy of patients with either wild-type or mutated NOTCH1. Here we present a systematic and comprehensive investigation unequivocally demonstrating that notch1 signaling functions as a tumor suppressor in HNSCC regardless of mutation or activation status and leads to reduction in frequency of cancer stem cells. We develop a robust gene expression signature of notch1 activation based on experimental data that when applied to patient samples shows notch1 signaling is associated with very early differentiation, an altered tumor microenvironment, and better prognosis-- consistent with a tumor suppressive role. Our work unifies the field by reconciling conflicting data and providing critical insights into the biological and clinical significance of the NOTCH1 pathway in HNSCC.

cancer biology↗

bioRxiv2025

Key genes and pathways in asparagine metabolism in Alzheimers Disease: a bioinformatics approach

BackgroundAsparagine (Asn) metabolism is essential for maintaining cellular homeostasis and supporting neuronal energy demands. Recent studies have suggested its dysregulation may contribute to Alzheimers disease (AD) pathogenesis; however, the specific genes and regulatory mechanisms involved remain incompletely understood. MethodsFour publicly available microarray datasets (GSE5281, GSE29378, GSE36980, and GSE138260) were utilized to investigate genes with differential expression between control and AD samples. Asparagine metabolism-related genes (AMGs) were retrieved from the GeneCards database, and their intersection with DEGs yielded candidate asparagine metabolism-related differentially expressed genes (AMG-DEGs). Functional enrichment analysis (Gene Set Enrichment Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes), protein-protein interaction (PPI) network analysis, and centrality scoring identified hub genes. Regulatory mechanisms were investigated through construction of competing endogenous RNA and transcription factor networks. Potential therapeutic compounds were predicted via drug-gene enrichment and evaluated using molecular docking simulations. ResultsThirty-nine AMG-DEGs were identified and found to be enriched in neurodevelopmental, synaptic transmission, and inflammatory signaling pathways. PPI analysis and centrality screening revealed seven hub genes (HPRT1, GAD2, TUBB3, GFAP, CD44, CCL2, and NFKBIA). Regulatory network analysis highlighted specific miRNAs, long non-coding RNAs, and transcription factors involved in their modulation. Drug screening and docking identified Bathocuproine disulfonate, DL-Mevalonic acid, and Phenethyl isothiocyanate as promising compounds with strong binding affinities to hub proteins. ConclusionThis study comprehensively maps the dysregulation of asparagine metabolism in Alzheimers disease and reveals a set of hub genes and regulatory elements potentially involved in disease progression. The predicted therapeutic compounds provide a foundation for further experimental validation and may contribute to the development of novel metabolism-targeted strategies for AD treatment.

neuroscience↗

bioRxiv2025

Robust Bayesian Integrative Modeling of Single Cell and Spatially Resolved Transcriptomics Data

A recent technology breakthrough in spatially resolved transcriptomics (SRT) has enabled comprehensive molecular characterization at the cellular level while preserving spatial information. However, many SRT technologies (e.g., spatial transcriptomics) cannot achieve single-cell resolution. Instead, they measure the average gene expression of a mixture of cells within a spot arranged on a lattice. Here, we introduce iMOSCATO, a fully Bayesian model that integrates single-cell RNA sequencing (scRNA-seq) data and SRT data to simultaneously decompose cell-type compositions of spots and identify the underlying spatial domains. We incorporate the lattice structure by employing a Markov random field prior, improving the accuracy of both cell-type deconvolution and spatial domain detection. Moreover, we use a zero-inflated Dirichlet distribution to capture cell-type sparsity. Finally, iMOSCATO shows competitive performance in accuracy compared to existing methods in both simulation studies and two real data applications.

bioinformatics↗

bioRxiv2025

Heme-NO dilates arteries via mobilization of NO moieties from a vascular intracellular NO store

Nitrosyl heme (heme-NO) has recently emerged as a surrogate signaling entity for nitric oxide (NO). However, questions remain about how heme-NO signals across the cell membrane. Herein, we test the hypothesis that heme-NO signals as a nitrodilator that vasodilates by mobilizing NO moiety from a nitrodilator-activated intracellular NO store (NANOS) in the vasculature. We identify a novel mechanism for glutathione-catalyzed formation of a model compound, alb-heme-NO, and determine glutathione (GSH) as a ligand in its structure. Heme-NO complexes with plasma proteins in blood and, as such, it is impermeable to red blood cells or the vascular wall. Alb-heme-NO-mediated vasodilation, both in vitro and in vivo, is attenuated by prior depletion of the NANOS and potentiated by NANOS supplementation. Incubation with alb-heme-NO induces efflux of NO moieties from arteries. Additionally, the role of nitrosyl hemoglobin (HbNO) in mediating NO bioactivity export from erythrocytes is challenged. In conclusion, heme-NO functions as an extracellular nitrodilator via activation of the intracellular NANOS.

physiology↗