Biology subjects

Lu, T.

Publications and source records attributed to Lu, T..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Therapeutic Potential of 20E in Pulmonary Arterial Hypertension: Involvement of Mas Receptor and PI3K/Akt Pathway

BACKGROUND20-Hydroxyecdysone (20E), a natural polyhydroxylated steroid found in various edible plants, exhibits diverse pharmacological effects. This study aims to investigate the preventive and therapeutic effects of 20E on pulmonary arterial hypertension (PAH) and elucidate its underlying molecular mechanisms. METHODSA monocrotaline (MCT)-induced PAH rat model was utilized to evaluate the efficacy of 20E. The Mas receptor antagonist A779 and agonist AVE0991 were used to investigate the role of Mas in PAH progression and 20E-mediated prevention. Molecular docking and pull-down assays were conducted to confirm the interaction between 20E and the Mas receptor. In vitro, the effects of 20E on Ang II-induced proliferation and migration of human pulmonary arterial smooth muscle cells (HPASMCs) were assessed. The PI3K/Akt signaling pathway was analyzed by Western blot. RESULTS20E prevented PAH at 30 mg/kg and 90 mg/kg, while 90 mg/kg rescued pre-existing PAH. The protective effects of 20E were attenuated by A779. 20E upregulated Mas receptor expression and directly bound to it. In vitro, 20E inhibited Ang II-induced HPASMC proliferation and migration. It also downregulated p-PI3K, p-Akt, and p-mTOR while restoring P27 and P21 expression. Furthermore, knockdown of the Mas in HPASMCs abolished the effects of 20E on these processes. CONCLUSIONS20E inhibits PASMC proliferation and migration by activating the Mas receptor and modulating the downstream PI3K/Akt signaling pathway, thereby effectively preventing and rescuing PAH. It may be a promising pharmacological candidate for PAH treatment.

molecular biology↗

bioRxiv2025

Characterizing Complex Upper Limb Movements with and without Visual Feedback in Typically Developing Children

The development of upper limb movements has been primarily described through reaching movements, which may not have the complex motor planning and execution demands of many daily tasks. In this study, we introduced a complex task in which individuals had to navigate their hand from a start target through two openings in a simple maze to reach an end target. In half the trials, participants received visual feedback of their hand position, and in half of the trials they did not. Thirty-one participants ages 8 to 17 years completed the study. We found that with visual feedback, reaction time, number of speed peaks, movement time, and hand path length all decreased with age. Number of speed peaks, movement time, and hand path length were all increased without visual feedback, however, the impact of removing visual feedback was greatest on the younger children and decreased with age. Our results demonstrate that complex upper limb movements are refined across childhood and adolescence, with a decreasing reliance on visual feedback likely due to increasing feedforward control and improved ability to use proprioceptive feedback. This task can be applied to clinical populations such as cerebral palsy to assess impairments in motor planning and execution as well as determine how proprioceptive impairments contribute to complex movements. NEW AND NOTEWORTHYThis study used a novel paradigm to examine how children plan and execute complex upper limb movements, both when they have visual feedback of hand position available and when they do not. We show that with age, performance with visual feedback improves reflecting advancing motor planning and execution abilities. Older children were less impacted by removing visual feedback than younger children, likely due to improved feedforward control and use of proprioceptive feedback.

neuroscience↗

bioRxiv2025

Mechanisms of Activation and Serotonin release from Human Enterochromaffin Cells

Background and AimsGastrointestinal (GI) enterochromaffin (EC) cells are specialised sensors of luminal stimuli. They secrete most of the bodys serotonin (5-HT), and are critical for modulating GI motility, secretion, and sensation, while also signalling satiety and intestinal discomfort. The aim of this study was to investigate mechanisms underlying the regulation of human EC cells, and the relative importance of direct nutrient stimulation compared with neuronal and paracrine regulation. MethodsIntestinal organoids from human duodenal biopsies were modified using CRISPR-Cas9 to specifically label EC cells with either the fluorescent protein Venus or the cAMP sensor Epac1-S. EC cells were purified by fluorescence-activated cell sorting for analysis by bulk RNA sequencing and liquid chromatography mass spectrometry peptidomics. The function of human EC cells was studied using single cell patch clamp, calcium and cAMP imaging and 5-HT ELISA assays. ResultsHuman EC cells showed expression of receptors for nutrients (including GPR142, GPBAR1, GPR119, FFAR2, OR51E1, OR51E2), gut hormones (including SSTR1,2&5, NPY1R, GIPR) and neurotransmitters (ADRA2A, ADRB1). Functional assays revealed EC responses (calcium, cAMP and/or secretion) to a range of stimuli, including bacterial metabolites, aromatic amino acids and adrenergic agonists. Electrophysiological recordings showed that isovalerate increased action potential firing. Conclusions5-HT release from EC cells controls many physiological functions and is currently being targeted to treat disorders of the gut-brain axis. Studying ECs from human organoids enables improved understanding of the molecular mechanisms underlying EC cell activation, which is fundamental for the development of new strategies to target 5-HT-related gut and metabolic disorders. SynopsisHuman duodenal organoids expressing fluorescent proteins in enterochromaffin cells were used to study mechanisms underlying serotonin secretion. Different expression of key sensory receptors was identified by transcriptomic analysis, and validated by live cell second messenger imaging and secretion assays.

cell biology↗

bioRxiv2025

Tumor hypoxia adaptation depends on FLAD1 mediated mitochondrial metabolic reprogramming

Hypoxia, a hallmark of solid tumors, promotes the malignant progression and is challenging to target. Metabolic reprogramming and the resulting metabolic vulnerabilities provide a promising strategy to target tumor hypoxia. Here we systematically compared the metabolic network differences between hypoxic and non-hypoxic cells, and developed a deep learning model, "DepFormer", to predict the dependent metabolic genes in hypoxic tumor cells. The performance of DepFormer was validated using CRISPR screening dataset. Oxidative phosphorylation was identified as the most significantly hypoxia-dependent metabolic pathway, and FLAD1 was predicted to be one of the key hypoxia-dependent metabolic genes. FLAD1 locus is amplified, and FLAD1 expression is upregulated in various tumor types, especially in hypoxic tumors. FLAD1 depletion compromises tumors adaptation to hypoxia by disrupting mitochondrial complex II activity, leading to an imbalance between succinate and fumarate, and consequent failure to adapt to hypoxia. Subsequently, we identified a drug-like inhibitor of FLAD1, which selectively inhibits the growth of tumor cells under hypoxia. Our findings reveal FLAD1 as an innovative therapeutic target for hypoxic tumors.

cancer biology↗

bioRxiv2025

Single-cell copy number alteration signature analysis reveals masked patterns and potential biomarkers for cancer

Copy number alteration (CNA) is a major type of cancer genome alteration that drives cancer progression. CNA signature analysis can reveal underlying etiology and provide biomarkers for cancer treatment, and existing CNA signature analyzes are all performed using bulk tissue samples. However CNA usually affect large proportion of genome, and the CNA profile of bulk sample does not reflect the actual CNA profiles of the individual cancer cells of the sample, especially in tumors with high heterogeneity, such as hepatocellular carcinoma (HCC). Furthermore, the evolutionary trajectory of CNA mutational processes still remain elusive. Here we build a method to comprehensively analyze the CNA signatures of HCC from single-cell and bulk sample perspective, revealing patterns and potential noise signals from the usually performed bulk tissue CNA signature analysis. Single-cell signature analysis delineated the evolutionary trajectory of HCC CNA signatures, and different CNA signatures consistently emerge in different HCC evolution stages. Single-cell CNA signatures show robust performance in patient prognosis and drug sensitivity prediction. This work not only reveals specific considerations in analyzing CNA signature derived from bulk tissue but also depicts CNA evolution process and provides potential biomarkers for the prognosis and treatment of HCC patients. HighlightSingle-cell analysis reveals CNA signatures masked in bulk tissue. Single-cell analysis delineates the evolutionary trajectory of CNA signature. Small CNAs occur early and large CNAs happens late in HCC evolution. Single-cell CNA signatures show robust performance in guiding cancer clinical treatment.

genomics↗

bioRxiv2025

De novo biosynthesis of cannabinoid and its analogs in Yarrowia lipolytica

Cannabis sativa has long been a cornerstone of both medicinal and cultural practices, with its therapeutic use spanning over 2,700 years. Central to its therapeutic effects are cannabinoids, which interact with the endocannabinoid system to influence various physiological processes such as anxiety, pain, and inflammation. Despite its benefits, cannabinoid production faces challenges and scarcity from plant extraction. This work leverages Yarrowia lipolytica as a platform for cannabinoid biosynthesis. By optimizing precursor supply, engineering biomolecular condensate-like dual prenyltransferase expression and expanding endogenous metabolism with a noncanonical polyketide synthase, we achieved the de novo biosynthesis of various cannabinoid and its analogs. Our engineered Y. lipolytica produced [~]3.5 mg/L of cannabigerolic acid, 18.8 mg/L of orsellinic acid, and 0.5 mg/L of cannabigerorcinic acid. Additionally, CBGA titer reached 15.7 mg/L with olivetolic acid supplement. This work demonstrates Y. lipolyticas versatility as a promising host for cannabinoid and its analogs production, which opens avenues for further research and medicinal applications.

synthetic biology↗

bioRxiv2025

Spatial distribution of the proteome in human body and cancers

A comprehensive spatial distribution of the proteome in human body and cancers is fundamental for understanding human biology and diseases including cancers. Here, we present an anatomically resolved human proteome derived from 1781 benign and malignant samples from 58 major tissue types encompassing 251 specific tissues and 25 carcinomas. Based on a spectral library covering over 75% of the human protein-coding genes with 208 understudied and 82 missing proteins characterized, we quantified over 13,000 proteins in these samples using data-independent acquisition proteomics. This data resource presents the so far most comprehensive quantitative proteomic landscape of human tissues and common carcinomas. It allows systematic evaluation of tissue-specific drug responses, identification of drug candidates that may be repurposed as antineoplastics, and discovery of novel targets for anticancer therapy. This resource, available as an online knowledgebase, refines our knowledge of spatial distribution of the human proteome and tumor-specific protein modulation.

systems biology↗

bioRxiv2025

Unveiling Cognitive Processes in Mice through Reinforcement Learning Models in the FST and TST

Simple behavioral tests like the forced swim test (FST) and tail suspension test (TST) are widely used to assess depression-like behaviors in rodents, primarily measuring immobility time. However, this approach oversimplifies behavioral readouts and overlooks the cognitive processes driving behavior, leaving the relationship between increased immobility and cognitive biases unclear. Here, we developed the SwimStruggleTracker (SST) to extract fine-grained behavioral trajectories and integrate computational modeling to methodically analyze behavior. Our findings reveal that behavior in the FST and TST follows reinforcement learning principles involving learning, consequence perception, and decision-making. Notably, the cognitive processes underlying behavior differ between the two tests, challenging the assumption that they are interchangeable for cross-validation. Regression analyses identify distinct behavior phases: early behavior is primarily influenced by learning-related factors, while later stages are more affected by consequence sensitivity. These findings suggest traditional analyses focusing final minutes may underestimate the role of learning and overemphasize consequence sensitivity. MotivationThe forced swim test (FST) and tail suspension test (TST) are among the most widely used paradigms for assessing depression-like behaviors in rodents. Yet, traditional analyses typically quantify only immobility during the final minutes, discarding rich temporal structure in the data and hindering efforts to uncover the cognitive mechanisms underlying these behaviors. To address this gap, we developed an automated tool that captures behavioral trajectories with fine temporal resolution and integrates computational modeling to dissect the cognitive processes driving behavior. Using this approach, we demonstrate that the FST and TST engage overlapping but partially distinct cognitive processes, and that the dominant cognitive components shift across different stages of the tests. HighlightsO_LISwimStruggleTracker (SST) accurately rejects passive movements, such as pendulum-like motion. C_LIO_LIReinforcement learning models capture the behavioral dynamics of mice in the FST and TST. C_LIO_LIDistinct winning models indicate that the FST and TST engage partially dissociable cognitive processes. C_LIO_LILearning factors dominate early stages, whereas consequence-sensitivity factors dominate later stages. C_LI

animal behavior and cognition↗

bioRxiv2025

Assessing Generative Model Coverage of Protein Structures with SHAPES

Recent advances in generative modeling enable efficient sampling of protein structures, but their tendency to optimize for designability imposes a bias toward idealized structures at the expense of loops and other complex structural motifs critical for function. We introduce SHAPES (Structural and Hierarchical Assessment of Proteins with Embedding Similarity) to evaluate five state-of-the-art generative models of protein structures. Using structural embeddings across multiple structural hierarchies, ranging from local geometries to global protein architectures, we reveal substantial undersampling of the observed protein structure space by these models. We use Frechet Protein Distance (FPD) to quantify distributional coverage. Different models are distinct in their coverage behavior across different sampling noise scales and temperatures; the frequency of TERtiary Motifs (TERMs) further supports the observations. More robust sequence design and structure prediction methods are likely crucial in guiding the development of models with improved coverage of the designable protein space.

bioengineering↗

bioRxiv2025

COSIME: Cooperative multi-view integration and Scalable and Interpretable Model Explainer

Single-omics approaches often provide a limited perspective on complex biological systems, whereas multi-omics integration enables a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and interpreting complex relationships between biological features--both within and across views--remains a major challenge. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration with a Scalable and Interpretable Model Explainer). COSIME applies the backpropagation of a learnable optimal transport algorithm to deep neural networks, thus enabling the learning of latent features from several views to predict disease phenotypes. It also incorporates Monte Carlo sampling to enable interpretable assessments of both feature importance and pairwise feature interactions for both within and across views. We applied COSIME to both simulated and real-world datasets--including single-cell transcriptomics, spatial transcriptomics, epigenomics and metabolomics--to predict Alzheimers disease-related phenotypes. Benchmarking of existing methods demonstrated that COSIME improves prediction accuracy and provides interpretability. For example, it reveals that synergistic interactions between astrocyte and microglia genes associated with Alzheimers disease are more likely to localize at the edges of the middle temporal gyrus. Finally, COSIME is also publicly available as an open source tool.

bioinformatics↗

bioRxiv2024

N1-methylpseudouridine mRNA modification enhances efficiency and specificity of gene overexpression by preventing Prkra-mediated global translation repression

In vitro transcribed messenger RNA (IVT mRNA) has emerged as a pivotal tool in mRNA-based therapies and has been extensively employed in gene function studies and genetic tool applications. However, the IVT process generates double-stranded RNA (dsRNA) by-products that are recognized by dsRNA sensors, triggering innate immune responses. In this study, we comprehensively analyzed the detrimental effects of dsRNA by-products on early zebrafish embryos, revealing that these by-products induce cell necrosis and delay maternal-zygotic transition by reducing global translation efficiency via Prkra, a recently identified dsRNA sensor in pluripotent cells. Importantly, we demonstrate that N1-methylpseudouridine (m1{varphi}) modification of IVT mRNAs effectively mitigates these adverse effects, as m1{varphi}-modified dsRNAs exhibit significantly lower binding affinity to the Prkra dimer. Our findings underscore a previously overlooked challenge in the use of IVT mRNA in early embryos and offer a robust solution to enhance the fidelity of mRNA applications. Furthermore, we elucidate that m1{varphi} modification minimizes the dsRNA-induced stress response in pluripotent cells through a distinct mechanism.

developmental biology↗

bioRxiv2024

Robust fine-mapping in the presence of linkage disequilibrium mismatch

Fine-mapping methods based on summary statistics from genome-wide association studies (GWAS) and linkage disequilibrium (LD) information are widely used to identify potential causal variants. However, LD mismatch between the external LD reference panel and the GWAS population is common and can lead to compromised accuracy of fine-mapping. We developed RSparsePro, a probabilistic graphical model with an efficient variational inference algorithm, to perform robust fine-mapping in the presence of LD mismatch. In simulation studies with a varying degree of LD mismatch, RSparsePro identified credible sets with a consistently higher power and coverage than SuSiE. In fine-mapping cis-protein quantitative trait loci, RSparsePro identified credible sets with a consistently higher enrichment of variants with functional impacts and cross-study replication rates. In fine-mapping risk loci for low-density lipoprotein cholesterol in ancestry-specific GWAS, RSparsePro identified biologically relevant variants in drug target genes and implicated potential regulatory mechanisms. RSparsePro is openly available at https://github.com/zhwm/RSparsePro_LD.

bioinformatics↗

bioRxiv2024

SpaMTP: Integrative Statistical Analysis and Visualisation of Spatial Metabolomics and Transcriptomics data.

The ability to spatially measure multi-modal data provides an unprecedented opportunity to comprehensively explore molecular regulation at transcriptional, translational and metabolic levels to acquire insights on cellular activities underpinning health and disease. However, there is currently a lack of analytical tools to integrate complementary information across different spatial-omics data modalities, particularly with respect to spatial metabolomics data, which is becoming increasingly invaluable. We introduce SpaMTP, a versatile software that implements an end-to-end integrative analysis of spatial metabolomics and transcriptomics data. Based in R, SpaMTP bridges processing functionalities for metabolomics data from Cardinal with user-friendly cell-centric analyses implemented in Seurat. Furthermore, SpaMTPs comprehensive analysis pipeline covers (1) automated mass-to-charge ratio (m/z) metabolite annotation; (2) a wide range of metabolite-gene based downstream statistical analyses including differential expression, pathway analysis, and correlation analysis; (3) integrative spatial-omics analysis; and (4) a suite of visualisation functions. For flexibility and interoperability, SpaMTP includes various functions for data import/export and object conversion, enabling seamless integration with other R and Python packages. We demonstrated the utility of SpaMTP to draw new biological understandings through analysing two biological system. We believe this software and implemented methods will be broadly utilised in spatial multi-omics and spatial metabolomics analyses.

bioinformatics↗

bioRxiv2024

An integrative spatial multi-omic workflow for unified analysis of tumor tissue

Combining molecular profiling with imaging techniques has advanced the field of spatial biology, offering new insights into complex biological processes. Focusing on diffuse IDH-mutated low-grade glioma, this study presents a workflow for Spatial Multi-omics Integration, SMINT, specifically combining spatial transcriptomics and spatial metabolomics. Our workflow incorporates both existing and custom-developed computational tools to enable cell segmentation and registration of spatial coordinates from both modalities to a common coordinate framework. During our investigation of cell segmentation strategies, we found that nuclei-only segmentation, while containing only 40% of segmented cell transcripts, enables accurate cell type annotation, but does not account for multinucleated cells. Our integrative workflow including cell-morphology segmentation identified distinct cellular neighborhoods at the infiltrating edge of gliomas, which were enriched in multinucleated and oligodendrocyte-lineage tumor cells, that may drive tumor invasion into the normal cortical layers of the brain. HighlightsO_LIAlignment and integrated analysis of spatial transcriptomic and metabolomic data C_LIO_LINuclei-only and cell-morphology segmentations are concordant for cell annotation C_LIO_LISpatially distinct regions are conserved in transcriptomic and metabolomic datasets C_LIO_LIMulti-omic exploration of glioma leading edge identifies novel biological features C_LI

bioinformatics↗

bioRxiv2024

Benchmarking Bayesian colocalization methods in validating Mendelian randomization-based target discoveries from circulating proteins for cardiometabolic diseases

Mendelian randomization (MR) is an important tool for identifying potential biomarkers and drug targets. Colocalization analysis is crucial for validating MR findings and guarding against confounding due to linkage disequilibrium. We aim to benchmark the performance of four Bayesian colocalization methods in validating MR-based target discoveries from circulating proteins for cardiometabolic traits. We assessed the associations between circulating levels of 1,535 proteins and five cardiometabolic traits, followed by colocalization analyses using coloc, coloc+SuSiE, PWCoCo and SharePro. All methods demonstrated well-controlled false discoveries. SharePro demonstrated the highest frequency in supporting 160 (79.6%) of the 201 Bonferroni-significant protein-trait associations identified by MR, compared to coloc (supporting 40.3% of these associations), coloc+SuSiE (46.8%), and PWCoCo (45.8%), and was robust to varying prior colocalization probabilities. Protein-trait associations supported by SharePro were more likely to agree with significant gene-level associations identified in exome-wide association studies and implicate known drug targets. Eight protein-trait associations were exclusively supported by SharePro, suggesting potential cardiometabolic biomarkers or drug targets, such as HSF1 and HAVCR2. In summary, SharePro most often supports statistically significant associations identified through MR for cardiometabolic traits. Combining multiple lines of evidence using different methods may substantially increase the yield of biomarker and drug target discovery programs.

genetics↗

bioRxiv2024

Human Vascularized Macrophage-Islet Organoids to Model Immune-Mediated Pancreatic β cell Pyroptosis upon Viral Infection

There is a paucity of human models to study immune-mediated host damage. Here, we utilized the GeoMx spatial multi-omics platform to analyze immune cell changes in COVID-19 pancreatic autopsy samples, revealing an accumulation of proinflammatory macrophages. Single cell RNA-seq analysis of human islets exposed to SARS-CoV-2 or Coxsackievirus B4 (CVB4) viruses identified activation of proinflammatory macrophages and {beta} cell pyroptosis. To distinguish viral versus proinflammatory macrophage-mediated {beta} cell pyroptosis, we developed human pluripotent stem cell (hPSC)-derived vascularized macrophage-islet (VMI) organoids. VMI organoids exhibited enhanced marker expression and function in both {beta} cells and endothelial cells compared to separately cultured cells. Notably, proinflammatory macrophages within VMI organoids induced {beta} cell pyroptosis. Mechanistic investigations highlighted TNFSF12-TNFRSF12A involvement in proinflammatory macrophage-mediated {beta} cell pyroptosis. This study established hPSC- derived VMI organoids as a valuable tool for studying immune cell-mediated host damage and uncovered mechanism of {beta} cell damage during viral exposure.

developmental biology↗

bioRxiv2024

MR Corge: Sensitivity analysis of Mendelian randomization based on the core gene hypothesis for polygenic exposures

SummaryMendelian randomization is being utilized to assess causal effects of polygenic exposures, where many genetic instruments are subject to horizontal pleiotropy. Existing methods for detecting and correcting for horizontal pleiotropy have important assumptions that may not be fulfilled. Built upon the core gene hypothesis, we developed MR Corge for performing sensitivity analysis of Mendelian randomization. MR Corge identifies a small number of putative core instruments that are more likely to affect genes with a direct biological role in an exposure and obtains causal effect estimates based on these instruments, thereby reducing the risk of horizontal pleiotropy. Using positive and negative controls, we demonstrated that MR Corge estimates aligned with established biomedical knowledge and the results of randomized controlled trials. MR Corge may be widely applied to investigate polygenic exposure-outcome relationships. Availability and ImplementationAn open-sourced R package is available at https://github.com/zhwm/MRCorge.

bioinformatics↗

bioRxiv2024

Prkra is the double-stranded RNA sensor to mediate an embryonic integrated stress response

Double-stranded RNAs (dsRNAs), known as conserved pathogen-associated molecular patterns, are recognized by interferon-induced protein kinase R (PKR) to trigger an integrated stress response, characterized by the inhibition of global translation. However, the interferon system is inactive in pluripotent cells, thus the mechanism underlying dsRNA sensing and translational control is unclear. In this study, we utilized early zebrafish embryos as a model of pluripotent cells and discovered a PKR-independent blockage of translation initiation induced by dsRNA stimulation. Prkra dimer was identified as the genuine dsRNA sensor. Upon binding to dsRNAs, the dimerized dsRNA binding domain 3 becomes activated to sequester the eIF2 complexes from the translation machinery, leading to a hindrance in global protein synthesis. This distinctive embryonic stress response restricts RNA virus SVCV replication in zebrafish embryos but is also conserved in early mouse embryos and embryonic stem cells. Therefore, the Prkra-mediated dsRNA sensing and translation blocking mechanism potentially represents a common strategy for reestablishing physiological homeostasis in response to environmental stresses.

immunology↗