Biology subjects

Huang, H.-Y.

Publications and source records attributed to Huang, H.-Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Targeting the sinusoidal-to-capillarized transition to normalize vessels in breast cancer liver metastasis

Liver metastases exhibit marked resistance to anti-VEGF anti-angiogenic therapies, yet the underlying mechanisms remain poorly understood. By combining single-cell RNA sequencing of human breast cancer liver metastases with a liver sinusoidal endothelial cell (LSEC) lineage-tracing mouse model, we show that liver metastasis-associated vessels originate from Lyve1+ sinusoidal endothelial cells but undergo a sinusoidal-to-capillarized transition as they grow into the metastatic nodule, characterized by enhanced inflammatory signaling, loss of sinusoidal markers, and acquisition of capillarized markers. We functionally perturbed each of these abnormalities individually. Unexpectedly, ectopic Lyve1 overexpression paradoxically enhanced hyaluronan and other extracellular matrix deposition in the tumor microenvironment, suggesting a compensatory mechanism. Similarly, targeting TNF signaling, a hallmark inflammatory pathway in liver metastasis, dampened the inflammatory state of metastasis-associated vessels but promoted metastatic outgrowth, indicating that TNF blockade is not a viable strategy for metastasis treatment. Strikingly, inhibition of the capillary tip cell marker Esm1 improved vessel perfusion and enhanced chemotherapeutic drug delivery, two defining features of vascular normalization. Pan-cancer analysis further revealed that Esm1 expression is restricted to tip cells and correlates with poor patient prognosis, positioning Esm1 as a candidate target for promoting vascular normalization. Collectively, our findings reveal the vascular plasticity of liver metastasis and, although not all abnormal features are actionable, we propose targeting Esm1 to inhibit sprouting angiogenesis and to normalize dysfunctional liver metastasis vessels, offering a promising therapeutic avenue for liver malignancies.

cancer biology↗

bioRxiv2026

MetExPred: A Comprehensive Prediction Framework with Protein-Context-Aware Multi-view Learning for Drug Metabolism and Excretion

Within the ADMET continuum, metabolism and excretion (ME) form a critical bridge between drug exposure established by absorption and distribution and downstream efficacy and toxicity. However, no existing framework for drug ME prediction has simultaneously achieved broad coverage of endpoints and robust data recency and completeness. Here, we developed MetExPred, a multi-view prediction framework that comprises 17 classification endpoints and two regression endpoints, covering the overall drug ME process. The framework combines sequence-based and graph-based molecular representations, while optionally incorporating ESM-2 protein representations when experimentally annotated targets are available. A protein-aware masking strategy enables the same architecture to operate in both molecular-only and target-enhanced settings, and multi-view attention adaptively integrates the available representations. Across the classification tasks, MetExPred achieved mean AUROC, AUPRC and F1 scores of 0.844, 0.734 and 0.697, respectively. For clearance and half-life prediction, the model achieved RMSE values of 0.686 and 0.668. MetExPred showed the strongest average performance among the evaluated baselines, while ablation studies confirmed the complementary contributions of molecular sequence, graph and protein information. These results provide a unified and flexible modeling framework for systematic ME prediction of drug compounds, enabling early-stage virtual screening and pharmacokinetic assessment during lead optimization.

bioinformatics↗

bioRxiv2026

MIRCID: Inferred Hub-miRNAs Drive Cross-Task Improvements in Drug Mechanistic Modeling

Drug mechanism-of-action (MoA) modeling commonly relies on perturbational transcriptomes, but matched microRNA (miRNA) measurements are often unavailable. Inferred regulatory features offer a scalable way to reuse these data. Here, we present MIRCID, a framework comparing gene expression with inferred transcription factor (TF) activity and miRNA expression across pathway classification and similarity-based MoA retrieval. HubmiRNet infers 414 pan-cancer hub miRNAs (HubmiRs) from 977 L1000 landmark genes, achieving a Pearson correlation coefficient of 87.72\%; its 1,298-output variant also outperformed SiCmiR on the full-miRNA task (71.21\% versus 67.30\%). In the evaluated comparisons, miRNA augmentation provided more consistent gains than TF activity. Generic embedding controls showed model-dependent utility, while complementarity analyses identified a distinct, partially linearly recoverable representation that retained gene-derived structure. Illustrative rescue cases linked improved classification to biologically plausible miRNA patterns in samples with weak transcriptional signatures. These findings support inferred HubmiRs as a biologically informed recoding of transcriptomic data for perturbational drug modeling, while leaving recovery of measured perturbational miRNA responses to further validation.

bioinformatics↗

bioRxiv2026

A natural glycolipid exposes the outer membrane interface as a tunable regulator of bacterial surface attachment.

Surface attachment initiates bacterial colonization and biofilm formation, yet remains difficult to target owing to redundant and species-specific mechanisms. Here we identify dalberoside, a natural glycolipid that inhibits adhesion by non-disruptive remodeling of the Gram-negative outer membrane interface. Dalberoside inhibited Pseudomonas aeruginosa and Acinetobacter baumannii attachment and biofilm formation without measurable bactericidal activity or membrane permeabilization. It reduced P. aeruginosa retention on epithelial cells, delayed P. aeruginosa cytotoxicity and rapidly detached surface-associated A. baumannii. High-resolution microscopy of a fluorescent analogue and in situ cryo-electron tomography support a model in which dalberoside associates with the bacterial outer membrane, remodeling its outer leaflet. Biophysical measurements further indicated altered local interfacial properties. Thus, dalberoside reveals the outer membrane interface as a chemically addressable regulator of bacterial surface attachment.

microbiology↗

bioRxiv2026

Dual inhibition of GTP-bound (ON) and GDP-bound (OFF) KRASG12C suppresses PI3Kα and leads to potent tumor inhibition

Current approved KRASG12C inhibitors covalently bind the inactive GDP-bound (OFF) form of KRASG12C. Recently, KRASG12C inhibitors that selectively bind to the GTP-bound (ON) form of both KRASG12C (ON) and (OFF) forms have been reported and entered clinical testing. In principle, KRASG12C (ON) inhibitors may be less susceptible to adaptive mechanisms that promote resistance to (OFF) inhibitors, however the specific mechanisms that differentiate the activity of (ON) versus (OFF) inhibition are not well understood. We profiled the activity of BBO-8520, a covalent dual inhibitor of GTP-bound (ON) and GDP-bound (OFF) KRASG12C, in KRASG12C-mutant non-small cell lung cancer models. BBO-8520 exerted more potent and sustained inhibition of KRASG12C and anti-tumor activity in vitro and in vivo compared with sotorasib, a KRASG12C (OFF)-only inhibitor. While cells treated with BBO-8520 or sotorasib both exhibited feedback reactivation of MAPK signaling driven by wild-type HRAS/NRAS isoforms, more durable suppression of KRASG12C by BBO-8520 was associated with decreased PI3K-AKT activation in vitro. Disruption of the interaction between RAS and PI3K using a novel protein:protein interaction inhibitor suppressed PI3K-AKT activation and increased the tumor response to sotorasib to a similar level as BBO-8520. Moreover, in some contexts, disruption of RAS-PI3K further increased the anti-tumor activity of BBO-8520 monotherapy. These results reveal mechanistic differences between KRAS (ON) and (OFF) inhibitors, highlight the importance of PI3K-AKT signaling in driving resistance to KRAS inhibition in lung cancer, and suggest combination strategies that suppress PI3K-AKT to improve the response to KRAS inhibitors.

cancer biology↗

bioRxiv2026

The Receptor Kinase MEE39/ATHE Mediates Cell Wall Integrity Surveillance During Root Vascular Pathogen Infection

Plant cell wall (CW) integrity signaling enables early detection of microbial invasion, yet the receptors involved and their spatial and temporal dynamics during infection remain largely unknown. We identify ATHENA (ATHE)/MEE39, a previously uncharacterized malectin-like leucin-rich repeat receptor kinase (Mal-LRR-RK) that contributes to defense against the root vascular pathogen Fusarium oxysporum (Fo), particularly in outer root layers where colonization begins. ATHE abundance, localization, and endocytic trafficking are rapidly remodeled during infection, and loss of ATHE compromises basal immunity and early pathogen-induced transcriptional reprogramming. ATHE responds to altered cellulose synthesis, cellulose-derived oligosaccharides, mechanically induced CW perturbations, and the fungal secreted peptide Fo-RALF. In most of these contexts, ATHE acts together with the LRR-RK MIK2, forming a pathogen-strengthened RK complex that fine-tunes root responses to Fo. This represents the first example of a receptor complex visualized subcellularly in vivo during a plant-microbe interaction. Although Brassicaceae-specific, heterologous expression of ATHE enhanced tomato resistance to Fo, highlighting its functional relevance across plant lineages and its potential use for crop engineering. Our work reveals a previously unrecognized strategy by which plants decode microbial threats through dynamic CW-integrity surveillance.

plant biology↗

bioRxiv2026

The Red Rice Bran Extract (RRBE) Mitigates Photoaging by Targeting Mitochondrial Oxidative Stress and Regulating Thermal Damage Responses

The photoprotective efficacy of natural skin-active complexes is well recognized, yet their ap-plication is often hindered by the challenge of deciphering their complex, multi-component, and multi-target mechanisms. To bridge the gap between established phenotypes and molecular mechanisms, we developed an AI-driven integrated platform that combines phytochemical profiling, network pharmacology, and deep learning-based target prediction with rigorous biophysical validation. We applied this platform to investigate RRBE, a bioactive complex refined from red rice bran extract. In vivo clinical studies confirmed that RRBE significantly accelerates the resolution of UV-induced erythema, while cellular and 3D tissue models demonstrated robust suppression of oxidative stress and DNA damage responses. To decode its material basis, the platform deconstructed RRBE into 10 distinct chemical modules. Leveraging our SCOPE-DTI deep learning model for global target prediction, we identified flavonoids (Module 1) and phenolic acids (Module 10) as the primary bioactive drivers relevant to photoprotection. These computational predictions were structurally supported by molecular docking and definitively validated in a physiological environment via Cellular Thermal Shift Assay-Mass Spectrometry (CETSA-MS). Mechanistically, RRBE functions through a synergistic polypharmacology: (1) Module 1 components, represented by procyanidin B2, target NDUFA7 to stabilize mitochondrial function and mitigate ROS; (2) Module 10 components, exemplified by caffeic acid, ferulic acid, and p-coumaric acid, engage FKBP11 and HSP90AA1 to regulate protein homeostasis and stress responses. This work not only deciphers the polypharmacological basis of RRBEs photoprotective action but also validates a scalable "AI-guided, cell-validated" discovery pipeline, offering a rational paradigm for uncovering the protective benefits of complex natural extracts.

systems biology↗

bioRxiv2025

DeepADR: Multi-modal Prediction of Adverse Drug Reaction Frequency by Integrating Early-Stage Drug Discovery Information via Kolmogorov-Arnold Networks

Adverse drug reactions (ADRs) are a major cause of clinical trial failure and post-market withdrawal, posing significant risks to public health and impeding drug development. While computational methods offer an alternative to costly preclinical testing, existing models often fail with novel compounds by requiring pre-existing information such as drug-ADR associations or by inadequately integrating diverse data sources. Here, we introduce DeepADR, a multi-modal deep learning framework for predicting both the occurrence and frequency of ADRs using early-stage, readily available data. DeepADR integrates chemical structures and biological target profiles with semantic representations of ADR terms derived from a large language model. These heterogeneous parameters are fused using a Kolmogorov-Arnold Network (KAN), which effectively models complex, non-linear cross-modal interactions to capture underlying toxicological mechanisms. Our model outperforms existing methods in predicting both ADR occurrence and frequency, demonstrating robust generalization to new chemical entities. By effectively integrating chemical, biological, and semantic datasets, DeepADR provides a powerful, scalable tool for the early-stage safety assessment and candidate prioritization. This framework not only facilitates the prioritization of safer drug candidates but also offers a methodology for predicting the toxicity of other hazardous materials, holding significant promise for advancing public health.

bioinformatics↗

bioRxiv2025

Imputation Disparities Driven by Recent Selectionand Their Impact on Disease Risk Estimation in East and Southeast Asian Populations

Using genotype data consisting of 8,316 individuals, we systematically evaluated imputation performance across six state-of-the-art reference panels for Chinese and Thai populations. A substantial proportion of variants identified through whole-genome sequencing, especially low-frequency variants, remained undetected by existing reference panels. In the Chinese population, the TOPMed panel required an R2 threshold of 0.60-0.70 to achieve comparable imputation accuracy of the ChinaMAP panel without R2 filtering, challenging the standard practice of applying a fixed R2 threshold for downstream analyses. Regional analysis highlighted the role of recent selection in imputation discrepancies and revealed an enrichment of immune-related genes in poorly imputed regions. In addition, we showed that the selection of reference panels and R2 thresholds could significantly influence estimation of polygenic risk score for disease prediction. These findings underscore the importance of developing ancestrally diverse reference panels and provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations.

genomics↗

bioRxiv2025

Rigid Control of Motor Unit Firing Rates in the Human Tibialis Anterior Muscle Persists during Neurofeedback

The conventional framework of motor-unit (MU) control assumes that MUs in a MU pool are constrained by a fixed recruitment order and a common input. This rigid-control framework has been challenged by recent findings suggesting that MU activity could be flexibly modulated, potentially mediated by descending cortical inputs. In this study, rather than evaluating flexibility from the perspective of recruitment thresholds, we investigated control flexibility by assessing if human participants can voluntarily modulate MU firing rates beyond rigid-control constraints. Specifically, we examined whether participants could voluntarily modulate the firing rates of a pair of MUs from the tibialis anterior muscle during real-time feedback. Two tasks involving target-reach with different visual feedback derived from the MUs firing rates were conducted. In both tasks, there was no evidence that participants were able to change MU firing rates in a way that would violate rigid control robustly. Our findings demonstrate limited flexibility in MU control in human tibialis anterior muscle within single-session training, even when real-time MU activity feedback was provided. The results suggest that MU flexibility is not inherently present in the human lower limb.

neuroscience↗

bioRxiv2024

Connection Building Method: High-Accuracy MicroRNA Target Prediction Using Disease Semantic Strings

MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, inhibiting translation, or promoting mRNA degradation. miRNAs are of great importance in the development of various diseases. Currently, numerous sequence-based miRNA target prediction tools are available, however, only 1% of their predictions have been experimentally validated. In this study, we propose a novel approach that leverages disease similarity degree between miRNAs and genes as a key feature to further refine human sequence-based predicted miRNA target interactions (MTIs). To quantify the similarity degree of diseases, we fine-tuned the Sentence-BERT model. Our method achieved an F1 score of 0.88 in accurately distinguishing human protein-level experimentally validated MTIs (functional MTIs, validated through western blot or reporter assay) and predicted MTIs. Moreover, this method exhibits exceptional generalizability across different databases. We applied the proposed method to analyze 1,220,904 human MTIs sourced from miRTarbase, miRDB, and miRWalk, encompassing 6,085 genes and 1,261 pre-miRNAs. Our model was trained in miRTarBase 2022. However, we accurately identified 90% (518/574) of the updated functional MTIs in miRTarbase 2025. This study has the potential to provide valuable insights into the understanding of miRNA-gene regulatory networks and to promote advancements in disease diagnosis, treatment, and drug development.

bioinformatics↗

bioRxiv2024

Availability of an inflammatory macrophage niche drives phenotypic and functional alterations in Kupffer cells

Inflammatory signals lead to recruitment of circulating monocytes and induce their differentiation into disease-associated macrophages1-3. Therefore, whether blocking inflammatory monocytes can mitigate disease progression is being actively evaluated4. Here, we employed multiple lineage tracing models and confirmed that monocyte-derived macrophages (mo-macs) are the major population of liver metastasis-associated macrophages (LMAMs), while the population of Kupffer cells (KCs), liver-resident macrophages, is diminished in liver metastatic nodules. Paradoxically, genetic ablation of mo-macs resulted in only a marginal decrease in LMAMs. Using a proliferation recording system and a KC tracing model in a monocyte-deficient background, we found that LMAMs can be replenished either via increased local macrophage proliferation or by promoting KC infiltration. After occupying macrophage niches left vacant by monocyte depletion, KCs exhibit substantial phenotypic and functional alterations through epigenetic reprogramming. These data suggest that dual blockade of monocytes and macrophages could be used to effectively target immunosuppressive myelopoiesis and to reprogram the microenvironment towards an immunostimulatory state.

immunology↗

bioRxiv2023

Genetic diversity of domestic cat hepadnavirus in Taiwan

Domestic cat hepadnavirus (DCH) is an infectious disease associated with chronic hepatitis in cats, suggesting a similarity with hepatitis B virus infection in humans. Since its first identification in Australia in 2018, DCH has been reported in several countries with varying prevalence rates, but its prevalence in Taiwan has not yet been investigated. Here, we aimed to identify the presence and prevalence of DCH infections in Taiwan. Among 71 samples tested, eight (11.27%) were positive for DCH. Of these positive cases, three cats had elevated levels of alanine transaminase (ALT) and aspartate transaminase (AST), suggesting an association between DCH infection and chronic hepatitis. Four DCH-positive samples were also tested for feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) co-infection, one (25%) was positive for FIV while none for FeLV (0%). In addition, we performed whole genome sequencing of six samples to determine the viral genome sequences. Phylogenetic analyses identified a distinct lineage compared with previously reported sequences. Considering the recent findings suggesting the potential risk of DCH for interspecies or zoonotic transmission, this study suggests the importance of continuous surveillance of DCH and further research to elucidate the pathophysiology and transmission route of DCH.

genetics↗

bioRxiv2023

The natural tannins oligomeric proanthocyanidins and punicalagin are potent inhibitors of infection by SARS-CoV-2 in vitro

The COVID-19 pandemic continues to infect people worldwide. While the vaccinated population has been increasing, the rising breakthrough infection persists in the vaccinated population. For living with the virus, the dietary guidelines to prevent virus infection are worthy of and timely to develop further. Tannic acid has been demonstrated to be an effective inhibitor of coronavirus and is under clinical trial. Here we found that two other members of the tannins family, oligomeric proanthocyanidins (OPCs) and punicalagin, are also potent inhibitors against SARS-CoV-2 infection with different mechanisms. OPCs and punicalagin showed inhibitory activity against omicron variants of SARS-CoV-2 infection. The water extractant of the grape seed was rich in OPCs and also exhibited the strongest inhibitory activities for viral entry of wild-type and other variants in vitro. Moreover, we evaluated the inhibitory activity of grape seed extractants (GSE) supplementation against SARS-CoV-2 viral entry in vivo and observed that serum samples from the healthy human subjects had suppressive activity against different variants of SARS-CoV-2 vpp infection after taking GSE capsules. Our results suggest that natural tannins acted as potent inhibitors against SARS-CoV-2 infection, and GSE supplementation could serve as healthy food for infection prevention. HighlightsO_LIOPCs and Punicalagin had inhibitory activity against omicron variants of SARS-CoV-2 infection. C_LIO_LIOPCs serve as a dual inhibitor of the viral Mpro and the cellular TMPRSS2 protease. C_LIO_LIPunicalagin possesses the most potent activity to suppress the Mpro and block the interaction of the viral spike protein and human ACE2. C_LIO_LIOPCs-enriched grape seed extractant exhibited inhibitory activities for viral entry of wild-type and other variants of SARS-CoV-2. C_LIO_LIThe daily intake of grape seed extractants may be able to prevent SARS-CoV-2 infection. C_LI

microbiology↗

bioRxiv2022

Mechanisms of AGO4 slicing-enhanced RNA-directed DNA methylation

RNA-directed DNA methylation in plants is guided by 24 nt siRNAs generated in parallel with 23 nt RNAs of unknown function. We show that 23 nt RNAs function as passenger strands during 24 nt siRNA incorporation into AGO4. The 23 nt RNAs are then sliced into 11 and 12 nt fragments, with 12 nt fragments remaining associated with AGO4. Slicing recapitulated with recombinant AGO4 and synthetic RNAs reveals that siRNAs of 21-24 nt, with any 5 terminal nucleotide, can guide slicing, with sliced RNAs then retained by AGO4. In vivo, RdDM target locus RNAs that copurify with AGO4 also display a sequence signature of slicing. Comparing plants expressing slicing-competent versus slicing-defective AGO4 shows that slicing elevates cytosine methylation levels at virtually all RdDM loci. We propose that siRNA passenger strand elimination and AGO4 tethering to sliced target RNAs are distinct modes by which AGO4 slicing enhances RNA-directed DNA methylation.

molecular biology↗

bioRxiv2022

Structural basis of transcriptional activation by the OmpR/PhoB-family response regulator PmrA

PmrA, an OmpR/PhoB-family response regulator, activates gene transcription responsible for polymyxin resistance in bacteria by recognizing promoters in which the canonical -35 element is replaced by the pmra-box, representing the PmrA recognition sequence. Here, we report a cryo-electron microscopy-derived structure of a bacterial PmrA-dependent transcription activation complex (TAC) containing a PmrA dimer, an RNA polymerase {sigma}70-holoenzyme (RNAPH), and the pbgP promoter DNA. Our structure reveals that the RNAPH mainly contacts the PmrA C-terminal DNA binding domain (DBD) via electrostatic interactions and reorients the DBD three base pairs upstream of the pmra-box, resulting in a dynamic TAC conformation. In vivo assays show that substitution of PmrA DNA-recognition residues eliminated its transcriptional activity, but variants with altered RNAPH-interacting residues exhibited elevated transcriptional activity. Our study indicates that both PmrA recognition-induced DNA distortion and PmrA promoter escape play important roles in its transcriptional activation.

biophysics↗

bioRxiv2022

Epitranscriptomic Modification of MicroRNA Increases Atherosclerosis Susceptibility

Emerging evidence indicates that oxidative stress causes the hydroxylation of guanine (G) to generate 8-oxo-7,8-dihydro guanosine (8OH-G) in microRNAs (miRs), which induces the guanine-to-uracil (G-to-U) transversion and thus changes the miR targetomes. However, whether and how the 8OH-G-modified miRs are involved in vascular endothelial dysfunction and atherogenesis were unexplored. Using 8OH-G crosslinking immunoprecipitation miR sequencing (8OH-G CLIP-miR-seq), we found that 8OH-G miR-483 were among the most enriched 8OH-G miR species in ECs induced by ox-LDL. Transcriptomic profiling by RNA-seq indicated that the G-to-U transversion of miR-483 altered the original mRNA targeting efficacy and allows 8OH-G miR-483 to recognize new mRNA target sites. A reduced ratio of 8OH-G miR-483 to miR-483 in lung ECs was found in the endothelial-specific miR-483 transgenic (EC-miR-483 Tg) mice. Moreover, reduction of atherosclerosis was significant in EC-miR-483 Tg mice administrated AAV8-PCSK9 and fed an atherogenic diet. In situ miR hybridization revealed an increased 8OH-G miR-483 level in the intima of human atherosclerotic arteries. Collectively, this study demonstrates that the redox burden incurred by cardiovascular risk factors is a culprit of the miR-483 to 8OH-G miR-483 transversion. Such epitranscriptomic modification of miR-483 causes endothelial dysfunction and increases atherosclerosis susceptibility via its targetomes shift.

molecular biology↗

bioRxiv2021

Impact of Glycosylation on SARS-CoV-2 Infection and Broadly Protective Vaccine Design

A major challenge to end the pandemic caused by SARS-CoV-2 is to develop a broadly protective vaccine. As the key immunogen, the spike protein is frequently mutated with conserved epitopes shielded by glycans. Here, we reveal that spike glycosylation has site-differential effects on viral infectivity and lung epithelial cells generate spike with more infective glycoforms. Compared to the fully glycosylated spike, immunization of spike protein with N-glycans trimmed to the monoglycosylated state (Smg) elicits stronger immune responses and better protection for hACE2 transgenic mice against variants of concern. In addition, a broadly neutralizing monoclonal antibody was identified from the Smg immunized mice, demonstrating that removal of glycan shields to better expose the conserved sequences is an effective and simple approach to broad-spectrum vaccine development. One-Sentence SummaryRemoving glycan shields to expose conserved epitopes is an effective approach to develop a broad-spectrum SARS-CoV-2 vaccine.

microbiology↗