Biology subjects

Lee, K.-H.

Publications and source records attributed to Lee, K.-H..

15 recordsLinked to original sources

bioRxiv2026

Coordinated subpocket engagement underlies nitazene potency at the μ-opioid receptor.

Nitazenes are emerging synthetic opioids that exhibit exceptionally high potency at the {micro}-opioid receptor (MOR) and contribute to rising overdose fatalities worldwide. Despite extensive in vitro profiling, the structural determinants underlying their structure-activity relationships (SARs) remain unresolved. Here, we combine functional profiling with quantum mechanical calculations and molecular dynamics (MD) simulations to establish a MOR structure-based SAR for nitazenes. Across functional assays, systematic variation at the R1, R2, and R3 positions revealed non-additive effects on potency and identified optimal R1 chain length, R2 N-desethylation, and retention of the 5-nitro group as key determinants of high MOR potency. Consistent with this framework, N-desethyl isotonitazene emerged as the most potent analogue. Structural analysis of the cryo-EM MOR-Gi-fluornitrazene complex, together with MD simulations of multiple nitazene analogues, revealed a conserved trivalent binding architecture in which each substituent engages distinct subpockets. N-desethylation at R2 increases the positive electrostatic surface at the protonated amine, reduces steric constraints near transmembrane helix (TM) 7, strengthens R3 interactions, and allosterically modulates R1 engagement in a substituent-dependent manner. Additionally, optimal R1 chain length and shape stabilize the TM5-TM6 interface and influence activation-relevant TM6 dynamics, defining a unified SAR at R1 across nitazene and fentanyl scaffolds. Together, these findings indicate that nitazene potency reflects substituent-dependent coupling among R1, R2, and R3 within the MOR binding pocket, with R3 engagement distinguishing nitazenes from fentanyl. This framework establishes a coherent structural model of nitazene-MOR recognition that accounts for their unusually high potency and efficacy.

molecular biology↗

bioRxiv2025

NeoPrecis: Enhancing Immunotherapy Response Prediction through Integration of Qualified Immunogenicity and Clonality-Aware Neoantigen Landscapes

Despite the transformative impact of cancer immunotherapy, the need for improved patient stratification remains critical due to suboptimal response rates. While neoantigens are central to anti-tumor immunity, current metrics like tumor mutation burden are limited by their neglect of immunogenicity and tumor heterogeneity. We present NeoPrecis, a computational framework designed to refine neoantigen characterization across MHC-I and MHC-II pathways and integrate tumor clonality to improve immunotherapy response prediction. NeoPrecis features an interpretable T-cell recognition model that reveals the critical influence of MHC molecules on TCR recognition beyond mere antigen presentation. Benefit HLA alleles identified through model-driven contribution analysis exhibit significant predictive power for patient outcomes in immune checkpoint inhibitor treatment (melanoma: p-value = 0.04; NSCLC: p-value = 0.01). Applying NeoPrecis to immunotherapy-treated tumors, we show the clonality-aware neoantigen landscape improves response prediction in melanoma and heterogeneous NSCLC, achieving 11% and 20% improvement of AUROC compared to TMB respectively. Heterogeneous NSCLCs, more common among never smokers, retain more subclonal neoantigens due to lower immunoediting pressure, where NeoPrecis better captures the varying prevalence of neoantigens. We propose NeoPrecis as a more comprehensive evaluative framework for neoantigen assessment by incorporating both immunogenicity and tumor clonality, offering insights into the link between collective quality of neoantigen landscapes and immunotherapy response.

bioinformatics↗

bioRxiv2024

High-coverage allele-resolved single-cell DNA methylation profiling by scDEEP-mC reveals cell lineage, X-inactivation state, and replication dynamics

DNA methylation is a relatively stable epigenetic mark with important roles in development and disease.1 Since cell-to-cell variation in epigenetic programming can reflect important differences in cell state and fate, it is clear that single-cell methods are essential to understanding this key epigenetic mark in heterogeneous tissues. Existing single-cell whole-genome bisulfite sequencing (scWGBS) methods2 have significant shortcomings, including very low CpG coverage3-7 or inefficient library generation requiring extremely deep sequencing.8 These methods offer limited insight into focal regulatory regions and generally preclude direct cell-to-cell comparisons. To address these shortcomings, we have developed an improved method, scDEEP-mC (single-cell Deep and Efficient Epigenomic Profiling of methyl-C). We show that high-coverage promoter methylation profiling by scDEEP-mC can identify multiple cell types, while allele-resolved methylation calls allow assessment of X-inactivation state in single cells and identification of transcription factor binding sites (TFBS) enriched for hemi-methylation. We also use scDEEP-mC to profile single-cell copy number alterations, identify actively replicating cells, and track DNA methylation dynamics during and after DNA replication. The high coverage of scDEEP-mC creates an exceptional opportunity to explore DNA methylation biology in individual cells.

genomics↗

bioRxiv2024

Complimentary vertebrate Wac models exhibit phenotypes relevant to DeSanto-Shinawi Syndrome

Monogenic syndromes are associated with neurodevelopmental changes that result in cognitive impairments and neurobehavioral phenotypes including autism and seizures. Limited studies and resources are available to make meaningful headway into the underlying molecular mechanisms that result in these symptoms. One such example is DeSanto-Shinawi Syndrome (DESSH), a rare disorder caused by pathogenic variants in the WAC gene. Individuals with DESSH syndrome exhibit a recognizable craniofacial gestalt, developmental delay/intellectual disability, neurobehavioral symptoms that include autism, ADHD, behavioral difficulties and seizures. However, no thorough studies from a vertebrate model exist to understand how these changes occur. To overcome this, we developed both murine and zebrafish Wac/wac deletion mutants and studied whether their phenotypes recapitulate those described in individuals with DESSH syndrome. We first show that the two Wac models exhibit craniofacial and behavioral changes, reminiscent of abnormalities found in DESSH syndrome. In addition, each model revealed impacts to GABAergic neurons and further studies showed that the mouse mutants are susceptible to seizures, changes in brain volumes that are different between sexes and relevant behaviors. Finally, we uncovered transcriptional impacts of Wac loss of function in mice that will pave the way for future molecular studies into DESSH. These studies present two new animals that begin to uncover some biological underpinnings of DESSH syndrome and elucidate the biology of Wac.

neuroscience↗

bioRxiv2024

Drosophila HCN mediates gustatory homeostasis by preserving sensillar transepithelial potential in sweet environments

Establishing transepithelial ion disparities is crucial for sensory functions in animals. In insect sensory organs called sensilla, a transepithelial potential, known as the sensillum potential (SP), arises through active ion transport across accessory cells, sensitizing receptor neurons such as mechanoreceptors and chemoreceptors. Because multiple receptor neurons are often co-housed in a sensillum and share SP, niche-prevalent overstimulation of single sensory neurons can compromise neighboring receptors by depleting SP. However, how such potential depletion is prevented to maintain sensory homeostasis remains unknown. Here, we find that the Ih-encoded hyperpolarization-activated cyclic nucleotide gated (HCN) channel bolsters the activity of bitter-sensing gustatory receptor neurons (bGRNs), albeit acting in sweet-sensing GRNs (sGRNs). For this task, HCN maintains SP despite prolonged sGRN stimulation induced by the diet mimicking their sweet feeding niche, such as overripe fruit. We present evidence that Ih-dependent demarcation of sGRN excitability is implemented to throttle SP consumption, which may have facilitated adaptation to a sweetness-dominated environment. Thus, HCN expressed in sGRNs serves as a key component of a simple yet versatile peripheral coding that regulates bitterness for optimal food intake in two contrasting ways: sweet-resilient preservation of bitter aversion and the previously reported sweet-dependent suppression of bitter taste.

neuroscience↗

bioRxiv2024

Integrated germline and somatic features reveal divergent immune pathways driving ICB response

Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses. Statement of SignificanceImmune checkpoint blockade works only in a fraction of patients for reasons that are still not fully understood. Our study reveals heterogeneity in the immune responses of ICB responders that correlates with characteristics of the neoantigen landscape. This heterogeneity is accompanied by differences in the duration of clinical benefit as well as by differences as to which immune checkpoint gene serves as a biomarker of ICB response. These findings suggest possible new strategies for improving ICB responses. HighlightsO_LIWe used machine learning to study ICB response across 708 patients from 8 studies across 3 tumor types (melanoma, RCC, and NSCLC). C_LIO_LICombining germline and somatic features improves prediction of ICB response C_LIO_LIInteractions between germline and somatic features reveal mechanisms contributing to ICB sensitivity. C_LIO_LIMHC-I vs. MHC-II reliance implicates LAG3 as a prognostic biomarker in the context of CD4 T cell driven responses. C_LIO_LIMHC-II neoantigen reliant responses provide superior durable clinical benefit in response to ICB. C_LI

cancer biology↗

bioRxiv2023

Extracellular vesicle-mediated Transfer of miR-1 from Primary tumor Repress Metastasis Growth

Metastases originate from primary tumors that conquer distant organs. Growing evidence suggests that metastases are still under primary tumor dominance, even out of the primary territory. However, the mechanism by which primary tumors prime the fate of metastasis is unclear. Here, we investigated the influence of primary tumor-derived extracellular vesicles (pTDEs) on distant metastasis. Metastatic growth was remarkably suppressed when cells were treated with pTDEs in vitro and intravenously in a spontaneous metastatic mouse model. pTDEs from primary tumors with cancer stem cell (CSC) characteristics inhibit metastatic growth by inducing intracellular ROS/DNA double-stranded damage, thus inhibiting G2/M phase accumulation. We found that miR-1 was the most abundant in pTDEs and showed a stronger inhibitory effect when miR-1 was overloaded in pTDEs. Collectively, we demonstrated that the primary tumor could control distant metastatic cancer via primary tumor-derived EV-miR-1. Additionally, our approach suggests the development of anticancer drugs for metastasis based on pTDE-miR-1.

cancer biology↗

bioRxiv2023

PGSbuilder: An end-to-end platform for human genome association analysis and polygenic risk score predictions

Understanding the genetic basis of human complex diseases is increasingly important in the development of precision medicine. Over the last decade, genome-wide association studies (GWAS) have become a key technique for detecting associations between common diseases and single nucleotide polymorphisms (SNPs) present in a cohort of individuals. Alternatively, the polygenic risk score (PRS), which often applies results from GWAS summary statistics, is calculated for the estimation of genetic propensity to a trait at the individual level. Despite many GWAS and PRS tools being available to analyze a large volume of genotype data, most clinicians and medical researchers are often not familiar with the bioinformatics tools and lack access to a high-performance computing cluster resource. To fill this gap, we provide a publicly available web server, PGSbuilder, for the GWAS and PRS analysis of human genomes with variant annotations. The user-friendly and intuitive PGSbuilder web server is developed to facilitate the discovery of the genetic variants associated with complex traits and diseases for medical professionals with limited computational skills. For GWAS analysis, PGSbuilder provides the most renowned analysis tool PLINK 2.0 package. For PRS, PGSbuilder provides six different PRS methods including Clumping and Thresholding, Lassosum, LDPred2, GenEpi, PRS-CS, and PRSice2. Furthermore, PGSbuilder provides an intuitive user interface to examine the annotated functional effects of variants from known biomedical databases and relevant literature using advanced natural language processing approaches. In conclusion, PGSbuilder offers a reliable platform to aid researchers in advancing the public perception of genomic risk and precision medicine for human disease genetics. PGSbuilder is freely accessible at http://pgsb.tw23.org.

bioinformatics↗

bioRxiv2022

Statistically unbiased prediction enables accurate denoising of voltage imaging data

Here we report SUPPORT (Statistically Unbiased Prediction utilizing sPatiOtempoRal information in imaging daTa), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatially neighboring pixels in the same time frame, even when its temporally adjacent frames do not provide useful information for statistical prediction. Such spatiotemporal dependency is captured and utilized to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulation and experiments, we show that SUPPORT enables precise denoising of voltage imaging data while preserving the underlying dynamics in the scene.

neuroscience↗

bioRxiv2022

Integrative mapping of the dog epigenome: reference annotation for comparative inter-tissue and cross-species studies

The domestic dog has become a valuable model in exploring multifaceted diseases and biology important for human health. Large-scale dog genome projects produced high-quality draft references but still lack comprehensive annotation of encoded functional elements. Through the integrative next generation sequencing of transcriptomes paired with histone marks and DNA methylome profiling of 11 adult tissue types, implemented in a cross-species approach, we generated a reference epigenome of a domesticated dog. Using genome orthologues and synthenies, we deciphered the dogs epigenetic code by defining distinct chromatin states, allowing for genome-wide, integratable data production. We then characterized somatic super-enhancer landscapes and showed that genes mapped on these regions are associated with a broad range of biological and disease traits and are traceable to their tissue-of-origin. Ultimately, we delineated conserved epigenomic changes at the tissue- and species-specific resolutions. Our study provides an epigenomic blueprint of the dog for comparative biology and medical research.

genomics↗

bioRxiv2022

DNA Methylation Dynamics and Dysregulation Delineated by High-Throughput Profiling in the Mouse

We have developed a mouse Infinium DNA methylation array that contains 297,415 probes to capture the diversity of mouse DNA methylation biology. We present a mouse DNA methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, age, sex, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, PDX assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. ApcMin/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This MM285 mouse array is widely accessible to the research community, and will accelerate future high sample-throughput studies in this important model organism.

genomics↗

bioRxiv2021

Connecting MHC-I-binding motifs with HLA alleles via deep learning

The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performance on binding affinity. However, the decisive MHC residues and their relation to the selection of binding peptides are still unrevealed. Here, we connected HLA alleles with binding motifs via our deep learning-based framework, MHCfovea. MHCfovea expanded the knowledge of MHC-I-binding motifs from 150 to 13,008 alleles. After clustering N-terminal and C-terminal sub-motifs on both observed and unobserved alleles, MHCfovea calculated the hyper-motifs and the corresponding allele signatures on the important positions to disclose the relation between binding motifs and MHC-I sequences. MHCfovea delivered 32 pairs of hyper-motifs and allele signatures (HLA-A: 13, HLA-B: 12, and HLA-C: 7). The paired hyper-motifs and allele signatures disclosed the critical polymorphic residues that determine the binding preference, which are believed to be valuable for antigen discovery and vaccine design when allele specificity is concerned.

bioinformatics↗

bioRxiv2019

variant2literature: full text literature search for genetic variants

MotivationWhole genome sequencing (WGS) by next-generation sequencing produces millions of variants for an individual. The retrieval of biomedical literature for such a large number of genetic variants remains challenging, because in many cases the variants are only present in tables as images, or in the supplementary documents of which the file formats are diverse.\n\nResultsThe proposed tool named variant2literature from the TaiGenomics (Toolkits for AI genomics) resolves the problem by incorporating text recognition with image processing. In addition to the adoption of advanced image-based text retrieval, the recall rate of finding the literature containing the variants of interest is further improved by employing the skill of variant normalization. Different variant presentations are transformed into chromosome coordinates (standard VCF format) such that false negatives can be largely avoided. variant2literature is available in two ways. First, a web-based interface is provided to search all the literature in PMC Open Access Subset. Second, the command-line executable can be downloaded such that the users are free to search all the files in a specified directory locally.\n\nAvailabilityhttp://variant2literature.taigenomics.com/\n\nContactchienyuchen@ntu.edu.tw

genetics↗

bioRxiv2019

Physicochemical Properties of Chromosomes in Live Cells Characterized by Label-Free Imaging and Fluorescence Correlation Spectroscopy

The cell nucleus is a three-dimensional, dynamic organelle that is organized into many subnuclear bodies, such as chromatin and nucleoli. The structure and function of these bodies is maintained by diffusion and interactions between related factors as well as dynamic and structural changes. Recent studies using fluorescent microscopic techniques suggest that protein factors can access and are freely mobile in mitotic chromosomes, despite their densely packed structure. However, the physicochemical properties of the chromosome itself during cell division are not yet fully understood. Physical parameters, such as the refractive index (RI), volume of the mitotic chromosome, and diffusion coefficients of fluorescent probes inside the chromosome were quantified using an approach combining label-free optical diffraction tomography with complementary confocal laser scanning microscopy and fluorescence correlation spectroscopy. Variance in these parameters correlated among various osmotic conditions, suggesting that changes in RI are consistent with those in the diffusion coefficient for mitotic chromosomes and cytosol. Serial RI tomography images of chromosomes in live cells during mitosis were compared with three-dimensional confocal micrographs to demonstrate that compaction and decompaction of chromosomes induced by osmotic change were characterized by linked changes in chromosome RI, volume, and the mobility of fluorescent proteins.

biophysics↗

bioRxiv2018

Transcriptional activation of DBP by hnRNP K facilitates circadian rhythm.

D-site albumin promoter binding protein (DBP) supports the rhythmic transcription of downstream genes, in part by displaying high-amplitude cycling of its own transcripts compared to other circadian clock genes. However, the underlying mechanism remains elusive. Here, we demonstrated that poly(C) motif within DBP proximal promoters, in addition to an E-box element, provoked the transcriptional activation through increased RNA polymerase 2 (Pol2) recruitment by inducing higher chromatin accessibility. We also clarified that heterogeneous nuclear ribonucleoprotein K (hnRNP K) is a key regulator that binds to the poly(C) motif on single-stranded DNAs in vitro. Chromatin immunoprecipitation further confirmed the expression-dependent and rhythmic binding of hnRNP K which was inhibited through its cytosolic localization mediated by time-dependent ERK activation. Knockdown of hnRNP K triggered low-amplitude mRNA rhythms in DBP and other core clock genes through transcriptional or post-transcriptional regulation. Finally, transgenic depletion of a Drosophila homolog of hnRNP K in circadian pacemaker neurons lengthened 24-hour periodicity in free-running locomotor behaviors. Taken together, our results provide new insights into the function of hnRNP K as a transcriptional amplifier of DBP, which acts rhythmically through its intracellular localization by the ERK phosphorylation and as an mRNA stabilizer along with its physiological significance in circadian rhythms of Drosophila.\n\nSignificance StatementIn the case of mood disorders and the aging process, the mRNA expression and amplitude level of clock genes, including DBP, were reported to be diminished. However, the reason behind this decrease of clock gene amplitude and expression level remained unclear. Through this study, we revealed the regulatory mechanism behind the expression of clock genes, especially of DBP mRNA expression. In addition, we discovered that hnRNP K regulates more core clock genes than what we have previously known, such as Clock and Periods. Finally, we demonstrated the physiological significance of hnRNP K in Drosophila through its RNAi line model. Hence, our findings show the regulatory mechanism of circadian rhythm that may provide insight on mood disorder and aging process.

neuroscience↗