Biology subjects

Lee, T.-Y.

Publications and source records attributed to Lee, T.-Y..

15 recordsLinked to original sources

bioRxiv2026

A Sequential Assembly Mechanism for Stable Cdc13 Dimerization on Telomeric DNA

The telomere-binding protein Cdc13 specifically binds to single-stranded telomeric DNA, playing a critical role in telomere protection and length regulation. While extensive biochemical, molecular biological, and genetic studies have shown that Cdc13 can form dimers or oligomers in solution and bind telomeric DNA with high specificity, the dynamic mechanism of its loading onto telomeres is less well characterized. Using two single-molecule methods, single-molecule fluorescence resonance energy transfer (smFRET) and colocalization single-molecule spectroscopy (CoSMoS), we demonstrate that Cdc13 initially loads onto telomeres as a monomer. This is followed by the recruitment of a second monomer, forming a stable Cdc13 dimer on a 12-nucleotide telomeric DNA segment. Although genetic studies suggest that monomeric Cdc13 binding alone is insufficient to maintain telomere length, it underscores the Cdc13 monomers regulatory importance in coordinating telomere synthesis and protection. This monomer-to-dimer transition provides a mechanistic basis for understanding the multi-tasked roles of Cdc13 in telomere replication and protection.

biophysics↗

bioRxiv2026

Geometry-enhanced protein language modeling enables discovery of novel antibiotic resistance genes

The global antibiotic resistome remains largely unexplored, not because antibiotic resistance genes (ARGs) are rare in the environment, but because many are evolutionarily distant from known ARGs. Current computational approaches primarily rely on sequence homology, and thus miss distant homologues. We develop GeoARG, a geometry-enhanced framework that integrates structural features with protein language models through knowledge distillation, enabling efficient large-scale screening using sequence input alone. Across multiple benchmarks, GeoARG substantially improves the detection of remotely homologous ARGs, particularly under low sequence identity and fragmented conditions. Large-scale metagenomic analysis uncovers 1,485 high-confidence ARG candidates that are highly divergent from known ARGs, expanding the phylogenetic and functional landscape of the resistome. Structural analyses further show that these candidates preserve active-site geometry and maintain stable ligand-binding configurations consistent with known resistance mechanisms. These results demonstrate that geometric constraints enable systematic expansion of the resistome and facilitate the discovery of evolutionarily distant yet functionally conserved genes. A public web server is available at https://ycclab.cuhk.edu.cn/GeoARG/.

bioinformatics↗

bioRxiv2025

TRIB2 couples UCP1 degradation to thermogenic adaptation and metabolic health

Genetic variation in TRIB2 has been associated with thermogenesis and fat accumulation, yet the underlying molecular mechanisms remain unclear. Uncoupling protein 1 (UCP1) is a key regulator of adaptive thermogenesis and energy expenditure. Here, we identified a human TRIB2 variant associated with migration patterns along latitude and environmental temperature, which destabilized its mRNA and is consistent with enhanced thermogenic capacity. We demonstrate that loss of Trib2 protects mice from diet-induced obesity, alleviates hepatic steatosis, and improves glucose tolerance and insulin sensitivity. Trib2 knockout mice exhibit elevated UCP1 expression in brown adipose tissue, leading to enhanced thermogenesis and increased heat production. Mechanistically, TRIB2 acts as a scaffold that binds UCP1 through its pseudokinase domain and recruits the E3 ligase MYCBP2, thereby promoting UCP1 ubiquitination and proteasomal degradation. Collectively, our findings reveal a previously unrecognized post-translational mechanism that regulates UCP1 stability and link TRIB2 function to both thermogenic adaptation and metabolic health, thereby highlighting TRIB2 as a potential therapeutic target for obesity and metabolic disorders.

molecular biology↗

bioRxiv2025

Impact of Peptide Initial Configuration and Membrane Composition on Melittin's Pore-Forming Ability under Unbiased All-Atom Molecular Dynamics Simulations

The rising challenge of antimicrobial resistance has accelerated the search for alternative therapeutics. Antimicrobial peptides (AMPs), a class of naturally occurring defense molecules found across diverse species, are promising candidates. Despite their potent membrane-disrupting activity, the atomic details of the pore formation process remain insufficiently understood. In this study, we employed all-atom molecular dynamics (MD) simulations to investigate the pore formation process of melittin under different initial configurations. Simulations were conducted using three different membrane systems: a pure POPC bilayer, a mammalian membrane model (DOPC:Cholesterol, 9:1), and a bacterial membrane model (DOPE:DOPG, 3:1). For each system, we examined four different starting configurations, in which six melittin peptides were arranged in a star-like pattern. Our results demonstrated that the pore formation process strongly depends on the initial peptide configuration. In one specific initial arrangement (termed as Conf.I), pore formation consistently occurred within 100 nanoseconds, regardless of membrane composition. Furthermore, the simulations revealed that pore formation was more challenging in the mammalian membrane model and even more so in the bacterial membrane model, in comparison with the pure POPC bilayer. These findings are in line with previously reported minimum inhibitory concentration (MIC) and the 50% hemolysis concentration (HC50) of melittin in the literature. Additionally, we identified lysine-7 (K7) as the key residue in determining whether a stable pore can form. In configurations where the K7 side chain formed electrostatic interactions with the phosphate group of a lipid, melittin were anchored to the membrane surface, thereby preventing pore formation. In contrast, simulations of melittin mutants K7A and K7Q showed no such anchoring effect, and thus pore formation was possible in multiple initial configurations. Notably, the K7Q mutation showed a preference for pore formation in bacterial membranes over mammalian membranes, suggesting that reducing toxicity while maintaining antimicrobial efficacy is possible.

biochemistry↗

bioRxiv2024

Resolving an unconventional non-photochemical quenching signature at the light-to-dark transition

Non-photochemical quenching (NPQ) protects photosynthetic organisms via diverse molecular players contributing at varying timescales. However, in the absence of one of the largest contributors to NPQ, energy-dependent quenching (qE), we observe an unusual but universal phenomenon: a transient increase in quenching in the dark following high light exposure. To mechanistically interrogate this light-to-dark (LtD) NPQ phenotype, we performed chlorophyll fluorescence lifetime snapshot measurements across a diverse array of Arabidopsis mutant backgrounds and chemical treatments. We found that the electrochemical gradient across the thylakoid membrane is essential for this phenomenon. Through analysis of higher-order Arabidopsis mutants, we also found that LtD NPQ is independent of the known forms of photoprotective NPQ, as well as the major and minor light-harvesting complexes (LHCII). Our results point to LtD NPQ as a photoinhibition (qI)-related, reaction center quenching with implications for photoprotection in fluctuating light.

plant biology↗

bioRxiv2024

Enhanced spatially resolved transcriptomics analysis by matching between expression profiles and spatial topology

Spatially resolved transcriptomics (SRT) quantifies gene expression covering contextual heterogeneity for the tissue section. Exploratory data analysis using SRT data sheds light on diverse biomedical research fields. We propose STForte, a pairwise graph autoencoding-based approach for SRT data analysis, which is capable of matching the information between expression profiles and spatial topology in the latent space. STForte benefits from the designed framework to provide encodings with justifiable spatial correlations for the down-stream analysis of both homogeneous and heterogeneous SRT data. Moreover, STForte can unravel the biological patterns of unobserved locations or recover deficient measurements to enable spatial enhancement. Latent encodings generated by STForte can be used to perform spatial region identification or other downstream tasks to gain biological insights and elucidate biological processes. In this work, we presented various analyses to show that STForte is scalable for analyzing SRT data under different scenarios with considerable performance.

bioinformatics↗

bioRxiv2023

Chlorophyll to Zeaxanthin Energy Transfer in Non-Photochemical Quenching: An Exciton Annihilation-free Transient Absorption Study

Zeaxanthin (Zea) is a key component in the energy-dependent, rapidly reversible, non-photochemical quenching process (qE) that regulates photosynthetic light harvesting. Previous transient absorption (TA) studies suggested that Zea can participate in direct quenching via Chlorophyll (Chl) to Zea energy transfer. However, the contamination of intrinsic exciton-exciton annihilation (EEA) makes the assignment of TA signal ambiguous. In this study, we present EEA-free TA data using Nicotiana benthamiana thylakoid membranes, including wild type and three NPQ mutants (npq1, npq4, and lut2) generated by CRISPR/Cas9 mutagenesis. Results show a strong correlation between excitation energy transfer from excited Chl Qy to Zea S1 and the xanthophyll cycle during qE activation. Notably, a Lut S1 signal is absent in the npq1 thylakoids which lack zeaxanthin. Additionally, the fifth-order response analysis shows a reduction in the exciton diffusion length (LD) from 55 {+/-} 5 nm to 38 {+/-} 3 nm under high light illumination, consistent with the reduced range of exciton motion being a key aspect of plants response to excess light.

plant biology↗

bioRxiv2023

Midbrain encodes sound detection behavior without auditory cortex

Hearing involves analyzing the physical attributes of sounds and integrating the results of this analysis with other sensory, cognitive and motor variables in order to guide adaptive behavior. The auditory cortex is considered crucial for the integration of acoustic and contextual information and is thought to share the resulting representations with subcortical auditory structures via its vast descending projections. By imaging cellular activity in the corticorecipient shell of the inferior colliculus of mice engaged in a sound detection task, we show that the majority of neurons encode information beyond the physical attributes of the stimulus and that the animals behavior can be decoded from the activity of those neurons with a high degree of accuracy. Surprisingly, this was also the case in mice in which auditory cortical input to the midbrain had been removed by bilateral cortical lesions. This illustrates that subcortical auditory structures have access to a wealth of non-acoustic information and can, independently of the auditory cortex, carry much richer neural representations than previously thought.

neuroscience↗

bioRxiv2022

Selective brain cooling monitored by CT perfusion as adjuvant therapy in a porcine model of severe ischemic stroke

Despite the advances in ischemic stroke treatment, not all patients are eligible for or fully recovered after recanalization therapies. Therapeutic hypothermia could be adjuvant therapy that optimizes the beneficial effect of reperfusion. While conventional whole-body cooling has severe adverse effects, selective brain cooling has emerged as an attractive alternative. However, clinical application is limited by the lack of optimal delivery methods and unknown treatment parameters. Optimal parameters may depend on injury levels and monitoring cerebral perfusion may provide valuable information. Here, we show that selective brain cooling via our in-house developed Vortex tube IntraNasal Cooling Instrument (VINCI), even with a clinically relevant delay in treatment, can attenuate subacute injuries in animals with severe ischemic stroke. The treatment responses of selective brain cooling were characterized by CT Perfusion (CTP). The predicted lesion volume by CTP matched the true infarct volume by histology when the brain temperature was decreased by 5{degrees}C from normothermia. More importantly, we found that global hyperemia (high cerebral blood flow) before rewarming could be an early manifestation of poor treatment outcomes. Altogether, our study shows that VINCI-enabled brain cooling could be guided by CTP imaging as adjuvant therapy for severe ischemic stroke. This work lays the groundwork toward individualized selective brain cooling. Significance StatementNot all patients suffering from ischemic stroke are eligible or fully recovered after recanalization therapies. Therapeutic hypothermia could be an adjuvant therapy, but the clinical application is hindered by the delivery methods. The optimum treatment depth and duration are also unknown, and they may depend on the injury level. We developed a non-invasive selective brain cooling device, Vortex tube IntraNasal Cooling Instrument (VINCI). The treatment responses were characterized by CT Perfusion (CTP). Global hyperemia (high cerebral blood flow) was identified and could be an early manifestation of poor treatment outcomes. Our work shows that VINCI-enabled brain cooling could be guided by CTP imaging as adjuvant therapy for ischemic stroke. This work also lays the groundwork toward individualized selective brain cooling.

neuroscience↗

bioRxiv2022

The molecular consequences of androgen activity in the human breast

The mammary gland has been extensively studied for estrogen and progesterone reactivity, but the molecular effects of androgen in the breast remain largely unexplored. Transgender men are recorded female at birth but identify as male and may undergo gender-affirming androgen therapy to align their physical characteristics and gender identity. Here we perform single cell resolution transcriptome, chromatin, and spatial profiling of androgen treated breasts from transgender men. We find male-biased androgen receptor gene targets are upregulated in cells expressing androgen receptor, and that paracrine signaling drives sex-relevant changes in other cell types. We observe an altered epithelium, shifts in immune populations, and a reduction of capillary vasculature. Finally, we find evidence of the metabolic impact of androgen and identify a gene regulatory network driving androgen-directed fat loss. This work elucidates the molecular consequences of androgen in the human breast at single cell resolution.

genomics↗

bioRxiv2021

KinasePhos 3.0: Redesign and Expansion of the Prediction on Kinase-specific Phosphorylation Sites

The purpose of this work is to enhance KinasePhos, a machine-learning-based kinase-specific phosphorylation site prediction tool. Experimentally verified kinase-specific phosphorylation data were collected from PhosphoSitePlus, UniProt, GPS 5.0, and Phospho.ELM. In total, 41,421 experimentally verified kinase-specific phosphorylation sites were identified. A total of 1380 unique kinases were identified, including 753 with existing classification information from KinBase and the remaining 627 annotated by building a phylogenetic tree. Based on this kinase classification, a total of 771 predictive models were built at the individual, family, and group levels, using at least 15 experimentally verified substrate sites in positive training datasets. The improved models were observed to be more effective than other prediction tools. For example, the prediction of sites phosphorylated by the Akt, CKT, and PKA families had accuracies of 94.5%, 92.5%, and 90.0%, respectively. The average prediction accuracy for all 771 models was 87.2%. For enhancing interpretability, the Shapley additive explanations (SHAP) method was employed to assess feature importance. The web interface of KinasePhos 3.0 has been redesigned with the goal of providing comprehensive annotations of kinase-specific phosphorylation sites on multiple proteins. Additionally, considering the large scale of phosphoproteomic data, a downloadable prediction tool is available at https://awi.cuhk.edu.cn/KinasePhos/index.html or https://github.com/tom-209/KinasePhos-3.0-executable-file.

bioinformatics↗

bioRxiv2021

Differential and synergistic effects of low birth weight and Western diet on skeletal muscle vasculature, mitochondrial lipid metabolism and insulin signaling in male guinea pigs

Low birth weight (LBW) offspring are at increased risk for developing insulin resistance, a key precursor in metabolic syndrome and type 2 diabetes mellitus. Altered skeletal muscle vasculature, extracellular matrix, amino acid and mitochondrial lipid metabolism, and insulin signaling are implicated in this pathogenesis. Using uteroplacental insufficiency (UPI) to induce intrauterine growth restriction (IUGR) and LBW in the guinea pig, we investigated the relationship between UPI-induced IUGR/LBW and later life skeletal muscle arteriole density, fibrosis, amino acid and mitochondrial lipid metabolism, markers of insulin signaling and glucose uptake, and how a postnatal high-fat, high-sugar "Western" diet (WD) modulates these changes. Muscle of 145-day-old male LBW glucose tolerant offspring displayed diminished vessel density and altered acylcarnitine levels. Disrupted muscle insulin signaling despite maintained whole-body glucose homeostasis also occurred in both LBW and WD-fed male lean offspring. Additionally, postnatal WD unmasked LBW-induced impairment of mitochondrial lipid metabolism as reflected by increased acylcarnitine accumulation. This study provides evidence that early markers of skeletal muscle metabolic dysfunction appear to be influenced by the in utero environment and interact with a high fat-sugar postnatal environment to exacerbate altered mitochondrial lipid metabolism promoting mitochondrial overload.

physiology↗

bioRxiv2021

Clinically applicable rapid susceptibility testing of multi-drug resistant Staphylococcus aureus by mass spectrometry and extreme gradient boosting machine

Multi-drug resistant Staphylococcus aureus is one of the major causes of severe infections. Due to the delays of conventional antibiotic susceptibility test (AST), most cases were prescribed by experience with a lower recovery rate. Linking a 7-year study of over 20,000 Staphylococcus aureus infected patients, we incorporated mass spectrometry and machine learning technology to predict the susceptibilities of patients for 4 different antibiotics that can enable early antibiotic decisions. The predictive models were externally validated in an independent patient cohort, resulting in an area under the receiver operating characteristic curve of 0.94, 0.90, 0.86, 0.91 and an area under the precision-recall curve of 0.93, 0.87, 0.87, 0.81 for oxacillin (OXA), clindamycin (CLI), erythromycin (ERY) and trimethoprim-sulfamethoxazole (SXT), respectively. Moreover, our pipeline provides AST 24-36 h faster than standard workflows, reduction of inappropriate antibiotic usage with preclinical prediction, and demonstrates the potential of combining mass spectrometry with machine learning (ML) to assist early and accurate prescription. Therapies to individual patients could be tailored in the process of precision medicine.

bioinformatics↗

bioRxiv2020

Rapidly predicting vancomycin resistance of Enterococcus faecium through MALDI-TOF MS spectra obtained in real-world clinical microbiology laboratory

Enterococcus faecium is one of the leading pathogens in the world. In this study, we proposed a strategy to rapidly and accurately distinguish vancomycin-resistant Enterococcus faecium (VREfm) and vancomycin-susceptible E. faecium (VSEfm) to help doctors correctly determine the use of vancomycin by a machine learning (ML)-based algorithm. A predictive model was developed and validated to distinguish VREfm and VSEfm by analyzing MALDI-TOF MS spectra of unique E. faecium isolates from different specimen types. Firstly, 5717 mass spectra, including 2795 VREfm and 2922 VSEfm, were used to develop the algorithm. And 2280 mass spectra of isolates, namely 1222 VREfm and 1058 VSEfm, were used to externally validate the algorithm. The random forest-based algorithm demonstrated good classification performances for overall specimens, whose mean AUROC in 5-fold cross validation, time-wise validation, and external validation was all greater than 0.84. For the detection of VREfm in blood, sterile body fluid, urinary tract, and wound, the AUROC in external validation was also greater than 0.84. The predictions with algorithms were significantly more accurate than empirical antibiotic use. The accuracy of antibiotics administration could be improved by 30%. And the algorithm could provide rapid antibiotic susceptibility results at least 24 hours ahead of routine laboratory tests. The turn-around-time of antibiotic susceptibility could be reduced by 50%. In conclusion, a ML algorithm using MALDI-TOF MS spectra obtained in routine workflow accurately differentiated VREfm from VSEfm, especially in blood and sterile body fluid, which can be applied to facilitate the clinical testing process due to its accuracy, generalizability, and rapidness.

microbiology↗

bioRxiv2018

Computational assessment of blood flow heterogeneity in dialysis patients’ cardiac ventricles

Dialysis prolongs life but augments cardiovascular mortality. Imaging data suggests that dialysis increases myocardial blood flow (BF) heterogeneity, but its causes remain poorly understood. A biophysical model of human coronary vasculature was used to explain the imaging observations, and highlight causes of coronary BF heterogeneity.\n\nPost-dialysis CT images from patients under control, pharmacological stress (adenosine), therapy (cooled dialysate), and adenosine and cooled dialysate conditions were obtained. The data presented disparate phenotypes. To dissect vascular mechanisms, a 3D human coronary vasculature model was implemented. Simulations were performed to investigate the effects of altered aortic pressure and blood vessel diameters on myocardial BF heterogeneity which was quantified using relative dispersion, fractal dimension, and transmural BF distribution.\n\nImaging showed that stress and therapy potentially increased mean and total BF, while reducing heterogeneity. BF histograms of one patient showed multi-modality. Using the model, it was found that total coronary BF increased as coronary perfusion pressure (CPP) was increased. BF heterogeneity was differentially affected by large or small vessel blocking. BF heterogeneity was found to be inversely related to small blood vessel diameters. Simulation of large artery stenosis indicates that BF became heterogeneous (increase relative dispersion) and gave multi-modal histograms. The total transmural BF as well as transmural BF heterogeneity reduced due to large artery stenosis, generating large patches of very low O_SCPCAPBFC_SCPCAP regions downstream. Blocking of arteries at various orders showed that blocking larger arteries results in multi-modal BF histograms and large patches of low BF, whereas smaller artery blocking results in augmented relative dispersion and fractal dimension. Transmural heterogeneity was also affected. Finally, the effects of augmented aortic pressure in the presence of blood vessel blocking shows differential effects on BF heterogeneity as well as transmural BF.\n\nImproved aortic blood pressure may lead to improved BF. Stress and therapy may be effective if they dilate small vessels. A potential cause for the observed complex BF distributions (multi-modal BF histograms) may indicate existing large vessel stenosis.\n\nThe intuitive BF heterogeneity methods used can be readily used in clinical studies. Further development of the model and methods will permit personalised assessment of patient BF status.

biophysics↗