Biology subjects

Lee, J.

Publications and source records attributed to Lee, J..

At least 217 records · Page 12Linked to original sources

bioRxiv2025

Allosteric Disordering of eIF2B Regulates the Integrated Stress Response

The ternary complex (TC), composed of translation initiation factor eIF2, GTP, and initiator methionyl tRNA, delivers the first amino acid to the ribosome to initiate protein synthesis. The activity of the decameric eukaryotic initiation factor 2B complex (eIF2B) initiates TC assembly by catalyzing GDP to GTP exchange on eIF2, thereby setting the TC levels in the cell. Stress-induced phosphorylation converts eIF2 from the substrate of the GDP/GTP exchange reaction into an inhibitor (eIF2-P) of eIF2B. This conversion reduces the cells TC levels and induces the widespread reprogramming of translation known as the Integrated Stress Response (ISR). Here, we chart an allosteric axis running through eIF2B, revealing the importance of a protrusive -helix in its {beta}-subunit, the latch-helix, that locks onto the -subunit to induce eIF2B activity. eIF2-P binding unhooks the latch-helix, opening eIF2B, which inhibits its GDP/GTP exchange activity. Distinct viral proteins have convergently evolved to bind to eIF2B and stabilize the latch-helix-bound active state. Using these insights, we generated ISR-ACTivating compounds, ISRACTs, that stabilize eIF2B in its inhibited, unlatched state. Our study thus highlights how state-transitions in eIF2B are regulated via long-range allostery.

biochemistry↗

bioRxiv2025

Tumor-myeloid crosstalk drives therapy resistance in localized bladder cancer

Neoadjuvant cisplatin-based chemotherapy results in pathologic complete response for only a minority of patients with muscle-invasive bladder cancer (MIBC), and mechanisms of resistance and the effects of chemotherapy on the MIBC microenvironment remain incompletely understood. Here, we defined the single-cell and spatial transcriptomes of cancer and immune cells from MIBC patients with resistance to cisplatin-based chemotherapy. Tumors with persistent MIBC after chemotherapy harbored cancer cells expressing epithelial-to-mesenchymal programs that were associated with worse overall survival in independent cisplatin-treated bladder cancer cohorts. These cisplatin-resistant tumor cells were infiltrated by macrophages that upregulated tumor permissive programs defined by increased PARP14 expression in spatially resolved multicellular niches. Macrophage reprogramming through PARP14 inhibition sensitized tumors to cisplatin via downregulation of tumor cell pathways implicated in resistance. Our results demonstrate that cancer cells and macrophages cooperate to promote cisplatin resistance and identify macrophage-directed PARP14 inhibition as a novel therapeutic strategy to sensitize MIBC to cisplatin.

cancer biology↗

bioRxiv2025

Targeted degradation of pathologic tau aggregates via AUTOTAC ameliorates tauopathy

The pathogenesis of tauopathies including Alzheimers disease (AD) and progressive supranuclear palsy (PSP) involves the misfolding and aggregation of tau. Here, we employed AUTOTAC to induce the lysosomal degradation of intraneuronal tau aggregates. ATB2005A is a 734-Da chimera that simultaneously binds {beta}-sheet-rich tau aggregates and the autophagic receptor p62/SQSTM1, leading to autophagosomal sequestration and lysosomal co-degradation. In mouse models of tauopathies, orally administered ATB2005A lowered intraneuronal tau aggregates and exerted the therapeutic efficacy in neuroinflammation as well as cognition, behavior, and muscle movements. A Phase 2 clinical trial (U34401-4/2023/14) with companion dogs carrying canine cognitive dysfunction (CCD) demonstrated the efficacy of ATB2005A, as a veterinary medicine, to reverse the disease progression. ATB2005A is under Phase 1 clinical trial with human participants in Korea (202300697). These results validate AUTOTAC as a versatile platform for developing therapeutics to eradicate toxic protein aggregates in a wide range of proteinopathies.

neuroscience↗

bioRxiv2025

Empirical optimization of dual-sgRNA design for in vivo CRISPR/Cas9-mediated exon deletion in mice

CRISPR/Cas9 has transformed gene editing, enabling precise genetic modifications across species. However, existing sgRNA design prediction models based on in vitro data are difficult to generalize to in vivo contexts. In particular, approaches based on single-sgRNA design require additional filtering of in-frame mutations, which is inefficient in terms of both time and cost. In this study, we developed the first mammalian in vivo-trained prediction model to evaluate the efficiency of a dual-sgRNA-based exon deletion strategy. Using 230 editing outcomes of postnatal viable individuals, eight prediction models were constructed and evaluated based on generalized linear models and random forests. The final selected model, a Combined GLM, integrated the DeepSpCas9 score with k-mer sequence features, achieving an AUC of 0.759 (95% Confidence Interval: 0.697-0.821). Motif analysis revealed that CC sequences were associated with high efficiency and TT sequences were associated with low editing efficiency. This study demonstrates that integrating sequence-based features with existing design scores can improve sgRNA efficiency prediction in vivo. The proposed framework can be applied to the development of next-generation sgRNA design tools, with direct implications for gene therapy, effective animal model generation, and precision genome engineering. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/675005v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@12e6170org.highwire.dtl.DTLVardef@1ff2599org.highwire.dtl.DTLVardef@1fd61dborg.highwire.dtl.DTLVardef@23a426_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Clinical and molecular features of primary gliosarcoma with digital spatial whole-transcriptome analysis of glial and mesenchymal components

Gliosarcoma is a rare subtype of IDH-wildtype glioblastoma defined by mixed malignant glial and high-grade sarcomatous histological elements. Gliosarcoma is clinically managed similarly to glioblastoma and has a poor clinical outcome. The sarcoma-like regions of gliosarcoma are thought to represent extreme mesenchymal metaplasia of neoplastic glial cells. Factors contributing to this phenomenon are not completely understood. Here we report a single-institution series of 37 gliosarcomas including next-generation sequencing data on 25 cases and digital spatial whole-transcriptome analysis on 4 cases to characterize differential gene expression between glial and mesenchymal components. Gliosarcoma demographic and genetic features were compared to a cohort of 75 primary adult hemispheric IDH-wildtype non-sarcomatous glioblastomas. Patient age, tumor location, sex, and overall survival in gliosarcoma were similar to glioblastoma. Gliosarcomas showed a significantly lower rate of EGFR amplification and a higher rate of NF1 mutation compared to glioblastomas in next-generation sequencing analysis. Digital spatial whole-transcriptome analysis showed a distinct transcriptomic profile in sarcomatous regions with over-expression of genes involved in extracellular matrix development and remodeling. Selected differentially expressed transcripts were examined further by immunohistochemistry. The glial elements of gliosarcomas showed higher immunoreactivity for Chitinase-3-like protein 1 (CHI3L1) than glioblastomas, but low to absent expression within the sarcomatous elements. Lymphoid Enhancer-Binding Factor 1 (LEF1) immunoreactivity was identified within sarcomatous regions of gliosarcoma without detectable nuclear {beta}-catenin, suggesting a role for {beta}-catenin independent wingless (WNT) effector signaling in sarcomatous transformation. This study adds to the growing literature demonstrating differences in the genetic underpinning of gliosarcoma and glioblastoma, establishes feasibility of spatial transcriptomic approaches in gliosarcoma, and validates digital spatial profiling-based results as a discovery platform to identify pathways and immunohistochemical markers for further study.

pathology↗

bioRxiv2025

Near real-time data on the human neutralizing antibody landscape to influenza virus to inform vaccine-strain selection in September 2025

The hemagglutinin of human influenza virus evolves rapidly to erode neutralizing antibody immunity. Twice per year, new vaccine strains are selected with the goal of providing maximum protection against the viruses that will be circulating when the vaccine is administered [~]8-12 months in the future. To help inform this selection, here we quantify how the antibodies in recently collected human sera neutralize viruses with hemagglutinins from contemporary influenza strains. Specifically, we use a high-throughput sequencing-based neutralization assay to measure how 188 human sera collected from Oct 2024 to April 2025 neutralize 140 viruses representative of the H3N2 and H1N1 strains circulating in humans as of the summer of 2025. This data set, which encompasses 26,148 neutralization titer measurements, provides a detailed portrait of the current human neutralizing antibody landscape to influenza A virus. The full data set and accompanying visualizations are available for use in vaccine development and viral forecasting.

microbiology↗

bioRxiv2025

An integrated in silico-in vitro workflow for discovering high-affinity, selective antibodies to the KRAS(G12D)-MHC I complex

Antibodies that recognize peptide-loaded class I major histocompatibility complex (pMHC I) molecules could enable therapeutic targeting of intracellular oncogenic proteins, yet their discovery has been hampered by the small size of peptide antigens and allele-specificity. We describe an integrated in silico-in vitro workflow for generating high-affinity, selective antibodies to KRAS(G12D)10 presented by HLA-C*08:02, a clinically validated cancer neoantigen. In silico, multiple human antibody-derived variable fragments (Fvs) plausibly docked to the target pMHC were generated, followed by limited complementarity-determining region (CDR) sequence design. In vitro, CDR diversity was introduced at 3-4 positions per Fv to construct yeast surface display library for iterative selections. This workflow yielded antibodies with exclusive binding to KRAS(G12D)10/HLA-C*08:02 without cross-reactivity. Affinity maturation achieved nanomolar dissociation constants, and incorporation into chimeric antigen receptor T cells enabled specific activation against target-positive cells. This study establishes a practical design-to-function pipeline for TCR-like antibody discovery, and demonstrates the feasibility of therapeutic targeting against KRAS(G12D)-driven malignancies.

biochemistry↗

bioRxiv2025

Targeted degradation of SARS-CoV-2 via the autophagy-lysosome system using chemical mimetics of the N-degron pathway

In the N-degron pathway, ATE1 transfers the amino acid L-arginine (L-Arg) from Arg-tRNAArg to N-terminal (Nt) residues of cellular proteins. The resulting Arg/N-degrons bind the autophagic receptor p62/SQSTSM-1/Sequestosome-1 to induce lysosomal degradation of various biomaterials. Here, we demonstrate that the chemical mimetics of Arg/N-degrons, termed autophagy-targeting ligands (ATLs), can induce lysosomal degradation of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) via p62-mediated macroautophagy. In Vero E6 cells infected with SARS-CoV-2, ATLs promoted p62 self-polymerization and enhanced LC3 synthesis and lipidation, leading to viral sequestration within autophagosomes for lysosomal degradation. In transgenic mice overexpressing human angiotensin-converting enzyme 2 (ACE2), oral administration of ATL1014 inhibited viral replication and increased viability. In a Syrian hamster model, ATL1014 attenuated viral replication in the lungs and demonstrated efficacy in inflammatory lesions and pulmonary congestions. These results identify the N-degron pathway as a potential target for a host-targeting strategy (HTS) against a broad spectrum of viruses.

microbiology↗

bioRxiv2025

Predicting Organ-Specific Toxicity of Selective Androgen Receptor Modulators, using Transfer Learning on Graph Convolutional Networks

Novel Quantitative Structure-Activity Relationship (QSAR) models were constructed using Graph Convolutional Networks (GCNs), to predict Drug-Induced Liver Injury (DILI), Drug-Induced Renal Injury (DIRI) and Drug-Induced Cardiotoxicity (DICT) of Selective Androgen Receptor Modulators (SARMs) - an emerging class of performance-enhancing drugs. Prior to training on DILI, DIRI and DICT datasets, the GCN QSAR models were first pre-trained on a variety of unrelated biomedical assay datasets, as an attempt to improve model performance via transfer learning. The success of the transfer learning was mixed; model performances were measurably improved via pre-training on certain datasets, by statistically weak increases. The optimal final QSAR models achieved overall accuracy scores of 68% for DILI (no significant improvement via ensemble modelling), 76% for DIRI (improved to 77% via ensemble modelling) and 65% for DICT (improved to 67% via ensemble modelling). Application of the most optimal singular models to a dataset of 25 SARMs predicted that 21 of the 25 SARMs are either DILI-positive, DIRI-positive, or both - which raises concern, given the rising use of SARMs. All SARMs except for one were predicted as DICT-negative. A novel definition of the Applicability Domain (AD) was used, intended for close relevance to the models, via generating three-dimensional graph embeddings, for each model. Convex hulls were fitted around training data embeddings, with a {+/-}10% buffer, defining the AD as the region of embedded chemical space covered by the convex hull, for a given model. Subsequent analysis found that a majority of DILI, DIRI and DICT testing data lay within the AD, alongside a majority of the SARMs - adding consensus to the reliability of the predictions.

pharmacology and toxicology↗

bioRxiv2025

Analysis of the phosphorylation networks characterizing distinct phenotypic states in glioblastoma cell Populations

Cancer cells, including the most aggressive brain cancer, glioblastoma, can exhibit a high degree of phenotypic plasticity. However, it is not well understood whether and how distinct phenotypic states might be associated with or driven by specific signaling processes. Here, we use a novel approach to the identification of phenotype-specific signaling networks in cells undergoing the Go-or-Grow switch in populations of GBM cell lines. We find that the transition to invasive spread may be associated with the onset of DNA damage response, cell cycle arrest, and activation of the AKT-mTOR signaling. We reconstructed the large-scale signaling networks, revealing integration of diverse pathways and possible feedback interactions mediating phenotypic stability. We further show that phosphorylation outcomes may be preferentially mediated by 14-3-3 proteins, previously implicated in stress response and control of the cell cycle. Finally, we demonstrate that the phenotype-specific phospho-site signatures have predictive power for disease-free patient survival. This study paves the way for a more comprehensive understanding of phenotypic plasticity in GBM and other aggressive cancers.

systems biology↗

bioRxiv2025

High-Resolution Spatial Transcriptomics Reveals Fibroblast and Neuroimmune Microenvironments in Endometriosis Lesions

Endometriosis is a chronic, systemic, inflammatory disease characterized by the presence of endometrium-like tissue growing outside of the uterus. One of its main symptoms is chronic pain and inflammation leading to a decreased quality of life. This is a common disease, as at least one in ten female-born individuals have endometriosis. Yet the understanding of the mechanisms that drive pain symptoms and disease progression remain poorly defined. This study establishes the precise spatial transcriptomic cartography of human ovarian and peritoneal lesions, two of the most commonly found lesions. We identified shared spatial features across lesion types, including immune cell infiltration, fibroblast specific compartments surrounding epithelial glands, and distinct distributions of neuronal and macrophage subsets. We precisely defined sensory neuronal subtypes, and mapped their spatial location relative to immune cells. We further validate the epithelial-neuronal interactome, using an in vitro 3D model of peripheral sensory brain organoids co-cultured with human endometriosis epithelial and fibroblast cells. By mapping spatial cellular interactions and identifying conserved features across lesion types linked to pain, our study provides emerging insights into endometriosis pathophysiology, paving the way for the development of novel targeted therapeutic strategies.

cell biology↗

bioRxiv2025

Functional dissection of SPOP on the amino acid level reveals a comprehensive functional landscape of variants during tumorigenesis

Numerous proteins display pleiotropic functions in different clinical contexts. However, molecular mechanism underlying such effects is rarely understood. Speckle-type POZ protein (SPOP) is a typical example, exhibiting tumor-suppressing or -promoting effects in different tumor types in accordance with different amino acid changes; specifically, two distinct sets of variants in SPOP are commonly found in subsets of prostate cancer and endometrial cancer patients. To comprehensively characterize the functional landscape of SPOP alteration, we performed a deep mutational screening (DMS), elucidating the functionality of 7,933 out of 8,228 possible single amino acid changes (96.4% coverage). Leveraging the observation that overexpression of human SPOP leads to yeast growth arrest, we assessed the functionality of each variant using a yeast proliferation assay. In addition, our approach combined long-read and short-read sequencing. Finally, our DMS model enables a clear distinction of likely-loss-of-function (LoF) variants that are enriched in prostate cancers and reveals their differential characteristics in both protein structure and genetic assessments. These results demonstrate the utility of our approach in high resolution mapping and amino-acid-level interpretation of protein function. Significance statementGenetic mutations often play different roles in cancer, driving or suppressing tumor growth depending on their molecular context. The protein SPOP is a striking example that acts as either a tumor-suppressor or oncogene depending on the specific mutation and tissue. However, understanding how thousands of possible mutations alter its function has been a major challenge. Here, we applied deep mutational scanning to experimentally measure the functional effects of nearly every possible amino acid change in SPOP. This work provides the first comprehensive functional map of SPOP variants, not only advancing basic knowledge of cancer biology but also establishing a framework for interpreting patient mutations in precision medicine.

genetics↗

bioRxiv2025

O-mannosylation and protein maturation check-points represent therapeutic opportunities in BRAF fusion protein oncogenesis

Fusions between protein-coding genes are common oncogenic drivers across cancers, typically pairing a proto-oncogene with partner that does not independently drive cancer. In all therapeutically actionable fusions, the proto-oncogene is the drug target, the contributions to oncogenicity of the fusion partner have largely been ignored. We studied the role of BRAF fusion partners and found that they are necessary for transformation. In the setting of KIAA1549::BRAF, the most common fusion protein across brain tumors, we found that KIAA1549 is necessary for the oncogenicity of KIAA1549::BRAF and engenders a striking and specific dependency on the protein O-mannosyltransferase complex (POMT1/2). Specifically, we show that genetic silencing or pharmacologic inhibition of the protein O-mannosyltransferase complex (POMT1/2) reverses fusion-induced transformation, thereby representing a novel and MAPK independent therapeutic target. Furthermore, POMT1/2 is required to glycosylate and enable maturation of the K::B fusion protein. These findings represent a proof-of-concept for targeting the partners in oncogenic fusions as a potential cancer therapeutic strategy.

cancer biology↗

bioRxiv2025

Commensal taxa in gut microbiota limit antibiotic resistance during extended oral antibiotic use

Certain bacterial infections, such as those involving prosthetics, can require antimicrobial therapy over months to years, potentially increasing the burden of antimicrobial resistance. Here we longitudinally track the antimicrobial resistome in mice during continuous antibiotic dosing over 21 months. The burden of antibiotic resistance genes (ARGs) initially increases, but, surprisingly, declines in later months, approaching levels observed in untreated animals. ARG burden is regulated by taxonomy and declines as ARG-harboring taxa that initially bloom are replaced by commensals. Furthermore, we find that the dynamics of antibiotic-induced ARG burden are influenced by age-related differences in microbial taxonomy and can be removed by fecal microbiota transplantation. We show that commensals may regulate the resistome by limiting the growth of ARG-harboring taxa, thereby providing antimicrobial expansion resistance.

microbiology↗

bioRxiv2025

Updated binding model for a splicing factor, PTBP1 (Polypyrimidine Tract Binding Protein1)

RNA-binding proteins (RBPs) are central regulators of post-transcriptional gene expression, and identifying their RNA targets is essential for understanding transcriptome dynamics. Predictive computational models enable the identification of RBP binding sites from RNA sequences in silico, complementing experimental assays. We previously developed a PTBP1 binding model based on a Hidden Markov Model (HMM) that utilized overlapping nucleotide triplets but was limited due to the assumption of independence between triplets. In this study, we present an improved PTBP1 binding model using Transcription Factor Flexible Models (TFFMs), which relax this assumption and accommodate flexible-length motifs. Trained on PTBP1 CLIP-seq data from HeLa cells, the TFFM-based approach captures positional dependencies among nucleotides, consistent with known PTBP1 binding motifs, and achieves improved predictive performance. The updated model shows a stronger correlation with experimental binding affinities (r = -0.95) compared to the previous HMM (r = -0.91) and maintains specificity by correctly scoring non-binding RNA substrates. This work highlights the advantage of flexible, context-aware modeling frameworks in predicting RBP-RNA interactions and offers a more accurate tool for studying PTBP1 binding specificity.

bioinformatics↗

bioRxiv2025

EpiPred: A gene-specific machine learning model for classifying missense variants in the epilepsy-related gene STXBP1

Missense variants in the STXBP1 gene are a frequent cause of early-onset developmental and epileptic encephalopathies and related neurodevelopmental disorders, but the clinical interpretation of these variants remains a major challenge. Most reported STXBP1 missense variants are classified as variants of uncertain significance (VUS), complicating diagnosis, counseling, and patient eligibility for precision therapies. Here, we developed EpiPred, a gene-specific machine learning classifier that predicts the pathogenicity of STXBP1 missense variants by integrating computational features with empirical evidence from cellular assays. Trained on a curated set of pathogenic and benign variants, EpiPred outperformed leading global prediction tools in accuracy, sensitivity, and specificity. We validated the models predictions using functional assays that measure protein abundance, solubility, stability, and interaction with the SNARE complex partner syntaxin 1. These biochemical readouts aligned closely with model outputs and enabled reclassification of several likely misdiagnosed variants. We deployed EpiPred in an interactive web application that allows clinicians, researchers, and patients to explore predictions for all possible missense variants in STXBP1. Our approach illustrates the power of gene-specific predictive modeling combined with experimental validation to improve variant interpretation and diagnostic resolution. By identifying likely pathogenic STXBP1 variants, including those that may respond to emerging therapies such as molecular chaperones, EpiPred supports more precise genetic diagnoses and offers a generalizable framework for other clinically relevant genes in neurological disease. ONE SENTENCE SUMMARYEpiPred improves STXBP1 variant interpretation, enabling precision genetic diagnoses and promoting access to targeted precision therapies

genetics↗

bioRxiv2025

Platelets drive immune suppression and glioblastoma growth in a sex-dependent manner via PAR4 signaling

Sex differences in cancer outcome, including that of glioblastoma (GBM), are shaped by biological, hormonal, and immunological factors and impact disease progression, treatment responses, survival, and tumor microenvironment (TME) interactions. Platelets regulate the immune responses and tumor progression in many cancers, but it is not clear how they contribute to these sex-based differences by affecting the dynamics of the TME. Here, we show that GBM patients exhibit heightened platelet reactivity driven by PAR4 signaling. In murine GBM models, both pharmacological inhibition of PAR4 using BMS986120 and genetic deletion of PAR4 significantly prolong survival in females but not males. This survival advantage is estrogen dependent: it is preserved in chromosomal male-hormonal female mice within the four-core genotype model and is rescued in ovariectomized mice treated with estrogen. The survival benefit is TME specific and is mediated by platelet-driven enhancement of CD8 T cell infiltration into the tumor. Inhibition of platelet PAR4 signaling increases calcium signaling through an estrogen-dependent interaction between PAR4 and estrogen receptor {beta} (ER{beta})--a receptor interaction not previously described. PAR4-activated platelets within the TME suppress CD8 T cell function, and depletion of CD8 T cells abolishes both the tumor-induced platelet reactivity and the survival benefit conferred by PAR4 inhibition. These findings establish platelet-mediated PAR4 signaling as a critical driver of tumor progression and identify sex-specific immune responses as key to therapeutic efficacy.

cancer biology↗

bioRxiv2025

Chlamydia iron starvation links nutritional immunity to pathogen recognition

Nutritional immunity is an antimicrobial strategy that evolved to starve pathogens of essential nutrients, with death as the desired outcome. Here, we report that transient iron starvation of the obligate intracellular pathogen Chlamydia trachomatis, growing in endocervical epithelial cells, enhances pathogen recognition by the host cell through the dysregulation of a peptidoglycan (PG) remodeling enzyme, resulting in the activation of the nucleotide-binding oligomerization domain 2 (NOD2) pathway that recognizes PG fragments, increased production of tumor necrosis factor alpha (TNF) via increased activation of NF-{kappa}B, which correlated with death of infected cells. Activation of the NOD2/ NF-{kappa}B signaling axis is linked to the dysregulated overexpression of the PG remodeling enzyme AmiA and the subsequent cleavage and mislocalization of D-Ala-D-Ala analog. Inhibiting amiA transcriptional upregulation by CRISPR interference reduced pathogen recognition. We propose that nutritional immunity in general mediate abnormal expression of bacterial genes linked to pathogen-associated molecular patterns. ImportanceLimiting pathogen access to essential nutrients is the central tenet of nutritional immunity, with the outcome being severe starvation and eventual death of the pathogen. However, pathogen starvation induces several physiological changes prior to its death. They include errors in several biological processes, including metabolism and gene expression, which could lead to pathogen death. Here, we demonstrate that iron starvation of the clinically relevant human pathogen Chlamydia trachomatis significantly dysregulates the expression of a peptidoglycan remodeling amidase, AmiA to enhance chlamydial recognition by the host cell and the subsequent increased production of tumor necrosis factor and death of infected cells to the detriment of Chlamydia.

microbiology↗