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Koh, Y.

Publications and source records attributed to Koh, Y..

18 recordsLinked to original sources
bioRxiv2026

Solanum americanum Bs2 and ZAR1 homologs recognize Xanthomonas euvesicatoria effectors essential for infection.

Multiple recognition events of pathogen-secreted effectors by immune receptors confer robust disease resistance in plants. Understanding the underlying mechanisms facilitates the discovery and deployment of valuable resistance genes for crop protection. Xanthomonas euvesicatoria causes devastating bacterial spot disease in solanaceous crops but cannot infect the wild relative Solanum americanum. Here, we identified X. euvesicatoria type III effectors (T3Es) that induce cell death in S. americanum when transiently expressed in leaf. By quantifying immune responses of the S. americanum SP2273 accession to X. euvesicatoria multiple-T3E knockout mutants, we demonstrated that at least nine T3Es (AvrBs2, XopAP, XopAU, XopE1, XopJ3, XopM, XopN, XopX, and XopZ1) collectively contribute to effector-triggered immunity (ETI). Among these, AvrBs2 and XopJ3 were the primary drivers of ETI, eliciting robust cell death and defense gene expression when naturally delivered into plant cells. We next generated S. americanum lines concomitantly edited at the corresponding immune receptor loci, SaBs2 and SaZAR1 (SP2273-bz). Genetic complementation of SP2273-bz confirmed that AvrBs2 and XopJ3 are specifically recognized by each of the four SaBs2 homologs and by SaZAR1, respectively. Moreover, enhanced growth of X. euvesicatoria on the characterized SP2273-bz line indicated that both effectors are required for bacterial multiplication in S. americanum. Together, our findings provide a framework for understanding the mechanisms of ETI-mediated resistance and establish a genetic foundation for resistance breeding in solanaceous crops.

plant biology↗
bioRxiv2025

The Closed State of the Shaker Potassium Channel and the Mechanism of Voltage Activation

To understand the process of voltage activation in Kv channels, we determined the cryo-EM structure of the Shaker channel ILT mutant (V369I, I372L, S376T), known to partially decouple the gating charge movement of the voltage sensing domain (VSD) and the opening of the pore domain (PD). The structure captures a previously unobserved intermediate state in which the VSD is only partially activated while the PD remains closed. Combined with computational modeling based on AlphaFold2 predictions and molecular dynamics simulations, it is shown that VSD activation does not mechanically pull the gate open, but instead induces a dynamic shift in the population equilibrium of the VSD-PD linker, providing the basis for electromechanical coupling between the two domains.

biophysics↗
bioRxiv2025

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/673780v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@19d5d7dorg.highwire.dtl.DTLVardef@64f7eborg.highwire.dtl.DTLVardef@d08b75org.highwire.dtl.DTLVardef@173c448_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of [~]19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax(R)) and the DNA analog TAS-102 (Lonsurf(R)), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

systems biology↗
bioRxiv2025

MEG3 Enhances Survival of Developing Human Neurons with CLCN4-Linked Autophagy Impairment

Genetic variations in CLCN4, encoding the H+/Cl- exchanger CLC-4, are associated with human neurodevelopmental disorders with highly variable phenotypes. A lack of physiologically relevant models has hampered molecular understanding of pathogenic mechanisms. We now establish engineered brain organoid and neuronal cell systems to examine impacts of patient-relevant CLCN4 genetic variations. We find that CLCN4 variants reduced excitatory neuron numbers due to early-stage cell death, accompanied by altered endo-lysosomal dynamics and disrupted autophagic flux. Transcriptomic profiling showed significant downregulation of long non-coding RNA MEG3 in CLCN4-variant neurons. Restoring MEG3 expression is sufficient to rescue cellular defects and improve survival of CLCN4-variant neurons. These findings link CLCN4 dysfunction with impaired autophagy and neuronal cell death, highlighting MEG3 as a potential therapeutic target for neurodevelopmental disorders involving autophagic dysfunction.

neuroscience↗
bioRxiv2024

Sequencing analysis of Helicobacter pylori infection in gastric mucosa and its progression to gastric mucosa-associated tissue (MALT) lymphoma

IntroductionThe pathogenesis of gastric mucosa-associated tissue (MALT) lymphoma is associated with Helicobacter pylori infection. Although treatment strategies and responsiveness according to the stage of gastric MALT lymphoma have been widely reported, a detailed study of the biological carcinogenic process is still required. MethodPaired, fresh tumor-adjacent normal and gastric mucosal tissue samples from 13 patients with gastric MALT lymphoma were prospectively collected. Whole exome sequencing (WES) and whole-transcriptome sequencing (WTS) data were generated. The analysis of mutations, gene fusion, gene expression, and the microbiome was stratified by H. pylori infection and disease status. ResultsSomatic mutations in TRAF3 and TNFAIP3 were identified in H. pylori-negative gastric MALT lymphoma. Fusions involving BIRC3-MALT1 (2 samples) and TBL1XR1-TP63 (1 sample with H. pylori infection) were detected. Stepwise comparative analysis of RNA expression revealed upregulation of immune response, inflammatory responses, and the NF- {kappa}B signaling pathway in H. pylori-positive MALT lymphoma cases. Pathways associated with pathogens were upregulated in H. pylori-negative MALT lymphoma cases, suggesting that infections other than H. pylori may affect lymphomagenesis. Microbiome analysis revealed that genus_Rothia was negatively correlated with alpha diversity. ConclusionA stepwise approach using diverse stages of WTS data revealed detailed pathogenic mechanisms of gastric MALT lymphoma. Chronic inflammation following infection contributes to gastric MALT lymphomagenesis in both H. pylori positive and negative cases.

bioinformatics↗
bioRxiv2023

Single-cell RNA sequencing reveals characteristics of myeloid cells in pulmonary post-acute sequelae of SARS-CoV-2

BackgroundAlthough our understanding of the immunopathology and subsequent risk and severity of COVID-19 disease is evolving, a detailed account of immune responses that contribute to the long-term consequences of pulmonary complication in COVID-19 infection remain unclear. Few studies have detailed the immune and cytokine profiles associated with post-acute sequalae of SARS-CoV-2 infection with persistent pulmonary symptoms (PPASC). However, the dysregulation of the immune system that drives pulmonary sequelae in COVID-19 survivors and PASC sufferers remains largely unknown. ResultsTo characterize the immunological features of pulmonary PASC (PPASC), we performed droplet-based single-cell RNA sequencing to study the transcriptomic profiles of peripheral blood mononuclear cells (PBMCs) from participants naive to SARS-CoV-2 (Control) and infected with SARS-CoV-2 with chronic pulmonary symptoms (PPASC). We analyzed more than 34,139 PBMCs by integrating our dataset with previously reported control datasets (GSM4509024) cell distribution. In total, 11 distinct cell populations were identified based on the expression of canonical markers. The proportion of myeloid-lineage cells ([MLCs]; CD14+/CD16+monocytes and dendritic cells) was increased in PPASC compared to controls. MLCs from PPASC displayed up-regulation of genes associated with pulmonary symptoms/fibrosis, while glycolysis metabolism-related genes were downregulated. Similarly, pathway analysis showed that fibrosis- related (VEGF, WNT, and SMAD) and cell death pathways were up-regulated, but immune pathways were down-regulated in PPASC. In PPASC, we observed interactive VEGF ligand- receptor pairs among MLCs, and network modules in CD14+ (cluster 4) and CD16+ (Cluster 5) monocytes displayed a significant enrichment for biological pathways linked to adverse COVID- 19 outcomes, fibrosis, and angiogenesis. Further analysis revealed a distinct metabolic alteration in MLCs with a down-regulation of glycolysis/gluconeogenesis in PPASC compared to SARS- CoV-2 naive samples. ConclusionThis study offers valuable insights into the immune response and cellular landscape in PPASC. The presence of elevated MLC levels and their corresponding gene signatures associated with fibrosis, immune response suppression, and altered metabolic states suggests their potential role as a driver of PPASC.

microbiology↗
bioRxiv2023

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data

BackgroundOncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to a large number of metabolites in a cell and the presence of multiple genes associated with cancer development. ResultsHere we report the development of a computational workflow that predicts metabolite-gene-pathway sets (MGPs). MGPs present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate MGPs. A GEM is a computational model that predicts reaction fluxes at a genome scale, and can be constructed in a cell-specific manner by using omics data (e.g., RNA-seq). The computational workflow is first validated by comparing the resulting metabolite-gene (MG) pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from 17 acute myeloid leukemia samples and 21 renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the MGPs predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting MGPs is also discussed. ConclusionsValidation of the MGP-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting MGPs will help identify novel oncometabolites, and also suggest cancer treatment strategies.

systems biology↗
bioRxiv2023

Systematic analysis of disease-linked rare germline variants reveals new classes of cancer predisposing genes

Despite recent insights into cancer predisposition genes (CPGs), the contribution of rare germline variants to carcinogenesis remains unclear. Here, we examine the enrichment of rare germline variants in Mendelian disease-associated genes using PCAWG and the 1,000 Genomes Project. Using an integrative approach that considers disease classes, cellular pathways, and tissue expression profiles, we find that subsets of Online Mendelian Inheritance in Man (OMIM) genes are strong candidate CPGs. These genes were classified into five clusters suggesting diverse mechanisms underlie tumor progression. We further analyzed PAH gene which shows the strongest prevalence of rare germline variants in cancers (2.2%) compared to controls (0.7%). This enrichment was validated in two independent cancer cohorts and present the possibility of tumorigenesis by contributing immune-associated pathways. Our data argue that rare germline variants of Mendelian disease-associated genes contribute to cancer progression and suggest new CPG classifications that may underlie diverse tumorigenesis mechanisms.

bioinformatics↗
bioRxiv2023

AMLs harboring DNMT3A-destabilizing variants show increased intratumor DNA methylation heterogeneity at bivalent chromatin domains

The mechanistic link between the complex mutational landscape of de novo methyltransferase DNMT3A and the pathology of acute myeloid leukemia (AML) has not been clearly elucidated so far. A recent discovery on the catalogue of DNMT3A-destabilizing mutations throughout the DNMT3A gene as well as the oligomerization-dependent catalytic property of DNMT3A prompted us to investigate the common effect of DNMT3A-destabilizing mutations (DNMT3AINS) on the genomewide methylation patterns of AML cells. In this study, we describe the characteristics of DNMT3AINS AML methylomes through the comprehensive computational analyses on three independent AML cohorts. As a result, we show that methylomes of DNMT3AINS AMLs are considerably different from those of DNMT3AR882 AMLs in that they exhibit both locally disordered DNA methylation states and increased across-cell DNA methylation heterogeneity in bivalent chromatin domains. This increased epigenetic heterogeneity was functionally associated with heterogeneous expression of membrane-associated factors shaping stem cell niche, implying the diversification of the modes of leukemic stem cell-niche interactions. We also present that the level of methylation disorder at bivalent domains predicts the response of AML cells to hypomethylating agents through cell line- and patient-level analyses, which supports that the survival of AML cells depends on stochastic DNA methylations at bivalent domains. Altogether, our work provides a novel mechanistic model suggesting the genomic origin of the aberrant epigenomic heterogeneity in disease conditions.

cancer biology↗
bioRxiv2023

Predicting the efficacy of BH3 mimetics through the profiling of multiple protein complexes

BH3 mimetics are protein-protein interaction (PPI) inhibitors that saturate anti-apoptotic proteins in the BCL2 family to induce apoptosis in cancer cells, a prominent example of protein complex-targeting therapies. Despite the remarkable success of the BH3 mimetic ABT-199 in treating hematological malignancies, only a fraction of patients respond to ABT-199 and eventually develop resistance, necessitating the predictive biomarkers for both initial responses and resistance development. We here used the single-molecule pull-down and co-immunoprecipitation platform to quantify more than 20 different types of PPI complexes using [~]1.2x106 cells in total, revealing the rewired status of the BCL2 family PPI network. By comparing the obtained multi-dimensional data with BH3 mimetic efficacies determined ex vivo, we constructed an analysis model for ABT-199 efficacy that designates the BCL2-BAX and BCLxL-BAK complexes as the primary mediators of drug effectiveness and resistance. We then applied this model to assist in therapeutic decision-making for acute myeloid leukemia patients in a prospective manner. Our work demonstrates a capability for the extensive characterization of PPI complexes in clinical specimens, potentially opening a new avenue of precision medicine for protein complex-targeting therapies.

molecular biology↗
bioRxiv2020

Transcriptional analysis of immune modulatory genes in melanoma treated with PD-1 blockade

Abstract/SummaryWe aimed to characterize immunological features of melanoma patients treated with PD-1 blockade using tumor transcriptomic datasets. Response-dependent and response-independent predictors based on biological knowledge were investigated. Domain knowledge-driven regression-based analysis identified CEACAM1, CD40, B7-H3, and CD112 as key genes that determine the melanoma immune status. We devised the transcriptional deviance score (TDS) representing the individual sample-wise contribution to the immune network. The TDS not only showed good predictive power for immune checkpoint inhibitor (ICI) responses but also suggested specific gene interactions that determine ICI responses. Dynamic TDS changes following ICI treatment were related to long survival, indicating immune network modulation by ICIs occurred in responders. A predictive model incorporating B7-H3 and CEACAM1 expression, mutational status, clinical features, and the TDS showed excellent performance for ICI response. Thus, our approaches suggest a novel measure for the tumor immune temperature and provide insight into melanoma immunobiology. HighlightsO_LIWe applied outcome-independent and outcome-dependent methods to investigate melanoma immunobiology. C_LIO_LICEACAM1, CD40, B7-H3, and CD112 expression levels are key determinants of immune status. C_LIO_LIWe devised a TDS that could measure tumor immune network status at the individual level. C_LIO_LIIncorporating regression and correlation approaches greatly improves predictive power. C_LI

cancer biology↗
bioRxiv2020

Simultaneous, cell-intrinsic downregulation of PD-1 and TIGIT enhances the effector function of CD19-targeting CAR T cells and promotes an early-memory phenotype

CD19-targeting chimeric antigen receptor (CAR) T cells have become an important therapeutic option for patients with relapsed and refractory B cell malignancies. However, recent clinical data indicate that a significant portion of patients still do not benefit from the therapy owing to various resistance mechanisms, including high expression of multiple inhibitory immune checkpoint receptors on activated CAR T cells. Here, we report a lentiviral two-in-one CAR T approach in which two checkpoint receptors are downregulated simultaneously by a dual short-hairpin RNA (shRNA) cassette integrated into a CAR vector. Using this system, we evaluated CD19-targeting CAR T cells in the context of four different checkpoint combinations--PD-1/TIM-3, PD-1/LAG-3, PD-1/CTLA-4 and PD-1/TIGIT--and found that CAR T cells with PD-1/TIGIT downregulation uniquely exerted synergistic antitumor effects in mouse xenograft models compared with PD-1 single downregulation, and maintained cytolytic and proliferative capacity upon repeated antigen exposure. Importantly, functional and phenotypic analyses of CAR T cells as well as analyses of transcriptomic profiles suggested that downregulation of PD-1 enhances short-term effector function, whereas downregulation of TIGIT is primarily responsible for maintaining a less-differentiated/exhausted state, providing a potential mechanism for the observed synergy. The PD-1/TIGIT-downregulated CAR T cells generated from diffuse large B-cell lymphoma patient-derived T cells using a clinically applicable manufacturing process also showed robust antitumor activity and significantly improved persistence in vivo compared with conventional CD19-targeting CAR T cells. Overall, our results demonstrate that the cell-intrinsic PD-1/TIGIT dual downregulation strategy may prove effective in overcoming immune checkpoint-mediated resistance in CAR T therapy.

immunology↗
bioRxiv2020

Ultra-fast Prediction of Somatic Structural Variations by Reduced Read Mapping via Pan-Genome k-mer Sets

Genome rearrangements often result in copy number alterations of cancer-related genes and cause the formation of cancer-related fusion genes. Current structural variation (SV) callers, however, still produce massive numbers of false positives (FPs) and require high computational costs. Here, we introduce an ultra-fast and high-performing somatic SV detector, called ETCHING, that significantly reduces the mapping cost by filtering reads matched to pan-genome and normal k-mer sets. To reduce the number of FPs, ETCHING takes advantage of a Random Forest classifier that utilizes six breakend-related features. We systematically benchmarked ETCHING with other SV callers on reference SV materials, validated SV biomarkers, tumor and matched-normal whole genomes, and tumor-only targeted sequencing datasets. For all datasets, our SV caller was much faster ([≥]15X) than other tools without compromising performance or memory use. Our approach would provide not only the fastest method for largescale genome projects but also an accurate clinically practical means for real-time precision medicine.

bioinformatics↗
bioRxiv2020

Non-canonical immune response to the inhibition of DNA methylation via stabilization of endogenous retrovirus dsRNAs

5-Aza-2'-deoxycytidine, also known as decitabine, is a DNA-methyltransferase inhibitor (DNMTi) used to treat acute myeloid leukemia (AML). Decitabine activates the transcription of endogenous retroviruses (ERV), which can induce an immune response by acting as cellular double-stranded RNAs (dsRNAs). Here, we employ an image-based screening platform to identify dsRNA-binding factors that mediate the downstream effect of ERV induction. We find that Staufen1 (Stau1) knockdown decreases the interferon signature and rescues decitabine-mediated cell death. Moreover, Stau1 directly binds to ERV RNAs and stabilizes them, together with a long non-coding RNA TINCR. We further show that TINCR enhances the interaction between Stau1 and ERV RNAs. Analysis of a clinical patient cohort reveals that AML patients with low Stau1 and TINCR expressions exhibits inferior treatment outcomes to the DNMTi therapy. Our study reveals that decitabine-mediated cell death is a consequence of complex interactions among different dsRNA-binding proteins for access to their common dsRNA targets. HIGHLIHGTSO_LIImage-based RNAi screening reveals multiple dsRBPs regulate response to decitabine C_LIO_LIStau1 binds to ERV RNAs and affects their stability and subcellular localization C_LIO_LITINCR binds to Stau1 and enhances Stau1-ERV interactions C_LIO_LIAML/MDS patients with low Stau1 and TINCR expressions show poor response to DNMTis C_LI

molecular biology↗
bioRxiv2018

Oncogenic effects of germline mutations in lysosomal storage disease genes

Clinical observations have indicated that patients with Gaucher disease or Fabry disease are at increased risk of cancer. However, a systematic evaluation of the oncogenic effects of causal mutations of lysosomal storage diseases (LSDs) has been lacking. Here we report a comprehensive association analysis between potentially pathogenic germline mutations in LSD genes and cancer interrogating genomic (or exomic) variant datasets derived from the Pan-Cancer Analysis of Whole Genomes project (case cohort), the 1000 Genomes project (primary control cohort), and the Exome Aggregation Consortium that does not include The Cancer Genome Atlas subset (validation control cohort). We show that potentially pathogenic variants (PPVs) in 42 LSD genes are significantly enriched in cancer patients in a histology-dependent manner, cancer risk is higher in individuals with a greater number of PPVs, and cancer develops earlier in PPV carriers. Analysis of tumor genomic and transcriptomic data from the pancreatic adenocarcinoma cohort revealed potential mechanisms that might be involved in the oncogenic contribution of PPVs. Our findings extend the mechanistic understanding of inherited cancer susceptibility and highlight the promise of harnessing available therapeutic strategies to restore lysosomal function for personalized cancer prevention.

genetics↗
bioRxiv2018

Immuno-genomic PanCancer Landscape Reveals Diverse Immune Escape Mechanisms and Immuno-Editing Histories

Immune reactions in the tumor micro-environment are one of the cancer hallmarks and emerging immune therapies have been proven effective in many types of cancer. To investigate cancer genome-immune interactions and the role of immuno-editing or immune escape mechanisms in cancer development, we analyzed 2,834 whole genomes and RNA-seq datasets across 31 distinct tumor types from the PanCancer Analysis of Whole Genomes (PCAWG) project with respect to key immuno-genomic aspects. We show that selective copy number changes in immune-related genes could contribute to immune escape. Furthermore, we developed an index of the immuno-editing history of each tumor sample based on the information of mutations in exonic regions and pseudogenes. Our immuno-genomic analyses of pan-cancer analyses have the potential to identify a subset of tumors with immunogenicity and diverse background or intrinsic pathways associated with their immune status and immuno-editing history.

genomics↗
bioRxiv2017

LPP3 mediates self-generation of chemotactic LPA gradients by melanoma cells

Melanoma cells steer out of tumours using self-generated lysophosphatidic acid (LPA) gradients. The cells break down LPA, which is present at high levels around the tumours, creating a dynamic gradient that is low in the tumour and high outside. They then also migrate up this gradient, creating a complex and evolving outward chemotactic stimulus. Here we introduce a new assay for self-generated chemotaxis, and show that raising LPA levels causes a delay in migration rather than loss of chemotactic efficiency. Knockdown of the lipid phosphatase LPP3 - but not its homologues LPP1 or LPP2 - diminishes the cells ability to break down LPA. This is specific for chemotactically active LPAs, such as the 18:1 and 20:4 species. Inhibition of autotaxin-mediated LPA production does not diminish outward chemotaxis, but loss of LPP3-mediated LPA breakdown blocks it. Similarly, in both 2D and 3D invasion assays, knockdown of LPP3 diminishes melanoma cells ability to invade. Our results demonstrate that LPP3 is the key enzyme in melanoma cells breakdown of LPA, and confirm the importance of attractant breakdown in LPAmediated cell steering.

cancer biology↗