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Koh, J.

Publications and source records attributed to Koh, J..

At least 19 recordsLinked to original sources

Single-Cell and Spatial Analysis Reveals Retention of FCRL4⁺ Memory B Cells in Pediatric Tonsillar Hypertrophy

Pediatric tonsillar hypertrophy is a leading cause of sleep disordered breathing in children, yet the immune mechanisms sustaining tonsillar enlargement remain unclear. Using integrated single cell and spatial profiling of pediatric tonsils in a discovery cohort (n = 45) and independent validation cohort (n = 32), we identify a selective expansion and follicular retention of FCRL4+ memory B cells within the mantle zone of hypertrophic tonsils. These cells exhibit a quiescent, tissue-adapted phenotype characterized by NFATC1 repression and reciprocal RUNX1/RUNX2 regulation. Their accumulation is orchestrated by follicular type 1 regulatory T (Tr1) cells, which engage CTLA-4/CD86 checkpoint interactions to suppress plasma cell differentiation and reinforce a local immune tolerance program. Together, these interactions establish a persistent follicular niche enriched in regulatory FCRL4+ memory B cells. Our findings delineate a mechanistic Tr1/FCRL4+ B cell axis underlying follicular hypertrophy and highlight potential immunomodulatory targets for nonsurgical management of pediatric sleep-disordered breathing.

immunology↗

Unveiling the Hidden Rules: Enhancing NMD Prediction for Protein-Truncating Variants

Nonsense-mediated decay (NMD) is a conserved RNA quality-control pathway that degrades transcripts containing premature termination codons. Because roughly a third of pathogenic variants in ClinVar can lead to truncated protein synthesis, predicting whether such transcripts undergo NMD is central to interpreting variant effects, yet the canonical 50-55 nucleotide rule explains only about half of observed outcome variability. Using paired whole-genome and RNA-sequencing from 10,306 individual samples in the Trans-Omics for Precision Medicine (TOPMed) program, we quantified NMD efficiency for 5,749 germline truncating variants via allele-specific expression and trained a gradient-boosting classifier, TrunCat, that distinguished NMD-sensitive from NMD-escape transcripts with [~]78% ROC-AUC (Receiver Operating Characteristic - Area Under the Curve). A reduced model using the ten features with the highest mean SHAP (SHapley Additive exPlanations) value as a measure of each features average contribution to predictions nearly matched this performance. Applied across large variant databases and a rare-disease cohort, the model produced NMD outcome predictions, with variants of uncertain significance showing higher predicted escape than pathogenic ones. This framework confirms the canonical rule, identifies non-canonical determinants, and offers a scalable resource for interpreting protein-truncating variants.

genomics↗

Intron 13 retention expands the ADAR1 isoform repertoire to rewire PKR signaling and promote tumorigenesis

For decades, the biology of ADAR1 has been framed around two major isoforms: the nuclear-enriched p110 and the predominantly cytoplasmic p150. Here, we reveal an unexpected repertoire expansion of ADAR1 isoforms that is driven by intron retention. Specifically, intron 13 (I13) can be retained in ADAR1 transcripts, conferred by an evolutionarily conserved weaker 5SS. In addition, we found that the I13 retention (I13R) is negatively autoregulated by ADAR1 through antagonizing the binding of hnRNPA1 to I13 in an editing-independent manner. Despite being sensitive to nonsense-mediated decay, I13R generates two previously uncharacterized truncated isoforms - p90 and p130, that both lack the C-terminal portion of the deaminase domain. Intriguingly, ADAR1p90 - a derivative of the canonical nuclear-enriched p110 isoform - is predominantly cytoplasmic, that effectively represses PKR and eIF2 activation through the sequestration of immunogenic double-stranded RNA (dsRNA) substrates. Furthermore, in a colorectal cancer (CRC) cohort, p90 levels are increased in most tumors relative to matched normal tissues that positively correlates with hnRNPA1 expression. Functionally, xenografts expressing ADAR1p90 grow significantly faster and larger than those expressing ADAR1p110, indicating enhanced tumorigenic potential. These findings revise the canonical view of ADAR1 isoforms, demonstrating that intron retention can generate alternative isoforms with augmented functions that tumors readily exploit. One Sentence SummaryThe conserved retention of I13 in ADAR1 transcripts gives rise to previously uncharacterized C-terminal truncated cytoplasmic ADAR1 isoforms, p90 and p130, which, although devoid of catalytic activity, sequester immunogenic dsRNA substrates, thereby preventing PKR binding and downstream activation of eIF2.

cell biology↗

MagNet: Computational Methods for Constructing High-Confidence Protein-Protein Interaction Networks in Magnaporthe oryzae

Magnaporthe oryzae, the rice blast fungus, plays a role as a model organism for molecular plant-microbe interaction research. Studies on the pathogenic mechanism of this fungus revealed many genes involved in signaling pathways. As multi-omics data are being available, genomic-level researches have been conducted to uncover the underlying biological processes during the pathogenesis of M. oryzae. Identifying the genome-wide protein-protein interaction (PPI) network is one of the omics-level approaches, which helps to understand signaling and regulatory pathways. However, existing biological network resources of M. oryzae are not sufficient to decipher pathogenesis mechanisms due to the abundance of false positives/negatives. In this study, a reliable PPI network database of M. oryzae, MagNet, was constructed with three methods, including homology-based Interolog search, co-expression network construction, and domain-domain interaction (DDI)-based prediction. With three approaches altogether, the pan-network with 5,600,976 interactions was generated, including 217,531 highly confident interactions supported by all three methods. Experimental data on M. oryzae PPIs supported that our PPI network can predict PPIs with higher accuracy compared to the previously constructed databases. MagNet would provide integrated biological network data, which can help to understand the molecular mechanisms of the rice blast fungus. The PPI data can be accessed via https:/magnet.scnu.ac.kr.

genomics↗

Distinct Spatial Programs of Response versus Resistance in Non-Small Cell Lung Cancer after Neoadjuvant Chemoimmunotherapy

BackgroundNeoadjuvant chemoimmunotherapy (nCIT) has become a standard treatment for locally advanced resectable non-small cell lung cancer (NSCLC), yet the spatial biology underlying treatment resistance remains poorly understood. We used spatial transcriptomics to define the microenvironmental architecture of residual cancers in patients who did not achieve major pathologic response (non-MPR) compared with those who did (MPR). MethodsSpatial transcriptomics was performed on 10 formalin-fixed paraffin-embedded (FFPE) tumor blocks (5 MPR, 5 non-MPR) obtained from 8 patients treated with nCIT. A deep learning algorithm was applied to detect viable residual cancer spots from treatment-induced fibrosis and necrosis. Spatial deconvolution, distance modeling, ligand-receptor analysis, and functional pathway scoring were integrated to characterize niche-specific programs. ResultsMPR cancer core displayed an immune-permissive remodeling environment with deep infiltration of cytotoxic CD8+ T cells, mature dendritic cells (LAMP3+, CCR7+), and active efferocytosis signaling (APOE-TREM2), alongside robust MHC class II expression. Non-MPR cancer core, by contrast, exhibited spatial immune exclusion: a dense fibroblast barrier reinforced by TIMP1-CD63 signaling and Treg-enriched boundaries physically restricted effector T cell access to the cancer core. Residual cancer cells in non-MPR samples maintained active cell cycling and independently upregulated cytochrome P450-mediated drug detoxification and DNA damage response pathways without inducing MHC class II expression -- effectively decoupling intrinsic survival from immune recognition. The non-MPR core also showed a hyper-metabolic profile, including elevated glutathione metabolism consistent with antioxidant buffering against chemotherapy-induced oxidative stress. TROP2 was broadly expressed across the non-MPR cancer core and co-localized with DNA damage response and nuclear factor erythroid 2-related factor 2 resistance signatures. ConclusionsResidual cancer cores in non-MPR tumors appear to represent evolved resistant niches sustained by structural immune exclusion, metabolic rewiring, and DNA repair proficiency. These findings highlight the spatial co-localization of epithelial anchors, such as TROP2, with intrinsic resistance pathways, providing a structural rationale for developing novel precision therapeutic strategies to bypass stromal barriers and overcome the cancer cores intrinsic repair capacity.

cancer biology↗

Fructose utilization by GM-CSF-differentiated macrophages aggravates autoimmune inflammation via MG-derived AGE-RAGE signaling

Excessive fructose intake is increasingly associated with metabolic and inflammatory pathologies; however, the direct impact of fructose metabolism on immune cell function remains insufficiently understood. Here, we demonstrate that GM-CSF-differentiated macrophages markedly upregulate the fructose-specific transporter GLUT5, enabling efficient fructose utilization through two complementary metabolic pathways. Using 13C-fructose tracing, we identified distinct carbon fluxes via a hexokinase (HK)-dependent glycolytic route and a ketohexokinase (KHK)-ALDOB-mediated fructolytic route. The HK-dependent pathway sustains glycolytic activity under glucose-limiting conditions, stabilizing HIF-1 and preserving pro-inflammatory gene expression. Conversely, the KHK-ALDOB axis increases dihydroxyacetone phosphate (DHAP) production, leading to methylglyoxal-derived advanced glycation end-products (MG-AGEs) that engage receptor for AGE (RAGE) signaling. This activation enhances MMP9 expression in macrophages and drives Th17 differentiation in CD4 T cells, amplifying inflammatory and tissue-remodeling processes. In vivo, fructose intake exacerbates autoimmune arthritis in SKG mice, and elevated fructose-driven glycolysis and MG-AGE accumulation are observed in monocytes from patients with rheumatoid arthritis. These results link fructose-driven carbonyl stress to macrophage effector programs and downstream T cell polarization. Collectively, these findings uncover a dual fructose metabolic program that integrates nutrient stress with persistent inflammation via the MG-AGE-RAGE axis and underscore the immunometabolic risks of excessive fructose exposure.

immunology↗

Graft-Induced Reprogramming Under Arterial Hemodynamic Stress is Associated with a Shared Proteomic Phenotype in Arterial and Venous Conduits Following Coronary Artery Bypass Grafting

BackgroundAutologous venous conduits remain the mainstay of coronary artery bypass grafting (CABG); however, their long-term patency is limited by adverse vascular remodeling. While arterial and venous grafts undergo structural and molecular adaptation to arterial hemodynamics, the mechanisms underlying successful adaptation remain poorly characterized owing to the scarcity of functioning human graft tissues. MethodsWe analyzed bypass grafts explanted en bloc during orthotopic heart transplantation, comprising patent vein grafts (VGP, n=19), occluded vein grafts (VGO, n=9), and patent arterial grafts (AGP, n=13), alongside freshly harvested controls (vein, n=23; artery, n=11). Quantitative histomorphometry, label-free LC-MS/MS proteomics, pathway analysis, and immunohistochemistry were performed. ResultsWhile patent arterial and venous grafts exhibited medial elastin reinforcement, adventitial neovascularization, and organized intimal remodeling, occluded vein grafts demonstrated elastic layer disruption, medial degeneration, and collagen-dense fibrosis. Proteomic analysis revealed a convergent adaptive signature in patent grafts enriched for RNA metabolism, protein synthesis, cytoskeletal dynamics, and extracellular matrix organization, with shared activation of NR4A3, STAT1, and EGFR signaling. Vein-specific adaptation involved SRC-PTGES activation with concomitant STAT3 suppression, whereas arterial grafts engaged IGF1-RUNX2-associated proliferative programs. Failed venous grafts exhibited angiotensin-driven fibroinflammatory remodeling. Endothelial nitric oxide synthase expression was markedly upregulated in the luminal endothelium and adventitial neovessels of patent grafts. ConclusionsDespite distinct vascular origins, arterial and venous grafts converged toward a shared adaptive phenotype characterized by structural maturation and vasoprotective signaling. Targeting common adaptive pathways--including NR4A3, STAT1, EGFR, and adventitial eNOS--may offer therapeutic strategies to enhance long-term graft durability. WHAT ARE THE CLINICAL IMPLICATIONS?This study provides human tissue-based evidence that patent coronary bypass grafts share a common adaptive remodeling program, irrespective of whether the conduit is arterial or venous. Rather than simple venous "arterialization," successful grafts converged on a phenotype characterized by coordinated biosynthetic activity, structural maturation, and vasoprotective signaling, whereas occluded vein grafts exhibited a distinct angiotensin-driven fibroinflammatory remodeling program. Importantly, patent grafts demonstrated conserved upregulation of NR4A3, STAT1, EGFR, and endothelial nitric oxide synthase (eNOS) in both luminal and adventitial endothelial compartments, identifying molecular features that distinguish adaptive from maladaptive remodeling in humans. These findings are clinically relevant because they highlight shared, potentially targetable pathways that may support graft durability across conduit types and provide mechanistic support for surgical strategies that preserve perivascular adipose tissue during vein harvesting. Moreover, the association of graft failure with angiotensin-centered extracellular matrix remodeling suggests a modifiable biological axis that warrants further investigation. Together, this work establishes a human molecular framework for graft adaptation that may inform future biomarker development, therapeutic targeting, and precision strategies aimed at improving outcomes after coronary artery bypass grafting.

pathology↗

Methylation mimic mutations of progesterone receptor AF1 impair gene-specific regulation through stabilized chromatin interactions

Progesterone receptor (PR) is a nuclear receptor that regulates gene transcription through recruiting coregulators and general transcription factors by activation functions AF1 and AF2. AF1 localizes to the non-conserved and disordered N terminal domain and is believed to facilitate tissue- and gene-specific activity. Our previous proteomic analysis identified three key functional residues (K464, K481 and R492) of AF1 that are monomethylated. Mutations of KKR to phenylalanine (FFF) that mimic methylation created hypoactive PR, whereas KKR/QQQ mutations generated hyperactive PR in gene reporter assays. The current study investigated specific involvement of AF1 in PR regulation of gene expression in breast cancer cells. AF1-FFF mutations attenuated progestin induced growth regulation, cell adhesion and apoptosis and AF1-QQQ mutation enhanced these effects. Genome-wide expression analysis showed attenuated gene regulation by AF1-FFF of two thirds of PR target genes including genes involved in hypoxia and TNF signalling via NFKB. Unexpectedly, AF1-FFF mutations had little effect on ligand-independent gene regulation, suggesting distinct mechanisms of gene regulation by liganded and unliganded PR. Intriguingly, impaired activity of methylation mimic mutant PR-FFF is associated with higher enhancer binding peaks in ChIP-Seq analysis. This corresponds to a stronger association of AF1-FFF with SRC-1 and AF2 as we previously reported. We propose that methylation mimic AF1 mutant impairs regulation of a subset of genes through tighter coregulator binding which restricts the dynamics of the disassembly of transcription complex.

molecular biology↗

National Scale Genomic Engine for Precision Medicine: Singapore PRECISE-SG100K Experience

The whole-of-nation National Precision Medicine (NPM) programme in Singapore aims to integrate a genomics backbone into standard healthcare. Phase II recently completed the sequencing of 102,202 genomes from the diverse Asian population of Singapore, generating the PRECISE-SG100K dataset. The scaling from the pilot SG10K_Health phase to national production scale demanded a central shift: from earlier generation workflows to an integrated, industrial grade "Genomic Engine". The initiative was co-developed under a public-private partnership model. Our Genomic Engine was designed with an automation-first approach, as a modular platform linking a purpose-built, centralized biospecimen processing and DNA extraction facility (EXTRACT Lab), a high-throughput sequencing operation (Illumina Data Generation Infrastructure, IDGI), with the cloud-native analytics (GRIDS) running on a fully integrated PRECISE Sample Tracking System (STS). Here we describe the key design features of our Genomic Engine. Highlighting the Stress Test phase where the automated DNA extraction yields failed to meet expectations. We share the operational adjustments which were implemented to stabilize production and resulted in a three-fold reduction in sample triage due to improved DNA recovery. Without establishing the operational guardrails during the Stress Test, the Engine would not have reached a steady-state production evidenced by >3,000 genomes per month, median turnaround time 11 days, 99.6% operational success, within in six months. This framework offers a practical blueprint for other population-scale initiatives seeking to bridge the gap between scientific piloting and industrial delivery.

genomics↗

Small Extracellular Vesicles by Nucleus Pulposus Cells Maintain Niche and Cell Homeostasis via Receptor Shuffling and Metabolic Enzyme Supplements

BackgroundSmall extracellular vesicles (sEV) are a conserved mean of communication across the domains of life and lately gained more interest in mammalian non-cancerous work as non-cellular, biological therapeutic with encouraging results in recent studies of chronic degenerative diseases. The nucleus pulposus (NP) is the avascular and aneural center of an intervertebral disc (IVD), home to unique niche conditions and affected in IVD degeneration. We investigated the proteome of autologous and mesenchymal stem cell (MSC) sEVs for their potential to contribute to cell and tissue homeostasis in this niche. MethodsWe aimed to identify characteristics of NP sEVs via mass spectrometric proteome and functional enrichment analysis. We explored the proteome profile of sEVs generated by autologous parent cell lines from bovine coccygeal IVD and adipose tissue, with a focus on NP cells, using adult and fetal donors. We compared these findings to published sEV databases and MSC sEV data. FindingsWe propose several mechanisms associated with NP sEVs: 1. Membrane receptor trafficking to modify signal responses promoting niche homeostasis. 2. Cell homeostasis via proteasome delivery; 3. Redox and energy homeostasis via metabolic enzymes delivery. 4. Immunomodulation beyond an association with a serum protein corona. ConclusionThe proteome signature of sEVs generated by NP parent cells is similar to previously published sEV data, yet with a focus on supplementing anaerobic metabolism and redox balance while contributing to the maintenance of an aneural and avascular microniche.

cell biology↗

Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression

While cancer-associated fibroblasts (CAFs) are crucial in influencing tumor growth and immune responses in lung cancer, we still lack a comprehensive understanding of their spatial organization associated with tumor progression and clinical outcomes. This gap highlights the need to elucidate how the intricate spatial arrangement of CAFs affects their interactions within the tumor microenvironment, ultimately shaping cancer progression and patient prognosis. Here, we unveil the spatial diversity of CAFs in lung squamous cell carcinoma (LUSC), a prevalent and aggressive lung cancer type, elucidating their impact on tumor progression and patient outcomes using spatial transcriptomics (ST). Image-based ST data from 33 LUSC patients demonstrated a significant association of spatial interactions of tumor epithelium and CAFs with tumor size and metabolic activity measured by [18F]fluorodeoxyglucose PET. Furthermore, the proximity of fibroblasts to tumor epithelial cells was linked to recurrence-free survival in LUSC patients. By characterizing CAFs based on their spatial relationship, we identified distinct molecular signatures related to spatially distinct fibroblast subpopulations. In addition, barcode-based ST data from 8 LUSC patients revealed spatially overlapping fibroblast regions characterized by upregulated glycolysis pathways. Our study underscores the importance of the complex spatial dynamics of the tumor microenvironment revealed by ST and its implications for patient outcomes in LUSC.

cancer biology↗

Unraveling the Complexity of Abdominal Aortic Aneurysm: Multiplexed Imaging Insights into C-Reactive Protein-Related Variations

BackgroundAbdominal aortic aneurysm (AAA) is a potentially lethal condition that often remains asymptomatic until it ruptures. Recent research suggests that immune-inflammatory processes are associated with AAA development, yet the exact mechanisms remain unclear. Serum C-reactive protein (CRP) serves as a prognostic marker for AAA and various cardiovascular diseases. When CRP accumulates in damaged tissues, it transforms into a monomeric form, exacerbating tissue damage. Our previous study confirmed the presence of CRP deposition in eroded AAA and atherosclerosis regions, accompanied by an increased infiltration of inflammatory cells. However, a comprehensive understanding of the specific changes in the inflammatory cellular landscape attributable to CRP deposition is lacking. Here, we aimed to explore cellular-level alterations in AAAs associated with varying CRP levels. MethodsWe categorized AAA patients into High-CRP ([≥]0.1 mg/dL, and [≥]3+ CRP IHC score, n=6) and Low-CRP ([≤]0.1 mg/dL, and [≤]1+ CRP IHC score, n=3), and used normal aorta specimens as a baseline control. The cellular landscape of immune and stromal components was characterized using Co-Detection by Indexing (CODEX) tissue imaging with 31 DNA-barcoded antibodies, followed by single-cell-based analysis and GPU-accelerated unsupervised clustering. ResultsWe identified 51 distinct immune and stromal cell types in the cohort and revealed significant differences in protein expression patterns among the groups. In AAA, stromal cells decreased significantly, while immune cell proportions sharply increased. Lag3+ T cell regulators decreased, leading to an increase in CD3+ T cells. The composition of immune cells within atherosclerotic plaques was associated with the degree of CRP deposition in AAA. The High-CRP group showed increased M1 and Ki67+ proliferating macrophages, while the Low-CRP group exhibited intensified fibrosis with M2 macrophages. ConclusionsOur study found significant variations in immune cell distribution within AAA walls based on CRP levels. These findings suggest a potential link between CRP-related immune changes and AAA progression. HIGHLIGHTSO_LIBy performing CODEX (co-detection by indexing) multiplexed imaging on paraffin-embedded, formalin-fixed archived abdominal aortic aneurysm (AAA) tissue samples with varying CRP levels, we segmented 415,365 cells into 51 distinct clusters. C_LIO_LIIn AAA, the presence of CRP deposition led to variations in the spatial relationships, distances, and enrichment patterns among immune and stromal cells.. C_LIO_LIIn AAA-High CRP, there was an intensified infiltration of M1 macrophages and various immune cells observed in the atherosclerotic plaque. C_LIO_LIIn AAA-Low CRP, severe stromal fibrosis was associated with M2 macrophages. C_LIO_LIOur results suggest that the deposition of CRP into the atherosclerotic plaque alters the immune-stromal landscape in AAA. C_LI

pathology↗

Altered methionine metabolism impacts phenylpropanoid production and plant development in Arabidopsis thaliana

Phenylpropanoids are specialized metabolites derived from phenylalanine. Glucosinolates are defense compounds derived mainly from methionine and tryptophan in Arabidopsis. It was previously shown that the phenylpropanoid pathway and glucosinolate production are metabolically linked. The accumulation of indole-3-acetaldoxime (IAOx), the precursor of tryptophan-derived glucosinolates, represses phenylpropanoid biosynthesis through accelerated degradation of phenylalanine-ammonia lyase (PAL). As PAL functions at the entry point of the phenylpropanoid pathway which produces indispensable specialized metabolites such as lignin, aldoxime-mediated phenylpropanoid repression is detrimental to plant survival. Although methionine-derived glucosinolates in Arabidopsis are abundant, any impact of aliphatic aldoximes (AAOx) derived from aliphatic amino acids such as methionine on phenylpropanoid production remains unclear. Here, we investigate the impact of AAOx accumulation on phenylpropanoid production using Arabidopsis aldoxime mutants, ref2 and ref5. REF2 and REF5 metabolize aldoximes to respective nitrile oxides redundantly, but with different substrate specificities. ref2 and ref5 mutants have decreased phenylpropanoid contents due to the accumulation of aldoximes. As REF2 and REF5 have high substrate specificity toward AAOx and IAOx respectively, it was assumed that ref2 accumulates AAOx, not IAOx. Our study indicates that ref2 accumulates both AAOx and IAOx. Removing IAOx partially restored phenylpropanoid production in ref2, but not to the wild-type level. However, when AAOx biosynthesis was silenced, phenylpropanoid production and PAL activity in ref2 were completely restored, suggesting an inhibitory effect of AAOx on phenylpropanoid production. Further feeding studies revealed that the abnormal growth phenotype commonly observed in Arabidopsis mutants lacking AAOx production is a consequence of methionine accumulation. Significance StatementAliphatic aldoximes are precursors of various specialized metabolites including defense compounds. This study reveals that aliphatic aldoximes repress phenylpropanoid production and that altered methionine metabolism affects plant growth and development. As phenylpropanoids include vital metabolites such as lignin, a major sink of fixed carbon, this metabolic link may contribute to available resource allocation during defense.

plant biology↗

Mapping cell types in the tumor microenvironment from tissue images via deep learning trained by spatial transcriptomics of lung adenocarcinoma

Profiling heterogeneous cell types in the tumor microenvironment (TME) is important for cancer immunotherapy. Here, we propose a method and validate in independent samples for mapping cell types in the TME from only hematoxylin and eosin (H&E)-stained tumor tissue images using spatial transcriptomic data of lung adenocarcinoma. We obtained spatial transcriptomic data of lung adenocarcinoma from 22 samples. The cell types of each spot were estimated using cell type inference based on a domain adaptation algorithm with single-cell RNA-sequencing data. They were used to train a convolutional neural network with a corresponding H&E image patch as an input. Consequently, the five predicted cell types estimated from the H&E images were significantly correlated with those derived from the RNA-sequencing data. We validated our model using immunohistochemical staining results with marker proteins from independent lung adenocarcinoma samples. Our resource of spatial transcriptomics of lung adenocarcinoma and proposed method with independent validation can provide an annotation-free and precise profiling method of tumor microenvironment using H&E images.

cancer biology↗

De novo fatty-acid synthesis protects invariant NKT cells from cell death, thereby promoting their homeostasis and pathogenic roles in airway hyperresponsiveness

AbstractInvariant natural-killer T (iNKT) cells play pathogenic roles in allergic asthma in murine models and possibly also humans. While many studies show that the development and functions of innate and adaptive immune cells depend on their metabolic state, the evidence for this in iNKT cells is very limited. It is also not clear whether such metabolic regulation of iNKT cells could participate in their pathogenic activities in asthma. Here, we showed that acetyl-coA-carboxylase 1 (ACC1)-mediated de novo fatty-acid synthesis is required for the survival of iNKT cells and their deleterious functions in allergic asthma. ACC1, which is a key fatty-acid synthesis enzyme, was highly expressed by lung iNKT cells from WT mice that were developing asthma. Cd4-CreAcc1fl/fl mice failed to develop OVA-induced and HDM-induced asthma. Moreover, iNKT cell-deficient mice that were reconstituted with ACC1-deficient iNKT cells failed to develop asthma, unlike when WT iNKT cells were transferred. ACC1 deficiency in iNKT cells associated with reduced expression of fatty acid-binding proteins (FABPs) and peroxisome proliferator-activated receptor (PPAR){gamma}, but increased glycolytic capacity that promoted iNKT-cell death. Furthermore, circulating iNKT cells from allergic-asthma patients expressed higher ACC1 and PPARG levels than the corresponding cells from non-allergic-asthma patients and healthy individuals. Thus, de novo fatty-acid synthesis prevents iNKT-cell death via an ACC1-FABP-PPAR{gamma} axis, which contributes to their homeostasis and their pathogenic roles in allergic asthma.

immunology↗

Pan-cancer proteomic map of 949 human cell lines reveals principles of cancer vulnerabilities

The proteome provides unique insights into biology and disease beyond the genome and transcriptome. Lack of large proteomic datasets has restricted identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types were analyzed by mass spectrometry. Deploying a clinically-relevant workflow to quantify 8,498 proteins, these data capture evidence of cell type and post-transcriptional modifications. Integrating multi-omics, drug response and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline revealed thousands of protein-specific biomarkers of cancer vulnerabilities. Proteomic data had greater power to predict drug response than the equivalent portion of the transcriptome. Further, random downsampling to only 1,500 proteins had limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger), available at https://cellmodelpassports.sanger.ac.uk, is a comprehensive resource revealing principles of protein regulation with important implications for future clinical studies.

systems biology↗

Automated Hyperspectral Vegetation Index Derivation Using A Hyperparameter Optimization Framework for High-Throughput Plant Phenotyping

O_LIHyperspectral vegetation indices (VIs) are widely deployed in agriculture remote sensing and plant phenotyping to estimate plant biophysical and biochemical traits. However, existing VIs consist mainly of simple 2-band indices which limits the net performance and often do not generalize well for other traits than they were originally designed for. C_LIO_LIWe present an automated hyperspectral vegetation index (AutoVI) system for the rapid generation of novel 2- to 6-band trait-specific indices in a streamlined process covering model selection, optimization and evaluation driven by the tree parzen estimator algorithm. Its performance was tested in generating novel indices to estimate chlorophyll and sugar contents in wheat. C_LIO_LIResults show that AutoVI can rapidly generate complex novel VIs ([≥]4-band index) which correlated strongly (R2 > 0.8) with measured chlorophyll and sugar contents in wheat. AutoVI-derived indices were used as features in simple and stepwise multiple linear regression for chlorophyll and sugar content estimation, and outperformed results achieved with existing 47 VIs and those provided by partial least squares regression. C_LIO_LIThe AutoVI system can deliver novel trait-specific VIs readily adoptable in high-throughput plant phenotyping platforms and should appeal to plant scientists and breeders. A graphical user interface of AutoVI is herein provided. C_LI

plant biology↗

CellDART: Cell type inference by domain adaptation of single-cell and spatial transcriptomic data

Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distribution of cells defined by single-cell level data using domain adaptation of neural networks and applied it to the spatial mapping of human lung tissue. The neural network that predicts the cell proportion in a pseudospot, a virtual mixture of cells from single-cell data, is translated to decompose the cell types in each spatial barcoded region. First, CellDART was applied to mouse brain and human dorsolateral prefrontal cortex tissue to identify cell types with a layer-specific spatial distribution. Overall, the suggested approach was competent to the other computational methods in predicting the spatial localization of excitatory neurons. Besides, CellDART was capable of decomposing cellular proportion in mouse hippocampus Slide-seq data. Furthermore, CellDART elucidated the cell type predominance defined by the human lung cell atlas across the lung tissue compartments and it corresponded to the known prevalent cell types. CellDART is expected to help to elucidate the spatial heterogeneity of cells and their close interactions in various tissues.

genomics↗