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Park, B.

Publications and source records attributed to Park, B..

At least 19 recordsLinked to original sources
bioRxiv2026

SON-mediated circular RNA suppression promotes PKR signaling and radiation resistance in glioblastoma

Glioblastoma (GBM) exhibits extensive loss of circular RNAs (circRNAs), yet the mechanisms driving this depletion and its functional consequences remain unclear. Here, we identify the splicing co-factor SON as a previously unrecognized suppressor of circRNA biogenesis in GBM. CircRNA sequencing revealed widespread increases in circRNA abundance following SON knockdown. Conversely, elevated SON expression in GBM, with further increases in radiation-resistant models, was associated with widespread circRNA loss, including reduced expression of circUSP1 and circSUCO. SON knockdown increased circRNA abundance and attenuated activation of the dsRNA-responsive kinase PKR and downstream NF{kappa}B signaling, whereas radiation-resistant GBM cells exhibited enhanced PKR/NF{kappa}B activation that was attenuated by SON depletion. Importantly, overexpression of the SON-suppressed circRNAs circUSP1 and circSUCO reduced PKR activation and selectively decreased clonogenic survival following irradiation in radiation-resistant GBM cells, with little effect on parental cells. Together, these findings identify a previously unrecognized SON/circRNA/PKR regulatory pathway linking RNA processing to acquired radiation resistance in GBM and highlight specific PKR-inhibitory circRNAs as potential therapeutic tools for resensitizing radiation-resistant GBM to radiotherapy.

cancer biology↗
bioRxiv2026

PREpiBind: Protein Representation-integrated Epitope--MHC Class II Binding Prediction

Accurate prediction of peptide-MHC class II (pMHC-II) binding remains challenging because of extensive MHC polymorphism and context-dependent peptide recognition, and it is unclear which protein representation best captures these determinants when the downstream model is held fixed. Here, we present PREpiBind, a pMHC-II prediction method based on a dual-stream, joint-attention framework that integrates MHC and epitope representations. We integrated ten protein representations spanning substitution-matrix, structure-prediction-derived, and protein language model (PLM) families and evaluated them under a common downstream architecture and identical splits across Qualitative, mass spectrometry (MS), and thresholded IC50 datasets. Overall, PREpiBind with PLM representations yielded higher performance than the evaluated reference methods in the Qualitative and MS datasets, whereas NetMHCIIpan-4.3 was higher on the thresholded IC50 datasets using its binding-affinity head. In pooled evaluations, PLM representations yielded the highest ROC-AUC values among the tested representations. ESM3 Large led the Qualitative dataset with an AUC value of 0.927 +/- 0.002, and PLMs also led on the MS and thresholded IC50 datasets. This advantage remained, but narrowed in allele-wise and leave-one-molecule-out evaluations, where structure-prediction-derived Chai-1 was competitive with the leading PLM representations. Under cross-species H2-out transfer, PLMs led when all H2 rows were pooled, whereas Chai-1 led when the eight H2 molecules were weighted equally. The small H2 panel did not support a stable ordering among these leading representations. The results indicate that protein representation choice should depend on the intended prediction scenario rather than on a single global ranking. PREpiBind is an openly available pMHC-II prediction framework with modular and flexible protein representations.

bioinformatics↗
bioRxiv2026

Chronic opioid-associated immune dysregulation among people living with HIV

Objectives: Persistent immune dysregulation contributes to chronic disease among people living with HIV (PWH), even after viral suppression with antiretroviral therapy (ART). Although chronic opioid exposure is associated with adverse clinical outcomes, its impact on immune homeostasis during ART remains incompletely understood. We investigated whether opioid use disorder (OUD) is associated with persistent systemic and cellular immune dysregulation despite ART-mediated reductions in HIV viral load (VL). Methods: Peripheral blood was collected longitudinally from PWH with OUD (PWH/OUD+) and detectable HIV VL during 6 months of optimized ART (months 0, 3, and 6). A reference cohort of PWH without OUD (PWH/OUD-) and suppressed HIV VL provided a single blood sample. Immune profiling included plasma inflammatory biomarkers, multiplex cytokine analyses, spectral flow cytometry, and assessment of monocyte cytokine responses following lipopolysaccharide (LPS) stimulation. Mixed-effects models adjusted for HIV VL and VL-stratified analyses were performed. Results: PWH/OUD+ exhibited persistent immune dysregulation despite reductions in HIV VL. Plasma sCD163, sCD14, fractalkine, and I-TAC remained elevated, whereas TGF-{beta}1 was reduced. OUD was associated with expansion of CD16 monocytes and altered expression of CCR2, CD38, and CD11b. CD4 and CD8 T cells, NK cells, and B cells also exhibited persistent alterations in markers of activation, metabolism, and trafficking. Monocytes from PWH/OUD+ displayed attenuated cytokine responses following LPS stimulation. Conclusions: OUD is associated with persistent systemic and cellular immune dysfunction in PWH despite ART-mediated viral suppression, supporting opioid exposure as an independent contributor to chronic immune dysregulation that may promote inflammation, immune dysfunction, and long-term HIV-associated comorbidities. Keywords: HIV, Opioid-use disorder, innate immunity, cytokine

immunology↗
bioRxiv2026

Requirement of hypoxia-inducible factor 1 alpha for interleukin 1 beta induced glycolysis in colorectal cancer cells

Colorectal cancer cells increase glycolysis to help meet the metabolic demands required for cell growth. Many factors, both endogenous and exogenous, likely drive cellular metabolism and enhance glycolytic flux in colorectal cells. Interleukin-1 beta (IL-1{beta}) is a pro-inflammatory cytokine that is elevated in colorectal cancer. In this study, we investigated the effect of IL-1{beta} toward driving the cancer cell to increase glycolysis, while also suppressing the oxidation of the fiber-derived nutrient butyrate. The results presented here demonstrate that IL-1{beta} stimulated glycolysis and inhibited maximal mitochondrial respiration. IL-1{beta} also increased the phosphorylation of AKT and hypoxia-inducible factor 1 alpha (HIF1) levels. Utilizing colorectal cancer cells with AKT1/2 or HIF1 knocked out showed the requirement of these proteins in mediating the increase in glycolysis following IL-1{beta} treatment. Importantly, AKT1/2 was identified as upstream of HIF1, as IL-1{beta} still increased phosphorylation of AKT even in the absence of HIF1. However, loss of AKT1/2 completely abolished the ability of IL-1{beta} to increase HIF1 protein levels. Tumor necrosis factor alpha (TNF), another cytokine found to be elevated in colorectal cancer, also increased glycolysis in an AKT and HIF1-dependent manner. Our data point to a common pathway through AKT activation and HIF1 upregulation, by which pro-inflammatory cytokines increase glycolysis in colorectal cancer cells to help promote cancer progression.

cell biology↗
bioRxiv2026

Scalable Extraction of Information on Protein-Protein Interactions using Topological Data Analysis

Protein-protein interactions (PPIs) govern a wide range of cellular functions. The ability to predict PPI interfaces from protein molecular surfaces is important for understanding protein function and enabling therapeutic discovery. While recent advances in structure-based learning, particularly molecular-surface geometric deep learning frameworks, have demonstrated that protein surfaces encode rich geometric and physicochemical information, such approaches often remain computationally intensive and data-hungry. Alternatively, topological data analysis (TDA) has emerged as a mathematically rigorous framework for extracting robust, multiscale shape information from complex data. In this work, we introduce a scalable TDA framework for extracting information on PPIs directly from localized protein surface patches. Our approach leverages multiscale topological descriptors, evaluated from patch-wise point cloud representations of protein mesh surfaces, combined with supervised machine learning models for interface prediction. On a full dataset of 3,362 proteins, the proposed approach substantially reduced computational cost relative to an established geometric deep learning method, MaSIF-site, decreasing preprocessing time from approximately 27 s/protein to 5-8 s/protein and total training time from approximately 6 h to 1-1.3 h. Importantly, this computational reduction is achieved while maintaining mean test area under the receiver operating characteristic curve (AUC) values of 0.76 and 0.77 for patch radii of 9 [A] and 12 [A], respectively, thus approaching the MaSIF-site test AUC of 0.84. Our results suggest that topology offers a scalable and computationally efficient approach for high-throughput extraction of information from complex biomolecular interfaces.

bioinformatics↗
bioRxiv2026

Cryptic disease-prone states in human mesocortical assembloids revealed by multimodal profiling

Neurodegenerative diseases are characterized by synaptic failure, aberrant protein accumulation, and neuroglial dysfunction that emerge long before clinical onset. Although brain assembloids, which recapitulate interregional circuit connectivity beyond the scope of single organoids, significantly advance the modeling of circuit pathophysiology, they are predominantly evaluated through single-modality approaches that cannot resolve the functional and molecular heterogeneity underlying differential disease susceptibility. Here we show that morphologically identical human iPSC-derived dorso forebrain-midbrain mesocortical assembloids (MCAs) spontaneously bifurcate into disease-prone and non-prone states under identical culture conditions, revealing that MCA heterogeneity reflects intrinsic neurodegeneration susceptibility rather than stochastic culture variability. Using integrated electrophysiological, molecular, and spatial profiling, we find that disease-prone MCAs exhibit a temporally ordered molecular cascade in which neurofilament light chain elevation precedes tau dysregulation, mirroring the sequential biomarker trajectories observed in pre-symptomatic human neurodegeneration. Disease-prone MCAs further display selective cortical hyperexcitability and aberrant brainwave-like oscillatory dynamics that remain undetectable by any single modality. Spatially, a discrete junction-like neuronal population at the midbrain-forebrain interface shows transcriptional priming for synaptic overactivation alongside impaired astrocytic glutamate clearance, defining a spatially confined neuron-glial uncoupling as a candidate early origin of the disease-prone state. These findings reframe MCA heterogeneity as a biological window into pre-symptomatic neurodegeneration, with broad implications for disease modeling, risk stratification, and therapeutic discovery.

neuroscience↗
bioRxiv2026

Revealing interactions between glutathione peroxidase 4 and phosphoinositides

Glutathione peroxidase 4 (GPx4) is the primary enzyme reducing lipid hydroperoxides, preventing membrane oxidative damage and protecting against ferroptosis. GPx4 is known to engage with lipid headgroups through electrostatic interactions, positioning the substrate for reduction. This work reveals and characterizes binding of highly anionic phosphoinositides (PIP lipids) by GPx4. PIPs are vital lipids in human cells and are central to many signaling processes, particularly in cytosolic facing membranes. Lipid overlay assays confirm interactions between GPx4 and phosphorylated PIPs, comparable to known anionic lipid binders. Protein NMR describes the interaction between GPx4 and PIPs within micelles. The greatest resonance shifting occurs with trisphosphorylated PIP, suggesting that higher anionic charge leads to greater binding, a known driver of GPx4 substrate recognition. Preferred anionic interactions were also confirmed with titration and crystallographic structure analysis of inositol phosphate 4 (IP4). A headgroup-binding site on GPx4 is revealed to be proximal to the cationic membrane interaction site. In conjunction with molecular simulations, these results show that PIP lipid interactions allow full engagement of GPx4 with the membrane and positions the headgroup to allow the lipid tail to interact with the catalytic site. Understanding whether GPx4 preferentially interacts with PIPs will allow better understanding of the protective function of this essential enzyme and a mechanism that may protect essential lipid signaling pathways from oxidative damage. SignificanceThis study allows a deeper structural and mechanistic understanding of GPx4, the primary enzyme that reduces lipid hydroperoxides and prevents ferroptosis. Gaining an understanding of phosphoinositide binding to GPx4 reveals a mechanism for potential preservation of these important signaling molecules and for ferroptosis protection. Observation of a specific binding site for headgroup engagement reveals a plausible lipid interaction mode and functional mechanism of this important cytoprotective enzyme.

biophysics↗
bioRxiv2026

Identifying Context-Specific Cell-Cell Interaction Genes Without Ligand-Receptor Databases from Spatial Transcriptomics

Current approaches to inferring cell-cell interactions (CCIs) are largely constrained by predefined ligand-receptor databases, particularly for low-resolution spatial transcriptomics (ST) platforms such as Visium. Due to the difficulties in accurately resolving interacting cells at coarse spatial resolution, other modes of interaction are often overlooked. Low-resolution ST data, however, can serve as an alternative to high-resolution ST, which suffers from low sensitivity, and to image-based ST, which is limited by restricted gene panels. Here, we present CellNeighborEX v2, a database-free framework that directly infers CCI-associated genes from ST data by detecting deviations between observed and expected gene expression at the spot-population level. These deviations are rigorously evaluated through a hybrid statistical framework involving permutation testing and are further refined by considering the abundance of interacting cell-type pairs. Compared with other conventional approaches relying on ligand-receptor databases, CellNeighborEX v2 can capture CCI genes from a broad spectrum of interactions, including both paracrine signaling and contact-dependent communication. Across datasets from hippocampus, liver cancer, colorectal cancer, ovarian cancer, and lymph node infection, CellNeighborEX v2 accurately recapitulated previously identified CCIs. Notably, it uniquely detected interactions absent from existing ligand-receptor databases, enabling detection of context-specific CCIs from Visium data. CellNeighborEX v2 is a tool that expands the analytical spectrum of Visium data and deepens our understanding of the molecular language of intercellular communication.

bioinformatics↗
bioRxiv2026

Computational design of blue melanin with peptide motif scaffolding

De novo melanin design seeks to extend natural melanin colors to new, stable colors (blue, purple, green) with sequence-to-color tunability. Natural melanin, polymerized from tyrosine (Y), is a robust pigment with heterogenous molecular weights. Control of melanin size (length) is challenging; thus, only specific colors (yellow to brown) exist in nature. In this work, we describe the design of blue melanin through the polymerization of Y-containing pentapeptides with two key properties: tight packing during peptide assembly and high solubility in aqueous environments. By motif scaffolding a pentapeptide-repeat protein (PRP) with RFdiffusion, we narrowed 160,000 possible combinations to a library of 905 Y-containing pentapeptides with tight packing features. Two of the most soluble designs successfully formed stable blue melanin with {lambda}max absorbing in 615-620 nm, contributed by homogeneous melanin length achieved around 60 Y units. Other designs also formed new colors (purple, green), along with more known colors (red, yellow, brown). We found that blue melanin exhibited thermal stability at an autoclave temperature of 121{degrees}C and photostability of weeks under 600 lux illumination. We also demonstrated the application of blue melanin as an electrophoretic ink. De novo color design from simple peptides could potentially transform how colorants are sourced and produced. Our approach with computational design should also inspire the development of new deep-learning tools to directly predict colors from amino acid sequences.

biochemistry↗
bioRxiv2026

Inflammation is the Driver of Butyrate-Producing Bacteria Change in Interleukin10 Knockout Mice

BackgroundAlterations of gut microbiota have been implicated in the development of inflammatory bowel disease. Specifically, patients with IBD show the reduced levels of gut bacteria to produce butyrate, a crucial metabolite for maintaining gut homeostasis, along with decreased levels of fecal butyrate. However, there is limited research on changes in butyrate-producing bacteria at various taxonomic levels during the development of inflammatory bowel disease. ResultsWe investigated the changes of butyrate-producing bacteria in interleukin10 knockout mice, a suitable IBD model, as these mice require gut microbiota to develop spontaneous chronic colitis. Our findings indicate increased inflammation and a metabolic shift from butyrate oxidation toward glycolysis in 9-week-old interleukin10 knockout mice. Furthermore, we observed significant changes in two terminal enzymes involved in butyrate production: a significant increase of butyrate kinase and a significant decrease of butyryl-CoA:acetate-CoA-transferase. These observations align with an increased abundance of Coprococcus comes, which utilizes butyrate kinase, and a decreased abundance of Faecalibacterium prausnitzii that utilizes butyryl-CoA:acetate-CoA-transferase. Moreover, reduced levels of acetate, a necessary co-substrate for butyryl-CoA:acetate-CoA-transferase activity, were observed in interleukin10 knockout mice. ConclusionsThese findings enhance our understanding of changes in butyrate-producing bacteria populations at various taxonomic levels, ranging from phylum to gene level in 9-week-old interleukin10 knockout mice. Furthermore, these data suggest a potential for diagnosing IBD at an early stage by analyzing the composition of butyrate-producing bacteria.

microbiology↗
bioRxiv2025

LDscore: a scalable, Python 3-powered web platform for LD score regression analysis

Linkage disequilibrium score regression (LDSC) is an important analytical tool for quantifying heritability and estimating genetic correlations between complex traits. However, the LDSC original implementation relies on an outdated Python 2 framework and deploying the standard command-line tools requires significant setup, data access, and computational expertise, creating a barrier for many researchers. To overcome these limitations, we developed LDscore, a significant technical and accessibility upgraded version of LDSC that allows for rapid analysis of GWAS data. The core advancement is the recoding of the LDSC framework in Python 3, enabling computational optimization and ensuring long-term sustainability. Built on top of this improved foundation, LDscore is implemented as a free, publicly available web application integrated within the popular NCI LDlink framework. LDscore can accelerate scientific research by providing an intuitive graphical interface for heritability estimation, genetic correlation, and LD score calculation, including access to an expanded range of reference populations for online analysis. Notably, our results show that selecting the most appropriate reference population LD panel, even at the subcontinental ancestry group level, is essential for minimizing population stratification bias in heritability estimation. By leveraging cloud computing for superior scalability and eliminating the need for local installation, LDscore adheres to FAIR principles, improving access, traceability, and reproducibility across an expanded set of reference populations, and effectively widens access to researchers worldwide providing support for in-depth genetic analyses. Brief summaryLinkage disequilibrium score regression (LDSC), a widely-used method for quantifying heritability and genetic correlation, is limited by an outdated Python 2 framework and complex command-line deployment. We developed LDscore, a significant technical upgrade built on Python 3 for sustainability and computational optimization. LDscore is a free, cloud-based web application integrated into NCI LDlink. LDscore eliminates installation barriers, offering an intuitive interface for computing heritability estimates, LD scores, and genetic correlation. Crucially, LDscore expands the range of reference populations available in LDSC, which can reduce population-stratification-based bias. Leveraging cloud computing, LDscore accelerates and widens global researcher access to LDSC-based genetic computation. AvailabilityLDscore is freely available within LDlink at https://ldlink.nih.gov/ldscore. Source code for the updated LDSC Python3 framework is available at https://github.com/CBIIT/ldsc under the GNU General Public License v3.0 and the webtool code is at https://github.com/CBIIT/nci-webtools-dceg-linkage (webtool code) under the MIT license.

genomics↗
bioRxiv2025

Decoding protein-membrane binding interfaces from surface-fingerprint-based geometric deep learning and molecular dynamics simulations

Predicting protein-membrane interactions is a formidable challenge due to the subtle physicochemical features that distinguish membrane-binding regions of a protein surface, as well as the scarcity of experimentally resolved membrane-bound protein conformations. Here, we present MaSIF-PMP, a geometric deep learning model that leverages molecular surface fingerprints to predict interfacial binding sites (IBSs) of peripheral membrane proteins (PMPs). MaSIF-PMP integrates geometric and chemical surface features to produce spatially resolved IBS predictions. Compared to existing models, MaSIF-PMP achieves superior performance for IBS classification, while feature ablation studies and transfer learning analyses reveal distinct determinants governing protein-membrane versus protein-protein interactions. We further show that molecular dynamics (MD) simulations can validate model predictions, refine IBS labels, and capture composition-dependent membrane binding patterns. These results establish MaSIF-PMP as an effective framework for IBS prediction and highlight the potential of incorporating conformational dynamics from MD to improve both model accuracy and biological interpretability.

bioinformatics↗
bioRxiv2025

Tau deletion results in sex-dependent modulation of synaptic weakening in rat hippocampus

Tangles, a defining characteristic of Alzheimers disease (AD), are composed principally of hyperphosphorylated and misfolded tau species. However, dysregulation of tau precedes tangle formation by many years and is associated with cognitive decline, the best functional correlate of which is synaptic weakening and eventual synaptic loss. Although tau is present at synapses, its normal synaptic function is poorly understood - information vital to the rational development of tau-modifying therapies. Since rats have a greater cognitive repertoire than mice and display more robust signs of tau pathology in AD models, we developed a tau knockout (Mapt-/-) rat to investigate the impact of tau elimination on synaptic function. We observed that long-term depression (LTD), a form of synaptic weakening, is enhanced in the hippocampus of male, but not female, rats. This enhanced LTD was dependent on the synaptic activation of group I metabotropic glutamate receptors and involved altered synaptic actin polymerization. These studies therefore provide mechanistic insights into how tau modulates synaptic function via regulation of the actin cytoskeleton. Our findings are relevant to the understanding of the physiological roles of synaptic tau, the functional consequences of tau-lowering therapies, and the influence of sex in AD susceptibility.

neuroscience↗
bioRxiv2025

Early-life Exposure to Arsenic Primes the Offspring to Increased Asthma Risk: Transcriptome and Epigenome Analysis

Inorganic arsenic (iAs) in drinking water is a global health concern. This study tests whether maternal exposure to iAs in drinking water at the WHO provisional level (10{micro}g/L) increases offspring asthma risk via epigenetic reprogramming. F1 mice prenatally exposed to iAs were analyzed at 5 months for blood transcriptome and methylome changes and challenged with house allergens before lung function testing. Prenatal iAs exposure led to increased airway hyperresponsiveness (AHR) and altered inflammation gene expression and DNA methylation changes. Notably, miR-101c was epigenetically reprogrammed early in development, with persistent downregulation in both target (fetal and adult lungs) and surrogate (amniotic fluid and blood) tissues. These changes correlated with increased allergic AHR and TGF{beta} pathway dysregulation. Findings suggest that maternal iAs exposure primes offspring for asthma risk through epigenetic alterations and may inform risk assessment and biomarker development in affected communities. KEY FINDINGSO_LIIn utero exposure to 10 part per billion (or 10 {micro}g/L, the current WHO and EPA provisional level in drinking water) inorganic arsenic (iAs) increases offspring asthma risk. These results raise concerns about the current safety thresholds for iAs in drinking water (Fig. 1). C_LIO_LITranscriptomic and methylome analyses of blood leukocytes from 5-month-old F1 mice revealed that maternal iAs exposure induces transcriptional changes in genes related to allergic airway responses. Pathway analysis highlighted the involvement of miR-101c and its connection with TGF{beta} downstream targets in regulating extracellular matrix signaling, embryonic development, and inflammatory (Figs. 2 and 3). C_LIO_LITranscriptional changes in col3a1 and miR-101c in blood were strongly correlated with allergen-induced airway hyperresponsiveness (AHR), with similar alterations detected in plasma samples. These findings provide new insights into respiratory health in affected communities and support the development of biomarkers for iAs risk assessment (Figs. 4 and 5). C_LIO_LISeveral gene-specific epigenetic alterations induced by early-life iAs exposure were consistently observed in both surrogate (blood) and target (lung) tissues across developmental stages, offering new panels of easily accessible markers for early detection and monitoring of lung disease risk in offspring. The persistence of these markers over time makes them valuable for predictive modeling and life course studies. (Fig. 6). C_LIO_LIDownregulation of miR-101c was validated in fetal lung and amniotic fluid of the iAs-exposed group, suggesting that epigenetic reprogramming of miR-101c is initiated early in gestation (Fig. 7). These findings help uncover causal pathways linking environmental exposures to asthma pathogenesis. C_LIO_LIDistinct sex-specific patterns in blood transcriptome and methylome alterations in respond to early-life iAs exposure underscore the importance of considering sex as a biological variable in omics research. C_LI O_FIG O_LINKSMALLFIG WIDTH=149 HEIGHT=200 SRC="FIGDIR/small/668223v1_fig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1f5394eorg.highwire.dtl.DTLVardef@855bf8org.highwire.dtl.DTLVardef@1592328org.highwire.dtl.DTLVardef@1133ec4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Maternal iAs exposure and study design to assess offspring asthma risk. A) Schematic shows the exposure window in which F0 dams received iAs in drinking water from preconception through lactation, followed by collection of F1 progeny for transcriptomic and methylomic analysis. A subset of 5-month-old F1 progenies were assessed for the HDM allergen-induced airway reactivity and airway inflammation. B) Lung resistance was assessed following methacholine (30mg/mL) challenge. C) BAL cells were stained with Diff-Quick, and eosinophil counts are shown. Each datapoint represents a pup from an individual dam; error bars indicate SEM. Five to six dams were used. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/668223v1_fig2.gif" ALT="Figure 2"> View larger version (23K): org.highwire.dtl.DTLVardef@7dc1b1org.highwire.dtl.DTLVardef@378529org.highwire.dtl.DTLVardef@1076fe3org.highwire.dtl.DTLVardef@142d801_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 2.C_FLOATNO Blood transcriptome profiles and predicted canonical pathways and regulatory networks. A) Numbers of differentially expressed genes (DEGs) identified in male and female progeny are illustrated with a Venn diagram. Enriched canonical pathways ranked by the p value are shown. B) Using the set of DEGs common in both sexes, Ingenuity Pathway Analysis (IPA) highlights TGF as a central upstream regulator linking overlapping DEGs related to extracellular matrix signaling (orange), inflammation (yellow), and embryonic development/cell metabolism (blue). C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/668223v1_fig3.gif" ALT="Figure 3"> View larger version (23K): org.highwire.dtl.DTLVardef@1732b53org.highwire.dtl.DTLVardef@216332org.highwire.dtl.DTLVardef@1f794d1org.highwire.dtl.DTLVardef@14b62df_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 3.C_FLOATNO Blood methylome analysis and associations between miR-101c and TGF-related differentially expressed genes. A) Number of differentially methylated CpGs (DMCs) identified in male and female progeny are illustrated with a Venn diagram. There are four DMCs overlapping DMCs annotated to miR-101c. B) Expression levels of miR-101c are shown. C) IPA-derived network linking this miRNA to TGF-related DEGs. Each datapoint represents a pup from an individual dam; error bars indicate SEM. Four to five dams were used. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/668223v1_fig4.gif" ALT="Figure 4"> View larger version (38K): org.highwire.dtl.DTLVardef@482e86org.highwire.dtl.DTLVardef@e666bdorg.highwire.dtl.DTLVardef@631538org.highwire.dtl.DTLVardef@10618f6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 4.C_FLOATNO Relationship between iAs-induced blood transcriptional changes and allergen-induced AHR. This figure presents correlation patterns between baseline blood DEGs expression changes prior to HDM challenge and subsequent changes in AHR. Pearson correlation coefficients are depicted using a color gradient to distinguish positive (blue) and negative (peach) associations. * Positive correlation: r>0.8, p<0.05; ^ negative correlation: r<-0.8, p<0.05 C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/668223v1_fig5.gif" ALT="Figure 5"> View larger version (20K): org.highwire.dtl.DTLVardef@150d27eorg.highwire.dtl.DTLVardef@12b4edeorg.highwire.dtl.DTLVardef@4702a8org.highwire.dtl.DTLVardef@1ff9600_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 5.C_FLOATNO Circulating miR-101c levels in progeny exposed to maternal iAs. Plasma levels of miR-101c and COL3A1 protein are shown at different developmental stages. A) Relative expression of miR-101c across F1 progeny at juvenile (3 weeks of age) and adult (5 months of age) prenatally exposed to iAs. B) Levels of COL3A1 protein are shown at juvenile and adult F1 progeny. Each datapoint represents a pup from an individual dam, error bars indicate SEM. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/668223v1_fig6.gif" ALT="Figure 6"> View larger version (46K): org.highwire.dtl.DTLVardef@d0ec76org.highwire.dtl.DTLVardef@5468a2org.highwire.dtl.DTLVardef@1a17e85org.highwire.dtl.DTLVardef@17956ce_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 6.C_FLOATNO Comparison of transcriptional patterns across tissues and developmental stages. Expression changes (FC: fold changes vs. unexposed) of DEGs and miR-101c are compared between blood and lung tissues in both A) juvenile (3 weeks of age) and B) adult (5 months of age) progeny. Blue and orange bars represent FC in blood from male and female progeny, respectively. Black bars represent FC in lung tissues. Solid bars indicate statistically significant changes. C_FIG O_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC="FIGDIR/small/668223v1_fig7.gif" ALT="Figure 7"> View larger version (22K): org.highwire.dtl.DTLVardef@131ef23org.highwire.dtl.DTLVardef@14b0652org.highwire.dtl.DTLVardef@8c1b30org.highwire.dtl.DTLVardef@4cf6d9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 7.C_FLOATNO Fetal lung and amniotic fluid levels of miR-101c. Relative levels of miR-101c are shown in fetal lung tissues and matched amniotic fluid at embryonic day 16. Data illustrate expression patterns in the context of maternal iAs exposure. Each datapoint represents a pup from an individual dam, error bars indicate SEM. C_FIG GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/668223v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@e25f49org.highwire.dtl.DTLVardef@1dddc22org.highwire.dtl.DTLVardef@9f4244org.highwire.dtl.DTLVardef@1b787e9_HPS_FORMAT_FIGEXP M_FIG C_FIG Description: F1 progeny prenatally exposed to iAs were assessed for blood transcriptomic and DNA methylome analysis at 5 months of age. Correlation analysis between transcriptional changes and allergen-induced airway hyperresponsiveness (AHR) was conducted to examine the epigenetic impact of maternal iAs exposure on offspring asthma risk.

genomics↗
bioRxiv2025

Comprehensive Transcriptomic and Epigenomic Insights into Environmental Toxicant Exposures: The TaRGET II Resource

Environmental exposures to toxic chemicals can profoundly alter the transcriptome and epigenome in both humans and animals, contributing to disease development across the lifespan. To elucidate how early-life exposure to toxicants exerts such persistent effects, the Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription II (TaRGET II) Consortium generated a landmark resource comprising 2,564 epigenomes and 1,043 transcriptomes from longitudinal studies in mice. All data are publicly available through the TaRGET II data portal and the WashU Epigenome Browser. This resource from target (liver, brain, lung, heart) and surrogate (blood) tissues at weaning (3 weeks) and two adult time-points (5 and 10 months) characterized the molecular response to arsenic (As), lead (Pb), bisphenol-A (BPA), di-2-ethylhexyl phthalate(DEHP), tributyltin (TBT), tetrachlorodibenzo-p-dioxin (TCDD), and particulate matter with a diameter of <2.5m (PM2.5). The findings revealed persistent, toxicant-specific, sex-dependent epigenomic and transcriptomic perturbations, resulting in disrupted expression of 14,908 genes, altered chromatin accessibility at 87,409 regulatory elements, DNA methylation changes at 113,186 genomic regions, and chromatin state switching of histone modifications. The resulting high-resolution map of how environmental exposures reprogram the epigenome and transcriptome is broadly accessible via ToxiTaRGET database, offering unparalleled opportunities for the scientific community to investigate the molecular underpinnings of environmental toxicant exposures and their contributions to disease pathogenesis.

pharmacology and toxicology↗
bioRxiv2025

Periventricular Diffusivity Reflects APOE4-modulated Amyloid Accumulation and Cognitive Impairment in Alzheimers Continuum

BackgroundAltered glymphatic-related fluid dynamics are increasingly recognized as a key feature of Alzheimers disease (AD). We generalized an established diffusion imaging technique to estimate periventricular diffusivity (PVeD), hypothesizing that fast diffusion signals in the periventricular region can reflect amyloid-beta (A{beta}) deposition across the Alzheimers continuum. MethodsParticipants from two multi-site cohorts (n = 440 and 414), comprising cognitively unimpaired individuals, those with mild cognitive impairment, and patients with AD, were included. We tested and validated the association of PVeD with A{beta} burden and core AD characteristics. ResultsLower PVeD was extensively associated with greater A{beta} burden, neurodegeneration, cognitive impairment, and clinical severity. Importantly, the relationship between PVeD and A{beta} burden was significantly modulated by APOE4 status, with APOE4 carriers showing a stronger negative association. Baseline PVeD also predicted longitudinal cognitive decline. DiscussionThese findings suggest that periventricular fast diffusion signals can reflect APOE4-modulated A{beta} burden and cognitive decline in AD. Research-in-ContextO_ST_ABSSystematic reviewC_ST_ABSA comprehensive PubMed literature search indicates that fluid movement related to glymphatic activity assessed by diffusion tensor image analysis along the perivascular space (DTI-ALPS) is associated with amyloid-beta deposition in Alzheimers disease (AD). However, recent evidence underscores certain limitations of DTI-ALPS, suggesting that it may not fully capture the diffusion processes involved in amyloid clearance. Moreover, no previous studies have investigated the role of APOE4 in modulating the relationship between glymphatic-related fast diffusion signals and amyloid-beta deposition. InterpretationThe transverse diffusion process along the perivenous space in the periventricular region appears to reflect glymphatic-related dysfunction manifested by amyloid-beta deposition. Reduced periventricular diffusivity is associated with greater amyloid burden across the AD continuum. This association is notably enhanced in APOE4 carriers, who exhibit higher amyloid accumulation for a given reduction in the periventricular diffusivity. Besides, periventricular diffusivity is related to other pathological markers of AD, including clinical symptom severity and neurodegeneration, and may also predict subsequent cognitive decline. Future directionsAlthough diffusion-based neuroimaging metrics hold promise as surrogate imaging biomarkers for glymphatic-related activity, they do not comprehensively capture the complex fluid dynamics such as convective bulk flow within the glymphatic system. By leveraging multimodal neuroimaging techniques and advanced analytic approaches, future research can refine these metrics into more sensitive, non-invasive tools capable of evaluating fluid dynamics related to glymphatic dysfunction in AD.

neuroscience↗
bioRxiv2024

Semaphorin 4A maintains functional diversity of the hematopoietic stem cell pool

Somatic stem cell pools are comprised of diverse, highly specialized subsets whose individual contribution is critical for the overall regenerative function. In the bone marrow, myeloid-biased HSC (myHSC) are indispensable for replenishment of myeloid cells and platelets during inflammatory response but at the same time, become irreversibly damaged during inflammation and aging. Here, we identify an extrinsic factor, Semaphorin 4A (Sema4A), which non cell-autonomously confers myHSC resilience to inflammatory stress. We show that the absence of Sema4A, myHSC inflammatory hyper-responsiveness in young mice drives excessive myHSC expansion, myeloid bias and profound loss of regenerative function with age. Mechanistically, Sema4A is mainly produced by neutrophils, signals via a cell surface receptor Plexin D1 and safeguards myHSC epigenetic state. Our study shows that by selectively protecting a distinct stem cell subset, an extrinsic factor preserves functional diversity of somatic stem cell pool throughout organismal lifespan.

cell biology↗
bioRxiv2024

Integrative single-cell analysis of neural stem/progenitor cells reveals epigenetically dysregulated interferon response in progressive multiple sclerosis

Progressive multiple sclerosis (PMS) is characterized by a primary smouldering pathological disease process associated with a superimposed inflammatory activity. Cellular and molecular processes sustaining the pathobiology of PMS remain to be identified. We previously discovered senescence signatures in neural stem/progenitor cells (NSCs) from people with PMS. Applying direct reprogramming to generate directly induced NSCs (iNSCs) from somatic fibroblasts, we retain epigenetic information and observe hypomethylation of genes associated with lipid metabolic processes and IFN signalling only in PMS lines. Single-cell/nucleus transcriptomic and epigenetic profiling reveal an inflammatory, senescent-like, IFN-responsive radial glia (RG)-like cell subcluster mainly in PMS iNSCs that is driven by IFN-associated transcription factors. Lastly, we identify a population of senescent, IFN-responsive, disease-associated RG-like cells (DARGs) in the PMS brain that share pseudotime trajectories with iNSCs in vitro. We describe the existence of a non-neurogenic, dysfunctional DARG population that has the potential to fuel smouldering inflammation in PMS.

neuroscience↗