Biology subjects

Park, J.

Publications and source records attributed to Park, J..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

Labile iron overload reprograms microglia and neurons for lipid droplet synthesis in the aging brain

Lipid-droplet (LD) accumulation emerges in microglia and neurons with age. Because neither cell type is specialized for lipid storage, LDs are linked to dysfunction. The upstream drivers of LD formation and their effects on neighboring cells remain unclear. Here, we identify a mitochondrial-iron axis that promotes LD formation in aging microglia via reactive oxygen species (ROS), which secondarily reshapes neuronal iron handling. LD-enriched microglia show reduced mitochondrial mass and increased labile iron, ROS, and lipid peroxidation. Chelating labile iron or scavenging ROS suppresses LD formation. Conditioned media from iron-stressed microglia alter neuronal iron homeostasis, indicating transcellular coupling. In primary neurons, iron overload increases LDs and activates coordinated iron, ROS, and lipogenesis programs, whereas antioxidant treatment attenuates iron-driven LD accumulation. Together, these findings position iron overload as an upstream regulator of ROS-dependent LD biogenesis in microglia and neurons and reveal a microglia-neuron axis that regulates neuronal iron metabolism during aging.

immunology↗

bioRxiv2025

Type 2 Diabetes and Obesity Alter Exercise Training-Induced Transcriptional Adaptations to Subcutaneous White Adipose Tissue

White adipose tissue (WAT) dysfunction contributes to obesity-associated metabolic disease and type 2 diabetes (T2D). Rodent studies have demonstrated that exercise training improves WAT function, but molecular studies investigating exercise training effects on WAT in humans have been limited, particularly in the context of metabolic disease. Here, we defined the subcutaneous WAT (scWAT) transcriptome in middle-aged adults (10 male, 19 female) that were classified by lower BMI (<27 kg/m2), higher BMI ([≥]27 kg/m2), and T2D status before and after a 10-week endurance exercise regimen. At baseline, 624 genes were significantly upregulated and 112 genes downregulated in the scWAT from higher BMI participants compared to lower BMI. There was a spectrum of pathway dysregulation in scWAT in higher BMI individuals, ranging from increased markers of extracellular matrix (ECM) deposition and inflammation to decreased circadian rhythm gene expression. In people with T2D, there were additional transcriptomic differences such as translation-related pathways, selenoamino acid metabolism, and proteoglycans. Exercise training had robust effects on the transcriptome regardless of metabolic status, and notably, for the high BMI and T2D groups, training reversed several of the detrimental gene expression patterns in a cell-type-specific manner. These beneficial exercise-induced transcriptomic adaptations significantly correlated with lower levels of free fatty acids and blood pressure, particularly in participants with higher BMI and T2D. By integrating our exercise training-modulated genes with GWAS meta-analysis of physical activity, genes influenced by exercise training in the higher BMI group showed a significant enrichment in genetic associations of exercise traits in the population. A circadian rhythm-related transcription factor NR1D1 was enriched in enhancers linked with both the exercise differentially expressed genes (DEGs) and GWAS signals, suggesting a link between the circadian rhythm and training-induced adaptations. These findings demonstrate that obesity and T2D result in marked, progressive alterations in cell-type specific gene transcription in scWAT, while endurance exercise training reverses many of the metabolic disease-associated adaptations. Identification of novel molecular pathways regulated by exercise training can lead to therapeutic targets for obesity and metabolic disease.

molecular biology↗

bioRxiv2025

Off-the-Shelf Engineered Liver Tissue Reverses Acute Liver Failure Without Immunosuppression

There is an urgent need for effective solutions to replace liver functions in patients with acute liver failure (ALF). We describe here a human engineered liver tissue composed of induced pluripotent stem cell (iPSC)-derived liver organoids encapsulated within a non-degradable biomaterial. Unlike most stem cell-derived products, this encapsulated liver tissue (ELT) achieves functional maturation during manufacturing. When transiently implanted into the peritoneal cavity of immunocompetent mice with ALF, the human ELT improves survival, treats hepatic encephalopathy and promotes liver regeneration, without requiring immunosuppression. Based on robust processes and designed to overcome challenges such as foreign body reaction, loss of function and cryopreservation, the ELT does not require vascularization and provides immediate and long-lasting functional replacement. Once the liver regenerated, the ELT is explanted, leaving the subjects cured. Macroencapsulation prevents rejection by shielding the organoids from the host immune system, and minimizes the risk of tumorigenicity. The data shown demonstrate the ELTs potential to be developed into a safe and effective off-the-shelf treatment that, if validated in upcoming clinical trials, could replace liver transplantation for many patients with ALF.

bioengineering↗

bioRxiv2025

Parallelized Brightfield and Fluorescence Imaging of Organoids Using a Scalable Multi-Camera Platform

Organoid viability, maturation, and growth is commonly assayed through brightfield and fluorescence microscopy using a single objective lens. However, standard microscopic imaging systems pose significant limitations for high-throughput applications, particularly in large-scale experiments where simultaneous imaging of multiple organoids requires increased throughput. There is a strong need for systems that can capture organoid growth rapidly and consistently while minimizing disturbances to culture conditions. Here, we present a novel multi-camera array scanner (MCAS) that parallelizes imaging through the simultaneous use of 48 objective lenses and sensors, resulting in a 95% reduction in acquisition times compared to commercial high-content imagers. We demonstrate and validate this system in multiple well plate formats, in both 2D and 3D neural cell cultures, and in brightfield and fluorescence. The MCAS improves efficiency for measuring organoid growth rates, assessing responses to morphogens and drugs, and measuring viral transduction efficiency. Together, these findings establish the MCAS as a scalable and versatile imaging platform for rapid phenotyping in organoid research.

neuroscience↗

bioRxiv2025

Artificial Intelligence-enabled Histological Analysis in Preclinical Respiratory Disease Models: A Scoping Review

Histological analysis is a cornerstone of preclinical respiratory disease research, enabling assessment of pathology, therapeutic effects, and mechanisms. However, conventional approaches rely on manual scoring, which is subjective, time-consuming, and difficult to scale due to low throughput and inter-observer variability. Artificial intelligence (AI), particularly deep learning, offers potential to automate histology workflows, but its use and evaluation in preclinical respiratory models have not been synthesized. We conducted a scoping review following Joanna Briggs Institute guidelines, searching MEDLINE and Embase (inception-January 2025) for preclinical studies using AI to analyze histology in respiratory disease models. Screening, full-text review, and data extraction were performed in duplicate. Of 6271 studies screened, 29 met inclusion criteria. Most used murine models (76%) and investigated lung cancer (28%), pulmonary fibrosis (24%), or tuberculosis (17%). Hematoxylin and eosin was the most common stain (48%), with others targeting collagen or immune markers. AI tasks included image classification (n=20), segmentation (n=10), and object detection (n=4), predominantly using convolutional neural networks (69%). Preprocessing methods (e.g., stain normalization) were common, but annotation and training practices were inconsistently reported. Performance was generally high (accuracy [≥]90%; 7 studies) though validation metrics varied, and external validation was absent. Most studies used "black box" models, with minimal application of explainability techniques. Reproducibility measures, such as sharing datasets or code were rarely reported. AI tools are poised to transform histological analysis in preclinical respiratory research. By addressing gaps in validation, transparency, and standardization, the field can harness these technologies to deliver robust, efficient, and scalable workflows. Registration: Open Science Framework https://doi.org/10.17605/OSF.IO/NM94E

cell biology↗

bioRxiv2025

Multi-platform framework for mapping somatic retrotransposition in human tissues

Mobile element insertions (MEI) shape the human genome in both germline and somatic tissues. While inherited MEIs are well characterized, mapping somatic MEIs (sMEI) in non-cancer tissues remains challenging due to their low allelic fraction and repetitive nature. We established an integrative framework for sMEI analysis leveraging modern sequencing technologies and analytical innovations. We first benchmarked sMEI detection and demonstrated advantages of long-read and MEI-targeted sequencing for ultra-low-frequency events using a mixture of well-established cell lines. We then showed that haplotype phasing and donor-specific assemblies refine sMEI detection, effectively distinguishing from germline and false signals in in-silico tumor-normal mixtures. We further developed a source-tracing strategy based on internal sequence variation, expanding the catalogue of active source elements beyond traditional transduction-based methods. Applying this framework to donor tissues, we identified 18 rare somatic L1 insertions, revealing structural and source diversity. Our work provides a foundational framework and biological insight into sMEIs.

genomics↗

bioRxiv2025

Single-cell spatial mapping reveals dynamic bone marrow microarchitectural alterations and enhances clinical diagnostics in MDS

Myelodysplastic neoplasms (MDS) disrupt bone marrow hematopoiesis, yet clinical assessment relies largely on blast enumeration and qualitative morphology, which incompletely capture marrow architecture and disease state. We applied whole-slide multiplex immunofluorescence imaging with single-cell phenotyping to map bone marrow microarchitecture in MDS. Diagnostic biopsies (n=36), longitudinal treatment samples (n=29), precursor states (n=13), and normal controls (n=21) were analyzed, comprising >5 million spatially resolved cells. MDS marrow exhibited coordinated, genotype-imprinted architectural remodeling, including altered progenitor composition and spatial patterning, disrupted erythroid island organization, and displacement of hematopoietic stem and progenitor cells from perivascular niches. Interrogation of 82 cellular and spatial features yielded a composite Microarchitectural Perturbation Score (MDS-MAPS), derived from diagnostic samples and fixed prior to longitudinal analyses. In leave-one-patient-out cross-validation, MDS-MAPS discriminated remission from active disease more accurately than blast percentage (AUC 0.883 vs 0.660) and distinguished low-blast MDS from clonal cytopenia of undetermined significance (CCUS) (AUC 0.815). Mixed-effects modeling showed MAPS decreased in remission statistically independent of blast burden, with architectural normalization during remission and re-emergence at relapse. These findings define quantitative bone marrow architecture as a dynamic tissue-state biomarker that complements molecular and blast-based assessment in MDS.

pathology↗

bioRxiv2025

The tetraspanin disc proteins, peripherin-2 and ROM1, facilitate CNG channel localization to the rod outer segment

The light-responsive outer segment of rod photoreceptors is composed of two distinct membrane subdomains: discs and the plasma membrane. We investigate how the disc protein peripherin-2 is engaged in CNG channel delivery to the outer segment. Instead of forming outer segments, peripherin-2 knockout (Rds-/-) photoreceptors release ciliary ectosomes, in which CNG channel levels are markedly reduced relative to other outer segment proteins. This is intriguing as downregulation of the CNG channel is not a general feature of degenerative mouse models with dysmorphic outer segments. Overexpression of the {beta}1-subunit of CNG in Rds-/- rods reveals that the majority is trapped in intracellular membranes, but is restored to the outer segment by co-expressing peripherin-2. We test peripherin-2 chimeras containing either the N-terminus, tetraspanin core, or C-terminus and find that the tetraspanin domain is sufficient to localize CNG{beta}1 to the outer segment. We further show that the membrane remodeling function of the tetraspanin domain facilitates this process by the redundant action of the tetraspanin domain from ROM1 and the reemergence of the endogenous CNG channel in aged Rds-/- rods that have produced ciliary membrane protrusions.

cell biology↗

bioRxiv2025

Circadian phosphotimer generates time cues through PER dimerization-mediated trans-phosphorylation

The circadian clock generates autonomous molecular rhythms that regulate sleep cycles, chronotypes, daily physiology, and expression patterns of almost the entire genome. Temporal phosphorylation of PERIOD (PER) proteins creates a phosphotimer that is critical for clock function. Although previous studies show that PER stably binds the casein kinase CK1, cis-acting phosphorylation of PER by CK1 is not compatible with slow PER phosphorylation extended over 24 hrs. So how can PER phosphorylation be programmed in a slow and controlled manner? Here, we show that the timing cues are encoded by PER-PER dimerization-mediated trans-phosphorylation, which enables the necessary time delay in phosphorylation and slow phosphorylation. When PER dimerization is disrupted, PER phosphorylation and circadian rhythms are severely compromised. In mouse models with point mutations in the PER dimerization domain, circadian period is shortened to [~]20 hrs, and the phase of wake/sleep cycles is dramatically advanced, switching a nocturnal animal to a half diurnal animal.

neuroscience↗

bioRxiv2025

Human patient-specific FOXG1 syndrome mouse model revealed FOXG1-MYCN-mediated regulation of protein homeostasis in neurodevelopmental disorder

Neurodevelopmental disorders are characterized by disruptions in brain development, resulting in cognitive, behavioral, and neurological impairments. FOXG1 syndrome (FS), caused by heterozygous mutations in the FOXG1 gene, exemplifies a severe monogenic neurodevelopmental disorder. To investigate its pathogenesis, we generated a patient-specific W300X mouse model carrying a truncation variant of FOXG1. We found that the truncated FOXG1 protein in W300X-heterozygous (W300X-Het) mice is more abundant and more nuclear-localized than the full-length FOXG1 protein, implicating a pathogenic mechanism involving the truncated protein. Interestingly, W300X-Het mice exhibited profound abnormalities in the dentate gyrus, including disrupted neurogenesis, impaired granule cell migration, and altered dendritic morphology. Transcriptomic profiling identified broad dysregulation in protein homeostasis pathways, particularly ribosomal biogenesis, translation, and proteostasis. Disruption of the FOXG1-MYCN pathway, critical for robust protein synthesis during neural stem cell division, synaptogenesis, and synaptic plasticity, emerged as a key mechanism underlying these defects. In parallel, microglial activation and inflammation were markedly increased in the dentate gyrus, contributing to a pro-inflammatory environment that exacerbates neurogenic and structural deficits. Consistent with hippocampal dysfunction in FS patients, W300X-Het mice exhibited significant spatial learning and memory impairments. Together, our study highlights disrupted protein homeostasis and neuroinflammation as key drivers of FS pathogenesis, providing a framework for developing therapeutic strategies targeting these pathways.

neuroscience↗

bioRxiv2025

ARID1A and ARID1B safeguard B cell identity, prevent myeloid transformation and expose therapeutic vulnerabilities in lymphoma

Chromatin remodeling by the SWI/SNF complex is essential for hematopoietic lineage commitment and differentiation. While core subunits ARID1A and ARID1B are frequently mutated in B cell malignancies, their functions remain unclear. Recent work established ARID1A- dependent functions within germinal center (GC) B cells, but its role during early B cell development, and whether its homolog, ARID1B, contributes distinct or compensatory roles at steady state or during transformation, remain unknown. Here, we used CD19-Cre-mediated deletion initiated at the pro-B cell stage to investigate their role in B cell development in vivo. Loss of either gene partially blocked B cell differentiation, reducing immature/recirculating B cell output, and impaired germinal center formation following antigen challenge. Combined deletion further reduced peripheral B cells, shortened survival, and resulted in aggressive leukemia. Unexpectedly, the malignancy was of myeloid origin and arose from a subset of CD19-expressing multipotent progenitors (MPPs). Arid1a/Arid1b-deficient MPPs exhibited abnormal expansion, reduced colony formation, and dysregulation of stemness and lineage-priming programs, including diminished CBFA2T3 (ETO2) and Fli1 signatures. In established B cell lymphoma cells in vitro, double ARID1A/ARID1B loss modestly affected cell growth, whereas loss of ARID1A increased sensitivity to EZH2 inhibition. Transcriptomic analyses revealed alterations in cell adhesion/migration pathways, cytokine-receptor interactions and DNA repair mechanisms. Collectively, these findings reveal stage-specific and compensatory roles for ARID1A and ARID1B in B cell development, uncover a mechanism by which SWI/SNF loss in MPPs redirects transformation towards myeloid leukemia, and suggest context-dependent therapeutic vulnerabilities.

cancer biology↗

bioRxiv2025

Prediction of zoonotic virus-host transmissibility using comparative airway organoids

AbstractThe emergence of new pandemic zoonotic diseases is accelerating. However, current approaches to control after outbreaks often allow the epidemic or pandemic spread of new zoonotic diseases, exemplified by the case of COVID-19. Prediction of zoonotic transmissibility will help minimize the outbreaks and socioeconomic damage. Here, we established highly efficient comparative airway organoids with minimal components from a panel of mammalian species for long-term culture and passaging and validated their utility to predict the transmissibility of zoonotic pathogens. Airway organoids from each species recapitulated the airway histology and contained the major cell types in the airway. They recapitulated the known susceptibility of their host species and tissues to diverse viruses. Transcriptomic analyses revealed that organoids from susceptible species induced genes of anti-viral immune responses only in common upon exposure to the same virus, although each species organoids displayed differential gene expression profiles. Also, organoids of the same species displayed differential transcriptomic responses against different viruses but induced anti-viral immune genes only in common. Our work provides a roadmap for comprehensive species- and tissue-level organoid panels for quick and reproducible uncharacterized pathogen surveillance to predict and prevent the next pandemic.

developmental biology↗

bioRxiv2025

Tumor-myeloid crosstalk drives therapy resistance in localized bladder cancer

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

cancer biology↗

bioRxiv2025

The mechanical code of DNA links DNA bending nucleosome organization and codon choice

Nucleosomes are the fundamental units of chromatin, yet how DNA sequence encodes the mechanics required for their formation remains incompletely understood. Using high-throughput measurements and predictive modeling, we show that nucleosomal DNA is distinguished not only by enhanced isotropic bendability but by coherent anisotropic bending aligned with the DNA helical repeat. Within nucleosome footprints, anisotropy vectors are phase-aligned across thousands of sequences, yielding ensemble-level signatures--such as [~]15 full rotations of bending direction--that directly mirror histone-DNA wrapping. We show that within nucleosomes, reinforcement of bending direction every helical repeat pre-disposes DNA to wrap smoothly around histones, lowering the energetic cost of nucleosome formation. Extending these principles to coding regions, we demonstrate that synonymous codon usage bias varies systematically around nucleosomes in a manner that optimizes DNA mechanical and structural features around nucleosomes and suggest that degeneracy of the genetic code has been exploited to encode both proteins and chromatin architecture. Together, our findings establish DNA anisotropy as a pervasive, sequence-encoded feature of nucleosomal DNA and identify codon usage as a key contributor to this hidden mechanical code.

biophysics↗

bioRxiv2025

Rapid elicitation of a new class of neutralizing N332-glycan independent V3-glycan antibodies against HIV-1 in nonhuman primates.

Sequential immunization is a promising approach to elicit broadly neutralizing antibodies (bNAbs) against the HIV-1 Envelope (Env). However, available protocols are inefficient and involve multiple immunizations over long periods of time. Here, we present WIN332, a new engineered Env-immunogen that induces a new class of neutralizing N332-glycan-independent antibodies to the conserved V3-glycan epitope of Env after a single bolus immunization in nonhuman primates. WIN332 binds to precursors of canonical human N332-glycan-dependent (Type-I) V3-glycan bNAbs but also of a first-of-its-class N332-glycan-independent (Type-II) V3-glycan bNAb. A single immunization elicits neutralizing serum and monoclonal antibodies that are boosted and affinity matured with a heterologous immunogen. EMPEM analysis of serum antibodies, antibody cloning and cryo-EM analysis reveal that WIN332 elicits N332-glycan-independent antibodies with remarkable sequence and binding similarities with the most potent human type-I and type-II V3-glycan bNAbs. Thus, WIN332 is a promising vaccine candidate to streamline V3-glycan bNAb elicitation.

immunology↗

bioRxiv2025

In Silico Design of APOE ε4 Interaction Inhibitor Peptides for Alzheimer's Disease

BackgroundProtein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzheimers disease (AD), characterized by its complex pathogenesis, poses an increasing societal burden with population aging. The APOE {varepsilon}4 allele represents the strongest genetic risk factor for late-onset AD, yet its pathological mechanisms remain incompletely understood. MethodsWe employed artificial intelligence-driven peptide design to elucidate the pathological interaction between APOE {varepsilon}4 and amyloid precursor protein (APP). Using advanced AI algorithms, we identified critical binding interfaces and designed mimetic peptides targeting the APOE {varepsilon}4-APP interaction site. Peptide efficacy was evaluated through comprehensive molecular dynamics simulations. ResultsOur analysis revealed key residues mediating APOE {varepsilon}4-APP binding. The designed inhibitory peptides demonstrated stable interaction with target sites, favorable binding energetics, and sustained structural integrity throughout simulations. Lead candidate effectively disrupted APOE {varepsilon}4- APP complex formation in silico. ConclusionThis study presents a novel AI-powered approach for developing PPI-targeted therapeutics against AD. Our computationally validated peptide inhibitors offer promising therapeutic candidates that warrant experimental validation. These findings demonstrate the potential of integrating artificial intelligence with structural biology for accelerating drug discovery in neurodegenerative diseases.

bioinformatics↗

bioRxiv2025

Machine learning-driven decoding of maternal immune signatures in repeated pregnancy loss

BackgroundRepeated pregnancy loss (RPL) is a multifactorial condition in which the underlying immunological mechanisms remain incompletely understood. Although immune tolerance at the maternal-fetal interface is critical for successful pregnancy, the immune disruptions that contribute to RPL, independent of fetal aneuploidy, remain poorly characterized. MethodsWe performed single-cell RNA sequencing of decidual tissues from RPL patients and gestational age-matched controls. We employed single-cell transcriptomics coupled with genotype-based origin analysis to dissect immune dysregulation in RPL. To identify cell type-specific RPL signatures, we mutually applied a supervised machine learning model and foundation model-based analysis, followed by pathway enrichment and network analysis. In addition, we prioritized drug repurposing candidates based on the drug response data, which reversed the RPL-associated transcriptional profiles. ResultsIn normal pregnancy, fetal immune cells were nearly absent but increased in RPL, whereas fetal trophoblasts were reduced, suggesting hindered placental development despite the absence of chromosomal abnormalities in fetal cells. Interestingly, by showing a strong common rejection module score, RPL immune cells resemble the transcriptional signatures of acute transplant rejection, indicating the contribution of the maternal immune system. Our machine learning and transformer-based models mutually identified T-cell-derived transcriptomic signatures that distinguished RPL immune cells. By examining biological confounding factors, including fetal-origin signatures, we prioritized CXCR4 and JUN in maternal T cells as RPL-associated signatures. For clinical application, we explored reversed transcriptional signatures from drug response data, and three compounds were highlighted as candidates for drug repurposing. ConclusionsTogether, our approach identifies maternal immune signatures such as those of CXCR4 and JUN and links them to potential drug repurposing candidates, thereby providing both mechanistic insights and therapeutic opportunities for RPL.

bioinformatics↗

bioRxiv2025

Adaptive generalization and efficient learning under uncertainty

People often use recognizable features to infer the value of novel consumables. This "generalization" strategy is known to be beneficial in stable environments, such that individuals can use previously learned rules and values in efficiently exploring new situations. However, it remains unclear whether and how individuals adjust their generalization strategy in volatile environments where previously learned information becomes obsolete. We hypothesized that individuals adaptively use generalization by continuously updating their beliefs about the credibility of the feature-based reward generalization model at each state. Our data showed that participants used generalization more when the novel environment remained consistent with the previously learned monotonic association between feature and reward, suggesting efficient utilization of prior knowledge. Against other accounts, we found that individuals incorporated an arbitration mechanism between feature-based value generalization and model-based learning based on volatility tracking. Notably, our suggested model captured differential impacts of generalization dependent on the context-volatility, such that individuals who were biased the most toward generalization showed the lowest learning errors when the value of stimuli are generalized along the recognizable feature, but showed the highest errors in a volatile environment. This work provides novel insights into the adaptive usage of generalization, orchestrating two distinctive learning mechanisms through monitoring their credibility, and highlights the potential adverse effects of overgeneralization in volatile contexts.

neuroscience↗