Molecular Omics

Genetic variation impacts biological response to chemical and environmental exposures, contributing to differences in resistance or susceptibility. Forward genetic screens of genetically diverse cell populations can be used to identify the precise genetic variants that drive response variation. Cell lines from laboratory mouse genetic reference populations like the Diversity Outbred (DO) population are well powered for genetic mapping. Diverse stem cell panels are especially beneficial for studying early developmental effects of chemical exposures like triphenyl phosphate (TPHP), an organophosphate flame retardant linked to adverse developmental effects, including altered cell cycle in stem cells. Self-renewal and pluripotency are defining properties of stem cells during development; therefore, it is important to understand how chemicals like TPHP may alter these critical characteristics. To better understand the influence of genetic variation on TPHP exposure response, we utilized a genetically diverse panel of DO induced pluripotent stem cells (DO iPSCs). Our analyses characterize interline variation in gene expression through differential gene expression analysis and expression quantitative trait locus (eQTL) mapping. We identified genomic loci that contribute to variation in gene expression following TPHP exposure, including a regulatory hotspot on chromosome 15. Gene set enrichment highlighted several pathways affected by TPHP including lipid metabolism, steroid hormone signaling, and cell cycle. Our study shows that genetic variation modulates the effects of TPHP on gene expression and cell cycle in stem cells. Additionally, our work demonstrates that genetically diverse cell panels like the DO iPSC resource offer a tractable and scalable approach for identifying the genetic determinants of chemical toxicity.

Phenylketonuria (PKU) is an autosomal recessive disorder caused by PAH gene defects and can cause irreversible neurological damage as early as the fetal period; however, non-invasive prenatal monitoring methods are lacking. In this study, Pah+/- female mice were mated with Pah+/-; male mice and wild-type male mice, respectively. Urine samples were collected longitudinally from pregnant mice at 10 time points during gestation from Day 1 to Day 19. Data-independent acquisition (DIA) quantitative proteomics combined with GO/KEGG analysis, WGCNA, and a dual-strategy LASSO-random forest approach was used to screen candidate biomarkers. The results showed that stable differentially expressed proteins between groups were detectable as early as Day 1, and the differences persisted throughout gestation and exhibited temporal dynamics. Permutation tests indicated that the probability of random generation of the differential protein combination was low (0.04-0.06), suggesting that it was not randomly generated. The intersection of the two strategies yielded five proteins, GINM1, PRG4, LY6A, NTM, and YIPF3, and after including GLO1, a total of six candidate biomarkers were obtained. The candidate proteins had interaction or co-expression associations with 14 proteins involved in PKU mechanisms, with GLO1 serving as a network hub. This study found that the maternal urine proteome can non-invasively reflect the systemic response induced by fetal-origin PKU, providing proof of concept and candidate biomarker resources for non-invasive early-pregnancy screening of PKU.

Chromatin profiling methods, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), are used to characterize the genomic localization of DNA-associated proteins. While ChIP and ChIP-seq have been used for decades, an orthogonal approach, CUT&Tag (Cleavage Under Targets and Tagmentation), is gaining popularity as an efficient and cost-effective alternative. Although previous comparative studies note discrepancies in signal-to-noise ratios and detection bias at certain genomic regions, many differences between ChIP-seq and CUT&Tag results remain largely unreconciled. Here, we systematically investigate the disagreeing signals captured by these two methods across well annotated genomic regions. We assess multiple histone mark profiles generated by different groups in two cell lines (K562 and MCF-7). Overall, our analysis indicates that compared to ChIP-seq, CUT&Tag may have limited sensitivity in low-GC environments and, as previously observed, increased signal in hyper-accessible chromatin. Notably, within GC-poor regions of active gene bodies and Polycomb-repressed domains, CUT&Tag exhibits a loss of H3K36me3 and H3K27me3 signal, respectively, where occupancy of these histone marks is otherwise expected. Further, active promoters with discrepant H3K4me3 and H3K27ac signal between the two assays differ systematically in GC content and chromatin accessibility. Promoters differentially enriched for CUT&Tag signal relative to ChIP-seq generally show higher, broader GC-content profiles and higher DNase-seq and ATAC-seq signal, while promoters enriched for ChIP-seq signal harbor the opposite characteristics. A local bias for high GC content and/or chromatin accessibility in CUT&Tag may also explain its differing signal patterns at nucleosome-depleted regions (NDRs) compared to ChIP-seq and MNase-seq promoter profiles. Altogether, our results highlight that studies focused on profiling the intensity and structure of histone modification occupancy can be sensitive to potential biases of CUT&Tag to GC content and chromatin accessibility. These characteristics should be accounted for when selecting a chromatin profiling approach, analyzing and interpreting data as well as drawing biological conclusions.

Abstract Polycystic ovarian syndrome and Type 2 diabetes mellitus are complex multivariate diseases that share well-established clinical pathophysiology, yet the molecular basis of their overlap is unknown. Prior bioinformatics studies have identified common differentially expressed genes between these two conditions. However, they have not accounted for the directionality of the gene expression changes observed, potentially obscuring any biological distinctions they may have. This study applied a direction-aware approach to classify molecular signatures between PCOS and T2DM as concordant or discordant. Transcriptomic analysis of GEO datasets GSE138518 (ovarian granulosa tissue, PCOS) and GSE25724 (pancreatic islet tissue, T2DM) identified 225 and 1,302 DEGs, respectively. Venn diagram analysis showed that only three genes (SLC6A8, RGS4, and SORL1) were shared between PCOS and T2DM from the total of 1,527 genes, and all 3 genes were regulated in opposing directions. Disease gene retrieval from the Comparative Toxicogenomics Database, Online Mendelian Inheritance in Man database, and GeneCards showed 214 shared disease-associated genes, with 311 genes unique to PCOS and 496 genes unique to T2DM. Protein-protein interaction construction using STRING (version 12.0) identified 70 interacting nodes. CytoHubba analysis across 6 scoring methods identified 18 high-confidence hub genes, including INS, BCL2, MTOR, LEP, MFN2, and PIK3CD. Functional enrichment analysis identified biological processes including immune activation, apoptosis, and insulin signaling, which were confirmed as the main pathways in KEGG pathway analysis. These findings show that while PCOS and T2DM share limited DEGs, they share common pathogenic pathways.

The enzymatic oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) is a key step in the sustainable production of polyethylene furanoate (PEF), yet the final oxidation of 5-formyl-2-furancarboxylic acid (FFCA) to FDCA remains the principal bottleneck for industrial application. Although hydroxymethylfurfural oxidases (HMFOs) can catalyze this transformation, naturally occurring enzymes with high FFCA-oxidizing activity remain largely unexplored. Here, we present an iterative computational bioprospecting campaign to identify natural HMFOs with improved activity toward this rate-limiting reaction. Across four successive rounds, the computational workflow evolved from conservative homology-based screening to large-scale sequence mining assisted by machine learning, with each iteration redesigned according to the principal limitations identified through molecular simulations and experimental characterization. This adaptive strategy led to the discovery of several natural HMFOs with substantially improved FFCA oxidation activity, including candidates whose performance under the tested conditions approached that of the engineered benchmark 8BxHMFO. Beyond the identification of promising biocatalysts, the study demonstrates the value of continuous integration of computational prediction and experimental feedback for refining enzyme discovery campaigns, and provides practical insights into balancing catalytic prioritization, sequence diversity, developability, and computational scalability in future simulation-guided bioprospecting efforts.

Background: Chronic low-grade inflammation and gut microbiota dysbiosis contribute to metabolic syndrome (MS). Huanglian Wendan Decoction (HLWDD) is a defined multi-herbal formulation used in Chinese medicine, but its effects on gut microbiota-associated metabolism and NLRP3 inflammasome signaling remain unclear. Objective: This study evaluated the pharmacological effects and candidate absorbed bioactive constituents of HLWDD in experimental MS. Methods: A high-fat, high-sugar diet-induced rat model of MS was assessed using metabolic, biochemical, histological, molecular, and multi-omics endpoints. Gut metagenomics, untargeted metabolomics of liver and colonic contents, liver transcriptomics, and UPLC-HRMS/MS analysis of serum-absorbed constituents were integrated with network pharmacology and molecular docking. Baicalin was further evaluated in PA-BSA-treated HepG2 cells. Results: HLWDD ameliorated obesity, dyslipidemia, hepatic steatosis, and systemic inflammation and attenuated NLRP3 inflammasome-related signaling. Multi-omics analysis identified nine shared differential metabolites and a strong positive association between Faecalibacterium and butyrate. Thirty-two serum-absorbed constituents were tentatively identified. Baicalin showed favorable predicted interactions with NLRP3 (-5.82 kcal/mol) and CASP1 (-5.41 kcal/mol) and concentration-dependently suppressed NLRP3 inflammasome-related signaling in HepG2 cells; the highest concentration increased intracellular butyrate. Conclusion: HLWDD ameliorated metabolic and inflammatory abnormalities in experimental MS in association with restoration of gut-liver metabolic homeostasis and attenuation of NLRP3 inflammasome signaling. Baicalin emerged as a candidate absorbed bioactive constituent.

The modeling of aroma release in food science is a complex, multidisciplinary field integrating mass transfer theory and principles of physical chemistry. While mechanistic models have long been used to understand volatile release, their practical adoption has been hindered because existing implementations are often private, "in-house" tools that lack reproducibility and extensibility. This paper introduces digimouth, an open-source Python framework designed to provide a unified, modular, and reproducible environment for simulating and fitting aroma release kinetics. A key innovation of digimouth is its handling of events and stages. Events represent discrete, instantaneous changes in the system (such as opening a bottle or swallowing), while stages allow for multi-phase simulations where experimental conditions or physical dynamics change over time. To demonstrate the tool's utility, the authors implemented established in vitro convection models and performed sensitivity analyses on parameters such as air-water partition coefficients and mass transfer coefficients. The package also includes an optimization module based on the least-squares method to fit parameters to experimental data. Validation against real-time data from Proton Transfer Reaction-Time of Flight- Mass Spectrometry (PTR-ToF-MS) shows a satisfactory fit, with an average error of approximately 2%. Ultimately, digimouth facilitates robust model development and hypothesis testing, offering the food science community a collaborative tool to better understand the mechanisms of flavor release.

Methylmalonic aciduria (MMA) is caused by deficiency of methylmalonyl-CoA mutase (MMUT), which catalyses the final step of propionate catabolism and fuels the tricarboxylic acid cycle for energy production. Previous studies reported disrupted mitochondrial homeostasis in MMA, including reduced mitochondrial membrane potential and increased oxidative stress, especially in energetically demanding and chronically affected tissues like brain and kidneys. However, how these changes impact mitochondrial energy production remains unclear. Here, we systematically investigated mitochondrial energy production using extracellular flux analysis in cellular models of MMA, including 293T cells, patient-derived fibroblasts, urine-derived epithelial kidney cells and induced pluripotent stem cells (iPSCs) as well as iPSC-derived neurons harbouring either complete loss (knockout, KO) or pathogenic missense variants in MMUT. We found no impact on mitochondrial energy production in MMUT-KO 293T cells and fibroblasts compared to controls. In contrast, fibroblasts and 293T cells expressing the pathogenic MMUT-p.N219Y variant showed decreased energy production. This corresponds to the altered mitochondrial membrane potential in 293T cells, but contrasts with their unchanged mitochondrial abundance. Depletion of glucose, glutamine and pyruvate from the media or provision of each individually as sole fuel source exacerbated the phenotype of MMUT-p.N219Y clones, but did not induce a phenotype in MMUT-KO 293T cells. Finally, we confirmed reduced mitochondrial energy production in patient-derived kidney cells but found no evidence in MMUT-p.N219Y iPSCs and their derived neurons. Overall, our work suggests that the impact of MMUT-deficiency on mitochondrial energy production is cell type- and variant-dependent. Further investigations should clarify molecular mechanisms and their clinical impact.

Ubiquitination is a post-translational modification with well described roles in the regulation of immune cell function, such as dendritic cells (DCs). DCs are crucial initiators and regulators of T cell-mediated immune responses. In this study, we use activity-based probes and proteomics to systematically profile DUBs in a DC line. Using the lysate-based biotin(bio)-Ubiquitin(Ub)-propargylamide(Prg) probe and proteomics, the activity and abundance of deubiquitinases was measured in unstimulated and CpG-stimulated MutuDCs to simulate responses to bacteria. This analysis was complemented with profiling using the cell-permeable DUB activity-based probe IMP-2373. The combined analysis with bio-Ub-Prg and IMP-2373 provided insights into the dynamics of DUB activity and abundance in DCs following stimulation and identified several DUBs for further study.

Ancestry-related genomic variation may contribute to phenotypic diversity. However, its cellular consequences remain difficult to evaluate. To address this, we developed a human induced pluripotent stem cell (hiPSC)-based framework for investigating such phenotypes. We used the Japanese population as a model of Jomon-related and continental East Asian ancestry admixture. Jomon ancestry, estimated using the Jomon allele score (JAS), was associated with clinical measures, including renal-related traits and serum triglycerides in 34,152 Tohoku Medical Megabank participants. Peripheral blood mononuclear cell transcriptomics of donors from the upper and lower extremes of the JAS distribution (n = 10) suggested group-level differences in immune-related gene expression. To test whether the serum triglyceride association coincided with hepatic cellular phenotypes, we differentiated hiPSCs from these donors into hepatocyte-like cells. Neither intracellular triglycerides nor lipid-related gene expression differed between groups. These findings highlight the value of a genetically characterized hiPSC-based framework for investigating ancestry-associated phenotypes across cellular contexts.

Myelin is an essential and highly specialized membrane in the central and peripheral nervous systems that enwraps axons to accelerate electrical transmission and support neuronal health. The generation of this multilamellar structure requires a tightly coordinated synthesis of specific proteins and lipids. Among these are sphingolipids (SLs), which are major components of myelin. SL production is initiated by the serine palmitoyltransferase (SPT) enzyme complex, the rate-limiting enzyme in the de novo SL biosynthesis pathway. ORMDL proteins (ORMDL1-3) are the regulatory subunits of SPT, which, by sensing ceramide levels, tune SL flux. Although ORMDL3 has been linked to asthma and peripheral myelination, its role in CNS myelination and the CNS myelin-making oligodendrocytes (OLGs) remains unclear. We therefore assessed the function of ORMDL3 in OLs by generating a Cnp-Cre-driven, oligodendrocyte-specific Ormdl3 conditional knockout (cKO) mouse model. Loss of Ormdl3 selectively increased myelin SLs, particularly long-chain sulfatides, without altering ceramide or galactosylceramide abundance. These changes are most prominent around postnatal day 35, a developmental period of active myelin turnover. Ultrastructural analysis of optic nerves shows a thicker myelin sheath and increased axon caliber in cKO mice. Unexpectedly, deletion of Ormdl3 also increases levels of major myelin proteins (MBP, MOG, and PLP) and is accompanied by dynamic, region- and sex-dependent regulation of enzymes involved in sulfatide biosynthesis, without altering OLGs number or maturation. Together, for the first time, these findings identify Ormdl3 as a key regulator of SL homeostasis during developmental myelination and suggest that it helps synchronize lipid synthesis with myelin protein expression.

Tumor-associated macrophages (TAMs) integrate multiple microenvironmental signals, including lectin-mediated recognition of tumor-associated glycans. Although several myeloid lectins have been implicated in tumor-macrophage interactions, their contributions to immunosuppressive TAM phenotypes remain poorly defined. We implemented a CRISPR-Cas9 ribonucleoprotein (RNP) workflow in primary human monocytes to enable comparative loss-of-function interrogation of five potentially immunosuppressive lectins we previously reported. CRISPR-Cas9 RNP delivery conditions were benchmarked in freshly isolated monocytes using CD14 as a technical target, followed by sgRNA editing efficiency screening for CLEC4E, CLEC6A, CD209, SELL, and SIGLEC9 in HeLa S3 cells. Selected guides were applied to primary monocytes before co-culture in a 3D model with BT474 breast cancer cells. Editing was quantified by Sanger-sequencing deconvolution, while co-culture-derived CD45+ macrophages were isolated by fluorescence-activated cell sorting and characterized by bulk RNA sequencing. All five lectins were successfully perturbed, although gene editing efficiency remained target- and donor-dependent. Transcriptomic analysis revealed target-specific reprogramming and recurrent immunometabolic responses. mTORC1 signaling was consistently enriched, together with the remodeling of cholesterol homeostasis, fatty acid metabolism, and oxidative phosphorylation. CLEC6A deletion achieved attenuation of hypoxia-, angiogenesis-, and TNF/NF-kB-associated programs. CD209 and SIGLEC9 deletion similarly reduced hypoxia- and angiogenesis-associated signatures while promoting lipid and oxidative metabolism. CLEC4E perturbation induced broad remodeling of lipid and oxidative metabolism and stress-response, despite comparatively limited editing efficiency. Comparative lectin perturbation thus identified CLEC6A as the strongest candidate for further mechanistic investigation, while CLEC4E showed broad transcriptional remodeling despite lower editing efficiency, supporting its prioritization for improved genetic interrogation. Responses to CD209 and SIGLEC9 targeting further support tumor glycan-myeloid signaling as a regulator of TAM state. Overall, lectin perturbation redirected TAM transcriptional states through distinct immunometabolic programs rather than a uniform pro-inflammatory polarization, highlighting lectin-dependent immunometabolic regulation as a promising axis for further investigation.

Minor introns are rare but evolutionarily conserved introns in the human genome. Defects in minor spliceosome components have been reported to cause several human diseases. Mutations in ZRSR2 are frequently observed in myelodysplastic syndrome (MDS) patients. However, the precise molecular mechanism by which these mutations cause a loss of ZRSR2 function in minor intron splicing remain elusive. In this study, we characterized the impact of MDS-causing missense mutations in ZRSR2. Most of the mutant ZRSR2 proteins we tested showed different subnuclear localization pattern from that of wild-type ZRSR2 protein. Co-immunoprecipitation (co-IP) analysis revealed that UHM missense mutations disrupted the interaction between ZRSR2 and SF3B complex. We also demonstrated that ZRSR2 preferentially immunoprecipitated minor spliceosome components over major spliceosome components and it directly interacts with SF3B1. Furthermore, co-IP analysis utilizing a variety of ZRSR2 mutants revealed that mutations in the UHM and Zn2 domains significantly attenuated the interaction with SF3B complex. Finally, UHM and Zn2 mutations markedly disrupted the supporting activity of ZRSR2 for minor intron splicing. Our results indicate that disruption of the physical interaction with SF3B complex is one of the hallmarks of MDS-causing mutations of ZRSR2, which results in aberrant splicing of minor introns.

Microplastics are pervasive environmental pollutants that pose a growing concern for human health. Oral ingestion is a common route of human microplastic exposure, yet the proteomic response of the gut epithelium to microplastics remains unclear. This study aimed to investigate the cellular effects of pristine and artificially digested microplastic exposure in primary rat duodenal epithelial cells using untargeted proteomics. Cells were exposed to pristine or digested 0.5 um polystyrene microplastics at 10 or 100 ug/mL for 72 hours and were then analyzed by tandem liquid chromatography and mass spectrometry (LC-MS). Proteins that were both significantly different in intensity compared to controls, with a threshold change of 1.3 or greater, were considered to be differentially expressed. This criterion identified 41 differentially expressed proteins after 100 ug/mL pristine MP exposure, with 19 downregulated and 21 upregulated. Following exposure to 100 ug/mL digested MP, only 3 differentially expressed proteins were upregulated and 7 were down regulated, demonstrating the impact of microplastic physicochemistry. FGSEA pathway analysis revealed that 270 Reactome pathways were significantly altered following microplastic exposure in either condition at both concentrations. These pathways contributed to functional domains including protein synthesis, DNA replication, cell cycle control and aerobic respiration. Overall, microplastic exposure was associated with upregulated mitochondrial respiration, and downregulation of nuclear-related processes including DNA synthesis, transcription and cell proliferation. This study provides targets for future investigation (mitochondria and nucleus) and emphasizes the need to consider biological and environmental conditions for in vitro models of microplastic exposure.

Central carbon metabolism coordinates energy production and carbon skeleton allocation across photosynthetic and heterotrophic organisms. Here, we established an optimized targeted metabolomics workflow for Chlamydomonas reinhardtii and Arabidopsis thaliana using a single-run HILIC-MS/MS assay with alternating positive and negative ionization. Our method provides robust multi-class coverage across 21 amino acids, 11 carboxylic acids, 4 sugars, 3 adenine nucleotides, 2 nucleotide sugars, 18 phosphorylated compounds in CCM, and Acetyl-CoA in a 20-minute run using both ESI modes. An optimal concentration of medronic acid with a BEH Amide column at high pH prevented metal adsorption, and low quantification limits (10 to 50 nM) for labile intermediates such as PEP, ATP and RUBP were achieved. Retention time variations remained below 1.3%, and over 90% of analytes showed high linearity (R2 > 0.990) across dynamic ranges spanning two to three orders of magnitude (typically 0.01-0.5 uM up to 15-20 uM). For sample preparation, glass-fiber filters (GF/C) outperformed nitrocellulose for harvesting C. reinhardtii. For A. thaliana, it was proved that no further grinding with micro pestle and extended cooling were necessary. A two-phase chloroform/methanol/water extraction was essential, as a single-phase extraction co-extracted green chlorophyll, which heavily suppressed phosphorylated signals. In Arabidopsis, glutamate, fumaric acid and citric acid were the dominant primary pools, indicating the importance of dilution and column washing for preventing carryover, and sensitive intermediates were reliably quantified at physiological levels. Together, this unified analytical and extraction strategy enables robust, artifact-free, high-throughput profiling of central metabolism in photosynthetic organisms.

Background: Alpha-mannosidosis (AM) is a debilitating lysosomal storage disorder (LSD) caused by insufficient activity of alpha-mannosidase, an enzyme responsible for cleavage of alpha-linked mannose residues from N-glycan-type oligosaccharides during their degradation. As a result, specific oligosaccharides accumulate in tissues and are also detectable in body fluids. AM is a progressive multi-organ disease for which hematopoietic stem cell transplantation (HSCT) and enzyme replacement therapy (ERT) are therapeutic options, however, treatment results depend considerably on early diagnosis. Therefore, inclusion of AM into newborn screening panels would significantly contribute to improving therapeutic outcome. Methods: A rapid and fully quantitative method for the specific AM oligosaccharide biomarker Man2GlcNAc in dried blood spots (DBS) using ultra-performance liquid chromatography coupled to tandem-mass spectrometry was developed. DBS from 420 controls, 27 AM patients (including five newborn screening samples), and 35 patients with other LSDs were analyzed. Results: A distinct separation in biomarker concentrations was observed between unaffected individuals and untreated AM patients (0.1 - 0.8 vs 3.2 - 11.3 mol Man2GlcNAc/L, p<0.0001). Furthermore, Man2GlcNAc concentrations significantly differed between untreated patients and those on ERT (n = 17, p<0.0001) or after HSCT (n = 15, p<0.0001), and between both treatment groups (p<0.0001). Moreover, we demonstrated that this method is appropriate for monitoring treatment efficacy by analysis of samples from individual patients before and after initiation of therapy. We retrospectively analyzed residual samples of dried blood spots (DBS) from routine newborn screening that had been stored from patients with later-confirmed AM, which resulted in clear separation from the concentrations observed in a newborn screening control cohort (7.7 - 11.3 vs 0.1 - 0.8 mol Man2GlcNAc/L, p=0.0001). Conclusion: We present a simple and rapid method for quantitative analysis of the specific AM oligosaccharide biomarker Man2GlcNAc, which is remarkably stable compared to enzymatic assays. Thus, the method is useful for selective screening in suspected cases as well as for monitoring the response to different forms of treatment. Furthermore, Man2GlcNAc has the potential to serve as a useful biomarker for newborn screening offering the prospect of earlier treatment initiation, improved therapeutic outcome and higher quality of life for AM patients.

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by the destruction of insulin-producing pancreatic {beta} cells. Both genetic susceptibility and epigenetic dysregulation contribute to T1D risk. Recent studies have reported {beta}-cell dysfunction before disease onset, suggesting that {beta}-cell-intrinsic mechanisms contribute to pathogenesis. However, the mechanistic link between disease-associated variants and {beta}-cell dysfunction remains poorly understood. We hypothesized that a subset of T1D-associated variants directly influences cell type-specific candidate cis-regulatory elements (cCREs) by disrupting transcription factor (TF) binding and altering gene expression. To define cell type-specific cCREs in human islets, we integrated publicly available epigenomic datasets, including bulk histone modification profiles and single-cell multiomic data from human pancreatic islets. We combined these data with T1D genome-wide association study (GWAS) variants to identify disease-associated SNPs located within enhancer regions. Using multiomic datasets from PANC-DB, we characterized cell type-specific chromatin accessibility in nondiabetic and T1D islets and identified regulatory regions that may control gene expression in {beta} cells and other islet cell types. We then applied ChromBPNet, a deep learning model that predicts base-pair-resolution chromatin accessibility from scATAC-seq data, to evaluate how specific variants may alter local regulatory activity. In parallel, we used TF footprinting to nominate TFs likely to bind these variant-containing regions. These analyses identified several T1D-associated SNPs predicted to alter chromatin accessibility at candidate TF binding sites, suggesting mechanisms by which noncoding variants may contribute to {beta}-cell dysfunction and T1D susceptibility. Our findings link T1D-associated variants to cell type-specific enhancer activity and regulatory pathways and provide candidates for future mechanistic studies.

Background/Objectives: Aldehyde dehydrogenase 2 (ALDH2), a mitochondrial enzyme, mitigates cellular stress by detoxifying reactive aldehydes produced during alcohol exposure and endogenous metabolic processes. ALDH2*2 polymorphism, which results in deficient catalytic activity, is prevalent in East Asian populations and is associated with an increased risk of cancer and other diseases. While the effects of ALDH2 deficiency on cellular stress responses are well documented, the specific metabolic dysregulations arising from this deficiency require further investigation. Methods; An ALDH2 knockout subline of SKBR-3 cells was established using CRISPR/Cas9 strategy. The metabolomic profiles of control (SKBR-3/C) and ALDH2 knockout (SKBR-3/ADKO) cells were evaluated via ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Results: ALDH2 knockout in SKBR-3 cells resulted in increased cellular stress, evidenced by elevated levels of 8-OHdG, reactive oxygen species (ROS), and malondialdehyde (MDA). Metabolomic analysis of the paired cell lines assigned a total of 5,033 signals, of which 281 were significantly different (fold change [&ge;] 2, p-value <0.05) between the two groups. Pathway analysis with MetaboAnalyst identified significant metabolic pathways associated with ALDH2 deficiency, particularly those involving arginine biosynthesis, and arginine and proline metabolism. ALDH2 deficiency reprogramed arginine metabolism toward polyamine pathways while suppressing the urea cycle. Network analysis further revealed alterations in amino acid and lipid metabolism in ALDH2-deficient cells. Conclusions; This study provides a novel insight into the role of ALDH2 in cancer metabolism and may have broader implication for cancer biology.

In our past study on human cilia from primary ciliary dyskinesia (PCD) patients using cryo-electron tomography and mass spectrometry, defects in the DNAH5 gene were proven to cause the loss of the entire outer dynein arm along with other proteins. This phenomenon was not observed in the unicellular green alga Chlamydomonas. In this study, we examined the loss of ciliary components caused by defects in various genes, based on proteomic and structural analyses of motile cilia from multiple PCD patients. The absence of single outer arm dynein genes causes a loss or significant decrease in other inner and outer arm dyneins. Interestingly, some patients with outer dynein defects show decreased intraflagellar transport (IFT) proteins, suggesting an influence of cargo components or assembly on transport. These phenomena were not observed in Chlamydomonas, suggesting a more complex mechanism of ciliogenesis in humans despite the high similarity in the final 3D architecture of the 9+2 axoneme. Defects in certain central pair proteins unexpectedly reduced components on the doublets as well. Our results demonstrate protein-protein interactions during stages of human motile ciliogenesis that are more complex than those in unicellular organisms.

The perception of flavor during food consumption is a complex process governed by the dynamic release of aroma compounds, which is influenced by the interaction between the food matrix and human physiology. While mechanistic models have been developed to simulate these phenomena, their practical application has often been limited by the lack of flexible software tools capable of integrating diverse food structures and real-time physiological data. This study addresses this gap by incorporating in vivo mechanistic models for both liquid foods and melting solid matrices in a modular Python-based framework: digimouth. The modeling approach treats the oral, pharyngeal, and nasal cavities as a series of interconnected reactors with mass transfer governed by ordinary differential equations (ODEs). These models explicitly integrate key physiological parameters, including salivary flow, bidirectional respiratory airflow, and discrete events such as mastication and swallowing. For solid foods, the framework incorporates additional mechanisms for matrix dissolution, temperature-dependent melting, and dynamic surface area change. The models were validated using experimental data from 30 subjects who consumed aroma solutions and flavored gelatin gummy discs while monitored by PTR-MS (Proton Transfer Reaction - Mass Spectrometry). The simulations successfully reproduced the main kinetic features and release profiles observed experimentally for both types of matrices. Despite some limitations related to the self-reporting of physiological events and the non-inclusion of initial orthonasal mass transfer in the models, the developed software package proved to be a robust and evolutive tool. It offers a foundation for exploring inter-individual variability and the impact of complex food structures on sensory perception.