Cell Commun Signal. 2025 Apr 8;23(1):174. doi: 10.1186/s12964-025-02141-y.

ABSTRACT

STX12 (syntaxin12 or syntaxin13), a member of the SNARE protein family, plays a crucial role in intracellular vesicle transport and membrane fusion. Our previous research demonstrated that Stx12 knockout mice exhibit perinatal lethality with iron deficiency anemia. Despite its importance, the comprehensive physiological and pathological mechanism of STX12 remains largely unknown. Here, we revealed that STX12 deficiency causes the depolarization of mitochondrial membrane potential in zebrafish embryos and mouse embryonic fibroblasts. Additionally, the loss of STX12 decreased the levels of mitochondrial complex subunits, accompanied by mitochondrial DNA (mtDNA) release and activated cGAS-STING pathway and Type I interferon pathway in the lung tissue of Stx12-/- mice. Additionally, we observed a substantial increase in cytokines and neutrophil infiltration within the lung tissues of Stx12 knockout mice, indicating severe inflammation, which could be a contributing factor for Stx12-/- mortality. Various interventions have failed to rescue the lethal phenotype, suggesting that systemic effects may contribute to lethality. Further research is warranted to elucidate potential intervention strategies. Overall, our findings uncover the critical role of STX12 in maintaining mitochondrial function and mtDNA stability in pulmonary cells, and reveal that STX12 depletion results in pulmonary mtDNA release and activates mtDNA-dependent innate immunity.

PMID:40200300 | DOI:10.1186/s12964-025-02141-y

BMC Bioinformatics. 2025 Apr 8;26(1):100. doi: 10.1186/s12859-025-06104-5.

ABSTRACT

BACKGROUND: Bayesian Network (BN) modeling is a prominent methodology in computational systems biology. However, the incommensurability of datasets frequently encountered in life science domains gives rise to contextual dependence and numerical irregularities in the behavior of model selection criteria (such as MDL, Minimum Description Length) used in BN reconstruction. This renders model features, first and foremost dependency strengths, incomparable and difficult to interpret. In this study, we derive and evaluate a model selection principle that addresses these problems.

RESULTS: The objective of the study is attained by (i) approaching model evaluation as a misspecification problem, (ii) estimating the effect that sampling error has on the satisfiability of conditional independence criterion, as reflected by Mutual Information, and (iii) utilizing this error estimate to penalize uncertainty with the novel Minimum Uncertainty (MU) model selection principle. We validate our findings numerically and demonstrate the performance advantages of the MU criterion. Finally, we illustrate the advantages of the new model evaluation framework on real data examples.

CONCLUSIONS: The new BN model selection principle successfully overcomes performance irregularities observed with MDL, offers a superior average convergence rate in BN reconstruction, and improves the interpretability and universality of resulting BNs, thus enabling direct inter-BN comparisons and evaluations.

PMID:40200184 | DOI:10.1186/s12859-025-06104-5

Cell Death Differ. 2025 Apr 8. doi: 10.1038/s41418-025-01509-4. Online ahead of print.

ABSTRACT

Accumulating evidence indicates that metabolic enzymes can directly couple metabolic signals to transcriptional adaptation and cell differentiation. Glycogen synthase 1 (GYS1), the key metabolic enzyme for glycogenesis, is a nucleocytoplasmic shuttling protein compartmentalized in the cytosol and nucleus. However, the spatiotemporal regulation and biological function of nuclear GYS1 (nGYS1) microcompartments remain unclear. Here, we show that GYS1 dynamically reorganizes into nuclear condensates under conditions of glycogen depletion or transcription inhibition. nGYS1 complexes with the transcription factor NONO/p54nrb and undergoes liquid-liquid phase separation to form biomolecular condensates, leading to its nuclear retention and inhibition of glycogen biosynthesis. Compared to their wild-type littermates, Nono-deficient mice exhibit exercise intolerance, higher muscle glycogen content, and smaller myofibers. Additionally, Gys1 or Nono deficiency prevents C2C12 differentiation and cardiotoxin-induced muscle regeneration in mice. Mechanistically, nGYS1 and NONO co-condense with the myogenic transcription factor MyoD and preinitiation complex (PIC) proteins to form transcriptional condensates, driving myogenic gene expression during myoblast differentiation. These results reveal the spatiotemporal regulation and subcellular function of nuclear GYS1 condensates in glycogenesis and myogenesis, providing mechanistic insights into glycogenoses and muscular dystrophy.

PMID:40200092 | DOI:10.1038/s41418-025-01509-4

Nat Protoc. 2025 Apr 8. doi: 10.1038/s41596-025-01150-y. Online ahead of print.

ABSTRACT

Spheroids are reaggregated multicellular three-dimensional structures generated from cells or cell cultures of healthy as well as pathological tissue. Basic and translational spheroid application across academia and industry have led to the development of multiple setups and analysis methods, which mostly lack the modularity to maximally phenotype spheroids. Here we present the self-assembly of single-cell suspensions into spheroids by the liquid overlay method, followed by a modular framework for a multifaceted phenotyping of spheroids. Cell seeding, supernatant handling and compound administration are elaborated by both manual and automated procedures. The phenotyping modules contain a suite of orthogonal assays to analyze spheroids longitudinally and/or at an endpoint. Longitudinal analyses include morphometry with or without spheroid or cell state specific information and supernatant evaluation (nutrient consumption and metabolite/cytokine production). Spheroids can also be used as a starting point to monitor single and collective cell migration and invasion. At an endpoint, spheroids are lysed, fixed or dissociated into single cells. Endpoint analyses allow the investigation of molecular content, single-cell composition and state and architecture with spatial cell and subcellular specific information. Each module addresses time requirements and quality control indicators to support reproducibility. The presented complementary techniques can be readily adopted by researchers experienced in cell culture and basic molecular biology. We anticipate that this modular protocol will advance the application of three-dimensional biology by providing scalable and complementary methods.

PMID:40200041 | DOI:10.1038/s41596-025-01150-y

Nat Commun. 2025 Apr 8;16(1):3340. doi: 10.1038/s41467-025-57807-5.

ABSTRACT

Longevity research aims to extend the healthspan while minimizing the duration of disability and morbidity, known as the sickspan. Most longevity interventions in model organisms extend healthspan, but it is not known whether they compress sickspan relative to the lifespan. Here, we present a theory that predicts which interventions compress relative sickspan, based on the shape of the survival curve. Interventions such as caloric restriction that extend mean lifespan while preserving the shape of the survival curve, are predicted to extend the sickspan proportionally, without compressing it. Conversely, a subset of interventions that extend lifespan and steepen the shape of the survival curve are predicted to compress the relative sickspan. We explain this based on the saturating-removal mathematical model of aging, and present evidence from longitudinal health data in mice, Caenorhabditis elegans and Drosophila melanogaster. We apply this theory to identify potential interventions for compressing the sickspan in mice, and to combinations of longevity interventions. This approach offers potential strategies for compressing morbidity and extending healthspan.

PMID:40199852 | DOI:10.1038/s41467-025-57807-5

Bioinformatics. 2025 Apr 8:btaf154. doi: 10.1093/bioinformatics/btaf154. Online ahead of print.

ABSTRACT

MOTIVATION: Single-cell time series data often exhibit significant variability within an isogenic cell population. When modeling intracellular processes, it is therefore more appropriate to infer parameter distributions that reflect this variability, rather than fitting the population average to obtain a single point estimate. The Global Two-Stage (GTS) approach for nonlinear mixed-effects (NLME) models is a simple and modular method commonly used for this purpose. However, this method is computationally intensive due to its repeated use of non-convex optimization and numerical integration of the underlying system.

RESULTS: We propose the Gradient Matching GTS (GMGTS) method as an efficient alternative to GTS. Gradient matching offers an integration-free approach to parameter estimation that is particularly powerful for systems that are linear in the unknown parameters, such as biochemical networks modeled by mass action kinetics. By incorporating gradient matching into the GTS framework, we expand its capabilities through uncertainty propagation calculations and an iterative estimation scheme for partially observed systems. Comparisons between GMGTS and GTS across various inference setups show that our method significantly reduces computational demands, facilitating the application of complex NLME models in systems biology.

AVAILABILITY AND IMPLEMENTATION: A Matlab implementation of GMGTS is provided at https://github.com/yulanvanoppen/GMGTS (DOI: http://doi.org/10.5281/zenodo.14884457).

SUPPLEMENTARY INFORMATION: Supplemental Information is available online and contains Tables S1-S4, Figures S1-S21, methodology, mathematical derivations, and software implementation details.

PMID:40199819 | DOI:10.1093/bioinformatics/btaf154

Thromb Haemost. 2025 Apr 8. doi: 10.1055/a-2561-2362. Online ahead of print.

NO ABSTRACT

PMID:40199492 | DOI:10.1055/a-2561-2362

Cancer Discov. 2025 Apr 8:OF1-OF26. doi: 10.1158/2159-8290.CD-24-0943. Online ahead of print.

ABSTRACT

This study reveals a broad convergence in genetic adaptation to hypoxia between natural populations and tumors, suggesting that insights from natural populations could enhance our understanding of cancer biology and identify novel therapeutic targets.

PMID:40199338 | DOI:10.1158/2159-8290.CD-24-0943

Curr Biol. 2025 Apr 4:S0960-9822(25)00345-8. doi: 10.1016/j.cub.2025.03.033. Online ahead of print.

ABSTRACT

Seed formation is essential for plant propagation and food production. We present a novel mechanism for the regulation of seed size by a newly identified "gate" at the chalazal end of the ovule regulating nutrient transport into the developing seed. This gate is blocked by callose deposition in unfertilized mature ovules (closed state), but the callose is removed after central cell fertilization, allowing nutrient transport into the seed (open state). However, if fertilization fails, callose deposition persists, preventing transportation of nutrients from the funiculus. A mutant in an ovule-expressed β-1,3-glucanase gene (AtBG_ppap) showed incomplete callose degradation after fertilization and produced smaller seeds, apparently due to its partially closed state. By contrast, an AtBG_ppap overexpression line produced larger seeds due to continuous callose degradation, fully opening the gate for nutrient transport into the seed. The mechanism was also identified in rice, indicating that it potentially could be applied widely to angiosperms to increase seed size.

PMID:40199323 | DOI:10.1016/j.cub.2025.03.033

Cell. 2025 Mar 25:S0092-8674(25)00192-8. doi: 10.1016/j.cell.2025.02.007. Online ahead of print.

ABSTRACT

Microglia, essential in the central nervous system (CNS), were historically considered absent from the peripheral nervous system (PNS). Here, we show a PNS-resident macrophage population that shares transcriptomic and epigenetic profiles as well as an ontogenetic trajectory with CNS microglia. This population (termed PNS microglia-like cells) enwraps the neuronal soma inside the satellite glial cell envelope, preferentially associates with larger neurons during PNS development, and is required for neuronal functions by regulating soma enlargement and axon growth. A phylogenetic survey of 24 vertebrates revealed an early origin of PNS microglia-like cells, whose presence is correlated with neuronal soma size (and body size) rather than evolutionary distance. Consistent with their requirement for soma enlargement, PNS microglia-like cells are maintained in vertebrates with large peripheral neuronal soma but absent when neurons evolve to have smaller soma. Our study thus reveals a PNS counterpart of CNS microglia that regulates neuronal soma size during both evolution and ontogeny.

PMID:40199320 | DOI:10.1016/j.cell.2025.02.007

Curr Biol. 2025 Apr 7;35(7):R251-R253. doi: 10.1016/j.cub.2025.02.057.

ABSTRACT

Germ granules are specialized RNA-protein condensates that drive germ cell development. A new study reveals that germ granules promote Drosophila germ cell formation by altering membrane mechanics through PIP2 and actin.

PMID:40199247 | DOI:10.1016/j.cub.2025.02.057

Biochem Biophys Res Commun. 2025 Apr 1;762:151745. doi: 10.1016/j.bbrc.2025.151745. Online ahead of print.

ABSTRACT

Reactive oxygen species play a crucial role in cellular processes, but their effects on protein structure and function in vivo remain challenging to study. Here, we present an approach using synchrotron-based X-ray footprinting methods to probe protein structure, via quantitative LC-coupled mass spectrometry of methionine oxidation (MSOx) in live E. coli. A label-free proteomic analysis identified 2104 proteins from E. coli, with 465 proteins exhibiting MSOx modifications distributed across multiple cellular compartments. Changes in MSOx modification with increasing X-ray dose revealed a correlation between rates of modification and solvent-accessible surface area in vivo for selected proteins responsive to exposure, providing a direct probe of protein structure and its conformational plasticity in the cell. The approach developed here offers a unique in-cell quantitative readout of methionine oxidation and solvent accessibility through radiolytic hydroxyl radical labeling. With this method, the landscape of methionine oxidation in E. coli can be mapped, providing insights into protein behavior under oxidative stress. It represents a first step in developing radiolysis and E. coli as platforms for in vivo protein structure assessment. The potential applications in drug discovery, protein engineering, and systems biology of protein conformations are considerable.

PMID:40199130 | DOI:10.1016/j.bbrc.2025.151745

ACS Synth Biol. 2025 Apr 8. doi: 10.1021/acssynbio.4c00704. Online ahead of print.

ABSTRACT

Natural biological systems use feedback regulation to effectively respond and adapt to their changing environment. Even though in engineered systems we understand how accurate feedback can be depending on the electronic or mechanical parts that it is implemented with, we largely lack a similar theoretical framework to study feedback regulation in biological systems. Specifically, it is not fully understood or quantified how accurate or robust the implementation of biological feedback actually is. In this paper, we study the sensitivity of biological feedback to variations in biochemical parameters using five example circuits: positive autoregulation, negative autoregulation, double-positive feedback, positive-negative feedback, and double-negative feedback (the toggle switch). We find that some of these examples of biological feedback are subjected to fundamental performance trade-offs, and we propose multi-objective optimization as a framework to study their properties. The impact of this work is to improve robust circuit design for synthetic biology and to improve our understanding of feedback for systems biology.

PMID:40198741 | DOI:10.1021/acssynbio.4c00704

PLoS Pathog. 2025 Apr 8;21(4):e1013053. doi: 10.1371/journal.ppat.1013053. Online ahead of print.

ABSTRACT

The tethering complexes HOPS/CORVET are central for vesicular fusion through the eukaryotic endolysosomal system, but the functions of these complexes in the intracellular development of malaria parasites are still unknown. Here we show that the HOPS/CORVET core subunits are critical for the intracellular proliferation of the malaria parasite Plasmodium falciparum. We demonstrate that HOPS/CORVET are required for parasite endocytosis and host cell cytosol uptake, as early functional depletion of the complex led to developmental arrest and accumulation of endosomes that failed to fuse to the digestive vacuole membrane. Late depletion of the core HOPS/CORVET subunits led to a severe defect in merozoite invasion as a result of the mistargeting of proteins destined to the apical secretory organelles, the rhoptries and micronemes. Ultrastructure-expansion microscopy revealed a reduced rhoptry volume and the accumulation of numerous vesicles in HOPS/CORVET deficient schizonts, further supporting a role of HOPS/CORVET in post-Golgi protein cargo trafficking to the invasion related organelles. Hence, malaria parasites have repurposed HOPS/CORVET to perform dual functions across the intraerythrocytic cycle, consistent with a canonical endocytic pathway for delivery of host cell material to the digestive vacuole in trophozoite stages and a parasite specific role in trafficking of protein cargo to the apical organelles required for invasion in schizont stages.

PMID:40198740 | DOI:10.1371/journal.ppat.1013053

PLoS Comput Biol. 2025 Apr 8;21(4):e1012919. doi: 10.1371/journal.pcbi.1012919. eCollection 2025 Apr.

ABSTRACT

Stochastic Simulation Algorithm (SSA) is crucial for modeling biochemical reactions and gene regulatory networks. Traditional SSA is characterized by Markovian property and cannot naturally model systems with time delays. Several algorithms have already been designed to handle delayed reactions, yet few easy-to-use implementations exist. To address these challenges, we have developed DelaySSA, an R package that implements currently available algorithms for SSA with or without delays. Meanwhile, we also provided Matlab and Python versions to support wider applications. We demonstrated its accuracy and validity by simulating two classical models: the Bursty model and Refractory model. We then tested its capability to simulate the RNA Velocity model, where it successfully reproduced both the up- and down-regulation stages in the phase portrait. Finally, we extended its application to simulate a gene regulatory network of lung cancer adeno-to-squamous transition (AST) and qualitatively analyzed its bistability behavior by approximating the Waddington's landscape. Modeling the therapeutic intervention of a SOX2 degrader as a delayed degradation reaction, AST is effectively blocked and reprogrammed back to the adenocarcinoma state, providing a useful clue for targeting drug-resistant AST in the future. Taken together, DelaySSA is a powerful and easy-to-use software suite, facilitating accurate modeling of various kinds of biological systems and broadening the scope of stochastic simulations in systems biology.

PMID:40198732 | DOI:10.1371/journal.pcbi.1012919

JCI Insight. 2025 Apr 8;10(7):e185758. doi: 10.1172/jci.insight.185758.

ABSTRACT

Using transcriptomic profiling at single-cell resolution, we investigated cell-intrinsic and cell-extrinsic signatures associated with pathogenesis and inflammation-driven fibrosis in both adult and pediatric patients with localized scleroderma (LS). We performed single-cell RNA-Seq on adult and pediatric patients with LS and healthy controls. We then analyzed the single-cell RNA-Seq data using an interpretable factor analysis machine learning framework, significant latent factor interaction discovery and exploration (SLIDE), which moves beyond predictive biomarkers to infer latent factors underlying LS pathophysiology. SLIDE is a recently developed latent factor regression-based framework that comes with rigorous statistical guarantees regarding identifiability of the latent factors, corresponding inference, and FDR control. We found distinct differences in the characteristics and complexity in the molecular signatures between adult and pediatric LS. SLIDE identified cell type-specific determinants of LS associated with age and severity and revealed insights into signaling mechanisms shared between LS and systemic sclerosis (SSc), as well as differences in onset of the disease in the pediatric compared with adult population. Our analyses recapitulate known drivers of LS pathology and identify cellular signaling modules that stratify LS subtypes and define a shared signaling axis with SSc.

PMID:40197368 | DOI:10.1172/jci.insight.185758

bioRxiv [Preprint]. 2025 Mar 28:2025.03.24.644676. doi: 10.1101/2025.03.24.644676.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) is a complex neurodegenerative disorder with substantial molecular variability across different brain regions and individuals, hindering therapeutic development. This study introduces PRISM-ML, an interpretable machine learning (ML) framework integrating multiomics data to uncover patient-specific biomarkers, subtissue-level pathology, and drug repurposing opportunities.

METHODS: We harmonized transcriptomic and genomic data of three independent brain studies containing 2105 post-mortem brain samples (1363 AD, 742 controls) across nine tissues. A Random Forest classifier with SHapley Additive exPlanations (SHAP) identified patient-level biomarkers. Clustering further delineated each tissue into subtissues, and network analysis revealed critical "bottleneck" (hub) genes. Finally, a knowledge graph-based screening identified multi-target drug candidates, and a real-world pharmacoepidemiologic study evaluated their clinical relevance.

RESULTS: We uncovered 36 molecularly distinct subtissues, each defined by a set of associated unique biomarkers and genetic drivers. Through network analysis of gene-gene interactions networks, we highlighted 262 bottleneck genes enriched in synaptic, cytoskeletal, and membrane-associated processes. Knowledge graph queries identified six FDA-approved drugs predicted to target multiple bottleneck genes and AD-relevant pathways simultaneously. One candidate, promethazine, demonstrated an association with reduced AD incidence in a large healthcare dataset of over 364000 individuals (hazard ratios ≤ 0.43; p < 0.001). These findings underscore the potential for multi-target approaches, reveal connections between AD and cardiovascular pathways, and offer novel insights into the heterogeneous biology of AD.

CONCLUSIONS: PRISM-ML bridges interpretable ML with multi-omics and systems biology to decode AD heterogeneity, revealing region-specific mechanisms and repurposable therapeutics. The validation of promethazine in real-world data underscores the clinical relevance of multi-target strategies, paving the way for more personalized treatments in AD and other complex disorders.

PMID:40196631 | PMC:PMC11974764 | DOI:10.1101/2025.03.24.644676

Front Pharmacol. 2025 Mar 24;16:1530109. doi: 10.3389/fphar.2025.1530109. eCollection 2025.

ABSTRACT

Impaired intestinal epithelial barrier function is closely associated with the pathogenesis of ulcerative colitis (UC). Atractylenolide-I (AT-I), a major sesquiterpene derived from the herb Atractylodes macrocephala Koidz., has been reported to alleviate DSS-induced colitis in mice. This study aims to investigated the protective effects of AT-1 on intestinal epithelial barrier function and elucidate it's underlying mechanisms. In vivo, an acute colitis model was established in mice, and transcriptomic analysis to identify differentially expressed genes. In vitro, overexpression plasmids and recombinant protein were used to evaluate their effects on intestinal barrier function, and further analysis of its potential mechanisms.The study found that AT-1 ameliorate DSS-induced acute ulcerative colitis, exhibiting protective effects on the intestinal barrier. Transcriptomic analysis revealed that AT-1 significantly modulated the expression of S100A8 and S100A9. Further investigations indicated that S100A9, rather than S100A8, mediated the expression of tight junction proteins, meanwhile, AT-1 reduces neutrophil activation and subsequent release of S100A9. Mechanistically, recombinant human S100A9 protein was found to induce a decrease in intracellular Ca2+ concentration, while AT-1 regulated the expression of tight junction proteins via modulation of the AMPK/mTOR signaling pathway. AT-1 enhances the recovery of DSS-induced intestinal barrier dysfunction by regulating the recombinant human S100A9 protein-mediated AMPK/mTOR signaling pathway. This study provides new insights into the pathogenesis of ulcerative colitis and suggests potential therapeutic strategies for its treatment.

PMID:40196359 | PMC:PMC11973269 | DOI:10.3389/fphar.2025.1530109

J Microbiol. 2025 Mar;63(3):e2501021. doi: 10.71150/jm.2501021. Epub 2025 Mar 28.

ABSTRACT

Existing microbial engineering strategies-encompassing metabolic engineering, systems biology, and systems metabolic engineering-have significantly enhanced the potential of microbial cell factories as sustainable alternatives to the petrochemical industry by optimizing metabolic pathways. Recently, systems metabolic engineering, which integrates tools from synthetic biology, enzyme engineering, omics technology, and evolutionary engineering, has been successfully developed. By leveraging modern engineering strategies within the Design-Build-Test-Learn (DBTL) cycle framework, these advancements have revolutionized the biosynthesis of valuable compounds. This review highlights recent progress in the metabolic engineering of Corynebacterium glutamicum, a versatile microbial platform, achieved through various approaches from traditional metabolic engineering to advanced systems metabolic engineering, all within the DBTL cycle. A particular focus is placed C5 platform chemicals derived from L-lysine, one of the key amino acid production pathways of C. glutamicum. The development of DBTL cycle-based metabolic engineering strategies for this process is discussed.

PMID:40195836 | DOI:10.71150/jm.2501021

Nat Microbiol. 2025 Apr 7. doi: 10.1038/s41564-025-01978-w. Online ahead of print.

ABSTRACT

Microbial genome-wide association studies (GWAS) have uncovered numerous host genetic variants associated with gut microbiota. However, links between host genetics, the gut microbiome and specific cellular contexts remain unclear. Here we use a computational framework, scBPS (single-cell Bacteria Polygenic Score), to integrate existing microbial GWAS and single-cell RNA-sequencing profiles of 24 human organs, including the liver, pancreas, lung and intestine, to identify host tissues and cell types relevant to gut microbes. Analysing 207 microbial taxa and 254 host cell types, scBPS-inferred cellular enrichments confirmed known biology such as dominant communications between gut microbes and the digestive tissue module and liver epithelial cell compartment. scBPS also identified a robust association between Collinsella and the central-veinal hepatocyte subpopulation. We experimentally validated the causal effects of Collinsella on cholesterol metabolism in mice through single-nuclei RNA sequencing on liver tissue to identify relevant cell subpopulations. Mechanistically, oral gavage of Collinsella modulated cholesterol pathway gene expression in central-veinal hepatocytes. We further validated our approach using independent microbial GWAS data, alongside single-cell and bulk transcriptomic analyses, demonstrating its robustness and reproducibility. Together, scBPS enables a systematic mapping of the host-microbe crosstalk by linking cell populations to their interacting gut microbes.

PMID:40195537 | DOI:10.1038/s41564-025-01978-w