JCI Insight. 2025 Jul 8:e191017. doi: 10.1172/jci.insight.191017. Online ahead of print.

ABSTRACT

The tumor microenvironment (TME) is highly heterogeneous and can dictate the success of therapeutic interventions. Identifying TMEs that are susceptible to specific therapeutic interventions paves the way for more personalized and effective treatments. In this study, using a spontaneous murine model of breast cancer, we characterize a TME that is responsive to inhibitors of the heme degradation pathway mediated by heme oxygenase (HO), resulting in CD8+ T- and NK-cell-dependent tumor control. A hallmark of this TME is a chronic type-I interferon (IFN) signal that is directly involved in orchestrating the anti-tumor immune response. Importantly, we identify that similar TMEs exist in human breast cancer which are associated with patient prognosis. Leveraging these observations, we demonstrate that combining a STING agonist, which induces type-I IFN responses, with an HO inhibitor produces a synergistic effect leading to superior tumor control. This study highlights HO activity as a potential resistance mechanism for type-I IFN responses in cancer offering a novel avenue for overcoming immune evasion in cancer therapy.

PMID:40627458 | DOI:10.1172/jci.insight.191017

Diabetes. 2025 Jul 8:dbi250003. doi: 10.2337/dbi25-0003. Online ahead of print.

ABSTRACT

High-quality weight loss, i.e., a high proportion of fat to skeletal muscle lost during the treatment of obesity, is advantageous for metabolic and physical health. Precise and accurate determinations of skeletal muscle mass in clinical settings are often challenging. In prevention of excessive loss of skeletal muscle during weight loss, advantages include minimization of metabolic adaptation that makes it difficult to sustain weight loss, improved glucose homeostasis and metabolic flexibility, and better mobility and strength. Effective approaches to preserving skeletal muscle include sufficient dietary protein and inclusion of exercise (especially resistance exercise) during weight loss; new pharmacological approaches are under development.

PMID:40627348 | DOI:10.2337/dbi25-0003

Angew Chem Int Ed Engl. 2025 Jul 8:e202508427. doi: 10.1002/anie.202508427. Online ahead of print.

ABSTRACT

Targeted protein degradation (TPD) is an emerging therapeutic approach for the selective elimination of disease-related proteins. While molecular glue degraders exhibit drug-like properties, their discovery has traditionally been serendipitous and often requires post-hoc rationalization. In this study, we demonstrate the rational, mechanism-guided design of molecular glue degraders using gluing moieties. Building on established principles, by appending a chemical gluing moiety to several small molecule inhibitors, we successfully transformed them into degraders, obviating the need for a specific E3 ubiquitin ligase recruiter. Specifically, we found that incorporating a hydrophobic aromatic ring or a double bond into a cyclin-dependent kinase 12 and 13 (CDK12/13) dual inhibitor enabled the recruitment of DNA damage-binding protein 1 (DDB1), thereby transforming a high-molecular-weight bivalent CDK12 degrader into a potent monovalent CDK12/13 molecular glue degrader. We also showcase that attaching a cysteine-reactive warhead to a bromodomain-containing protein 4 (BRD4) inhibitor converts it into a degrader by recruiting the DDB1 and CUL4 associated factor 16 (DCAF16) E3 ligase.

PMID:40626960 | DOI:10.1002/anie.202508427

Protein Eng Des Sel. 2025 Jul 8:gzaf009. doi: 10.1093/protein/gzaf009. Online ahead of print.

ABSTRACT

Interleukin-17A (IL-17A) is a cytokine involved in pro-inflammatory responses and tissue regeneration, with potential therapeutic and research applications. However, its short serum half-life limits in vivo use. Here, we report the systematic design of Fc-IL-17A fusion proteins for extended half-life. Through computational analysis of 25 design variants using AlphaFold, we found that IL-17A's native N-terminal unstructured region functions as a crucial natural linker that cannot be effectively replaced by artificial sequences. We therefore generated mouse and human Fc-IL-17A variants using direct N-terminal fusion without additional linkers. The resulting proteins retain IL-17A's ability to stimulate IL-6 production and erythroid cell growth. Pharmacokinetic analysis confirms that the Fc fusion increases the serum half-life in mice from 1.5 to 13 hours post-subcutaneous injection. This enables tractable experimental use of IL-17A in vivo for studying its role in inflammation and tissue repair. We further perform pharmacokinetics and pharmacodynamics modeling and propose a dosing regimen with reduced frequency of injection for delivering comparable IL-17A activity. This work provides a valuable pharmacological tool for injectable delivery, enabling investigation of IL-17A's biological functions in homeostasis and disease and exploration of its therapeutic potential in tissue regeneration.

PMID:40626948 | DOI:10.1093/protein/gzaf009

mSystems. 2025 Jul 8:e0174424. doi: 10.1128/msystems.01744-24. Online ahead of print.

ABSTRACT

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change.

IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

PMID:40626735 | DOI:10.1128/msystems.01744-24

Elife. 2025 Jul 8;14:e85300. doi: 10.7554/eLife.85300. Online ahead of print.

ABSTRACT

Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human neuronal cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro.

PMID:40626695 | DOI:10.7554/eLife.85300

Front Pharmacol. 2025 Jun 23;16:1601712. doi: 10.3389/fphar.2025.1601712. eCollection 2025.

ABSTRACT

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder described as progressive cognitive decline and neuronal dysfunction, affecting millions globally. While current pharmacological treatments provide symptomatic relief and modestly slow disease progression, they fail to address the underlying pathophysiology and are often accompanied by severe adverse effects. This underscores the urgent need for innovative, multi-target therapeutic strategies that can effectively step in AD's complex pathogenesis. Emerging evidence highlights the therapeutic potential of natural products, particularly herbal medicines, as versatile modulators of key pathogenic processes in AD. These compounds exert neuroprotective effects by mitigating oxidative stress, suppressing neuroinflammation, inhibiting tau hyperphosphorylation, and reducing amyloid-beta aggregation. Additionally, they strengthen synaptic plasticity and stabilize mitochondrial function, offering a holistic approach to disease control. This comprehensive review synthesizes findings from network pharmacology, in vitro and in vivo studies, and clinical trials to evaluate the role of natural products in AD treatment. Advances in bioinformatics and systems biology facilitate the mapping of intricate protein-protein interactions, the identification of potential biomarkers, and the clarification of molecular mechanisms underlying AD progression. Integrating phytochemicals with conventional AD medications may improve therapeutic efficacy through synergistic mechanisms; however, pharmacokinetic interactions and safety considerations must be rigorously assessed. Notably, clinical trials investigating compounds such as curcumin, resveratrol, and ginsenosides suggest promising adjunctive benefits when incorporated into established treatment regimens. Furthermore, the convergence of herbal therapeutics with modern pharmacology presents an avenue for customized and integrative AD management. This review also emphasizes advancements in experimental models, including brain organoids and transgenic animals, which serve as crucial platforms for mechanistic studies and therapeutic validation. Ongoing trials on plant-derived compounds continue to pave the way for translational applications, reinforcing the viability of natural product-based interventions. By advocating a multidisciplinary framework that merges traditional medicine, modern pharmacology, and precision medicine, this work contributes to reshaping the AD landscape of therapy. It provides a roadmap for future research, fostering novel treatment paradigms that prioritize efficacy, safety, and sustainability in combating this disastrous disorder.

PMID:40626308 | PMC:PMC12230064 | DOI:10.3389/fphar.2025.1601712

Bioinform Adv. 2025 May 9;5(1):vbaf106. doi: 10.1093/bioadv/vbaf106. eCollection 2025.

ABSTRACT

Summary: Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discuss recent computational progress and challenges toward solving this fundamental problem. We describe how cis-regulatory elements are mapped with various genomics assays and how studies of the 3D chromatin organization could help identifying long-range regulatory effects. We discuss how the cis-regulatory sequence rules can be learned and interpreted with sequence-to-function neural networks, with the goal of identifying genetic variants in human disease. We also describe current methods for mapping gene regulatory networks to describe biological processes. We point out current gaps in knowledge along with technical limitations and benchmarking challenges of computational methods. Finally, we discuss newly emerging technologies, such as spatial transcriptomics, and outline strategies for creating a more general model of the cis-regulatory code that is more broadly applicable across cell types and individuals.

PMID:40626041 | PMC:PMC12233095 | DOI:10.1093/bioadv/vbaf106

iScience. 2025 Apr 11;28(5):112405. doi: 10.1016/j.isci.2025.112405. eCollection 2025 May 16.

ABSTRACT

Cancer, driven by genomic instability, is profoundly influenced by DNA damage and repair mechanisms. Double-strand breaks (DSBs), repaired via homologous recombination (HR), and non-homologous end joining (NHEJ), are critical for genomic integrity. Defects in DNA damage repair (DDR) pathways, caused by impaired repair mechanisms or mutations in DDR-related proteins, increase cancer risk and therapy resistance. Recent studies highlight amino acid metabolism as a key regulator of DDR, influencing redox balance, energy metabolism, and protein synthesis, which directly impact DNA repair efficiency. This review explores the interplay between DDR, amino acid metabolism, and nanomedicine, emphasizing metabolic reprogramming to enhance genotoxic therapies. By integrating cancer metabolism and precision medicine, we propose targeting amino acid pathways to improve DNA repair and develop next-generation nanomedicine, bridging basic research, and clinical applications for advanced cancer therapy.

PMID:40625405 | PMC:PMC12230337 | DOI:10.1016/j.isci.2025.112405

Ecol Evol. 2025 Jul 7;15(7):e71766. doi: 10.1002/ece3.71766. eCollection 2025 Jul.

ABSTRACT

Facultative parthenogenesis enables females to switch from asexual (parthenogenetic) to sexual reproduction after mating, but the process of fertilisation is poorly understood in such animals. In particular, it is not known whether switching reproductive modes requires changes in the eggs themselves, delaying the transition from laying unfertilised to fertilised eggs. Likewise, very little is known about patterns of sperm precedence in facultatively parthenogenetic females that mate with multiple males. In this study, we manipulated reproductive mode in females of the facultatively parthenogenetic stick insect Megacrania batesii. We used offspring sex ratio, fertilisation rate and paternity analysis to investigate how females descended from distinct natural populations switch between reproductive modes and utilise sperm from different males. In the switch treatment group, females were first allowed to lay unfertilised eggs and then paired with a male. In the non-switch treatment group, females were instead paired successively with two different males. We collected eggs laid over two successive 10-day periods after male introduction (switch treatment) or substitution (non-switch treatment). We found little difference between the treatment groups in fertilisation rate or in the number of sons produced during the first and second 10-day egg collection. We also observed similar reproductive performance between switch and non-switch treatment groups, but females' population of origin influenced fertilisation rate and offspring sex ratio. In the non-switch group, we found near-equal fertilisation rates by the first and second male. Our results show that M. batesii females can quickly switch from producing parthenogenetic to fertilised eggs, suggesting that this transition does not require production of distinct types of eggs. Our results also show that M. batesii females can rapidly utilise sperm from a new mate and exhibit near-complete sperm mixing, which suggests that paternity may be evenly distributed in this species.

PMID:40625314 | PMC:PMC12234150 | DOI:10.1002/ece3.71766

J Oral Pathol Med. 2025 Jul 8. doi: 10.1111/jop.70008. Online ahead of print.

ABSTRACT

BACKGROUND: Adenoid cystic carcinoma (ACC) is a common salivary gland carcinoma with high recurrence and distant metastasis rates. Currently, there is no standard systemic treatment available. TROP2 is a transmembrane glycoprotein involved in the oncogenesis of several tumors that can be therapeutically targeted by a TROP2-antibody-drug conjugate (ADC). We aimed to characterize TROP2 expression in ACC and assess TROP2 as a potential therapeutic target.

METHODS: TROP2 immunohistochemistry was performed in a tissue microarray including 165 ACC of salivary gland. The tumors were grouped according to the histological pattern as non-solid, solid + non-solid, or solid. TROP2 protein expression in ACC cell lines was assessed and subjected to drug screening with TROP2-ADC.

RESULTS: TROP2 expression was high in 59%, moderate in 30%, weak in 8%, and negative in 3% of cases. TROP2 expression was significantly higher in non-solid compared with solid or solid + non-solid (p < 0.001). Notably, TROP2 expression was heterogenous among the dual cellular component, with TROP2 expression identified predominantly in the ductal and not in the myoepithelial cells. In vitro drug screening demonstrated that TROP2-ADC had selective anti-tumor effect in TROP2 expressing ACC cells.

CONCLUSIONS: TROP2 expression is prevalent in ACC, particularly in the ductal cell component of the non-solid tumors. The pre-clinical drug screening findings provide a biological rationale for exploring TROP2 as a therapeutic target in TROP2-expressing ACC.

TRIAL REGISTRATION: clinicaltrials.gov: NCT05884320; NCI-2023-04260.

PMID:40624990 | DOI:10.1111/jop.70008

Microbiome. 2025 Jul 7;13(1):161. doi: 10.1186/s40168-025-02156-0.

ABSTRACT

BACKGROUND: Understanding pairwise bacterial interactions in the human gut is crucial for deciphering the complex networks of bacterial interactions and their contributions to host health. However, there is a lack of large-scale experiments focusing on bacterial interactions within the human gut microbiome.

METHODS: We investigated the pairwise interactions of 113 bacterial strains isolated from healthy Chinese volunteers, selected for their high abundance and functional representation of the human gut microbiome. Using mGAM agar plates, a rich medium designed to maintain community structure, we established the "PairInteraX" dataset, which includes 3233 pair combinations of culturable human gut bacteria. This dataset was analyzed to identify interaction patterns and the key factors influencing these patterns.

RESULTS: Our analysis revealed that negative interactions were predominant among the bacteria in the PairInteraX dataset. When combined with in vivo gut metagenome datasets, we noted a diminishing mutualism and an increasing competition as microbial abundances increased; consequently, the maintenance of community diversity requires the participation of various types of interactions, especially the negative interactions. We also identified key factors influencing these interaction patterns including metabolic capacity and motility.

CONCLUSIONS: This study provides a comprehensive overview of pairwise bacterial interactions within the human gut microbiome, revealing a dominance of negative interactions. Besides, metabolic capacity and motility were identified as the key factors to influence the pairwise interaction patterns. This large-scale dataset and analysis offer valuable insights for further research on microbial community dynamics and their implications for host health. Video Abstract.

PMID:40624564 | DOI:10.1186/s40168-025-02156-0

Cell Biosci. 2025 Jul 7;15(1):98. doi: 10.1186/s13578-025-01434-6.

ABSTRACT

Revival stem cells (revSCs) defined by transient induction of clusterin (CLU) expression rapidly expand and differentiate into multiple IEC lineages during intestinal regeneration. Although revSC induction is well-studied, the mechanisms governing their differentiation remain unclear. In this study, we demonstrate that CREPT/RPRD1B, a protein highly expressed in tumors and essential for crypt-base columnar cell (CBC) maintenance, was required for revSC differentiation during intestinal regeneration. Using Villin-Cre-mediated CREPT knockout (Vil-CREPTKO) mice, we found that CREPT deletion leads to regeneration failure following irradiation-induced damage. Interestingly, revSCs were remarkably accumulated, but enterocytes were decreased in Vil-CREPTKO mice. Our single-cell transcriptome analyses demonstrated that CREPT deletion impaired the stem potential of revSCs and inhibited their differentiation into enterocytes and goblet cells. Lineage tracing experiments confirmed the reduced regenerative capacity of CREPT-deficient revSCs in vivo. Together, our findings identified CREPT as an important regulator of revSC differentiation during intestinal regeneration.

PMID:40624542 | DOI:10.1186/s13578-025-01434-6

Sci Rep. 2025 Jul 7;15(1):24284. doi: 10.1038/s41598-025-05844-x.

ABSTRACT

Recent excavations at the Phoenician coastal site of Tell el-Burak, a large-scale agricultural production centre in use during 725-350 BCE, have uncovered the first Iron Age wine press in Lebanon. This discovery enabled a systematic, interdisciplinary study of its plaster, offering insights into ancient construction technologies. The analysis extended to two other plastered installations found in separate rooms within the complex, allowing for a comprehensive comparison. An integrated program of archaeometric analysis, including optical microscopy in polarising light, X-ray powder diffraction, scanning electron microscopy, thermogravimetry, and organic residue analysis, was applied to samples from these three structures to investigate plaster composition and technological variability. Previous studies identified the use of crushed ceramic fragments in a lime-based plaster. Now, new analyses provide deeper insights into the nature of the binder, revealing how the addition of ceramic sherds may have enhanced the plaster's mechanical properties and hydraulicity, making it a significant early example of hydraulic mortar. These findings confirm the existence of a local, innovative tradition of lime-plaster manufacture in southern Phoenicia. This investigation not only sheds light on the specific technological practices of Tell el-Burak, but also contributes to the broader understanding of Phoenician and Punic technological advancements in the Iron Age Mediterranean.

PMID:40624179 | DOI:10.1038/s41598-025-05844-x

NPJ Syst Biol Appl. 2025 Jul 7;11(1):74. doi: 10.1038/s41540-025-00556-4.

ABSTRACT

The escalating global environmental crisis demands transformative biotechnological solutions that are both sustainable and scalable. This perspective advocates Data-Driven Synthetic Microbes (DDSM); engineered microorganisms designed through integrating omics, machine learning, and systems biology to tackle challenges like PFAS degradation, greenhouse gas mitigation, and sustainable biomanufacturing. DDSMs offer a rational framework for developing robust microbial systems, reshaping the future of synthetic biology toward environmental resilience and circular bioeconomy.

PMID:40624030 | DOI:10.1038/s41540-025-00556-4

BMJ Glob Health. 2025 Jul 7;10(7):e017256. doi: 10.1136/bmjgh-2024-017256.

ABSTRACT

BACKGROUND: Hypoxaemia predicts mortality at all levels of care, and appropriate management can reduce preventable deaths. However, pulse oximetry and oxygen therapy remain inaccessible in many primary care health facilities. We aimed to develop and validate a simple risk score comprising commonly evaluated clinical features to predict hypoxaemia in 2-59-month-old children with pneumonia.

METHODS: Data from seven studies conducted in five countries from the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) dataset were included. Readily available clinical features and demographic variables were used to develop a multivariable logistic regression model to predict hypoxemia (oxygen saturation <90%) at presentation to care. The adjusted log coefficients were transformed to derive the PREPARE hypoxemia risk score and its diagnostic value was assessed in a held-out, temporal validation dataset. The model and risk score were analysed by evaluating the area under the receiver operating characteristic curve (AUC), sensitivity and specificity.

RESULTS: We included 14 509 children in the analysis; 9.8% (n=2515) were hypoxemic at presentation. The multivariable regression model to predict hypoxemia included age, sex, respiratory distress (nasal flaring, grunting and/or head nodding), lower chest indrawing, respiratory rate, body temperature and weight-for-age z-score. The model showed fair discrimination (AUC 0.70, 95% CI 0.67 to 0.73) and calibration in the validation dataset. The simplified PREPARE hypoxaemia risk score includes five variables: age, respiratory distress, lower chest indrawing, respiratory rate and weight-for-age z-score.

CONCLUSION: The PREPARE hypoxemia risk score, comprising five easily available characteristics, has the potential to be used to identify hypoxemia in children with pneumonia with a fair degree of certainty for use in health facilities without pulse oximetry. Its implementation would require careful consideration to limit the burden of inappropriate referrals on patients and the health system. Further external validation in community settings in low- and middle-income countries is required.

PMID:40623791 | DOI:10.1136/bmjgh-2024-017256

Exp Gerontol. 2025 Jul 5:112815. doi: 10.1016/j.exger.2025.112815. Online ahead of print.

ABSTRACT

Premature ovarian failure (POF) is a common female endocrine disorder in women, and there is currently no effective pharmacological treatment available. Acupuncture, an important component of traditional Chinese medicine, has demonstrated clinical efficacy in improving ovarian function in patients with POF; however, its underlying mechanisms remain unclear. This study systematically investigated the therapeutic mechanisms of acupuncture in cyclophosphamide (CTX)-induced POF through combined analysis of proteomic and metabolomic data. In a rat model of chemotherapy-induced ovarian dysfunction, 28-day acupuncture intervention significantly delayed the pathological alterations in ovarian morphology and slowed the decline of endocrine function, as evidenced by normalized serum FSH, LH, and AMH levels. Metabolomic profiling identified 1683 differential metabolites across positive/negative ion modes, with taurine-hypotaurine metabolism (KEGG map00430) emerging as a key antioxidant axis, correlating with enhanced superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities. Proteomic analysis revealed acupuncture-mediated reversal of 115 ovarian proteins, particularly PPAR signaling components (FABP5, ADIPOQ and PLIN1), which orchestrated lipid metabolic reprogramming. Combined analysis of proteomic and metabolomic data demonstrated strong Spearman correlations between metabolic regulators (taurine, d-aspartate) and ovarian reserve markers, while PPAR-associated proteins exhibited network connectivity with oxidative stress mediators. These findings establish that acupuncture delays POF through synchronized modulation of metabolic flexibility and PPARγ-driven antioxidant defense, providing a novel systems biology framework for understanding traditional medicine interventions in reproductive aging.

PMID:40623466 | DOI:10.1016/j.exger.2025.112815

Comput Biol Chem. 2025 Jul 3;119:108568. doi: 10.1016/j.compbiolchem.2025.108568. Online ahead of print.

ABSTRACT

Cancer is a disease rooted in genomic alterations and has long stood as one of the most formidable foes for humanity since its inception. A patient's survival often hinges on the specific genomic mutations present and the corresponding immune system response. As each genomic alteration has its deleterious damage, identification of potential drivers of cancer progression may risk yielding false positives without a mutation-specific approach. To advance our understanding of tumor biology, there is a need for a systematic computational framework that combines both bulk RNA-seq and single-cell RNA-seq data analyses. In this work, we developed a pan-cancer R package called TCGAimmunosurv that integrates bulk RNA-Seq data from The Cancer Genome Atlas (TCGA) with single-cell RNA-Seq data to identify the genes to investigate mutation-specific immune dynamics. TCGAimmunosurv allows mutation-specific analysis by allowing users to select the genes of interest. It then identifies survival-associated genes from the mutation-specific samples obtained from TCGA. Then, it analyzes the user-given single-cell datasets and performs immune-subtype-specific pseudotime trajectory analysis. Finally, it seeks the gene(s) with strong expression patterns along pseudotime trajectories that are also associated with patient survivability and, thereby, bridges bulk and single-cell analyses for a comprehensive insight into the cancer driver genes.

PMID:40623343 | DOI:10.1016/j.compbiolchem.2025.108568

PLoS Comput Biol. 2025 Jul 7;21(7):e1012733. doi: 10.1371/journal.pcbi.1012733. Online ahead of print.

ABSTRACT

MOTIVATION: Metabolic kinetic models are widely used to model biological systems. Despite their widespread use, it remains challenging to parameterize these Ordinary Differential Equations (ODE) for large scale kinetic models. Recent work on neural ODEs has shown the potential for modeling time-series data using neural networks, and many methodological developments in this field can similarly be applied to kinetic models.

RESULTS: We have implemented a simulation and training framework for Systems Biology Markup Language (SBML) models using JAX/Diffrax, which we named jaxkineticmodel. JAX allows for automatic differentiation and just-in-time compilation capabilities to speed up the parameterization of kinetic models, while also allowing for hybridizing kinetic models with neural networks. We show the robust capabilities of training kinetic models using this framework on a large collection of SBML models with different degrees of prior information on parameter initialization. We furthermore showcase the training framework implementation on a complex model of glycolysis. Finally, we show an example of hybridizing kinetic model with a neural network if a reaction mechanism is unknown. These results show that our framework can be used to fit large metabolic kinetic models efficiently and provides a strong platform for modeling biological systems.

IMPLEMENTATION: Implementation of jaxkineticmodel is available as a Python package at https://github.com/AbeelLab/jaxkineticmodel.

PMID:40623114 | DOI:10.1371/journal.pcbi.1012733

PLoS Pathog. 2025 Jul 7;21(7):e1013325. doi: 10.1371/journal.ppat.1013325. Online ahead of print.

ABSTRACT

Protein glycosylation, a co- and post-translational modification that enhances the functional diversity of the proteome, contributes to various molecular and cellular functions by transferring different polysaccharides onto proteins. During the last decade, the role of glycosylation in plant pathogenic fungi has received significant attention, and glycoproteins are expected to play essential roles in various biological processes including pathogenicity. However, the comprehensive functional genetic analyses for protein glycosylation pathways and glycan structures of phytopathogenic fungi are still largely unknown. Here, we investigated the role of protein glycosylation in Fusarium graminearum by identifying 65 putative genes involved in protein glycosylation and characterizing their functions. Through cell wall component profiling and HPLC analysis, we characterized the overall N- and O-glycan structures in F. graminearum and found that deletion of ALG3 and ALG12 led to truncated core N-glycan structures. Quantitative proteomics analysis revealed that the truncated core N-glycans, generated by the loss of two key enzymes in the initial core N-glycosylation pathway, Alg3 and Alg12, affected a wide range of glycoproteins-including transcription factors, phosphatases, kinases, peroxidases, and other proteins involved in various biological processes-ultimately impacting the virulence of F. graminearum. This study elucidates the complex roles of glycosylation, highlighting the connections among genes involved in the protein glycosylation pathway, glycans, and glycoproteins in regulating the general biology and pathogenicity of F. graminearum. It also would be the fungal glycobiology study initiative.

PMID:40623063 | DOI:10.1371/journal.ppat.1013325