Nat Commun. 2025 Aug 5;16(1):7189. doi: 10.1038/s41467-025-62318-4.

ABSTRACT

Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenicity classification, but the functional impact of missense variants is multi-dimensional. Pathogenic missense variants in the same gene may act through different modes of action (i.e., gain/loss-of-function) by affecting different aspects of protein function. They may result in distinct clinical conditions that require different treatments. We develop a new method, PreMode, to perform gene-specific mode-of-action predictions. PreMode models effects of coding sequence variants using SE(3)-equivariant graph neural networks on protein sequences and structures. Using the largest-to-date set of missense variants with known modes of action, we show that PreMode reaches state-of-the-art performance in multiple types of mode-of-action predictions by efficient transfer-learning. Additionally, PreMode's prediction of G/LoF variants in a kinase is consistent with inactive-active conformation transition energy changes. Finally, we show that PreMode enables efficient study design of deep mutational scans and can be expanded to fitness optimization of non-human proteins with active learning.

PMID:40764308 | DOI:10.1038/s41467-025-62318-4

Nat Commun. 2025 Aug 5;16(1):7178. doi: 10.1038/s41467-025-62593-1.

ABSTRACT

Spatial transcriptomics links gene expression with tissue morphology, however, current tools often prioritize genomic analysis, lacking integrated image interpretation. To address this, we present Thor, a comprehensive platform for cell-level analysis of spatial transcriptomics and histological images. Thor employs an anti-shrinking Markov diffusion method to infer single-cell spatial transcriptome from spot-level data, effectively combining gene expression and cell morphology. The platform includes 10 modular tools for genomic and image-based analysis, and is paired with Mjolnir, a web-based interface for interactive exploration of gigapixel images. Thor is validated on simulated data and multiple spatial platforms (ISH, MERFISH, Xenium, Stereo-seq). Thor characterizes regenerative signatures in heart failure, screens breast cancer hallmarks, resolves fine layers in mouse olfactory bulb, and annotates fibrotic heart tissue. In high-resolution Visium HD data, it enhances spatial gene patterns aligned with histology. By bridging transcriptomic and histological analysis, Thor enables holistic tissue interpretation in spatial biology.

PMID:40764306 | DOI:10.1038/s41467-025-62593-1

Gut Microbes. 2025 Dec;17(1):2541028. doi: 10.1080/19490976.2025.2541028. Epub 2025 Aug 5.

ABSTRACT

Systematic identification of prebiotic-microbe interactions is essential for developing precision microbiome-targeted interventions to improve human health. In this study, we developed an in vivo systematic screening platform to evaluate microbiota-prebiotic crosstalk and applied it to identify a synbiotic combination effective against dextran sulfate sodium (DSS)-induced colitis in mice. Specifically, we first established a humanized gut microbiota mouse model by colonizing mice with 73 microbial strains, which showed highly abundant and prevalent in the human gut. Concurrently, we administered the mice with 28 different prebiotic or prebiotic candidates, including polyphenols, polysaccharides, vitamins, and minerals common in the market. Following the DSS-induced colitis, we evaluated the protective effects of each microbiota-prebiotic pairing. Fourteen prebiotic or prebiotic candidates, designated as the ESS group, significantly alleviated colitis, partly by enriching specific beneficial microbes such as Bacteroides thetaiotaomicron, Akkermansia muciniphila, and Erysipelatoclostridium ramosum prior to disease onset. Further experiments revealed two symbiotic combinations with the strongest anti-inflammatory effects: calcium-magnesium tablets (CMT) combined with either B. thetaiotaomicron or A. muciniphila. Mechanistically, CMT promoted the growth of B. thetaiotaomicron and alleviated inflammation by upregulating genes associated with probiotic activity. Finally, in an intervention trial involving healthy human volunteers, CMT selectively increased B. thetaiotaomicron abundance without altering the overall gut microbiota composition. Together, our study presents a systematic framework for elucidating microbe-prebiotic interactions, identifying synbiotic combinations with therapeutic potential, and advancing precision microbiome-based strategies for disease prevention and treatment.

PMID:40764272 | DOI:10.1080/19490976.2025.2541028

Genome Res. 2025 Aug 5:gr.280848.125. doi: 10.1101/gr.280848.125. Online ahead of print.

ABSTRACT

All animals live in tight association with complex microbial communities, yet studying the effects of individual bacteria remains challenging. Bacterial feeding nematodes are powerful systems to study host microbe interactions as worms can be grown on monoxenic cultures. Here, we present three different types of resources that may assist future research of cross-species interactions in the nematode Pristionchus pacificus, but also in other organisms. First, by sequencing the genomes of 84 Pristionchus-associated bacteria, we establish a genomic basis to study host microbe interactions and we demonstrate its utility to identify candidate pathways in the bacteria affecting chemotaxis behavior and survival in the nematodes. Second, we generated nematode transcriptomes of P. pacificus nematodes on 38 bacterial diets and characterized 60 coexpression modules with differential responses to environmental microbiota. Third, we link the microbial genome and host transcriptome data by predicting a global map of more than 2,800 metabolic interactions. These interactions represent statistical associations between variation in bacterial metabolic potential and differential transcriptomic responses of coexpression modules in the nematode. Analysis of the interactome identifies several intestinal modules as the primary response layer to diverse microbiota and reveals a number of broadly conserved metabolic interactions. In summary, our study establishes a multiomic framework for future mechanistic studies in P. pacificus and may also be conceptually transferred and reimplemented in other organisms in order to investigate the evolution of the host microbe interactome.

PMID:40764054 | DOI:10.1101/gr.280848.125

Genome Res. 2025 Aug 5. doi: 10.1101/gr.279906.124. Online ahead of print.

ABSTRACT

The spatial heterogeneity of gene expression has driven the development of diverse spatial transcriptomics technologies. Here, we present photocleavage and ligation sequencing (PCL-seq), a spatial indexing method utilizing a light-controlled DNA labeling strategy applied to tissue sections. PCL-seq employs photocleavable oligonucleotides and ligation adapters to construct transcriptional profiles of specific regions of interest (ROIs) designated via microscopically controlled photo-illumination. In frozen mouse embryos, PCL-seq generates spatially aligned gene expression matrices and produces high-quality data, detecting approximately 170,000 unique molecular identifiers (UMIs) and 8600 genes (illumination diameter = 100 µm). Moreover, PCL-seq is compatible with formalin-fixed paraffin-embedded (FFPE) tissues, successfully identifying thousands of differentially enriched transcripts in the digits and vertebrae of mouse embryo FFPE sections. Additionally, PCL-seq achieves subcellular resolution, as demonstrated by differential expression profiling between nuclear and cytoplasmic compartments. These characteristics establish PCL-seq as an accessible and versatile workflow for spatial transcriptomic analyses in both frozen and FFPE tissues with subcellular resolution.

PMID:40764053 | DOI:10.1101/gr.279906.124

Biomed Pharmacother. 2025 Aug 4;190:118390. doi: 10.1016/j.biopha.2025.118390. Online ahead of print.

ABSTRACT

Colon cancer is currently the leading cause of cancer death in men and the second in women under 50. Standard therapy includes surgical resection and - in the case of non-resectable CRC -radiotherapy, chemotherapy and immunotherapy. One of the therapeutic approaches is also a combinational regimen. Numerous experimental, epidemiological and clinical studies suggest that non-steroidal anti-inflammatory drugs (NSAIDs) may exert anticancer effects against colon cancer. In our work, we studied the effect of pure indomethacin (IND) and two lipid hybrids containing IND on HT29 and HT29/Dx cells. We analyzed the cytotoxicity and anti-inflammatory potential of the compounds but also their ability to induce apoptosis and produce reactive oxygen species. Experimental investigations were complemented by theoretical studies on the based on Density Functional Theory (DFT), molecular docking and classical molecular dynamics. These studies enabled a detailed description of the ligands and host-guest complexes. Based on the molecular docking study a general picture of the binding affinity to ABCB1 and COX-2 proteins was obtained. Moreover, we were able to detect amino acids involved in the protein-ligand complex formation. Classical molecular dynamics provided information on the thermodynamic properties and stability of the investigated complexes. We found that lysophosphatidylcholine containing IND represented a promising candidate for adjuvant therapy of colon cancer.

PMID:40763485 | DOI:10.1016/j.biopha.2025.118390

J Clin Invest. 2025 Aug 5:e192923. doi: 10.1172/JCI192923. Online ahead of print.

ABSTRACT

The leukemia fusion gene CBFB-MYH11 requires RUNX1 for leukemogenesis, but the underlying mechanism is unclear. By in vitro studies, we found that CBFβ-SMMHC, the chimeric protein encoded by CBFB-MYH11, could enhance the binding affinity between RUNX1 and its target DNA. Increased RUNX1-DNA binding was also observed in myeloid progenitor cells from mice expressing CBFβ-SMMHC. Moreover, only CBFβ-SMMHC variants able to enhance the DNA binding affinity by RUNX1 could induce leukemia in mouse models. Marked transcriptomic changes, affecting genes associated with inflammatory response and target genes of CBFA2T3, were observed in mice expressing leukemogenic CBFβ-SMMHC variants. Finally, we show that CBFβ-SMMHC could not induce leukemia in mice with a Runx1-R188Q mutation, which reduces RUNX1 DNA binding but not affecting its interaction with CBFβ-SMMHC or its sequestration to cytoplasm by CBFβ-SMMHC. Our data suggest that, in addition to binding RUNX1 to regulate gene expression, enhancing RUNX1 binding affinity to its target DNA is an important mechanism by which CBFβ-SMMHC contributes to leukemogenesis, highlighting RUNX1-DNA interaction as a potential therapeutic target in inv(16) AML.

PMID:40763310 | DOI:10.1172/JCI192923

PLoS Pathog. 2025 Aug 5;21(8):e1013395. doi: 10.1371/journal.ppat.1013395. eCollection 2025 Aug.

NO ABSTRACT

PMID:40763154 | DOI:10.1371/journal.ppat.1013395

J Math Biol. 2025 Aug 5;91(3):25. doi: 10.1007/s00285-025-02253-6.

ABSTRACT

The complex and dynamic crosstalk between tumour and immune cells results in tumours that can exhibit distinct qualitative behaviours-elimination, equilibrium, and escape-and intricate spatial patterns, yet share similar cell configurations in the early stages. We offer a topological approach to analyse time series of spatial data of cell locations (including tumour cells and macrophages) in order to predict malignant behaviour. We propose four topological vectorisations specialised to such cell data: persistence images of Vietoris-Rips and radial filtrations at static time points, and persistence images for zigzag filtrations and persistence vineyards varying in time. To demonstrate the approach, synthetic data are generated from an agent-based model with varying parameters. We compare the performance of topological summaries in predicting-with logistic regression at various time steps-whether tumour niches surrounding blood vessels are present at the end of the simulation, as a proxy for metastasis (i.e., tumour escape). We find that both static and time-dependent methods accurately identify perivascular niche formation, significantly earlier than simpler markers such as the number of tumour cells and the macrophage phenotype ratio. We find additionally that dimension 0 persistence applied to macrophage data, representing multi-scale clusters of the spatial arrangement of macrophages, performs best at this classification task at early time steps, prior to full tumour development, and performs even better when time-dependent data are included; in contrast, topological measures capturing the shape of the tumour, such as tortuosity and punctures in the cell arrangement, perform best at intermediate and later stages. We analyse the logistic regression coefficients for each method to identify detailed shape differences between the classes.

PMID:40762719 | DOI:10.1007/s00285-025-02253-6

Biochem Soc Trans. 2025 Aug 5:BST20253058. doi: 10.1042/BST20253058. Online ahead of print.

ABSTRACT

Critical for the regulation of eukaryotic gene transcription is the assembly and interplay of general transcription factors (GTFs) with RNA polymerases (RNAPs), leading to the formation of pre-initiation complexes (PICs) as a rate-limiting step in transcription activation. Compared with RNAPII PIC assembly involving many GTFs, activators, and co-activators, RNAPIII PIC assembly is less complex, involving mainly the four GTFs TFIIIA, TFIIIB, TFIIIC, and snRNA activating protein complex with only a few additional factors. The RNAPIII-specific GTF TFIIIC is present in type I and II promoters. One prominent area of investigation has been the dynamic interaction between TFIIIC and its promoter elements, the varying affinities of TFIIIC toward these elements, and the flexible linker within TFIIIC. Additionally, evidence suggests that TFIIIC may play a dual role, acting as an assembly factor that positions TFIIIB during PIC formation and as a barrier during RNAPIII-mediated transcription. By summarizing recent structural, biochemical, and genomic data, this review explores the mechanisms by which RNAPIII-specific GTFs, with a focus on TFIIIC, dynamically regulate RNAPIII transcription.

PMID:40762516 | DOI:10.1042/BST20253058

Front Immunol. 2025 Jul 21;16:1597676. doi: 10.3389/fimmu.2025.1597676. eCollection 2025.

ABSTRACT

BACKGROUND: Sepsis is a life-threatening condition with limited therapeutic options. Emerging evidence implicates gut microbial metabolites in modulating host immunity, but the specific interactions between these metabolites and host druggable targets remain poorly understood.

METHODS: We utilized a systems biology framework integrating genetic analyses, multi-omics profiling, and structure-based virtual screening to systematically map the interaction landscape between human gut microbial metabolites and druggable G-protein-coupled receptors (GPCRs), ion channels (ICs), and kinases (termed the "GIKome") in sepsis. Key findings were validated by molecular dynamics (MD) simulation, microscale thermophoresis (MST), and functional assays in a murine cecal ligation and puncture (CLP) model of sepsis.

RESULTS: We evaluated 190,950 metabolite-protein interactions, linking 114 sepsis-related GIK targets to 335 gut microbial metabolites, and prioritized indole-3-lactic acid (ILA), a metabolite enriched in Akkermansia muciniphila, as a promising therapeutic candidate. MD simulation and MST further revealed that ILA binds stably to PFKFB2, a pivotal kinase in regulating glycolytic flux and immune activation during sepsis. In vivo, ILA administration improved survival, attenuated cytokine storm, and mitigated multi-organ injury in CLP-induced septic mice.

CONCLUSIONS: This systems-level investigation unveils previously unrecognized therapeutic targets, offering a blueprint for microbiota-based precision interventions in critical care medicine.

PMID:40761792 | PMC:PMC12318984 | DOI:10.3389/fimmu.2025.1597676

Front Pharmacol. 2025 Jul 21;16:1629941. doi: 10.3389/fphar.2025.1629941. eCollection 2025.

ABSTRACT

INTRODUCTION: In the context of epidermal inflammation, the inflammatory response not only involves the release of inflammatory cytokines like interleukin 8 (IL-8), but also modulation of tight junction protein expression levels. Previous studies showed that the tight junction protein claudin 1 (CLDN1) is upregulated during tumor necrosis factor α (TNFα)-induced inflammation by capsaicin in keratinocytes in a transient receptor potential channel vanilloid 1 (TRPV1)-dependent manner. However, the caveat with TRPV1 ligands is the undesired pain response elicited by the activation of neuronal TRPV1 channels. In this study, we hypothesized that also less or non-pungent homovanillic acid esters as structural analogs of capsaicin target CLDN1 upregulation during inflammation.

METHODS: We aimed to identify beneficial structural characteristics by selecting homovanillic acid esters with different aliphatic tail structures and screening them for CLDN1 upregulation at early stages of TNFα-induced inflammation in basal keratinocytes.

RESULTS: CLDN1 expression was upregulated independently of TRPV1 by compounds with a tail of 5 or 6 C-atoms, regardless of the presence of ramifications and double bonds with a maximum fold change of 2.05 ± 0.22 against control. The induction of CLDN1 expression was accompanied by increased expression of the differentiation marker involucrin (IVL).

DISCUSSION: The results suggest that the homovanillic ester-induced CLDN1 upregulation is a result of increased differentiation of the basal keratinocytes towards the keratinocyte morphology present in the stratum granulosum (SG), where tight junctions are formed. In conclusion, homovanillic acid esters with a 5 or 6 C-atom long aliphatic chain induced CLDN1 expression, thereby stimulating keratinocyte differentiation, independent from TRPV1 activation.

PMID:40761393 | PMC:PMC12319341 | DOI:10.3389/fphar.2025.1629941

J Exp Clin Cancer Res. 2025 Aug 4;44(1):225. doi: 10.1186/s13046-025-03478-5.

ABSTRACT

BACKGROUND: The metastatic microenvironment is often rich in tumor-associated macrophages (TAMs). In uveal melanoma (UM), high levels of TAMs positively correlate with tumor progression and poorer prognosis. We hypothesize that the immunomodulation of TAMs can remodel the UM tumor microenvironment and make it more susceptible to therapeutic interventions.

METHODS: In our work, we designed a novel computational pipeline that combines single-cell transcriptomics data, network analysis, multicriteria decision techniques, and pharmacophore-based docking simulations to select molecular targets and matching repurposable drugs for TAM immunomodulation. The method generates a ranking of drug-target interactions, the most promising of which are channeled towards experimental validation.

RESULTS: To identify potential immunomodulatory targets, we created a network-based representation of the TAM interactome and extracted a regulatory core conditioned on UM expression data. Further, we selected 13 genes from this core (NLRP3, HMOX1, CASP1, GSTP1, NAMPT, HSP90AA1, B2M, ISG15, LTA4H, PTGS2, CXCL2, PLAUR, ZFP36, TANK) for pharmacophore-based virtual screening of FDA-approved compounds, followed by flexible molecular docking. Based on the ranked docking results, we chose the interaction between caspase-1 and clindamycin for experimental validation. Functional studies on macrophages confirmed that clindamycin inhibits caspase-1 activity and thereby inflammasome activation, leading to a decrease in IL-1β, IL-18, and gasdermin D cleavage products as well as a reduction in pyroptotic cell death. This clindamycin-mediated inhibition of caspase-1 was also observable in TAMs derived from the bone marrow of multiple myeloma patients.

CONCLUSIONS: Our computational workflow for drug repurposing identified clindamycin as an efficacious inhibitor of caspase-1 that suppresses inflammasome activity and pyroptosis in vitro in TAMs.

PMID:40759978 | DOI:10.1186/s13046-025-03478-5

Cell Commun Signal. 2025 Aug 4;23(1):362. doi: 10.1186/s12964-025-02306-9.

ABSTRACT

Candida albicans, responsible for approximately 70% of all Candida infections, is a leading cause of invasive candidiasis and poses a significant global health threat. With the emergence of drug-resistant strains, mortality rates have reached a staggering 63.6% in severe cases, complicating treatment options and demanding the discovery of novel therapeutic targets. To address this pressing need, using a unique multidisciplinary approach, we attempted to identify some the critical metabolic pathways that can be targeted to modulate the virulence of CAL. Condition-specific genome-scale metabolic models (GSMMs), along with a novel integrated host-CAL model developed in this study, highlighted the central role of arginine (Arg) metabolism and uncovered ALT1, an arginine biosynthesis enzyme, as a critical metabolic vulnerability in CAL virulence. Heightened expression of arginine biosynthesis genes indicated that increased arginine synthesis mainly occurred through proline intermediates during host interaction. Significantly impaired virulence and in vivo pathogenicity of ALT1-deleted CAL highlighted the potential of targeting arginine metabolism as a novel strategy to combat antifungal resistance and underscored the power of integrating systems biology with experimental approaches in identifying new therapeutic targets.

PMID:40759957 | DOI:10.1186/s12964-025-02306-9

Inflammopharmacology. 2025 Aug 4. doi: 10.1007/s10787-025-01872-1. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder marked by cognitive decline, cholinergic dysfunction, synaptic loss, and neuroinflammation. Existing therapies such as Donepezil and estrogen replacement offer only symptomatic relief, failing to address the complexity of the disease due to their reductionist, single-targeted approach. In this study, we employed an integrative systems biology framework to evaluate the neurotherapeutic potential of Dioscorea bulbifera (DB), a core component of the US-patented polyherbal formulation BHD (comprising Bacopa monnieri, Hippophae rhamnoides, and DB), which has shown promising neuroprotective properties in preclinical models. We identified active phytoconstituents of DB-including Emodin, Beta-sitosterol, Diosgenin, Stigmasterol, Diosbulbin B, Jarnol, and Myricetin-and systematically assessed their interaction with Alzheimer's-relevant hub-bottleneck (H-B) genes using molecular docking, gene expression integration, network pharmacology, and molecular dynamics simulations. Our findings delineate a dual mechanistic model of DB's action: (1) an Estrogen Signaling Module centered around ESR1 and its key signaling associates (MAPK1, MAPK8, AKT1, EGFR, PIK3CA, and MAP2K1), forming a tightly interconnected, feedback-regulated pathway modulating memory, synaptic plasticity, neuroprotection, and inflammation; and (2) a Cholinergic Module involving direct inhibition of ACHE, providing rapid symptomatic relief. Molecular docking and dynamic simulations confirmed the strong and stable interactions of DB bioactives with both ESR1 and ACHE, showing comparable or superior stability to reference drugs (Estradiol and Donepezil). Regulatory network analysis revealed that ESR1 is one of the most connected genes in hippocampal-specific PPI networks and is co-regulated by numerous miRNAs and transcription factors. Co-expression analysis identified additional AD-relevant genes (e.g., PIK3R1, MAPK14, PTEN, DHODH, CAV1) involved in synaptic signaling, oxidative stress, and neurogenesis, while TF-miRNA coregulatory nodes such as miR-199a-3p, miR-181a-5p, GATA2, CREB1, and HINFP added further mechanistic layers to DB's network modulation. KEGG and GO enrichment analyses mapped DB-targeted genes to critical AD pathways, including Estrogen signaling, MAPK, PI3K-AKT, TNF, FoxO, and the Alzheimer's disease pathway itself. This multi-targeted, systems-level modulation by DB underscores its potential not only as a neuroprotective nutraceutical-especially for postmenopausal women vulnerable to estrogen loss-but also as a promising adjuvant to standard AD therapies.

PMID:40759849 | DOI:10.1007/s10787-025-01872-1

Nat Plants. 2025 Aug 4. doi: 10.1038/s41477-025-02064-z. Online ahead of print.

ABSTRACT

Flowering plants rely on double fertilization for their sexual reproduction. A pair of immotile sperm cells (SCs) are conveyed through a pollen tube into the female gametophyte, where they fertilize the egg cell and central cell to give rise to the embryo and endosperm in seeds, respectively1-4. The SCs and the pollen vegetative nucleus (VN) move as a male germ unit (MGU) in pollen tubes5,6. The tryptophan-proline-proline (WPP) domain-interacting tail-anchored proteins (WITs) and WPP domain-interacting proteins (WIPs) are involved in VN migration, and the cytoskeleton is required for MGU transportation in pollen tubes7-11. Here we report that two kinesins, referred to as HUG1 and HUG2, localize at the VN envelope in a WIT- and WIP-dependent manner and surround the SCs in pollen. Mutation of HUG1 and HUG2 leads to disconnected VN and SCs, impaired MGU transportation and reduced plant fertility, supporting key roles of HUG proteins in MGU formation and transportation in pollen.

PMID:40759770 | DOI:10.1038/s41477-025-02064-z

Nat Plants. 2025 Aug 4. doi: 10.1038/s41477-025-02056-z. Online ahead of print.

ABSTRACT

Auxins are plant hormones that direct the growth and development of organisms on the basis of environmental cues. Indole-3-acetic acid (IAA) is the most abundant auxin in most plants. A variety of membrane transport proteins work together to distribute auxins. These include the AUX/LAX protein family that mediate auxin import from the apoplast to the cytosol. Here we use structural and biophysical approaches combined with molecular dynamics to study transport by Arabidopsis thaliana LAX3, which is essential for plant root formation. Transport assays document high-affinity transport of IAA, as well as competitive behaviour of the synthetic phenoxyacetic acid auxin herbicide 2,4-dichlorophenoxyacetic acid and the auxin transport inhibitors 1-naphthoxyacetic acid and 2-naphthoxyacetic acid. Four cryo-EM structures were solved with resolutions of 2.9-3.4 Å: an inward open apo structure, two inward semi-occluded structures in complex with IAA and 2,4-dichlorophenoxyacetic acid, and a fully occluded structure in complex with 2-naphthoxyacetic acid. Structurally, LAX3 consists of a bundle and a scaffold domain. The ligand-binding site is sandwiched between these domains with two histidines occupying positions analogous to the sodium-binding sites in distantly related sodium:neurotransmitter transporters. This architecture suggests that these histidines couple transport to the proton motive force. Molecular dynamics simulations are used to explore substrate binding and release, including their dependence on specific protonation states. This study advances our understanding of auxin recognition and transport by AUX/LAX, providing insights into a fundamental aspect of plant physiology and development.

PMID:40759769 | DOI:10.1038/s41477-025-02056-z

Sci Rep. 2025 Aug 4;15(1):28458. doi: 10.1038/s41598-025-13146-5.

ABSTRACT

This paper presents an intelligent computational framework for modeling nonlinear irreversible biochemical reactions (NIBR) using artificial neural networks (ANNs). The biochemical reactions are modeled using an extended Michaelis-Menten kinetic scheme involving enzyme-substrate and enzyme-product complexes, expressed through a system of nonlinear ordinary differential equations (ODEs). Datasets were generated using the Runge-Kutta 4th order (RK4) method and used to train a multilayer feedforward ANN employing the Backpropagation Levenberg-Marquardt (BLM) algorithm. The proposed BLM-ANN model is compared with two other training algorithms: Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG). Six kinetic scenarios, each with four cases of varying reaction rate constants [Formula: see text], were used to validate the models. Performance was evaluated using mean squared error (MSE), absolute error (AE), regression coefficients (R), error histograms, and auto-correlation analysis. Results show that the BLM-ANN model outperforms BR and SCG in terms of accuracy (with MSE as low as [Formula: see text]), convergence speed, and robustness across diverse kinetic profiles. Regression plots confirm high correlation with RK4 solutions, and error distributions validate the model's predictive capability. The comparison between the solution of BLM-ANN and RK4 method of the proposed model. These results demonstrate the high accuracy, reliability, and generalization capability of the proposed framework.

PMID:40759699 | DOI:10.1038/s41598-025-13146-5

Nat Commun. 2025 Aug 4;16(1):7146. doi: 10.1038/s41467-025-62478-3.

ABSTRACT

Parkinson's Disease (PD) is an incurable neurodegenerative disease that causes movement disorders. Neurons in PD aggregate α-synuclein and are depleted from the substantia nigra (SN), which is a movement control hub. The presence of α-synuclein-reactive T cells in PD patient blood suggests a role for adaptive immunity in the pathogenesis of PD. However, the characteristics of this response within the brain are not well understood. Here, we employed single-nucleus RNAseq, spatial transcriptomics, and T cell receptor (TCR) sequencing to analyze T cell and glial cell states in post-mortem PD brain tissue. CD8 + T cells were enriched in the PD SN and characterized by clonal expansion and TCR sequences with homology to those reactive to α-synuclein. Furthermore, PD T cells were spatially correlated with CD44+ astrocytes, which increased in the PD SN. Silencing CD44 in cultured astrocytes attenuated neuroinflammatory signatures, suggesting a potential therapeutic target. These findings provide insight into the neurodegenerative niche underlying T cell-mediated neuroinflammation in PD.

PMID:40759663 | DOI:10.1038/s41467-025-62478-3

Nat Commun. 2025 Aug 4;16(1):7160. doi: 10.1038/s41467-025-62529-9.

ABSTRACT

Engineering mammalian cells with synthetic circuits drives innovation in next-generation biotherapeutics and industrial biotechnology. However, applications often depend on cellular productivity, which is constrained by finite cellular resources. Here, we harness computational biology to identify drugs that boost productivity without additional genetic modifications. We perform RNA-sequencing on cells expressing an incoherent feed-forward loop (iFFL), a genetic circuit that enhances operational capacity. To find drugs that mimic this effect, we use DECCODE (Drug Enhanced Cell COnversion using Differential Expression), an unbiased method that matches our transcriptional data with thousands of drug-induced profiles. Among the compound candidates, we select Filgotinib, that enhances expression of both transiently and stably expressed genetic payloads across various experimental scenarios and cell lines, including AAV and lentivirus transduction. Our results reveal cell-specific responses, underscoring the context dependency of small-molecule treatments. Altogether, we present a versatile tool for biomedical and industrial applications requiring enhanced productivity from engineered cells.

PMID:40759644 | DOI:10.1038/s41467-025-62529-9