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PubMed2026

RePo index: a multidimensional framework to quantify genetic resilience in data-limited amphibian faunas.

This study explores the resilience of Chilean amphibians to environmental disturbances through an integrative approach that combines ecological, demographic, bibliometric, and molecular information. A total of 58 species distributed across 14 genera and 9 families were evaluated via the resilience potential (RePo) index, which incorporates eleven criteria grouped into five dimensions: distribution, population trends, emerging diseases, evolutionary history, and genetic records. The results revealed high ecological vulnerability: 83% of the species were classified as non resilient (45% with no resilience and 38% with low resilience), and none reached the high-resilience category. At the family level, Telmatobiidae presented the lowest resilience values, whereas Leptodactylidae presented the highest. At the genus level, Insuetophrynus was identified as the most vulnerable taxon, with no molecular records and an extremely restricted distribution. In contrast, species such as Rhinella spinulosa and Pleurodema thaul presented moderate resilience, suggesting greater adaptive potential and relevance for functional studies. From a bibliometric perspective, a bias toward classical research topics (distribution, physiology, and taxonomy) was detected, with limited representation of integrative approaches such as genetic conservation or climate change. The conceptual modularity in the literature was low (Q = 0.1328), indicating weak thematic differentiation and little integration of omics tools. Most species lack transcriptomic and genomic data, severely limiting the assessment of their adaptive mechanisms. In this context, the RePo index has emerged as an integrative tool useful for operationalizing concepts such as evolutionarily significant units (ESUs) and management units (MUs), which are essential for evidence-based conservation. Finally, this study highlights the need to incorporate high-throughput sequencing (HTS) technologies and to participate in international initiatives, such as the Amphibian Genomics Consortium, as a strategic path forward for advancing adaptive conservation of Chilean amphibians.

Animals↗

PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

PubMed2025

Consumption of traditional Sardinian fermented milk promotes changes in the rat gut microbiota composition and functions.

BACKGROUND: Fermented milk products are part of the staple diet for many Mediterranean populations. Most of these traditional foods are enriched with lactobacilli and other lactic acid bacteria, as well as with metabolites resulting from lactose fermentation. Currently, there is very little scientific knowledge on how dietary supplementation with fermented milk affects the composition of the gut microbiota and its metabolic activities. RESULTS: We integrated 16 S rRNA gene-based taxonomic profiling with metaproteomics-based functional analysis to investigate gut microbiota changes in rats exposed to an 8-week dietary supplementation with casu axedu, a traditional fermented milk produced within rural communities in Sardinia (Italy). Several microbial taxa showed a significantly increased abundance at the end of the dietary treatment, including Phascolarctobacterium, Prevotella, Blautia glucerasea, and Lactococcus lactis, while Bacteroides dorei and Helicobacter rodentium were decreased compared to the control rats. Metaproteomic analysis highlighted a striking reshaping of the Prevotella proteome in agreement with its blooming in casu axedu-fed animals, suggesting an increase of the glycolytic activity through the Embden-Meyerhof-Parnas pathway over the Entner-Doudoroff pathway. Moreover, an increased production of enzymes involved in succinate biosynthesis was observed, which in turn significantly boosted the abundance of Phascolarctobacterium and its production of propionate. Fermented milk consumption also promoted microbial synthesis of branched chain essential amino acids L-valine and L-leucine. Finally, metaproteomic data indicated a reduction of bacterial virulence factors and host inflammatory markers, suggesting that the consumption of casu axedu can have beneficial effects on the gut mucosa health. CONCLUSIONS: Our integrated multi-omics approach reveals that dietary supplementation with the traditional Sardinian fermented milk, casu axedu, induces significant shifts in the rat gut microbiota composition and function, characterized by the enrichment of beneficial taxa and metabolic pathways associated with improved gut health and reduced inflammation.

Animals↗

PubMed2026

Differentiating hemorrhagic shock and organophosphate poisoning through integrated skin microbiome-metabolome signatures.

Accurate determination of cause of death and estimation of postmortem interval (PMI) are critical yet challenging tasks in forensic science, particularly in cases with rapid demise and absence of obvious morphological abnormalities. We employed an integrative multi-omics approach to characterize postmortem microbial succession and metabolic alterations on facial skin in mouse models of hemorrhagic shock (HS) and organophosphorus poisoning (OP) across three decomposition stages: bloating (2 days), active decay (8 days), and advanced decay (16 days). Metagenomic profiling revealed significantly reduced α-diversity in HS compared with OP throughout all stages (p < 0.001), accompanied by stage-dependent compositional shifts, including early enrichment of Firmicutes in HS and Proteobacteria in OP. A total of 237 differential taxa were identified, with Providencia and Morganella predominating in OP, whereas Staphylococcus and Corynebacterium dominated bloating stage of HS. Untargeted metabolomics uncovered distinct cause-of-death-linked metabolites, notably elevated 2'-deoxycytidine-5'-diphosphate in early OP and persistent cholic acid/cholate accumulation in HS at later PMI. Functional analysis highlighted histidine and phosphate/phosphonate metabolism as key discriminatory pathways, exhibiting stage-specific oscillations and strong correlations with characteristic taxa. These findings demonstrate that skin-based metagenomic-metabolomic integration provides robust, mechanistically informed biomarkers for both PMI estimation and cause-of-death differentiation, offering a minimally invasive and temporally dynamic tool for forensic investigations.

Animals↗

PubMed2026

Integrated methylome and transcriptome analysis provides insight into DNA methylation-mediated networks in sexual dimorphism of Vernicia montana.

BACKGROUND: Sexual dimorphism is fundamental to reproduction in dioecious plants and is regulated by both genetic and epigenetic mechanisms. DNA methylation is a central epigenetic mark known to influence phenotypic variation in plants. However, its specific role in shaping sexual dimorphism in dioecious trees remains poorly understood. To address this question, we performed integrated genome-wide DNA methylome and transcriptome analyses of four tissue types in the dioecious tung tree (Vernicia montana), including male and female flower buds and their corresponding leaves. RESULTS: Our analysis revealed distinct DNA methylation patterns between male and female tissues. Notably, the coordination between DNA methylation reprogramming and transcriptional regulation appeared to be more strongly associated with reproductive development than with vegetative growth in V. montana. We identified a set of sex-biased genes that may reflect different reproductive strategies between the sexes. Further analysis identified several key transcription factors (TFs) potentially associated with promoter differentially methylated regions (DMRs), including flowering-time regulators (e.g., FRS5, REM16, and VRN1) and TFs involved in hormone signaling pathways such as jasmonic acid, auxin, and salicylic acid signaling. Cis-regulatory element analysis showed that some promoter DMRs overlapped with hormone response elements related to abscisic acid, auxin, and gibberellin. Co-expression network analysis further revealed potential regulatory correlations among promoter DMR-mediated TFs, hormone-responsive pathways, and key floral development regulators. CONCLUSIONS: Collectively, our results suggest that interactions among DNA methylation, transcriptional regulation, and hormone-responsive pathways may contribute to the establishment of sexual dimorphism in V. montana. This study provides the first integrated view of these regulatory layers in V. montana and supports a species-specific regulatory framework for understanding the epigenetic basis of sexual dimorphism in this economically important dioecious tree. The proposed framework is based on multi-omics analyses and warrants further validation through targeted functional studies.

DNA Methylation↗

PubMed2026

Decoding protein signatures and protein interactions in oral potentially malignant disorders: a systematic review and network analysis.

BACKGROUND: Proteomic profiling offers thorough insights into protein structure and function, as well as it acts as an essential approach for analyzing molecular changes at the tissue level. However, because of the proteome's diversity and dynamic nature, biomarker discovery remains challenging. By combining proteomics with bioinformatics, the level of understanding in relation to molecular interactions and disease processes can be improved. Through an integrative approach, few limitations can be addressed, thereby promoting proteomic profiling for the discovery of new therapeutic targets and novel biomarkers for a variety of disorders. AIM: To identify differentially expressed protein markers and their key molecular pathways associated with Oral Potentially Malignant Disorders. METHODS: Systematic Review was conducted following the PRISMA guidelines and the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration ID number CRD42024557545. A comprehensive literature review was performed using electronic databases, yielding 12,797, studies from which 15 eligible articles were selected. The Newcastle-Ottawa Scale was used to assess the risk of bias. Vote counting was performed to identify proteins reported in more than one study. A bipartite network was constructed using Cytoscape to identify shared and disease-specific protein markers. Lesion-wise protein-protein interaction networks were generated using STRING and analysed in Cytoscape to identify highly interconnected hub proteins, and pathway enrichment analysis for these hubs was performed using Reactome. RESULTS: A total of fifteen studies (Leukoplakia (LK) - n = 1, Proliferative Verrucous Leukoplakia (PVL) - n = 2, Oral Submucous Fibrosis (OSMF) - n = 7, and Oral Lichen Planus (OLP) - n = 5) were included. The Newcastle-Ottawa Scale was used to evaluate methodological quality and the quality of studies included in this systematic review was high for 4 articles and moderate in the remaining 11. The most commonly employed technique was mass spectrometry. A total of 318 candidate proteins (LK - 14, PVL - 82, OSMF - 172, and OLP - 50) were identified across the oral potentially malignant disorders. Key markers identified through vote counting included ERO1A, NUCB1, RHOA, and IL36A for PVL; LUM, KRT1, KRT9, ALB, and VIM for OSMF; and ALB, LYZ, HP, HBB, and AMY1A for OLP. The bipartite network showed that OSMF and OLP shared the highest number of proteins, indicating the strongest overlap among lesions. Network analysis further highlighted distinct hub proteins for each lesion: for LK- AMY1A, AMY1B and APOA1; for PVL- CFL1, RHOA and CDC42; for OSMF- HSP90AA1, ENO1 and SERPINA1; and for OLP- HP, B2M, and ORM1. Lesion-specific pathway enrichment revealed that LK was associated with epithelial differentiation, PVL with oncogenic signaling, OSMF with stress-driven fibrosis, and OLP with immune-mediated inflammation. CONCLUSIONS: Proteomic expression offers insights into disease pathogenesis by identifying important molecular changes across OPMDs. However, the majority of biomarkers are still in the exploratory stage due to the considerable variation in lesion types, sample sources, proteomic techniques, and reporting systems. In order to create reliable and clinically applicable biomarkers, future studies should concentrate on combining multi-omics techniques with large-scale, standardized cohorts.

Humans↗

PubMed2026

Social isolation and 59 common health conditions: insights from observational and genetics analyses.

BACKGROUND: The impacts of social isolation on diverse health conditions and how it contributes to health risks remain unclear. We aimed to investigate the associations of social isolation with 59 health conditions among older adults. METHODS: Participants from the UK Biobank without baseline diagnosis of the included diseases were selected. Social isolation was assessed with three questions. The 59 health conditions included all-cause mortality, 5 cause-specific mortalities, and 53 diseases. We used an instrumental variable from multivariable common factor GWAS in Mendelian randomization (MR) to explore causal links of social isolation with diseases. Omics analyses were conducted to assess the roles of Olink plasma proteins and metabolomics, and PERM was calculated to evaluate the influence of other factors. RESULTS: A total of 489,741 individuals [266,706 (54.5%) women; mean age 56.5 years (SD 8.1)] were included. During a median follow-up of 12.5 years, social isolation was uncorrelated with the majority of 59 health conditions. Significantly, it was associated with increased risks of all-cause [adjusted HR (aHR) 1.28, 95% CI 1.25-1.32], 5 cause-specific mortalities (aHR range, 1.18-1.38), and 11 specific diseases (aHR range, 1.08-1.17). Living alone was the strongest item of isolation in predicting mortality (aHR range, 1.18-1.45) and selected diseases. MR analyses offered little evidence to support a causal link between social isolation and these diseases. The proteins involved in these associations are predominantly related to "response to stimulus". Proteomic signatures (PERM, 36%-49%), health behaviours (32%-59%), and socioeconomic factors (22%-42%) were the main explanatory factors linking social isolation to 8 health outcomes. CONCLUSIONS: Social isolation is associated with elevated risks of 17 out of the 59 examined adverse health outcomes, predominantly mortality-related conditions; however, MR analyses indicate an absence of evidence supporting causality for these associations.

Humans↗

PubMed2026

Artificial intelligence for translational personalized neoantigen cancer vaccine development.

Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor antigens. Early clinical studies have demonstrated the feasibility, safety, and immunogenicity of these vaccines across multiple solid tumors, with encouraging outcomes particularly when combined with immune checkpoint blockade. However, broader clinical translation remains limited by sequential bottlenecks across the vaccine development pipeline, including false-positive neoantigen selection,  imperfect modeling of antigen processing and HLA presentation, limited prediction of T-cell receptor recognition, and challenges in formulation, delivery, and manufacturing. Artificial intelligence and advanced computational workflows are increasingly integrated into this pipeline to improve candidate prioritization and support more reproducible decision-making. In this review, we summarize clinical progress and key translational barriers in personalized neoantigen vaccination, and discuss how AI-enabled approaches may contribute across four major stages: multi-omics integration for neoantigen discovery, processing-aware HLA presentation prediction, structure-aware and TCR-informed immunogenicity modeling, and data-driven formulation optimization, particularly for lipid nanoparticle-based delivery systems. These approaches are able to help narrow biological and chemical search spaces, improve prioritization, and provide mechanistic insights into antigen presentation and immune recognition rather than replacing experimental validation. This articlefurther addresses future implementation challenges, including dataset diversity, model interpretability, prospective benchmarking, manufacturing traceability, and evolving regulatory frameworks for individualized mRNA cancer immunotherapies. Integrating computational innovation with rigorous immunological validation, scalable manufacturing, and regulatory oversight will be essential for advancing personalized neoantigen vaccines toward broader clinical implementation.

Cancer Vaccines↗

PubMed2026

LLPS-based classification and a novel prognostic signature reveal NRF1 as a therapeutic target in pancreatic cancer.

BACKGROUND: Aberrant liquid-liquid phase separation (LLPS) can alter biomolecular condensate functions and may influence pancreatic tumorigenesis and progression, but the specific role of LLPS regulators in prognosis and the tumor immune microenvironment (TIME) in pancreatic ductal adenocarcinoma (PDAC) remains unclear. METHODS: We integrated transcriptome data of LLPS regulator-related differentially expressed genes (DEGs; n = 298) in a cohort of 176 PDAC patients from TCGA. Three LLPS regulator subtypes (LS1-LS3) were identified through multi-omics analyses, and a prognostic LLPS subtype-related risk model (LRRPC) was developed and validated. Chromatin immunoprecipitation confirmed NRF1 binding to promoters of key risk genes, and in vitro and in vivo experiments assessed the effects of NRF1 targeting on tumor growth. RESULTS: The three LLPS regulator subtypes exhibited significant differences in prognosis, clinical features, genomic alterations, TIME patterns and predicted immunotherapy response. The LRRPC signature predicted prognosis and immunotherapy efficacy across cohorts and was associated with tumor biomarkers and immune infiltration. Nuclear Respiratory Factor 1 (NRF1) directly regulated hub genes such as FAM83A, RHOV and ITGB6, promoting PDAC cell proliferation, while its inhibition induced apoptosis and reduced tumor growth. CONCLUSIONS: This study proposes an LLPS-based stratification framework for PDAC, and the LRRPC model provides an LLPS subtype-related risk score that may assist personalized prognostic assessment and immunotherapy stratification. NRF1 emerges as a promising therapeutic candidate whose targeting can inhibit tumor progression in PDAC experimental models and warrants further evaluation.

Immunotherapy↗

PubMed2026

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) with anti-angiogenic agents is the preferred first-line therapy option for patients with advanced hepatocellular carcinoma (HCC), yet only a subset of patients responds, urging the quest for prediction biomarkers. We aimed to integrate genomics with radiology to propose an immune-derived radiogenomics biomarker of response to such combination immunotherapy and evaluate its added value in clinical context. METHODS: We integrated bulk RNA sequencing (RNA-seq) and proteomics data of 994 HCC patients with single-cell RNA-seq data of 11 samples across multiple datasets to identify an immune-related signature (IRS) that may influence sensitivity or resistance to such combined immunotherapy strategy, followed by verification of selected marker genes using immunohistochemistry and cytological experiments. We then trained/validated a cross-modality radiogenomics biomarker using machine learning based on TCIA database that was further tested in multi-scale independent cohorts covering 754 HCC patients. RESULTS: Integrative multi-omics analysis identifed a parsimonious 2-gene prognostic signature including KPNA2 and SMG5 that was significantly associated with immune heterogeneity and response to combination immunotherapy. Machine-learning pipeline exported the optimal 4-feature radiogenomics biomarker using support vector machine that significantly discriminated prognosis (hazard ratio 1.415–1.890; p < 0.05 for all) and modestly predicted response to ICI plus anti-angiogenic therapy (area under the curve 0.720–0.829) in independent retrospective series across major imaging modalities (computed tomography/magnetic resonance imaging). In a prospective neoadjuvant cohort, this biomarker also showed favorable performance for predicting pathological response and tumor recurrence, accompanied by biological validation through single-cell RNA-seq analysis of pre-treatment biopsies. CONCLUSIONS: Our study provides a cross-device-cross-modal radiogenomics biomarker that can improve patient selection for emerging ICI plus anti-angiogenic therapy with novel potential therapeutic targets in HCC.

Humans↗

PubMed2026

Cell-type specific activation of the cGAS-STING pathway in tumor immunotherapy: mechanisms and therapeutic implications.

BACKGROUND: The cyclic GMP–AMP synthase–stimulator of interferon genes (cGAS–STING) pathway acts as a pivotal innate immune sensor that detects cytosolic DNA and links genomic instability to antitumor immune activation. Therapeutic activation of this pathway has garnered substantial interest as a strategy to enhance cancer immunotherapy by promoting dendritic cell maturation, augmenting antigen presentation, and facilitating cytotoxic lymphocyte infiltration. However, the functional outcomes of cGAS–STING signaling are highly context dependent and influenced by both cell type and tumor microenvironmental (TME) conditions. MAIN BODY: Recent advances in single-cell and spatial transcriptomic profiling have revealed profound heterogeneity in cGAS–STING activation across distinct cellular and regional compartments within tumors. Acute and spatially restricted activation of the pathway can elicit potent antitumor immune responses, whereas chronic or dysregulated signaling may promote immune tolerance and tumor progression. Moreover, metabolic stress, epigenetic silencing, and microenvironmental immunosuppressive factors such as TGF-β and IL-10 can further modulate STING activity, leading to resistance to immunotherapy. Current translational efforts focus on next-generation STING agonists, nanoparticle-based delivery systems, and rational combination strategies with immune checkpoint blockade and metabolic modulators to overcome tumor-intrinsic resistance and minimize systemic toxicity. CONCLUSIONS: Understanding the cell-type-specific and spatial dynamics of cGAS–STING signaling is crucial for the rational design of precision immunotherapies. Future research should emphasize context-dependent modulation of STING activity to maximize therapeutic benefit while limiting adverse effects. Integrating multi-omics technologies and spatially guided drug delivery may ultimately enable personalized modulation of the cGAS–STING axis, transforming it into a clinically effective and safe strategy for cancer immunotherapy.

Humans↗

PubMed2026

LDHC4 promotes ovarian cancer progression through H4K12 lactylation to regulate PGK1 expression and modulate glycolysis.

OBJECTIVE: Ovarian cancer (OC) pathogenesis involves metabolic and epigenetic alterations, yet the underlying mechanisms remain unclear. Here, we sought to investigate the role and regulatory mechanism of lactate dehydrogenase C4 (LDHC4) in OC progression. METHODS: Multi-omics approaches were employed, including analyses of The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts, tissue microarrays, molecular biology experiments, and in vivo mouse models. LDHC4 expression was modulated in OC cell lines (A2780 and ES-2) to assess its effects on proliferation, migration, invasion, and metastasis. Lactylproteomic profiling, cleavage under targets and tagmentation (CUT&Tag), and chromatin analyses were conducted to explore epigenetic mechanisms. The functional role of the downstream glycolytic enzyme phosphoglycerate kinase 1 (PGK1) was examined using pharmacological inhibition. Molecular docking and xenograft models were used to evaluate the therapeutic potential of targeting H4K12lac (lactylation of histone H4 at lysine 12). RESULTS: LDHC4 was significantly overexpressed in OC tissues and associated with poor overall survival (OS) (hazard ratio [HR] = 4.017, 95% confidence interval [CI]: 2.308–6.989, P < 0.0001). It promoted proliferation, migration, invasion, and metastasis in vitro and in vivo. LDHC4 overexpression increased global lactylation, notably upregulating H4K12lac, which was enriched at the PGK1 promoter. Inhibition of PGK1 with CBR-470-1 (half-maximal inhibitory concentration [IC₅₀] = 14.56 µM) suppressed OC growth and metastasis. Importantly, Elbasvir, identified as a high-affinity H4K12lac inhibitor, significantly reduced tumor burden in mouse xenografts across multiple doses (10–20 mg·kg⁻¹) and downregulated H4K12lac and Ki-67 expression. CONCLUSION: We conclude that LDHC4 promotes OC progression via lactylation-mediated epigenetic upregulation of PGK1. Targeting this pathway through H4K12lac inhibitors such as Elbasvir thus emerges as a viable therapeutic approach for OC.

Female↗

PubMed2026

Proteomic and machine learning analysis predicts treatment response signatures in Myasthenia Gravis.

BACKGROUND: Myasthenia gravis (MG) is a prototypical antibody-mediated autoimmune disease with variable treatment responses with a need for biomarkers to guide therapeutic decision making. Proteomic profiling, coupled with machine learning, offers a hypothesis-free approach to identify multi-protein signatures associated with treatment response. METHODS: We analyzed sera collected at entry (baseline) from participants in a phase 3 trial randomized trial comparing thymectomy plus prednisone versus prednisone alone, along with matched controls using liquid chromatography-mass spectrometry. We derived disease-specific proteomic signatures and evaluated associations between baseline proteins and 6-month clinical outcomes using multiple machine-learning approaches with internal validation. RESULTS: Baseline serum proteomes distinguished MG from controls, with pathway enrichment implicating complement activation, immunoglobulin production, and T-cell receptor signaling. Distinct protein panels predicted 6-month clinical improvement within each treatment arm. In the thymectomy-plus-prednisone group, models captured non-linear relationships of predictive proteins in contrast with the predominant additive patterns observed in the prednisone-alone group. Predictive proteins were enriched for T-cell signaling and leukocyte trafficking functions, providing insight into treatment-specific biology. CONCLUSIONS: Baseline serum proteomics captures core disease characteristics of MG and predicts short-term clinical response in a treatment-specific manner. While our results require validation in independent cohorts, these findings could enable biomarker-guided selection of thymectomy, refine risk stratification, and furnish mechanistic readouts for future MG trials and clinical care. We aim to conduct future studies using -omic approaches to validate these baseline predictive biomarkers and pathways of treatment response in patients with MG.

Adult↗

PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗

PubMed2025

Altered ruminal microbiome tryptophan metabolism and their derived 3-indoleacetic acid inhibit ruminal inflammation in subacute ruminal acidosis goats.

BACKGROUND: Subacute ruminal acidosis (SARA) is a digestive disorder that often severely jeopardizes the health and lactation performance of ruminants fed a high-energy diet. Different dairy ruminants exhibit varying degrees of inflammation accompanied by variations in the rumen microbiota when SARA occurs. Our understanding of the occurrence of SARA and varying degrees of rumen epithelial inflammation is lacking. Hence, we performed rumen metagenomic, metagenome-assembled genome and metabolomic analyses, with transcriptome and single-nucleus RNA sequence analyses, to explore the microbial mechanism of SARA occurrence and different degrees of inflammation. RESULTS: A total of 36 goats fed two diets with gradually increasing levels of rumen-degradable starch (RDS) were included in this study, and SARA goats fed 70% concentrate diets supplemented with whole corn (HGW-SARA) and SARA goats fed 70% concentrate diets supplemented with crushed corn (HGC-SARA) were identified. Moreover, 11 goats fed a control basal diet, named LGW-CON, were also included. Compared with those in the LGW-CON group, the rumen fermentation capacity was enhanced, accompanied by ruminal epithelial and systemic inflammation, in goats from HGW-SARA and HGC-SARA. Between them, HGC-SARA goats presented less inflammation. Notably, the ruminal inflammation-related pathways were increased only in the HGW-SARA group but not in the HGC-SARA group. Metagenomic analysis revealed that the β diversity of SARA goats was significantly different from that of LGW-CON goats. Ruminococcus significantly increased in both SARA groups, whereas Prevotella and Bacteroidales significantly decreased, which was accompanied by a decrease in cellulose and hemicellulose enzymes and an increase in lysozymes and lipopolysaccharide synthesis enzymes. Multi-omics analysis of the ruminal contents and tissues suggested that epithelial inflammation was caused by disturbed ruminal microbiome-induced Th17 cell differentiation and IL-17 signalling pathway activation. Comparative analyses between the HGW-SARA and HGC-SARA groups highlighted the importance of Selenomonas and Bifidobacterium, as well as bacterial tryptophan metabolism, in the production of 3-indoleacetic acid, which mitigated ruminal epithelial inflammation by modulating Th17 cells and inhibiting IL-17 signalling. Ruminal microbiota transplantation from HGW-SARA goats to healthy dairy goats and mice revealed the role of microbes in epithelial inflammation. Additionally, 3-indoleacetic acid supplementation reduced rumen inflammation and the IL-17 concentration in the serum, improved VFAs absorption, and enhanced milk production. CONCLUSIONS: This study unveiled that after SARA was induced by high-concentrate feeding, the rumen homeostasis was disrupted, and rumen fiber degradation capacity of dairy goats decreased, but the LPS synthesis capacity increased, and inflammation of the rumen epithelium was observed. However, the ruminal microbial species from the Bifidobacterium and Selenomonas genera and bacterial 3-indole acetic acid are pivotal in mitigating ruminal epithelial inflammation during SARA in dairy goats. This could potentially be attributed to the modulation of ruminal Th17 cell proportions and the inhibition of IL-17 signalling pathways. Video Abstract.

Rumen↗

PubMed2026

Beyond borders: plasmids drive a shared antibiotic resistome in European urban water systems.

BACKGROUND: Urban wastewater systems (UWSs) act as reservoirs and conduits for the dissemination of antibiotic resistance genes (ARGs), with plasmids playing a central role in their spread. Despite their significance, the diversity and persistence of plasmids in UWSs remain underexplored. RESULTS: This study applies a multi-omics approach, including metagenomic and direct plasmidome sequencing, high-throughput qPCR array, and whole genome sequencing of plasmid isolates, to comprehensively profile the microbial plasmidome and resistome on 78 samples across UWSs in Denmark, Spain, and the UK. We successfully uncovered an extensive plasmid and ARG diversity that could not be fully captured by a single method, especially identified 78,574 plasmids, including 20,925 plasmids previously unreported. We also observed that plasmids carried a disproportionate share of clinically relevant ARGs, particularly beta-lactamase resistance genes; most importantly, they were preferentially located on transmissible plasmids. Furtherly, plasmids harbor ARG can enhance their persistence in wastewater ecosystems, especially harboring multiple types of ARGs. Moreover, Bacteroides emerged as a unique persistent ARG reservoir not only for harboring and disseminating diverse resistance genes especially in residential-relevant areas, but also emerged as a major driver of antimicrobial resistance dynamics across different wastewater treatment processes. CONCLUSIONS: Overall, this work provides the first attempt at a holistic description of the UWSs' resistome, its structure, dynamics, and mobility and significantly expands the current knowledge. Video Abstract.

Plasmids↗

PubMed2026

Characterization of age-related changes in the gut microbiome and metabolome of Kunming dogs and their associations with police performance.

BACKGROUND: Gut microbiota plays a pivotal role in regulating the host's central nervous system (CNS) activity and behavior. However, its influence on the police performance of Kunming dogs and the underlying mechanisms remain largely unexplored. This study was the first to apply multi-omics technologies to investigate the dynamic variations in gut microbiota and their metabolic profiles across different ages of Kunming dogs. Furthermore, we systematically examined the associations between these microbial alterations and police performance metrics, providing a theoretical foundation for enhancing the working capabilities of Kunming dogs through targeted modulation of intestinal microecology. RESULTS: The study showed that puppies, young dogs and adult dogs had significantly better police performance than elderly dogs, with young dogs exhibiting the highest scores. Analysis of 16S rRNA sequencing demonstrated that gut microbial diversity and stability were highest during the young dog stage, gradually declining with age. Metagenomic analysis revealed that the abundance of Lactobacillus acidophilus, Lactobacillus johnsonii, Limosilactobacillus reuteri, Ligilactobacillus animalis and Muribaculum gordoncarteri were strongly correlated with police performance. The results of metagenome-assembled genomes (MAGs) indicated that the above species have functional genes involved in GABAergic and glutamatergic synapse pathways. Furthermore, metabolomic analysis showed that differential metabolites were enriched in the neuroactive ligand-receptor interaction pathway, in which GABA (γ-aminobutyric acid), histamine and tyramine metabolites were positively correlated with the above species and police performance. CONCLUSION: The species L. acidophilus, L. johnsonii, L. reuteri, L. animalis, and M. gordoncarteri, which were enriched in the gut of puppies and young Kunming dogs, may potentially influence the nervous system through the production of neurotransmitters and neuromodulators, suggesting a possible association with police performance. Video Abstract.

Animals↗

PubMed2026

Precisely designed keystone metabolites boost shrimp disease resistance by recruiting symbionts via the lipoxin A4-AP-1 pathway.

BACKGROUND: Gut metabolites and symbionts are indispensable for host health, yet the precise identification of keystone metabolites and construction of synthetic microbial communities (SynComs) to enhance disease resistance remains limited. RESULTS: Using Litopenaeus vannamei as a model, we identified pyruvic acid and DL-glutamine (1:2) as keystone metabolites by borrowing the microbial ecology principles of bio-indicators and driver taxa. Dietary supplementation with these metabolites sufficiently protected shrimp from white feces syndrome (WFS). Multi-omics analyses demonstrated that keystone metabolites exerted positive effects by enriching beneficial Ruegeria lacuscaerulensis, Bacillus subtilis and Nioella nitratireducens, strengthening the gut network stability, and enhancing shrimp immunity, which collectively potentiated WFS resistance. The recruited three strains were consumers and producers of the two keystone metabolites, and discriminative strains between healthy and diseased shrimp across global datasets. A SynCom constructed from the three strains (4:3:2) replicated the efficacy of keystone metabolites. Both keystone metabolites and SynCom elevated shrimp gut and hepatopancreas lipoxin A4 (LXA4) levels, which suppressed the pro-inflammatory transcription factor AP-1, as validated by in vivo inhibition assay. CONCLUSIONS: Our findings demonstrate that precisely designed keystone metabolites enhance shrimp disease resistance through the recruitment of key symbionts-LXA4-AP-1 axis. The rationally designed keystone metabolites and SynCom are compelling biocontrol solutions in improving host disease resistance. Video Abstract.

Animals↗