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PubMed2026

Proteomics combined with single-cell sequencing reveals key genes and computational lead compound related to ligamentum flavum hypertrophy, lactate metabolism and lactate modification.

Ligamentum flavum hypertrophy (LFH) is a hallmark pathological feature of lumbar spinal stenosis; however, its underlying molecular mechanisms remain incompletely understood. Lactate metabolism and related lactylation modifications have emerged as critical links between cellular metabolism and epigenetic regulation, with established roles in various fibrotic and inflammatory diseases. Nevertheless, the specific contribution of lactylation to LFH pathogenesis remains unexplored. In this study, we integrated proteomic profiling of ligamentum flavum tissues with single-cell transcriptomic data to identify differentially expressed proteins associated with LFH. Cross-referencing these genes with genes involved in lactate metabolism and lactylation yielded 16 candidate genes. Through functional enrichment analysis, protein-protein interaction network construction, and GraphBAN model prediction, we identified five hub genes (NDUFS2, HMOX1, SPR, FABP5, and PFKP) and two potential lead compounds (ZINC000014879975 and ZINC000242437513). Molecular docking analysis confirmed favorable binding affinities between these compounds, suggesting that they may serve as potential lead compounds worthy of further experimental investigation. Single-cell analysis further revealed that macrophages occupy a central position in the LFH microenvironment, resulting in pronounced metabolic reprogramming and remodeling of intercellular communication networks, particularly via the MIF-CD74/CD44 axis, under pathological conditions.

Proteomics↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Proteomic responses of the oil palm pest Metisa plana (Psychidae) to farnesyl acetate exposure.

Metisa plana Walker (Lepidoptera: Psychidae) is a major defoliator of oil palm in Malaysia, causing substantial economic losses. Farnesyl acetate (FA), a sesquiterpenoid compound, has been proposed as a potential insecticidal agent against M. plana, yet its molecular impact on larval physiology remains poorly understood. Here, we employed label-free quantitative proteomics, functional enrichment analysis, and targeted transcript assessment to characterize the temporal proteomic response of M. plana larvae at 7 and 14 days after treatment (DAT) with FA. Principal component analysis revealed robust separation between treated and control samples at both time points, indicating sustained treatment-driven proteomic restructuring. Early exposure (7 DAT) elicited a heterogeneous response involving stress-associated proteins, redox enzymes, and cytoskeletal regulators, whereas later exposure (14 DAT) produced a consolidated profile characterized by metabolic reprogramming, downregulation of ribosomal proteins, induction of heat shock proteins, and enrichment of RNA surveillance and mitochondrial pathways. Targeted transcript analysis qualitatively supported proteomic trends for HSP83 and aldehyde dehydrogenase X, although limited amplification precluded quantitative inference. Collectively, these findings demonstrate that FA exposure drives a shift from acute proteomic perturbation toward a maintenance-oriented physiological state, prioritizing proteostasis, energy management, and stress adaptation over growth and development. This integrated molecular perspective provides mechanistic insight into the chronic effects of FA, highlighting its potential to suppress larval performance and informing the development of biorational, physiology-based pest management strategies in non-model insects.

Animals↗

PubMed2026

Crosstalk between the Wnt pathway and other signaling pathways.

The Wnt/β-catenin signaling pathway is a deeply conserved regulatory network that governs embryonic development, stem cell maintenance, and tissue homeostasis. Aberrant activation of the Wingless/Integrated protein (Wnt) signaling is a hallmark of numerous human diseases, most prominently in colorectal cancer, where it cooperates with additional oncogenic pathways to drive tumor initiation, progression, and therapeutic resistance (See Supplementary Table 1 for a list of the abbreviations used in this manuscript and their definitions.). Increasing evidence indicates that Wnt signaling does not function as an isolated linear cascade but rather as an integrative signaling hub that dynamically interfaces with major signaling pathways, including the RAS-RAF-MAPK and PI3K-AKT-mTOR pathways. Rat Sarcoma protein (RAS)- Rapidly Accelerated Fibrosarcoma protein (RAF)- Mitogen-Activated Protein Kinase (MAPK) and Phosphoinositide 3-Kinase (PI3K)- Ak strain transforming protein (AKT)- Mechanistic Target of Rapamycin (mTOR) pathways. These interactions occur at multiple molecular levels, encompassing shared kinases, transcriptional regulators, metabolic nodes, and cytoskeletal components, thereby coordinating proliferative, metabolic, and migratory programs. In this review, we synthesize current mechanistic and clinical insights into the crosstalk between Wnt signaling and the RAS-RAF-MAPK and PI3K-AKT-mTOR pathways, with particular emphasis on colorectal cancer. We discuss how these signaling networks converge to regulate β-catenin stability, transcriptional activity, cell adhesion, and metabolic reprogramming, thereby generating oncogenic phenotypes that cannot be explained by activation of individual pathways alone. To illustrate the evolutionary conservation and biological significance of these interactions, we integrate developmental paradigms from early Xenopus embryogenesis, where Wnt signaling governs zygotic genome activation, body axis formation, and the regulation of cell growth, protein stability, and biomass accumulation. Finally, we examine how an improved understanding of Wnt-centered signaling networks is informing emerging therapeutic strategies, including combinatorial pathway inhibition and nanoparticle-based drug delivery. Collectively, this review highlights Wnt signaling as a central integrator of developmental and oncogenic programs, providing a conceptual framework for understanding signaling network crosstalk and identifying new therapeutic opportunities in cancer.

Humans↗

PubMed2026

Recent advances in immunotherapy for breast cancer: An updated review.

Immunotherapy has revolutionized the treatment landscape of breast cancer, particularly for triple-negative breast cancer (TNBC), yet primary and acquired resistance remain formidable obstacles limiting durable clinical benefit. This review provides a comprehensive update on recent advances in breast cancer immunotherapy, with a focused emphasis on the molecular and cellular mechanisms driving treatment resistance and emerging strategies to overcome them. We dissect tumor-intrinsic resistance pathways, including loss of tumor antigens, defects in antigen processing and presentation machinery, insensitivity to interferon-γ signaling, metabolic reprogramming, and epigenetic dysregulation. Tumor-extrinsic mechanisms, such as infiltration of immunosuppressive cells, abnormal angiogenesis, extracellular matrix remodeling, and FGF/FGFR genomic amplification, are highlighted as key barriers to effective immune checkpoint blockade. Emerging evidence implicates novel resistance mediators, including the DUSP22-LGALS1 axis, THSD4-driven T cell exclusion, and the MTDH-SND1 complex impairing antigen presentation, etc. We critically evaluate current strategies to surmount resistance, encompassing combination regimens with chemotherapy, targeted therapies, radiotherapy, and novel immunomodulators. The review also addresses challenges in managing immune-related adverse events, controversies surrounding patient selection biomarkers, and the urgent need for optimized efficacy evaluation systems beyond RECIST criteria. Finally, we discuss future directions, including novel immune checkpoints, microbiome modulation, artificial intelligence-assisted decision-making, and innovative trial designs. By integrating mechanistic insights with clinical evidence, this review provides a framework for understanding and overcoming immunotherapy resistance, advancing the paradigm from "effective" to "precise" immuno-oncology in breast cancer.

Humans↗

PubMed2026

Snail immunity to schistosomes: insights from omics studies.

Schistosomiasis is a serious public health concern, with transmission facilitated by a small number of freshwater snail intermediate host species. Infection outcomes vary greatly across the primary vector genera, Biomphalaria (for Schistosoma mansoni), Bulinus (for S. haematobium), and Oncomelania (for S. japonicum), even within species, ranging from full resistance to high compatibility. Omics methods have altered this field by correlating host genotype, baseline immunological status, and time-resolved responses to whether invading miracidia are eliminated or develop sporocysts. Evidence from genomes, transcriptomics, proteomics, and epigenomics suggests that resistance is frequently primed prior to exposure. However, the clearest divergence between resistant and susceptible trajectories occurs during a small early window (<12-48 h) after penetration. During this time, recognition, hemocyte recruitment, and soluble effector deployment either come together quickly or are delayed and guided by parasite-derived modulators. Established infections cause the host to adapt to chronic conditions through immune regulation, metabolic reprogramming, tissue and neuroendocrine remodeling, microbiome modification, and parasite castration. Comparative genomics reveals that each vector genus has evolved its own immunogenomic profile, which includes lineage-specific expansions of recognition and effector gene families. Together, these findings can help with field surveillance and intervention by providing molecular compatibility markers, functional tools for testing candidate genes, and tactics that target parasite-derived immune modulators. Integrated multi-omics approaches are a top priority, yet they are still limited in snail vectors compared to other disease vector systems.

Animals↗

PubMed2026

PGC1α expression using targeted redox-responsive nanogels protects against prostate cancer in vivo.

Prostate cancer is among the most frequently diagnosed cancers in men in the UK and US. Increasing evidence implicates metabolic dysregulation as a critical driver of disease progression. Central to this process is peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) that promotes oxidative metabolism and mitochondrial biogenesis while inhibiting metastatic programs. This work investigated the therapeutic potential of PGC1α overexpression via mRNA delivery. Here, we report a prostate-specific, targeted disulphide-crosslinked nanogel system for intracellular delivery of mRNA encoding the N-terminal isoform of PGC1α (NT-PGC1α). Functionalization of the NGs with a peptide targeting prostate-specific membrane antigen (PSMA) enabled selective delivery of NT-PGC1α mRNA in PCa cells and 3D spheroid models. We confirmed sustained PGC1α expression, and increased mitochondrial protein content, indicative of enhanced mitochondrial biogenesis. These nanogels, which were prepared in situ using a nanopolymerization technique, exhibited high mRNA loading capacity, low cytotoxicity, and redox-responsive cargo release, enabling controlled cytosolic delivery following intracellular glutathione-mediated degradation. In vivo, systemic administration of the PSMA-targeted NT-PGC1α mRNA-loaded nanogels resulted in tumor-preferential accumulation and significant suppression of xenograft growth (by 73.4% relative to untreated control), with minimal systemic toxicity. This study presents the first example of a prostate-targeted, disulfide-crosslinked nanogel system for mRNA-mediated metabolic reprogramming in prostate cancer, and highlights its promise as a platform for future RNA-based targeted and precision stimuli-responsive cancer therapies.

Male↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

A rare germline TXNIP missense mutation may contribute to the genesis of familial ovarian mature teratoma in human.

Ovarian mature teratoma (OT) is a common ovarian germ cell tumor, and its early onset, multifocality, recurrence and familial aggregation suggest that genetic susceptibility contributes to a subset of cases. Whole-exome sequencing was used to identify candidate susceptibility variants in a family with recurrent and multifocal OT. A rare heterozygous germline TXNIP variant, NM_006472.6:c.1049C > T (p.Pro350Leu), was identified and confirmed by Sanger sequencing. p.Pro350Leu TXNIP showed lower steady-state abundance, faster cycloheximide-chase decay, and greater K48-linked polyubiquitination than wild-type TXNIP. Familial OT specimens also showed weaker TXNIP staining and stronger GLUT1 staining than sporadic OT specimens. TXNIP depletion increased plasma-membrane GLUT1, glucose uptake, lactate production and hyperactivated the PI3K/mTOR pathway, and familial tissues reproduced this PI3K/mTOR-dominant state. To our knowledge, this is the first genomic and functional investigation of a germline susceptibility mechanism for human familial ovarian mature teratoma. These findings establish TXNIP as the first functional candidate susceptibility gene for this phenotype and connect inherited susceptibility to ubiquitin-dependent protein turnover, GLUT1-driven metabolic reprogramming, and PI3K/mTOR-dominant follicular signaling.

Missense mutation↗

PubMed2026

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers↗

PubMed2026

Ovarian aging and systemic health: Mechanisms and emerging intervention strategies.

Ovarian aging may contribute to systemic aging via the ovarian-systemic axis. This review outlines intrinsic ovarian cellular defects such as genomic instability, epigenetic shifts, and mitochondrial and proteostasis damage, which may trigger senescence-associated secretory phenotype (SASP)-related inflammaging, fibrosis, and distal pro-aging signals. Ovarian-derived endocrine disruption, especially estrogen decline, broadly affects bodily physiology. We summarize emerging multimodal interventions, including senolytics, metabolic reprogramming, regenerative medicine, and systemic approaches, and we discuss their dual potential to preserve fertility and intercept ovarian contributions to systemic aging. Ovarian aging is possibly associated with female age-related multimorbidity. Ovary-targeted prevention may extend healthspan, as assessed by combined reproductive and systemic clinical evaluations.

Humans↗

PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗

PubMed2026

The metabolic and anatomical complexity of root microhabitats modulate their interaction with the microbiota.

Plant roots constantly communicate with their microbiota, adapting their anatomy to facilitate microbial colonisation under abiotic stresses. Microbes, in turn, can reshape root anatomy once they establish. However, the mechanisms that coordinate this interplay remain largely unknown. Working with the aquatic plant family Lemnaceae, we reveal that the inherent complexity of root anatomy determines root plasticity in response to microbial colonisation. This microbiota-driven anatomical plasticity enhances plant survival in nutrient-competitive environments. By combining synthetic root models with real roots, we also find that anatomical plasticity is associated with metabolic reprogramming during microbial establishment. Moreover, we identify a plant metabolite, N6,N6,N6-Trimethyl-L-lysine, that regulates anatomical plasticity in response to microbial colonisation. Our work generalizes the importance of microhabitat complexity for microbiome recruitment under challenging environmental conditions.

Plant Roots↗

PubMed2026

Spatially guided in vivo single-cell functional genomics of postnatal heart.

Understanding how spatial organization and cell-cell interactions shape gene regulatory programs is central to decoding tissue development and function. The transition at birth, marked by increased circulatory demands and rapid tissue growth, requires precise spatiotemporal coordination of cardiac maturation. In this study, we generated a high-resolution spatial and temporal atlas of the postnatal mouse heart by integrating single-nucleus RNA sequencing with image-based spatial transcriptomics. This framework revealed dynamic cellular interactions, niche-specific signaling and transcriptional programs guiding cardiomyocyte maturation. To functionally test prioritized regulators in vivo and at scale, we developed PIP-seq (probe-based indel-detectable Perturb-seq), a high-throughput platform that detects single guide RNA identity, infers gene editing and profiles transcription from fixed nuclei. Applying PIP-seq to the developing postnatal heart, we identified 21 previously uncharacterized regulators of cardiomyocyte maturation, including genes essential for sarcomere assembly, metabolic reprogramming and electrophysiological transitions. Together, our findings define how microenvironmental signals and intrinsic gene programs cooperate to guide heart maturation and establish a broadly applicable framework for functional genomics in complex tissues.

Animals↗

PubMed2026

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature of malignant brain tumors such as glioblastoma. Emerging evidence indicates that BBB dysfunction not only alters the tumor microenvironment but also shapes the mutational processes that drive genomic instability in CNS malignancies. This review synthesizes current understanding of the biological mechanisms linking BBB breakdown with distinct mutational signatures, including those arising from oxidative stress, hypoxia-induced replication stress, lipid peroxidation, inflammation, and metabolic reprogramming. Advances in next-generation sequencing, coupled with computational tools such as non-negative matrix factorization, Bayesian modeling, and deep learning, have enabled precise extraction of these signatures and their integration with multi-omics data. Clinically, BBB-associated mutational signatures offer significant promise for therapeutic stratification, prediction of treatment response, and noninvasive monitoring through cerebrospinal fluid - derived circulating tumor DNA. Despite these advances, challenges persist due to limited tissue accessibility, low-yield CSF samples, incomplete mechanistic models, and the lack of CNS-specific analytical frameworks. A deeper understanding of BBB-driven mutational processes, supported by improved computational approaches and integrative datasets, holds potential to advance precision oncology in neuro-oncology.

Humans↗

PubMed2025

GiantHunter: accurate detection of giant virus in metagenomic data using reinforcement-learning and Monte Carlo tree search.

MOTIVATION: Nucleocytoplasmic large DNA viruses (NCLDVs) are notable for their large genomes and extensive gene repertoires, which contribute to their widespread environmental presence and critical roles in processes such as host metabolic reprogramming and nutrient cycling. Metagenomic sequencing has emerged as a powerful tool for uncovering novel NCLDVs in environmental samples. However, identifying NCLDV sequences in metagenomic data remains challenging due to their high genomic diversity, limited reference genomes, and shared regions with other microbes. Existing alignment-based and machine learning methods struggle with achieving optimal trade-offs between sensitivity and precision. RESULTS: In this work, we present GiantHunter, a reinforcement learning-based tool for identifying NCLDVs from metagenomic data. By employing a Monte Carlo tree search strategy, GiantHunter dynamically selects representative non-NCLDV sequences as the negative training data, enabling the model to establish a robust decision boundary. Benchmarking on rigorously designed experiments shows that GiantHunter achieves high precision while maintaining competitive sensitivity, improving the F1-score by 10% and reducing computational cost by 90% compared to the second-best method. To demonstrate its real-world utility, we applied GiantHunter to 60 metagenomic datasets collected from six cities along the Yangtze River, located both upstream and downstream of the Three Gorges Dam. The results reveal significant differences in NCLDV diversity correlated with proximity to the dam, likely influenced by reduced flow velocity caused by the dam. These findings highlight GiantHunter's potential to advance our understanding of NCLDVs and their ecological roles in diverse environments. AVAILABILITY AND IMPLEMENTATION: The source code of GiantHunter is available via: https://github.com/FuchuanQu/GiantHunter.

Metagenomics↗

PubMed2025

Untargeted metabolomics reveals anion and organ-specific metabolic responses of salinity tolerance in willow.

Willows can alleviate soil salinisation while generating sustainable feedstock for biorefinery, yet the metabolomic adaptations underlying their tolerance remain poorly understood. Salix miyabeana was treated with two environmentally abundant salts, NaCl and Na2SO4, in a 12-week pot trial. Willows tolerated salts across all treatments (up to 9.1 dS m-1 soil ECe), maintaining biomass while selectively partitioning ions, confining Na+ to roots and accumulating Cl- andin the canopy and adapting to osmotic stress via reduced stomatal conductance. Untargeted metabolomics captured >5000 putative compounds, including 278 core willow metabolome compounds constitutively produced across organs. Across all treatments, salinity drove widespread metabolic reprogramming, altering 28% of the overall metabolome, with organ-tailored strategies. Comparing salt forms at equimolar sodium, shared differentially abundant metabolites were limited to 3% of the metabolome, representing the generalised salinity response, predominantly in roots. Anion-specific metabolomic responses were extensive. NaCl reduced carbohydrates and tricarboxylic acid cycle intermediates, suggesting potential carbon and energy resource pressure, and accumulated root structuring compounds, antioxidant flavonoids, and fatty acids. Na2SO4 salinity triggered accumulation of sulphur-containing larger peptides, suggesting excess sulphate incorporation leverages ion toxicity to produce specialised salt-tolerance-associated metabolites. This high-depth picture of the willow metabolome underscores the importance of capturing plant adaptations to salt stress at organ scale and considering ion-specific contributions to soil salinity.

Salix↗

PubMed2025

Tracking Nongenetic Evolution from Primary to Metastatic ccRCC: TRACERx Renal.

While the key aspects of genetic evolution and their clinical implications in clear cell renal-cell carcinoma (ccRCC) are well-documented, how genetic features co-evolve with the phenotype and tumor microenvironment (TME) remains elusive. Here, through joint genomic-transcriptomic analysis of 243 samples from 79 patients recruited to the TRACERx Renal study, we identify pervasive non-genetic intratumor heterogeneity, with over 40% not attributable to genetic alterations. By integrating tumor transcriptomes and phylogenetic structures, we observe convergent evolution to specific phenotypic traits, including cell proliferation, metabolic reprogramming and overexpression of putative cGAS-STING repressors amid high aneuploidy. We also uncover a co-evolution between the tumor and the T cell repertoire, as well as a longitudinal shift in the TME from an anti-tumor to an immunosuppressive state, linked to the acquisition of recurrently late ccRCC drivers 9p loss and SETD2 mutations. Our study reveals clinically-relevant and hitherto underappreciated non-genetic evolution patterns in ccRCC.

Journal Article↗