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PubMed2026

Identifying Co-Expressed lncRNAs Correlated With Traits of Interest in an Animal Model for Metabolic Diseases in Humans.

Nutrigenomics investigates how nutrients modulate gene expression. Among them, fatty acids (FA) play important roles in regulating gene transcription, while long non-coding RNAs (lncRNAs) may be associated with gene regulation and metabolic diseases. This study aimed to analyze the hepatic transcriptome of pigs, a species frequently used as a model for nutrigenomic studies, to identify novel lncRNAs and their potential target genes in response to diets containing different sources of FA. Seventy-two pigs were fed four diets supplemented with 1.5% soybean oil (control), 3% canola oil, 3% fish oil, and 3% soybean oil. RNA sequencing of liver samples was performed to identify novel lncRNAs. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules associated with phenotypic traits related to lipid metabolism and inflammation. Functional enrichment analyses were then conducted to annotate genes within these modules using Gene Ontology (GO) terms and to assess overlap with Quantitative Trait Loci (QTL). The results revealed 106 novel lncRNAs potentially regulating genes associated with lipid metabolism and immune responses in pigs fed diets with different FA sources. These findings enhance understanding of the regulatory role of lncRNAs in pigs and reinforce their relevance as models for human metabolic diseases.

Animals↗

PubMed2026

Brachyury expression levels predict lineage potential and axis-forming ability of in vitro-derived neuromesodermal progenitors.

Neuromesodermal progenitors (NMPs) produce the spinal cord and musculoskeleton in the elongating anterior-posterior axis. In vivo, NMPs possess dual potency, coinciding with regions co-expressing SOX2 and Brachyury (TBXT). In vitro, SOX2/TBXT co-expressing cells can be produced from pluripotent cells and, like their in vivo counterparts, can produce neural tube and somitic mesoderm. However, the functional characteristics of in vitro SOX2/TBXT co-expressing cells remain unclear, confounding comparisons with in vivo data. To address this, we developed a dual Sox2/Tbxt reporter mouse ESC line. SOX2/TBXT reporter-positive cells emerge in vitro from pluripotent populations with dynamics that mirror their appearance in the embryo. Purified SOX2/TBXT co-expressing populations can differentiate towards neurectoderm or mesoderm, including lateral mesoderm upon BMP stimulation. In gastruloids, quantitative live imaging shows that WNT or NOTCH inhibition rapidly leads to downregulation of TBXT expression and diminished axial extension. We show that clonally plated SOX2/TBXT co-expressing cells are bipotent NMPs that can also self-propagate. By combining clonal analysis with mathematical inference, we identify two thresholds of TBXT and/or SOX2 expression, switching clonal output from neural- to mesoderm-biased, and from mesoderm-biased to mesoderm-specified. Image analysis of embryonic NMPs supports a model whereby SOX2 and TBXT independently influence neuromesodermal differentiation. Thus, this Sox2/Tbxt double reporter cell line highlights unsuspected heterogeneity in NMPs, and together with image analysis of embryonic SOX2/TBXT levels, challenges the assumption that neuromesodermal fate choice is primarily governed by mutual antagonism between SOX2/TBXT.

Animals↗

PubMed2026

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Dual-Reporter Gene-Based Multimodal Imaging for Tracking Mesenchymal Stem Cells in Diabetic Skin Wound Repair.

BACKGROUND: Diabetic foot ulcer (DFU) is a clinically challenging complication characterized by poor healing outcomes, and conventional therapies provide limited benefit. Mesenchymal stem cell (MSC) transplantation offers a promising strategy for DFU repair. However, the low survival of transplanted MSCs in the hostile wound microenvironment, coupled with the lack of real-time, non-invasive methods to track these cells in vivo, severely hampers their therapeutic efficacy and clinical translation. METHODS: We engineered MSCs to co-express a dual reporter system comprising near-infrared fluorescent protein (iRFP) and ferritin heavy chain (FTH1). These modified cells were then integrated with a fibrin glue (FG) scaffold to create a unified platform that supports both multimodal imaging and therapeutic function within skin wounds. First, FTH1 overexpression enhances the antioxidant capacity of MSCs, while the FG scaffold provides structural support; this combination enhances cell survival and retention. Second, the iRFP/FTH1 dual reporter enables near-infrared fluorescence imaging and MRI-based localization, establishing a multimodal platform for real-time cell tracking. RESULTS: In a full-thickness skin defect model in diabetic mice, multimodal imaging revealed that transplanted cells persisted in the wound area for approximately seven days. Treatment with iRFP/FTH1-MSCs/FG significantly accelerated wound closure and promoted hair follicle regeneration and angiogenesis. Additionally, local iron deposition resulting from FTH1 expression enhanced fibroblast migration and collagen synthesis, further facilitating extracellular matrix remodeling. Mechanistic studies demonstrated that this therapy drives macrophage polarization toward the anti-inflammatory M2 phenotype and activates the PI3K-AKT-VEGF signaling pathway. These complementary effects synergistically enhance tissue regeneration and systematically improve diabetic wound healing. CONCLUSIONS: Collectively, this multimodal stem cell-scaffold system effectively integrates dynamic cell tracking with stem cell therapy during skin wound repair. It addresses a critical technical gap in visualizing stem cells within the wound microenvironment and provides valuable methodological and theoretical foundations for optimizing regenerative strategies for diabetic skin wounds.

Animals↗

PubMed2026

Pan-cancer single-cell atlas of immunotherapy response identifies ZNF385A as a regulator of immune evasion in small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of solid tumors, response rates in patients with small cell lung cancer (SCLC) remain limited, and acquired resistance is highly prevalent. The underlying mechanisms of this immunotherapy resistance remain to be fully elucidated. Clinically, SCLC typically manifests as an "immune-cold" tumor, characterized by a low abundance of CD8+ T cell infiltration and the rare formation of tertiary lymphoid structures (TLS). While DNA damage repair (DDR) is closely linked to innate immune responses, how DDR networks orchestrate the SCLC immune microenvironment remains obscure. In this study, we integrated single-cell transcriptomic data (comprising 344,447 high-quality cells) from six cancer types (BCC, CRC, HCC, HNSCC, iCCA, and SCLC). Our comparative analysis revealed a fundamental depletion of TLS-associated cellular subpopulations (e.g., CXCL13+ CD8+ T cells, HLA-DRB5+ B cells, and CXCL9+ dendritic cells) in SCLC, which was significantly correlated with aberrant DDR activity. Through high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified ZNF385A as the core hub gene within the DDR-associated module. ZNF385A is highly expressed in SCLC and is associated with poorer prognosis. In vitro, ZNF385A depletion suppressed SCLC cell proliferation and induced apoptosis, accompanied by R-loop accumulation and activation of cGAS-STING signaling, indicating a potential link between ZNF385A, genomic stability and tumor-intrinsic innate immune signaling. Collectively, these findings identify ZNF385A as a potential regulator associated with TLS deficiency and immune evasion in SCLC.

Immunotherapy resistance↗

PubMed2026

GSTT1 promotes stemness and FGFR inhibitor sensitivity in pancreatic cancer through regulation of CD133 (PROM1).

Pancreatic ductal adenocarcinoma (PDA) is among the deadliest malignancies, driven by metastatic progression and profound cellular heterogeneity. We previously identified glutathione S-transferase theta 1 (GSTT1) as a regulator of a slow-cycling, highly metastatic tumor cell population, suggesting that GSTT1High cells may possess stem-like properties. Here, we define the functional and molecular features of this subpopulation in metastatic PDA. Using a mCherry-tagged Gstt1 reporter system in metastatic murine PDAC cells, we enriched for Gstt1High cells and observed increased tumor sphere formation, accompanied by upregulation of stemness-associated genes including PROM1 (CD133) and activation of Wnt and FGF signaling pathways. In human PDA models, CD133HighGSTT1High cells exhibited enhanced tumor sphere initiation and expansion compared to other populations, defining a maximal stem-like state. Notably, sensitivity to FGFR inhibitors was observed only under tumor sphere conditions, highlighting a context-dependent therapeutic vulnerability. Mechanistically, FGFR3 expression correlated with GSTT1 and CD133 levels, and FGF signaling was required to sustain this state. GSTT1 knockdown reduced CD133 protein levels, impaired tumor sphere formation, and altered sensitivity to FGFR inhibition. These findings were largely recapitulated in patient-derived PDA organoids, where GSTT1 and PROM1 co-expression predicted increased tumor sphere formation and enhanced response to the multi-kinase inhibitor Nintedanib. Together, these results identify a GSTT1HighCD133High stem-like subpopulation in metastatic PDA and identify an FGFR-dependent signaling axis that sustains this state, representing a potential therapeutic vulnerability.

AC133 Antigen↗

PubMed2026

Unveiling the molecular basis of gonadal development: Multi-omics uncovers sex-related genes and steroid pathways in Sinonovacula constricta.

The razor clam Sinonovacula constricta is an economically important cultured mollusk in China, but the molecular mechanism of its gonadal development and sexual differentiation remains unclear. This study integrated gonadal transcriptomic, proteomic, and metabolomic analysis to identify key sex-related molecules. Transcriptome analysis identified 2795 DELs and 6497 DEGs between sexes, including the sex-related genes Fem-1b, Fem-1c, GUCY1B2 and FAT4, as well as a regulatory network of 39 lncRNA-mRNA pairs involving Tektin-4, Ropporin-1, Histone H1, and FoxN4. Proteomic analysis revealed 3217 DEPs: Tektin family members, Ropporin-1 and Tssk proteins were upregulated in the testis, while histone H1 and FAT4 were upregulated in the ovary. Metabolomic analysis detected 409 DEMs, with uridine identified as a potential sex differential marker (upregulated in the ovary), and 23 gonadal development-related DEMs showed sex-specific upregulation. Integrative transcriptome-proteome analysis identified 1543 co-expressed DEGs/DEPs enriched in nucleosome assembly, oxidative phosphorylation, and carbon metabolism, including key sex-related genes AKAP14, Tektin/Tssk families, Histone H1, and FAT4. Transcriptome-metabolome integration identified 32 shared KEGG pathways (e.g., biosynthesis of unsaturated fatty acids, pyrimidine metabolism), while proteome-metabolome integration revealed 5 (positive ion) and 6 (negative ion) co-enriched pathways, with alanine, aspartate and glutamate metabolism and oxidative phosphorylation being functionally relevant to gonadal development. Collectively, these results reveal the molecular basis of gonadal development, highlight critical sex-related genes and steroid metabolic pathways, and provide valuable resources for future reproduction and breeding in S. constricta.

Animals↗

PubMed2026

Uncovering molecular regulatory networks of low-temperature stress response in Trachinotus ovatus via integrated transcriptome and metabolome analyses.

Golden pompano (Trachinotus ovatus) is one of the most economically important marine fish species in China. It is susceptible to low-temperature stress, which significantly challenges its production and supply. Nevertheless, study on the regulatory mechanisms underlying low-temperature stress responses in golden pompano remains limited. Here, we firstly performed a time-series transcriptome analysis to reconstruct dynamic response patterns under low-temperature stress in golden pompano. Transcriptome profiling identified common differentially expressed genes (DEGs), including fos, hlf, and hmgb1, as well as condition-specific DEGs across distinct low-temperature stress groups. Based on cluster analysis, all DEGs were classified into five distinct expression patterns, reflecting diversified regulation of expression in golden pompano during low-temperature stress. Furthermore, condition-specific regulatory modules were explored via weighted gene co-expression network analysis (WGCNA), highlighting that the two module hub genes, serbf2 and lipc, might respond to low-temperature stress by regulating the lipid catabolic process. Subsequently, untargeted metabolomic analysis revealed that glycerophospholipid metabolism was a significantly enriched common pathway, highlighting its crucial role in mediating the response to low-temperature stress. Finally, by integrating transcriptomic and metabolomic analyses, a gene-metabolite interaction network associated with glycerophospholipid metabolism under low-temperature stress was established. These findings underscore the significance of multiple candidate genes and glycerophospholipid metabolism in golden pompano's response to low-temperature stress, thereby laying a solid molecular foundation for the development of low-temperature-tolerant fish strains.

Animals↗

PubMed2026

Sex- and development-specific transcriptomic profiling of venom and silk genes in the wolf spider Pardosa astrigera provides insights into ecological adaptation and predatory strategies.

Spider venom and silk glands are two major secretory systems that contribute to prey capture, defense, and reproduction, but their sex- and development-specific molecular regulation in wandering wolf spiders remains poorly understood. Here, the transcriptome of Pardosa astrigera, an important agricultural natural enemy in China, revealed significant sex- and development-associated molecular differentiation among adult females, adult males, and spiderlings. A total of 100,025 unigenes were obtained, of which 23,852 were functionally annotated, providing a comprehensive transcriptomic resource for this species. Differential expression patterns showed marked variation among groups, with 531, 1792, and 832 DEGs detected in PAF vs PAS, PAM vs PAS, and PAF vs PAM, respectively. These genes were mainly associated with metabolic, oxidation-reduction, cuticle development, MAPK signaling, and lysosome pathways. Fifteen co-expression modules revealed distinct expression patterns. The turquoise, pink, yellow, and red modules were development-related, whereas the blue module was male-biased. Venom- and spidroin-related genes were distributed across multiple modules, suggesting coordinated regulation. Overall, 42 venom peptides, 21 venom proteins, and 11 spidroins were identified. Representative genes showed strongly biased expression, including spiderling-biased U3_Pp1a and U5_Pp1e, female-biased U4_Pp1a, and male-biased SMase D_108750 and PaTuSp_108466. These findings reveal sex- and development-biased expression patterns of venom- and silk-related candidate genes in P. astrigera and may provide molecular insights into ecological adaptation and predatory strategies in wandering wolf spiders.

Animals↗

PubMed2026

Transcriptomics reveals species-specific adaptive strategies to calorie restriction in two Argopecten scallops with distinct lifespans.

Calorie restriction (CR) is a well-established non-genetic intervention for lifespan extension in multiple model organisms. Seasonal food shortage in cold and temperate seas may mimic CR, inducing in bivalves a response similar to that in vertebrates and thereby prolonging life expectancy. However, the relationship and the mechanism underlying the food availability and lifespan in bivalves remain largely unexplored. Two closely related scallop species the short-lived warm-water Argopecten irradians (lifespan <2 years) and the longer-lived cold-water Argopecten purpuratus (7-10 years) provide an ideal comparative system to investigate species-specific adaptive strategies. In this study, we subjected both species to CR for 30 and 56 days and performed comparative transcriptomic profiling, weighted gene co-expression network analysis (WGCNA), and physiological assays to elucidate their distinct molecular responses. Transcriptomic analysis revealed that A. purpuratus exhibited substantially more DEGs than A. irradians at both time points under CR, with both species showing downregulation of metabolic pathways but to different extents. A. irradians mounted an early nutrient-sensing response at 30 days (IGF1R, PIK3R3, INSR suppression), indicating acute sensitivity to limitation; by contrast, A. purpuratus displayed delayed FoxO activation at 56 days, along with its downstream effectors NFKBIA, CREB3L4, and SMAD4, suggesting a gradual adaptive program may link to its extended lifespan. WGCNA identified three negatively correlated modules in each species, with coral2 being the most prominent in A. irradians and darkolivegreen in A. purpuratus. The former was dominated by ciliary motility genes, whereas the latter featured coordinated repression of oxidative phosphorylation. Additionally, both species exhibited conserved suppression of mTOR/S6K growth signaling and activation of cellular maintenance programs. Collectively, these findings expand the understanding of CR-mediated longevity regulation in bivalves and provide candidate gene resources for future functional studies and breeding programs.

Pectinidae↗

PubMed2026

Multi-omics analysis reveals coordinated epigenetic dysregulation in atrazine-induced dopaminergic neurotoxicity.

Atrazine (ATR), a widely used triazine herbicide, has been linked to neurotoxicity, yet the epigenetic mechanisms underlying its dopaminergic effects remain unclear. This study investigated whether coordinated miRNA dysregulation and DNA methylation alterations contribute to ATR-induced Parkinson's disease (PD)-like neurotoxicity. Male Sprague-Dawley rats were administered ATR (50 mg/kg/day) for 90 days, resulting in motor and cognitive deficits with dopaminergic dysfunction, including increased α-synuclein and reduced tyrosine hydroxylase expression. Small RNA sequencing identified 72 differentially expressed miRNAs in the substantia nigra, enriched in PI3K-Akt, MAPK, and Ras signaling pathways. In a cohort of six PD patients and six matched controls, genome-wide DNA methylation profiling revealed 4694 differentially methylated positions, predominantly hypomethylated, with overlapping enrichment in neuronal signaling pathways. Weighted gene co-expression network analysis identified a PD-associated module strongly correlated with disease status (r = -0.95, P < 0.001). Multi-omics integration identified CASP3 as a central hub gene. External validation supported CASP3 relevance in PD (AUC = 0.833), and molecular docking suggested potential ATR-CASP3 interaction. Further analysis predicted upregulated miR-3552 as a potential upstream regulator of CASP3. These findings indicate that ATR-induced neurotoxicity may be mediated through the miR-3552/CASP3 signaling axis, ultimately regulating apoptosis and contributing to neurodegeneration.

Animals↗

PubMed2026

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2026

A dual-dimensional CRISPR toolkit enables one-step high-efficiency multiplex genome editing in Komagataella phaffii.

Against the backdrop of green biomanufacturing, engineering methanol-utilizing Komagataella phaffii (K. phaffii) represents an effective strategy to expand the one carbon (C1) product profile and speed up the industrialization of C1-based bioeconomy. To address the technical challenges of low efficiency and cumbersome experimental procedures for multiplex gene editing and precise large-fragment integration during the reconstruction of complex metabolic pathways in K. phaffii, this study established a CRISPR toolkit - Efficient Multi-Gene Editing System 3.0 (EMGES 3.0) - which enabled one-step large-fragment integration coupled with multiplex gene knockout. EMGES 3.0 was constructed through the synergistic optimization of a repair-engineered chassis and an episomal CRISPR vector. For chassis engineering, five DNA repair modules: Δlig4 (DNA Ligase IV, non-homologous end joining end ligation), ppMRE11(The endogenous MRE11 gene from Pichia pastoris) overexpression (The Meiotic Recombination 11, DNA double-strand break end resection), Δrad9 (Radiation-Sensitive 9, DNA damage checkpoint regulation), Δmph1 (Mutator Phenotype Helicase 1, improvement of homologous recombinant strand extension), and PapRecT-PaSSB co-expression (stabilization of recombination intermediates) were integrated to generate the highly recombinogenic strain Y09. For vector engineering, cenARS was replaced by panARS and the endogenous promoter PGAP was employed to drive the double hammerhead ribozyme-single guide RNA-hepatitis delta virus ribozyme (double HH-sgRNA-HDV: dHgH)-mediated sgRNA expression, yielding the optimized vector Nov_pGAP_panARS_pLAT1_Cas9. These two features on K. phaffii together enhanced the EMGES 3.0 to a higher standard of transformation rate and editing efficiency. According to our results, EMGES 3.0 achieved dual-functional gene knockout efficiencies between 76.6% and 100%. For insertion of medium-long fragments (>4.5 kb), the efficiency achieved 93.3%. In addition, the one-step integration of ultra-long fragments (>16 kb) achieved 14.8%, which was reported for the first time. Furthermore, the efficiency of simultaneous long-fragment integration at three neutral loci reached 38.4% (>15 kb). We applied the system for one-step production of free fatty acids (FFAs, yield: 5.82 ∼ 7.30 mg/L/OD600) and resveratrol (yield: 1.14 ∼ 1.28 mg/L) using methanol as the sole carbon source. EMGES 3.0 provides a robust technical foundation for complex compounds biosynthesis and high-yield industrial strains, while also advancing K. phaffii as an industrial synthetic biology chassis for efficient C1 utilization.

CRISPR-Cas Systems↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗

PubMed2026

New insights into diagnostic values and mechanisms of ferroptosis associated with immune infiltration in diabetic kidney disease.

The pathogenesis of diabetic kidney disease (DKD) is complex and closely related to ferroptosis and immune dysregulation, but the relevance is unclear. The present study investigates the potential mechanisms of ferroptosis-related genes (FRGs) in DKD and their relationship with the immune-inflammatory response. It searches for new diagnostic biomarkers to help diagnose and treat DKD. Four Gene Expression Omnibus (GEO) datasets, GSE30528, GSE30529 and GSE30122 as the test set, and GSE96804 for validation, were analyzed. FRGs were obtained from GeneCards, and 47 ferroptosis-related differentially expressed genes (FRDEGs) were identified by intersecting with DKD-related differentially expressed genes. Functional enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment Analysis and Gene Set Variation Analysis, revealed that these FRDEGs are primarily associated with ferroptosis, hypoxia response and immune inflammation. Subsequently, the weighted gene co-expression network analysis (WGCNA) was employed to expand the ferroptosis-related gene network, and intersection of the 47 FRDEGs with key WGCNA module genes yielded 10 key genes. Based on the 10 key genes, the least absolute shrinkage and selection operator and support vector machine algorithms identified three hub genes [chemokine ligand 5 (CCL5), forkhead box C1 (FOXC1) and lactotransferrin (LTF)] for DKD diagnosis. Receiver operating characteristic curves confirmed their diagnostic value, with FOXC1 and LTF validated in the independent dataset. Immune infiltration analysis via CIBERSORT revealed eight immune cell types with significantly different infiltration levels between the DKD and control group in the integrated GEO datasets. Notably, both LTF and CCL5 showed a significant positive correlation with gamma delta T cells (γδT). Quantitative PCR results confirmed differential expression of the three hub genes in the DKD group, with elevated expression observed in DKD mice following intervention with rosiglitazone and hyperoside.

bioinformatics analysis↗