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PubMed2005

Transcriptome analysis of zebrafish embryogenesis using microarrays.

Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html).

Journal Article↗

PubMed2005

The agony and ecstasy of "OMIC" technologies in drug development.

Over the last decade we have witnessed a fundamental change in how biomedical research is carried out and we can now assess the impact of the Human Genome Project on drug discovery and development. Advances in "omics" technologies (genomics, transcriptomics, proteomics and metabonomics) were touted as having the potential to revolutionize our approach to disease diagnosis, prognostication and development of novel therapeutics. However, the promise of rapid advances in medicine "from the lab bench to the bedside" has not manifested as of yet. Indeed it appears that the translational applications of genomic-based research have preceded the development of both (i) a conceptual framework for disease understanding and (ii) effective tools that can exploit the vast amounts of data derived from these efforts. In reality great progress has been made, however understanding processes such as disease progression (or drug response) requires systematic insight into dynamic (and temporal) differences in gene regulation, interaction and function. This review will discuss "omic" technologies with the emphasis upon advances in our understanding of the human genome derived transcriptome (RNA), and its proteome (proteins), while focusing upon the translation of this information into the drug development paradigm.

Computational Biology↗

PubMed2025

Ketone body mediated histone β-hydroxybutyrylation is reno-protective.

Starvation, intermittent fasting and exercise, all of which are recommended lifestyle modifiers share a common metabolic signature, ketogenesis to generate the ketone bodies, predominantly β-hydroxybutyrate. β-hydroxybutyrate exerts beneficial effects across various contexts, preventing or mitigating disease. We hypothesized that these dynamic health benefits of β-hydroxybutyrate might stem from its ability to regulate genome architecture through chromatin remodeling via histone β-hydroxybutyrylation, thereby influencing the transcriptome. Focusing on the kidney, which is an end organ protected by β-hydroxybutyrate, we examined histone β-hydroxybutyrylation-mediated chromatin remodeling. Notably, regions of the genome associated with lipid catabolism were predominantly in an open chromatin configuration, leading to active transcription and translation. Significant β-hydroxybutyrylation was observed in the kidneys and the most highly upregulated gene actively transcribed and translated was 3-hydroxy-3-methyglutaryl CoA Synthase 2 (Hmgcs2), a gene responsible for the biosynthesis of β-hydroxybutyrate in mitochondria. In contrast, regions with more compact chromatin structures were enriched with genes related to immune function such as protein tyrosine phosphatase receptor type C (Ptprc) and lymphocyte cytosolic protein 1 (Lcp1), which exhibited reduced transcription and translation. These results reveal that renal epigenetic histone β-hydroxybutyrylation is a novel mechanism by which transcriptional regulation of both energy metabolism and immune function occur concomitantly to protect kidneys and lower hypertension.

Blood pressure↗

PubMed2006

Modulation of gene expression and cytoskeletal dynamics by the amyloid precursor protein intracellular domain (AICD).

Amyloidogenic processing of the amyloid precursor protein (APP) results in the generation of beta-amyloid, the main constituent of Alzheimer plaques, and the APP intracellular domain (AICD). Recently, it has been demonstrated that AICD has transactivation potential; however, the targets of AICD-dependent gene regulation and hence the physiological role of AICD remain largely unknown. We analyzed transcriptome changes during AICD-dependent gene regulation by using a human neural cell culture system inducible for expression of AICD, its coactivator FE65, or the combination of both. Induction of AICD was associated with increased expression of genes with known function in the organization and dynamics of the actin cytoskeleton, including alpha2-Actin and Transgelin (SM22). AICD target genes were also found to be differentially regulated in the frontal cortex of Alzheimer's disease patients compared with controls as well as in AICD/FE65 transiently transfected murine cortical neurons. Confocal image analysis of neural cells and cortical neurons expressing both AICD and FE65 confirmed pronounced changes in the organization of the actin cytoskeleton, including the destabilization of actin fibers and clumping of actin at the sites of cellular outgrowth. Our data point to a role of AICD in developmental and injury-related cytoskeletal dynamics in the nervous system.

Actins↗

PubMed2006

Resources for integrative systems biology: from data through databases to networks and dynamic system models.

In systems biology, biologically relevant quantitative modelling of physiological processes requires the integration of experimental data from diverse sources. Recent developments in high-throughput methodologies enable the analysis of the transcriptome, proteome, interactome, metabolome and phenome on a previously unprecedented scale, thus contributing to the deluge of experimental data held in numerous public databases. In this review, we describe some of the databases and simulation tools that are relevant to systems biology and discuss a number of key issues affecting data integration and the challenges these pose to systems-level research.

Animals↗

PubMed2025

Innovative strategies for mitochondrial dysfunction in myeloproliferative neoplasms a step toward precision medicine.

Myeloproliferative neoplasms (MPNs) are clonal disorders of hematopoietic stem cells characterized by aberrant proliferation of myeloid lineages, driven primarily by mutations in JAK2, CALR, and myeloproliferative leukemia, leading to constitutive activation of the JAK-STAT pathway. Emerging evidence highlights mitochondrial dysfunction as a key factor in MPN pathogenesis, contributing to increased reactive oxygen species production, mitochondrial DNA mutations, and dysregulated mitochondrial dynamics, which collectively promote clonal expansion and apoptosis resistance. Targeting mitochondrial pathways has gained attention as a therapeutic strategy, with approaches including mitochondria-targeted antioxidants, metabolic inhibitors, and modulation of mitophagy and mitochondrial fission/fusion dynamics. However, challenges such as drug delivery specificity, therapeutic resistance, and off-target effects remain significant. Recent advances in precision medicine, incorporating genomic, transcriptomic, and proteomic profiling, offer a more personalized approach to MPN treatment by tailoring interventions to individual mutation patterns. Additionally, novel therapeutic strategies, including gene editing technologies, RNA-based therapies, and nanoparticle-mediated drug delivery systems, hold promise for overcoming current treatment limitations. The integration of artificial intelligence in drug discovery and biomarker identification further enhances the potential for targeted therapies. Future research should focus on refining these strategies, developing reliable biomarkers for patient stratification, and exploring combination therapies that enhance treatment efficacy while minimizing adverse effects. By addressing mitochondrial dysfunction as an underlying driver of MPNs, these emerging approaches have the potential to improve disease management, extend patient survival, and enhance quality of life. Also, this new approach of precision medicine allows patient stratification and ensures that treatments are formed according to the individual disease biology of each patient, which results in overall better outcomes.

combination drug therapy↗

PubMed2026

Unveiling tumor heterogeneity by single cell RNA-sequencing: From basic considerations to clinical applications.

Tumor heterogeneity-encompassing diverse cellular phenotypes, genomic alterations, and microenvironmental contexts-is a principal barrier to effective cancer therapy. Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve this complexity by capturing transcriptomes at single-cell resolution. Here, we review the technical foundations required for high-quality scRNA-seq studies. We then trace the evolution of scRNA-seq platforms from manual micromanipulation to high-throughput systems, and describe the computational pipelines that enable reliable data interpretation. The application of scRNA-seq is exemplarily shown in the context of lung cancer, where single-cell profiling has revealed (i) the clonal and sub-clonal architecture of tumors, (ii) extensive remodeling of the immune microenvironment, iii) key mechanisms underlying resistance to targeted agents and immune-checkpoint blockade, and (iv) the dynamics of neo-antigen-specific T-cell responses. Integrating machine-learning techniques-such as deep-learning classifiers and graph-based models-with single-cell transcriptomic data has markedly sped up biomarker discovery, produced more accurate risk-stratification scores, and enabled the generation of patient-specific therapeutic predictions. We surveyed the major trial registry ClinicalTrials.gov and identified ∼380 ongoing or completed studies that explicitly incorporate scRNA-seq as a correlative or pharmacodynamic endpoint. Overall, the analysis shows that scRNA-seq becomes an increasingly important component of modern trials, providing high-resolution cellular and molecular readouts that complement conventional imaging and bulk-omics endpoints. While key challenges remain, ranging from costs, scalability and need for rigorous validation before routine clinical deployment, ongoing technological advances continue to expand the potential of scRNA-seq as a cornerstone of precision medicine.

Humans↗

PubMed2005

Nocturnal changes in leaf growth of Populus deltoides are controlled by cytoplasmic growth.

Growing leaves do not expand at a constant rate but exhibit pronounced diel growth rhythms. However, the mechanisms giving rise to distinct diel growth dynamics in different species are still largely unknown. As a first step towards identifying genes controlling rate and timing of leaf growth, we analysed the transcriptomes of rapidly expanding and fully expanded leaves of Populus deltoides Bartr. ex. Marsh at points of high and low expansion at night. Tissues with well defined temporal growth rates were harvested using an online growth-monitoring system based on a digital image sequence processing method developed for quantitative mapping of dicot leaf growth. Unlike plants studied previously, leaf growth in P. deltoides was characterised by lack of a base-tip gradient across the lamina, and by maximal and minimal growth at dusk and dawn, respectively. Microarray analysis revealed that the nocturnal decline in growth coincided with a concerted down-regulation of ribosomal protein genes, indicating deceleration of cytoplasmic growth. In a subsequent time-course experiment, Northern blotting and real-time RT-PCR confirmed that the ribosomal protein gene RPL12 and a cell-cycle gene H2B were down-regulated after midnight following a decrease in cellular carbohydrate concentrations. Thus, we propose that the spatio-temporal growth pattern in leaves of P. deltoides primarily arises from cytoplasmic growth whose activity increases from afternoon to midnight and thereafter decreases in this species.

Carbohydrate Metabolism↗

PubMed2026

Spatiotemporal mapping of tertiary lymphoid structure heterogeneity shapes immune niches and clinical outcomes in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy with limited therapeutic options. The spatial architecture and functional diversity of tertiary lymphoid structures (TLSs) in iCCA remain unclear. Here, we present a multimodal spatial atlas of TLSs and identified intratumoral TLSs (iTLSs) as independent prognostic markers. Bulk proteomic profiling of 214 discovery and 155 validation cases identified a four-tier TLS-based tumor microenvironment classification system and supported development of a TLS-predictive random forest classifier. Imaging mass cytometry revealed that iTLS+ tumors harbor structured immune architectures, where M1-like tissue-resident macrophages (RTMs), dendritic cells, and CXCL13+ CD4+ T cells colocalize to form antigen-presenting neighborhoods (apc-CNs) spatially coupled to TLS core regions (TLScore-CNs). Single-cell spatial transcriptomics further resolved 61 TLSs into 14 spatial niches and defined a pseudotemporal maturation continuum: aggregated, activated, and postactivated. Intraniche communication, primarily mediated by ifnCAFs, iCAFs, and CXCL12+ macrophages, evolved dynamically with maturation. Single-nucleus RNA sequencing combined with Tangram-based spatial mapping revealed CXCL12+ macrophages and iCAFs forming a peripheral band in aggregated TLSs, whereas ifnCAFs infiltrated TLS interiors during activation. These findings define TLS heterogeneity and provide insights for stroma-directed immunotherapy.

Cholangiocarcinoma↗

PubMed2024

Comparative transcriptomics of Venus flytrap (Dionaea muscipula) across stages of prey capture and digestion.

The Venus flytrap, Dionaea muscipula, is perhaps the world's best-known botanical carnivore. The act of prey capture and digestion along with its rapidly closing, charismatic traps make this species a compelling model for studying the evolution and fundamental biology of carnivorous plants. There is a growing body of research on the genome, transcriptome, and digestome of Dionaea muscipula, but surprisingly limited information on changes in trap transcript abundance over time since feeding. Here we present the results of a comparative transcriptomics project exploring the transcriptomic changes across seven timepoints in a 72-hour time series of prey digestion and three timepoints directly comparing triggered traps with and without prey items. We document a dynamic response to prey capture including changes in abundance of transcripts with Gene Ontology (GO) annotations related to digestion and nutrient uptake. Comparisons of traps with and without prey documented 174 significantly differentially expressed genes at 1 hour after triggering and 151 genes with significantly different abundances at 24 hours. Approximately 50% of annotated protein-coding genes in Venus flytrap genome exhibit change (10041 of 21135) in transcript abundance following prey capture. Whereas peak abundance for most of these genes was observed within 3 hours, an expression cluster of 3009 genes exhibited continuously increasing abundance over the 72-hour sampling period, and transcript for these genes with GO annotation terms including both catabolism and nutrient transport may continue to accumulate beyond 72 hours.

Droseraceae↗

PubMed2005

Comprehensive regional and temporal gene expression profiling of the rat brain during the first 24 h after experimental stroke identifies dynamic ischemia-induced gene expression patterns, and reveals a biphasic activation of genes in surviving tissue.

In order to identify biological processes relevant for cell death and survival in the brain following stroke, the postischemic brain transcriptome was studied by a large-scale cDNA array analysis of three peri-infarct brain regions at eight time points during the first 24 h of reperfusion following middle cerebral artery occlusion in the rat. K-means cluster analysis revealed two distinct biphasic gene expression patterns that contained 44 genes (including 18 immediate early genes), involved in cell signaling and plasticity (i.e. MAP2K7, Sprouty2, Irs-2, Homer1, GPRC5B, Grasp). The first gene induction phase occurred at 0-3 h of reperfusion, and the second at 9-15 h, and was validated by in situ hybridization. Four gene clusters displayed a progressive increase in expression over time and included 50 genes linked to cell motility, lipid synthesis and trafficking (i.e. ApoD, NPC1, G3P-dehydrogenase1, and Choline kinase) or cell death-regulating genes such as mitochondrial CLIC. We conclude that a biphasic transcriptional up-regulation of the brain-derived neurotrophic factor (BDNF)-G-protein coupled receptor (GPCR)-mitogen-activated protein (MAP) kinase signaling pathways occurs in surviving tissue, concomitant with a progressive and persistent activation of cell proliferation signifying tissue regeneration, which provide the means for cell survival and postischemic brain plasticity.

Animals↗

PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗

PubMed2026

The DLX/Notch axis is necessary for spatiotemporal regulation of neural cell fate.

Neuronal-glial cell fate switch during forebrain development is highly regulated. DLX transcription factors are necessary for promoting GABAergic interneuron differentiation and migration but the mechanisms for concomitant repression of glial fate in neural progenitors remain elusive. Here, the DLX2 regulatory network dynamic in the developing ventral telencephalon is characterised using a multi-omic approach at single-cell resolution, including single-cell whole genome spatial transcriptomics. We identify a secondary proliferative zone in the ventral subventricular zone and spatiotemporal-context dependent Notch pathway repression by DLX2 in maintaining progenitor populations and facilitating neural differentiation. We find that DLX2 controls cell fate determination by directly repressing Notch signalling genes as well as glial fate-promoting transcription factors, thereby inhibiting early adoption of oligodendroglial differentiation during neurogenesis. Here, we show that temporal cell fate switch is mediated by DLX2 via a multilayer gene regulatory network, redefining current understanding of neuronal-glial cell specification mechanisms in the developing telencephalon.

Animals↗

PubMed2003

An ancestral secretory apparatus in the protozoan parasite Giardia intestinalis.

The protozoan parasite Giardia intestinalis belongs to one of the earliest diverged eukaryotic lineages. This is also reflected in a simple intracellular organization, as Giardia lacks common subcellular compartments such as mitochondria, peroxisomes, and apparently also a Golgi apparatus. During encystation, developmentally regulated formation of large secretory compartments containing cyst wall material occurs. Despite the lack of any morphological similarities, these encystation-specific vesicles (ESVs) show several biochemical characteristics of maturing Golgi cisternae. Previous studies suggested that Golgi structure and function are induced only during encystation in Giardia, giving rise to the hypothesis that ESVs, as a Giardia Golgi equivalent, are generated de novo. Alternatively, ESV compartments could be built on the template structure of a cryptic Golgi in trophozoites in response to ER export of cyst wall material during encystation. We addressed this question by defining the molecular framework of the Giardia secretory apparatus using a comparative genomic approach. Analysis of the corresponding transcriptome during growth and encystation revealed surprisingly little stage-specific regulation. A panel of antibodies was generated against selected marker proteins to investigate the developmental dynamics of the endomembrane system. We show evidence that Giardia accommodates the export of large amounts of cyst wall material through re-organization of membrane compartment(s) in trophozoites with biochemical similarities to ESVs. This suggests that ESVs are selectively stabilized Golgi-like compartments in a unique and archetypical secretory system, which arise from a structural template in trophozoites rather than being generated de novo.

Animals↗

PubMed2026

Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

BACKGROUND: Predicting enterocutaneous fistula (ECF)-associated sepsis and mortality poses significant challenges in digital health care due to the disease's complexity and heterogeneous clinical manifestations. Current approaches that rely on single-modal data or traditional scoring systems often fail to capture the intricate immune-inflammatory dynamics and multisystem involvement in patients with ECF. OBJECTIVE: This study aims to develop an artificial intelligence (AI)-driven multimodal fusion model integrating clinical, imaging, and transcriptomic data for early prediction of ECF-associated sepsis and 28-day mortality, addressing the limitations of conventional single-dimensional models. METHODS: This study leveraged publicly available datasets (Medical Information Mart for Intensive Care III [MIMIC-III], electronic Intensive Care Unit [eICU], and The Cancer Genome Atlas) to construct a multimodal framework. Clinical parameters were processed using Extreme Gradient Boosting, abdominal imaging features were extracted via convolutional neural networks, and transcriptomic profiles were analyzed with variational autoencoders. A Transformer-based fusion network was employed for joint prediction and validated through cross-validation and external testing. Key features were identified using Shapley Additive Explanations and Local Interpretable Model-Agnostic Explanations interpretability algorithms, while immune regulatory mechanisms were explored via weighted gene co-expression network analysis. RESULTS: The multimodal model achieved an area under the curve (AUC) of 0.89 for predicting sepsis and 28-day mortality, outperforming unimodal models (clinical-only model, AUC 0.72, and imaging-only model, AUC 0.78). Critical predictors included Sequential Organ Failure Assessment score, lactate levels, intra-abdominal free fluid on imaging, and immunoregulatory genes (programmed death-ligand 1 [PD-L1] and indoleamine 2,3-dioxygenase 1 [IDO1]). Mechanistic analysis revealed distinct immune reprogramming in patients with sepsis, characterized by increased regulatory T cells and M2 macrophages, along with downregulated cluster of differentiation 8+ (CD8+) T cells. CONCLUSIONS: This multimodal AI model offers an innovative digital solution in medical informatics, enabling precise early risk stratification for ECF-associated sepsis. By integrating multisource data and providing interpretable insights into immune-inflammatory pathways, the model enhances health care quality for patients with ECF and paves the way for personalized intervention strategies.

Humans↗

PubMed2025

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and approaches have been introduced for studying nerve injury and regeneration. This review highlights the application and progress of multi-omics in uncovering the mechanisms of nerve injury, guiding the development of regenerative strategies, and promoting clinical translation. By integrating multi-omics datasets, researchers can comprehensively track dynamic molecular changes following nerve injury, including abnormal gene expression, disrupted protein signaling, altered metabolic programs, and shifts in the immune microenvironment. Single-cell multi-omics technologies resolve cellular heterogeneity, revealing the distinct functions of neurons, glial cells, and immune cell subpopulations during the injury response. Spatially resolved transcriptomics maintain the spatial context of lesion and regeneration sites, enabling precise localization for targeted interventions. Multi-omics technologies not only identify key molecular players involved in nerve regeneration but also create opportunities for personalized medicine. Nonetheless, integrating multi-omics data poses technical challenges, including high dimensionality, batch effects, and algorithmic constraints, while ethical concerns related to stem cell therapy and gene editing require stringent oversight. To transition from structural reconstruction to functional remodeling, future research should emphasize artificial intelligence-driven data integration, organ-on-a-chip modeling, and cross-disciplinary collaboration to overcome existing technical barriers and accelerate the clinical application of neuroregenerative therapies.

artificial intelligence↗

PubMed2026

Virus-mediated fate of antimicrobial resistance genes in livestock manure anaerobic digestion.

Antimicrobial resistance (AMR) poses a critical global health challenge, with livestock manure acting as a significant environmental reservoir for antimicrobial resistance genes (ARGs). Anaerobic digestion (AD) is a pivotal process for mitigating ARG dissemination at the livestock-environment-human interface. This study aims to elucidate the global dynamics of ARGs in AD systems, focusing on virus-host interactions and arms race, to identify actionable strategies for AMR control. We analyzed 205 metagenomic (4.5 Tb) and 36 meta-transcriptomic (640 Gb) datasets, including 15 newly generated datasets, revealing that pig manure AD harbors the highest ARG abundance (0.668 ARGs/16S rRNA), while AD systems generally exhibit limited transcriptional activation of ARGs. We constructed a viral dataset for livestock manure AD (GVD_LMAD), comprising 59,316 DNA and 727 RNA viral operational taxonomic units (vOTUs). Virus-host interactions established by CRISPR-Cas spacer, tRNA and homology matches revealed 889 lytic infections of antimicrobial-resistant bacteria (ARB) compared to only 18 ARG transduction events. Further analysis showed that the relative abundance of vOTUs assigned to the reduction role (4.11% ± 3.19%) was substantially higher than that of reproduction (0.72% ± 0.64%) and transduction (0.19% ± 0.30%), demonstrating that, among viral processes, lysis outweighs transduction in contributing to ARG abundance reduction in AD. Furthermore, an antiviral defense system (ADS) catalogue (GADSC_LMAD), derived from 2760 high-quality metagenome-assembled genomes (MAGs) containing 39,307 ADS, with ADS prevalence in ARB (7.8 ± 6.0 per MAG), indicating an intensified virus-host arms race in AD that may shield ARB from phage lysis. The resulting CRISPR-Cas immune network with expressed spacers targets foreign ARG-carrying sequences (primarily plasmids and ICEs), suggesting a mechanism that restricts horizontal gene transfer (HGT) via conjugation and transformation, despite shielding ARB from phage lysis. Collectively, these findings highlight that viral communities significantly contribute to ARG reduction through phage lysis relative to transduction, while the ADS-mediated arms race, despite protecting ARB, constructs a biological firewall that potentially limits HGT of ARGs. This study provides novel insights into virus-host dynamics as a key mechanism for controlling ARG dissemination in AD systems.

Animals↗

PubMed2026

Integrative analysis of transcriptome and chromatin accessibility reveals promoter-proximal regulation and identifies candidate ABC transporters associated with cold stress responses in maize.

BACKGROUND: Low-temperature stress is a formidable environmental constraint that severely limits the growth and productivity of maize (Zea mays L.), particularly during the highly vulnerable early seedling stage. While cold tolerance is a critical agronomic objective, the integrated transcriptional and epigenetic regulatory mechanisms that govern this trait remain largely elusive. Characterizing these coordinated molecular networks is fundamental to the genetic enhancement of cold resilience in maize. METHODS: Using two maize inbred lines contrasting in chilling response (ZHB12 tolerant, B73 sensitive), we performed integrative time‑course RNA‑seq and ATAC‑seq to thoroughly and systematically characterize the precise dynamic interplay between gene expression and chromatin accessibility under cold stress conditions at the seedling stage. RESULTS: Physiological assessments confirmed that ZHB12 possesses superior cold tolerance, manifested by significantly attenuated electrolyte leakage and reduced foliar damage compared to B73. Transcriptomic profiling revealed a massive, time-dependent divergence in gene expression between the two genotypes, with a major regulatory transition identified at 24 h of cold exposure. Functional enrichment analysis demonstrated that ZHB12 preferentially activates a robust defense repertoire, including Photosystem II electron transport, diterpenoid biosynthesis, and ATP biosynthetic pathways. Notably, multiple ATP-binding cassette (ABC) transporter genes were coordinately upregulated under chilling, suggesting their potential involvement in cellular homeostasis. ATAC-seq analysis indicated that cold stress is associated with chromatin remodeling in ZHB12, with increased accessibility observed in proximal promoter regions. Integrative analysis identified a core set of dual-responsive genes, in which increased promoter accessibility coincided with transcriptional upregulation. These genes were predominantly enriched in transporter activity and transcriptional regulation, suggesting potential epigenetic link to the superior stress response of ZHB12. CONCLUSION: Our findings reveal extensive transcriptional and chromatin accessibility changes in ZHB12 under cold stress. The observed associations between promoter accessibility and gene activation, particularly in genes involved in transport processes, highlight candidate regulators potentially contributing to cold tolerance. This study provides a molecular framework and identifies high-value candidate genes that may inform future efforts in breeding cold-tolerant maize, pending functional validation.

Zea mays↗