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PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Epigenetic Reprogramming and Zygotic Genome Activation in Human Preimplantation Development: Mechanisms, Models, and Translational Prospects.

PURPOSE: Early human embryogenesis unfolds through a tightly coupled sequence of events-clearance of maternal transcripts, remodeling of parental chromatin, zygotic genome activation (ZGA), lineage segregation, implantation, and post-implantation patterning-accompanied by epigenetic reprogramming, including X-chromosome dosage compensation around the time of implantation. This review aims to synthesize recent advances in understanding this developmental program and to consider their implications for reproductive medicine. METHODS: I review recent literature on human early embryogenesis, with particular emphasis on findings enabled by single-cell genomics and stem-cell-based embryo modeling, and integrate these insights to identify human-specific features of early development. RESULTS: These approaches have made previously inaccessible aspects of human early embryogenesis experimentally tractable, revealing molecular and epigenetic features that distinguish human development from that of model organisms, including species-specific dynamics of ZGA, maternal transcript clearance, chromatin reprogramming, and X-chromosome dosage compensation. CONCLUSIONS: Advances in single-cell genomics and embryo modeling are transforming our understanding of human early embryogenesis. Building on these insights, while recognizing their current limitations, I propose a vision for improving reproductive medicine, including the potential for next-generation embryo selection strategies.

Journal Article↗

PubMed2026

ScRNA-seq analysis reveals the effects of nitrite stress on the endocrine system of the eyestalk in Litopenaeus vannamei.

Nitrite is a harmful substance generated in Litopenaeus vannamei farming systems, largely originating from the inadequate breakdown of surplus feed and shrimp feces. Its accumulation in the water can affect the growth and physiological functions of shrimp, damage the immune system, and even cause mass mortality, thus becoming a key environmental factor restricting the green development of the industry. Under nitrite stress, the eyestalk, as an important neuroendocrine regulatory center in crustaceans, participates in the stress adaptation of the organism and exerts a protective effect by regulating energy metabolism and immune function. However, the molecular regulatory mechanism of the eyestalk in response to nitrite stress remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) technology was used to analyze the heterogeneity of eyestalk cells in L. vannamei under nitrite stress. A total of 18, 394 high-quality cells were obtained, and six major cell subpopulations, including Neurosecretory cell, Motor neuron, Sensory neuron, Interneuron, Neurogliocyte, and Support cell, were identified. Differential expression analysis identified 839 differentially expressed genes, and different cell types showed distinct specific responses to nitrite stress. Functional enrichment analysis indicated that pathways such as glycolysis, oxidative phosphorylation, ribosome function, and endoplasmic reticulum protein processing were significantly activated, while signal transduction and DNA repair-related pathways were inhibited. Further analysis revealed that nitrite stress could induce mitochondrial function changes and trigger oxidative stress, thereby affecting the neuroendocrine system function of the eyestalk. This study provided insights into transcriptomic responses of the eyestalk to nitrite stress at the single-cell level, laying a theoretical foundation for the management of aquaculture environments.

Animals↗

PubMed2026

Regulatory Evolution and the Genetic Basis of Human Brain Expansion.

The evolution of the human brain is characterized by profound changes in structure and function, despite relatively limited divergence in protein-coding genes compared to other primates. This paradox has led to increasing recognition of gene regulatory elements (GREs) as primary drivers of evolutionary innovation. In this review, we synthesize current knowledge on the role of conserved noncoding elements (CNEs), human accelerated regions (HARs), and transposable element (TE)-derived sequences in shaping gene regulatory networks (GRNs) underlying brain development. Comparative analyses across humans and closely related primates, including the chimpanzee, gorilla, and orangutan, reveal that while core regulatory architectures are highly conserved, subtle changes in regulatory elements drive species-specific gene expression patterns. We highlight how CNEs provide a stable regulatory framework, whereas HARs and TE-derived elements introduce lineage-specific modifications that fine-tune neurodevelopmental processes. Advances in functional genomics, including CRISPR-based perturbations, massively parallel reporter assays, and single-cell multi-omics, have enabled direct interrogation of regulatory function, linking sequence variation to cellular phenotypes. Furthermore, we discuss how regulatory evolution contributes to both cognitive innovation and susceptibility to neurological disorders. Despite significant progress, challenges remain in establishing causal relationships between regulatory variation and phenotypic outcomes. Future integration of multi-omics data and comparative models will be essential for resolving these complexities. Together, this review provides a comprehensive framework for understanding the molecular basis of primate brain evolution through the lens of gene regulation.

Brain evolution↗

PubMed2026

Diversification of yeast proteins as an approach for the development of sustainable food systems.

Despite growing trend in sustainable protein sources, yeast proteins have mainly been explored as a source of bioactive peptides using a monospecies and general protein approach. The contribution of highly abundant protein fractions in the yeast proteome to peptide formation remains insufficiently investigated, limiting a comprehensive understanding of yeast proteins as optimized peptide sources. The current review presents a systematic analysis of yeast proteins as emerging protein sources and evaluates the suitability of high-abundance proteins as bioactive peptide precursors by in silico techniques. Moreover, brewery by-product and single-cell yeast protein approaches are compared in terms of composition and techno-functionality whereas peptide formation mechanisms (in situ and ex situ) and regulatory aspects for food applications are also addressed. Cytoplasmic metabolic proteins, particularly glycolytic enzymes (GAPDH), are identified as highly abundant fractions of the yeast proteome. Proteins associated with cell and organelle membranes also contribute substantially based on cellular localization. These findings imply that such proteins may act as key precursors of yeast-derived bioactive peptides. In silico hydrolysis with Alcalase suggests a tendency toward the generation of short-chain peptides (3-11/14 aa), which may support biological activity. Moreover, peptide profiles appear to vary across yeast species, highlighting the role of species diversity in peptide generation. While single-cell yeast protein allows more controlled production than brewery by-products, nucleic acid content in both may limit applications. Overall, yeast proteins appear to be metabolically adaptable and species-diverse sources for various biological peptides.

Saccharomyces cerevisiae↗

PubMed2026

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans↗

PubMed2026

High-Content CRISPR Screening: Methods and Applications.

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screening has become a central technology in functional genomics, enabling genome-scale interrogation via pooled perturbations. Early CRISPR screens employed survival or simple phenotypic readouts to identify essential genes and drug resistance mechanisms. However, as biological questions have shifted toward understanding regulatory networks, cellular heterogeneity, and context-dependent gene functions, there has been increasing demand for screening strategies capable of capturing complex cellular phenotypes beyond cell fitness. Recent advances in single-cell sequencing, high-content imaging, and spatial transcriptomics have expanded the resolution of CRISPR screening by enabling multidimensional phenotypic characterization following genetic perturbation. By integrating pooled perturbations with diverse readouts, these approaches systematically map targeted gene edits to transcriptional states, cellular phenotypes, and microenvironmental contexts. Meanwhile, innovations in library design, delivery, and computational pipelines have further improved the robustness and interpretability of high-content screening platforms. This review synthesizes the methodological evolution of CRISPR screening, emphasizing advances in perturbation strategies, delivery systems, and multimodal readouts. Representative applications spanning oncology, immunotherapy, developmental biology, neurobiology, and infectious diseases are delineated to demonstrate refined gene network annotations. Additionally, existing technical bottlenecks, such as scalability, cost constraints, and in vivo limitations, are critically assessed. Finally, future directions are proposed to facilitate the development of precise medicine.

CRISPR screening↗

PubMed2026

Tumor-Intrinsic Blood and Imaging Correlatives in Advanced Prostate Cancer Treated with Combination Radiopharmaceutical Therapy and Immunotherapy.

The PRINCE trial showed the clinical activity for 177Lu-PSMA-617 in combination with pembrolizumab for metastatic castration-resistant prostate cancer. To refine patient selection and improve response monitoring strategies to this combination, we investigated candidate tumor-intrinsic biomarkers of treatment response and resistance. Methods: We performed circulating tumor DNA (ctDNA), circulating tumor cell (CTC), and PET imaging analyses at baseline, 12 wk on-treatment, and disease progression in participants enrolled in PRINCE (n = 37). We performed targeted sequencing for ctDNA quantification and genomic analysis of more than 70 prostate cancer genes. CTC enumeration was performed on the EpicSciences platform and was combined with selective single-cell whole-genome sequencing. PET imaging included serial PSMA PET as well as 18F-FDG PET imaging at baseline. Results: A low baseline ctDNA fraction and high PSMA avidity in metastatic lesions were linked to superior treatment responses and may have composite biomarker value. Genomic alterations in tumor suppressor genes TP53, RB1, or PTEN were associated with higher 18F-FDG avidity and metabolic tumor volume on 18F-FDG PET imaging and worse prognosis. At 12-wk on-treatment, both ctDNA detection and PSMA PET imaging were strong indicators of response depth and durability. At disease progression, PSMA expression on PET imaging was lower compared with baseline and supported by subclonal remodeling of ctDNA and CTC copy number profiles and by clonal expansions of tumor suppressor gene mutations. Conclusion: We provide the first integrated molecular and imaging insights into determinants of response and resistance to combined radiopharmaceutical therapy and immunotherapy in prostate cancer and propose biomarker strategies to inform future clinical development.

177Lu-PSMA-617↗

PubMed2026

Identifying fate-determining transcription factors with single-cell omics.

Single-cell sequencing enables the systematic discovery of cell fate-determining transcription factors (TFs), or key TFs, that define cellular identity or drive cell state transitions. A wide range of computational methods have been developed for this goal, but they differ substantially in the input data and the biological questions they address. In this article, we systematically review computational approaches for key TF identification and organize them from three perspectives: whether they identify TFs defining cell state identity or driving state transitions, whether transitions are modeled as discrete or continuous processes, and whether TFs act individually or combinatorially. We summarize key features and application scenarios of relevant methods to guide tool selection and discuss emerging trends in this field toward programmable and active control of cell fate.

Transcription Factors↗

PubMed2026

CTCF aligns single-cell TAD-like domain boundaries and stabilizes long-range active chromatin clusters.

CCCTC-binding factor (CTCF) is a key architectural protein in the three-dimensional (3D) genome, yet how its loss reshapes chromatin structure and transcription at single-cell resolution remains unclear. Using HiRES, which jointly profiles chromatin contacts and RNA from the same nucleus, we examined genome-wide effects of CTCF depletion. Topologically associating domain (TAD)-like domains (TLDs) across single cells remained largely unchanged in number and size after CTCF loss, but their boundaries became more variably positioned, and pseudobulk analyses revealed reduced interactions within A compartments. We also developed SALTAFinder to identify Spatially Aggregated Long-distance TLD Assemblies (SALTAs), clusters of TLDs occupying shared 3D space within single cells. A subset of SALTAs is enriched for highly expressed genes and super-enhancers and declines upon CTCF depletion. This structural reorganization coincided with a global reduction in per-cell RNA output, as indicated by HiRES and orthogonal measurements. Together, these findings suggest that CTCF contributes to the coordinated regulation of chromatin organization and transcriptional capacity and is associated with stabilization of long-range active chromatin clusters.

CCCTC-Binding Factor↗

PubMed2026

Deciphering CD8+ T cell exhaustion in human cancers through single-cell and spatial transcriptomics.

Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.

Humans↗

PubMed2026

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗

PubMed2026

Human Monocytic Models Reveal Genotype-Dependent Inflammatory Programs in VEXAS Syndrome.

OBJECTIVES: VEXAS syndrome is a severe X-linked autoinflammatory disorder caused by somatic mutations in ubiquitin-like modifier activating enzyme 1 (UBA1), with clinical outcomes that vary by UBA1 genotype. We aimed to elucidate genotype-specific inflammatory programs and identify potential therapeutic targets. METHODS: We conducted longitudinal deep phenotyping, including whole-blood RNA sequencing (RNA-seq) and clinical activity assessment. Peripheral blood samples were analyzed by single-cell RNA-seq. Human monocytic cell lines harboring each major UBA1 mutation (p.Met41Val, p.Met41Thr, or p.Met41Leu) were generated and subjected to transcriptomic and functional analyses. RESULTS: Thirteen patients with VEXAS syndrome contributed a total of 79 RNA-seq samples. Among genes upregulated in VEXAS syndrome, RNASE1 showed the strongest correlation with longitudinal disease activity (r = 0.70, FDR < 0.05) and was upregulated in patients' monocytes. In UBA1-mutant monocytic cell lines, genotype-dependent ubiquitination defects were observed in a graded manner (p.Met41Val > p.Met41Thr > p.Met41Leu), even in the absence of exogenous stimuli. These defects were accompanied by unfolded protein response activation, increased pro-inflammatory cytokine production, progressive cell death, and RNASE1 upregulation, all following the same graded pattern, recapitulating patient genotype-phenotype associations. Transcriptomic analyses demonstrated enrichment of pro-inflammatory, interferon, and necroptosis signatures in more severe genotypes. Notably, inhibition of receptor-interacting protein kinase 3 (RIPK3) markedly attenuated all pathological features, including RNASE1 upregulation. CONCLUSIONS: Our UBA1-mutant monocytic cell-line models, representing three distinct genotypes, recapitulate genotype-dependent inflammatory phenotypes that can be modulated by RIPK3 inhibition, providing a translational platform for mechanistic investigation and precision therapy development in VEXAS syndrome.

Journal Article↗

PubMed2026

Site-specific gene integration by recombinase-mediated cassette exchange in anhydrobiotic Pv11 cells.

Pv11 cells, derived from Polypedilum vanderplanki, uniquely tolerate complete desiccation (anhydrobiosis). Although a CRISPR/Cas9-based precise integration method (CRIS-PITCh) has been developed for Pv11 cells, a CRISPR-free strategy that fixes both the genomic locus and transgene copy number has not yet been established. Here, we implement recombinase-mediated cassette exchange (RMCE) in Pv11 cells and generate master cell lines that retain anhydrobiosis following genetic engineering. We first evaluated the activity of multiple site-specific recombinases in Pv11 cells using a transient two-plasmid reporter assay. Flp, Cre, and Bxb1 recombinases all excised a test cassette and activated a green fluorescent protein (GFP) reporter, whereas phiC31 integrase mediated recombination at the DNA sequence level but did not induce reporter expression under our construct configuration. To enable genomic RMCE, we inserted an FRT/FRT3-landing pad (LP) into a previously identified genomic safe-harbor locus using CRIS-PITCh and isolated clonal master cell lines by single-cell sorting. Using the established master line, Flp-based RMCE achieved site-specific cassette exchange at the LP, producing HaloTag fluorescence and drug resistance upon successful exchange. In addition, the expected post-exchange sequence was confirmed by sequencing. We further established an all-in-one RMCE vector combining the Flp recombinase and donor cassette on a single plasmid. Together, these results demonstrate locus-defined, single-copy transgene integration in anhydrobiotic Pv11 cells via RMCE and provide a standardized, CRISPR-free workflow for routine genetic manipulation in this unique cell line. This workflow facilitates both fundamental research and applied biotechnological applications using desiccation-tolerant cells.

Anhydrobiosis↗

PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗

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

ARX mutation-associated interneuron defects provide insights into mechanisms underlying developmental epilepsies.

Cortical interneuron (cIN) dysfunction is associated with various neurodevelopmental and neurological disorders, including developmental epilepsies, autism spectrum disorders and intellectual disabilities. Mutations in ARX (aristaless-related homeobox) are linked to these conditions, with or without accompanying structural brain anomalies. We previously demonstrated that the loss of Arx in the mouse ganglionic eminence, the birthplace of cINs, is associated with seizures, whereas its loss in cortical excitatory neuron progenitor cells results in structural anomalies but no seizures. To elucidate the pathophysiological role of ARX in cINs and its relationship to seizure phenotype, Arx conditional mutant mouse lines were investigated using Gad2- and Nkx2.1-Cre drivers to target distinct populations in the cIN lineage. Our data demonstrate that ARX abrogation results in defects in cIN density and distribution, as well as perinatal lethality. In these mice, we observed defects in cell cycle exit, a biased loss of the marginal zone migration stream of cINs, shifts in cell fate from caudal ganglionic eminence to medial ganglionic eminence identity, and a reduced number of parvalbumin⁺ and somatostatin⁺ cINs, with parvalbumin⁺ cINs being more severely affected. Single-cell RNA sequencing combined with chromatin immunoprecipitation and sequencing revealed that ARX regulates key processes involved in cell cycle progression, cIN subtype differentiation and cIN migration. Investigation of one downregulated target gene, Lmo1, uncovered a potential mechanism by which ARX regulates the number and distribution of cINs in the cortex. Cortical slice cultures demonstrate that LMO1 inhibits cIN migration by repressing Cxcr4 expression, which encodes a key receptor involved in cortical guidance. These data indicate that ARX positively regulates cIN migration by derepressing LMO1's repressive role. Consistent with our mouse model, we observed a significant loss of parvalbumin+ and somatostatin+ cINs in the brain of a patient carrying a pathogenic variant of ARX, who was diagnosed with developmental epileptic encephalopathy. Together, our data provide novel insights into how ARX and its target genes regulate cIN development and migration and into the pathogenic mechanisms underlying a spectrum of neurodevelopmental disorders linked to loss of ARX.

Animals↗

PubMed2026

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗