Abstract Primary aldosteronism (PA), also known as Conn’s syndrome or adrenal aldosterone producing adenoma (APA), is predominantly caused by functional adrenal tumors and is a common cause of secondary hypertension. The KCNJ5 gene mutations are frequently associated with APA, leading to increased aldosterone production. This study investigates the effect of KCNJ5 mutations on CYP11A1 and the aldosterone biosynthesis pathway. We created two model cell lines by introducing homozygous p.L168R and p.G151R mutations in the KCNJ5 gene to SW13 cell line using CRISPR/Cas9 technology. The mutations were verified succeed through Sanger sequencing and multi-omics analysis. Aldosterone and its biosynthesis intermediates were quantitatively analyzed, and the expression of CYP11A1 mRNA in wild-type and mutant cell lines was detected through qPCR. Increased concentrations of aldosterone, pregnenolone, progesterone, and corticosterone in the KCNJ5 mutated cell lines were observed compared to the wild type, while cholesterol levels remained unchanged. qPCR results showed increased CYP11A1 mRNA expression in KCNJ5 mutant cells. Therefore, KCNJ5 mutations promote aldosterone synthesis by enhancing CYP11A1 activity, which catalyzes the conversion of cholesterol to pregnenolone, a critical step in the aldosterone biosynthesis pathway. This study highlights the potential of CYP11A1 as a therapeutic target for treating APA-induced secondary hypertension.

Corynebacterium ulcerans is an emerging zoonotic pathogen that can cause diphtheria-like infections in humans. In this study, we report the novel detection and comprehensive phenotypic and genomic characterization of three atoxigenic C. ulcerans strains isolated from domestic animals in Brazil. Notably, all isolates belonged to the multilocus sequence type ST-339, which has been previously identified in both human and animal hosts from geographically distant regions, suggesting the potential for international dissemination. Whole-genome sequencing confirmed species identity and revealed high genetic simila-rity among isolates, although distinct phylogenetic subclades were observed. Genomic analyses identified conserved virulence-associated determinants, including incomplete pilus gene clusters, iron acquisition systems, and the pld gene encoding phospholipase D. In contrast, the tox gene was absent in all strains. Notably, one isolate exhibited ciproflo-xacin resistance associated with double mutations (S89L and D93G) in the quinolone- resistance-determining region of GyrA. Molecular modeling and dynamics simulations demonstrated that these mutations impair key interactions within the ciprofloxacin– magnesium–water complex, thereby compromising the stability of drug binding. Additionally, the presence of diverse mobile genetic elements, prophages, and CRISPR-Cas systems highlighted the genomic plasticity of these isolates. Our findings provide new insights into the zoonotic potential, antimicrobial resistance mechanisms, and genomic diversity of C. ulcerans, underscoring the need for strengthened surveillance and mole-cular monitoring of this emerging pathogen in both veterinary and public health contexts.

Summary Polyamines are essential and evolutionarily conserved metabolites present at millimolar concentrations in mammalian cells. Cells tightly regulate polyamine homeostasis through complex feedback mechanisms, yet the precise role necessitating this regulation remains unclear. Here, we show that polyamines function as endogenous buffers of redox-active iron, providing a molecular link between polyamine metabolism and ferroptosis. Using genome-wide CRISPR screens, we identified a synthetic lethal dependency between polyamine depletion and the key ferroptosis suppressor, GPX4. Mechanistically, we show that polyamine deficiency triggers a redistribution of cellular iron, increasing the labile iron pool and upregulating ferritin. To directly visualize this iron buffering in living cells, we developed a genetically encoded fluorescent reporter for redox-active iron. Live-cell analysis revealed a striking inverse correlation between intracellular polyamine levels and redox-active iron at single-cell resolution. These findings reposition polyamines as key regulators of iron homeostasis, with implications for ferroptosis-linked disease states and cellular redox balance.

ABSTRACT Mosaic analysis has been instrumental in advancing developmental and cell biology. Most current mosaic techniques rely on exogenous site-specific recombination sequences that need to be introduced into the genome, limiting their application. Mosaic analysis by gRNA-induced crossing-over (MAGIC) was recently developed in Drosophila to eliminate this requirement by inducing somatic recombination through CRISPR/Cas9-generated DNA double-strand breaks. However, MAGIC has not been widely adopted because gRNA-markers, a required component for this technique, are not yet available for most chromosomes. Here, we present a complete, genome-wide gRNA-marker kit that incorporates optimized designs for enhanced clone induction and more effective clone labeling in both positive MAGIC (pMAGIC) and negative MAGIC (nMAGIC). With this kit, we demonstrate clonal analysis in a broad range of Drosophila tissues, including cell types that have been difficult to analyze using recombinase-based systems. Notably, MAGIC enables clonal analysis of pericentromeric genes and deficiency chromosomes and in interspecific hybrid animals, opening new avenues for gene function study, rapid gene discovery, and understanding cellular basis of speciation. This MAGIC kit complements existing systems and makes mosaic analysis accessible to address a wider range of biological questions.

Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emerged as the core pathway to safeguard food security. As the world’s fourth-largest food crop, soybean (Glycine max) possesses multiple strategic values for food security, livestock feed, and industrial raw materials, thanks to its high protein content (accounting for over 40% of the dry weight of seeds) and oil resource attributes. However, the soybean industry is confronted with multiple challenges: the long cycle of genetic breeding (8-10 years required by traditional methods), annual losses from diseases and pests reaching 40% (data from FAO 2023), and the reliance on empirical decision-making in field management, all of which urgently call for intelligent solutions.At present, agricultural knowledge is experiencing explosive growth - more than 4,000 new soybean-related literatures are added annually in PubMed, and agricultural technology Q&A platforms (Zhihu, Baidu Tieba, etc.) generate over 3,000 daily questions. However, this multi-source heterogeneous knowledge is scattered in books, literatures, Q&A communities, and gene databases, lacking systematic integration, resulting in a knowledge utilization rate of less than 30%. In response to this, this paper proposes the “Fengshu-Agri” large model, an agricultural knowledge integration and innovation engine based on the collaboration of Retrieval-Augmented Generation (RAG) and Knowledge Graph (KG). The model achieves breakthroughs through the following core technological innovations: Deep integration of multi-source heterogeneous data: For the first time, a systematic integration of 256 agricultural monographs (covering standardized knowledge such as planting techniques and pest control), 66,772 cutting-edge research literatures (genomics, agronomic trait analysis, etc.), 880,000 production practice Q&A (covering scenarios such as pest diagnosis and environmental stress response), and 120,000 gene annotation data (functional genes, expression regulation mechanisms) has been carried out to construct the largest knowledge graph in the agricultural field - containing 2 million entity nodes, realizing full-chain knowledge modeling from molecular-level gene regulation to field management. Double-layer collaborative retrieval mechanism: Innovatively integrating RAG semantic vector retrieval with KG structured reasoning to solve problems such as low recall rate (<65%) and semantic ambiguity in traditional systems. Specifically, it achieves dual matching through local keywords (entity-level) and global keywords (relationship-level); Optimization of domain-specific generation engine: Based on the QWEN-QWQ32B large language model, a three-stage fine-tuning is carried out (pre-training, agricultural instruction fine-tuning, and reinforcement learning from human feedback) [15], which improves the professionalism of generated texts by 35% (manual evaluation index) and significantly reduces the LLM hallucination problem [12]. Experimental results show that Fengshu-Agri achieves an accuracy rate of 89.6% in soybean knowledge retrieval tasks (a 25.4% improvement over traditional RAG models), a recall rate of 87.3% (20.5% higher than pure KG reasoning models), and an F1 score of 88.4%. It can efficiently answer complex questions involving multi-entity associations (such as “the impact mechanism of CRISPR-editing the GmSWEET gene on lepidopteran pest resistance”). Analysis of typical cases indicates that the model’s responses not only cover technical principles (sgRNA design, Agrobacterium transformation procedures) but also integrate metabolomics data (70% improvement in insect resistance with no significant yield reduction), demonstrating cross-modal knowledge fusion capabilities. In the future, this model will be expanded to crops such as maize and potato to construct an agricultural intelligent ecosystem covering the entire process of cultivation management and breeding improvement, promoting the upgrading of precision agriculture toward a data-driven model.

The CRISPR–Cas9 system has become a widely used tool for genome engineering. Here we present a new method for small-molecule control of CRISPR-Cas9 using bio-orthogonal chemistry between tetrazine (Tz) and trans -cyclooctene (TCO). We carried out molecular modeling studies and identified a unique position on single guide RNA (sgRNA) that can be site-specifically tagged with Tz without disrupting its activity. We also synthesized a series of TCO-modified CRISPR suppressors. When exogenously added, they click to the Tz-tagged sgRNA, perturb the system and drastically reduce the nuclease activity. The most successful suppressor is a TCO-modified six amino acid long cell-penetrating peptide, which shows excellent cell permeability. We showed that out method to control CRISPR-Cas9 nuclease activity is general by applying it to three different sgRNAs. We also showed that our method works in solution, as well as live HEL293 cells. We utilized flow cytometry to demonstrate temporal control of CRISPR-Cas9 targeting GFP. Lastly, we showed the therapeutic potential of our method by targeting vascular endothelial growth factor A (VEGFA).

Type III CRISPR systems typically generate cyclic oligoadenylate (cOA) second messengers such as cyclic tetra-adenylate (cA 4 ) on detection of foreign RNA, activating ancillary effector proteins which elicit a diverse range of immune responses. The CalpLTS system elicits a transcriptional response to infection when CalpL binds cA 4 in its SAVED (SMODS associated and fused to various effectors domain) sensor domain, resulting in filament formation and activation of the Lon protease domain, which cleaves the anti-Sigma factor CalpT, releasing the CalpS Sigma factor for transcriptional remodelling. Here, we show that thermophilic viruses have appropriated the SAVED domain of CalpL as an anti-CRISPR, AcrIII-2, which they use to degrade cA 4 . AcrIII-2 dimers sandwich cA 4 , degrading it in a shared active site to short linear products, using a mechanism highly reminiscent of CalpL. This results in inhibition of a range of cA 4 activated effectors in vitro . This is the first example of a virally-encoded SAVED domain with ring nuclease activity, highlighting the complex interplay between viruses and cellular defences.

Extracellular vesicles (EVs) are emerging as versatile mediators of intercellular communication and promising tools for drug discovery and targeted therapies. These lipid bilayer-bound nanovesicles facilitate the transfer of functional proteins, RNAs, lipids, and other biomolecules between cells, thereby influencing various physiological and pathological processes. This review outlines the molecular mechanisms governing EV biogenesis and cargo sorting, emphasizing the role of regulators, such as ubiquitin-like 3 (UBL3), in modulating protein packaging. We explored the critical involvement of EVs in various disease microenvironments, including cancer progression, neurodegeneration, and immune modulation. Their ability to cross biological barriers and deliver bio-active cargo renders them highly attractive for precise drug delivery systems, especially in neurological and oncological disorders. Moreover, this review highlights advances in engineering EVs for delivering RNA therapeutics, CRISPR-Cas systems, and targeted small molecules. The utility of EVs as diagnostic tools in liquid biopsies and their integration into personalized medicine and companion diagnostics were also discussed. Patient-derived EVs offer dynamic insights into disease state and enable real-time treatment stratification. Despite their potential, challenges such as scalable isolation, cargo heterogeneity, and regulatory ambiguity remain significant hurdles. We also reported novel pharmacological approaches targeting EV biogenesis, secretion, and uptake pathways, and considered UBL3 as a promising drug target for EV cargo modulation. Future directions include the standardization of EV analytics, scalable biomanufacturing, and classification of EV-based therapeutics under evolving regulatory frameworks. This review emphasizes the multifaceted roles of EVs and their transformative potential as therapeutic platforms and biomarker reservoirs in next-generation precision medicine.

Gliomas, particularly aggressive glioblastoma (GBM), pose significant therapeutic challenges due to limited understanding of their single-cell drivers. Here, we integrate large glioma genetic data with brain multi-omics (bulk and single-cell) to identify causal genes and their cell-type-specific roles. We prioritize 11 high-confidence and 47 potential causal genes; 41 are novel associations. Analyses suggest most of these 58 genes are druggable, supported by CRISPR/RNAi screens showing essentiality/dependency for 53.7% novel candidates in glioma cell lines. Single-cell data identifies astrocytes and oligodendrocyte precursor cells (OPCs) as likely GBM cells-of-origin and reveals increased tumor microenvironment (TME) communication involving neurons. We uncover 14 cell-type-specific causal gene effects, including EGFR in astrocytes, CDKN2A in OPCs, and JAK1 in excitatory neurons. Notably, 85.7% effects occur in non-risk populations (glial and neural), highlighting complex interplays. This study provides critical cell-resolved insights into glioma susceptibility mechanisms and identifies potential therapeutic targets within complex intratumoral interactions, advancing targeted precision therapies.

The "dark genome," comprising pseudogenes and various non-coding DNA elements, has historically been overlooked due to the assumption of its non-functionality. Recent advances in genomics and epigenetics have overturned this view, revealing that these sequences play crucial roles in genetic regulation, development, disease, and evolution. Pseudogenes, once dismissed as evolutionary relics, are now recognized for their regulatory potential via RNA interference, decoy functions, and epigenetic modulation. Non-coding regions such as long non-coding RNAs (lncRNAs), enhancer RNAs (eRNAs), and other untranslated elements contribute to transcriptional control and chromatin architecture. This review explores the biological functions of these components, their implications in health and disease, and their growing relevance in biomedical research. Furthermore, we examine how emerging technologies such as single-cell sequencing, CRISPR-based editing, and integrative multi-omics are shedding light on the regulatory functions of the dark genome. Despite significant progress, many challenges persist, including functional validation, annotation inconsistency, and interpretation of non-coding variants. This paper aims to synthesize current findings, highlight biomedical applications, discuss limitations, and propose future research directions, emphasizing the need to embrace the dark genome for a more comprehensive understanding of gene regulation and genome complexity.

Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes and underscored the value of GI maps for functional genomics. To advance efforts toward a reference human GI network, we developed the q uantitative G enetic I nteraction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in isogenic human cell lines. We found surprising systematic variation unrelated to genetic interactions in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging ∼40 control screens and half a billion differential fitness effect measurements, we developed a CRISPR screen data processing and normalization pipeline to correct these artifacts and measure accurate, quantitative GIs. Finally, we comprehensively characterized GI reproducibility by recording 4 – 5 biological replicates for ∼125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.

Modern gene-synthesis platforms let us probe protein function and genome biology at unprecedented scale. Yet in large, diverse gene libraries the proportion of error-free constructs decreases with length due to the propagation of oligo synthesis errors. To rescue these rare, error-free molecules we developed BAR-CAT (Barcode-Assisted Retrieval CRISPR-Activated Targeting), an in-vitro enrichment method that couples unique PAM-adjacent 20-nt barcodes to each library member and uses multiplexed dCas9-sgRNA complexes to fish out the barcodes corresponding to perfect assemblies. After a single 15-min reaction and optimized wash regime (BAR-CAT v1.0), three low-abundance targets in a 300, 000-member test library were enriched 600-fold, greatly reducing downstream requirements. When applied to 384x and 1, 536x member DropSynth gene libraries, BAR-CAT retrieved up to 122-fold enrichment for 12 targets and revealed practical limits imposed by sgRNA competition and library complexity, which now guide ongoing protocol scaling. By eliminating laborious clone-by-clone validation and working directly on plasmid libraries, BAR-CAT provides a versatile platform for recovering perfect synthetic genes, subsetting large libraries, and ultimately lowering the cost of functional genomics at scale.

The impact of genotype on gene expression can depend on both cellular and organismal context. Here, we leverage an extensive blood atlas of genotyped patients with varying severity of infection produced by the COVID-19 Multi-omics Blood ATlas (COMBAT) Consortium to study the role of genetic regulation on gene expression in a context-specific manner. We analyzed single-cell transcriptomic and genome-wide genetic data from ∼500,000 cells and 76 donors of European ancestry. Across 15 cell types, we identified 2,607 independent cis-eQTLs in high linkage disequilibrium (R2>0.8) with 48 infectious and 386 inflammatory disease-associated risk variants, including rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). Notably, we found infection-specific eQTLs absent from a general population dataset (OneK1K), such as REL , IRF5 and TRAF , all of which were differentially regulated by infection and whose variants are associated with RA and/or IBD. We also identified infection-modified eQTLs, including RPS26 and ADAM10 , implying that the regulatory sequences context of these genes may play a role in specific immune cell subsets in infection. Our work demonstrates that the overriding effect of genetics on gene expression in blood immune cells is independent of infection status or severity. However, small numbers of eQTLs are modified by infection, and these differences can illustrate potentially important immune biology.

CRISPR homing gene drive holds great potential for pest control, but its success is challenged by the generation of resistance alleles. To mitigate the impact of resistance, multiplexed gRNA strategies have been demonstrated. However, unless both outmost sites are cleaved simultaneously, poor homology during DNA repair may compromise efficiency, leading to decline in drive conversion efficiency when the number of gRNAs is higher than two. Here, to better estimate the rate of drive efficiency decline, we designed and assessed the efficiency of single gRNA drives with imperfect homologous arms, refining a detailed gRNA multiplexing model. To mitigate the greater than expected efficiency loss, we further evaluated two new strategies: (1) extended homology arms to span all target sites with mutations in the PAMs and (2) a population-level multiplexing gRNAs system involving two or more drives, each carrying two gRNAs. Specifically, the population-level multiplexing system has four adjacent gRNA target sites, and the drives have small mutations in their homologous arms to prevent cleavage by the other drive. Mutations in both strategies did not impair efficiency, but they were not consistently inherited, and undesired cutting in the homologous arms decreased drive efficiency. We simulated homing suppression drive using a dual 2-gRNA population-level gRNA multiple xing strategy based on our experimental evaluation. Despite being somewhat more vulnerable to functional resistance than a standard 4-gRNA drive, the higher individual drive efficiency of the population-level multiplexing system increased successful population elimination outcomes. Thus, population-level multiplexing can be a useful for improving suppression drive power.

Plants rely on specialised sensing systems, including transcriptional regulators, to maintain iron (Fe) homeostasis. Among these, Hemerythrin RING Zinc finger (HRZ) proteins have emerged as key regulators of Fe homeostasis. In this study, six wheat HRZ homoeologs TaHRZ1 and TaHRZ2 were identified from rice HRZ sequences and mapped to chromosomes 1 and 3. These encode proteins with conserved N-terminal Hemerythrin (HHE) domains and C-terminal CHY-RING and Zn-ribbon motifs. Phylogenetic analysis grouped these genes into distinct clades, while expression profiling revealed strong root-specific and Fe-responsive expression patterns, indicating roles in nutrient sensing. Functional conservation was demonstrated by complementation of the Arabidopsis bts-1 mutant, where both wheat genes restored normal Fe regulation. Full-length TaHRZ1 and TaHRZ2 interacted with members of wheat bHLH IVc transcription factors, while truncated versions lacking the RING domain did not, emphasising their conserved role in protein interactions. CRISPR-Cas9 editing of the conserved HHE3 domain in all the TaHRZ1 homoeologs, coupled with GRF4-GIF1 chimeric protein, achieved ∼9% regeneration efficiency in wheat cultivar C306. Grain ICP-MS analysis indicated enhanced iron loading in the edited lines, particularly in the scutellum, suggesting improved iron partitioning compared to the wild type. Additionally, qRT-PCR revealed upregulation of FIT and IRO3 , and downregulation of IDEF1 in edited lines, supporting a central role for TaHRZ1 in Fe homeostasis signalling. These findings position TaHRZ1 as a valuable target for biofortification strategies to enhance Fe content in wheat grains.

CRISPR-based nucleic acid diagnostics are a promising class of point-of-care tools that could dramatically improve healthcare outcomes for millions worldwide. However, these diagnostics require nucleic acid pre-amplification, an additional step that complicates deployment to low resource settings. Here, we developed CATNAP ( Ca s t rans - n uclease detection of a mplified p roducts), a method that integrates isothermal linear DNA amplification with Cas12a detection in a single reaction. CATNAP uses a nicking enzyme and DNA polymerase to continuously generate single-stranded DNA, activating Cas12a’s trans -cleavage activity without damaging the template. We optimized enzyme combinations, buffer conditions, and target selection to achieve high catalytic efficiency. CATNAP successfully distinguished between high- and low-risk HPV strains and detects HPV-16 in a cervical cancer crude cell lysate at room temperature with minimal equipment, offering advantages over PCR-based approaches. We conclude that CATNAP bridges the sensitivity gap in CRISPR diagnostics while maintaining simplicity, making accurate disease detection more accessible in resource-limited settings.

Triple-negative breast cancer (TNBC) is a highly aggressive subtype, accounting for 10–15% of breast cancer cases in the United States. Liver metastases, common in advanced TNBC, are linked to especially poor outcomes, with a 5-year survival rate of just 11%. Although immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 show promise, durable responses in TNBC remain uncommon. This is largely due to a profoundly immunosuppressive tumor microenvironment (TME), driven by tumor-associated myeloid cells. Tumor-associated macrophages (TAMs) and neutrophils (TANs) polarize into immunosuppressive M2 and N2 phenotypes, respectively, suppressing T cell activity through cytokines, ROS, and checkpoint ligands such as VISTA. Myeloid-derived suppressor cells (MDSCs) further inhibit immunity by depleting nutrients and inducing regulatory T cells. As a result, despite its immunogenic features, TNBC remains resistant to immunotherapy due to persistent myeloid-mediated suppression. Here, we developed ionizable lipid nanoparticles (iLNPs) engineered to deliver the CRISPR-Cas12a ribonuclease complex targeting Rictor, a critical component of mTORC2, for in vivo reprograming of myeloid cells. The intravenous (IV) injection of CRISPR Rictor-targeting iLNP (CR-Ric-LNP) showed efficient uptake by circulating myeloid cells and accumulation into the breast cancer liver metastases. Notably, Rictor gene editing triggered pro-inflammatory activation of myeloid cells in the TME, enhancing antitumor responses. Single-cell RNA sequencing revealed that Rictor silencing treated samples showed induced rapid remodeling of the TME, with a significant reduction in immunosuppressive macrophages within 24 hours of treatment. Concurrently, cytotoxic T-cell populations exhibited increased interferon-gamma ( Ifng ) production, driving the emergence of specific myeloid clusters that were responsive to Interferon signaling, particularly in macrophages and neutrophils. A shift from an immunosuppressive to an inflammatory TME was further evidenced by an elevated Cxcl10/Spp1 ratio in myeloid cells. CR-Ric-LNP treatment also enhanced T-cell activation, reducing exhausted T cells and regulatory T cells (Tregs) while expanding natural killer (NK) cells, naïve CD4+, and CD8+ T cells. These changes correlated with a decreased proportion of tumor cells and proliferating cells, ultimately leading to a significant survival benefit in a 4T1 breast cancer liver metastasis model. Our findings demonstrate that myeloid-targeted Rictor silencing reprograms the TME, promoting antitumor immunity and improving therapeutic outcomes.

Summary Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest malignancies, exemplifies a paradox of transcriptional plasticity and rigidity: it displays dynamic transcriptional states yet retains a stable classical epithelial identity, which resists therapeutic intervention. This rigidity reflects robust transcriptional memory, but the underlying mechanisms remain poorly understood. While the master transcription factors OCT4, SOX2, KLF4, and MYC (OSKM) can reprogram normal cells by erasing lineage identity, reprogramming in solid tumors such as PDAC is inefficient, with reprogrammed cells retaining features of their malignant origin—suggesting the presence of active epigenetic barriers. Long noncoding RNAs (lncRNAs) regulate chromatin state and cell identity, but whether they actively enforce cancer-specific transcriptional memory and restrict reprogramming remains largely unexplored. Herein, through CRISPR interference screens targeting cancer-associated lncRNAs, we identified a subset of cancer-associated lncRNAs whose depletion significantly enhanced OSKM-mediated reprogramming in PDAC cells. Knockdown of these lncRNAs enabled the acquisition of pluripotency-associated features, suppressed PDAC identity programs, and reduced tumorigenicity in vivo. Among the most potent repressors of reprogramming were ATXN7L3-AS1, INTS4P2, and AC079921.2, which were upregulated in PDAC but minimally expressed in normal pancreas. ATXN7L3-AS1 and AC079921.2 were associated with mitotic progression and extracellular matrix organization gene programs, respectively, and showed anticorrelation with translational and metabolic gene signatures across TCGA cancer cohorts. These findings uncover a previously unrecognized role for cancer-associated lncRNAs as key enforcers of transcriptional memory in PDAC. By stabilizing malignant identity and opposing reprogramming, these lncRNAs may represent a novel class of epigenetic regulators. Targeting them offers a conceptual and therapeutic framework for erasing cancer cell memory, resetting epigenetic state, and exposing latent vulnerabilities in PDAC.

RNA-based/associated biosensors represent a rapidly expanding area of research, providing highly sensitive tools for detecting and monitoring RNA in diverse biological contexts. These sensors offer the ability to track RNA localization, modifications, and interactions in real-time, making them particularly well-suited for developmental biology research. Despite their demonstrated utility in fields such as diagnostics, synthetic biology and environmental science, the application of RNA biosensors in developmental biology has only begun to emerge within the past decade. This gap is notable given the potential of these tools to address key questions about spatiotemporal RNA regulation and cellular signaling during development. This perspective review presents a selection of RNA biosensors, including fluorescent RNA aptamers, CRISPR-Cas-based systems, riboswitches, and catalytic RNA sensors, which have gained attraction in other scientific disciplines. These tools can be used not only to study intrinsic RNA biology, such as RNA expression, splicing, and localization, but also to detect the effects of extrinsic physical and chemical factors, including pH, temperature, redox state, and mechanical stress, on RNA behavior during developmental processes. These examples illustrate how RNA biosensors could be adapted to study developmental mechanisms in model organisms, enabling investigations into RNA dynamics and their role in shaping developmental processes. By revisiting these underutilized tools, this review highlights their relevance for advancing the understanding of molecular mechanisms in developmental biology studies.

Hypoxia within the tumor microenvironment poses a major barrier to the efficacy of NK cell-based immunotherapies for solid tumors. In this study, we investigated the influence of hypoxia on NK cell function and mitochondria. We found that hypoxia reduced NK cell cytotoxicity, mitochondrial content, and membrane potential, while increasing mtROS and inducing broad transcriptional changes in metabolic and stress response pathways. CAR engineering with CD70 and IL-15, while designed to enhance persistence and metabolic fitness, did not prevent hypoxia-induced impairment. Given the mitochondrial disruption, we then explored whether DRP1 ablation could mitigate hypoxia-induced dysfunction. Pharmacological inhibition of DRP1 restored mitochondrial content and cytotoxic function. To confirm the role of DRP1, we generated CRISPR-Cas9-mediated DRP1 KO NK cells, which preserved mitochondrial load and membrane potential under hypoxia. When armed with CD70-CAR-IL-15, DRP1 KO cells retained cytotoxic activity under hypoxic conditions. These findings show that DRP1 inactivation can support NK cell function in hypoxic environments, and that metabolic engineering may enhance CAR NK cell efficacy in solid tumors. Graphical abstract NK cells become dysfunctional in hypoxic conditions, while DRP1 KO NK cells retain their function.

Urinary small extracellular vesicles (sEVs), which can reflect systemic conditions, hold great promise for non-invasive cancer diagnostics, yet the mechanism by which tumor-derived sEVs reach urine remains unclear. Here, we demonstrate that the glomerulus actively transcytoses circulating tumor-derived sEVs into urine. Using CRISPR gRNA-tagged glioma sEVs and bioluminescent/fluorescent GeNL-tagged lung and pancreatic cancer sEVs, we tracked their journey from tumors to urine in multiple mouse models. In vivo and in vitro analyses revealed endocytic uptake and transcytotic release by glomerular cells, accompanied by changes in sEV size and surface composition. GeNL-tagged sEVs consistently showed higher signals in urine than plasma, indicating selective excretion. These findings redefine the glomerulus as a dynamic regulator of EV processing and establish a mechanistic foundation for urinary liquid biopsy.

Summary Calcium, as a cellular second messenger, is essential for plant growth. A tip-focused Ca 2+ gradient in polarized cells is considered to drive cell expansion. The cell wall polysaccharide pectin is a major Ca 2+ binding structure and Ca 2+ homeostasis is influenced by the cell wall architecture. LRR-extensin (LRX) proteins are extracellular regulators of cell wall development that are anchored in the cell wall by their extensin domain. The extensin-less LRX1ΔE14 variant of the root hair-expressed LRX1 of Arabidopsis induces a dominant-negative effect resulting in aberrant root hairs. In an effort to identify the underlying mechanism of the root hair defect caused by LRX1ΔE14 , we isolated a su ppressor of dominant- ne gative effect mutant, sune42 . It codes for the CATION CALCIUM EXCHANGER 4 (CCX4) that localizes to the Golgi apparatus and was shown to have Ca 2+ transport activity. A detailed investigation of the Ca 2+ dynamics revealed that LRX1ΔE14 coincides with a defect in tip-focused cytoplasmic Ca 2+ oscillation, and this effect is alleviated by the sune42 mutation. Additionally, reducing Ca 2+ availability influences the LRX1ΔE14 -induced root hair defect. We conclude that sune42 suppresses the root hair defect in LRX1ΔE14 through modulating cytoplasmic Ca 2+ dynamics, pointing at the importance of the Golgi apparatus for cellular Ca 2+ homeostasis.

Anaplastic thyroid cancer (ATC) is the most aggressive form of thyroid cancer. Despite recent advances in treating BRAFV600E-driven ATC, therapy resistance remains a significant challenge, often resulting in disease progression and death. Leveraging a focused CRISPR/KO screen in parallel with a CRISPR/activation screen, both tailored on response to BRAFV600E inhibitor treatment, we identified TAZ (encoded by the WWTR1 gene) deficiency as synthetically lethal with BRAF inhibitor in ATC. TAZ is overexpressed in ATC compared to well-differentiated thyroid tumors. We demonstrate that TAZ-deficient ATC cells display heightened sensitivity to BRAF inhibitors both in vitro and in vivo . Using gene essentiality score across a large panel of cancer cell lines, we found that BRAFV600E-driven cancers are highly sensitive to TAZ loss, unlike their counterparts with wild-type BRAF and non-BRAFV600E. Mechanistically, we demonstrate that dabrafenib triggers the Unfolded Protein Response (UPR) under ER stress and suppresses protein synthesis. TAZ loss represses the UPR, reverses the inhibition of protein synthesis, and triggers increased cell death by ferroptosis in dabrafenib-treated ATC. Collectively, our findings unveil TAZ as a new target to overcome resistance to BRAF inhibitors in undifferentiated thyroid cancer.

Abstract We performed a comprehensive meta-analysis of four major medical innovations (2015–2025) CRISPR gene editing, mRNA vaccines, AI diagnostics, and telemedicine focusing on clinical efficacy, health outcomes, and adoption. For CRISPR therapies in hemoglobinopathies, pooled data from six trials (115 patients) show robust clinical benefits: significant fetal hemoglobin induction, transfusion independence in β-thalassemia, and reduced sickle crises【1,2】. mRNA COVID-19 vaccines exhibited extremely high efficacy; pooled vaccine effectiveness was ~96% (95% CI 93–98%) after two doses【3】, far exceeding traditional platforms. AI diagnostic tools demonstrated moderate accuracy: a meta-analysis of 83 studies found mean diagnostic accuracy ~52% statistically comparable to physicians overall (no significant difference) but lower than expert clinicians【4】. Telemedicine interventions produced modest but positive effects: in a meta-review of 33 RCTs, telemedicine outcomes were at least as good as usual care (Cohen’s d≈0.21) across diverse conditions【5】. Notably, telehealth adoption surged during COVID-19 (e.g. a 683% increase in tele-visits at one center【6】). Comparative analysis indicates mRNA vaccines delivered the largest population-level impact (via prevention of disease), while CRISPR offers potentially curative benefits in niche populations. AI and telemedicine have improved diagnostic and care delivery processes with varying effect sizes. Our findings underscore each innovation’s significant but distinct contribution to global health.

Abstract Leishmania is a protozoan parasite causing leishmaniasis, a disease affecting millions globally. It is transmitted through bites from infected sand-flies, primarily of the Phlebotomus spp. or Lutzomyia spp. The parasite has two main life stages: the promastigote, found in the insect vector, and the amastigote, residing in the macrophages of the host. The mechanisms behind stage differentiation are not well understood. This study shows that redox metabolism modulations are crucial for the life cycle of Leishmania infantum, influencing stage transitions. Inhibiting redox metabolism caused significant morphological changes, from flagellated promastigotes to amastigote-like forms. These changes were evidenced by transcriptomic and metabolomic analyses. RNA sequencing indicated that redox inhibition affected several genes, including one for an iron transporter, LINF_310039600. Using CRISPR-Cas9, knockout mutants of this gene were created, revealing upregulation of amastin, a marker of the amastigote form, underscoring the role of redox metabolism in stage differentiation.