Nucleic Acids Res. 2025 Jul 8;53(13):gkaf647. doi: 10.1093/nar/gkaf647.

ABSTRACT

Recent research has indicated the presence of highly protein occupied, transcriptionally silent regions of bacterial genomes which show functional parallels to eukaryotic heterochromatin. We utilized an integrative approach to track chromatin structure and transcription in Escherichia coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors (TFs) regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 45 sRNA-TF candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB (also known as AzuCR), CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

PMID:40671525 | DOI:10.1093/nar/gkaf647

BMC Bioinformatics. 2025 Jul 16;26(1):179. doi: 10.1186/s12859-025-06186-1.

ABSTRACT

BACKGROUND: Inferring Gene Regulatory Networks (GRNs) from gene expression data is a pivotal challenge in systems biology. Most existing methods fail to consider the skewed degree distribution of genes, complicating the application of directed graph embedding methods.

RESULTS: The Cross-Attention Complex Dual Graph Embedding Model (XATGRN) was proposed to address this issue. It employs a cross-attention mechanism and a dual complex graph embedding approach to manage the skewed degree distribution, ensuring precise prediction of regulatory relationships and their directionality. The model consistently outperforms existing state-of-the-art methods across various datasets.

CONCLUSIONS: XATGRN provides an effective solution for inferring GRNs with skewed degree distribution, enhancing the understanding of complex gene regulatory mechanisms. The codes and detailed requirements have been released on Github: ( https://github.com/kikixiong/XATGRN ).

PMID:40670912 | DOI:10.1186/s12859-025-06186-1

Nature. 2025 Jul 16. doi: 10.1038/s41586-025-09240-3. Online ahead of print.

ABSTRACT

Whole-genome doubling (WGD) is a common feature of human cancers and is linked to tumour progression, drug resistance, and metastasis1-6. Here we examine the impact of WGD on somatic evolution and immune evasion at single-cell resolution in patient tumours. Using single-cell whole-genome sequencing, we analysed 70 high-grade serous ovarian cancer samples from 41 patients (30,260 tumour genomes) and observed near-ubiquitous evidence that WGD is an ongoing mutational process. WGD was associated with increased cell-cell diversity and higher rates of chromosomal missegregation and consequent micronucleation. We developed a mutation-based WGD timing method called doubleTime to delineate specific modes by which WGD can drive tumour evolution, including early fixation followed by considerable diversification, multiple parallel WGD events on a pre-existing background of copy-number diversity, and evolutionarily late WGD in small clones and individual cells. Furthermore, using matched single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signalling and cGAS-STING pathway activation result from ongoing chromosomal instability, but this is restricted to predominantly diploid tumours (WGD-low). By contrast, predominantly WGD tumours (WGD-high), despite increased missegregation, exhibited cell-cycle dysregulation, STING1 repression, and immunosuppressive phenotypic states. Together, these findings establish WGD as an ongoing mutational process that promotes evolvability and dysregulated immunity in high-grade serous ovarian cancer.

PMID:40670783 | DOI:10.1038/s41586-025-09240-3

Nat Microbiol. 2025 Jul 16. doi: 10.1038/s41564-025-02056-x. Online ahead of print.

ABSTRACT

Bifidobacteria are beneficial saccharolytic microbes that are widely used as probiotics or in synbiotic formulations, yet individual responses to supplementation can vary with strain type, microbiota composition, diet and lifestyle, underscoring the need for strain-level insights into glycan metabolism. Here we reconstructed 68 pathways for the utilization of mono-, di-, oligo- and polysaccharides by analysing the distribution of 589 curated metabolic gene functions (catabolic enzymes, transporters and transcriptional regulators) across 3,083 non-redundant Bifidobacterium genomes of human origin. Thirty-eight predicted phenotypes were validated in vitro for 30 geographically diverse strains, supporting genomics-based predictions. Our analysis uncovered extensive inter- and intraspecies functional heterogeneity, including a distinct clade within Bifidobacterium longum that metabolizes α-glucans and Bangladeshi isolates carrying unique gene clusters for xyloglucan and human milk oligosaccharide utilization. This large-scale genomic compendium advances our understanding of bifidobacterial carbohydrate metabolism and can inform the rational design of probiotic and synbiotic formulations tailored to strain-specific nutrient preferences.

PMID:40670725 | DOI:10.1038/s41564-025-02056-x

Nat Ecol Evol. 2025 Jul 16. doi: 10.1038/s41559-025-02780-x. Online ahead of print.

ABSTRACT

Bats are the only mammals capable of self-powered flight, an evolutionary innovation based on the transformation of forelimbs into wings. The bat wing is characterized by an extreme elongation of the second to fifth digits with a wing membrane called the chiropatagium connecting them. Here we investigated the developmental and cellular origin of this structure by comparing bat and mouse limbs using omics tools and single-cell analyses. Despite the substantial morphological differences between the species, we observed an overall conservation of cell populations and gene expression patterns including interdigital apoptosis. Single-cell analyses of micro-dissected embryonic chiropatagium identified a specific fibroblast population, independent of apoptosis-associated interdigital cells, as the origin of this tissue. These distal cells express a conserved gene programme including the transcription factors MEIS2 and TBX3, which are commonly known to specify and pattern the early proximal limb. Transgenic ectopic expression of MEIS2 and TBX3 in mouse distal limb cells resulted in the activation of genes expressed during wing development and phenotypic changes related to wing morphology, such as the fusion of digits. Our results elucidate fundamental molecular mechanisms of bat wing development and illustrate how drastic morphological changes can be achieved through repurposing of existing developmental programmes during evolution.

PMID:40670657 | DOI:10.1038/s41559-025-02780-x

Mol Syst Biol. 2025 Jul 16. doi: 10.1038/s44320-025-00132-2. Online ahead of print.

ABSTRACT

The activity of bacterial transcription factors (TFs) is typically modulated through direct interactions with small molecules. However, these input signals remain unknown for most TFs, even in well-studied model bacteria. Identifying these signals typically requires tedious experiments for each TF. Here, we develop a systematic workflow for the identification of TF input signals in bacteria based on metabolomics and transcriptomics data. We inferred the activity of 173 TFs from published transcriptomics data and determined the abundance of 279 metabolites across 40 matched experimental conditions in Escherichia coli. By correlating TF activities with metabolite abundances, we successfully identified previously known TF-metabolite interactions and predicted novel TF effector metabolites for 41 TFs. To validate our predictions, we conducted in vitro assays and confirmed a predicted effector metabolite for LeuO. As a result, we established a network of 80 regulatory interactions between 71 metabolites and 41 E. coli TFs. This network includes 76 novel interactions that encompass a diverse range of chemical classes and regulatory patterns, bringing us closer to a comprehensive TF regulatory network in E. coli.

PMID:40670652 | DOI:10.1038/s44320-025-00132-2

Nat Commun. 2025 Jul 16;16(1):6556. doi: 10.1038/s41467-025-61862-3.

ABSTRACT

Proper regulation of glycogen metabolism is fundamental to cellular energy homeostasis, and its disruption is associated with various metabolic disorders, including glycogen storage diseases (GSDs) and potentially diabetes. Despite glycogen's role as an essential energy reservoir, the mechanisms governing its synthesis and structural diversity across tissues remain unclear. Here, we uncover the distinct physiological roles of the human glycogenins GYG1 and GYG2 in glycogen synthesis. Through cellular models, structural biology, and biochemical analyses, we demonstrate that, unlike GYG1, GYG2 exhibits minimal autoglycosylation activity and acts as a suppressor of glycogen formation. Together, these two glycogenins coordinate glycogen synthase activity and influence glycogen assembly in a cell-type-dependent manner. Importantly, these glycogenins modulate glucose metabolic pathways, thereby ensuring cellular glucose homeostasis. These findings address longstanding questions in glycogen metabolism and establish both GYG1 and GYG2 as critical regulators of glycogen synthesis and breakdown in human, providing insights with potential therapeutic implications for treating GSDs and metabolic diseases.

PMID:40670355 | DOI:10.1038/s41467-025-61862-3

Nat Commun. 2025 Jul 16;16(1):6545. doi: 10.1038/s41467-025-61734-w.

ABSTRACT

Oral facial cleft (OFC) comprises cleft lip with or without cleft palate (CL/P) or cleft palate only. Genome wide association studies (GWAS) of isolated OFC have identified common single nucleotide polymorphisms (SNPs) in many genomic loci where the presumed effector gene (for example, IRF6 in the 1q32 locus) is expressed in embryonic oral epithelium. To identify candidates for functional SNPs at eight such loci we conduct a massively parallel reporter assay in a fetal oral epithelial cell line, revealing SNPs with allele-specific effects on enhancer activity. We filter these SNPs against chromatin-mark evidence of enhancers and test a subset in traditional reporter assays, which support the candidacy of SNPs at loci containing FOXE1, IRF6, MAFB, TFAP2A, and TP63. For two SNPs near IRF6 and one near FOXE1, we engineer the genome of induced pluripotent stem cells, differentiate the cells into embryonic oral epithelium, and discover allele-specific effects on the levels of effector gene expression, and, in two cases, the binding affinity of transcription factors FOXE1 or ETS2. Conditional analyses of GWAS data suggest the two functional SNPs near IRF6 account for the majority of risk for CL/P at this locus. This study connects genetic variation associated with OFC to mechanisms of pathogenesis.

PMID:40670354 | DOI:10.1038/s41467-025-61734-w

Cell Rep Med. 2025 Jul 15;6(7):102236. doi: 10.1016/j.xcrm.2025.102236.

ABSTRACT

Endoscopic healing (EH) is the major long-term treatment target for inflammatory bowel diseases (IBDs), mainly achieved by immune-suppressive therapies. However, the chronic and relapsing nature of the disease indicates a lifelong persistence of unknown tissue-associated IBD residues. Based on longitudinally collected gastrointestinal biopsies (n = 217) from pediatric patients with IBD (N = 32) and pediatric non-IBD controls (N = 5), we describe cellular, molecular, and microbial drivers of IBD that persist under EH in the terminal ileum and sigmoid colon. Whole biopsy transcriptomics in combination with single T cell analysis (72,026 cells) characterizes an inflammatory bowel residual disease (IBrD) signature, connecting stress- and inflammation-related tissue markers (e.g., DUOX2, SAA2, and NOS2) with pathogenic interleukin-17 (IL-17)-producing T helper cells. 16S rRNA gene sequencing reveals individual microbial composition with persistently low diversity, irrespective of disease location and activity. Overall, our study identifies a persisting IBD signature that reflects ongoing mucosal alterations despite EH. These markers may provide targets for future or sequential therapies.

PMID:40669446 | DOI:10.1016/j.xcrm.2025.102236

J Hazard Mater. 2025 Jul 11;496:139213. doi: 10.1016/j.jhazmat.2025.139213. Online ahead of print.

ABSTRACT

Acid in-situ leach uranium (U) mining layers (ML) characterized by anaerobic, oligotrophic conditions, high arsenic (As) concentration, represent an unique but poorly characterized microbial habitat. Herein, autotrophic microbial metabolisms and arsenic detoxification strategies in underground ML (depth >111 m) were revealed through 16S rRNA gene amplicon sequencing and metagenomic analysis. Dissolved organic matter (DOM) content in ML after acid in-situ leach mining was significantly higher than that in non-mining layers (NML). Compared with NML, the arsenite (As(III)) content in ML showed a decreasing trend, while the As(V) content correspondingly increased significantly. As(III) and DOM showed significant positive effects on the diversity of bacterial communities in ML and NML. The genes involved in Calvin Benson Bassham (CBB) pathway and monosaccharide decomposition dominated the DOM dynamics in ML and NML. Notably, metabolic pathway analyses demonstrated that microbial As(III) anaerobic oxidation by coupling with nitrate reduction favors CO2 fixation driven by CBB pathway, reducing As toxicity and enhancing DOM content in ML. Chemolithoautotrophs utilize multiple survival strategies (e.g., nitrate assimilation, metals efflux) in ML. These findings reveal that chemolithoautotropic microbial As(III) oxidation contributes to CO2 fixation and As detoxification in ML, broadening our horizons of As and carbon cycling in deep underground mining environments.

PMID:40669347 | DOI:10.1016/j.jhazmat.2025.139213

JCO Precis Oncol. 2025 Jul;9:e2500015. doi: 10.1200/PO-25-00015. Epub 2025 Jul 16.

ABSTRACT

PURPOSE: Progression-free survival (PFS) has been proposed as a surrogate end point in clinical trials for advanced hepatocellular carcinoma (aHCC). However, there have been concerns about the discrepancy between PFS and overall survival. Here, we aimed to characterize the behavior of individual lesions within the same patient/liver that play a key role in response assessment to a systemic treatment and how this changed temporally.

METHODS: We obtained serial lesion measurement data from six clinical trials undertaken in the modern era (by which we mean since the first controlled trial in aHCC). In each patient, the percentage change of their lesion size was calculated at each visit compared with the baseline/screening phase. To assess lesion behavior, the patients were classified according to the degree of divergence (DOD) categories that ranged from 0 (all lesions behaved similarly) to 2 (completely discordant behavior). Finally, the results were summarized per treatment arm as the proportion of patients in each divergence category per follow-up visit.

RESULTS: Of the 8,260 visits where DOD was assessed in patients, there was a considerable proportion of patients with divergent lesion behavior at the treatment arm level-approximately 58% were DOD 0, 38% were DOD 1, and 4% were DOD 2. Individually, there was evidence of lesions both increasing and decreasing in size within the same liver despite the treatment remaining the same.

CONCLUSION: The evidence presented here suggests that caution should be exercised in the application of progression-based metrics such as PFS as an end point in HCC clinical trials. Ultimately, there was consistently a considerable proportion of patients who were classified as having lesions within their liver which had a divergent response to treatment.

PMID:40669018 | DOI:10.1200/PO-25-00015

Mol Biol Evol. 2025 Jul 16:msaf172. doi: 10.1093/molbev/msaf172. Online ahead of print.

ABSTRACT

Many algorithms are available for inferring species trees from various input types while accounting for gene tree discordance. Several quartet-based species tree inference methods, collectively known as the ASTRAL family, are based on similar ideas and are in wide use. Here, we integrate all ASTRAL-like methods into a single package called ASTER, comprising several tools, each designed for a different input type: (1) ASTRAL for single-copy gene tree topologies, (2) weighted ASTRAL (wASTRAL) for singlecopy gene tees with branch length and/or support, (3) ASTRAL-Pro for multi-copy gene tree topologies, (4) CASTER for multiple sequence alignments, including genome alignments, and (5)WASTER for shortreads and assembled genomes. These tools collectively enhance the scalability, accuracy, and versatility of species tree inference.

PMID:40668947 | DOI:10.1093/molbev/msaf172

Am J Physiol Cell Physiol. 2025 Jul 16. doi: 10.1152/ajpcell.00438.2025. Online ahead of print.

ABSTRACT

Pharmaceutical research has undergone significant transformation over time, particularly in the development of potent compounds that target specific physiological mechanisms. The need to demonstrate clinical benefit posed challenges. These challenges led to the rise of translational physiology and precision medicine aided by the development of the chemical biology platform. The chemical biology platform is an organizational approach to optimize drug target identification and validation and improve safety and efficacy of biopharmaceuticals. The platform achieves this goal through emphasis on understanding the underlying biological processes and leveraging knowledge gained from the action of similar molecules on these biological processes. The platform connects a series of strategic steps to determine whether a newly developed compound could translate into clinical benefit using translational physiology. Translational physiology examines biological functions across multiple levels, from molecular interactions to population-wide effects, and has been deeply influenced by the advancement of the chemical biology platform. Unlike traditional trial-and-error methods, by leveraging systems biology techniques, such as proteomics, metabolomics and transcriptomics, chemical biology prioritizes targeted selection to enhance drug discovery. This historical review explores the evolution of the chemical biology platform and its role in precision medicine, highlighting its continued influence in both academic research and pharmaceutical innovation. By fostering a mechanism-based approach to clinical advancement, chemical biology remains a critical component in modern drug development. Additionally, understanding the history and integrative nature of this platform is essential for training the next generation of researchers in the design of experimental studies that effectively incorporate translational physiology.

PMID:40668627 | DOI:10.1152/ajpcell.00438.2025

Bioinformatics. 2025 Jul 16:btaf366. doi: 10.1093/bioinformatics/btaf366. Online ahead of print.

ABSTRACT

MOTIVATION: Convergence analysis can characterize genetic elements underlying morphological adaptations. However, its performance on regulatory elements is limited due to their modular composition of transcription factor motifs, which have rapid turnover and experience different evolutionary pressures.

RESULTS: We introduce phyloConverge, a phylogenetic method that performs scalable, fine-grained local convergence analysis of genomic elements at flexible length scales. Using a benchmarking case of convergent subterranean mammal adaptation, phyloConverge identifies rate-accelerated conserved non-coding elements (CNEs) with high specificity and statistical robustness relative to competing methods. From CNE-level scoring, we detect the convergent regression of entire CNE units and highlight the contrast that subterranean-associated coding region regression is highly specific to ocular functions, whereas regulatory element regression is enriched for accompanying neuronal phenotypes and other developmental processes. From transcription factor motif-level scoring, we dissect elements into subregions with uneven convergence signals and demonstrate the modular adaptation of CNEs with high functional specificity. Finally, we demonstrate phyloConverge's scalability to perform high-resolution convergence analysis genome-wide.

AVAILABILITY AND IMPLEMENTATION: phyloConverge is available at https://github.com/ECSaputra/phyloConverge.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40668213 | DOI:10.1093/bioinformatics/btaf366

bioRxiv [Preprint]. 2025 Jun 21:2025.06.16.659967. doi: 10.1101/2025.06.16.659967.

ABSTRACT

Probiotic supplements are marketed for diverse health benefits, yet species inclusion often lacks functional rationale. We surveyed 352 U.S. probiotic products and found 36 unique microbial species, with most supplements containing only one species and no clear link between species and intended health benefit. To evaluate probiotic function, we developed CoPaPro, a collection of 1,012 genome-scale metabolic models spanning commensal, pathogenic, and probiotic bacteria. Flux balance analysis revealed that current probiotic species fail to capture the metabolic diversity of native commensals. Focusing on vaginal health, we identified commensals with metabolic profiles overlapping Gardnerella vaginalis , a key pathobiont. In vitro spent media assays using 11 vaginal isolates showed variable inhibition of G. vaginalis , primarily driven by D-lactic acid production rather than metabolic similarity. Several non- Lactobacillus species produced inhibitory levels of D-lactate. These findings highlight the need for function-based probiotic design and demonstrate a scalable framework integrating metabolic modeling with experimental validation.

PMID:40667100 | PMC:PMC12262460 | DOI:10.1101/2025.06.16.659967

bioRxiv [Preprint]. 2025 Jun 27:2025.06.27.661827. doi: 10.1101/2025.06.27.661827.

ABSTRACT

Microbes drive ecosystem function through their physical interactions and metabolic transformations. However, since microbiomes are ecologically and metabolically interconnected, it is challenging to predict emergent ecosystem responses once the microbiome is disturbed. While it is widely acknowledged that mammalian gut dysbiosis influences host metabolism, mechanistic links that predict these effects are understudied. This study employs a genome-resolved eco-systems biology approach, using a high-resolution 'spinal cord-gut axis' model system and dataset, to predict how dysbiotic gut metabolism impacts overall mammalian health. By scaling and combining temporally resolved network analytics and consensus statistical methods, key microbial species were identified that predict overall host physiology and presumably control the gut ecosystem. In silico validation by pathway-centric functional analyses and comparative genomics revealed that key bacteria, sometimes exclusively, encode functions linking microbial and host metabolisms. Notably, spinal-mediated disturbances in the ecosystem shifted gut microbial nitrogen metabolism from urease-to amino acid-dependent pathways, with patterns that varied by host sex and bacterial species. Overall, this research challenges the traditional paradigm that only the host maintains whole-body nitrogen balance and instead invokes the microbiome as an environmentally-sensitive regulatory organ that can dictate health or disease by influencing mammalian whole-body elemental balance.

PMID:40667084 | PMC:PMC12262403 | DOI:10.1101/2025.06.27.661827

medRxiv [Preprint]. 2025 Jun 24:2025.06.23.25330157. doi: 10.1101/2025.06.23.25330157.

ABSTRACT

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are environmental toxicants associated with adverse neonatal outcomes. The exact mechanisms by which PFAS impairs neonatal health are undefined, but the placenta is a likely target.

OBJECTIVE: We applied a systems biology approach to identify placental RNA co-expression modules (gene sets) associated with PFAS exposure and birth weight.

METHODS: Placental tissue samples (n = 147) from the GLOWING study underwent RNA-sequencing, and PFAS concentrations were quantified using liquid chromatography-tandem mass spectrometry. We constructed a weighted gene co-expression network using Spearman correlations across 15,028 transcripts, identifying 20 gene modules. Linear regression models were used to examine associations between PFAS and module eigengenes, adjusting for potential confounders. Effect modification by fetal sex was also tested.

RESULTS: One module showed a negative association with perfluorononanoic acid (PFNA; β = - 0.012, q = 0.009). This association was sex-specific, with the sexes exhibiting varied PFAS associations but similar directional effects. Genes within the PFNA-associated module were involved in histone modification (q ≤ 0.05) and were enriched for targets of the Vitamin D Receptor (VDR), a transcription factor previously linked to PFAS.

DISCUSSION: Our research indicates that prenatal exposure to PFNA influences placental gene expression differently based on sex, which may affect insulin growth factor signaling and histone modification. The presence of VDR in this module and the transcription enrichment analysis align with previous findings regarding PFAS and VDR interactions. This module related to PFNA could shed light on the molecular pathways connecting PFAS exposure to health outcomes in neonates.

PMID:40666376 | PMC:PMC12262800 | DOI:10.1101/2025.06.23.25330157

Front Plant Sci. 2025 Jul 1;16:1597030. doi: 10.3389/fpls.2025.1597030. eCollection 2025.

ABSTRACT

Nitric oxide (NO), a key signaling molecule in plants, induces various biological and biochemical processes, including growth and development, adaptive responses, and signaling pathways. The intricate nature of NO dynamics requires vigorous statistical approaches to guarantee precise data interpretation and significant biological conclusions. This review underscores the importance of statistical methodologies in NO study, discussing experimental design, data collection, and advanced analytical tools. In addition, vital statistical challenges such as high variability in NO measurements, small sample sizes, and complex interactions with other signaling molecules, are investigated along with approaches to alleviate these limitations. New computational techniques, including machine learning, integrative omics approaches, and network-based systems biology, present commanding outlines for identifying NO-mediated regulatory mechanisms. Furthermore, we underscore the necessity for interdisciplinary collaboration, open science practices, and standardized protocols to improve the reproducibility and dependability of NO research. By combining robust statistical methods with advanced computational tools, researchers can gain enhanced insights into NO biology and its effects on plant adaptation and resilience.

PMID:40666296 | PMC:PMC12259607 | DOI:10.3389/fpls.2025.1597030

J Exp Biol. 2025 Jul 15;228(14):jeb250770. doi: 10.1242/jeb.250770. Epub 2025 Jul 16.

ABSTRACT

The digestive system facilitates exchanges between animals and their environments. It not only converts resources into energy and growth but also shapes ecosystem processes through waste outputs, all while mediating an animal's relationship with complex microbial communities. The Special Issue: The Integrative Biology of the Gut delves into many aspects of this expansive relationship. Further, this Commentary collects the special issue papers under themes to highlight and explore the physiology of the digestive system and the plasticity that enables its acclimatization to dietary and environmental changes. The themes that have been identified portray the gastrointestinal (GI) tract as an integrative moderator of physiology, and show that when this system is explored using novel techniques or by asking innovative questions, one can reveal phenomena with applications well beyond digestive biology. Further, we discuss how embracing multidisciplinary approaches - including systems biology, evolutionary comparisons and environmental considerations - will allow us to use the unique physiology of the GI tract to form critical insights into evolved organismal biology, microbial symbioses and ecological stewardship. Ultimately, the pivotal role of the GI tract in connecting internal physiology with external ecological dynamics across taxa exemplifies its value as a model system.

PMID:40665871 | DOI:10.1242/jeb.250770

Alzheimers Dement. 2025 Jul;21(7):e70464. doi: 10.1002/alz.70464.

ABSTRACT

INTRODUCTION: The apolipoprotein E (APOE) ε4 allele is widely recognized as the strongest genetic risk factor for late-onset Alzheimer's disease. Therapeutic strategies to reduce apoE4 expression in APOE ε4 carriers hold promise to mitigate neuroinflammatory and neurodegenerative processes driving disease progression.

METHODS: Focused ultrasound (FUS) was employed to transiently open the blood-brain barrier (BBB) for efficient knockdown of humanized APOE ε4 in the mouse brain via gene editing. The all-in-one clustered regularly interspaced short palindromic repeats (CRISPR)-based adeno-associated virus (AAV) vectors were administered intravenously at a dose of 1.5×1012 vg per mouse to determine the gene-editing efficacy within the hippocampus.

RESULTS: FUS-enhanced delivery of AAV resulted in a 12.6% knockdown of APOE ε4 gene expression in the targeted hippocampus, accompanied by an over 20% decrease in apoE4 protein levels and significant reductions in astrocyte and microglia levels.

DISCUSSION: Our findings demonstrate a noninvasive, targeted approach for APOE ε4 knockdown, highlighting FUS-mediated brain-directed interventions as a promising therapeutic strategy for Alzheimer's disease.

HIGHLIGHTS: Focused ultrasound (FUS) enables noninvasive, transient blood-brain barrier (BBB) opening for enhanced adeno-associated virus (AAV) delivery. FUS-mediated gene editing achieves a 12.6% knockdown in APOE ε4 expression within the hippocampus of mouse brain. APOE ε4 knockdown significantly reduces apoE4 protein levels and astrocyte and microglia levels. No detectable gross toxicity was observed following the FUS-mediated gene editing.

PMID:40665471 | DOI:10.1002/alz.70464