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Homoharringtonine (HHT) is widely used in combination regimens for acute myeloid leukemia (AML), yet its direct cellular targets remain undefined, limiting precision application. Here, we identified EWS RNA-binding protein 1 (EWSR1) as the primary target of HHT through chemical proteomics and biophysical validation. HHT bound the RNA recognition motif of EWSR1 with micromolar affinity, inducing an allosteric conformational switch that promoted oligomerization and liquid-liquid phase separation (LLPS). EWSR1 condensates selectively recruited the N⁶-methyladenosine (m⁶A) reader YTHDF2, forming cytoplasmic hubs where HHT disrupted YTHDF2-mRNA interactions. This sequestration attenuated m⁶A-mediated RNA decay, stabilizing key transcripts such as TNFRSF1B and HMOX1, and thereby impairing AML cell proliferation. Integrated transcriptomics and single-cell RNA-seq analyses revealed that EWSR1 was markedly upregulated in AML, particularly in hematopoietic progenitor and myeloid subpopulations, and high EWSR1 expression correlated with poor prognosis and enhanced HHT sensitivity. In vivo, the anti-leukemic efficacy of HHT was significantly diminished upon EWSR1 knockdown, demonstrating that EWSR1 was required for therapeutic response. Collectively, these findings uncover a phase separation-centric mechanism by which HHT exerts anti-AML activity, establish the EWSR1-YTHDF2-m⁶A axis as a critical regulator of leukemia progression, and position EWSR1 as both a functional target and a predictive biomarker for optimizing HHT-based therapies.

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity by providing a micro-level perspective in the past decade. While heterogeneity is fundamental to diverse biological communities, existing platforms are primarily designed for eukaryotic cells, leaving significant gaps in the study of other single biological entities, such as viruses and bacteria. Current methodologies for single-entity sequencing remain limited by low throughput, inefficient lysis, and highly fragmented genomes. Here, we present the Generic Single-Entity Sequencing (GSE-Seq), a versatile and high-throughput framework that overcomes key limitations in single-entity sequencing through an integrated workflow. GSE-Seq combines (1) one-step generation of massive barcodes, (2) degradable hydrogel-based in situ sample processing and whole genome amplification, (3) integrated in-droplet library preparation, and (4) long-read sequencing. We applied GSE-Seq to profile viral communities from human fecal and marine sediment samples, generating thousands of high-quality single-entity genomes and revealing that most are novel. GSE-Seq identified not only dsDNA and ssDNA viruses, but also hard-to-detect giant viruses and crAssphages. GSE-Seq of bacterial genomes also revealed putative novel bacterial species, validating the versatility of this platform across different microbial kingdoms. Collectively, GSE-Seq represents a robust framework that addresses persistent challenges in high-throughput profiling for generic applications and holds immense promise for single-cell deconvolution of diverse biological entities.

The vaginal microbiome is central to reproductive health, yet large-scale studies in East Asian populations remain scarce. Here, we characterized the vaginal microbiota of 6423 Chinese women of reproductive age across 18 provinces and assessed associations with 33 host factors. We observed a striking compositional transition around age 40, marked by declining Lactobacillus crispatus and enrichment of dysbiosis-associated taxa including Gardnerella vaginalis, independent of lifestyle or sociodemographic influences. Sexual behavior, contraceptive use, and educational attainment emerged as key determinants of community structure, differentially shaping Lactobacillus crispatus and Lactobacillus iners. Despite these associations, host factors explained less than 2% of overall variation, highlighting the resilience and individuality of the vaginal microbiome. To quantify vaginal health, we derived a microbiome balance score, validated it in external cohorts, and demonstrated its predictive power for incident bacterial vaginosis and sexually transmitted infections. Our findings establish a national-scale reference for the vaginal microbiome in Chinese women, reveal a midlife inflection point in microbial composition, and introduce a clinically actionable metric for risk stratification. These insights advance mechanistic understanding of host-microbiome interactions and inform strategies for precision interventions to preserve vaginal health.

The iMeta Conference 2025, part of the iMeta Conference series, themed "Creating High-Impact International Journals," held at the Huangjiahu Campus of Hubei University of Chinese Medicine from August 23rd to 25th, 2025, and focused on frontier topics such as microbiology, medicine, traditional Chinese medicine, botany, and research career development. The event aimed to support the development of researchers and strengthen the impact of academic journals. Through invited reports, thematic seminars, and poster presentations, the conference highlighted hot topics including multi-omics technologies, microbe-host interactions, AI-assisted research, live biotherapeutic products, and the modernization of traditional Chinese medicine. The event demonstrated the innovative momentum of interdisciplinary integration and technological convergence, providing an international platform for academic exchange and laying a foundation for building an innovative scientific research ecosystem and enhancing the global influence of Chinese academic journals.

Social media platforms have revolutionized scientific communication by bridging gaps between researchers, academic journals, and global audiences. This article showcases iMeta, an open-access journal that leverages a diversified social media framework to enhance bilingual dissemination, boost full-text downloads, and amplify international influence. Since its editorial board founded, iMeta has achieved a series of milestones: integrating platforms like WeChat, Bilibili, X (formerly Twitter), YouTube, and BlueSky; launching iMeta-branded journals iMetaOmics and iMetaMed; and being indexed in prominent databases including PubMed, SCIE, and ESI. As of August 2025, the journal has recorded 1,334,761 full-text downloads and 10,560 total citations, with a 2024 impact factor of 33.2. A significant positive correlation between downloads and citations highlights how strategic social media integration and iMeta's growth drive visibility and influence, positioning it as a leading journal in its field.

Spatial clustering is a critical step in the analysis of spatially resolved transcriptomics, serving as the foundation for downstream investigation of tissue heterogeneity. Although numerous computational tools have been developed, systematic benchmarking across different technologies, organs, and biological replicates has been limited. Here, we present a comprehensive evaluation of 14 spatial clustering methods using approximately 600 datasets, including both real-world and simulated data with ground truth. We evaluated accuracy and applicability across diverse technologies and organs, revealing method-specific strengths and preferences. Using simulation of adjacent tissue slices and spatial neighborhood disruptions, we further examined performance in the context of biological replicates. Furthermore, we investigated how data characteristics, spatial distribution patterns, and preprocessing pipelines influence clustering outcomes. Together, our results provide practical benchmarking guidance, enabling researchers to select appropriate spatial clustering methods tailored to specific technologies, organs, and biological replicates.

The 2025 CHINAGUT Conference has assembled a panel of 63 experts (30 scientists, 26 physicians, and 7 corporate R&D personnel) collaborated in three groups to present 30 scientific recommendations to advance probiotics, live biotherapeutic products, and fecal microbiota transplantation, addressing key issues on standardization, translation, supervision, regulation, and regulatory harmonization. These interdisciplinary guidelines aim to synthesize cutting-edge knowledge and practical needs to transform microbiota-based treatments from applications into precision-driven medical solutions, and serve as reference by scientific researchers, medical educators, pharmaceutical enterprises, clinicians, food and drug administrations, policymakers, and patients.

Using culturomics and metagenomics, we demonstrate the existence of non-pathogenic microbiota in the internal organs of healthy experimental mice, challenging the traditional dogma of organ sterility. Based on the analysis of 104 commercially sourced mice (C57BL/6J, BALB/c, ICR), the study reveals that over 20% of the analyzed mice harbored a high microbial burden in the internal organs and identified a total of 463 microbial species. Several species, including Ligilactobacillus murinus, Alcaligenes faecalis, Micrococcus luteus, Pseudochrobactrum asaccharolyticum, Escherichia coli, and Microbacterium sp., were frequently identified and were abundant in the mouse tissues. Further investigation implies that microorganisms in the “sterile” tissues could be associated with the gut microbiota. Given the wide use of experimental mice in medical and biological research, these findings of resident microorganisms in the animal's internal organs raise concerns about potential variability in experimental outcomes.

This study proposes a novel strategy that prioritizes functional recognition, followed by targeted high-throughput sorting, to enable the comprehensive, rapid, and efficient acquisition of target microorganisms. Using metagenomic sequencing and binning analysis, we identified 215 potential anaerobic hydrogen-producing strains from 12 large-scale biogas samples. Digital cell models were subsequently constructed from metagenome-assembled genomes, which guided the design of 14 selective culture media for enriching these hydrogen-producing bacteria. Flow cytometry-based high-throughput sorting successfully isolated 81 potential anaerobic hydrogen-producing strains, achieving a target acquisition rate above 37% and a survival rate exceeding 70%. This method holds broad potential for the discovery and sorting of functional microorganisms across diverse environments and may ultimately facilitate the development of synthetic microbiomes for industrial applications.

Early identification of patients at risk of acute coronary syndrome (ACS) remains a major unmet need, particularly among those with stable coronary artery disease (sCAD), where timely intervention could markedly improve outcomes. The gut microbiota has been implicated in coronary artery disease (CAD), but its ability to distinguish ACS from sCAD is not well defined. Here, we performed cross-sectional multi-omics profiling of fecal microbiota and plasma metabolites in 548 individuals, including participants with normal coronary arteries (N = 175), primary sCAD (N = 161), and ACS (N = 212). To assess whether disease-associated changes resolve with treatment, we further analyzed an independent cohort of ACS patients (N = 52) who transitioned to sCAD following standard therapy. We identified profound ACS-associated alterations in gut microbial composition and systemic metabolism, marked by enrichment of pro-inflammatory taxa such as Streptococcus spp. and elevated circulating levels of 3-hydroxybutyrate (3-HB). Strikingly, many of these ACS-specific microbial and metabolic signatures, including 3-HB and related microbial functional pathways, were restored toward sCAD-like levels after clinical recovery. Integrative models combining microbial taxa, metabolites, and clinical biomarkers robustly discriminated ACS from healthy controls (AUC = 0.91) and from sCAD (AUC = 0.83), significantly outperforming clinical markers alone (AUC = 0.69 for NCA vs. ACS; 0.59 for sCAD vs. ACS). These findings establish the gut microbiome and its metabolic outputs as key discriminators of ACS, reveal their dynamic resolution during disease recovery, and highlight their potential as biomarkers and therapeutic targets for cardiovascular risk stratification and management.