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.

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.

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.

The intratumoral microbiome is an emerging hallmark of cancer, yet its multi-kingdom host–microbiome ecosystem in colorectal cancer (CRC) remains poorly characterized. Here, we conducted an integrated analysis using deep shotgun metagenomics and proteomics on 185 tissue samples, including adenoma (A), paired tumor (T), and para-tumor (P). We identified 4057 bacterial, 61 fungal, 108 archaeal, and 374 viral species in tissues and revealed distinct intratumor microbiota dysbiosis, indicating a CRC-specific multi-kingdom microbial ecosystem. Proteomic profiling uncovered four CRC subtypes (C1–C4), each with unique clinical prognoses and molecular signatures. We further discovered that host-microbiome interactions are dynamically reorganized during carcinogenesis, where different microbial taxa converge on common host pathways through distinct proteins. Leveraging this interplay, we identified 14 multi-kingdom microbial and 8 protein markers that strongly distinguished A from T samples (area under the receiver operating characteristic curve (AUROC) = 0.962), with external validation in two independent datasets (AUROC = 0.920 and 0.735). Moreover, we constructed an early- versus advanced-stage classifier using 8 microbial and 4 protein markers, which demonstrated high diagnostic accuracy (AUROC = 0.926) and was validated externally (AUROC = 0.659–0.744). Functional validation in patient-derived organoids and murine allograft models confirmed that enterotoxigenic Bacteroides fragilis and Fusobacterium nucleatum promoted tumor growth by activating Wnt/β-catenin and NF-κB signaling pathways, corroborating the functional potential of these biomarkers. Together, these findings reveal dynamic host–microbiome interactions at the protein level, tracing the transition from adenoma to carcinoma and offering potential diagnostic and therapeutic targets for CRC.

Shen, Juan, Weiming Liang, Ruizhen Zhao, Yang Chen, Yanmin Liu, Wei Cheng, Tailiang Chai, et al. 2025. “Cross-tissue multi-omics analyses reveal the gut microbiota's absence impacts organ morphology, immune homeostasis, bile acid and lipid metabolism.” iMeta 4, e272. https://doi.org/10.1002/imt2.272.

In the author list of the main text and the supplementary materials, the corresponding author's name “Kristiansen Karsten” should be written as “Karsten Kristiansen.”

We apologize for this error.

MCMCtree and r8s are among the most popular molecular dating tools in the current genomic era, but their utility is hampered by steep learning curves, particularly concerning input file formatting, the complexity of fossil calibration setup, tree visualization, and model selection. To enhance their usability and improve research efficiency, we developed three new tools: MDGUI (for molecular dating analysis), TimeTreeAnno (for timetree visualization), and MCMCTracer (for convergence assessment). We integrated these into the PhyloSuite v2 platform, along with MCMCtree and r8s plugins, to create a comprehensive molecular dating suite. Compared to existing solutions that we benchmarked, our toolkit offers a more intuitive interface and streamlined workflow, featuring visual calibration point configuration, support for multiple alignment formats, automated model selection and implementation for downstream analyses, one-click pause/resume functionality, multithreading acceleration, and on-demand MCMC convergence assessment and plotting. Furthermore, PhyloSuite v2 introduces other advanced features, including gene duplicate resolution during the extraction step, significantly accelerated data handling capabilities (specifically, format conversion and concatenation), deeper integration of the latest IQ-TREE models and functions, and further streamlining of the entire phylogenetic analysis workflow. The update also includes adaptation to high-resolution screens and numerous bug fixes. The source code for the new version of PhyloSuite is available at https://github.com/dongzhang0725/PhyloSuite.

Cancer immune evasion is orchestrated by tumor-intrinsic molecular constraints that remain incompletely defined. Here, we performed an in vivo genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) loss-of-function screen to catalogue gene regulatory determinants of immune evasion in cancer cells. We identify C9ORF50 as a novel splicing regulator whose inhibition profoundly sensitizes cancer to immune surveillance. Integrated multi-omics profiling reveals this intrinsically disordered protein exhibits liquid–liquid phase separation properties and forms nuclear condensates that colocalize with spliceosome components. Genetic ablation correlates with intron retention in multiple spliceosome components and cytoplasmic accumulation of double-stranded RNA, which is associated with type I interferon activation and enhances chemokine-mediated T cell recruitment. As a result, C9ORF50 inhibition amplifies tumor cell immunogenicity, enhancing T cell infiltration in poorly infiltrated tumors. Clinically, elevated C9ORF50 expression correlates with poor survival and diminished lymphoid infiltration across malignancies. Therapeutic targeting of C9ORF50 using RNA interference enhances T cell infiltration and suppresses tumor growth. Our work identifies C9ORF50 as a candidate therapeutic target that modulates RNA splicing and tumor immunity, suggesting splicing regulation as a potential strategy to enhance immunotherapy responses.

Deciphering how plant–microbiota interactions achieve beneficial outcomes for crops will provide innovative strategies for sustainable agriculture. Here, we dissected rice-microbiota dynamics using a tailored gnotobiotic cultivation system that models the semiaquatic environment in a paddy field. Inoculation with native soil microbiota resulted in root-growth-promotion (RGP) and root-growth-inhibition (RGI) phenomena in different cultivars. This preference persisted in a simplified synthetic community and individual bacterial strains, indicating that cultivar-specific growth promotion is an intrinsic property of microbial inocula. Though stochastic process dominated the assembly of root microbiome in gnotobiotic cultivation, absolute quantification revealed that imbalance of detrimental and beneficial bacterial loads in roots correlated with RGP or RGI outcomes in different rice cultivars. From the host perspective, genetic screening identified that receptor-like kinase mutants, including OsFLS2 (FLAGELLIN-SENSITIVE 2), inverted microbiota functionality, converting RGP to RGI. In particular, over 4534 rice genes responded to microbiota inoculation and 46.1% of them were reprogrammed in osfls2 mutants, demonstrating the prominent regulatory role of OsFLS2 in rice-microbiota signaling. On the basis of these results, we propose that the rice-microbiota relationships are gated by cultivar-specific preferences of the bacterial microbiota and host immune receptor kinase, which provides a useful framework for crop microbiome engineering in the future.

Oxygen signaling is essential for cellular homeostasis and tightly linked to metabolism, growth, and survival. In dairy cows, oxidative stress, arising from an imbalance between reactive oxygen species and antioxidants, is a major postpartum challenge that contributes to disease susceptibility. Using single-cell transcriptomes from 1,793,854 cells across 59 tissues, we analyzed oxygen signaling states within 1006 cellular clusters. The gastrointestinal tract (GIT) epithelium, particularly the forestomach, exhibits the strongest antioxidant activity, closely coupled to oxidative phosphorylation (OXPHOS) and glycolysis, with OXPHOS levels surpassing those of cardiomyocytes and hepatocytes (Cohen's d > 3.9, p < 0.001). Pseudotime and spatial transcriptomics demonstrated that both OXPHOS and antioxidant capacity increase progressively along the basal-to-luminal differentiation axis. Functional experiments in primary rumen epithelial cells showed that antioxidant supplementation or GPX1 modulation enhances mitochondrial respiration, boosts intracellular glutathione, and accelerates epithelial differentiation. Limited proteolysis-mass spectrometry (LiP-MS) analysis identified GPX1, GSTP1, COX7A2, and COX6B1 as candidate targets mediating antioxidant-driven metabolic remodeling. Together, these results reveal a redox-governed metabolic program in the forestomach epithelium and highlight antioxidant interventions as a potential strategy to support epithelial development and mitigate oxidative stress-related disorders in dairy cattle.