Efficient downstream analysis of microbiome data remains a major challenge for researchers. Since its initial release in late 2020, the R microeco package has been widely used for downstream statistical analysis and visualization of omics data, such as amplicon sequencing. Compared with its initial release, the current second version of the microeco package has undergone extensive updates and enhancements. The key upgrades include: (1) The addition of classes for data normalization and machine learning, respectively; (2) The incorporation of additional analytical methods and the addition of functions across various classes; (3) Optimization of the parameter system to expand the applicable scenarios of relevant methods; (4) Code restructuring to enhance the connectivity between statistical analysis and visualization within each class; (5) Extension of certain functions to enable the analysis of abundance data in complex formats generated from bioinformatic analyses of metagenomic/metatranscriptomic data; (6) Incorporation of several analytical methods commonly used in transcriptomic and metabolomic data analyses. Overall, the microeco package 2.0 offers broader method coverage and a wider range of application scenarios compared to the previous version and other existing R packages. The steady growth in user downloads demonstrates that the microeco package, which is built on R6 (a class-based object-oriented programming system for R), has established a broad and active user base. The second version of the microeco R package is open-source and available on the Comprehensive R Archive Network and GitHub (https://github.com/ChiLiubio/microeco).

Microbial networks and keystone taxa play pivotal roles in maintaining gut microecological stability and host homeostasis, irrespective of their abundance. However, most previous studies of aging-associated gut microbiota have relied on abundance-based analyses, largely overlooking microbial networks and microbe-host interactions. Here, we employed a co-occurrence network approach to identify keystone taxa during aging in humans and mice. We found that centenarians harbor distinctive keystone taxa dominated by members of Clostridium, of which Clostridium scindens (C. scindens) can significantly enhance microbial network stability, probably contributing to longevity and reduced susceptibility to age-related diseases. Mechanistically, C. scindens produces indole-3-acetic acid (IAA) from tryptophan via the enzymes amidase (AMIE) and aldehyde dehydrogenase (ALDH). Oral administration of either C. scindens or IAA effectively mitigates intestinal aging by restoring gut barrier dysfunction in aged mice. Further analysis revealed that C. scindens-derived IAA restores intestinal dysfunction through activation of aryl hydrocarbon receptor (AHR) signaling, leading to upregulation of intestinal CLDN10, a key tight junction protein. Structurally, IAA enhances Claudin-10 transcription by promoting AHR binding to its promoter region. Our findings provide new insights into the characterization of microbial networks in centenarians and highlight that C. scindens and IAA may contribute to healthy longevity by promoting gut microecological stability and host homeostasis.

Systematic characterization of cellular gene expression in livestock tissues during development is essential for understanding the regulation of complex traits. Despite the comprehensive profiling of cell atlases in livestock, a dynamic view of tissue development remains lacking. Here, using both single-cell and single-nucleus RNA sequencing, we present a comprehensive single-cell transcriptomic landscape of 252,033 cells/nuclei, mapping 83 distinct cell types across five pig tissues from prenatal to postnatal developmental stages. Our findings highlight the coordinated remodeling of tissue architecture through stem/progenitor cell proliferation, lineage specification, and functional maturation during organogenesis. We identified key transcription factors and regulatory networks that drive lineage-specific and spatiotemporally dynamic transcriptional programs. Developmental trajectory analysis identified a conserved bifurcatetranscriptional organization of immune cells, accompanied by dynamic changes in transcription factors associated with immune cell maturation. Integrative analysis utilizing multi-omic, single-cell, and pig population genomics data identified a muscle-specific enhancer of the MYOT gene as a target of artificial selection, underlying meat-quality divergence between Asian and European pig breeds. Moreover, cross-species comparison between pigs and humans revealed conserved cell types, underscoring the evolutionary link. In summary, the comprehensive pig developmental cell atlas serves as a key resource for understanding livestock development, provides insights for precision breeding, and highlights the value of the reference pig cell atlas as a powerful resource for biomedical research.

Nanopore direct RNA sequencing (DRS) has transformed transcriptomics by enabling single-molecule, long-read sequencing of native RNA without the need for reverse transcription or amplification. In contrast to short-read RNA-seq and cDNA-based long-read approaches, DRS can simultaneously capture multiple RNA modifications, full-length transcript architecture, alternative splicing patterns, and poly(A) tail features within individual molecules, thereby providing an integrated view of transcriptomic and epitranscriptomic regulation. In this comprehensive review, we outline the biophysical principles underlying nanopore DRS and trace its technological evolution. We compare its performance with short-read RNA sequencing, long-read cDNA sequencing, and conventional RNA-modification mapping strategies, highlighting its advantages in isoform-resolved quantification and multilayer RNA feature integration, while also clarifying contexts in which alternative or combined approaches may be more appropriate for robust biological interpretation. We further summarize optimized experimental workflows, including library construction strategies tailored to diverse RNA biotypes (mRNA, rRNA, tRNA, circRNA, miRNA, and nonpoly(A) transcripts), as well as recommended quality-control procedures and sequencing optimization practices. Emphasizing recent computational advances and translational applications of DRS, we cover state-of-the-art algorithms for RNA modification detection, transcript reconstruction, and isoform quantification. We also propose analytical pipelines for poly(A) tail length inference and integrative frameworks that jointly analyze these regulatory layers. We distinguish direct nanopore signals from computational inferences to define confidence levels and emphasize benchmarking and orthogonal validation of readouts. Practical implementation examples are included to facilitate reproducible analysis. Finally, we highlight emerging applications of integrated DRS, including the resolution of complex transcriptomes, the characterization of coordinated epitranscriptomic regulation, and the identification of disease-associated RNA signatures. We also discuss current technical challenges and future perspectives, particularly in relation to multi-omics integration and the broader deployment of DRS in precision medicine as well as in plant and animal research.

Recurrent spontaneous abortion (RSA) poses a significant challenge to successful early pregnancy, and trophoblast cell ferroptosis is an important pathogenic mechanism of RSA. However, it remains unclear whether decidual macrophages, as key immune regulators at the maternal–fetal interface, participate in the regulation of ferroptosis in trophoblast cells. This study observed significant ferroptosis in the placental trophoblast cells of patients with RSA and aborted mice. Transcriptomic sequencing results revealed that decidual macrophages derived from patients with RSA significantly promoted trophoblast cell ferroptosis while simultaneously impairing trophoblast cell function. Mechanistically, silencing heme oxygenase 1 (HMOX1) in trophoblast cells effectively reversed ferroptosis and restored trophoblast cell function, which was inhibited by decidual macrophages derived from patients with RSA. Notably, decidual macrophages regulate trophoblast ferroptosis and function by secreting C-X-C motif chemokine ligand 2 (CXCL2). Furthermore, the nuclear factor kappa-B (NF-κB) pathway was significantly enriched in trophoblast cells co-cultured with decidual macrophages derived from patients with RSA. Further reversal experiments indicated that the CXCL2/NF-κB/HMOX1 signaling axis may be a crucial mechanism by which decidual macrophages regulate trophoblast cell ferroptosis and function in RSA. Our subsequent findings demonstrated that trophoblast cells co-cultured with RSA-derived decidual macrophages promoted pro-inflammatory polarization in macrophages. This effect was mediated by the interleukin-6 (IL-6) deficiency-inhibited janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling axis. Finally, pharmacological analysis revealed Eriodictyol exhibits CXCL2-axis-associated protective effects in RSA. In conclusion, we observed that decidual macrophages in patients with RSA can induce ferroptosis in trophoblast cells, implying that targeting this mechanism may offer novel opportunities for reshaping maternal-fetal tolerance.

Intracellular metal dyshomeostasis has emerged as a key regulator of specialized regulated cell death (RCD) programs, challenging classical views that regard necrosis as entirely accidental. This review systematically delineates the molecular architecture and translational trajectories underlying metal-dependent RCD, including iron-driven ferroptosis, copper-mediated cuproptosis, and additional emerging modalities such as calcicoptosis, necrosis by sodium overload (NECSO), and the newly designated zincoptosis, mnoptosis, and coptosis. We examined distinct execution mechanisms, ranging from membrane lipid peroxidation and lipoylation-targeted proteotoxic stress to organelle-specific bioenergetic failure, which arise following disruption of compartmentalized metal-buffering networks. To bridge the persistent knowledge gap between foundational metallobiology and clinical application, we evaluated a bidirectional therapeutic framework: exploiting synthetic lethality and metabolic gating via clinical inducers (e.g., sorafenib, elesclomol) to selectively eliminate therapy-resistant malignancies while deploying targeted pathway inhibitors and systemic agonists (e.g., dipyridamole, omaveloxolone) to limit pathological tissue degeneration in ischemic and neurodegenerative disorders. Recognizing that off-target multiorgan toxicity and complex in vivo crosstalk among interconnected death pathways (e.g., disulfidptosis and PANoptosis) represent major translational challenges, we assessed advanced materials-science strategies designed to overcome these barriers. Specifically, we highlighted the integration of single-atom catalysts, stimuli-responsive nanomedicines, and biomimetic carriers engineered to spatiotemporally confine catalytic oxidative flux. Finally, we examined the systemic immunological consequences of targeted metal dysregulation, detailing how metal-induced immunogenic cell death and cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway hyperactivation reshape immunosuppressive microenvironments and modulate sterile inflammation, thereby enhancing responsiveness to immune checkpoint blockade, providing a definitive molecular blueprint for next-generation precision therapeutics.

Spatial omics technologys help overcome key limitations of conventional omics approaches that lack spatial information, by providing a panoramic perspective from the molecular level to the microenvironment scale for addressing spatially resolved biological questions in life sciences. With the rapid advancement of this field, there are significant differences among technology platforms, algorithms, and research workflows, which bring three core challenges to interdisciplinary researchers: the detailed explanation of technical principles, the selection of appropriate algorithms, and the future development directions. This review systematically summarizes the technical platforms and analytical algorithms of spatial omics, compares their advantages and disadvantages in the context of specific tasks and presents application cases across multiple biological fields. It also outlines the emerging research directions and advances in large model integration. It ultimately aims to provide a reference for researchers from diverse disciplines to design and implement spatial omics studies.