Organization of the human intestine at single-cell resolution

Exploring the mechanism of intestinal bacterial translocation after severe acute pancreatitis: the role of Toll-like receptor 5

Severe acute pancreatitis (SAP)-induced intestinal bacterial translocation and enterogenic infection are among the leading causes of mortality in patients. However, the mechanisms by which SAP disrupted the intestinal barrier and led to bacterial translocation remained unclear. Therefore, we employed multi-omics analysis including microbiome, metabolome, epigenome, transcriptome, and mass cytometry (CyTOF) to identify potential targets, followed by functional validation using transgenic mice. The integrated multi-omics analysis primarily indicated overgrowth of intestinal flagellated bacteria, upregulation of intestinal Toll-like receptor 5 (TLR5) and acute inflammatory response, and increased infiltration of intestinal high-expressing TLR5 lamina propria dendritic cells (TLR5hi LPDC) after SAP. Subsequently, intestinal flagellin-TLR5 signaling was activated after SAP. Intestinal barrier disruption, bacterial translocation, and helper T cells (Th) differentiation imbalance caused by SAP were alleviated in TLR5 knocked out (Tlr5-/-) or conditionally knocked out on LPDC (Tlr5ΔDC) mice. However, TLR5 conditional knockout on intestinal epithelial cells (Tlr5ΔIEC) failed to improve SAP-induced bacterial translocation. Moreover, depletion of LPDC and regulatory T cells (Treg) ameliorated bacterial translocation after SAP. Our findings identify TLR5 on LPDC as a potential novel target for preventing or treating intestinal bacterial translocation caused by SAP.

The landscape of malignant transition: Unraveling cancer cell-of-origin and heterogeneous tissue microenvironment

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.

Intestinal secretory differentiation reflects niche-driven phenotypic and epigenetic plasticity of a common signal-responsive terminal cell

Enterocytes and four classic secretory cell types derive from intestinal epithelial stem cells. Based on morphology, location, and canonical markers, goblet and Paneth cells are considered distinct secretory types. Here, we report high overlap in their transcripts and sites of accessible chromatin, in marked contrast to those of their enteroendocrine or tuft cell siblings. Mouse and human goblet and Paneth cells express extraordinary fractions of few antimicrobial genes, which reflect specific responses to local niches. Wnt signaling retains some ATOH1+ secretory cells in crypt bottoms, where the absence of BMP signaling potently induces Paneth features. Cells that migrate away from crypt bottoms encounter BMPs and thereby acquire goblet properties. These phenotypes and underlying accessible cis-elements interconvert in post-mitotic cells. Thus, goblet and Paneth properties represent alternative phenotypic manifestations of a common signal-responsive terminal cell type. These findings reveal exquisite niche-dependent cell plasticity and cis-regulatory dynamics in likely response to antimicrobial needs.

Pdia3 deficiency exacerbates intestinal injury by disrupting goblet and Paneth cell function during ischemia/reperfusion

Intestinal ischemia/reperfusion (I/R) injury is a severe medical condition associated with high mortality rates due to its disruption of intestinal homeostasis and impairment of mucosal defenses. The intestinal epithelium, particularly goblet and Paneth cells, plays a critical role in maintaining gut barrier integrity. Protein disulfide isomerase A3 (PDIA3) is involved in protein folding within intestinal epithelial cells (IECs) and has been linked to the stress response during I/R injury. This study aims to explore the role of PDIA3 in preserving intestinal integrity and immune function during I/R injury. Our study employed both human and mouse models to investigate PDIA3's expression and function. The correlation between PDIA3 expression and disease severity was analyzed using statistical tests, including Pearson's correlation coefficient. An intestinal I/R model was established in intestinal epithelium-specific conditional knockout mice lacking the Pdia3 gene. Single-cell RNA sequencing, immunohistochemistry, and transcriptomic analysis were used to assess PDIA3 expression in various intestinal cell types and to evaluate its role in epithelial differentiation and immune responses. PDIA3 was found to be highly expressed in healthy IECs, especially in goblet and Paneth cells. Its expression was reduced in patients with mesenteric artery ischemia and Pdia3-deficient mice, leading to severe intestinal damage, including impaired goblet and Paneth cell function, reduced antimicrobial peptide production, and altered gut microbiota. Treatment with recombinant defensin α1, an antimicrobial peptide secreted by Paneth cells, significantly alleviated the adverse effects of Pdia3 deficiency, restoring gut microbiota balance and reducing inflammation in the intestinal I/R injury mice. Taken together, our findings suggest that Pdia3 plays a vital role in maintaining intestinal barrier function and immune defense. Its deficiency exacerbates I/R-induced intestinal damage by impairing epithelial differentiation, mucus production, and antimicrobial peptide secretion. Targeting Pdia3 and associated pathways offers promising therapeutic strategies for mitigating I/R injury and restoring intestinal homeostasis.

Integration of signal transduction pathways in sensory epithelial enteroendocrine cells

The gastrointestinal (GI) tract plays a crucial role in nutrient absorption, motility, and metabolism, while serving as a barrier against pathogens. The intestinal epithelial layer, particularly enteroendocrine cells (EEC), is pivotal in sensing luminal stimuli due to its strategic position. Although comprising only 1% of the GI epithelium, in total EEC comprises perhaps the largest endocrine organ that couples GI luminal stimuli with release of hormones and neurotransmitters such as serotonin, glucagon-like peptide-1 (GLP-1), and peptide-tyrosine-tyrosine (PYY), which regulate local and systemic physiology. In this review, we use EECs as a model to explore critical intracellular signaling pathways-centering around calcium (Ca²⁺) and cyclic adenosine monophosphate (cAMP). EECs utilize ionotropic and metabotropic receptors to detect luminal stimuli, leading to increased intracellular cytoplasmic Ca²⁺ and altered intracellular cAMP dynamics. Ca²⁺ influx is critical for the exocytosis of signaling molecules. The interplay between Ca²⁺ and cAMP signaling pathways enhances the release of these molecules, affecting both local and systemic responses. We make a point to discuss the conventional and emerging methodologies for measuring Ca²⁺ and cAMP dynamics in EECs, which is a rapidly expanding toolbox, containing genetically encoded indicators and resonance energy transfer techniques. Understanding these signaling cascades is essential for deciphering the complex roles of EECs in GI physiology and their impact on systemic health.

scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

Recent advancements in single-cell technologies have enabled comprehensive characterization of cellular states through transcriptomic, epigenomic, and proteomic profiling at single-cell resolution. These technologies have significantly deepened our understanding of cell functions and disease mechanisms from various omics perspectives. As these technologies evolve rapidly and data resources expand, there is a growing need for computational methods that can integrate information from different modalities to facilitate joint analysis of single-cell multi-omics data. However, integrating single-cell omics datasets presents unique challenges due to varied feature correlations and technology-specific limitations. To address these challenges, we introduce scMODAL, a deep learning framework tailored for single-cell multi-omics data alignment using feature links. scMODAL integrates datasets with limited known positively correlated features, leveraging neural networks and generative adversarial networks to align cell embeddings and preserve feature topology. Our experiments demonstrate scMODAL's effectiveness in removing unwanted variation, preserving biological information, and accurately identifying cell subpopulations across diverse datasets. scMODAL not only advances integration tasks but also supports downstream analyses such as feature imputation and feature relationship inference, offering a robust solution for advancing single-cell multi-omics research.

Characterization of Pro-Drug Metabolism and Drug Permeability Kinetics in a Microphysiological In Vitro Model of the Human Small Intestinal Barrier Incorporating Mucus-Generating Cells Coupled with LC-MS/MS Analysis

A micro-physiological model of the human small intestinal barrier incorporating mucus-generating cells has been developed. The established barrier was utilized to assess the absorption kinetics of three selected therapeutic compounds: Doxycycline, Ganciclovir, and its prodrug Valganciclovir, following the implementation of a thorough LC-MS/MS validation protocol. The co-culture of Caco-2 cells, representing absorptive enterocytes, and HT-29 MTX cells, modeling goblet cells, enabled the in-situ generation of a sufficiently thick mucus layer covering the entire cell monolayer. The presence of HT-29 MTX cells, which exhibit weaker tight junctions than enterocytes, contributed to the observed lower transepithelial electrical resistance (TEER) and higher FITC-dextran flux. The permeability of all the compounds was higher when tested in the co-culture system containing mucus-generating cells, compared to the Caco-2 monoculture, demonstrating the impact of mucus on intestinal drug transport kinetics. The permeability of ganciclovir following its generation from the prodrug valganciclovir was significantly higher than the permeability of ganciclovir itself, as the active metabolite ganciclovir exhibited an enhanced transport rate compared to when administered without metabolic activation. The developed microfluidic-based intestinal barrier model has demonstrated the capability to reliably simulate drug absorption and prodrug metabolism, and its impact on drug permeation kinetics across the small intestine.

Accurate Transcription Factor Activity Inference to Decipher Cell Identity from Single-Cell Transcriptomic Data with MetaTF

Cellular heterogeneity within cancer tissues determines cancer progression and treatment response. Single-cell RNA sequencing (scRNA-seq) has provided a powerful approach for investigating the cellular heterogeneity of both cancer cells and stroma cells in the tumor microenvironment. However, the common practice to characterize cell identity based on the similarity of their gene expression profiles may not really indicate distinct cellular populations with unique roles. Generally, the cell identity and function are orchestrated by the expression of given specific genes tightly regulated by transcription factors (TFs). Therefore, deciphering TF activity is essential for gaining a better understanding of the uniqueness and functionality of each cell type. Herein, metaTF, a computational framework designed to infer TF activity in scRNA-seq data, is introduced and existing methods are outperformed for estimating TF activity. It presents the improved effectiveness in characterizing cell identity during mouse hematopoietic stem cell development. Furthermore, metaTF provides a superior characterization of the functional identity of breast cancer epithelial cells, and identifies a novel subset of neural-regulated T cells within the tumor immune microenvironment, which potentially activates BCL6 in response to neural-related signals. Overall, metaTF enables robust TF activity analysis from scRNA-seq data, significantly enhancing the characterization of cell identity and function.

Human intestinal enteroids: Nonclinical applications for predicting oral drug disposition, toxicity, and efficacy

The application of human enteroid systems presents a significant opportunity within the drug development pipeline, highlighting considerable potential for advancements in the characterization and evaluation of new molecular entities. Derived from LGR5+ crypt-based columnar cells, enteroid systems more accurately recapitulate the microanatomy and physiological processes of the human intestinal mucosa compared to traditionally used systems. They contain the complement of major mucosal epithelial cell types, maintain the genetic identity of the donor and intestinal segment they were derived from, and exhibit biological functions and specific activities that are seen in vivo. In this review, we examine the applications of human enteroid systems in nonclinical drug development and compare findings to existing and emerging in vitro models of the small intestine. Specifically, we explore enteroid systems in the context of predicting oral drug disposition, focusing on apparent permeability, intestinal first-pass metabolism, and drug interactions, as well as their utility in assessing drug-induced gastrointestinal toxicity and screening therapeutic efficacy against enteric diseases. Additionally, we highlight aspects of enteroid systems that warrant further study.

Latest Advanced Techniques for Improving Intestinal Organoids Limitations

Intestinal organoids are valuable tools across different disciplines, from a clinical aspect to the biomedical research, providing a unique perspective on the complexity of the gastrointestinal system. They are alternatives to common cell lines as they can offer insights into architectural functionality and reduce the use of animal models. A deeper understanding of their organoid characteristics is required to harness their full potential. Despite their beneficial uses and multiple advantages, organoids have limitations that remain unaddressed. This review aims to elucidate the principal limitations of intestinal organoids, investigate structural defects such as the deficiency in a vascularized and lymphatic system, and absence of the microbiome, restrictions in mimicking the physiological gut model, including the lack of an acid-neutralizing system or a shortage of digestive enzymes, and the difficulties in their long-term maintenance and polarity accessibility. Development of innovative techniques to address these limitations will lead to improve in vivo recapitulation and pioneering further advancements in this field.

Phenotypic heterogeneity and plasticity in colorectal cancer metastasis

Phenotypic heterogeneity and plasticity in colorectal cancer (CRC) has a crucial role in tumor progression, metastasis, and therapy resistance. However, the regulatory factors and the extrinsic signals driving phenotypic heterogeneity remain unknown. Using a combination of single-cell multiomics and spatial transcriptomics data from primary and metastatic CRC patients, we reveal cancer cell states with regenerative and inflammatory phenotypes that closely resemble metastasis-initiating cells in mouse models. We identify an intermediate population with a hybrid regenerative and stem phenotype. We reveal the transcription factors AP-1 and nuclear factor κB (NF-κB) as their key regulators and show localization of these states in an immunosuppressive niche both at the invasive edge in primary CRC and in liver metastasis. We uncover ligand-receptor interactions predicted to activate the regenerative and inflammatory phenotype in cancer cells. Together, our findings reveal regulatory and signaling factors that mediate distinct cancer cell states and can serve as potential targets to impair metastasis.

Spatial and multiomics analysis of human and mouse lung adenocarcinoma precursors reveals TIM-3 as a putative target for precancer interception

How tumor microenvironment shapes lung adenocarcinoma (LUAD) precancer evolution remains poorly understood. Spatial immune profiling of 114 human LUAD and LUAD precursors reveals a progressive increase of adaptive response and a relative decrease of innate immune response as LUAD precursors progress. The immune evasion features align the immune response patterns at various stages. TIM-3-high features are enriched in LUAD precancers, which decrease in later stages. Furthermore, single-cell RNA sequencing (scRNA-seq) and spatial immune and transcriptomics profiling of LUAD and LUAD precursor specimens from 5 mouse models validate high TIM-3 features in LUAD precancers. In vivo TIM-3 blockade at precancer stage, but not at advanced cancer stage, decreases tumor burden. Anti-TIM-3 treatment is associated with enhanced antigen presentation, T cell activation, and increased M1/M2 macrophage ratio. These results highlight the coordination of innate and adaptive immune response/evasion during LUAD precancer evolution and suggest TIM-3 as a potential target for LUAD precancer interception.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Improving Spatial Transcriptomics with Membrane-Based Boundary Definition and Enhanced Single-Cell Resolution

Accurately defining cell boundaries for spatial transcriptomics is technically challenging. The current major approaches are nuclear staining or mathematical inference, which either exclude the cytoplasm or determine a hypothetical boundary. Here, a new method is introduced for defining cell boundaries: labeling cell membranes using genetically coded fluorescent proteins, which allows precise indexing of sequencing spots and transcripts within cells on sections. Use of this membrane-based method greatly increases the number of genes captured in cells compared to the number captured using nucleus-based methods; the numbers of genes are increased by 67% and 119% in mouse and axolotl livers, respectively. The obtained expression profiles are more consistent with single-cell RNA-seq data, demonstrating more rational clustering and apparent cell type-specific markers. Furthermore, improved single-cell resolution is achieved to better identify rare cell types and elaborate spatial domains in the axolotl brain and intestine. In addition to regular cells, accurate recognition of multinucleated cells and cells lacking nuclei in the mouse liver is achieved, demonstrating its ability to analyze complex tissues and organs, which is not achievable using previous methods. This study provides a powerful tool for improving spatial transcriptomics that has broad potential for its applications in the biological and medical sciences.

Dissecting the Single-Cell Diversity and Heterogeneity Underlying Cervical Precancerous Lesions and Cancer Tissues

The underlying cellular diversity and heterogeneity from cervix precancerous lesions to cervical squamous cell carcinoma (CSCC) is investigated. Four single-cell datasets including normal tissues, normal adjacent tissues, precancerous lesions, and cervical tumors were integrated to perform disease stage analysis. Single-cell compositional data analysis (scCODA) was utilized to reveal the compositional changes of each cell type. Differentially expressed genes (DEGs) among cell types were annotated using BioCarta. An assay for transposase-accessible chromatin sequencing (ATAC-seq) analysis was performed to correlate epigenetic alterations with gene expression profiles. Lastly, a logistic regression model was used to assess the similarity between the original and new cohort data (HRA001742). After global annotation, seven distinct cell types were categorized. Eight consensus-upregulated DEGs were identified in B cells among different disease statuses, which could be utilized to predict the overall survival of CSCC patients. Inferred copy number variation (CNV) analysis of epithelial cells guided disease progression classification. Trajectory and ATAC-seq integration analysis identified 95 key transcription factors (TF) and one immunohistochemistry (IHC) testified key-node TF (YY1) involved in epithelial cells from CSCC initiation to progression. The consistency of epithelial cell subpopulation markers was revealed with single-cell sequencing, bulk sequencing, and RT-qPCR detection. KRT8 and KRT15, markers of Epi6, showed progressively higher expression with disease progression as revealed by IHC detection. The logistic regression model testified the robustness of the resemblance of clusters among the various datasets utilized in this study. Valuable insights into CSCC cellular diversity and heterogeneity provide a foundation for future targeted therapy.

A Spatial Multi-Omic Framework Identifies Gliomas Permissive to TIL Expansion

Tumor-infiltrating lymphocyte (TIL) therapy, recently approved by the FDA for melanoma, is an emerging modality for cell-based immunotherapy. However, its application in immunologically "cold" tumors such as glioblastoma remains limited due to sparse T cell infiltration, antigenic heterogeneity, and a suppressive tumor microenvironment. To identify genomic and spatial determinants of TIL expandability, we performed integrated, multimodal profiling of high-grade gliomas using spectral flow cytometry, TCR sequencing, single-cell RNA-seq, Xenium in situ transcriptomics, and CODEX spatial proteomics. Comparative analysis of TIL-generating (TIL+) versus non-generating (TIL-) tumors revealed that IL7Rexpression, structured perivascular immune clustering, and tumor-intrinsic metabolic programs such as ACSS3 were associated with successful TIL expansion. In contrast, TIL-tumors were enriched for neuronal lineage signatures, immunosuppressive transcripts including TOX and FERMT1, and tumor-connected macrophages. This study defines spatial and molecular correlates of TIL manufacturing success and establishes a genomics-enabled selection platform for adoptive T cell therapy. The profiling approach is now being prospectively implemented in the GIANT clinical trial (NCT06816927), supporting its translational relevance and scalability across glioblastoma and other immune-excluded cancers.

Deconvolution of cell types and states in spatial multiomics utilizing TACIT

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we develop TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000 cells; 51 cell types) from three niches (brain, intestine, gland), TACIT outperforms existing unsupervised methods in accuracy and scalability. Integrating TACIT-identified cell types reveals new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

A Spatial Multi-Omic Framework Identifies Gliomas Permissive to TIL Expansion

Tumor-infiltrating lymphocyte (TIL) therapy, recently approved by the FDA for melanoma, is an emerging modality for cell-based immunotherapy. However, its application in immunologically 'cold' tumors such as glioblastoma remains limited due to sparse T cell infiltration, antigenic heterogeneity, and a suppressive tumor microenvironment. To identify genomic and spatial determinants of TIL expandability, we performed integrated, multimodal profiling of high-grade gliomas using spectral flow cytometry, TCR sequencing, single-cell RNA-seq, Xenium in situ transcriptomics, and CODEX spatial proteomics. Comparative analysis of TIL-generating (TIL+) versus non-generating (TIL-) tumors revealed that IL7R expression, structured perivascular immune clustering, and tumor-intrinsic metabolic programs such as ACSS3 were associated with successful TIL expansion. In contrast, TIL-; tumors were enriched for neuronal lineage signatures, immunosuppressive transcripts including TOX and FERMT1, and tumor-connected macrophages. This study defines spatial and molecular correlates of TIL manufacturing success and establishes a genomics-enabled selection platform for adoptive T cell therapy. The profiling approach is now being prospectively implemented in the GIANT clinical trial ( NCT06816927 ), supporting its translational relevance and scalability across glioblastoma and other immune-excluded cancers.

Interferon-responsive intestinal BEST4/CA7+ cells are targets of bacterial diarrheal toxins

BEST4/CA7+ cells of the human intestine were recently identified by single-cell RNA sequencing. While their gene expression profile predicts a role in electrolyte balance, BEST4/CA7+ cell function has not been explored experimentally owing to the absence of BEST4/CA7+ cells in mice and the paucity of human in vitro models. Here, we establish a protocol that allows the emergence of BEST4/CA7+ cells in human intestinal organoids. Differentiation of BEST4/CA7+ cells requires activation of Notch signaling and the transcription factor SPIB. BEST4/CA7+ cell numbers strongly increase in response to the cytokine interferon-γ, supporting a role in immunity. Indeed, we demonstrate that BEST4/CA7+ cells generate robust CFTR-mediated fluid efflux when stimulated with bacterial diarrhea-causing toxins and find the norepinephrine-ADRA2A axis as a potential mechanism in blocking BEST4/CA7+ cell-mediated fluid secretion. Our observations identify a central role of BEST4/CA7+ cells in fluid homeostasis in response to bacterial infections.

Functional maturation of preterm intestinal epithelium through CFTR activation

Preterm birth disrupts intestinal epithelial maturation, impairing digestive and absorptive functions. This study integrates analysis of single-cell RNA sequencing datasets, spanning fetal to adult stages, with human preterm intestinal models derived from the ileal tissue of preterm infants. We investigate the potential of extracellular vesicles (EVs) derived from human Wharton's jelly mesenchymal stem cells to promote intestinal maturation. Distinct enterocyte differentiation trajectories are identified during the transition from immature to mature stages of human intestinal development. EV treatment, particularly with the EV39 line, significantly upregulates maturation-specific gene expression related to enterocyte function. Gene set enrichment analysis reveals an enrichment of TGFβ1 signaling pathways, and proteomic analysis identifies TGFβ1 and FGF2 as key mediators of EV39's effects. These treatments enhance cell proliferation, epithelial barrier integrity, and fatty acid uptake, primarily through CFTR-dependent mechanisms-unique to human preterm models, not observed in mouse intestinal organoids. This highlights the translational potential of EV39 and CFTR activation in promoting the functional maturation of the premature human intestine.

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage

The Human BioMolecular Atlas Program (HuBMAP) aims to construct a 3D Human Reference Atlas (HRA) of the healthy adult body. Experts from 20+ consortia collaborate to develop a Common Coordinate Framework (CCF), knowledge graphs and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes and biomarkers) and to use the HRA to characterize changes that occur with aging, disease and other perturbations. HRA v.2.0 covers 4,499 unique anatomical structures, 1,195 cell types and 2,089 biomarkers (such as genes, proteins and lipids) from 33 ASCT+B tables and 65 3D Reference Objects linked to ontologies. New experimental data can be mapped into the HRA using (1) cell type annotation tools (for example, Azimuth), (2) validated antibody panels or (3) by registering tissue data spatially. This paper describes HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interfaces, flexible hybrid cloud infrastructure and previews atlas usage applications.

Quantitative characterization of tissue states using multiomics and ecological spatial analysis

The spatial organization of cells in tissues underlies biological function, and recent advances in spatial profiling technologies have enhanced our ability to analyze such arrangements to study biological processes and disease progression. We propose MESA (multiomics and ecological spatial analysis), a framework drawing inspiration from ecological concepts to delineate functional and spatial shifts across tissue states. MESA introduces metrics to systematically quantify spatial diversity and identify hot spots, linking spatial patterns to phenotypic outcomes, including disease progression. Furthermore, MESA integrates spatial and single-cell multiomics data to facilitate an in-depth, molecular understanding of cellular neighborhoods and their spatial interactions within tissue microenvironments. Applying MESA to diverse datasets demonstrates additional insights it brings over prior methods, including newly identified spatial structures and key cell populations linked to disease states. Available as a Python package, MESA offers a versatile framework for quantitative decoding of tissue architectures in spatial omics across health and disease.

Genome-wide association meta-analysis identifies 126 novel loci for diverticular disease and implicates connective tissue and colonic motility

Diverticular disease is a common and morbid complex phenotype influenced by both innate and environmental risk factors. We performed the largest genome-wide association study meta-analysis for diverticular disease, identifying 126 novel loci. Employing multiple downstream analytic strategies, including tissue and pathway enrichment, statistical fine-mapping, allele-specific expression, protein quantitative trait loci and drug-target investigations, and linkage disequilibrium score regression, we prioritized causal genes and produced several lines of evidence linking diverticular disease to connective tissue biology and colonic motility. We substantiated these findings by integrating single-cell RNA sequencing data, showing that prioritized diverticular disease-associated genes are enriched for expression in colonic smooth muscle, fibroblasts, and interstitial cells of Cajal. In quantitative analysis of surgical specimens, we found a substantial reduction in the density of elastin present in the sigmoid colon in severe diverticulitis.

Spatial mapping of immune cell environments in NF2-related schwannomatosis vestibular schwannoma

NF2-related Schwannomatosis (NF2 SWN) is a rare disease characterised by the growth of multiple nervous system neoplasms, including bilateral vestibular schwannoma (VS). VS tumours are characterised by extensive leucocyte infiltration. However, the immunological landscape in VS and the spatial determinants within the tumour microenvironment that shape the trajectory of disease are presently unknown. In this study, to elucidate the complex immunological networks across VS, we performed imaging mass cytometry (IMC) on clinically annotated VS samples from NF2 SWN patients. We reveal the heterogeneity in neoplastic cell, myeloid cell and T cell populations that co-exist within VS, and that distinct myeloid cell and Schwann cell populations reside within varied spatial contextures across characteristic Antoni A and B histomorphic niches. Interestingly, T-cell populations co-localise with tumour-associated macrophages (TAMs) in Antoni A regions, seemingly limiting their ability to interact with tumorigenic Schwann cells. This spatial landscape is altered in Antoni B regions, where T-cell populations appear to interact with PD-L1+ Schwann cells. We also demonstrate that prior bevacizumab treatment (VEGF-A antagonist) preferentially reduces alternatively activated-like TAMs, whilst enhancing CD44 expression, in bevacizumab-treated tumours. Together, we describe niche-dependent modes of T-cell regulation in NF2 SWN VS, indicating the potential for microenvironment-altering therapies for VS.

Miniature chicken ileal explant culture to investigate the inflammatory response induced by pathogen-associated molecular patterns

Gastrointestinal inflammation leads to maldigestion and systemic diseases in poultry. To tackle the problem of the industry and to search for therapeutic candidates in vitro models are inevitable. Both immersion and air-liquid interface explant models are available, although there is limited information on the size-dependent applicability and response to different pathogen-associated molecular patterns (PAMPs) in the case of these model systems. The study aimed to compare the morphology and viability of miniature chicken gut explant cultures obtained with a biopsy punch to examine the size-dependent change over time. To verify the applicability of the model, pathogen-associated molecular patterns (PAMPs): flagellin, lipoteichoic acid (LTA) and polyinosinic polycytidylic acid (poly I:C) were applied to induce inflammation. The 2 mm diameter explants showed a decrease in metabolic activity measured by CCK-8 assay after 12 h and a significantly higher extracellular lactate dehydrogenase activity indicating cellular damage compared to the 1 mm explants, supported by histological differences after 24 h of culturing. After 12 h of incubation, the 1.5 mm explants retained columnar epithelial lining with moderate damage of the lamina propria (H&E and pan-cytokeratin staining). Exposure to 100 μg/mL poly I:C reduced the metabolic activity of the 1.5 mm explants. LTA and poly I:C increased IFN-γ concentration at both applied doses and IFN-α concentration was elevated by 50 μg/mL poly I:C treatment. Flagellin administration raised IL-2, IL-6, and RANTES levels, while higher LTA and poly I:C concentrations increased the IFN-γ/IL-10 ratio. According to the observations, the viability and integrity of the explants decreases with their size. After 12 h, the 1.5 mm diameter miniature chicken ileal explant stimulated with PAMPs can be an appropriate model to mimic diseases involving tissue damage and inflammation.

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data

MOTIVATION

Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods.

RESULTS

We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets.

AVAILABILITY AND IMPLEMENTATION

Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

AI-driven 3D bioprinting for regenerative medicine: From bench to bedside

In recent decades, 3D bioprinting has garnered significant research attention due to its ability to manipulate biomaterials and cells to create complex structures precisely. However, due to technological and cost constraints, the clinical translation of 3D bioprinted products (BPPs) from bench to bedside has been hindered by challenges in terms of personalization of design and scaling up of production. Recently, the emerging applications of artificial intelligence (AI) technologies have significantly improved the performance of 3D bioprinting. However, the existing literature remains deficient in a methodological exploration of AI technologies' potential to overcome these challenges in advancing 3D bioprinting toward clinical application. This paper aims to present a systematic methodology for AI-driven 3D bioprinting, structured within the theoretical framework of Quality by Design (QbD). This paper commences by introducing the QbD theory into 3D bioprinting, followed by summarizing the technology roadmap of AI integration in 3D bioprinting, including multi-scale and multi-modal sensing, data-driven design, and in-line process control. This paper further describes specific AI applications in 3D bioprinting's key elements, including bioink formulation, model structure, printing process, and function regulation. Finally, the paper discusses current prospects and challenges associated with AI technologies to further advance the clinical translation of 3D bioprinting.

Profiling immune cell tissue niches in the spatial -omics era

Immune responses require complex, spatially coordinated interactions between immune cells and their tissue environment. For decades, we have imaged tissue sections to visualize a limited number of immune-related macromolecules in situ, functioning as surrogates for cell types or processes of interest. However, this inevitably provides a limited snapshot of the tissue's immune landscape. Recent developments in high-throughput spatial -omics technologies, particularly spatial transcriptomics, and its application to human samples has facilitated a more comprehensive understanding of tissue immunity by mapping fine-grained immune cell states to their precise tissue location while providing contextual information about their immediate cellular and tissue environment. These data provide opportunities to investigate mechanisms underlying the spatial distribution of immune cells and its functional implications, including the identification of immune niches, although the criteria used to define this term have been inconsistent. Here, we review recent technological and analytic advances in multiparameter spatial profiling, focusing on how these methods have generated new insights in translational immunology. We propose a 3-step framework for the definition and characterization of immune niches, which is powerfully facilitated by new spatial profiling methodologies. Finally, we summarize current approaches to analyze adaptive immune repertoires and lymphocyte clonal expansion in a spatially resolved manner.

Host-directed therapies modulating innate immunity against infection in hematologic malignancies

Patients with hematologic malignancies (HM) are highly susceptible to bloodstream infection (BSI), particularly those undergoing treatments such as chemotherapy. A common and debilitating side effect of chemotherapy is oral and intestinal mucositis. These Patients are also at high risk of developing sepsis, which can arise from mucosal barrier injuries and significantly increases mortality in these patients. While conventional antibiotics are effective, their use can lead to antimicrobial resistance (AMR) and disrupt the gut microbiota (dysbiosis). In this review, we discuss utilizing host defense peptides (HDPs), key components of the innate immune system, and immune system inducers (ISIs) to maintain mucosal barrier integrity against infection, an underexplored host-directed therapy (HDT) approach to prevent BSI and sepsis. We advocate for the discovery of potent and safe ISIs for clinical use and call for further research into the mechanisms by which these ISIs induce HDPs and strengthen mucosal barriers.

Encapsulated hesperetin modulates inflammatory responses in an in vitro intestinal immune co-culture model

In vitro cell models are an effective way to evaluate the biological activities of functional compounds. Hesperetin (HST) is a flavanone with various potential health-related benefits, and encapsulation improved its stability and bioavailability. This study aimed to investigate the anti-inflammatory effects of encapsulated HST using different delivery systems, including β-cyclodextrin (CD), nanoliposomes (NL), and NL coated with chitosan (CH) and carrageenan (CGN). A Caco-2 and THP-1 co-culture model characterized by direct cell-to-cell contact was developed, and these delivery systems were digested in vitro and subsequently tested on this model. The addition of lipopolysaccharide (LPS) in the model resulted in high secretion of the pro-inflammatory cytokines (IL-8, TNF-α, and IL-1β), the upregulation of the phenotype genes (CD68 and CD80) and the inflammation-related genes (MYD88, NFκB, and COX-2), marking the differentiation of M0 macrophages into M1 macrophages. Among the delivery systems, HST encapsulated in CH and CGN coated NL (CGN-CH-NL-HST) was the most effective in suppressing the production of IL-8 and expression of MYD88 and COX-2 in the inflammatory co-culture model. Metabolomic data showed that the M1 macrophage metabolic profile was changed by applying free HST and encapsulated HST, mostly in glycolysis and amino acid metabolism. Encapsulated HST in the CGN-CH-NL delivery system showed anti-inflammatory activity in the Caco-2 and THP-1 direct co-culture model, suggesting a potential of encapsulated bioactive compounds in treating inflammatory bowel disease.

Tissue-resident memory CD8 T cell diversity is spatiotemporally imprinted

Tissue-resident memory CD8 T (TRM) cells provide protection from infection at barrier sites. In the small intestine, TRM cells are found in at least two distinct subpopulations: one with higher expression of effector molecules and another with greater memory potential1. However, the origins of this diversity remain unknown. Here we proposed that distinct tissue niches drive the phenotypic heterogeneity of TRM cells. To test this, we leveraged spatial transcriptomics of human samples, a mouse model of acute systemic viral infection and a newly established strategy for pooled optically encoded gene perturbations to profile the locations, interactions and transcriptomes of pathogen-specific TRM cell differentiation at single-transcript resolution. We developed computational approaches to capture cellular locations along three anatomical axes of the small intestine and to visualize the spatiotemporal distribution of cell types and gene expression. Our study reveals that the regionalized signalling of the intestinal architecture supports two distinct TRM cell states: differentiated TRM cells and progenitor-like TRM cells, located in the upper villus and lower villus, respectively. This diversity is mediated by distinct ligand-receptor activities, cytokine gradients and specialized cellular contacts. Blocking TGFβ or CXCL9 and CXCL10 sensing by antigen-specific CD8 T cells revealed a model consistent with anatomically delineated, early fate specification. Ultimately, our framework for the study of tissue immune networks reveals that T cell location and functional state are fundamentally intertwined.

Organoids from pluripotent stem cells and human tissues: When two cultures meet each other

Human organoids are a widely used tool in cell biology to study homeostatic processes, disease, and development. The term organoids covers a plethora of model systems from different cellular origins that each have unique features and applications but bring their own challenges. This review discusses the basic principles underlying organoids generated from pluripotent stem cells (PSCs) as well as those derived from tissue stem cells (TSCs). We consider how well PSC- and TSC-organoids mimic the different intended organs in terms of cellular complexity, maturity, functionality, and the ongoing efforts to constitute predictive complex models of in vivo situations. We discuss the advantages and limitations associated with each system to answer different biological questions including in the field of cancer and developmental biology, and with respect to implementing emerging advanced technologies, such as (spatial) -omics analyses, CRISPR screens, and high-content imaging screens. We postulate how the two fields may move forward together, integrating advantages of one to the other.

STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance

Motivation

Spatial transcriptomic technologies allow researchers to explore the diversity and specificity of gene expression within their original tissue structure. Accurately identifying regions that are spatially coherent in both gene expression and physical tissue structures is an emerging topic, but challenging due to the lack of ground truth labels which renders complicating validation of clustering consistency and reproducibility. This highlights a need for a computational evaluation framework to rigorously and unbiasedly assess clustering performance.

Results

To address this gap, we propose STEAM (Spatial Transcriptomics Evaluation Algorithm and Metric), a user-friendly computational pipeline designed to evaluate the consistency and reliability of clustering results by leveraging machine learning classification and prediction methods, with the goal of maintaining the spatial proximity and gene expression patterns within clusters. We benchmarked STEAM on various public datasets, spanning multi-cell to single-cell resolution, as well as spatial transcriptomics and proteomics. The results highlighted its robustness and generalizability through comprehensive statistical evaluation metrics, such as Kappa score, F1 score, accuracy, and adjusted rand index. Notably, STEAM supports multi-sample training, enabling cross-replicate clustering consistency assessment. Moreover, STEAM provides practical guidance by comparing clustering results across multiple approaches; here, we evaluated four different methods, including spatial-aware and spatial-ignorant approaches. In summary, we believe that STEAM provides researchers a promising tool for evaluating clustering robustness and benchmarking clustering performance for spatial omics data, offering valuable insights to drive reproducible discoveries in spatial biology.

Availability and implementation

Source code and the R software tool STEAM are available from https://github.com/fanzhanglab/STEAM .

Functional tissue units in the Human Reference Atlas

Functional tissue units form the basic building blocks of organs and are important for understanding and modeling the healthy physiological function of the organ and changes that occur during disease states. In this comprehensive catalog of 22 anatomically based, nested functional tissue units from 10 healthy human organs, we document the definition, physical dimensions, blood vasculature connections, and cellular composition. All anatomy terms are mapped to the multi-species Uber-anatomy Ontology (Uberon) and cells are mapped to Cell Ontology to support computational access via standardized metadata. The catalog includes datasets, illustrations, and a large printable poster illustrating how the blood vasculature connects the 22 functional tissue units in 10 organs. All data and code are freely available. The work is part of an ongoing international effort to construct a Human Reference Atlas of the 37 trillion cells that make up the healthy human body.

Single-cell omics in inflammatory bowel disease: recent insights and future clinical applications

Inflammatory bowel diseases (IBDs), which include ulcerative colitis (UC) and Crohn's disease (CD), are chronic conditions characterised by inflammation of the intestinal tract. Alterations in virtually all intestinal cell types, including immune, epithelial and stromal cells, have been described in these diseases. The study of IBD has historically relied on bulk transcriptomics, but this method averages signals across diverse cell types, limiting insights. Single-cell omic technologies overcome the intrinsic limitations of bulk analysis and reveal the complexity of multicellular tissues at a cell-by-cell resolution. Within healthy and inflamed intestinal tissues, single-cell omics, particularly single-cell RNA sequencing, have contributed to uncovering novel cell types and cell functions linked to disease activity or the development of complications. Collectively, these results help identify therapeutic targets in difficult-to-treat complications such as fibrostenosis, creeping fat accumulation, perianal fistulae or inflammation of the pouch. More recently, single-cell omics have gradually been adopted in studies to understand therapeutic responses, identify mechanisms of drug failure and potentially develop predictors with clinical utility. Although these are early days, such studies lay the groundwork for the implementation in clinical practice of new technologies in diagnostics, monitoring and prediction of disease prognosis. With this review, we aim to provide a comprehensive survey of the studies that have applied single-cell omics to the study of UC or CD, and offer our perspective on the main findings these studies contribute. Finally, we discuss the limitations and potential benefits that the integration of single-cell omics into clinical practice and drug development could offer.

Disruption of serotonin homeostasis in intestinal organoids provides insights into drug-induced gastrointestinal toxicity

Drug-induced gastrointestinal toxicity is a frequent clinical adverse event that needs to be carefully monitored and managed to ensure patient compliance. While preclinical assessment of drug-induced gastrointestinal toxicity mostly relies on animal experimentation, intestinal organoids have gained increasing attention to identify gastrointestinal toxicants in vitro. Nonetheless, current in vitro protocols primarily assess structural alterations induced by drugs, whereas gastrointestinal adverse events can often stem from functional disturbances. Disruption of serotonin signaling in the gastrointestinal tract is associated with impaired motility, as well as nausea and vomiting. We aimed to investigate alterations of serotonin homeostasis in organoids derived from the canine small intestine as a driver of drug-induced gastrointestinal toxicity. Treatment of the organoids with a compound (NVS-1) inducing acute gastrointestinal toxicity in dogs as well as with three tyrosine kinase inhibitors with known preclinical and clinical gastrointestinal adverse effects (afatinib, crizotinib and vandetanib) led to increased supernatant serotonin levels. Mechanistic assays showed that, while NVS-1 and afatinib stimulate serotonin release, crizotinib and vandetanib inhibit serotonin re-uptake via direct inhibition of the serotonin re-uptake transporter. Using a data mining approach, we further suggest that inhibition of serotonin re-uptake could contribute to gastrointestinal toxicity observed with multiple marketed drugs. In conclusion, we present the implementation of a novel in vitro gastrointestinal toxicity endpoint that could complement current methods and serve as a mechanistic and predictive/screening tool for drug-induced gastrointestinal toxicity.

Recent advancement in the spatial immuno-oncology

Recent advancements in spatial transcriptomics and spatial proteomics enabled the high-throughput profiling of single or multi-cell types and cell states with spatial information. They transformed our understanding of the higher-order architectures and paired cell-cell interactions within a tumor microenvironment (TME). Within less than a decade, this rapidly emerging field has discovered much crucial fundamental knowledge and significantly improved clinical diagnosis in the field of immuno-oncology. This review summarizes the conceptual frameworks to understand spatial omics data and highlights the updated knowledge of spatial immuno-oncology.

A multi-omics spatial framework for host-microbiome dissection within the intestinal tissue microenvironment

The intricate interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host and microbiome across multiple spatial modalities. We demonstrate MicroCart by investigating gut host and microbiome changes in a murine colitis model, using spatial proteomics, transcriptomics, and glycomics. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multi-omics.

Polygonatum kingianum polysaccharide alleviated intestinal injuries by mediating antioxidant ability and microbiota

Introduction

Polygonatum kingianum is a well-known medicinal herb with proven bioactivities; however, little is known about the effects of its polysaccharide on intestinal injuries in animals induced by lipopolysaccharide (LPS).

Methods

A total of 30 Institute of Cancer Research (ICR) mice were divided into control (CH), induced (MH), and treated (H) groups. Mice in group H were supplemented with 100 mg/kg Polygonatum kingianum polysaccharides, while groups C and M were treated with the same amount of normal saline by gavage for 18 days. On the 18th day animals in groups M and H were induced by LPS (10 mg/kg).

Results

The results showed the weight of mice in group MH significantly dropped (P < 0.0001), while mice in the PK group had a higher weight (P < 0.01). Pathological analysis found that the majority of the villi in mice induced by LPS were broken and short, while PK-treated animals had longer and considerably integrated villi. The villi length in groups CH (P < 0.0001) and H (P < 0.0001) was longer than that in group M, and the value of villi length/crypt depth in group MH was smaller than that in groups CH (P < 0.0001) and H (P < 0.0001), while the crypt depth in group MH was higher than in groups CH (P < 0.0001) and H (P < 0.0001). Serum inspection showed that MAD (P < 0.05), IL-1β (P < 0.05), IL-6 (P < 0.05), and TNF-α (P < 0.01) were significantly higher in group MH, while SOD (P < 0.001), T-AOC (P < 0.01), and GSH-Px (P < 0.01) were notably higher in groups CH and H. Microbiome sequencing of mice obtained 844,477 raw and 725,469 filtered reads. There were 2,407 ASVs detected in animals, and there were 312 and 328 shared ASVs between CH and MH, and CH and H, respectively. There were 5 phyla and 20genera of remarkable bacteria found among mice groups including genera of Escherichia, Pseudomonas_E, Mailhella, Paramuribaculum, NM07-P-09, Odoribacter, Nanosyncoccus, SFM01, Onthenecus, Clostridium_Q, UBA6985, Ructibacterium, UBA946, Lachnoclostridium_B, Evtepia, CAG-269, Limivicinus, Formimonas, Dehalobacterium, Dwaynesavagella, and UBA6985. We revealed that Polygonatum kingianum polysaccharide could alleviate intestinal injuries by promoting oxidation resistance, decreasing inflammatory responses, and accommodating the intestinal microbiota of mice.

Discussion

Our results suggest the possibility of developing novel therapies for intestinal diseases.

mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite generates a local immunostimulatory niche for cancer immunotherapy

Hydrogel materials have emerged as versatile platforms for various biomedical applications. Notably, the engineered nanofiber-hydrogel composite (NHC) has proven effective in mimicking the soft tissue extracellular matrix, facilitating substantial recruitment of host immune cells and the formation of a local immunostimulatory microenvironment. Leveraging this feature, here we report an mRNA lipid nanoparticle (LNP)-incorporated NHC microgel matrix, termed LiNx, by incorporating LNPs loaded with mRNA encoding tumour antigens. Harnessing the potent transfection efficiency of LNPs in antigen-presenting cells (APCs), LiNx demonstrates remarkable immune cell recruitment, antigen expression and presentation, and cellular interaction. These attributes collectively create an immunostimulating milieu and yield a potent immune response achievable with a single dose, comparable to the conventional three-dose LNP immunization regimen. Further investigations reveal that the LiNx not only generates heightened Th1 and Th2 responses but also elicits a distinctive Type 17 T helper cell-mediated response pivotal for bolstering antitumour efficacy. Our findings elucidate the mechanism underlying LiNx's role in potentiating antigen-specific immune responses, presenting a new strategy for cancer immunotherapy.

Bionic Recognition Technologies Inspired by Biological Mechanosensory Systems

Mechanical information is a medium for perceptual interaction and health monitoring of organisms or intelligent mechanical equipment, including force, vibration, sound, and flow. Researchers are increasingly deploying mechanical information recognition technologies (MIRT) that integrate information acquisition, pre-processing, and processing functions and are expected to enable advanced applications. However, this also poses significant challenges to information acquisition performance and information processing efficiency. The novel and exciting mechanosensory systems of organisms in nature have inspired us to develop superior mechanical information bionic recognition technologies (MIBRT) based on novel bionic materials, structures, and devices to address these challenges. Herein, first bionic strategies for information pre-processing are presented and their importance for high-performance information acquisition is highlighted. Subsequently, design strategies and considerations for high-performance sensors inspired by mechanoreceptors of organisms are described. Then, the design concepts of the neuromorphic devices are summarized in order to replicate the information processing functions of a biological nervous system. Additionally, the ability of MIBRT is investigated to recognize basic mechanical information. Furthermore, further potential applications of MIBRT in intelligent robots, healthcare, and virtual reality are explored with a view to solve a range of complex tasks. Finally, potential future challenges and opportunities for MIBRT are identified from multiple perspectives.

Multiomic analysis reveals cellular, transcriptomic and epigenetic changes in intestinal pouches of ulcerative colitis patients

Total proctocolectomy with ileal pouch anal anastomosis is the standard of care for patients with severe ulcerative colitis. We generated a cell-type-resolved transcriptional and epigenetic atlas of ileal pouches using scRNA-seq and scATAC-seq data from paired biopsy samples of the ileal pouch and the ileal segment above the pouch (pre-pouch) from patients (male=4, female=2), and paired biopsies of the terminal ileum and ascending colon from healthy individuals (male=3, female=3) serving as reference. Our study finds an additional population of absorptive and secretory epithelial cells within the pouch but not the pre-pouch. These pouch-specific enterocytes express a subset of colon-specific genes, including CEACAM5 and CD24. However, compared to normal colonocytes, expression of these genes is lower, and these enterocytes also express inflammatory and secretory genes while maintaining expression of some ileal-specific genes. This cell-type-resolved transcriptomic and epigenetic atlas of the ileal pouch establishes a reference for investigating pouch physiology and pathology.

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single voxels dissected by LCM to the tube cap and SOP voxel processing in the same collection cap. This method enables reproducible, label-free quantification of approximately 900 and 4600 proteins for single voxels at 20 µm × 20 µm × 10 µm (~1 cell region) and 200 µm × 200 µm × 10 µm (~100 cell region) from fresh frozen human spleen tissue, respectively. It can reveal spatially resolved protein signatures and region-specific signaling pathways. Furthermore, wcSOP-MS is demonstrated to be broadly applicable for OCT-embedded and FFPE human archived tissues as well as for small-scale 2D proteome mapping of tissues at high spatial resolutions. wcSOP-MS may pave the way for routine robust single voxel proteomics and spatial proteomics.

Multiomic analysis reveals cellular, transcriptomic and epigenetic changes in intestinal pouches of ulcerative colitis patients

Total proctocolectomy with ileal pouch anal anastomosis is the standard of care for patients with severe ulcerative colitis. We generated a cell-type-resolved transcriptional and epigenetic atlas of ileal pouches using scRNA-seq and scATAC-seq data from paired biopsy samples of the ileal pouch and the ileal segment above the pouch (pre-pouch) from patients (male=4, female=2), and paired biopsies of the terminal ileum and ascending colon from healthy individuals (male=3, female=3) serving as reference. Our study finds previously uncharacterized populations of absorptive and secretory epithelial cells within the pouch but not the pre-pouch. These pouch-specific enterocytes express a subset of colon-specific genes, including CEACAM5 and CD24. However, compared to normal colonocytes, expression of these genes is lower, and these enterocytes also express inflammatory and secretory genes while maintaining expression of some ileal-specific genes. This cell-type-resolved transcriptomic and epigenetic atlas of the ileal pouch establishes a reference for investigating pouch physiology and pathology.

Integrin-activating Yersinia protein Invasin sustains long-term expansion of primary epithelial cells as 2D organoid sheets

Matrigel®/BME®, a basement membrane-like preparation, supports long-term growth of epithelial 3D organoids from adult stem cells [T. Sato et al., Nature 459, 262-265 (2009); T. Sato et al., Gastroenterology 141, 1762-1772 (2011)]. Here, we show that interaction between Matrigel's major component laminin-111 with epithelial α6β1-integrin is crucial for this process. The outer membrane protein Invasin of Yersinia is known to activate multiple integrin-β1 complexes, including integrin α6β1. A C-terminal integrin-binding fragment of Invasin, coated on culture plates, mediated gut epithelial cell adhesion. Addition of organoid growth factors allowed multipassage expansion in 2D. Polarization, junction formation, and generation of enterocytes, goblet cells, Paneth cells, and enteroendocrine cells were stable over time. Sustained expansion of other human, mouse, and even snake epithelia was accomplished under comparable conditions. The 2D "organoid sheet" format holds advantages over the 3D "in gel" format in terms of imaging, accessibility of basal and apical domains, and automation for high-throughput screening. Invasin represents a fully defined, affordable, versatile, and animal-free complement to Matrigel®/BME®.

scProAtlas: an atlas of multiplexed single-cell spatial proteomics imaging in human tissues

Spatial proteomics can visualize and quantify protein expression profiles within tissues at single-cell resolution. Although spatial proteomics can only detect a limited number of proteins compared to spatial transcriptomics, it provides comprehensive spatial information with single-cell resolution. By studying the spatial distribution of cells, we can clearly obtain the spatial context within tissues at multiple scales. Spatial context includes the spatial composition of cell types, the distribution of functional structures, and the spatial communication between functional regions, all of which are crucial for the patterns of cellular distribution. Here, we constructed a comprehensive spatial proteomics functional annotation knowledgebase, scProAtlas (https://relab.xidian.edu.cn/scProAtlas/#/), which is designed to help users comprehensively understand the spatial context within different tissue types at single-cell resolution and across multiple scales. scProAtlas contains multiple modules, including neighborhood analysis, proximity analysis and neighborhood network, to comprehensively construct spatial cell maps of tissues and multi-modal integration, spatial gene identification, cell-cell interaction and spatial pathway analysis to display spatial variable genes. scProAtlas includes data from eight spatial protein imaging techniques across 15 tissues and provides detailed functional annotation information for 17 468 394 cells from 945 region of interests. The aim of scProAtlas is to offer a new insight into the spatial structure of various tissues and provides detailed spatial functional annotation.

Characterizing cell-type spatial relationships across length scales in spatially resolved omics data

Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we present CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package. To demonstrate the utility of such multi-scale characterization, recapitulate expected cell-type spatial relationships, and evaluate against other cell-type spatial analyses, we apply CRAWDAD to various simulated and real SRO datasets of diverse tissues assayed by diverse SRO technologies. We further demonstrate how such multi-scale characterization enabled by CRAWDAD can be used to compare cell-type spatial relationships across multiple samples. Finally, we apply CRAWDAD to SRO datasets of the human spleen to identify consistent as well as patient and sample-specific cell-type spatial relationships. In general, we anticipate such multi-scale analysis of SRO data enabled by CRAWDAD will provide useful quantitative metrics to facilitate the identification, characterization, and comparison of cell-type spatial relationships across axes of interest.

Control of Cellular Differentiation Trajectories for Cancer Reversion

Cellular differentiation is controlled by intricate layers of gene regulation, involving the modulation of gene expression by various transcriptional regulators. Due to the complexity of gene regulation, identifying master regulators across the differentiation trajectory has been a longstanding challenge. To tackle this problem, a computational framework, single-cell Boolean network inference and control (BENEIN), is presented. Applying BENEIN to human large intestinal single-cell transcriptome data, MYB, HDAC2, and FOXA2 are identified as the master regulators whose inhibition induces enterocyte differentiation. It is found that simultaneous knockdown of these master regulators can revert colorectal cancer cells into normal-like enterocytes by synergistically inducing differentiation and suppressing malignancy, which is validated by in vitro and in vivo experiments.