Organization of the human intestine at single-cell resolution

Tissue and cellular spatiotemporal dynamics in colon aging

Tissue structure and molecular circuitry in the colon can be profoundly impacted by systemic age-related effects, but many of the underlying molecular cues remain unclear. Here, we built a cellular and spatial atlas of the colon across three anatomical regions and 11 age groups, encompassing ~1,500 mouse gut tissues profiled by spatial transcriptomics and ~400,000 single nucleus RNA-seq profiles. We developed a new computational framework, cSplotch, which learns a hierarchical Bayesian model of spatially resolved cellular expression associated with age, tissue region, and sex, by leveraging histological features to share information across tissue samples and data modalities. Using this model, we identified cellular and molecular gradients along the adult colonic tract and across the main crypt axis, and multicellular programs associated with aging in the large intestine. Our multi-modal framework for the investigation of cell and tissue organization can aid in the understanding of cellular roles in tissue-level pathology.

Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here, we integrated CODEX multiplexed tissue imaging with multiscale modeling software to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface. A record of this paper's transparent peer review process is included in the supplemental information.

scAnnoX: an R package integrating multiple public tools for single-cell annotation

Background

Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking.

Methods

This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms. Ten single-cell annotation algorithms were selected based on the classification of either reference dataset-dependent or marker gene-dependent approaches. These algorithms included SingleR, Seurat, sciBet, scmap, CHETAH, scSorter, sc.type, cellID, scCATCH, and SCINA. Building upon these algorithms, we developed an R package named scAnnoX for the integration and comparative analysis of single-cell annotation algorithms.

Results

The development of the scAnnoX software package provides a cohesive framework for annotating cells in scRNA-seq data, enabling researchers to more efficiently perform comparative analyses among the cell type annotations contained in scRNA-seq datasets. The integrated environment of scAnnoX streamlines the testing, evaluation, and comparison processes among various algorithms. Among the ten annotation tools evaluated, SingleR, Seurat, sciBet, and scSorter emerged as top-performing algorithms in terms of prediction accuracy, with SingleR and sciBet demonstrating particularly superior performance, offering guidance for users. Interested parties can access the scAnnoX package at https://github.com/XQ-hub/scAnnoX.

Functional Diversity of Memory CD8 T Cells is Spatiotemporally Imprinted

Tissue-resident memory CD8 T cells (TRM) kill infected cells and recruit additional immune cells to limit pathogen invasion at barrier sites. Small intestinal (SI) TRM cells consist of distinct subpopulations with higher expression of effector molecules or greater memory potential. We hypothesized that occupancy of diverse anatomical niches imprints these distinct TRM transcriptional programs. We leveraged human samples and a murine model of acute systemic viral infection to profile the location and transcriptome 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. TRM populations were spatially segregated: with more effector- and memory-like TRM preferentially localized at the villus tip or crypt, respectively. Modeling ligand-receptor activity revealed patterns of key cellular interactions and cytokine signaling pathways that initiate and maintain TRM differentiation and functional diversity, including different TGFβ sources. Alterations in the cellular networks induced by loss of TGFβRII expression revealed a model consistent with TGFβ promoting progressive TRM maturation towards the villus tip. Ultimately, we have developed a framework for the study of immune cell interactions with the spectrum of tissue cell types, revealing that T cell location and functional state are fundamentally intertwined.

Accessible luminal interface of bovine rectal organoids generated from cryopreserved biopsy tissues

Developing precise species-specific in vitro models that closely resemble in vivo intestinal tissues is essential for advancing our understanding of gastrointestinal physiology and associated diseases. This is especially crucial in examining host-pathogen interactions, particularly in bovines, a known reservoir for microbes and pathogens posing substantial public health threats. This research investigated the viability of producing bovine rectal organoids from cryopreserved tissues. We compared two cryopreservation methods with a traditional technique using fresh tissues, evaluating their effectiveness through growth rates, long-term viability, and comprehensive structural, cellular, and genetic analyses. These assessments utilized phase-contrast imaging, immunofluorescence imaging, and RT-qPCR assays. Additionally, the study developed a sophisticated method for forming a functional epithelial barrier from organoid-derived bovine rectal monolayers, incorporating a wide range of epithelial cells. This methodology employed transepithelial electrical resistance (TEER), parallel artificial membrane permeability assay (Papp), confocal microscopy, and advanced imaging techniques like scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Our findings decisively show that bovine rectal organoids can be effectively generated from cryopreserved biopsy tissues. Moreover, we formulated a robust and optimized protocol for creating functional rectal monolayers from these organoids. This significant progress is particularly relevant given the susceptibility of the bovine rectum to various enteric pathogens of public health concern, marking a vital step forward in veterinary and biomedical research. The creation of accurate species specific in vitro models that faithfully mimic in vivo intestinal tissues is critical for enhancing our understanding of gut physiology and related pathologies. This is particularly relevant in studying the interactions between hosts and microbes or pathogens with significant public health risks where bovine can be the major reservoir.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic 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 features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. 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, and 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 multiomics.

BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis

Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.

Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

Stromal Niche Signals That Orchestrate Intestinal Regeneration

Stromal cell populations have a central role in providing signals that support the maintenance, differentiation, and function of the intestinal epithelium. The behavior and fate of epithelial cells is directed by the spatial organization of stromal cells that either sustain stem and progenitor cell identity or drive differentiation. A combination of single-cell analyses, mouse models, and organoid coculture assays have provided insight into the diversity of signals delivered by stromal cells. Signaling gradients are established and fine-tuned by the expression of signaling agonists and antagonists along the crypt-villus axis. On epithelial injury, there are disruptions to the abundance and organization of stromal populations. There are also distinct changes in the signals originating from these cells that impact remodeling of the epithelium. How these signals coordinate to mediate epithelial repair or sustain tissue injury in inflammatory bowel diseases is beginning to emerge. Understanding of these processes may lead to opportunities to target stromal cell populations as a strategy to modify disease states.

Telocytes in the Luminal GI Tract

Telocytes are unique mesenchymal cells characterized by multiple remarkably long cytoplasmic extensions that extend hundreds of micron away from the cell body. Through these extensions, telocytes establish a 3-dimensional network by connecting with other telocytes and various cell types within the tissue. In the intestine, telocytes have emerged as an essential component of the stem cell niche, providing Wnt proteins that are critical for the proliferation of stem and progenitor cells. However, the analysis of single-cell RNA sequencing has revealed other stromal populations and mechanisms for niche organization, raising questions about the role of telocytes as a component of the stem cell niche. This review explores the current state-of-the-art, existing controversies, and potential future directions related to telocytes in the luminal gastrointestinal tract.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Epithelial zonation along the mouse and human small intestine defines five discrete metabolic domains

A key aspect of nutrient absorption is the exquisite division of labour across the length of the small intestine, with individual nutrients taken up at different proximal:distal positions. For millennia, the small intestine was thought to comprise three segments with indefinite borders: the duodenum, jejunum and ileum. By examining the fine-scale longitudinal transcriptional patterns that span the mouse and human small intestine, we instead identified five domains of nutrient absorption that mount distinct responses to dietary changes, and three regional stem cell populations. Molecular domain identity can be detected with machine learning, which provides a systematic method to computationally identify intestinal domains in mice. We generated a predictive model of transcriptional control of domain identity and validated the roles of Ppar-δ and Cdx1 in patterning lipid metabolism-associated genes. These findings represent a foundational framework for the zonation of absorption across the mammalian small intestine.

Pseudo-spectral angle mapping for automated pixel-level analysis of highly multiplexed tissue image data

The rapid development of highly multiplexed microscopy systems has enabled the study of cells embedded within their native tissue, which is providing exciting insights into the spatial features of human disease [1]. However, computational methods for analyzing these high-content images are still emerging, and there is a need for more robust and generalizable tools for evaluating the cellular constituents and underlying stroma captured by high-plex imaging [2]. To address this need, we have adapted spectral angle mapping - an algorithm used widely in hyperspectral image analysis - to compress the channel dimension of high-plex immunofluorescence images. As many high-plex immunofluorescence imaging experiments probe unique sets of protein markers, existing cell and pixel classification models do not typically generalize well. Pseudospectral angle mapping (pSAM) uses reference pseudospectra - or pixel vectors - to assign each pixel in an image a similarity score to several cell class reference vectors, which are defined by each unique staining panel. Here, we demonstrate that the class maps provided by pSAM can directly provide insight into the prevalence of each class defined by reference pseudospectra. In a dataset of high-plex images of colon biopsies from patients with gut autoimmune conditions, sixteen pSAM class representation maps were combined with instance segmentation of cells to provide cell class predictions. Finally, pSAM detected a diverse set of structure and immune cells when applied to a novel dataset of kidney biopsies imaged with a 43-marker panel. In summary, pSAM provides a powerful and readily generalizable method for evaluating high-plex immunofluorescence image data.

Quantitative Analysis of NKX2-3 Expression in Human Colon: An Immunohistochemical Study

In mice, Nkx2-3 homeodomain transcription factor defines the vascular specification of secondary and tertiary lymphoid tissues of the intestines. In human studies, polymorphisms in NKX2-3 have been identified as a susceptibility factor in inflammatory bowel diseases, whereas in mice, its absence is associated with protection against experimental colitis and enhanced intestinal epithelial proliferation. Here, we investigated the expression of NKX2-3 in normal, polyp, and adenocarcinoma human colon samples using immunohistochemistry and quantitative morphometry, correlating its expression with endothelial and mesenchymal stromal markers. Our results revealed that the expression of NKX2-3 is regionally confined to the lamina propria and lamina muscularis mucosae, and its production is restricted mostly to endothelial cells and smooth muscle cells with variable co-expression of CD34, alpha smooth muscle antigen (αSMA), and vascular adhesion protein-1 (VAP-1). The frequency of NKX2-3-positive cells and intensity of expression correlated inversely with aging. Furthermore, in most colorectal carcinoma samples, we observed a significant reduction of NKX2-3 expression. These findings indicate that the NKX2-3 transcription factor is produced by both endothelial and non-endothelial tissue constituents in the colon, and its expression changes during aging and in colorectal malignancies. (J Histochem Cytochem XX: XXX-XXX, XXXX).

T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response

Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8+ T cells. T cell-focused analysis indicates T cells are found along a continuum of neighborhoods that reflect the progressive steps coordinating the anti-tumor immune response. More effective anti-tumor immune responses are characterized by inflamed tumor-T cell neighborhoods, flanked by dense immune infiltration neighborhoods. Conversely, ineffective T cell therapies express anti-inflammatory cytokines, resulting in regulatory neighborhoods, spatially disrupting productive T cell-immune and -tumor interactions. Our study provides in situ mechanistic insights into temporal tumor microenvironment changes, cell interactions critical for response, and spatial correlates of immunotherapy outcomes, informing cellular therapy evaluation and engineering.

Single-cell profiling reveals the impact of genetic alterations on the differentiation of inflammation-induced colon tumors

Genetic mutations and chronic inflammation of the colon contribute to the development of colorectal cancer (CRC). Using a murine model of inflammation-induced colon tumorigenesis, we determined how genetic mutations alter colon tumor cell differentiation. Inflammation induced by enterotoxigenic Bacteroides fragilis (ETBF) colonization of multiple intestinal neoplasia (Min ApcΔ716/+ ) mice triggers loss of heterozygosity of Apc causing colon tumor formation. Here, we report that the addition of BRAF V600E mutation ( BRAF FV600E Lgr5 tm1(Cre/ERT2)Cle Min ApcΔ716/+ , BLM) or knocking out Msh2 ( Msh2 LoxP/LoxP Vil1-cre Min ApcΔ716/+ , MSH2KO) in the Min model altered colon tumor differentiation. Using single cell RNA-sequencing, we uncovered the differences between BLM, Min, and MSH2KO tumors at a single cell resolution. BLM tumors showed an increase in differentiated tumor epithelial cell lineages and a reduction in the stem cell population. In contrast, MSH2KO tumors were characterized by an increased stem cell population that had higher WNT signaling activity compared to Min tumors. Additionally, comparative analysis of single-cell transcriptomics revealed that BLM tumors had higher expression of transcription factors that drive differentiation, such as Cdx2, than Min tumors. Using RNA velocity, we were able to identify additional potential regulators of BLM tumor differentiation such as NDRG1. The role of CDX2 and NDRG1 as putative regulators for BLM tumor cell differentiation was verified using organoids derived from BLM tumors. Our results demonstrate the critical connections between genetic mutations and cell differentiation in inflammation-induced colon tumorigenesis. Understanding such roles will deepen our understanding of inflammation-associated colon cancer.

Decoding the tumor microenvironment with spatial technologies

Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.

Adult Bovine-Derived Small and Large Intestinal Organoids: In Vitro Development and Maintenance

Recent progress in bovine intestinal organoid research has expanded opportunities for creating improved in vitro models to study intestinal physiology and pathology. However, the establishment of a culture condition capable of generating organoids from all segments of the cattle intestine has remained elusive. Although previous research has described the development of bovine jejunal, ileal, and colonic organoids, this study marks the first report of successful bovine duodenal and rectal organoid development. Maintenance of these organoids through serial passages and cryopreservation was achieved, with higher success rates observed in large intestinal organoids compared to their small intestinal counterparts. A novel approach involving the use of biopsy forceps during initial tissue sampling streamlined the subsequent tissue processing, simplifying the procedure compared to previously established protocols in cattle. Additionally, our study introduced a more cost-effective culture medium based on Advanced DMEM/F12, diverging from frequently used commercially available organoid culture media. This enhancement improves accessibility to organoid technology by reducing culture costs. Crucially, the derived organoids from jejunum, ileum, colon and rectum faithfully preserved the structural, cellular, and genetic characteristics of in vivo intestinal tissue. This research underscores the significant potential of adult bovine intestinal organoids as a physiologically and morphologically relevant in vitro model. Such organoids provide a renewable and sustainable resource for a broad spectrum of studies, encompassing investigations into normal intestinal physiology in cattle and the intricate host-pathogen interactions of clinically and economically significant enteric pathogens.

Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics

Optimizing and benchmarking data reduction methods for dynamic or spatial visualization and interpretation (DSVI) face challenges due to many factors, including data complexity, lack of ground truth, time-dependent metrics, dimensionality bias and different visual mappings of the same data. Current studies often focus on independent static visualization or interpretability metrics that require ground truth. To overcome this limitation, we propose the MIBCOVIS framework, a comprehensive and interpretable benchmarking and computational approach. MIBCOVIS enhances the visualization and interpretability of high-dimensional data without relying on ground truth by integrating five robust metrics, including a novel time-ordered Markov-based structural metric, into a semi-supervised hierarchical Bayesian model. The framework assesses method accuracy and considers interaction effects among metric features. We apply MIBCOVIS using linear and nonlinear dimensionality reduction methods to evaluate optimal DSVI for four distinct dynamic and spatial biological processes captured by three single-cell data modalities: CyTOF, scRNA-seq and CODEX. These data vary in complexity based on feature dimensionality, unknown cell types and dynamic or spatial differences. Unlike traditional single-summary score approaches, MIBCOVIS compares accuracy distributions across methods. Our findings underscore the joint evaluation of visualization and interpretability, rather than relying on separate metrics. We reveal that prioritizing average performance can obscure method feature performance. Additionally, we explore the impact of data complexity on visualization and interpretability. Specifically, we provide optimal parameters and features and recommend methods, like the optimized variational contractive autoencoder, for targeted DSVI for various data complexities. MIBCOVIS shows promise for evaluating dynamic single-cell atlases and spatiotemporal data reduction models.

Single cell transcriptome analyses reveal the roles of B cells in fructose-induced hypertension

Rationale

While the immune system plays a crucial role in the development of hypertension, the specific contributions of distinct immune cell populations remain incompletely understood. The emergence of single-cell RNA-sequencing (scRNA-seq) technology enables us to analyze the transcriptomes of individual immune cells and to assess the significance of each immune cell type in hypertension development.

Objective

We aimed to investigate the hypothesis that B cells play a crucial role in the development of fructose-induced hypertension.

Methods and Results

Eight-week-old Dahl salt-sensitive (SS) male rats were divided into two groups and given either tap water (TW) or a 20% fructose solution (HFS) for 4 weeks. Systolic blood pressure was measured using the tail-cuff method. ScRNA-seq analysis was performed on lamina propria cells (LPs) and peripheral blood mononuclear cells (PBMCs) obtained from SS rats subjected to either TW or HFS. The HFS treatment induced hypertension in the SS rats. The analysis revealed 27 clusters in LPs and 28 clusters in PBMCs, allowing for the identification and characterization of various immune cell types within each cluster. Specifically, B cells and follicular helper T (Tfh) cells were prominent in LPs, while B cells and M1 macrophages dominated PBMCs in the HFS group. Moreover, the HFS treatment triggered an increase in the number of B cells in both LPs and PBMCs, accompanied by activation of the interferon pathway.

Conclusions

The significant involvement of B cells in intestinal and PBMC responses indicates their pivotal contribution to the development of hypertension. This finding suggests that targeting B cells could be a potential strategy to mitigate high blood pressure in fructose-induced hypertension. Moreover, the simultaneous increase in follicular B cells and Tfh cells in LPs, along with the upregulation of interferon pathway genes in B cells, underscores a potential autoimmune factor contributing to the pathogenesis of fructose-induced hypertension in the intestine.

Functional Tissue Units in the Human Reference Atlas

Functional tissue units (FTUs) form the basic building blocks of organs and are important for understanding and modeling the healthy physiological function of the organ and changes during disease states. In this first comprehensive catalog of FTUs, we document the definition, physical dimensions, vasculature, and cellular composition of 22 anatomically correct, nested functional tissue units (FTUs) in 10 healthy human organs. The catalog includes datasets, illustrations, an interactive online FTU explorer, and a large printable poster. All data and code are freely available. This is part of a larger ongoing international effort to construct a Human Reference Atlas (HRA) of all cells in the human body.

Tuft Cells: Detectors, Amplifiers, Effectors and Targets in Parasite Infection

Tuft cells have recently emerged as the focus of intense interest following the discovery of their chemosensory role in the intestinal tract, and their ability to activate Type 2 immune responses to helminth parasites. Moreover, they populate a wide range of mucosal tissues and are intimately connected to immune and neuronal cells, either directly or through the release of pharmacologically active mediators. They are now recognised to fulfil both homeostatic roles, in metabolism and tissue integrity, as well as acting as the first sensors of parasite infection, immunity to which is lost in their absence. In this review we focus primarily on the importance of tuft cells in the intestinal niche, but also link to their more generalised physiological role and discuss their potential as targets for the treatment of gastrointestinal disorders.

Omics and Multi-Omics in IBD: No Integration, No Breakthroughs

The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of "big data" research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics "big data" can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD.

Epithelial zonation along the mouse and human small intestine defines five discrete metabolic domains

A key aspect of nutrient absorption is the exquisite division of labor across the length of the small intestine, with individual classes of micronutrients taken up at different positions. For millennia, the small intestine was thought to comprise three segments with indefinite borders: the duodenum, jejunum, and ileum. By examining fine-scale longitudinal segmentation of the mouse and human small intestines, we identified transcriptional signatures and upstream regulatory factors that define five domains of nutrient absorption, distinct from the three traditional sections. Spatially restricted expression programs were most prominent in nutrient-absorbing enterocytes but initially arose in intestinal stem cells residing in three regional populations. While a core signature was maintained across mice and humans with different diets and environments, domain properties were influenced by dietary changes. We established the functions of Ppar-ẟ and Cdx1 in patterning lipid metabolism in distal domains and generated a predictive model of additional transcription factors that direct domain identity. Molecular domain identity can be detected with machine learning, representing the first systematic method to computationally identify specific intestinal regions in mice. These findings provide a foundational framework for the identity and control of longitudinal zonation of absorption along the proximal:distal small intestinal axis.

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 important tissue heterogeneity, which make it impossible for proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single tissue voxel 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 tissue voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ∼900 and ∼4,600 proteins for single voxel from fresh frozen human spleen tissue at 20 μm × 20 μm × 10 μm (close to single cells) and 200 μm × 200 μm × 10 μm (∼100 cells), respectively. 100s-1000s of protein signatures with differential expression levels were identified to be spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. Antibody-based CODEX imaging was used to validate label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

Segmenting functional tissue units across human organs using community-driven development of generalizable machine learning algorithms

The development of a reference atlas of the healthy human body requires automated image segmentation of major anatomical structures across multiple organs based on spatial bioimages generated from various sources with differences in sample preparation. We present the setup and results of the Hacking the Human Body machine learning algorithm development competition hosted by the Human Biomolecular Atlas (HuBMAP) and the Human Protein Atlas (HPA) teams on the Kaggle platform. We create a dataset containing 880 histology images with 12,901 segmented structures, engaging 1175 teams from 78 countries in community-driven, open-science development of machine learning models. Tissue variations in the dataset pose a major challenge to the teams which they overcome by using color normalization techniques and combining vision transformers with convolutional models. The best model will be productized in the HuBMAP portal to process tissue image datasets at scale in support of Human Reference Atlas construction.

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.