Screening for modulators of the cellular composition of gut epithelia via organoid models of intestinal stem cell differentiation

Imaging 3D cell cultures with optical microscopy

Three-dimensional (3D) cell cultures have gained popularity in recent years due to their ability to represent complex tissues or organs more faithfully than conventional two-dimensional (2D) cell culture. This article reviews the application of both 2D and 3D microscopy approaches for monitoring and studying 3D cell cultures. We first summarize the most popular optical microscopy methods that have been used with 3D cell cultures. We then discuss the general advantages and disadvantages of various microscopy techniques for several broad categories of investigation involving 3D cell cultures. Finally, we provide perspectives on key areas of technical need in which there are clear opportunities for innovation. Our goal is to guide microscope engineers and biomedical end users toward optimal imaging methods for specific investigational scenarios and to identify use cases in which additional innovations in high-resolution imaging could be helpful.

Developments in gastrointestinal organoid cultures to recapitulate tissue environments

Culture platforms that closely mimic the spatial architecture, cellular diversity, and extracellular matrix composition of native tissues can serve as invaluable tools for a range of scientific discovery and biomedical applications. Organoids have emerged as a promising alternative to both traditional 2D cell culture and animal models, offering a physiologically relevant 3D culture system for studying human cell biology. Organoids provide a manipulable platform to investigate organ development and function as well as to model patient-specific phenotypes. This mini review examines various methods used for culturing organoids to model normal and disease conditions in gastrointestinal tissues. We focus on how the matrix composition and media formulations can impact cell signaling, altering the baseline cellular phenotypes as well as response to perturbations. We discuss future directions for optimizing organoid culture conditions to improve basic and translational potential.

Analysis of a Single Cell RNA-seq Workflow by Random Matrix Theory Methods

Single cell RNA-seq (scRNAseq) workflows typically start with a count matrix and end with the clustering of sampled cells. While a range of methods have been developed to cluster scRNAseq datasets, no theoretical tools exist to explain why a particular cluster exists or why a hypothesized cluster is missing. Recently, several authors have shown that eigenvalues of scRNAseq count matrices can be approximated using random matrix models. In this work, we extend these previous works to the study of a scRNAseq workflow. We model scaled count matrices using random matrices with normally distributed entries. Using these random matrix models, we quantify the differential expression of a cluster and develop predictions for the workflow, and in particular clustering, as a function of the differential expression. We also use results from random matrix theory (RMT) to develop predictive formulas for portions of the scRNAseq workflow. Using simulated and real datasets, we show that our predictions are accurate if certain conditions hold on differential expression, with our RMT based predictions requiring particularly stringent condition. We find that real datasets violate these conditions, leading to bias in our predictions, but our predictions are better than a naive estimator and we point out future work that can improve the predictions. To our knowledge, our formulas represents the first predictive results for scRNAseq workflows.

Characterizing the effects of triclosan and triclocarban on the intestinal epithelial homeostasis using small intestinal organoids

Intestinal epithelium has the largest surface of human body, contributes dramatically to defense of toxicant-associated intestinal injury. Triclosan (TCS) and triclocarban (TCC), extensively employed as antibacterial agents in personal care products (PCPs) and healthcare facilities, caused serious damage to human intestine. However, the role of the intestinal epithelium in TCS/TCC-induced intestinal toxicity and its underlying toxic mechanisms remain incompletely understood. In this study, a novel 3D intestinal organoid model was utilized to investigate that exposure to TCS/TCC led to a compromised self-renewal and differentiation of intestinal stem cells (ISCs). Consequently, this disrupted intestinal epithelial homeostasis ultimately caused a reduction in nutrient absorption and deficient of epithelial defense to exogenous and endogenous pathogens stimulation. The inhibition of the Wnt signaling pathway in intestinal stem cell was contributed to the intestinal toxicity of TCS/TCC. These results were further confirmed in vivo with mice exposed to TCS/TCC. The findings of this study provide evidence that TCS/TCC possess the capacity to disturb the homeostasis of the intestinal epithelium, and emphasize the credibility of organoids as a valuable model for toxicological studies, as they could faithfully recapitulate in vivo phenomena.

Scalable, compressed phenotypic screening using pooled perturbations

High-throughput phenotypic screens using biochemical perturbations and high-content readouts are constrained by limitations of scale. To address this, we establish a method of pooling exogenous perturbations followed by computational deconvolution to reduce required sample size, labor and cost. We demonstrate the increased efficiency of compressed experimental designs compared to conventional approaches through benchmarking with a bioactive small-molecule library and a high-content imaging readout. We then apply compressed screening in two biological discovery campaigns. In the first, we use early-passage pancreatic cancer organoids to map transcriptional responses to a library of recombinant tumor microenvironment protein ligands, uncovering reproducible phenotypic shifts induced by specific ligands distinct from canonical reference signatures and correlated with clinical outcome. In the second, we identify the pleotropic modulatory effects of a chemical compound library with known mechanisms of action on primary human peripheral blood mononuclear cell immune responses. In sum, our approach empowers phenotypic screens with information-rich readouts to advance drug discovery efforts and basic biological inquiry.

Establishment of advanced tumor organoids with emerging innovative technologies

Tumor organoids have emerged as a crucial preclinical model for multiple cancer research. Their high establishment rates, stability, and ability to replicate key biological features of original tumor cells in vivo render them invaluable for exploring tumor molecular mechanisms, discovering potential anti-tumor drugs, and predicting clinical drug efficacy. Here, we review the establishment of tumor organoid models and provide an extensive overview of organoid culturing strategies. We also emphasize the significance of integrating cellular components of the tumor microenvironment and physicochemical factors in the organoid culturing system, highlighting the importance of artificial intelligence technology in advancing organoid construction. Moreover, we summarize recent advancements in utilizing organoid systems for novel anti-cancer drug screening and discuss promising trends for enhancing advanced organoids in next-generation disease modeling.

Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas

Comprehensively charting the biologically causal circuits that govern the phenotypic space of human cells has often been viewed as an insurmountable challenge. However, in the last decade, a suite of interleaved experimental and computational technologies has arisen that is making this fundamental goal increasingly tractable. Pooled CRISPR-based perturbation screens with high-content molecular and/or image-based readouts are now enabling researchers to probe, map, and decipher genetically causal circuits at increasing scale. This scale is now eminently suitable for the deployment of artificial intelligence and machine learning (AI/ML) to both direct further experiments and to predict or generate information that was not-and sometimes cannot-be gathered experimentally. By combining and iterating those through experiments that are designed for inference, we now envision a Perturbation Cell Atlas as a generative causal foundation model to unify human cell biology.

A novel function of benzoic acid to enhance intestinal barrier defense against PEDV infection in Piglets

The intestinal barrier of newborn piglets is vulnerable and underdeveloped, making them susceptible to enteric virus infections. Benzoic acid (BA), employed as a growth promoter, exhibits the potential to enhance the gut health of piglets by modulating intestinal morphometry and tight junction dynamics. However, the extent to which BA regulates the intestinal mucus barrier through its impact on stem cells remains inadequately elucidated. Therefore, this study was conducted to investigate the effects of BA on the intestinal barrier and the differentiation of intestinal stem cells, employing in vivo piglet and in vitro intestinal organoid models. Our investigation revealed a significant increase in the number of goblet cells within the small intestine, as well as the strengthening of the mucus barrier in vivo following oral treatment with BA, providing partial protection against PEDV infection in piglets. Additionally, in vitro cultivation of enteroids with BA led to a notable increase in the number of MUC2+ GCs, indicating the promotion of GC differentiation by BA. Furthermore, transcriptome analysis revealed an upregulation of the number of GCs and the expression of cell vesicle transport-related genes during BA stimulation, accompanied by the downregulation of the Wnt and Notch signaling pathways. Mechanistically, MCT1 facilitated the transport of BA, subsequently activating the MAPK pathway to mediate GC differentiation. Overall, this study highlights a novel function for BA as a feed additive in enhancing the intestinal mucus barrier by promoting intestinal GC differentiation, and further prevents viral infection in piglets.

Exploring cell death mechanisms in spheroid cultures using a novel application of the RIP3-caspase3-assay

This study explores the application of the RIP3-caspase3-assay in heterogeneous spheroid cultures to analyze cell death pathways, emphasizing the nuanced roles of apoptosis and necroptosis. By employing directly conjugated monoclonal antibodies, we provide detailed insights into the complex mechanisms of cell death. Our findings demonstrate the assay's capability to differentiate between RIP1-independent apoptosis, necroptosis, and RIP1-dependent apoptosis, marking a significant advancement in organoid research. Additionally, we investigate the effects of TNFα on isolated intestinal epithelial cells, revealing a concentration-dependent response and an adaptive or threshold reaction to TNFα-induced stress. The results indicate a preference for RIP1-independent cell death pathways upon TNFα stimulation, with a notable increase in apoptosis and a secondary role of necroptosis. Our research underscores the importance of the RIP3-caspase3-assay in understanding cell death mechanisms in organoid cultures, offering valuable insights for disease modeling and the development of targeted therapies. The assay's adaptability and robustness in spheroid cultures enhances its potential as a tool in personalized medicine and translational research.

PIKfyve controls dendritic cell function and tumor immunity

The modern armamentarium for cancer treatment includes immunotherapy and targeted therapy, such as protein kinase inhibitors. However, the mechanisms that allow cancer-targeting drugs to effectively mobilize dendritic cells (DCs) and affect immunotherapy are poorly understood. Here, we report that among shared gene targets of clinically relevant protein kinase inhibitors, high PIKFYVE expression was least predictive of complete response in patients who received immune checkpoint blockade (ICB). In immune cells, high PIKFYVE expression in DCs was associated with worse response to ICB. Genetic and pharmacological studies demonstrated that PIKfyve ablation enhanced DC function via selectively altering the alternate/non-canonical NF-κB pathway. Both loss of Pikfyve in DCs and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively controls DCs, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

PIKfyve, expressed by CD11c-positive cells, controls tumor immunity

Cancer treatment continues to shift from utilizing traditional therapies to targeted ones, such as protein kinase inhibitors and immunotherapy. Mobilizing dendritic cells (DC) and other myeloid cells with antigen presenting and cancer cell killing capacities is an attractive but not fully exploited approach. Here, we show that PIKFYVE is a shared gene target of clinically relevant protein kinase inhibitors and high expression of this gene in DCs is associated with poor patient response to immune checkpoint blockade (ICB) therapy. Genetic and pharmacological studies demonstrate that PIKfyve ablation enhances the function of CD11c+ cells (predominantly dendritic cells) via selectively altering the non-canonical NF-κB pathway. Both loss of Pikfyve in CD11c+ cells and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively regulates the function of CD11c+ cells, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network

Cells respond divergently to drugs due to the heterogeneity among cell populations. Thus, it is crucial to identify drug-responsive cell populations in order to accurately elucidate the mechanism of drug action, which is still a great challenge. Here, we address this problem with scRank, which employs a target-perturbed gene regulatory network to rank drug-responsive cell populations via in silico drug perturbations using untreated single-cell transcriptomic data. We benchmark scRank on simulated and real datasets, which shows the superior performance of scRank over existing methods. When applied to medulloblastoma and major depressive disorder datasets, scRank identifies drug-responsive cell types that are consistent with the literature. Moreover, scRank accurately uncovers the macrophage subpopulation responsive to tanshinone IIA and its potential targets in myocardial infarction, with experimental validation. In conclusion, scRank enables the inference of drug-responsive cell types using untreated single-cell data, thus providing insights into the cellular-level impacts of therapeutic interventions.

Advanced 3D imaging and organoid bioprinting for biomedical research and therapeutic applications

Organoid cultures offer a valuable platform for studying organ-level biology, allowing for a closer mimicry of human physiology compared to traditional two-dimensional cell culture systems or non-primate animal models. While many organoid cultures use cell aggregates or decellularized extracellular matrices as scaffolds, they often lack precise biochemical and biophysical microenvironments. In contrast, three-dimensional (3D) bioprinting allows precise placement of organoids or spheroids, providing enhanced spatial control and facilitating the direct fusion for the formation of large-scale functional tissues in vitro. In addition, 3D bioprinting enables fine tuning of biochemical and biophysical cues to support organoid development and maturation. With advances in the organoid technology and its potential applications across diverse research fields such as cell biology, developmental biology, disease pathology, precision medicine, drug toxicology, and tissue engineering, organoid imaging has become a crucial aspect of physiological and pathological studies. This review highlights the recent advancements in imaging technologies that have significantly contributed to organoid research. Additionally, we discuss various bioprinting techniques, emphasizing their applications in organoid bioprinting. Integrating 3D imaging tools into a bioprinting platform allows real-time visualization while facilitating quality control, optimization, and comprehensive bioprinting assessment. Similarly, combining imaging technologies with organoid bioprinting can provide valuable insights into tissue formation, maturation, functions, and therapeutic responses. This approach not only improves the reproducibility of physiologically relevant tissues but also enhances understanding of complex biological processes. Thus, careful selection of bioprinting modalities, coupled with appropriate imaging techniques, holds the potential to create a versatile platform capable of addressing existing challenges and harnessing opportunities in these rapidly evolving fields.

Cellograph: a semi-supervised approach to analyzing multi-condition single-cell RNA-sequencing data using graph neural networks

With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respond to perturbations. Many existing approaches rely on discretizing the data into clusters for differential gene expression (DGE), effectively ironing out any information unveiled by the single-cell variability across cell-types. In addition, DGE often assumes a statistical distribution that, if erroneous, can lead to false positive differentially expressed genes. Here, we present Cellograph: a semi-supervised framework that uses graph neural networks to quantify the effects of perturbations at single-cell granularity. Cellograph not only measures how prototypical cells are of each condition but also learns a latent space that is amenable to interpretable data visualization and clustering. The learned gene weight matrix from training reveals pertinent genes driving the differences between conditions. We demonstrate the utility of our approach on publicly-available datasets including cancer drug therapy, stem cell reprogramming, and organoid differentiation. Cellograph outperforms existing methods for quantifying the effects of experimental perturbations and offers a novel framework to analyze single-cell data using deep learning.

Mechanisms of Stem Cells and Their Secreted Exosomes in the Treatment of Autoimmune Diseases

Stem cells play a therapeutic role in many diseases by virtue of their strong self-renewal and differentiation abilities, especially in the treatment of autoimmune diseases. At present, the mechanism of the stem cell treatment of autoimmune diseases mainly relies on their immune regulation ability, regulating the number and function of auxiliary cells, anti-inflammatory factors and proinflammatory factors in patients to reduce inflammation. On the other hand, the stem cell- derived secretory body has weak immunogenicity and low molecular weight, can target the site of injury, and can extend the length of its active time in the patient after combining it with the composite material. Therefore, the role of secretory bodies in the stem cell treatment of autoimmune diseases is increasingly important.

Chronic metabolic stress drives developmental programs and loss of tissue functions in non-transformed liver that mirror tumor states and stratify survival

Under chronic stress, cells must balance competing demands between cellular survival and tissue function. In metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD/NASH), hepatocytes cooperate with structural and immune cells to perform crucial metabolic, synthetic, and detoxification functions despite nutrient imbalances. While prior work has emphasized stress-induced drivers of cell death, the dynamic adaptations of surviving cells and their functional repercussions remain unclear. Namely, we do not know which pathways and programs define cellular responses, what regulatory factors mediate (mal)adaptations, and how this aberrant activity connects to tissue-scale dysfunction and long-term disease outcomes. Here, by applying longitudinal single-cell multi -omics to a mouse model of chronic metabolic stress and extending to human cohorts, we show that stress drives survival-linked tradeoffs and metabolic rewiring, manifesting as shifts towards development-associated states in non-transformed hepatocytes with accompanying decreases in their professional functionality. Diet-induced adaptations occur significantly prior to tumorigenesis but parallel tumorigenesis-induced phenotypes and predict worsened human cancer survival. Through the development of a multi -omic computational gene regulatory inference framework and human in vitro and mouse in vivo genetic perturbations, we validate transcriptional (RELB, SOX4) and metabolic (HMGCS2) mediators that co-regulate and couple the balance between developmental state and hepatocyte functional identity programming. Our work defines cellular features of liver adaptation to chronic stress as well as their links to long-term disease outcomes and cancer hallmarks, unifying diverse axes of cellular dysfunction around core causal mechanisms.

Intestinal organoid technology and applications in probiotics

The impacts of probiotics on maintaining the host's intestinal health have been extensively confirmed. Organoid technology revolutionizes intestinal health research by providing a unique platform to study the effects of probiotics. It overcomes challenges posed by animal models and 2D cell models in accurately simulating the in vivo environment. This review summarizes the development of intestinal organoid technology and its potential applications in intestinal health research as well as highlights the regulatory mechanisms of probiotics on intestinal health, which have been revealed using intestinal organoid technology. Furthermore, an overview of its potential applications in probiotic research has also been provided. This review aims to improve the understanding of intestinal organoid technology's applications in this field as well as to contribute to its further development.

Role of MAIT cells in gastrointestinal tract bacterial infections in humans: More than a gut feeling

Mucosa-associated invariant T (MAIT) cells are the largest population of unconventional T cells in humans. These antimicrobial T cells are poised with rapid effector responses following recognition of the cognate riboflavin (vitamin B2)-like metabolite antigens derived from microbial riboflavin biosynthetic pathway. Presentation of this unique class of small molecule metabolite antigens is mediated by the highly evolutionarily conserved major histocompatibility complex class I-related protein. In humans, MAIT cells are widely found along the upper and lower gastrointestinal tracts owing to their high expression of chemokine receptors and homing molecules directing them to these tissue sites. In this review, we discuss recent findings regarding the roles MAIT cells play in various gastrointestinal bacterial infections, and how their roles appear to differ depending on the etiological agents and the anatomical location. We further discuss the potential mechanisms by which MAIT cells contribute to pathogen control, orchestrate adaptive immunity, as well as their potential contribution to inflammation and tissue damage during gastrointestinal bacterial infections, and the ensuing tissue repair following resolution. Finally, we propose and discuss the use of the emerging three-dimensional organoid technology to test different hypotheses regarding the role of MAIT cells in gastrointestinal bacterial infections, inflammation, and immunity.

Applications of single-cell RNA sequencing in drug discovery and development

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Potential Effect of Glutamine in the Improvement of Intestinal Stem Cell Proliferation and the Alleviation of Burn-Induced Intestinal Injury via Activating YAP: A Preliminary Study

Burn injury is a common form of traumatic injury that leads to high mortality worldwide. A severe burn injury usually induces gut barrier dysfunction, partially resulting from the impairment in the proliferation and self-renewal of intestinal stem cells (ISCs) post burns. As a main energy substance of small intestinal enterocytes, glutamine (Gln) is important for intestinal cell viability and growth, while its roles in ISCs-induced regeneration after burns are still unclear. To demonstrate the potential effects of Gln in improving ISCs proliferation and alleviating burn-induced intestinal injury, in this study, we verified that Gln significantly alleviated small intestine injury in burned mice model. It showed that Gln could significantly decrease the ferroptosis of crypt cells in the ileum, promote the proliferation of ISCs, and repair the crypt. These effects of Gln were also confirmed in the mouse small intestine organoids model. Further research found that Yes-associated protein (YAP) is suppressed after burn injury, and Gln could improve cell proliferation and accelerate the renewal of the damaged intestinal mucosal barrier after burns by activating YAP. YAP is closely associated with the changes in intestinal stem cell proliferation after burn injury and could be served as a potential target for severe burns.

Gene expression in organoids: an expanding horizon

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.

Microbiota-directed biotherapeutics: considerations for quality and functional assessment

Mounting evidence points to causative or correlative roles of gut microbiome in the development of a myriad of diseases ranging from gastrointestinal diseases, metabolic diseases to neurological disorders and cancers. Consequently, efforts have been made to develop and apply therapeutics targeting the human microbiome, in particular the gut microbiota, for treating diseases and maintaining wellness. Here we summarize the current development of gut microbiota-directed therapeutics with a focus on novel biotherapeutics, elaborate the need of advanced -omics approaches for evaluating the microbiota-type biotherapeutics, and discuss the clinical and regulatory challenges. We also discuss the development and potential application of ex vivo microbiome assays and in vitro intestinal cellular models in this context. Altogether, this review aims to provide a broad view of promises and challenges of the emerging field of microbiome-directed human healthcare.

Organoid Cultures In Silico: Tools or Toys?

The implementation of stem-cell-based organoid culture more than ten years ago started a development that created new avenues for diagnostic analyses and regenerative medicine. In parallel, computational modelling groups realized the potential of this culture system to support their theoretical approaches to study tissues in silico. These groups developed computational organoid models (COMs) that enabled testing consistency between cell biological data and developing theories of tissue self-organization. The models supported a mechanistic understanding of organoid growth and maturation and helped linking cell mechanics and tissue shape in general. What comes next? Can we use COMs as tools to complement the equipment of our biological and medical research? While these models already support experimental design, can they also quantitatively predict tissue behavior? Here, we review the current state of the art of COMs and discuss perspectives for their application.

Impact of the Human Cell Atlas on medicine

Single-cell atlases promise to provide a 'missing link' between genes, diseases and therapies. By identifying the specific cell types, states, programs and contexts where disease-implicated genes act, we will understand the mechanisms of disease at the cellular and tissue levels and can use this understanding to develop powerful disease diagnostics; identify promising new drug targets; predict their efficacy, toxicity and resistance mechanisms; and empower new kinds of therapies, from cancer therapies to regenerative medicine. Here, we lay out a vision for the potential of cell atlases to impact the future of medicine, and describe how advances over the past decade have begun to realize this potential in common complex diseases, infectious diseases (including COVID-19), rare diseases and cancer.

Molecular regulation after mucosal injury and regeneration in ulcerative colitis

Ulcerative colitis (UC) is a chronic nonspecific inflammatory disease with a complex etiology. Intestinal mucosal injury is an important pathological change in individuals with UC. Leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5+) intestinal stem cells (ISCs) exhibit self-renewal and high differentiation potential and play important roles in the repair of intestinal mucosal injury. Moreover, LGR5+ ISCs are intricately regulated by both the Wnt/β-catenin and Notch signaling pathways, which jointly maintain the function of LGR5+ ISCs. Combination therapy targeting multiple signaling pathways and transplantation of LGR5+ ISCs may lead to the development of new clinical therapies for UC.

Applications of human organoids in the personalized treatment for digestive diseases

Digestive system diseases arise primarily through the interplay of genetic and environmental influences; there is an urgent need in elucidating the pathogenic mechanisms of these diseases and deploy personalized treatments. Traditional and long-established model systems rarely reproduce either tissue complexity or human physiology faithfully; these shortcomings underscore the need for better models. Organoids represent a promising research model, helping us gain a more profound understanding of the digestive organs; this model can also be used to provide patients with precise and individualized treatment and to build rapid in vitro test models for drug screening or gene/cell therapy, linking basic research with clinical treatment. Over the past few decades, the use of organoids has led to an advanced understanding of the composition of each digestive organ and has facilitated disease modeling, chemotherapy dose prediction, CRISPR-Cas9 genetic intervention, high-throughput drug screening, and identification of SARS-CoV-2 targets, pathogenic infection. However, the existing organoids of the digestive system mainly include the epithelial system. In order to reveal the pathogenic mechanism of digestive diseases, it is necessary to establish a completer and more physiological organoid model. Combining organoids and advanced techniques to test individualized treatments of different formulations is a promising approach that requires further exploration. This review highlights the advancements in the field of organoid technology from the perspectives of disease modeling and personalized therapy.

Human organoids: New strategies and methods for analyzing human development and disease

For decades, insight into fundamental principles of human biology and disease has been obtained primarily by experiments in animal models. While this has allowed researchers to understand many human biological processes in great detail, some developmental and disease mechanisms have proven difficult to study due to inherent species differences. The advent of organoid technology more than 10 years ago has established laboratory-grown organ tissues as an additional model system to recapitulate human-specific aspects of biology. The use of human 3D organoids, as well as other advances in single-cell technologies, has revealed unprecedented insights into human biology and disease mechanisms, especially those that distinguish humans from other species. This review highlights novel advances in organoid biology with a focus on how organoid technology has generated a better understanding of human-specific processes in development and disease.