Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition

Patient-Derived Tumor Organoids Combined with Function-Associated ScRNA-Seq for Dissecting the Local Immune Response of Lung Cancer

In vitro models coupled with multimodal approaches are needed to dissect the dynamic response of local tumor immune microenvironment (TIME) to immunotherapy. Here the patient-derived primary lung cancer organoids (pLCOs) are generated by isolating tumor cell clusters, including the infiltrated immune cells. A function-associated single-cell RNA sequencing (FascRNA-seq) platform allowing both phenotypic evaluation and scRNA-seq at single-organoid level is developed to dissect the TIME of individual pLCOs. The analysis of 171 individual pLCOs derived from seven patients reveals that pLCOs retain the TIME heterogeneity in the parenchyma of parental tumor tissues, providing models with identical genetic background but various TIME. Linking the scRNA-seq data of individual pLCOs with their responses to anti-PD-1 (αPD-1) immune checkpoint blockade (ICB) allows to confirm the central role of CD8+ T cells in anti-tumor immunity, to identify potential tumor-reactive T cells with a set of 10 genes, and to unravel the factors regulating T cell activity, including CD99 gene. In summary, the study constructs a joint phenotypic and transcriptomic FascRNA-seq platform to dissect the dynamic response of local TIME under ICB treatment, providing a promising approach to evaluate novel immunotherapies and to understand the underlying molecular mechanisms.

Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

An Automated Single-Cell Droplet-Digital Microfluidic Platform for Monoclonal Antibody Discovery

Monoclonal antibody (mAb) discovery plays a prominent role in diagnostic and therapeutic applications. Droplet microfluidics has become a standard technology for high-throughput screening of antibody-producing cells due to high droplet single-cell confinement frequency and rapid analysis and sorting of the cells of interest with their secreted mAbs. In this work, a new method is described for on-demand co-encapsulation of cells that eliminates the difficulties associated with washing in between consecutive steps inside the droplets and enables the washing and addition of fresh media. The new platform identifies hybridoma cells that are expressing antibodies of interest using antibody-characterization assays to find the best-performing or rare-cell antibody candidates.

Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry

Gene expression profiling of tissue cells with spatial context is in high demand to reveal cell types, locations, and intercellular or molecular interactions for physiological and pathological studies. With rapid advances in barcoding chemistry and sequencing chemistry, spatially resolved transcriptome (SRT) techniques have emerged to quantify spatial gene expression in tissue samples by correlating transcripts with their spatial locations using diverse strategies. These techniques provide both physical tissue structure and molecular characteristics and are poised to revolutionize many fields, such as developmental biology, neuroscience, oncology, and histopathology. In this context, this Perspective focuses on next-generation sequencing-based SRT methods, particularly highlighting spatial barcoding chemistry. It delves into optically manipulated spatial indexing methods and DNA array-barcoded spatial indexing methods by exploring current advances, challenges, and future development directions in this nascent field.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

Image-based profiling and deep learning reveal morphological heterogeneity of colorectal cancer organoids

Patient-derived organoids have proven to be a highly relevant model for evaluating of disease mechanisms and drug efficacies, as they closely recapitulate in vivo physiology. Colorectal cancer organoids, specifically, exhibit a diverse range of morphologies, which have been analyzed with image-based profiling. However, the relationship between morphological subtypes and functional parameters of the organoids remains underexplored. Here, we identified two distinct morphological subtypes ("cystic" and "solid") across 31360 bright field images using image-based profiling, which correlated differently with viability and apoptosis level of colorectal cancer organoids. Leveraging object detection neural networks, we were able to categorize single organoids achieving higher viability scores as "cystic" than "solid" subtype. Furthermore, a deep generative model was proposed to predict apoptosis intensity based on a apoptosis-featured dataset encompassing over 17000 bright field and matched fluorescent images. Notably, a significant correlation of 0.91 between the predicted value and ground truth was achived, underscoring the feasibility of this generative model as a potential means for assessing organoid functional parameters. The underlying cellular heterogeneity of the organoids, i.e., conserved colonic cell types and rare immune components, was also verified with scRNA sequencing, implying a compromised tumor microenvironment. Additionally, the "cystic" subtype was identified as a relapse phenotype featuring intestinal stem cell signatures, suggesting that this visually discernible relapse phenotype shows potential as a novel biomarker for colorectal cancer diagnosis and prognosis. In summary, our findings demonstrate that the morphological heterogeneity of colorectal cancer organoids explicitly recapitulate the association of phenotypic features and exogenous perturbations through the image-based profiling, providing new insights into disease mechanisms.

Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets

Assigning single cell transcriptomes to cellular lineage trees by lineage tracing has transformed our understanding of differentiation during development, regeneration, and disease. However, lineage tracing is technically demanding, often restricted in time-resolution, and most scRNA-seq datasets are devoid of lineage information. Here we introduce Gene Expression Memory-based Lineage Inference (GEMLI), a computational tool allowing to robustly identify small to medium-sized cell lineages solely from scRNA-seq datasets. GEMLI allows to study heritable gene expression, to discriminate symmetric and asymmetric cell fate decisions and to reconstruct individual multicellular structures from pooled scRNA-seq datasets. In human breast cancer biopsies, GEMLI reveals previously unknown gene expression changes at the onset of cancer invasiveness. The universal applicability of GEMLI allows studying the role of small cell lineages in a wide range of physiological and pathological contexts, notably in vivo. GEMLI is available as an R package on GitHub ( https://github.com/UPSUTER/GEMLI ).

Plastic persisters: revival stem cells in colorectal cancer

Colorectal cancer (CRC) is traditionally considered to be a genetically driven disease. However, nongenetic plasticity has recently emerged as a major driver of tumour initiation, metastasis, and therapy response in CRC. Central to these processes is a recently discovered cell type, the revival colonic stem cell (revCSC). In contrast to traditional proliferative CSCs (proCSCs), revCSCs prioritise survival over propagation. revCSCs play an essential role in primary tumour formation, metastatic dissemination, and nongenetic chemoresistance. Current evidence suggests that CRC tumours leverage intestinal stem cell plasticity to both proliferate (via proCSCs) when unchallenged and survive (via revCSCs) in response to cell-extrinsic pressures. Although revCSCs likely represent a major source of therapeutic failure in CRC, our increasing knowledge of this important stem cell fate provides novel opportunities for therapeutic intervention.

MAGIC matrices: freeform bioprinting materials to support complex and reproducible organoid morphogenesis

Organoids are powerful models of tissue physiology, yet their applications remain limited due to a lack of complex tissue morphology and high organoid-to-organoid structural variability. To address these limitations we developed a soft, composite yield-stress extracellular matrix that supports freeform 3D bioprinting of cell slurries at tissue-like densities. Combined with a custom piezoelectric printhead, this platform allows more reproducible and complex morphogenesis from uniform and spatially organized organoid "seeds." At 4 °C the material exhibits reversible yield-stress behavior to support long printing times without compromising cell viability. When transferred to cell culture at 37 °C, the material cross-links and exhibits similar viscoelasticity and plasticity to basement membrane extracts such as Matrigel. We use this setup for high-throughput generation of intestinal and salivary gland organoid arrays that are morphologically indistinguishable from those grown in pure Matrigel, but exhibit dramatically improved homogeneity in organoid size, shape, maturation time, and budding efficiency. The reproducibility of organoid structure afforded by this approach increases the sensitivity of assays by orders of magnitude, requiring less input material and reducing analysis times. The flexibility of this approach additionally enabled the fabrication of perfusable intestinal organoid tubes. Combined, these advances lay the foundation for the efficient design of complex tissue morphologies in both space and time.

Enhancing single-cell encapsulation in droplet microfluidics with fine-tunable on-chip sample enrichment

Single-cell encapsulation in droplet microfluidics is commonly hindered by the tradeoff between cell suspension density and on-chip focusing performance. In this study, we introduce a novel droplet microfluidic chip to overcome this challenge. The chip comprises a double spiral focusing unit, a flow resistance-based sample enrichment module with fine-tunable outlets, and a crossflow droplet generation unit. Utilizing a low-density cell/bead suspension (2 × 106 objects/mL), cells/beads are focused into a near-equidistant linear arrangement within the double spiral microchannel. The excess water phase is diverted while cells/beads remain focused and sequentially encapsulated in individual droplets. Focusing performance was assessed through numerical simulations and experiments at three flow rates (40, 60, 80 μL/min), demonstrating successful focusing at 40 and 80 μL/min for beads and cells, respectively. In addition, both simulation and experimental results revealed that the flow resistance at the sample enrichment module is adjustable by punching different outlets, allowing over 50% of the aqueous phase to be removed. YOLOv8n-based droplet detection algorithms realized the counting of cells/beads in droplets, statistically demonstrating single-cell and bead encapsulation rates of 72.2% and 79.2%, respectively. All the results indicate that this on-chip sample enrichment approach can be further developed and employed as a critical component in single-cell encapsulation in water-in-oil droplets.

Construction of multiplexed transcriptome NGS libraries of microdissected tissue samples based on combinational DNA barcode microbeads

The combination of single-cell RNA sequencing and microdissection techniques that preserves positional information has become a major tool for spatial transcriptome analyses. However, high costs and time requirements, especially for experiments at the single cell scale, make it challenging for this approach to meet the demand for increased throughput. Therefore, we proposed combinational DNA barcode (CDB)-seq as a medium-throughput, multiplexed approach combining Smart-3SEQ and CDB magnetic microbeads for transcriptome analyses of microdissected tissue samples. We conducted a comprehensive comparison of conditions for CDB microbead preparation and related factors and then applied CDB-seq to RNA extracts, fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) mouse brain tissue samples. CDB-seq transcriptomic profiles of tens of microdissected samples could be obtained in a simple, cost-effective way, providing a promising method for future spatial transcriptomics.

An oncogenic phenoscape of colonic stem cell polarization

Cancer cells are regulated by oncogenic mutations and microenvironmental signals, yet these processes are often studied separately. To functionally map how cell-intrinsic and cell-extrinsic cues co-regulate cell fate, we performed a systematic single-cell analysis of 1,107 colonic organoid cultures regulated by (1) colorectal cancer (CRC) oncogenic mutations, (2) microenvironmental fibroblasts and macrophages, (3) stromal ligands, and (4) signaling inhibitors. Multiplexed single-cell analysis revealed a stepwise epithelial differentiation phenoscape dictated by combinations of oncogenes and stromal ligands, spanning from fibroblast-induced Clusterin (CLU)+ revival colonic stem cells (revCSCs) to oncogene-driven LRIG1+ hyper-proliferative CSCs (proCSCs). The transition from revCSCs to proCSCs is regulated by decreasing WNT3A and TGF-β-driven YAP signaling and increasing KRASG12D or stromal EGF/Epiregulin-activated MAPK/PI3K flux. We find that APC loss and KRASG12D collaboratively limit access to revCSCs and disrupt stromal-epithelial communication-trapping epithelia in the proCSC fate. These results reveal that oncogenic mutations dominate homeostatic differentiation by obstructing cell-extrinsic regulation of cell-fate plasticity.

Stem cell heterogeneity, plasticity, and regulation

As a population of homogeneous cells with both self-renewal and differentiation potential, stem cell pools are highly compartmentalized and contain distinct subsets that exhibit stable but limited heterogeneity during homeostasis. However, their striking plasticity is showcased under natural or artificial stress, such as injury, transplantation, cancer, and aging, leading to changes in their phenotype, constitution, metabolism, and function. The complex and diverse network of cell-extrinsic niches and signaling pathways, together with cell-intrinsic genetic and epigenetic regulators, tightly regulate both the heterogeneity during homeostasis and the plasticity under perturbation. Manipulating these factors offers better control of stem cell behavior and a potential revolution in the current state of regenerative medicine. However, disruptions of normal regulation by genetic mutation or excessive plasticity acquisition may contribute to the formation of tumors. By harnessing innovative techniques that enhance our understanding of stem cell heterogeneity and employing novel approaches to maximize the utilization of stem cell plasticity, stem cell therapy holds immense promise for revolutionizing the future of medicine.

Biomimetic Gland Models with Engineered Stratagems

As extensively distributed tissues throughout the human body, glands play a critical role in various physiological processes. Therefore, the construction of biomimetic gland models in vitro has aroused great interest in multiple disciplines. In the biological field, the researchers focus on optimizing the cell sources and culture techniques to reconstruct the specific structures and functions of glands, such as the emergence of organoid technology. From the perspective of biomedical engineering, the generation of biomimetic gland models depends on the combination of engineered scaffolds and microfluidics, to mimic the in vivo environment of glandular tissues. These engineered stratagems endowed gland models with more biomimetic features, as well as a wide range of application prospects. In this review, we first describe the biomimetic strategies for constructing different in vitro gland models, focusing on the role of microfluidics in promoting the structure and function development of biomimetic glands. After summarizing several common in vitro models of endocrine and exocrine glands, the applications of gland models in disease modelling, drug screening, regenerative medicine, and personalized medicine are enumerated. Finally, we conclude the current challenges and our perspective of these biomimetic gland models.

Single-cell sequencing of individual retinal organoids reveals determinants of cell-fate heterogeneity

With a critical need for more complete in vitro models of human development and disease, organoids hold immense potential. Their complex cellular composition makes single-cell sequencing of great utility; however, the limitation of current technologies to a handful of treatment conditions restricts their use in screens or studies of organoid heterogeneity. Here, we apply sci-Plex, a single-cell combinatorial indexing (sci)-based RNA sequencing (RNA-seq) multiplexing method to retinal organoids. We demonstrate that sci-Plex and 10× methods produce highly concordant cell-class compositions and then expand sci-Plex to analyze the cell-class composition of 410 organoids upon modulation of critical developmental pathways. Leveraging individual organoid data, we develop a method to measure organoid heterogeneity, and we identify that activation of Wnt signaling early in retinal organoid cultures increases retinal cell classes up to 6 weeks later. Our data show sci-Plex's potential to dramatically scale up the analysis of treatment conditions on relevant human models.

spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

Single-cell sequencing of individual retinal organoids reveals determinants of cell fate heterogeneity

With a critical need for more complete in vitro models of human development and disease, organoids hold immense potential. Their complex cellular composition makes single-cell sequencing of great utility; however, the limitation of current technologies to a handful of treatment conditions restricts their use in screens or studies of organoid heterogeneity. Here, we apply sci-Plex, a single-cell combinatorial indexing (sci)-based RNA-seq multiplexing method to retinal organoids. We demonstrate that sci-Plex and 10x methods produce highly concordant cell class compositions and then expand sci-Plex to analyze the cell class composition of 410 organoids upon modulation of critical developmental pathways. Leveraging individual organoid data, we develop a method to measure organoid heterogeneity, and we identify that activation of Wnt signaling early in retinal organoid cultures increases retinal cell classes up to six weeks later. Our data show sci-Plex's potential to dramatically scale-up the analysis of treatment conditions on relevant human models.

Approaches for single-cell RNA sequencing across tissues and cell types

Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.

High-throughput microfluidic droplets in biomolecular analytical system: A review

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

Middle-out methods for spatiotemporal tissue engineering of organoids

Organoids recapitulate many aspects of the complex three-dimensional (3D) organization found within native tissues and even display tissue and organ-level functionality. Traditional approaches to organoid culture have largely employed a top-down tissue engineering strategy, whereby cells are encapsulated in a 3D matrix, such as Matrigel, alongside well-defined biochemical cues that direct morphogenesis. However, the lack of spatiotemporal control over niche properties renders cellular processes largely stochastic. Therefore, bottom-up tissue engineering approaches have evolved to address some of these limitations and focus on strategies to assemble tissue building blocks with defined multi-scale spatial organization. However, bottom-up design reduces the capacity for self-organization that underpins organoid morphogenesis. Here, we introduce an emerging framework, which we term middle-out strategies, that relies on existing design principles and combines top-down design of defined synthetic matrices that support proliferation and self-organization with bottom-up modular engineered intervention to limit the degrees of freedom in the dynamic process of organoid morphogenesis. We posit that this strategy will provide key advances to guide the growth of organoids with precise geometries, structures and function, thereby facilitating an unprecedented level of biomimicry to accelerate the utility of organoids to more translationally relevant applications.

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.

High precision, high throughput generation of droplets containing single cells

The Poisson limit is a major problem for the isolation of single cells in different single-cell technologies and applications. In droplet-based single-cell assays, a scheme that is increasingly popular, the intrinsic randomness during single-cell encapsulation in droplets requires most of the created droplets to be empty, which has a profound impact on the efficiency and throughput of such techniques, and on the predictability of the combinatory droplet assays. Here we present a simple passive microfluidic system overcoming this limitation with unprecedented efficacy, allowing the generation of single-cell droplets for a wide range of operating conditions, with extremely high throughput (more than 22 000 single-cell loaded droplets per minute) and with an extremely low fault ratio (doublets or empty droplets), applicable to any cells and deformable particles. This versatile technique will shift the paradigm of single-cell encapsulation and will impact single-cell sequencing, rare cell isolation, multicellular/bead studies in immunology or cancer biology, etc.

Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics

Single-cell RNA sequencing (scRNA-seq) has been developed for characterizing the transcriptome of cells that are rare but of biological significance. With cell barcoding and microchip technologies, a suite of high-throughput scRNA-seq protocols enable transcriptome profiling in thousands of individual cells at single-cell resolution for classifying cell types, discovering novel cell populations, investigating cellular heterogeneity and elucidating lineage trajectories. Microchip technologies including microfluidics- and microwell-based platforms play a major role in high-throughput scRNA-seq. As the emerging technology, spatial transcriptomics integrates cellular transcriptomics with their spatial coordinates within tissues for spatially deciphering cellular composition, heterogeneity and cell-cell communications. Spatial transcriptomics has been increasingly recognized as one of the most powerful tools for discovering new biology and advancing precision medicine. Microfluidics as an enabling technology plays an increasingly important role in spatial transcriptomics. We review the technological spectrum and advances in high-throughput scRNA-seq and spatial transcriptomics, discuss their advantages and limitations, and pitch into new biology learned from these new tools.

Organoids

Organoids have attracted increasing attention because they are simple tissue-engineered cell-based in vitro models that recapitulate many aspects of the complex structure and function of the corresponding in vivo tissue. They can be dissected and interrogated for fundamental mechanistic studies on development, regeneration, and repair in human tissues. Organoids can also be used in diagnostics, disease modeling, drug discovery, and personalized medicine. Organoids are derived from either pluripotent or tissue-resident stem (embryonic or adult) or progenitor or differentiated cells from healthy or diseased tissues, such as tumors. To date, numerous organoid engineering strategies that support organoid culture and growth, proliferation, differentiation and maturation have been reported. This Primer serves to highlight the rationale underlying the selection and development of these materials and methods to control the cellular/tissue niche; and therefore, structure and function of the engineered organoid. We also discuss key considerations for generating robust organoids, such as those related to cell isolation and seeding, matrix and soluble factor selection, physical cues and integration. The general standards for data quality, reproducibility and deposition within the organoid community is also outlined. Lastly, we conclude by elaborating on the limitations of organoids in different applications, and key priorities in organoid engineering for the coming years.

Collagen type I-mediated mechanotransduction controls epithelial cell fate conversion during intestinal inflammation

BACKGROUND

The emerging concepts of fetal-like reprogramming following tissue injury have been well recognized as an important cue for resolving regenerative mechanisms of intestinal epithelium during inflammation. We previously revealed that the remodeling of mesenchyme with collagen fibril induces YAP/TAZ-dependent fate conversion of intestinal/colonic epithelial cells covering the wound bed towards fetal-like progenitors. To fully elucidate the mechanisms underlying the link between extracellular matrix (ECM) remodeling of mesenchyme and fetal-like reprogramming of epithelial cells, it is critical to understand how collagen type I influence the phenotype of epithelial cells. In this study, we utilize collagen sphere, which is the epithelial organoids cultured in purified collagen type I, to understand the mechanisms of the inflammatory associated reprogramming. Resolving the entire landscape of regulatory networks of the collagen sphere is useful to dissect the reprogrammed signature of the intestinal epithelium.

METHODS

We performed microarray, RNA-seq, and ATAC-seq analyses of the murine collagen sphere in comparison with Matrigel organoid and fetal enterosphere (FEnS). We subsequently cultured human colon epithelium in collagen type I and performed RNA-seq analysis. The enriched genes were validated by gene expression comparison between published gene sets and immunofluorescence in pathological specimens of ulcerative colitis (UC).

RESULTS

The murine collagen sphere was confirmed to have inflammatory and regenerative signatures from RNA-seq analysis. ATAC-seq analysis confirmed that the YAP/TAZ-TEAD axis plays a central role in the induction of the distinctive signature. Among them, TAZ has implied its relevant role in the process of reprogramming and the ATAC-based motif analysis demonstrated not only Tead proteins, but also Fra1 and Runx2, which are highly enriched in the collagen sphere. Additionally, the human collagen sphere also showed a highly significant enrichment of both inflammatory and fetal-like signatures. Immunofluorescence staining confirmed that the representative genes in the human collagen sphere were highly expressed in the inflammatory region of ulcerative colitis.

CONCLUSIONS

Collagen type I showed a significant influence in the acquisition of the reprogrammed inflammatory signature in both mice and humans. Dissection of the cell fate conversion and its mechanisms shown in this study can enhance our understanding of how the epithelial signature of inflammation is influenced by the ECM niche.

Integrating Micro and Nano Technologies for Cell Engineering and Analysis: Toward the Next Generation of Cell Therapy Workflows

The emerging field of cell therapy offers the potential to treat and even cure a diverse array of diseases for which existing interventions are inadequate. Recent advances in micro and nanotechnology have added a multitude of single cell analysis methods to our research repertoire. At the same time, techniques have been developed for the precise engineering and manipulation of cells. Together, these methods have aided the understanding of disease pathophysiology, helped formulate corrective interventions at the cellular level, and expanded the spectrum of available cell therapeutic options. This review discusses how micro and nanotechnology have catalyzed the development of cell sorting, cellular engineering, and single cell analysis technologies, which have become essential workflow components in developing cell-based therapeutics. The review focuses on the technologies adopted in research studies and explores the opportunities and challenges in combining the various elements of cell engineering and single cell analysis into the next generation of integrated and automated platforms that can accelerate preclinical studies and translational research.

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.

Intestinal cellular heterogeneity and disease development revealed by single-cell technology

The intestinal epithelium is responsible for food digestion and nutrient absorption and plays a critical role in hormone secretion, microorganism defense, and immune response. These functions depend on the integral single-layered intestinal epithelium, which shows diversified cell constitution and rapid self-renewal and presents powerful regeneration plasticity after injury. Derailment of homeostasis of the intestine epithelium leads to the development of diseases, most commonly including enteritis and colorectal cancer. Therefore, it is important to understand the cellular characterization of the intestinal epithelium at the molecular level and the mechanisms underlying its homeostatic maintenance. Single-cell technologies allow us to gain molecular insights at the single-cell level. In this review, we summarize the single-cell RNA sequencing applications to understand intestinal cell characteristics, spatiotemporal evolution, and intestinal disease development.

Everything You Always Wanted to Know About Organoid-Based Models (and Never Dared to Ask)

Homeostatic functions of a living tissue, such as the gastrointestinal tract, rely on highly sophisticated and finely tuned cell-to-cell interactions. These crosstalks evolve and continuously are refined as the tissue develops and give rise to specialized cells performing general and tissue-specific functions. To study these systems, stem cell-based in vitro models, often called organoids, and non-stem cell-based primary cell aggregates (called spheroids) appeared just over a decade ago. These models still are evolving and gaining complexity, making them the state-of-the-art models for studying cellular crosstalk in the gastrointestinal tract, and to investigate digestive pathologies, such as inflammatory bowel disease, colorectal cancer, and liver diseases. However, the use of organoid- or spheroid-based models to recapitulate in vitro the highly complex structure of in vivo tissue remains challenging, and mainly restricted to expert developmental cell biologists. Here, we condense the founding knowledge and key literature information that scientists adopting the organoid technology for the first time need to consider when using these models for novel biological questions. We also include information that current organoid/spheroid users could use to add to increase the complexity to their existing models. We highlight the current and prospective evolution of these models through bridging stem cell biology with biomaterial and scaffold engineering research areas. Linking these complementary fields will increase the in vitro mimicry of in vivo tissue, and potentially lead to more successful translational biomedical applications. Deepening our understanding of the nature and dynamic fine-tuning of intercellular crosstalks will enable identifying novel signaling targets for new or repurposed therapeutics used in many multifactorial diseases.