Long-term live imaging and multiscale analysis identify heterogeneity and core principles of epithelial organoid morphogenesis

Differential Effects of Confinement on the Dynamics of Normal and Tumor-Derived Pancreatic Ductal Organoids

Pancreatic ductal adenocarcinoma (PDAC) is a cancer of the epithelia comprising the ductal network of the pancreas. During disease progression, PDAC tumors recruit fibroblasts that promote fibrosis, increasing local tissue stiffness and subjecting epithelial cells to increased compressive forces. Previous in vitro studies have documented cytoskeletal and nuclear adaptation following compressive stresses in two-dimensional (2D) and three-dimensional (3D) environments. However, a comparison of the responses of normal and tumor-derived ductal epithelia to physiologically relevant confinement remains underexplored, especially in 3D organoids. Here we control confinement with an engineered 3D microenvironment composed of Matrigel mixed with a low yield stress granular microgel. Normal and tumor-derived murine pancreas organoids (normal and tumor) were cultured for 48 h within this composite 3D environment or in pure Matrigel to investigate the effects of confinement on morphogenesis and lumen expansion. In confinement, tumor organoids (mT) formed a lumen that expanded rapidly, whereas normal organoids (mN) expanded more slowly. Moreover, a majority of normal organoids in more-confined conditions exhibited an inverted apicobasal polarity compared to those in less-confined conditions. Tumor organoids exhibited a collective "pulsing" behavior that increased in confinement. These pulses generated forces sufficient to locally overcome the yield stress of the microgels in the direction of organoid expansion. Normal organoids more commonly exhibit unidirectional rotation. Our in vitro microgel confinement platform enabled the discovery of two distinct modes of collective force generation in organoids that may shed light on the mutual interactions between tumors and the microenvironment. These insights into in vitro dynamics may deepen our understanding of how the confinement of healthy cells within a fibrotic tumor niche disrupts tissue organization and function in vivo.

Ciliopathy organoid models: a comprehensive review

Cilia are membrane-bound organelles found on the surface of most mammalian cell types and play numerous roles in human physiology and development, including osmo- and mechanosensation, as well as signal transduction. Ciliopathies are a large group of, usually rare, genetic disorders resulting from abnormal ciliary structure or ciliary dysfunction that have a high collective prevalence. Autosomal dominant or recessive polycystic kidney disease (ADPKD/ARPKD), Bardet-Biedl-Syndrome, and primary ciliary dyskinesia (PCD) are the most frequent etiologies. Rodent and zebrafish models have improved the understanding of ciliopathy pathophysiology. Yet, the limitations of these genetically modified animal strains include the inability to fully replicate the phenotypic heterogeneity found in humans, including variable multiorgan involvement. Organoids, self-assembled three-dimensional cell-based models derived from human induced pluripotent stem cells (iPSCs) or primary tissues, can recapitulate certain aspects of the development, architecture, and function of the target organ "in the dish." The potential of organoids to model patient-specific genotype-phenotype correlations has increased their popularity in ciliopathy research and led to the first preclinical organoid-based ciliopathy drug screens. This review comprehensively summarizes and evaluates current ciliopathy organoid models, focusing on kidney, airway, liver, and retinal organoids, as well as the specific methodologies used for their cultivation and for interrogating ciliary dysfunction.

Revolutionising oral organoids with artificial intelligence

The convergence of organoid technology and artificial intelligence (AI) is poised to revolutionise oral healthcare. Organoids - three-dimensional structures derived from human tissues - offer invaluable insights into the complex biology of diseases, allowing researchers to effectively study disease mechanisms and test therapeutic interventions in environments that closely mimic in vivo conditions. In this review, we first present the historical development of organoids and delve into the current types of oral organoids, focusing on their use in disease models, regeneration and microbiome intervention. We then compare single-source and multi-lineage oral organoids and assess the latest progress in bioprinted, vascularised and neural-integrated organoids. In the next part of the review, we highlight significant advancements in AI, emphasising how AI algorithms may potentially promote organoid development for early disease detection and diagnosis, personalised treatment, disease prediction and drug screening. However, our main finding is the identification of remaining challenges, such as data integration and the critical need for rigorous validation of AI algorithms to ensure their clinical reliability. Our main viewpoint is that current AI-enabled oral organoids are still limited in applications but, as we look to the future, we offer insights into the potential transformation of AI-integrated oral organoids in oral disease diagnosis, oral microbial interactions and drug discoveries. By synthesising these components, this review aims to provide a comprehensive perspective on the current state and future implications of AI-enabled oral organoids, emphasising their role in advancing oral healthcare and improving patient outcomes.

Non-invasive label-free imaging analysis pipeline for in situ characterization of 3D brain organoids

Brain organoids provide a unique opportunity to model organ development in a system similar to human organogenesis in vivo. Brain organoids thus hold great promise for drug screening and disease modeling. Conventional approaches to organoid characterization predominantly rely on molecular analysis methods, which are expensive, time-consuming, labor-intensive, and involve the destruction of the valuable three-dimensional (3D) architecture of the organoids. This reliance on end-point assays makes it challenging to assess cellular and subcellular events occurring during organoid development in their 3D context. As a result, the long developmental processes are not monitored nor assessed. The ability to perform non-invasive assays is critical for longitudinally assessing features of organoid development during culture. In this paper, we demonstrate a label-free high-content imaging approach for observing changes in organoid morphology and structural changes occurring at the cellular and subcellular level. Enabled by microfluidic-based culture of 3D cell systems and a novel 3D quantitative phase imaging method, we demonstrate the ability to perform non-destructive high-resolution quantitative image analysis of the organoid. The highlighted results demonstrated in this paper provide a new approach to performing live, non-destructive monitoring of organoid systems during culture.

Applications of Lightsheet Fluorescence Microscopy by High Numerical Aperture Detection Lens

This Review explores the evolution, improvements, and recent applications of Light Sheet Fluorescence Microscopy (LSFM) in biological research using a high numerical aperture detection objective (lens) for imaging subcellular structures. The Review begins with an overview of the development of LSFM, tracing its evolution from its inception to its current state and emphasizing key milestones and technological advancements over the years. Subsequently, we will discuss various improvements of LSFM techniques, covering advancements in hardware such as illumination strategies, optical designs, and sample preparation methods that have enhanced imaging capabilities and resolution. The advancements in data acquisition and processing are also included, which provides a brief overview of the recent development of artificial intelligence. Fluorescence probes that were commonly used in LSFM will be highlighted, together with some insights regarding the selection of potential probe candidates for future LSFM development. Furthermore, we also discuss recent advances in the application of LSFM with a focus on high numerical aperture detection objectives for various biological studies. For sample preparation techniques, there are discussions regarding fluorescence probe selection, tissue clearing protocols, and some insights into expansion microscopy. Integrated setups such as adaptive optics, single objective modification, and microfluidics will also be some of the key discussion points in this Review. We hope that this comprehensive Review will provide a holistic perspective on the historical development, technical enhancements, and cutting-edge applications of LSFM, showcasing its pivotal role and future potential in advancing biological research.

Ecological and evolutionary dynamics to design and improve ovarian cancer treatment

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.

Patient-derived organoid models to decode liver pathophysiology

Liver diseases represent a growing global health challenge, and the increasing prevalence of obesity and metabolic disorders is set to exacerbate this crisis. To meet evolving regulatory demands, patient-specific in vitro liver models are essential for understanding disease mechanisms and developing new therapeutic approaches. Organoid models, which faithfully recapitulate liver biology, can be established from both non-malignant and malignant liver tissues, offering insight into various liver conditions, from acute injuries to chronic diseases and cancer. Improved understanding of liver microenvironments, innovative biomaterials, and advanced imaging techniques now facilitate comprehensive and unbiased data analysis, paving the way for personalised medicine. In this review, we discuss state-of-the-art patient-derived liver organoid models, recent technological advancements, and strategies to enhance their clinical impact.

A Curated Cell Life Imaging Dataset of Immune-enriched Pancreatic Cancer Organoids with Pre-trained AI Models

Tumor organoids are three-dimensional in vitro models which can recapitulate the complex mutational landscape and tissue architecture observed in cancer patients, providing a realistic model for testing novel therapies, including immunotherapies. A significant challenge in organoid research in oncology lies in developing efficient and reliable methods for segmenting organoid images, quantifying organoid growth, regression and response to treatments, as well as predicting the behavior of organoid systems. Up to now, a curated dataset of organoids co-cultured with immune cells is not available. To address this gap, we present a new public dataset, comprising both phase-contrast images of murine and patient-derived tumor organoids of one of the deadliest cancer types, the Pancreatic Ductal Adenocarcinoma, co-cultured with immune cells, and state-of-the-art algorithms for object detection and segmentation. Our dataset, OrganoIDNetData, encompassing 180 images with 33906 organoids, can be a potential common benchmark for different organoids segmentation protocols, moving beyond the current practice of training and testing these algorithms on isolated datasets.

Landscape of human organoids: Ideal model in clinics and research

In the last decade, organoid research has entered a golden era, signifying a pivotal shift in the biomedical landscape. The year 2023 marked a milestone with the publication of thousands of papers in this arena, reflecting exponential growth. However, amid this burgeoning expansion, a comprehensive and accurate overview of the field has been conspicuously absent. Our review is intended to bridge this gap, providing a panoramic view of the rapidly evolving organoid landscape. We meticulously analyze the organoid field from eight distinctive vantage points, harnessing our rich experience in academic research, industrial application, and clinical practice. We present a deep exploration of the advances in organoid technology, underpinned by our long-standing involvement in this arena. Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors, including oncology, toxicology, and drug development. We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine, enhancing high-throughput drug screening, and constructing physiologically pertinent disease models. Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology. We spotlight technological innovations, methodological evolution, and the broadening spectrum of applications, emphasizing the revolutionary influence of organoids in personalized medicine, oncology, drug discovery, and other fields. Looking ahead, we cautiously anticipate future developments in the field of organoid research, especially its potential implications for personalized patient care, new avenues of drug discovery, and clinical research. We trust that our comprehensive review will be an asset for researchers, clinicians, and patients with keen interest in personalized medical strategies. We offer a broad view of the present and prospective capabilities of organoid technology, encompassing a wide range of current and future applications. In summary, in this review we attempt a comprehensive exploration of the organoid field. We offer reflections, summaries, and projections that might be useful for current researchers and clinicians, and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.

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.

Bioengineering toolkits for potentiating organoid therapeutics

Organoids are three-dimensional, multicellular constructs that recapitulate the structural and functional features of specific organs. Because of these characteristics, organoids have been widely applied in biomedical research in recent decades. Remarkable advancements in organoid technology have positioned them as promising candidates for regenerative medicine. However, current organoids still have limitations, such as the absence of internal vasculature, limited functionality, and a small size that is not commensurate with that of actual organs. These limitations hinder their survival and regenerative effects after transplantation. Another significant concern is the reliance on mouse tumor-derived matrix in organoid culture, which is unsuitable for clinical translation due to its tumor origin and safety issues. Therefore, our aim is to describe engineering strategies and alternative biocompatible materials that can facilitate the practical applications of organoids in regenerative medicine. Furthermore, we highlight meaningful progress in organoid transplantation, with a particular emphasis on the functional restoration of various organs.

LUBAC-mediated M1 Ub regulates necroptosis by segregating the cellular distribution of active MLKL

Plasma membrane accumulation of phosphorylated mixed lineage kinase domain-like (MLKL) is a hallmark of necroptosis, leading to membrane rupture and inflammatory cell death. Pro-death functions of MLKL are tightly controlled by several checkpoints, including phosphorylation. Endo- and exocytosis limit MLKL membrane accumulation and counteract necroptosis, but the exact mechanisms remain poorly understood. Here, we identify linear ubiquitin chain assembly complex (LUBAC)-mediated M1 poly-ubiquitination (poly-Ub) as novel checkpoint for necroptosis regulation downstream of activated MLKL in cells of human origin. Loss of LUBAC activity inhibits tumor necrosis factor α (TNFα)-mediated necroptosis, not by affecting necroptotic signaling, but by preventing membrane accumulation of activated MLKL. Finally, we confirm LUBAC-dependent activation of necroptosis in primary human pancreatic organoids. Our findings identify LUBAC as novel regulator of necroptosis which promotes MLKL membrane accumulation in human cells and pioneer primary human organoids to model necroptosis in near-physiological settings.

Imaging actin organisation and dynamics in 3D

The actin cytoskeleton plays a critical role in cell architecture and the control of fundamental processes including cell division, migration and survival. The dynamics and organisation of F-actin have been widely studied in a breadth of cell types on classical two-dimensional (2D) surfaces. Recent advances in optical microscopy have enabled interrogation of these cytoskeletal networks in cells within three-dimensional (3D) scaffolds, tissues and in vivo. Emerging studies indicate that the dimensionality experienced by cells has a profound impact on the structure and function of the cytoskeleton, with cells in 3D environments exhibiting cytoskeletal arrangements that differ to cells in 2D environments. However, the addition of a third (and fourth, with time) dimension leads to challenges in sample preparation, imaging and analysis, necessitating additional considerations to achieve the required signal-to-noise ratio and spatial and temporal resolution. Here, we summarise the current tools for imaging actin in a 3D context and highlight examples of the importance of this in understanding cytoskeletal biology and the challenges and opportunities in this domain.

Combining organotypic tissue culture with light-sheet microscopy (OTCxLSFM) to study glioma invasion

Glioblastoma is a very aggressive tumor and represents the most common primary brain malignancy. Key characteristics include its high resistance against conventional treatments, such as radio- and chemotherapy and its diffuse tissue infiltration, preventing complete surgical resection. The analysis of migration and invasion processes in a physiological microenvironment allows for enhanced understanding of these phenomena and can lead to improved therapeutic approaches. Here, we combine two state-of-the-art techniques, adult organotypic brain tissue slice culture (OTC) and light-sheet fluorescence microscopy (LSFM) of cleared tissues in a combined method termed OTCxLSFM. Using this methodology, we can show that glioblastoma tissue infiltration can be effectively blocked through treatment with arsenic trioxide or WP1066, as well as genetic depletion of the tetraspanin, transmembrane receptor CD9, or signal transducer and activator of transcription 3 (STAT3). With our analysis pipeline, we gain single-cell level, three-dimensional information, as well as insights into the morphological appearance of the tumor cells.

Spectroscopic techniques for monitoring stem cell and organoid proliferation in 3D environments for therapeutic development

Spectroscopic techniques for monitoring stem cell and organoid proliferation have gained significant attention in therapeutic development. Spectroscopic techniques such as fluorescence, Raman spectroscopy, and infrared spectroscopy offer noninvasive and real-time monitoring of biochemical and biophysical changes that occur during stem cell and organoid proliferation. These techniques provide valuable insight into the underlying mechanisms of action of potential therapeutic agents, allowing for improved drug discovery and screening. This review highlights the importance of spectroscopic monitoring of stem cell and organoid proliferation and its potential impact on therapeutic development. Furthermore, this review discusses recent advances in spectroscopic techniques and their applications in stem cell and organoid research. Overall, this review emphasizes the importance of spectroscopic techniques as valuable tools for studying stem cell and organoid proliferation and their potential to revolutionize therapeutic development in the future.

Generative models of morphogenesis in developmental biology

Understanding the mechanism by which cells coordinate their differentiation and migration is critical to our understanding of many fundamental processes such as wound healing, disease progression, and developmental biology. Mathematical models have been an essential tool for testing and developing our understanding, such as models of cells as soft spherical particles, reaction-diffusion systems that couple cell movement to environmental factors, and multi-scale multi-physics simulations that combine bottom-up rule-based models with continuum laws. However, mathematical models can often be loosely related to data or have so many parameters that model behaviour is weakly constrained. Recent methods in machine learning introduce new means by which models can be derived and deployed. In this review, we discuss examples of mathematical models of aspects of developmental biology, such as cell migration, and how these models can be combined with these recent machine learning methods.

Dynamic full-field optical coherence tomography module adapted to commercial microscopes allows longitudinal in vitro cell culture study

Dynamic full-field optical coherence tomography (D-FFOCT) has recently emerged as a label-free imaging tool, capable of resolving cell types and organelles within 3D live samples, whilst monitoring their activity at tens of milliseconds resolution. Here, a D-FFOCT module design is presented which can be coupled to a commercial microscope with a stage top incubator, allowing non-invasive label-free longitudinal imaging over periods of minutes to weeks on the same sample. Long term volumetric imaging on human induced pluripotent stem cell-derived retinal organoids is demonstrated, highlighting tissue and cell organization processes such as rosette formation and mitosis as well as cell shape and motility. Imaging on retinal explants highlights single 3D cone and rod structures. An optimal workflow for data acquisition, postprocessing and saving is demonstrated, resulting in a time gain factor of 10 compared to prior state of the art. Finally, a method to increase D-FFOCT signal-to-noise ratio is demonstrated, allowing rapid organoid screening.

In-silico and in-vitro morphometric analysis of intestinal organoids

Organoids offer a powerful model to study cellular self-organisation, the growth of specific tissue morphologies in-vitro, and to assess potential medical therapies. However, the intrinsic mechanisms of these systems are not entirely understood yet, which can result in variability of organoids due to differences in culture conditions and basement membrane extracts used. Improving the standardisation of organoid cultures is essential for their implementation in clinical protocols. Developing tools to assess and predict the behaviour of these systems may produce a more robust and standardised biological model to perform accurate clinical studies. Here, we developed an algorithm to automate crypt-like structure counting on intestinal organoids in both in-vitro and in-silico images. In addition, we modified an existing two-dimensional agent-based mathematical model of intestinal organoids to better describe the system physiology, and evaluated its ability to replicate budding structures compared to new experimental data we generated. The crypt-counting algorithm proved useful in approximating the average number of budding structures found in our in-vitro intestinal organoid culture images on days 3 and 7 after seeding. Our changes to the in-silico model maintain the potential to produce simulations that replicate the number of budding structures found on days 5 and 7 of in-vitro data. The present study aims to aid in quantifying key morphological structures and provide a method to compare both in-vitro and in-silico experiments. Our results could be extended later to 3D in-silico models.

Light and electron microscopy continuum-resolution imaging of 3D cell cultures

3D cell cultures, in particular organoids, are emerging models in the investigation of healthy or diseased tissues. Understanding the complex cellular sociology in organoids requires integration of imaging modalities across spatial and temporal scales. We present a multi-scale imaging approach that traverses millimeter-scale live-cell light microscopy to nanometer-scale volume electron microscopy by performing 3D cell cultures in a single carrier that is amenable to all imaging steps. This allows for following organoids' growth, probing their morphology with fluorescent markers, identifying areas of interest, and analyzing their 3D ultrastructure. We demonstrate this workflow on mouse and human 3D cultures and use automated image segmentation to annotate and quantitatively analyze subcellular structures in patient-derived colorectal cancer organoids. Our analyses identify local organization of diffraction-limited cell junctions in compact and polarized epithelia. The continuum-resolution imaging pipeline is thus suited to fostering basic and translational organoid research by simultaneously exploiting the advantages of light and electron microscopy.

Quantifying the drug response of patient-derived organoid clusters by aggregated morphological indicators with multi-parameters based on optical coherence tomography

Patient-derived organoids (PDOs) serve as excellent tools for personalized drug screening to predict clinical outcomes of cancer treatment. However, current methods for efficient quantification of drug response are limited. Herein, we develop a method for label-free, continuous tracking imaging and quantitative analysis of drug efficacy using PDOs. A self-developed optical coherence tomography (OCT) system was used to monitor the morphological changes of PDOs within 6 days of drug administration. OCT image acquisition was performed every 24 h. An analytical method for organoid segmentation and morphological quantification was developed based on a deep learning network (EGO-Net) to simultaneously analyze multiple morphological organoid parameters under the drug's effect. Adenosine triphosphate (ATP) testing was conducted on the last day of drug treatment. Finally, a corresponding aggregated morphological indicator (AMI) was established using principal component analysis (PCA) based on the correlation analysis between OCT morphological quantification and ATP testing. Determining the AMI of organoids allowed quantitative evaluation of the PDOs responses to gradient concentrations and combinations of drugs. Results showed that there was a strong correlation (correlation coefficient >90%) between the results using the AMI of organoids and those from ATP testing, which is the standard test used for bioactivity measurement. Compared with single-time-point morphological parameters, the introduction of time-dependent morphological parameters can reflect drug efficacy with improved accuracy. Additionally, the AMI of organoids was found to improve the efficiency of 5-fluorouracil(5FU) against tumor cells by allowing the determination of the optimum concentration, and the discrepancies in response among different PDOs using the same drug combinations could also be measured. Collectively, the AMI established by OCT system combined with PCA could quantify the multidimensional morphological changes of organoids under the drug's effect, providing a simple and efficient tool for drug screening in PDOs.

Who's really in charge: Diverse follower cell behaviors in collective cell migration

Collective cell migrations drive morphogenesis, wound healing, and cancer dissemination. Cells located at the front are considered leaders while those behind them are defined topologically as followers. Leader cell behaviors, including chemotaxis and their coupling to followers, have been well-studied and reviewed. However, the contributions of follower cells to collective cell migration represent an emerging area of interest. In this perspective, we highlight recent research into the broadening array of follower cell behaviors found in moving collectives. We describe examples of follower cells that possess cryptic leadership potential and followers that lack that potential but contribute in diverse and sometimes surprising ways to collective movement, even steering from behind. We highlight collectives in which all cells both lead and follow, and a few passive passengers. The molecular mechanisms controlling follower cell function and behavior are just emerging and represent an exciting frontier in collective cell migration research.

Label-free photothermal optical coherence microscopy to locate desired regions of interest in multiphoton imaging of volumetric specimens

Biochip-based research is currently evolving into a three-dimensional and large-scale basis similar to the in vivo microenvironment. For the long-term live and high-resolution imaging in these specimens, nonlinear microscopy capable of label-free and multiscale imaging is becoming increasingly important. Combination with non-destructive contrast imaging will be useful for effectively locating regions of interest (ROI) in large specimens and consequently minimizing photodamage. In this study, a label-free photothermal optical coherence microscopy (OCM) serves as a new approach to locate the desired ROI within biological samples which are under investigation by multiphoton microscopy (MPM). The weak photothermal perturbation in sample by the MPM laser with reduced power was detected at the endogenous photothermal particles within the ROI using the highly sensitive phase-differentiated photothermal (PD-PT) OCM. By monitoring the temporal change of the photothermal response signal of the PD-PT OCM, the hotspot generated within the sample focused by the MPM laser was located on the ROI. Combined with automated sample movement in the x-y axis, the focal plane of MPM could be effectively navigated to the desired portion of a volumetric sample for high-resolution targeted MPM imaging. We demonstrated the feasibility of the proposed method in second harmonic generation microscopy using two phantom samples and a biological sample, a fixed insect on microscope slide, with dimensions of 4 mm wide, 4 mm long, and 1 mm thick.

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis

Plant organ morphogenesis spans several orders of magnitude in time and space. Because of limitations in live-imaging, analysing whole organ growth from initiation to mature stages typically rely on static data sampled from different timepoints and individuals. We introduce a new model-based strategy for dating organs and for reconstructing morphogenetic trajectories over unlimited time windows based on static data. Using this approach, we show that Arabidopsis thaliana leaves are initiated at regular 1-day intervals. Despite contrasted adult morphologies, leaves of different ranks exhibited shared growth dynamics, with linear gradations of growth parameters according to leaf rank. At the sub-organ scale, successive serrations from same or different leaves also followed shared growth dynamics, suggesting that global and local leaf growth patterns are decoupled. Analysing mutants leaves with altered morphology highlighted the decorrelation between adult shapes and morphogenetic trajectories, thus stressing the benefits of our approach in identifying determinants and critical timepoints during organ morphogenesis.

Prominin-1 promotes restitution of the murine extrahepatic biliary luminal epithelium following cholestatic liver injury

BACKGROUND AND AIMS

Restitution of the extrahepatic biliary luminal epithelium in cholangiopathies is poorly understood. Prominin-1 (Prom1) is a key component of epithelial ciliary body of stem/progenitor cells. Given that intrahepatic Prom1-expressing progenitor cells undergo cholangiocyte differentiation, we hypothesized that Prom1 may promote restitution of the extrahepatic bile duct (EHBD) epithelium following injury.

APPROACH AND RESULTS

Utilizing various murine biliary injury models, we identified Prom1-expressing cells in the peribiliary glands of the EHBD. These Prom1-expressing cells are progenitor cells which give rise to cholangiocytes as part of the normal maintenance of the EHBD epithelium. Following injury, these cells proliferate significantly more rapidly to re-populate the biliary luminal epithelium. Null mutation of Prom1 leads to significantly >10-fold dilated peribiliary glands following rhesus rotavirus-mediated biliary injury. Cultured organoids derived from Prom1 knockout mice are comprised of biliary progenitor cells with altered apical-basal cellular polarity, significantly fewer and shorter cilia, and decreased organoid proliferation dynamics consistent with impaired cell motility.

CONCLUSIONS

We, therefore, conclude that Prom1 is involved in biliary epithelial restitution following biliary injury in part through its role in supporting cell polarity.

Automated detection and growth tracking of 3D bio-printed organoid clusters using optical coherence tomography with deep convolutional neural networks

Organoids are advancing the development of accurate prediction of drug efficacy and toxicity in vitro. These advancements are attributed to the ability of organoids to recapitulate key structural and functional features of organs and parent tumor. Specifically, organoids are self-organized assembly with a multi-scale structure of 30-800 μm, which exacerbates the difficulty of non-destructive three-dimensional (3D) imaging, tracking and classification analysis for organoid clusters by traditional microscopy techniques. Here, we devise a 3D imaging, segmentation and analysis method based on Optical coherence tomography (OCT) technology and deep convolutional neural networks (CNNs) for printed organoid clusters (Organoid Printing and optical coherence tomography-based analysis, OPO). The results demonstrate that the organoid scale influences the segmentation effect of the neural network. The multi-scale information-guided optimized EGO-Net we designed achieves the best results, especially showing better recognition workout for the biologically significant organoid with diameter ≥50 μm than other neural networks. Moreover, OPO achieves to reconstruct the multiscale structure of organoid clusters within printed microbeads and calibrate the printing errors by segmenting the printed microbeads edges. Overall, the classification, tracking and quantitative analysis based on image reveal that the growth process of organoid undergoes morphological changes such as volume growth, cavity creation and fusion, and quantitative calculation of the volume demonstrates that the growth rate of organoid is associated with the initial scale. The new method we proposed enable the study of growth, structural evolution and heterogeneity for the organoid cluster, which is valuable for drug screening and tumor drug sensitivity detection based on organoids.

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.

Label-Free Imaging Analysis of Patient-Derived Cholangiocarcinoma Organoids after Sorafenib Treatment

Monitoring tumor growth dynamics is crucial for understanding cancer. To establish an in vitro method for the continuous assessment of patient-specific tumor growth, tumor organoids were generated from patients with intrahepatic CCA (iCCA). Organoid growth was monitored for 48 h by label-free live brightfield imaging. Growth kinetics were calculated and validated by MTS assay as well as immunohistochemistry of Ki67 to determine proliferation rates. We exposed iCCA organoids (iCCAOs) and non-tumor intrahepatic cholangiocyte organoids (ICOs) to sub-therapeutic concentrations of sorafenib. Monitoring the expansion rate of iCCAOs and ICOs revealed that iCCAO growth was inhibited by sorafenib in a time- and dose-dependent fashion, while ICOs were unaffected. Quantification of the proliferation marker Ki67 confirmed inhibition of iCCAO growth by roughly 50% after 48 h of treatment with 4 µM sorafenib. We established a robust analysis pipeline combining brightfield microscopy and a straightforward image processing approach for the label-free growth monitoring of patient-derived iCCAOs. Combined with bioanalytical validation, this approach is suitable for a fast and efficient high-throughput drug screening in tumor organoids to develop patient-specific systemic treatment options.

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses. However, these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (95%) and size (97%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified strong dose effect sizes on organoid circularity, solidity, and eccentricity. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

Pancreas organoid models of development and regeneration

Organoids have become one of the fastest progressing and applied models in biological and medical research, and various organoids have now been developed for most of the organs of the body. Here, we review the methods developed to generate pancreas organoids in vitro from embryonic, fetal and adult cells, as well as pluripotent stem cells. We discuss how these systems have been used to learn new aspects of pancreas development, regeneration and disease, as well as their limitations and potential for future discoveries.

Multiscale fluorescence imaging of living samples

Fluorescence microscopy is a highly effective tool for interrogating biological structure and function, particularly when imaging across multiple spatiotemporal scales. Here we survey recent innovations and applications in the relatively understudied area of multiscale fluorescence imaging of living samples. We discuss fundamental challenges in live multiscale imaging and describe successful examples that highlight the power of this approach. We attempt to synthesize general strategies from these test cases, aiming to help accelerate progress in this exciting area.

Multiscale light-sheet organoid imaging framework

Organoids provide an accessible in vitro system to mimic the dynamics of tissue regeneration and development. However, long-term live-imaging of organoids remains challenging. Here we present an experimental and image-processing framework capable of turning long-term light-sheet imaging of intestinal organoids into digital organoids. The framework combines specific imaging optimization combined with data processing via deep learning techniques to segment single organoids, their lumen, cells and nuclei in 3D over long periods of time. By linking lineage trees with corresponding 3D segmentation meshes for each organoid, the extracted information is visualized using a web-based "Digital Organoid Viewer" tool allowing combined understanding of the multivariate and multiscale data. We also show backtracking of cells of interest, providing detailed information about their history within entire organoid contexts. Furthermore, we show cytokinesis failure of regenerative cells and that these cells never reside in the intestinal crypt, hinting at a tissue scale control on cellular fidelity.

RNA-sequencing of single cholangiocyte-derived organoids reveals high organoid-to organoid variability

Over the last decades, organoids have been established from most of the tissue-resident stem and iPS cells. They hold great promise for our understanding of mammalian organ development, but also for the study of disease or even personalised medicine. In recent years, several reports hinted at intraculture organoid variability, but a systematic analysis of such heterogeneity has not been performed before. Here, we used RNA-seq of individual intrahepatic cholangiocyte organoids to address this question. We find that batch-to-batch variation is very low, whereas passage number has a profound impact on gene expression profiles. On the other hand, there is organoid-to-organoid variability within a culture. Using differential gene expression, we did not identify specific pathways that drive this variability, pointing towards possible effects of the microenvironment within the culture condition. Taken together, our study provides a framework for organoid researchers to properly consider experimental design.

Fourier light-field imaging of human organoids with a hybrid point-spread function

Volumetric interrogation of the cellular morphology and dynamic processes of organoid systems with a high spatiotemporal resolution provides critical insights for understanding organogenesis, tissue homeostasis, and organ function. Fluorescence microscopy has emerged as one of the most vital and informative driving forces for probing the cellular complexity in organoid research. However, the underlying scanning mechanism of conventional imaging methods inevitably compromises the time resolution of volumetric acquisition, leading to increased photodamage and inability to capture fast cellular and tissue dynamic processes. Here, we report Fourier light-field microscopy using a hybrid point-spread function (hPSF-FLFM) for fast, volumetric, and high-resolution imaging of entire organoids. hPSF-FLFM transforms conventional 3D microscopy and enables exploration of less accessible spatiotemporally-challenging regimes for organoid research. To validate hPSF-FLFM, we demonstrate 3D imaging of rapid responses to extracellular physical cues such as osmotic and mechanical stresses on human induced pluripotent stem cells-derived colon organoids (hCOs). The system offers cellular (2-3 μm and 5-6 μm in x-y and z, respectively) and millisecond-scale spatiotemporal characterization of whole-organoid dynamic changes that span large imaging volumes (>900 μm × 900 μm × 200 μm in x, y, z, respectively). The hPSF-FLFM method provides a promising avenue to explore spatiotemporal-challenging cellular responses in a wide variety of organoid research.

Present Application and Perspectives of Organoid Imaging Technology

An organoid is a miniaturized and simplified in vitro model with a similar structure and function to a real organ. In recent years, the use of organoids has increased explosively in the field of growth and development, disease simulation, drug screening, cell therapy, etc. In order to obtain necessary information, such as morphological structure, cell function and dynamic signals, it is necessary and important to directly monitor the culture process of organoids. Among different detection technologies, imaging technology is a simple and convenient choice and can realize direct observation and quantitative research. In this review, the principle, advantages and disadvantages of imaging technologies that have been applied in organoids research are introduced. We also offer an overview of prospective technologies for organoid imaging. This review aims to help biologists find appropriate imaging techniques for different areas of organoid research, and also contribute to the development of organoid imaging systems.

Computational Methods for Single-Cell Imaging and Omics Data Integration

Integrating single cell omics and single cell imaging allows for a more effective characterisation of the underlying mechanisms that drive a phenotype at the tissue level, creating a comprehensive profile at the cellular level. Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques such as MRI, CT, and PET. These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring at the tissue level. Single cell imaging can act as an intermediary between these levels. Meanwhile new technologies continue to arrive that can be used to interrogate the genome of single cells and its related omics datasets. As these two areas, single cell imaging and single cell omics, each advance independently with the development of novel techniques, the opportunity to integrate these data types becomes more and more attractive. This review outlines some of the technologies and methods currently available for generating, processing, and analysing single-cell omics- and imaging data, and how they could be integrated to further our understanding of complex biological phenomena like ageing. We include an emphasis on machine learning algorithms because of their ability to identify complex patterns in large multidimensional data.

Fluorescence Microscopy-An Outline of Hardware, Biological Handling, and Fluorophore Considerations

Fluorescence microscopy has become a critical tool for researchers to understand biological processes at the cellular level. Micrographs from fixed and live-cell imaging procedures feature in a plethora of scientific articles for the field of cell biology, but the complexities of fluorescence microscopy as an imaging tool can sometimes be overlooked or misunderstood. This review seeks to cover the three fundamental considerations when designing fluorescence microscopy experiments: (1) hardware availability; (2) amenability of biological models to fluorescence microscopy; and (3) suitability of imaging agents for intended applications. This review will help equip the reader to make judicious decisions when designing fluorescence microscopy experiments that deliver high-resolution and informative images for cell biology.

Thin fluorinated polymer film microcavity arrays for 3D cell culture and label-free automated feature extraction

There is an increasing need for automated label-free morphometric analysis using brightfield microscopy images of 3D cell culture systems. This requires automated feature detection which can be achieved by improving the image contrast, e.g. by reducing the refractive index mismatch in the light path. Here, a novel microcavity platform fabricated using microthermoforming of thin fluorinated ethylene-propylene (FEP) films which match the refractive index of cell culture medium and provide a homogenous background signal intensity is described. FEP is chemically inert, mechanically stable and has been used as a substrate for light sheet microscopy. The microcavities promote formation of mouse embryonic stem cell (mESC) aggregates, which show axial elongation and germ layer specification similar to embryonic development. A label-free feature extraction pipeline based on a machine-learning plugin for FIJI is used to extract morphometric features from time-lapse imaging in a highly robust and reproducible manner. Lastly, the pipeline is utilized for testing the effect of the drug Latrunculin A on the mESC aggregates, highlighting the platform's potential for high-content screening (HCS) in drug discovery. This new microengineered tool is an important step towards label-free imaging of free-floating stem cell aggregates and paves the way for high-content drug testing and translational studies.

Human neural organoids: Models for developmental neurobiology and disease

Human organoids stand at the forefront of basic and translational research, providing experimentally tractable systems to study human development and disease. These stem cell-derived, in vitro cultures can generate a multitude of tissue and organ types, including distinct brain regions and sensory systems. Neural organoid systems have provided fundamental insights into molecular mechanisms governing cell fate specification and neural circuit assembly and serve as promising tools for drug discovery and understanding disease pathogenesis. In this review, we discuss several human neural organoid systems, how they are generated, advances in 3D imaging and bioengineering, and the impact of organoid studies on our understanding of the human nervous system.

MOrgAna: accessible quantitative analysis of organoids with machine learning

Recent years have seen a dramatic increase in the application of organoids to developmental biology, biomedical and translational studies. Organoids are large structures with high phenotypic complexity and are imaged on a wide range of platforms, from simple benchtop stereoscopes to high-content confocal-based imaging systems. The large volumes of images, resulting from hundreds of organoids cultured at once, are becoming increasingly difficult to inspect and interpret. Hence, there is a pressing demand for a coding-free, intuitive and scalable solution that analyses such image data in an automated yet rapid manner. Here, we present MOrgAna, a Python-based software that implements machine learning to segment images, quantify and visualize morphological and fluorescence information of organoids across hundreds of images, each with one object, within minutes. Although the MOrgAna interface is developed for users with little to no programming experience, its modular structure makes it a customizable package for advanced users. We showcase the versatility of MOrgAna on several in vitro systems, each imaged with a different microscope, thus demonstrating the wide applicability of the software to diverse organoid types and biomedical studies.

Non-invasive analysis of pancreas organoids in synthetic hydrogels defines material-cell interactions and luminal composition

The cultivation of cells forming three-dimensional structures like organoids holds great potential in different fields of life sciences and is gaining increasing interest with regards to clinical applications and personalised medicine. However, conventional hydrogels used as cell cultivation matrices (e.g. Matrigel®) contain animal-derived components in varying quantities, implicating low reproducibility of experiments and limited applicability for clinical use. Based on the strong need for developing novel, well defined, and animal-free hydrogels for 3D cell cultures, this study presents a comprehensive analysis of pancreas organoid cultivation in two synthetic hydrogels. Besides established visualisation techniques to monitor organoid formation and growth, confocal Raman microscopy was used for the first time to evaluate the gel matrices and organoid formation within the gels. The approach revealed so far not accessible information about material-cell interactions and the composition of the organoid lumen in a non-invasive and label-free manner. Confocal Raman microscopy thereby enabled a systematic characterisation of different hydrogels with respect to cell culture compatibility and allowed for the rational selection of a hydrogel formulation to serve as a synthetic and fully defined alternative to animal-derived cultivation matrices.

Current Advances in Basic and Translational Research of Cholangiocarcinoma

Simple Summary

Cholangiocarcinoma (CCA) is highly malignant biliary tract cancer, which is characterized by limited treatment options and poor prognosis. Basic science studies to seek therapies for CCA are also limited due to lack of gold-standard experimental models and heterogeneity of CCA resulting in various genetic alterations and origins of tumor cells. Recent studies have developed new experimental models and techniques that may facilitate CCA studies leading to the development of novel treatments. This review summarizes the update in current basic studies of CCA.

Abstract

Cholangiocarcinoma (CCA) is a type of biliary tract cancer emerging from the biliary tree. CCA is the second most common primary liver cancer after hepatocellular carcinoma and is highly aggressive resulting in poor prognosis and patient survival. Treatment options for CCA patients are limited since early diagnosis is challenging, and the efficacy of chemotherapy or radiotherapy is also limited because CCA is a heterogeneous malignancy. Basic research is important for CCA to establish novel diagnostic testing and more effective therapies. Previous studies have introduced new techniques and methodologies for animal models, in vitro models, and biomarkers. Recent experimental strategies include patient-derived xenograft, syngeneic mouse models, and CCA organoids to mimic heterogeneous CCA characteristics of each patient or three-dimensional cellular architecture in vitro. Recent studies have identified various novel CCA biomarkers, especially non-coding RNAs that were associated with poor prognosis or metastases in CCA patients. This review summarizes current advances and limitations in basic and translational studies of CCA.