Artificial three-dimensional niches deconstruct pancreas development in vitro.
Ontology highlight
ABSTRACT:
SUBMITTER: Greggio C
PROVIDER: S-EPMC4007719 | biostudies-literature | 2013 Nov
REPOSITORIES: biostudies-literature
Publications
Artificial three-dimensional niches deconstruct pancreas development in vitro.
Greggio Chiara C De Franceschi Filippo F Figueiredo-Larsen Manuel M Gobaa Samy S Ranga Adrian A Semb Henrik H Lutolf Matthias M Grapin-Botton Anne A
Development (Cambridge, England) 20131101 21
In the context of a cellular therapy for diabetes, methods for pancreatic progenitor expansion and subsequent differentiation into insulin-producing beta cells would be extremely valuable. Here we establish three-dimensional culture conditions in Matrigel that enable the efficient expansion of dissociated mouse embryonic pancreatic progenitors. By manipulating the medium composition we generate either hollow spheres, which are mainly composed of pancreatic progenitors, or complex organoids that ...[more]
Similar Datasets
Project description:Pancreatic islets are endocrine micro-organs scattered throughout the exocrine pancreas. Islets are surrounded by a network of vasculature, ducts, neurons, and extracellular matrix. Three-dimensional imaging is critical for such structural analyses. We have adapted transparent tissue tomography to develop a method to image thick pancreatic tissue slices (1 mm) with multifluorescent channels. This method takes only 2 to 3 days from specimen preparation and immunohistochemical staining to clearing tissues and imaging. Reconstruction of the intact pancreas visualizes islets with ?, ?, and ? cells together with their surrounding networks. Capturing several hundred islets at once ensures sufficient power for statistical analyses. Further surface rendering provides clear views of the anatomical relationship between islets and their microenvironment as well as the basis for volumetric quantification. As a proof-of-principle demonstration, we show an islet size-dependent increase of intraislet capillary density and an inverse decrease in sphericity.
| S-EPMC5839749 | biostudies-literature
Project description:Background and aimsAssessing algorithms of artificial pancreas systems is critical in developing automated and fault-tolerant solutions that work outside clinical settings. The development and evaluation of algorithms can be facilitated with a platform that conducts virtual clinical trials. We present in this paper a clinically validated cloud-based distributed platform that supports the development and comprehensive testing of single and dual-hormone algorithms for type 1 diabetes mellitus (T1DM).MethodsThe platform is built on principles of object-oriented design and runs user algorithms in real-time virtual clinical trials utilizing a multi-threaded environment enabled by concurrent execution over a cloud infrastructure. The platform architecture isolates user algorithms located on personal machines from proprietary patient data running on the cloud. Users import a plugin into their algorithms (Matlab, Python, or Java) to connect to the platform. Once connected, users interact with a graphical interface to design experimental protocols for their trials. Protocols include trial duration in days, mealtimes and amounts, variability in mealtimes and amounts, carbohydrate counting errors, snacks, and onboard insulin levels.ResultsThe platform facilitates development by solving the ODE model in the cloud on large CPU-optimized machines, providing a 62% improvement in memory, speed and CPU utilization. Users can easily debug & modify code, test multiple strategies, and generate detailed clinical performance reports. We validated and integrated into the platform a glucoregulatory system of ordinary differential equations (ODEs) parameterized with clinical data to mimic the inter and intra-day variability of glucose responses of 15 T1DM patients.ConclusionThe platform utilizes the validated patient model to conduct virtual clinical trials for the rapid development and testing of closed-loop algorithms for T1DM.
| S-EPMC7746189 | biostudies-literature
Project description:Modeling the in vivo microenvironment typically involves placing cells in a three-dimensional (3D) extracellular matrix (ECM) in physiologically relevant context with respect to other cells. The mechanical and chemical features of 3D microenvironments play important roles in tissue engineering, tumor growth and metastasis, and in defining stem cell niches, and it is increasingly recognized that cells behave much differently when surrounded by a 3D ECM than when anchored to a 2D substrate. To create microenvironments that more closely mimic in vivo settings, here we describe a novel microfluidic device that allows multiple discrete constructs of 3D cell-laden hydrogels to be patterned in a sequence of simple steps. The microfluidic platform allows for real-time imaging of the interactions between multiple cell types exposed to both autocrine and paracrine signaling molecules, all within a 3D ECM environment. Detailed modeling determined that surface tension, hydrophobic interactions, and spatial geometry were important factors in containing the gels within distinct separate channels during the filling process. This allowed us to pattern multiple gel types side-by-side and pattern 3D gels spatially with tight dimensional control. Cells embedded in gels could be patterned by culturing MDA-MB-231 metastatic breast cancer cells and RAW 264.1 macrophage cells within distinct collagen type I and Matrigel ECM environments, respectively. Over a 7 day culture experiment, RAW cells invaded into neighboring gels containing MDA-MB-231 cells, but not into gels lacking cells. These studies demonstrate the versatility and potential of this new microfluidic platform to engineer 3D microscale architectures to investigate cell-cell and cell-matrix interactions.
| S-EPMC3758562 | biostudies-literature
Project description:Neuroendocrine tumors (NETs) of the pancreas are rare neoplasms that present complex challenges to diagnosis and treatment due to their indolent course. The incidence of pancreatic neuroendocrine tumors has increased significantly over the past two decades. A limited number of pancreatic neuroendocrine cell lines are currently available for the research. Here, we present 3D-iNET ORION, a novel 3-dimensional (spheroid) cell line, isolated from human pancreatic neuroendocrine tumor liver metastasis. Three-dimensionally grown (3D) cancer cell lines have gained interest over the past years as 3D cancer cell lines better recapitulate the in vivo structure of tumors, and are more suitable for in vitro and in vivo experiments. 3D-iNET ORION cancer cell line showed high potential to form tumorspheres when embedded in Matrigel matrix and expresses synaptophysin and EpCAM. Electron microscopy analysis of cancer cell line proved the presence of dense neurosecretory granules. When xenografted into athymic mice, 3D-iNET ORION cells produce slow-growing tumors, positive for chromogranin and synaptophysin. Human Core Exome Panel Analysis has shown that 3DiNET ORION cell line retains the genetic aberration profile detected in the original tumor. In conclusion, our newly developed neuroendocrine cancer cell line can be considered as a new research tool for in vitro and in vivo experiments.
| S-EPMC11341600 | biostudies-literature
Project description:ObjectiveOur aim is to analyze the identifiability of three commonly used control-oriented models for glucose control in patients with type 1 diabetes (T1D).MethodsStructural and practical identifiability analysis were performed on three published control-oriented models for glucose control in patients with type 1 diabetes (T1D): the subcutaneous oral glucose minimal model (SOGMM), the intensive control insulin-nutrition-glucose (ICING) model, and the minimal model control-oriented (MMC). Structural identifiability was addressed with a combination of the generating series (GS) approach and identifiability tableaus whereas practical identifiability was studied by means of (1) global ranking of parameters via sensitivity analysis together with the Latin hypercube sampling method (LHS) and (2) collinearity analysis among parameters. For practical identifiability and model identification, continuous glucose monitor (CGM), insulin pump, and meal records were selected from a set of patients (n = 5) on continuous subcutaneous insulin infusion (CSII) that underwent a clinical trial in an outpatient setting. The performance of the identified models was analyzed by means of the root mean square (RMS) criterion.ResultsA reliable set of identifiable parameters was found for every studied model after analyzing the possible identifiability issues of the original parameter sets. According to an importance factor ([Formula: see text]), it was shown that insulin sensitivity is not the most influential parameter from the dynamical point of view, that is, is not the parameter impacting the outputs the most of the three models, contrary to what is assumed in the literature. For the test data, the models demonstrated similar performance with most RMS values around 20 mg/dl (min: 15.64 mg/dl, max: 51.32 mg/dl). However, MMC failed to identify the model for patient 4. Also, considering the three models, the MMC model showed the higher parameter variability when reidentified every 6 hours.ConclusionThis study shows that both structural and practical identifiability analysis need to be considered prior to the model identification/individualization in patients with T1D. It was shown that all the studied models are able to represent the CGM data, yet their usefulness in a hypothetical artificial pancreas could be a matter of debate. In spite that the three models do not capture all the dynamics and metabolic effects as a maximal model (ie, our FDA-accepted UVa/Padova simulator), SOGMM and ICING appear to be more appealing than MMC regarding both the performance and parameter variability after reidentification. Although the model predictions of ICING are comparable to the ones of the SOGMM model, the large parameter set makes the model prone to overfitting if all parameters are identified. Moreover, the existence of a high nonlinear function like [Formula: see text] prevents the use of tools from the linear systems theory.
| S-EPMC6134618 | biostudies-literature
Project description:A predictive framework for the evolution of stem cell biology in 3-D is currently lacking. In this study we propose deep image informatics of the nuclear biology of stem cells to elucidate how 3-D biomaterials steer stem cell lineage phenotypes. The approach is based on high content imaging informatics to capture minute variations in the 3-D spatial organization of splicing factor SC-35 in the nucleoplasm as a marker to classify emergent cell phenotypes of human mesenchymal stem cells (hMSCs). The cells were cultured in varied 3-D culture systems including hydrogels, electrospun mats and salt leached scaffolds. The approach encompasses high resolution 3-D imaging of SC-35 domains and high content image analysis (HCIA) to compute quantitative 3-D nuclear metrics for SC-35 organization in single cells in concert with machine learning approaches to construct a predictive cell-state classification model. Our findings indicate that hMSCs cultured in collagen hydrogels and induced to differentiate into osteogenic or adipogenic lineages could be classified into the three lineages (stem, adipogenic, osteogenic) with ⩾80% precision and sensitivity, within 72h. Using this framework, the augmentation of osteogenesis by scaffold design exerted by porogen leached scaffolds was also profiled within 72h with ∼80% high sensitivity. Furthermore, by employing 3-D SC-35 organizational metrics, differential osteogenesis induced by novel electrospun fibrous polymer mats incorporating decellularized matrix could also be elucidated and predictably modeled at just 3days with high precision. We demonstrate that 3-D SC-35 organizational metrics can be applied to model the stem cell state in 3-D scaffolds. We propose that this methodology can robustly discern minute changes in stem cell states within complex 3-D architectures and map single cell biological readouts that are critical to assessing population level cell heterogeneity.Statement of significanceThe sustained development and validation of bioactive materials relies on technologies that can sensitively discern cell response dynamics to biomaterials, while capturing cell-to-cell heterogeneity and preserving cellular native phenotypes. In this study, we illustrate the application of a novel high content image informatics platform to classify emergent human mesenchymal stem cell (hMSC) phenotypes in a diverse range of 3-D biomaterial scaffolds with high sensitivity and precision, and track cell responses to varied external stimuli. A major in silico innovation is the proposed image profiling technology based on unique three dimensional textural signatures of a mechanoreporter protein within the nuclei of stem cells cultured in 3-D scaffolds. This technology will accelerate the pace of high-fidelity biomaterial screening.
| S-EPMC5262522 | biostudies-literature
Project description:The ability to predict and guide stem cell differentiation remains a major challenge in regenerative medicine. Numerous dynamic microenvironmental cues often provide synergistic or combinatorial signals that influence the fate of stem cells, and ultimately drive functional tissue formation. This interplay between microenvironmental cues within tissues is under intense investigation. Our goal was to better understand this interplay within the framework of a systematic 3D platform that would enable high-throughput screening (HTS) of factors that contribute to stem cell fate decisions. It is important that such platforms provide valid biomimetic microenvironments, which can be translated to macroscale constructs. Specifically, we reported on a technique for screening of combinatorial 3D niches to guide the osteogenic differentiation of human mesenchymal stem cells (hMSCs). This platform offers a rapid, cost-effective and multiplexed approach for a variety of tissue engineering applications.
| S-EPMC4594548 | biostudies-other
Project description:The best assay for confirmation of pluripotency for mouse embryonic stem cells (ESCs) is blastocyst chimerism and for human ESCs the production of teratomas in immunodeficient mice that contain lineages from all three primordial germ layers. However, the latter assay has been interpreted by some as one type of human-animal chimera and studies involving human-animal chimerism present a wide range of ethical issues with restrictive legislation in some countries. The need for teratoma assays is compelling because unproven differentiation may suggest a dangerously flawed cell resource for use in future therapies. We find that a three dimensional anchorage independent growth protocol for hESCs using methylcellulose and matrigel encourages prolonged growth of embryoid bodies (EBs) leading onto formation of teratomas in vitro. Our late EBs are a miniature form of teratomas containing lineages from all three germ layers, do not show embryonal carcinoma cells and allows integration of microinjected cancer cells (HepG2-GFP). Additional data files are linked below as supplementary files: [1] Beadstudio_Controls_non-normalized.txt: Control Probe Profile intensity data exported from Beadstudio. [2] Beadstudio_background_removed_non-normalized.txt: Background corrected intensity data exported from Beadstudio using the default Beadstudio background correction setting. No normalization carried out on the data. [3] VST_quantile_filterp0.01_normalized.txt: Data after VST transformation, quantile normalized and filtered with detection p-value 0.01. This data set was used for analysis in the accompanying publication.
2009-12-24 | GSE16484 | GEO
Project description:Three-dimensional (3D) cell culture is gaining acceptance in response to the need for cellular models that better mimic physiologic tissues. Spheroids are one such 3D model where clusters of cells will undergo self-assembly to form viable, 3D tumor-like structures. However, to date little is known about how spheroid biology compares to that of the more traditional and widely utilized 2D monolayer cultures. Therefore, the goal of this study was to characterize the phenotypic and functional differences between lung tumor cells grown as 2D monolayer cultures, versus cells grown as 3D spheroids. Eight lung tumor cell lines, displaying varying levels of epidermal growth factor receptor (EGFR) and cMET protein expression, were used to develop a 3D spheroid cell culture model using low attachment U-bottom plates. The 3D spheroids were compared with cells grown in monolayer for 1) EGFR and cMET receptor expression, as determined by flow cytometry, 2) EGFR and cMET phosphorylation by MSD assay, and 3) cell proliferation in response to epidermal growth factor (EGF) and hepatocyte growth factor (HGF). In addition, drug responsiveness to EGFR and cMET inhibitors (Erlotinib, Crizotinib, Cetuximab [Erbitux] and Onartuzumab [MetMab]) was evaluated by measuring the extent of cell proliferation and migration. Data showed that EGFR and cMET expression is reduced at day four of untreated spheroid culture compared to monolayer. Basal phosphorylation of EGFR and cMET was higher in spheroids compared to monolayer cultures. Spheroids showed reduced EGFR and cMET phosphorylation when stimulated with ligand compared to 2D cultures. Spheroids showed an altered cell proliferation response to HGF, as well as to EGFR and cMET inhibitors, compared to monolayer cultures. Finally, spheroid cultures showed exceptional utility in a cell migration assay. Overall, the 3D spheroid culture changed the cellular response to drugs and growth factors and may more accurately mimic the natural tumor microenvironment.
| S-EPMC3956916 | biostudies-literature
Project description:It has been suggested that chemoresistance of chondrosarcoma (CHS), the cartilage tumor, is caused by the phenotypic microenvironmental features of the tumor tissue, mainly the chondrogenic extracellular matrix (ECM), and hypoxia. We developed and characterized a multicellular tumor spheroid (MCTS) of human chondrosarcoma HEMC-SS cells to gain insight into tumor cell biology and drug response. At Day 7, HEMC-SS spheroids exhibited a homogeneous distribution of proliferative Ki-67 positive cells, whereas in larger spheroids (Day 14 and Day 20), proliferation was mainly localized in the periphery. In the core of larger spheroids, apoptotic cells were evidenced by TUNEL assay, and hypoxia by pimonidazole staining. Interestingly, VEGF excretion, evidenced by ELISA on culture media, was detectable from Day 14 spheroids, and increased as the spheroids grew in size. HEMC-SS spheroids synthesized a chondrogenic extracellular matrix rich in glycosaminoglycans and type-2 collagen. Finally, we investigated the sensitivity of Day 7 and Day 14 chondrosarcoma MCTS to hypoxia-activated prodrug TH-302 and doxorubicin compared with their 2D counterparts. As expected, TH-302 exhibited higher cytotoxic activity on larger hypoxic spheroids (Day 14) than on non-hypoxic spheroids (Day 7), with multicellular resistance index (MCRI) values of 7.7 and 9.1 respectively. For doxorubicin, the larger-sized spheroids exhibited higher drug resistance (MCRI of 5.0 for Day 7 and 18.3 for Day 14 spheroids), possibly due to impeded drug penetration into the deep layer of spheroids, evidenced by its auto-fluorescence property. We have developed a model of human chondrosarcoma MCTS that combines an ECM rich in glycosaminoglycans with a high hypoxic core associated with VEGF excretion. This model could offer a more predictive in vitro chondrosarcoma system for screening drugs targeting tumor cells and their microenvironment.
| S-EPMC5509331 | biostudies-literature