Paracrine mechanisms in early differentiation of human pluripotent stem cells: Insights from a mathematical model

Pluripotent stem cells for skeletal tissue engineering

Here, we review the use of human pluripotent stem cells for skeletal tissue engineering. A number of approaches have been used for generating cartilage and bone from both human embryonic stem cells and induced pluripotent stem cells. These range from protocols relying on intrinsic cell interactions and signals from co-cultured cells to those attempting to recapitulate the series of steps occurring during mammalian skeletal development. The importance of generating authentic tissues rather than just differentiated cells is emphasized and enabling technologies for doing this are reported. We also review the different methods for characterization of skeletal cells and constructs at the tissue and single-cell level, and indicate newer resources not yet fully utilized in this field. There have been many challenges in this research area but the technologies to overcome these are beginning to appear, often adopted from related fields. This makes it more likely that cost-effective and efficacious human pluripotent stem cell-engineered constructs may become available for skeletal repair in the near future.

A 3D Mathematical Model of Coupled Stem Cell-Nutrient Dynamics in Myocardial Regeneration Therapy

Stem cell therapy is a promising treatment for the regeneration of myocardial tissue injured by an ischemic event. Mathematical modeling of myocardial regeneration via stem cell therapy is a challenging task, since the mechanisms underlying the processes involved in the treatment are not yet fully understood. Many aspects must be accounted for, such as the spread of stem cells and nutrients, chemoattraction, cell proliferation, stages of cell maturation, differentiation, angiogenesis, stochastic effects, just to name a few. In this paper we propose a 3D mathematical model with a free boundary that aims to provide a qualitative description of some main aspects of the stem cell regenerative therapy in a simplified scenario. The paper mainly focuses on the description of the shrinking of the necrotic core during treatment. The stem cell and nutrients dynamics are described through coupled reaction-diffusion problems. Proliferation, chemoattraction, tissue regeneration and nutrient consumption are included in the model.

Generation of heart-forming organoids from human pluripotent stem cells

Heart-forming organoids (HFOs) derived from human pluripotent stem cells (hPSCs) are a complex, highly structured in vitro model of early heart, foregut and vasculature development. The model represents a potent tool for various applications, including teratogenicity studies, gene function analysis and drug discovery. Here, we provide a detailed protocol describing how to form HFOs within 14 d. In an initial 4 d preculture period, hPSC aggregates are individually formed in a 96-well format and then Matrigel-embedded. Subsequently, the chemical WNT pathway modulators CHIR99021 and IWP2 are applied, inducing directed differentiation. This highly robust protocol can be used on many different hPSC lines and be combined with manipulation technologies such as gene targeting and drug testing. HFO formation can be assessed by numerous complementary methods, ranging from various imaging approaches to gene expression studies. Here, we highlight the flow cytometry-based analysis of individual HFOs, enabling the quantitative monitoring of lineage formation.

Human heart-forming organoids recapitulate early heart and foregut development

Organoid models of early tissue development have been produced for the intestine, brain, kidney and other organs, but similar approaches for the heart have been lacking. Here we generate complex, highly structured, three-dimensional heart-forming organoids (HFOs) by embedding human pluripotent stem cell aggregates in Matrigel followed by directed cardiac differentiation via biphasic WNT pathway modulation with small molecules. HFOs are composed of a myocardial layer lined by endocardial-like cells and surrounded by septum-transversum-like anlagen; they further contain spatially and molecularly distinct anterior versus posterior foregut endoderm tissues and a vascular network. The architecture of HFOs closely resembles aspects of early native heart anlagen before heart tube formation, which is known to require an interplay with foregut endoderm development. We apply HFOs to study genetic defects in vitro by demonstrating that NKX2.5-knockout HFOs show a phenotype reminiscent of cardiac malformations previously observed in transgenic mice.

Heart-forming organoids model early cardiac development.

Identification of potential specific biomarkers and key signaling pathways between osteogenic and adipogenic differentiation of hBMSCs for osteoporosis therapy

Background

The differentiation of bone mesenchymal stem cells (BMSCs) into adipogenesis (AD) rather than osteogenesis (OS) is an important pathological feature of osteoporosis. Illuminating the detailed mechanisms of the differentiation of BMSCs into OS and AD would contribute to the interpretation of osteoporosis pathology.

Methods

To identify the regulated mechanism in lineage commitment of the BMSCs into OS and AD in the early stages, the gene expression profiles with temporal series were downloaded to reveal the distinct fates when BMSCs adopt a committed lineage. For both OS and AD lineages, the profiles of days 2–4 were compared with day 0 to screen the differentially expressed genes (DEGs), respectively. Next, the functional enrichment analysis was utilized to find out the biological function, and protein-protein interaction network to predict the central genes. Finally, experiments were performed to verify our finding.

Results

FoxO signaling pathway with central genes like FoxO3, IL6, and CAT is the crucial mechanism of OS, while Rap1 signaling pathway of VEGFA and FGF2 enrichment is more significant for AD. Besides, PI3K-Akt signaling pathway might serve as the latent mechanism about the initiation of differentiation of BMSCs into multiple lineages.

Conclusion

Above hub genes and early-responder signaling pathways control osteogenic and adipogenic fates of BMSCs, which maybe mechanistic models clarifying the changes of bone metabolism in the clinical progress of osteoporosis. The findings provide a crucial reference for the prevention and therapy of osteoporosis.

Prediction of Human Induced Pluripotent Stem Cell Cardiac Differentiation Outcome by Multifactorial Process Modeling

Human cardiomyocytes (CMs) have potential for use in therapeutic cell therapy and high-throughput drug screening. Because of the inability to expand adult CMs, their large-scale production from human pluripotent stem cells (hPSC) has been suggested. Significant improvements have been made in understanding directed differentiation processes of CMs from hPSCs and their suspension culture-based production at chemically defined conditions. However, optimization experiments are costly, time-consuming, and highly variable, leading to challenges in developing reliable and consistent protocols for the generation of large CM numbers at high purity. This study examined the ability of data-driven modeling with machine learning for identifying key experimental conditions and predicting final CM content using data collected during hPSC-cardiac differentiation in advanced stirred tank bioreactors (STBRs). Through feature selection, we identified process conditions, features, and patterns that are the most influential on and predictive of the CM content at the process endpoint, on differentiation day 10 (dd10). Process-related features were extracted from experimental data collected from 58 differentiation experiments by feature engineering. These features included data continuously collected online by the bioreactor system, such as dissolved oxygen concentration and pH patterns, as well as offline determined data, including the cell density, cell aggregate size, and nutrient concentrations. The selected features were used as inputs to construct models to classify the resulting CM content as being "sufficient" or "insufficient" regarding pre-defined thresholds. The models built using random forests and Gaussian process modeling predicted insufficient CM content for a differentiation process with 90% accuracy and precision on dd7 of the protocol and with 85% accuracy and 82% precision at a substantially earlier stage: dd5. These models provide insight into potential key factors affecting hPSC cardiac differentiation to aid in selecting future experimental conditions and can predict the final CM content at earlier process timepoints, providing cost and time savings. This study suggests that data-driven models and machine learning techniques can be employed using existing data for understanding and improving production of a specific cell type, which is potentially applicable to other lineages and critical for realization of their therapeutic applications.

A general mathematical framework for understanding the behavior of heterogeneous stem cell regeneration

Stem cell heterogeneity is essential for homeostasis in tissue development. This paper establishes a general mathematical framework to model the dynamics of stem cell regeneration with cell heterogeneity and random transitions of epigenetic states. The framework generalizes the classical G0 cell cycle model and incorporates the epigenetic states of individual cells represented by a continuous multidimensional variable. In the model, the kinetic rates of cell behaviors, including proliferation, differentiation, and apoptosis, are dependent on their epigenetic states, and the random transitions of epigenetic states between cell cycles are represented by an inheritance probability function that describes the conditional probability of cell state changes. Moreover, the model can be extended to include genotypic changes and describe the process of gene mutation-induced tumor development. The proposed mathematical framework provides a generalized formula that helps us to understand various dynamic processes of stem cell regeneration, including tissue development, degeneration, and abnormal growth.

Continuous WNT Control Enables Advanced hPSC Cardiac Processing and Prognostic Surface Marker Identification in Chemically Defined Suspension Culture

Aiming at clinical translation, robust directed differentiation of human pluripotent stem cells (hPSCs), preferentially in chemically defined conditions, is a key requirement. Here, feasibility of suspension culture based hPSC-cardiomyocyte (hPSC-CM) production in low-cost, xeno-free media compatible with good manufacturing practice standards is shown. Applying stirred tank bioreactor systems at increasing dimensions, our advanced protocol enables routine production of about 1 million hPSC-CMs/mL, yielding ∼1.3 × 10⁸ CM in 150 mL and ∼4.0 × 10⁸ CMs in 350–500 mL process scale at >90% lineage purity. Process robustness and efficiency is ensured by uninterrupted chemical WNT pathway control at early stages of differentiation and results in the formation of almost exclusively ventricular-like CMs. Modulated WNT pathway regulation also revealed the previously unappreciated role of ROR1/CD13 as superior surrogate markers for predicting cardiac differentiation efficiency as soon as 72 h of differentiation. This monitoring strategy facilitates process upscaling and controlled mass production of hPSC derivatives.

•

Chemically defined hPSC cardiac differentiation applicable to stirred tank reactors

•

Protocol generates >90% purity of ventricular-like cardiomyocytes

•

Uninterrupted WNT pathway control enables superior cardiac mesoderm formation

•

Novel ROR1/CD13 combination as superior, predictive marker of cardiomyogenesis