Revealing the metabolic characteristics of human embryonic stem cells by genome-scale metabolic modeling

A holistic view of muscle metabolic reprogramming through personalized metabolic modeling in newly diagnosed diabetic patients

Type 2 diabetes mellitus (T2DM) is a challenging and progressive metabolic disease caused by insulin resistance. Skeletal muscle is the major insulin-sensitive tissue that plays a pivotal role in blood sugar homeostasis. Dysfunction of muscle metabolism is implicated in the disturbance of glucose homeostasis, the development of insulin resistance, and T2DM. Understanding metabolism reprogramming in newly diagnosed patients provides opportunities for early diagnosis and treatment of T2DM as a challenging disease to manage. Here, we applied a system biology approach to investigate metabolic dysregulations associated with the early stage of T2DM. We first reconstructed a human muscle-specific metabolic model. The model was applied for personalized metabolic modeling and analyses in newly diagnosed patients. We found that several pathways and metabolites, mainly implicating in amino acids and lipids metabolisms, were dysregulated. Our results indicated the significance of perturbation of pathways implicated in building membrane and extracellular matrix (ECM). Dysfunctional metabolism in these pathways possibly interrupts the signaling process and develops insulin resistance. We also applied a machine learning method to predict potential metabolite markers of insulin resistance in skeletal muscle. 13 exchange metabolites were predicted as the potential markers. The efficiency of these markers in discriminating insulin-resistant muscle was successfully validated.

Proliferation toxicity and mechanism of novel mixed bromine/chlorine transformation products of tetrabromobisphenol A on human embryonic stem cell

Mixed bromine/chlorine transformation products of tetrabromobisphenol A (Cl_yBr_xBPAs) are mixed halogenated-type compounds recently identified in electronic waste dismantling sites. There are a lack of toxicity data on these compounds. To study their development toxicity, the proliferation toxicity was investigated using human embryonic stem cells (hESC) exposed to the lowest effective dose of two Cl_yBr_xBPA analogues (2-chloro-2',6-dibromobisphenol A and 2,2'-dichloro-6-monobromobisphenol A). For comparison, tetrabromobisphenol A, 2,2',6-tribromobisphenol A, and bisphenol A were also assessed. It was observed that Cl_yBr_xBPAs inhibited hESCs proliferation in a concentration-dependent manner. The cell bioaccumulation efficiency of Cl_yBr_xBPAs was higher than that of tetrabromobisphenol A. Also, Cl_yBr_xBPAs were more toxic than tetrabromobisphenol A, with 2,2'-dichloro-6-monobromobisphenol A exhibiting the most potent toxicity. Furthermore, flow cytometry and oxidative stress results showed that increased reactive oxygen species raised the degree of apoptosis and reduced DNA synthesis. Metabolomics analysis on the effect of Cl_yBr_xBPAs on metabolic pathway alteration showed that Cl_yBr_xBPAs mainly interfered with four metabolic pathways related to amino acid metabolism and biosynthesis. These results provide an initial perspective on the proliferation toxicity of Cl_yBr_xBPAs, indicating development toxicity in children.

Metabolism-based cardiomyocytes production for regenerative therapy

Human pluripotent stem cells (hPSCs) are currently used in clinical applications such as cardiac regenerative therapy, studying disease models, and drug screening for heart failure. Transplantation of hPSC-derived cardiomyocytes (hPSC-CMs) can be used as an alternative therapy for heart transplantation. In contrast to differentiated somatic cells, hPSCs possess unique metabolic programs to maintain pluripotency, and understanding their metabolic features can contribute to the development of technologies that can be useful for their clinical applications. The production of hPSC-CMs requires stepwise specification during embryonic development and metabolic regulation is crucial for proper embryonic development. These metabolic features have been applied to hPSC-CM production methods, such as mesoderm induction, specifications for cardiac progenitors, and their maturation. This review describes the metabolic programs in hPSCs and the metabolic regulation in hPSC-CM production for cardiac regenerative therapy.

Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

Cancer Stem Cells (CSCs) contribute to cancer aggressiveness, metastasis, chemo/radio-therapy resistance, and tumor recurrence. Recent studies emphasized the importance of metabolic reprogramming of CSCs for the maintenance and progression of the cancer phenotype through both the fulfillment of the energetic requirements and the supply of substrates fundamental for fast-cell growth, as well as through metabolite-induced epigenetic regulation. Therefore, it is of paramount importance to develop therapeutic strategies tailored to target the metabolism of CSCs. In this work, we built computational Genome-Scale Metabolic Models (GSMMs) for CSCs of different tissues. Flux simulations were then used to predict metabolic phenotypes, identify potential therapeutic targets, and spot already-known Transcription Factors (TFs), miRNAs and antimetabolites that could be used as part of drug repurposing strategies against cancer. Results were in accordance with experimental evidence, provided insights of new metabolic mechanisms for already known agents, and allowed for the identification of potential new targets and compounds that could be interesting for further in vitro and in vivo validation.

Amino Acid-Mediated Metabolism: A New Power to Influence Properties of Stem Cells

The self-renewal and differentiation potentials of stem cells are dependent on amino acid (AA) metabolism. We review the literature on the metabolic preference of both cancer and noncancer stem cells. The balance in AA metabolism is responsible for maintaining the functionality of noncancer stem cells, and altering the levels of AAs can influence the malignant biological behavior of cancer stem cells. AAs are considered nutrients participating in metabolism and playing a critical role in maintaining the activity of normal stem cells and the effect of therapy of cancer stem cells. Targeting AA metabolism helps inhibit the stemness of cancer stem cells and remodels the function of normal stem cells. This review summarizes the metabolic characteristics and regulation pathways of AA in different stem cells, not only from the nutritional perspective but also from the genomic perspective that have been reported in the recent five years. In addition, we briefly survey new therapeutic modalities that may help eradicate cancer stem cells by exploiting nutrient deprivation. Understanding AA uptake characteristics helps researchers define the preference for AA in different stem cells and enables clinicians make timely interventions to specifically target the cell behavior.

The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells

The molecular study of fat cell development in the human body is essential for our understanding of obesity and related diseases. Mesenchymal stem/stromal cells (MSC) are the ideal source to study fat formation as they are the progenitors of adipocytes. In this work, we used human MSCs, received from surgery waste, and differentiated them into fat adipocytes. The combination of several layers of information coming from lipidomics, metabolomics and proteomics enabled network analysis of the biochemical pathways in adipogenesis. Simultaneous analysis of metabolites, lipids, and proteins in cell culture is challenging due to the compound’s chemical difference, so most studies involve separate analysis with unimolecular strategies. In this study, we employed a multimolecular approach using a two–phase extraction to monitor the crosstalk between lipid metabolism and protein-based signaling in a single sample (~10⁵ cells). We developed an innovative analytical workflow including standardization with in-house produced ¹³C isotopically labeled compounds, hyphenated high-end mass spectrometry (high-resolution Orbitrap MS), and chromatography (HILIC, RP) for simultaneous untargeted screening and targeted quantification. Metabolite and lipid concentrations ranged over three to four orders of magnitude and were detected down to the low fmol (absolute on column) level. Biological validation and data interpretation of the multiomics workflow was performed based on proteomics network reconstruction, metabolic modelling (MetaboAnalyst 4.0), and pathway analysis (OmicsNet). Comparing MSCs and adipocytes, we observed significant regulation of different metabolites and lipids such as triglycerides, gangliosides, and carnitine with 113 fully reprogrammed pathways. The observed changes are in accordance with literature findings dealing with adipogenic differentiation of MSC. These results are a proof of principle for the power of multimolecular extraction combined with orthogonal LC-MS assays and network construction. Considering the analytical and biological validation performed in this study, we conclude that the proposed multiomics workflow is ideally suited for comprehensive follow-up studies on adipogenesis and is fit for purpose for different applications with a high potential to understand the complex pathophysiology of diseases.

The metabolic network model of primed/naive human embryonic stem cells underlines the importance of oxidation-reduction potential and tryptophan metabolism in primed pluripotency

Background

Pluripotency is proposed to exist in two different stages: Naive and Primed. Conventional human pluripotent cells are essentially in the primed stage. In recent years, several protocols have claimed to generate naive human embryonic stem cells (hESCs). To the best of our knowledge, none of these protocols is currently recognized as the gold standard method. Furthermore, the consistency of the resulting cells from these diverse protocols at the molecular level is yet to be shown. Additionally, little is known about the principles that govern the metabolic differences between naive and primed pluripotency. In this work, using a computational approach, we tried to shed light on these basic issues.

Results

We showed that, after batch effect removal, the transcriptome data of eight different protocols which supposedly produce naive hESCs are clustered consistently when compared to the primed ones. Next, by integrating transcriptomes of all hESCs obtained by these protocols, we reconstructed p-hESCNet and n-hESCNet, the first metabolic network models representing hESCs. By exploiting reporter metabolite analysis we showed that the status of NAD\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{+}$$\end{document}+ and the metabolites involved in the TCA cycle are significantly altered between naive and primed hESCs. Furthermore, using flux variability analysis (FVA), the models showed that the kynurenine-mediated metabolism of tryptophan is remarkably downregulated in naive human pluripotent cells.

Conclusion

The aim of the present paper is twofold. Firstly, our findings confirm the applicability of all these protocols for generating naive hESCs, due to their consistency at the transcriptome level. Secondly, we showed that in silico metabolic models of hESCs can be used to simulate the metabolic states of naive and primed pluripotency. Our models confirmed the OXPHOS activation in naive cells and showed that oxidation-reduction potential vary between naive and primed cells. Tryptophan metabolism is also outlined as a key pathway in primed pluripotency and the models suggest that decrements in the activity of this pathway might be an appropriate marker for naive pluripotency.