Metabolomic Applications in Stem Cell Research: a Review

Cellular and Molecular Insights into the Divergence of Neural Stem Cells on Matrigel and Poly-l-lysine Interfaces

Poly-l-lysine (PLL) and Matrigel, both classical coating materials for culture substrates in neural stem cell (NSC) research, present distinct interfaces whose effect on NSC behavior at cellular and molecular levels remains ambiguous. Our investigation reveals intriguing disparities: although both PLL and Matrigel interfaces are hydrophilic and feature amine functional groups, Matrigel stands out with lower stiffness and higher roughness. Based on this diversity, Matrigel surpasses PLL, driving NSC adhesion, migration, and proliferation. Intriguingly, PLL promotes NSC differentiation into astrocytes, whereas Matrigel favors neural differentiation and the physiological maturation of neurons. At the molecular level, Matrigel showcases a wider upregulation of genes linked to NSC behavior. Specifically, it enhances ECM-receptor interaction, activates the YAP transcription factor, and heightens glycerophospholipid metabolism, steering NSC proliferation and neural differentiation. Conversely, PLL upregulates genes associated with glial cell differentiation and amino acid metabolism and elevates various amino acid levels, potentially linked to its support for astrocyte differentiation. These distinct transcriptional and metabolic activities jointly shape the divergent NSC behavior on these substrates. This study significantly advances our understanding of substrate regulation on NSC behavior, offering novel insights into optimizing and targeting the application of these surface coating materials in NSC research.

Isotopic Tracing of Nucleotide Sugar Metabolism in Human Pluripotent Stem Cells

Metabolism not only produces energy necessary for the cell but is also a key regulator of several cellular functions, including pluripotency and self-renewal. Nucleotide sugars (NSs) are activated sugars that link glucose metabolism with cellular functions via protein N-glycosylation and O-GlcNAcylation. Thus, understanding how different metabolic pathways converge in the synthesis of NSs is critical to explore new opportunities for metabolic interference and modulation of stem cell functions. Tracer-based metabolomics is suited for this challenge, however chemically-defined, customizable media for stem cell culture in which nutrients can be replaced with isotopically labeled analogs are scarcely available. Here, we established a customizable flux-conditioned E8 (FC-E8) medium that enables stem cell culture with stable isotopes for metabolic tracing, and a dedicated liquid chromatography mass-spectrometry (LC-MS/MS) method targeting metabolic pathways converging in NS biosynthesis. By 13C6-glucose feeding, we successfully traced the time-course of carbon incorporation into NSs directly via glucose, and indirectly via other pathways, such as glycolysis and pentose phosphate pathways, in induced pluripotent stem cells (hiPSCs) and embryonic stem cells. Then, we applied these tools to investigate the NS biosynthesis in hiPSC lines from a patient affected by deficiency of phosphoglucomutase 1 (PGM1), an enzyme regulating the synthesis of the two most abundant NSs, UDP-glucose and UDP-galactose.

NMR-based metabolomics applied to ecotoxicology with zebrafish (Danio rerio) as a prominent model for metabolic profiling and biomarker discovery: Overviewing the most recent approaches

Metabolomics is an innovative approach used in the medical, toxicological, and biological sciences. As an interdisciplinary topic, metabolomics and its relation with the environment and toxicological research are extensive. The use of substances, such as drugs and pesticides, contributes to the continuous releasing of xenobiotics into the environment, harming organisms and their habitats. In this context, fish are important bioindicators of the environmental condition and have often been used as model species. Among them, zebrafish (Danio rerio) presents itself as a versatile and straightforward option due to its unique attributes for research. Zebrafish proves to be a valuable model for toxicity assays and also for metabolomics profiling by analytical tools. Thus, NMR-based metabolomics associated with statistical analysis can reasonably assist researchers in critical factors related to discovering and validating biomarkers through accurate diagnosis. Therefore, this review aimed to report the studies that applied zebrafish as a model for (eco)toxicological assays and essentially utilized NMR-based metabolomics analysis to assess the biochemical profile and thus suggest the potential biological marker.

Mass spectrometry-based quantitation combined with time-dependent metabolomics to discover metabolic features in human neurogenesis using neural constructs generated from neural progenitor cells

Direct studies focusing on the human brain are difficult to plan and conduct due to ethical and practical reasons. The advent of human pluripotent stem cell (hPSC)-derived neurons has revolutionized the research of the human brain and central nervous system, but relevant analytical techniques have been much less explored. Herein, we have designed a novel bioanalytical strategy to discover the characteristics of human neurogenesis using liquid chromatography-mass spectrometry-based quantitation and time-dependent metabolomics in combination with hPSC-derived neural constructs. To examine the growth of neurons in vitro, a quantitative method for the simultaneous measurement of N-acetylaspartic acid (NAA) and N-acetylglutamic acid (NAG) in a culture medium was established. The analysis of endogenous NAA and NAG concentrations over 28 days of neural cell culture not only illustrated the growth and maturation process of neural progenitors, but also confirmed the successful achievement of human neural constructs. Depending on the quantitative results, day 0, 10, 18, and 28 samples representing different growth phases were selected for further investigation of the global metabolic changes in developing human neurons. A versatile non-targeted, time-dependent metabolomics study identified 17 significantly changed metabolites and revealed the altered metabolic pathways including amino acid metabolism (tryptophan, phenylalanine, aspartate and beta-alanine metabolisms), pantothenate and coenzyme A biosynthesis, fatty acid metabolism, and purine and pyrimidine metabolism. The new metabolite profiles and overall metabolic pathways advance our understanding of human neurodevelopment. Additionally, the bioanalytical approach proposed in this study opens an interesting window for the capture and evaluation of the complex metabolic states of human neural cells, which would potentially be utilized in other in vitro models relevant to pathophysiology and treatment of neurological disorders, benefiting biomarker discovery and metabolic mechanism interpretation.

An Intracellular Metabolic Signature as a Potential Donor-Independent Marker of the Osteogenic Differentiation of Adipose Tissue Mesenchymal Stem Cells

This paper describes an untargeted NMR metabolomics study to identify potential intracellular donor-dependent and donor-independent metabolic markers of proliferation and osteogenic differentiation of human adipose mesenchymal stem cells (hAMSCs). The hAMSCs of two donors with distinct proliferating/osteogenic characteristics were fully characterized regarding their polar endometabolome during proliferation and osteogenesis. An 18-metabolites signature (including changes in alanine, aspartate, proline, tyrosine, ATP, and ADP, among others) was suggested to be potentially descriptive of cell proliferation, independently of the donor. In addition, a set of 11 metabolites was proposed to compose a possible donor-independent signature of osteogenesis, mostly involving changes in taurine, glutathione, methylguanidine, adenosine, inosine, uridine, and creatine/phosphocreatine, choline/phosphocholine and ethanolamine/phosphocholine ratios. The proposed signatures were validated for a third donor, although they require further validation in a larger donor cohort. We believe that this proof of concept paves the way to exploit metabolic markers to monitor (and potentially predict) cell proliferation and the osteogenic ability of different donors.

Sánchez B, León C, Nozal L, Mora-Rodríguez JM, Castro F, Crego AL, Díaz-Laviada I. Metabolic fingerprinting of chemotherapy-resistant prostate cancer stem cells. An untargeted metabolomic approach by liquid chromatography-mass spectrometry

Chemoresistance is one of the most important challenges in cancer therapy. The presence of cancer stem cells within the tumor may contribute to chemotherapy resistance since these cells express high levels of extrusion pumps and xenobiotic metabolizing enzymes that inactivate the therapeutic drug. Despite the recent advances in cancer cell metabolism adaptations, little is known about the metabolic adaptations of the cancer stem cells resistant to chemotherapy. In this study, we have undertaken an untargeted metabolomic analysis by liquid chromatography–high-resolution spectrometry combined with cytotoxicity assay, western blot, quantitative real-time polymerase chain reaction (qPCR), and fatty acid oxidation in a prostate cancer cell line resistant to the antiandrogen 2-hydroxiflutamide with features of cancer stem cells, compared to its parental androgen-sensitive cell line. Metabolic fingerprinting revealed 106 out of the 850 metabolites in ESI+ and 67 out of 446 in ESI- with significant differences between the sensitive and the resistant cell lines. Pathway analysis performed with the unequivocally identified metabolites, revealed changes in pathways involved in energy metabolism as well as posttranscriptional regulation. Validation by enzyme expression analysis indicated that the chemotherapy-resistant prostate cancer stem cells were metabolically dormant with decreased fatty acid oxidation, methionine metabolism and ADP-ribosylation. Our results shed light on the pathways underlying the entry of cancer cells into dormancy that might contribute to the mechanisms of drug resistance.

Endo- and Exometabolome Crosstalk in Mesenchymal Stem Cells Undergoing Osteogenic Differentiation

This paper describes, for the first time to our knowledge, a lipidome and exometabolome characterization of osteogenic differentiation for human adipose tissue stem cells (hAMSCs) using nuclear magnetic resonance (NMR) spectroscopy. The holistic nature of NMR enabled the time-course evolution of cholesterol, mono- and polyunsaturated fatty acids (including ω-6 and ω-3 fatty acids), several phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens), and mono- and triglycerides to be followed. Lipid changes occurred almost exclusively between days 1 and 7, followed by a tendency for lipidome stabilization after day 7. On average, phospholipids and longer and more unsaturated fatty acids increased up to day 7, probably related to plasma membrane fluidity. Articulation of lipidome changes with previously reported polar endometabolome profiling and with exometabolome changes reported here in the same cells, enabled important correlations to be established during hAMSC osteogenic differentiation. Our results supported hypotheses related to the dynamics of membrane remodelling, anti-oxidative mechanisms, protein synthesis, and energy metabolism. Importantly, the observation of specific up-taken or excreted metabolites paves the way for the identification of potential osteoinductive metabolites useful for optimized osteogenic protocols.

NMR Metabolomics Assessment of Osteogenic Differentiation of Adipose-Tissue-Derived Mesenchymal Stem Cells

This Article presents, for the first time to our knowledge, an untargeted nuclear magnetic resonance (NMR) metabolomic characterization of the polar intracellular metabolic adaptations of human adipose-derived mesenchymal stem cells during osteogenic differentiation. The use of mesenchymal stem cells (MSCs) for bone regeneration is a promising alternative to conventional bone grafts, and untargeted metabolomics may unveil novel metabolic information on the osteogenic differentiation of MSCs, allowing their behavior to be understood and monitored/guided toward effective therapies. Our results unveiled statistically relevant changes in the levels of just over 30 identified metabolites, illustrating a highly dynamic process with significant variations throughout the whole 21-day period of osteogenic differentiation, mainly involving amino acid metabolism and protein synthesis; energy metabolism and the roles of glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation; cell membrane metabolism; nucleotide metabolism (including the specific involvement of O-glycosylation intermediates and NAD⁺); and metabolic players in protective antioxidative mechanisms (such as glutathione and specific amino acids). Different metabolic stages are proposed and are supported by putative biochemical explanations for the metabolite changes observed. This work lays the groundwork for the use of untargeted NMR metabolomics to find potential metabolic markers of osteogenic differentiation efficacy.

Human metabolite detection by surface-enhanced Raman spectroscopy

Metabolites are important biomarkers in human body fluids, conveying direct information of cellular activities and physical conditions. Metabolite detection has long been a research hotspot in the field of biology and medicine. Surface-enhanced Raman spectroscopy (SERS), based on the molecular “fingerprint” of Raman spectrum and the enormous signal enhancement (down to a single-molecule level) by plasmonic nanomaterials, has proven to be a novel and powerful tool for metabolite detection. SERS provides favorable properties such as ultra-sensitive, label-free, rapid, specific, and non-destructive detection processes. In this review, we summarized the progress in recent 10 years on SERS-based sensing of endogenous metabolites at the cellular level, in tissues, and in biofluids, as well as drug metabolites in biofluids. We made detailed discussions on the challenges and optimization methods of SERS technique in metabolite detection. The combination of SERS with modern biomedical technology were also anticipated.