Challenges in Studying Stem Cell Metabolism

The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use these methodologies fruitful, many challenges are posed the intricacies culturing cells vitro, along with distinctive scarcity adult tissue complexities their niches vivo. This review provides an examination used to characterize metabolism, highlighting utility while placing a sharper focus on limitations hurdles needs overcome for optimal study metabolic networks. Metabolism is intricate set reactions that process nutrients production energy, biomass, active biomolecules. Beyond cellular energetics, now regarded as participant mechanisms governing growth (Valvezan Manning, 2019Valvezan A.J. Manning B.D. Molecular logic mTORC1 signalling rheostat.Nat Metab. 2019; 1: 321-333Crossref PubMed Scopus (67) Google Scholar) epigenetics (Boon et al., 2020Boon R. Silveira G.G. 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Biomed. Data 61-87Crossref ScholarImaging MS Open table tab Chemical standard snapshot at any given time Over decade, techniques evolved toward detection thousands metabolites, approach referred “metabolomics.” Mass (MS) coupled liquid chromatography (LC-MS) or gas (GC-MS) culture, extracellular environment (culture medium) 1A). New being developed, others continuously improved expand scope detection, allowing more view landscape, vitro can be done targeted manner identified cross-referenced pre-existing library standards accurate identification. Additionally, through untargeted enables surveying signals discovery players information abundance carbon pathway nucleotides, amino acids, other small molecules. LC-MS profile pluripotent (PSCs) insights involved efforts sorted 10,000 (DeVilbiss 2021DeVilbiss A.W. Zhao Z. Martin-Sandoval Ubellacker Tasdogan Agathocleous Mathews T.P. Morrison S.J. Metabolomic rare populations isolated flow cytometry tissues.eLife. 10: e61980Crossref (8) Another LC-MS-based incorporation isotopically labeled into experimental workflows, which facilitates nutrient contributions, dynamic quantitation flux. Stable isotope versions such glucose, glutamine, acids administered amenability MS-based instrumental characterizing landscape PSCs (Gu 2016Gu Gaeta Sahakyan Chan A.B. Hong C.S. Kim Braas D. Plath Lowry W.E. Glycolytic plays regulating human state.Cell 19: 476-490Abstract 2016Zhang Badur Divakaruni Parker Jäger Hiller Murphy A.N. Metallo C.M. Distinct states support self-renewal lipogenesis under culture conditions.Cell 1536-1547Abstract (70) tracing mice patients enabled thorough analysis disease (Fernández-García 2020Fernández-García Altea-Manzano Pranzini Fendt S.M. isotopes mammalian-cell vivo.Trends 45: 185-201Abstract As push greater they hold great potential elucidate govern behavior. Generally, major drawback characterization proper sample preparation. Most still require hundreds reliable measurements. Optimization extraction should aim maximize quantitative yields minimize degradation chemical interconversion (Lu Sample preparation must account artifacts analyte loss ion suppression. instance, rigorous make introduced prior processing represent suitable correction confounding factors, particularly compartmentalized (Trefely 2019Trefely Huber Doan Jiang Singh von Krusenstiern Bostwick Xu Bogner-Strauss al.Subcellular kinetics revealed correcting artifactual post harvest metabolism.Mol. 61-71Crossref no universal platform exists complete metabolome, detector separation selected optimally groups interest, polar versus non-polar compounds. Furthermore, compounds share identical molecular weight challenge identification often strategies, fragmentation, and/or derivatization. instrumentation offers versatility cost intensive due expensive components requirement skilled personnel instrument data interpretation. limitation challenging aspect analysis. absence standardized strategy represents complicating factor newcomers interested metabolomics. some utilize in-house pipelines varying levels automation, may take advantage commercially available tools, open-source software, web-based portals offer user during collaborative effort survey preference analytical computational reported XCMS (Smith 2006Smith C.A. O’Maille Abagyan XCMS: nonlinear peak alignment, matching, identification.Anal. 2006; 78: 779-787Crossref (2799) most-used software (Weber 2017Weber R.J.M. Lawson T.N. Salek R.M. Ebbels T.M.D. Glen R.C. Goodacre Griffin J.L. Haug Koulman Moreno al.Computational workflows metabolomics: An international highlights opportunity harmonisation Galaxy.Metabolomics. 13: 12Crossref (53) describing plethora resources useful researchers guidance selection (O’Shea Misra, 2020O’Shea Misra B.B. Software databases updates 2018 2019.Metabolomics. 36Crossref (15) Spicer 2017Spicer Cañueto Steinbeck Navigating freely-available analysis.Metabolomics. 106Crossref (113) Targeted metabolomic provide general outline analyzing hundred identifiable metabolites. conjunction techniques, robust flux achievable. Further accompanied that, albeit only categorized mass, help identify playing functions biology. now, thoroughly optimized cultures where number not issue. enrichment protocols emerge, will become prominent, technology “go-to” systems. magnetic resonance (NMR) define aspects determine structural properties molecules (Jansen 2006Jansen J.F.A. Shamblott M.J. Zijl P.C.M. Lehtimäki Bulte J.W.M. 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