Unveiling dynamic metabolic signatures in human induced pluripotent and neural stem cells

Author summary Metabolism is no longer considered simply a consequence of cellular regulation, as it can trigger regulatory signals that modulate key cell fate decisions such as proliferation, differentiation and death. To be able to maintain homeostasis, cells regulate and control the metabolic state within defined boundaries. Therefore, to prevent phenotypic changes, key metabolites must be subjected to tight control. Identification of the most tightly regulated metabolites in cellular systems has been hampered by limitations of current methodologies, which typically focus on steady-state data, overlooking transient dynamics and potential regulators. We proposed an innovative approach to face this challenge, by exploring the dynamic response of metabolic pools of human stem cells to a sudden metabolic perturbation. Our data suggests that intracellular metabolic pools respond to extracellular changes in a controlled and cell type-specific manner. This approach might also contribute to systematically uncover potential key metabolic regulators involved in cell fate decisions, which can be translated not only into advances in stem cell manufacturing and disease understanding but ultimately help unveil new therapeutic solutions. Metabolism plays an essential role in cell fate decisions. However, the methods used for metabolic characterization and for finding potential metabolic regulators are still based on characterizing cellular metabolic steady-state which is dependent on the extracellular environment. In this work, we hypothesized that the response dynamics of intracellular metabolic pools to extracellular stimuli is controlled in a cell type-specific manner. We applied principles of process dynamics and control to human induced pluripotent stem cells (hiPSC) and human neural stem cells (hNSC) subjected to a sudden extracellular glutamine step. The fold-changes of steady-states and the transient profiles of metabolic pools revealed that dynamic responses were reproducible and cell type-specific. Importantly, many amino acids had conserved dynamics and readjusted their steady state concentration in response to the increased glutamine influx. Overall, we propose a novel methodology for systematic metabolic characterization and identification of potential metabolic regulators.