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Toxicol Appl Pharmacol. 2018 Sep 1;354:64-80. doi: 10.1016/j.taap.2017.12.013. Epub 2017 Dec 24.

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity.

Author information

1
In Vitro Toxicology and Biomedicine, Dept Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, 78457 Konstanz, Germany.
2
Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich 52425, Germany.
3
Max-Delbrück-Center of Molecular Medicine in the Helmholtz Association, Berlin 13125, Germany.
4
Johns Hopkins University, Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA.
5
Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.
6
Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Faculty of Information Technology, Monash University, Melbourne, Australia.
7
Department of Life Sciences, Albstadt-Sigmaringen University of Applied Sciences, Sigmaringen, Germany.
8
In Vitro Toxicology and Biomedicine, Dept Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, 78457 Konstanz, Germany; CAAT-Europe, University of Konstanz, Konstanz 78457, Germany. Electronic address: marcel.leist@uni-konstanz.de.

Abstract

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary 13C-metabolic flux analysis (INST 13C-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

KEYWORDS:

(13)C labeling experiment; Developmental neurotoxicity; Energy metabolism; Metabolic flux; Metabolomics; Oxygen consumption

PMID:
29278688
DOI:
10.1016/j.taap.2017.12.013

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