Article Abstract

Human induced pluripotent stem cell-derived neuronal progenitors are a suitable and effective drug discovery model for neurological mtDNA disorders

Authors: Jonas Walter, Sarah Louise Nickels, Jens Christian Schwamborn


Mitochondria are double-membraned organelles of endosymbiotic origin (1). Mitochondria are critically involved in cellular homeostasis and need to be tightly controlled to maintain normal cellular function (2). Malfunctioning mitochondria can interfere with cellular homeostasis in multiple ways (3). Consequently, mitochondria have been associated with diverse diseases, including neurological and neurodegenerative disorders (4). Among those diseases, a group of severe disorders is directly associated with specific mutagenesis of the mitochondrial DNA (mtDNA) (5,6). Thus, despite the fact that most mitochondrial genes are encoded in the nucleus, mutagenesis of the mtDNA can have severe outcomes. Hence, the status of the mtDNA is of crucial relevance for normal cellular function (7). Several studies revealed that modeling and targeting mtDNA related diseases is experimentally extremely challenging. Therefore, the modeling of human mtDNA disorders is often based on so-called cybrid models (cytoplasmic hybrids), combining immortalized cells and the particular patient’s mitochondria. These models were able to recapitulate the influence of patient specific mitochondria on cellular physiology, but unfortunately, cybrid models have limited physiological relevance. Cybrid models lack the patient-specific genetic background, are not suitable for modeling disease relevant tissues (8), and possess incompatible metabolic and bioenergetic states (1). Different cell types and subtypes strongly differ in their bioenergetic demands. Simplified, stem cells rather rely on glycolysis more than on mitochondrial oxidative phosphorylation (OXPHOS). In contrast, during commitment and differentiation especially cells from the neuronal lineage increasingly address their bioenergetic demands by using OXPHOS for energy generation (9).


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