ABSTRACT
Living cells can express different metabolic pathways that support growth. The criteria that determine which pathways are selected in which environment remain unclear. One recurrent selection is overflow metabolism: the simultaneous usage of an ATP-efficient and -inefficient pathway, shown for example in Escherichia coli, Saccharomyces cerevisiae and cancer cells. Many models, based on different assumptions, can reproduce this observation. Therefore, they provide no conclusive evidence which mechanism is causing overflow metabolism. We compare the mathematical structure of these models. Although ranging from flux balance analyses to self-fabricating metabolism and expression models, we can rewrite all models into one standard form. We conclude that all models predict overflow metabolism when two, model-specific, growth-limiting constraints are hit. This is consistent with recent theory. Thus, identifying these two constraints is essential for understanding overflow metabolism. We list all imposed constraints by these models, so that they can hopefully be tested in future experiments.
Subject(s)
Escherichia coli/metabolism , Metabolic Networks and Pathways/physiology , Saccharomyces cerevisiae/metabolism , Adenosine Triphosphate/metabolism , Models, BiologicalABSTRACT
Identification of patients with increased risk of 5-fluorouracil (5-FU)-related toxicity is an important challenge for cancer treatment. Research often focus on dihydropyrimidine dehydrogenase (DPYD) deficiency in this context. However, patients with normal DPYD activity may also develop life-threatening 5-FU adverse effects. DPYD initiates the catabolic route of 5-FU generating metabolites such as fluoroacetate (FAC). The catabolite FAC is known to inhibit the TCA cycle enzyme aconitase, which is supposed to impair mitochondrial energy metabolism. Therefore, we aim for a systems understanding of the association of 5-FU-related cardiac side effects with aconitase inhibition caused by FAC. Using a mitochondrial model of cardiomyocytes we found strong depletion of ATP production and citrate accumulation as main effects of aconitase inhibition. Shadow price analysis revealed that the uptakes of valine, arginine, proline and glutamate are most effective in compensating the impairment of energy metabolism. Our findings suggest that 5-FU catabolism contributes to the occurrence of cardiac adverse effects and are the basis for further biomarker identifications and development of side effect treatment.