In silico modeling and metabolome analysis of long-stored erythrocytes to improve blood storage methods.
There is currently no effective method for preventing ATP and 2,3-bisphosphoglycerate (2,3-BPG) depletion during long-term erythrocyte storage in the cold, although these metabolites are strongly associated with cell viability and oxygen delivery after transfusion. Metabolite reduction is caused by whole metabolic networks in the cell, which are regulated by various physical or chemical factors. Mathematical modeling is a powerful tool for integrating such complex and dynamic systems. Here, we developed a mathematical model to predict metabolism in erythrocytes preserved with a mannitol-adenine-phosphate solution (MAP) at 4 degrees C, by modifying a published model of large-scale erythrocyte metabolism. Our model successfully reproduced the reported decreases in ATP and 2,3-BPG during storage. Analysis of our model identified several enzymatic reactions and factors related to ATP and 2,3-BPG depletions, which may serve as possible targets for improving blood storage methods. We also performed metabolome analysis of laboratory-made MAP-stored erythrocytes using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), which provided a comprehensive view of the metabolism dynamics. Alterations in the metabolic intermediate concentrations after long storage were qualitatively predicted by the model. Finally, through further systematic analysis, we also discuss the usability of our model.