人類的大腦常伴隨著大量的能量消耗,當能量的供需平衡發生異常時,勢必會造成神經系統地損害,也使其原本所負責的功能喪失,逐漸演變成神經退化性疾病(Neurodegenerative Disease) 。然而研究神經退化性疾病在臨床上需耗費長久的時間,故希望藉由代謝網路模型的建立來模擬出其代謝網絡的通量分布。 本研究利用各個生物資訊庫所提供的資料,建造出屬於人類大腦的多巴胺神經元細胞代謝網路模型(Dopaminergic neurons model) ,此模型包含1022個代謝物、1131條反應式、48個代謝途徑(如醣酵解、檸檬酸循環、過氧化物質的代謝、酪氨酸代謝系統等)以及六個胞器間隔。 為了探討能量代謝與疾病的關係,我們選用三種目標函數的組合,提供維持神經元細胞所需要的營養攝取物(氧氣、葡萄糖、必需胺基酸…等),且使用通量均衡分析方法(Flux balance analysis, FBA) 得到正常狀態下的通量分布。再利用突變通量均衡分析(Mutant-Flux Balance Analysis, mFBA) 模擬出抑制酪胺酸代謝系統酵素的通量分布,並比較正常與異常情況下通量分布的差異性。 我們發現當酪胺酸代謝系統發生異常的時候,會導致整個神經元細胞生成能量的能力會有所下降,且過氧化物質的合成速率上升,也觀察到二氧化碳的排放量下降。
Human brain often associate with massive energy dissipation. When an exception of the energy demand and supply occurs, it is bound to damage the nervous system. Also, it will lose the original function and evolve into Neurodegenerative Disease. Therefore, it takes plenty of time to study this disease. As a result, we hope that we can simulate metabolic flux distribution network by a Genome-scale metabolic model of brain. This research reconstructed the Dopaminergic neurons model by collecting data from bioinformatics database. This model includes 1022 metabolites, 1131 chemical reaction equations, and 48 metabolic pathways. In order to discuss the relationship between the energy metabolism and disease, we provided the nutrients to Dopaminergic neurons to maintain its physiological function. Under these circumstances, we set the three types objective functions, which consists of maximize the flux of ATP synthesis, maximize the flux of NADPH synthesis and minimize the internal flux. We used Flux balance analysis and Mutant-Flux balance analysis to get the flux distribution of network at steady state. We compared the results of perturbations to the fluxes of normal condition, then observed the fluxes with significant difference. We found that the tyrosine metabolism getting abnormal, it will lead the ability of generate energy to decline in the neuronal cells. Also, we observed the flux of Carbon dioxide will be decreased, and the flux of Reactive oxygen species will be increased.
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