Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA.
Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA.
Metab Eng. 2018 May;47:190-199. doi: 10.1016/j.ymben.2018.03.008. Epub 2018 Mar 9.
Completeness and accuracy of metabolic mapping models impacts the reliability of flux estimation in photoautotrophic systems. In this study, metabolic fluxes under photoautotrophic growth conditions in the widely-used cyanobacterium Synechocystis PCC 6803 are quantified by re-analyzing an existing dataset using genome-scale isotopic instationary C-Metabolic Flux Analysis (INST-MFA). The reconstructed carbon mapping model imSyn617 and implemented algorithmic updates afforded an approximately 48% reduction in computation time. The mapping model encompasses 18 novel carbon paths spanning Calvin-Benson-Bassham cycle, photorespiration, an expanded glyoxylate metabolism, and corrinoid biosynthetic pathways and 190 additional metabolites absent in core models currently used for MFA. Flux elucidation reveals that 98% of the fixed carbons is routed towards biomass production with small amounts diverted towards organic acids and glycogen storage. 12% of the fixed carbons are oxidized to CO2 in the TCA cycle and anabolic reactions in peripheral metabolism. Flux elucidation using instationary MFA reveals that these carbons are not re-fixed by RuBisCO and are instead off-gassed as CO. A newly discovered modality is the bifurcated topology of glycine metabolism using parts of photorespiration and the phosphoserine pathways to avoid carbon losses associated with glycine oxidation. The TCA cycle is shown to be incomplete with a bifurcated topology. Inactivity of futile cycles and alternate routes results in pathway usage and (in)dispensability predictions consistent with experimental findings. The resolved flux map is consistent with the maximization of biomass yield from fixed carbons as the cellular objective function. Flux prediction departures from the ones obtained with the core model demonstrate the importance of constructing mapping models with global coverage to reliably glean new biological insights using labeled substrates.
代谢映射模型的完整性和准确性会影响光自养系统中通量估计的可靠性。在这项研究中,通过使用基于基因组规模的同位素非稳态 C-代谢通量分析(INST-MFA)重新分析现有数据集,量化了广泛使用的蓝藻集胞藻 PCC 6803 在光自养生长条件下的代谢通量。重建的碳映射模型 imSyn617 和实施的算法更新使计算时间减少了约 48%。该映射模型包含了 18 条新的碳途径,涵盖了卡尔文-本森-巴斯汉姆循环、光呼吸、扩展的乙醛酸代谢以及钴胺素生物合成途径,以及目前用于 MFA 的核心模型中缺少的 190 种其他代谢物。通量阐明表明,98%的固定碳被定向用于生物量生产,只有少量的碳被分流到有机酸和糖原储存中。12%的固定碳在 TCA 循环和周边代谢的合成反应中被氧化为 CO2。使用非稳态 MFA 进行通量阐明表明,这些碳不是由 RuBisCO 重新固定的,而是作为 CO 逸出。一个新发现的模式是使用光呼吸和磷酸丝氨酸途径的部分来避免与甘氨酸氧化相关的碳损失的甘氨酸代谢的分支拓扑。TCA 循环显示出分支拓扑的不完整。无效循环和替代途径的不活跃导致了与实验结果一致的途径使用和(不可) dispensability 预测。解析的通量图与从固定碳中最大化生物量产量作为细胞目标函数一致。与核心模型获得的通量预测偏差表明,构建具有全局覆盖范围的映射模型对于使用标记底物可靠地获得新的生物学见解非常重要。