Maeda Kousuke, Okahashi Nobuyuki, Toya Yoshihiro, Matsuda Fumio, Shimizu Hiroshi
Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
Metab Eng Commun. 2016 Jun 7;3:187-195. doi: 10.1016/j.meteno.2016.06.001. eCollection 2016 Dec.
The C-MFA experiments require an optimal design since the precision or confidence intervals of the estimated flux levels depends on factors such as the composition of C-labeled carbon sources, as well as the metabolic flux distribution of interest. In this study, useful compositions of C-labeled glucose for C-metabolic flux analysis (C-MFA) of are investigated using a computer simulation of the stable isotope labeling experiment. Following the generation of artificial mass spectra datasets of amino acid fragments using five literature-reported flux distributions of , the best fitted flux distribution and the 95% confidence interval were estimated by the C-MFA procedure. A comparison of the precision scores showed that [1, 2-C]glucose and a mixture of [1-C] and [U-C]glucose at 8:2 are one of the best carbon sources for a precise estimation of flux levels of the pentose phosphate pathway, glycolysis and the TCA cycle. Although the precision scores of the anaplerotic and glyoxylate pathway reactions were affected by both the carbon source and flux distribution, it was also shown that the mixture of non-labeled, [1-C], and [U-C]glucose at 4:1:5 was specifically effective for the flux estimation of the glyoxylate pathway reaction. These findings were confirmed by wet C-MFA experiments.
C-MFA实验需要优化设计,因为估计通量水平的精度或置信区间取决于诸如C标记碳源的组成以及感兴趣的代谢通量分布等因素。在本研究中,使用稳定同位素标记实验的计算机模拟,研究了用于[具体物质]的C代谢通量分析(C-MFA)的C标记葡萄糖的有用组成。在使用[具体物质]的五个文献报道的通量分布生成氨基酸片段的人工质谱数据集之后,通过C-MFA程序估计了最佳拟合通量分布和95%置信区间。精度得分的比较表明,[1,2-C]葡萄糖以及8:2比例的[1-C]和[U-C]葡萄糖混合物是精确估计磷酸戊糖途径、糖酵解和三羧酸循环通量水平的最佳碳源之一。尽管回补途径和乙醛酸循环途径反应的精度得分受碳源和通量分布两者的影响,但研究还表明,4:1:5比例的未标记、[1-C]和[U-C]葡萄糖混合物对乙醛酸循环途径反应的通量估计特别有效。这些发现通过湿C-MFA实验得到了证实。