Kajihata Shuichi, Furusawa Chikara, 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.
Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan ; Quantitative Biology Center, RIKEN, 6-2-3 Furuedai, Suita, Osaka 565-0874, Japan.
Biomed Res Int. 2014;2014:627014. doi: 10.1155/2014/627014. Epub 2014 Jun 11.
The in vivo measurement of metabolic flux by (13)C-based metabolic flux analysis ((13)C-MFA) provides valuable information regarding cell physiology. Bioinformatics tools have been developed to estimate metabolic flux distributions from the results of tracer isotopic labeling experiments using a (13)C-labeled carbon source. Metabolic flux is determined by nonlinear fitting of a metabolic model to the isotopic labeling enrichment of intracellular metabolites measured by mass spectrometry. Whereas (13)C-MFA is conventionally performed under isotopically constant conditions, isotopically nonstationary (13)C metabolic flux analysis (INST-(13)C-MFA) has recently been developed for flux analysis of cells with photosynthetic activity and cells at a quasi-steady metabolic state (e.g., primary cells or microorganisms under stationary phase). Here, the development of a novel open source software for INST-(13)C-MFA on the Windows platform is reported. OpenMebius (Open source software for Metabolic flux analysis) provides the function of autogenerating metabolic models for simulating isotopic labeling enrichment from a user-defined configuration worksheet. Analysis using simulated data demonstrated the applicability of OpenMebius for INST-(13)C-MFA. Confidence intervals determined by INST-(13)C-MFA were less than those determined by conventional methods, indicating the potential of INST-(13)C-MFA for precise metabolic flux analysis. OpenMebius is the open source software for the general application of INST-(13)C-MFA.
通过基于¹³C的代谢通量分析（¹³C-MFA）进行体内代谢通量测量，可提供有关细胞生理学的有价值信息。已经开发了生物信息学工具，用于根据使用¹³C标记碳源的示踪同位素标记实验结果来估计代谢通量分布。代谢通量是通过将代谢模型与通过质谱测量的细胞内代谢物的同位素标记丰度进行非线性拟合来确定的。虽然¹³C-MFA传统上是在同位素恒定条件下进行的，但最近已经开发出同位素非稳态¹³C代谢通量分析（INST-¹³C-MFA），用于具有光合活性的细胞以及处于准稳态代谢状态的细胞（例如，原代细胞或稳定期的微生物）的通量分析。在此，报告了一种用于Windows平台上的INST-¹³C-MFA的新型开源软件的开发情况。OpenMebius（代谢通量分析开源软件）提供了从用户定义的配置工作表自动生成代谢模型的功能，用于模拟同位素标记丰度。使用模拟数据进行的分析证明了OpenMebius在INST-¹³C-MFA中的适用性。由INST-¹³C-MFA确定的置信区间小于传统方法确定的置信区间，表明INST-¹³C-MFA在精确代谢通量分析方面的潜力。OpenMebius是用于INST-¹³C-MFA通用应用的开源软件。
