Centre for Analytical Bioscience, Advanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham, United Kingdom.
Nottingham BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of Life Sciences, BioDiscovery Institute, University of Nottingham, Nottingham, United Kingdom.
PLoS Comput Biol. 2021 Jan 25;17(1):e1007694. doi: 10.1371/journal.pcbi.1007694. eCollection 2021 Jan.
Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.
在基因组后时代，代谢工程的特点是开发新的代谢组学和通量组学方法，这些方法得到了遗传工程工具和数学建模的整合的支持。特别是，基于约束的化学计量模型得到了广泛的研究：（i）通量平衡分析（FBA）（计算机模拟），和（ii）代谢通量分析（MFA）（体内）。最近的研究使这些方法能够整合热力学和代谢组学数据，以提高其预测能力。然而，这些方法之间缺乏深入的比较和评估。本研究对两种不同的计算机模拟方法进行了全面分析，这些方法针对中温菌大肠杆菌的实验数据（代谢组学和 13C-MFA）进行了测试。特别是，创建了一个最近发表的 matTFA 工具箱的修改版本，提供了更广泛的物理化学参数范围。通过与实验数据的验证，确定了进行 TFA（基于热力学的通量分析）的最佳物理化学参数。对 13C-MFA 和 TFA 之间的中心碳代谢通量模式变化的分析，突出了这两种方法在阐明氨酰化通量方面的有限能力。此外，提出了一种基于中心性度量的方法，以确定重要的代谢物，如果能够定量，将允许进一步约束 TFA。最后，本研究强调了通量组学社区需要标准化：新方法经常被发布，但并不总是与当前接受的方法进行全面比较。
