EI du Pont de Nemours and Company, Central Research and Development, Experimental Station, Wilmington, DE 19880, United States.
Curr Opin Biotechnol. 2010 Feb;21(1):55-62. doi: 10.1016/j.copbio.2010.01.014. Epub 2010 Feb 23.
Fluxes and metabolites are the functional manifestations of a living cell. Metabolic flux analysis evolved as a powerful means for systems biology to quantitatively analyze intracellular flux distributions. With the integration of data from tracer experiments, the formerly descriptive methodology has turned into a versatile tool to validate assumptions on genome-derived flux networks. Powerful modeling frameworks balancing 'isotopomers', 'cumomers', or 'elementary modeling units' have reduced computational effort and introduced rigorous statistical quality measures. The advent of metabolomics, stimulus response experiments, and highly sensitive mass spectrometry techniques for mass isotopomer analysis has extended the reach of metabolic flux analysis from steady-state to highly dynamic conditions. With the integration of regulatory circuits and more 'omics' data into mechanistic flux models, the simulation-based prediction of cellular responses to environmental and network perturbations becomes possible-an in silico cell.
通量和代谢物是活细胞的功能表现。代谢通量分析作为系统生物学的一种强大手段，已经发展成为定量分析细胞内通量分布的方法。通过将示踪实验的数据进行整合，这一曾经具有描述性的方法已经转变为验证基于基因组的通量网络假设的通用工具。强大的建模框架平衡了“同位素标记物”、“累积物”或“基本建模单元”，减少了计算工作量，并引入了严格的统计质量措施。代谢组学的出现、刺激反应实验以及用于质量同位素分析的高灵敏度质谱技术，已经将代谢通量分析从稳态扩展到了高度动态的条件。通过将调控回路和更多的“组学”数据整合到机制通量模型中，基于模拟的对细胞对环境和网络扰动的响应的预测成为可能——即虚拟细胞。
