Quantifying the propagation of parametric uncertainty on flux balance analysis
Quantifying the propagation of parametric uncertainty on flux balance analysis
复制标题
DOI：
10.1016/j.ymben.2021.10.012
复制
发表时间：
2021-11-01
影响因子：
8.4
通讯作者：
Maranas, Costas D.
中科院分区：
文献类型：
--
作者：
Dinh, Hoang, V;Sarkar, Debolina;Maranas, Costas D.
通量平衡分析（FBA）和在化学计量基因组规模代谢模型上运行的相关技术在量化代谢流和限制可行表型方面发挥着核心作用。这些方法的核心在于两个重要的假设：（i）生物质前体和能量需求既不会因生长条件或环境/遗传扰动而变化，（ii）代谢物的产生和消耗率在任何时候都是相等的（即稳态）。尽管这两个假设非常严格，但 FBA 在预测细胞表型方面表现出惊人的稳健性。在本文中，我们通过量化生物量反应系数的不确定性以及由于时间波动而偏离稳态如何传播到 FBA 结果，正式评估这两个假设对 FBA 结果的影响。在第一种情况下，需要对参数空间进行条件采样来重新称量生物质反应，以便分子量保持等于 1 g mmol-1，而在第二种情况下，必须在随时间变化的条件下实施代谢物（和元素）池保护。结果证实了执行上述约束的重要性，并解释了 FBA 生物量产量预测的稳健性。
Flux balance analysis (FBA) and associated techniques operating on stoichiometric genome-scale metabolic models play a central role in quantifying metabolic flows and constraining feasible phenotypes. At the heart of these methods lie two important assumptions: (i) the biomass precursors and energy requirements neither change in response to growth conditions nor environmental/genetic perturbations, and (ii) metabolite production and consumption rates are equal at all times (i.e., steady-state). Despite the stringency of these two assumptions, FBA has been shown to be surprisingly robust at predicting cellular phenotypes. In this paper, we formally assess the impact of these two assumptions on FBA results by quantifying how uncertainty in biomass reaction coefficients, and departures from steady-state due to temporal fluctuations could propagate to FBA results. In the first case, conditional sampling of parameter space is required to re-weigh the biomass reaction so as the molecular weight remains equal to 1 g mmol- 1, and in the second case, metabolite (and elemental) pool conservation must be imposed under temporally varying conditions. Results confirm the importance of enforcing the aforementioned constraints and explain the robustness of FBA biomass yield predictions.