Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.
PLoS Comput Biol. 2023 Sep 18;19(9):e1011489. doi: 10.1371/journal.pcbi.1011489. eCollection 2023 Sep.
Intracellular fluxes represent a joint outcome of cellular transcription and translation and reflect the availability and usage of nutrients from the environment. While approaches from the constraint-based metabolic framework can accurately predict cellular phenotypes, such as growth and exchange rates with the environment, accurate prediction of intracellular fluxes remains a pressing problem. Parsimonious flux balance analysis (pFBA) has become an approach of choice to predict intracellular fluxes by employing the principle of efficient usage of protein resources. Nevertheless, comparative analyses of intracellular flux predictions from pFBA against fluxes estimated from labeling experiments remain scarce. Here, we posited that steady-state flux distributions derived from the principle of maximizing multi-reaction dependencies are of improved accuracy and precision than those resulting from pFBA. To this end, we designed a constraint-based approach, termed complex-balanced FBA (cbFBA), to predict steady-state flux distributions that support the given specific growth rate and exchange fluxes. We showed that the steady-state flux distributions resulting from cbFBA in comparison to pFBA show better agreement with experimentally measured fluxes from 17 Escherichia coli strains and are more precise, due to the smaller space of alternative solutions. We also showed that the same principle holds in eukaryotes by comparing the predictions of pFBA and cbFBA against experimentally derived steady-state flux distributions from 26 knock-out mutants of Saccharomyces cerevisiae. Furthermore, our results showed that intracellular fluxes predicted by cbFBA provide better support for the principle of minimizing metabolic adjustment between mutants and wild types. Together, our findings point that other principles that consider the dynamics and coordination of steady states may govern the distribution of intracellular fluxes.
细胞内通量代表细胞转录和翻译的共同结果,反映了环境中营养物质的可用性和利用情况。虽然基于约束的代谢框架的方法可以准确预测细胞表型,如生长和与环境的交换率,但准确预测细胞内通量仍然是一个紧迫的问题。简约通量平衡分析(pFBA)已成为通过利用蛋白质资源有效利用原则来预测细胞内通量的首选方法。然而,pFBA 预测的细胞内通量与标记实验估计的通量之间的比较分析仍然很少。在这里,我们假设从最大化多反应依赖性的原则得出的稳态通量分布比从 pFBA 得出的具有更高的准确性和精度。为此,我们设计了一种基于约束的方法,称为复杂平衡 FBA(cbFBA),以预测支持给定特定生长速率和交换通量的稳态通量分布。我们表明,与 pFBA 相比,cbFBA 产生的稳态通量分布与来自 17 株大肠杆菌的实验测量通量更吻合,并且由于替代解决方案的空间较小,因此更精确。我们还通过比较来自酿酒酵母 26 个敲除突变体的实验衍生的稳态通量分布的 pFBA 和 cbFBA 的预测,表明了同样的原理在真核生物中也成立。此外,我们的结果表明,cbFBA 预测的细胞内通量为突变体和野生型之间最小代谢调整的原则提供了更好的支持。总之,我们的研究结果表明,其他考虑稳态动态和协调的原则可能支配细胞内通量的分布。