Department of Computer Science & Engineering, University of Minnesota - Twin Cities, Minneapolis, MN 55455, USA.
J Theor Biol. 2022 Oct 7;550:111223. doi: 10.1016/j.jtbi.2022.111223. Epub 2022 Jul 16.
Due to its implication in cancer treatment, the Warburg Effect has received extensive in silico investigation. Flux Balance Analysis (FBA), based on constrained optimization, was successfully applied in the Warburg Effect modelling. Yet, the assumption that cell types have one invariant cellular objective severely limits the applicability of the previous FBA models. Meanwhile, we note that cell types with different objectives show different extents of the Warburg Effect. To extend the applicability of the previous model and model the disparate cellular pathway preferences in different cell types, we built a Nonlinear Multi-Objective FBA (NLMOFBA) model by including three key objective terms (ATP production rate, lactate generation rate and ATP yield) into one objective function through linear scalarization. By constructing a cellular objective map and iteratively varying the objective weights, we showed disparate cellular pathway preferences manifested by different cell types driven by their unique cellular objectives, and we gained insights about the causal relationship between cellular objectives and the Warburg Effect. In addition, we obtained other biologically consistent results by using our NLMOFBA model. For example, augmented with the constraint associated with inefficient mitochondria function, low oxygen availability, or limited substrate, NLMOFBA predicts cellular pathways supported by the biology literature. Collectively, our NLMOFBA model can help build a complete understanding towards the Warburg Effect in different cell types. Finally, we investigated the impact of glutaminolysis, an important pathway related to glycolysis, on the occurrence of the Warburg Effect by using linear programming.
由于其在癌症治疗中的作用，瓦博格效应已经受到了广泛的计算机模拟研究。基于约束优化的通量平衡分析（FBA）成功地应用于瓦博格效应建模。然而，细胞类型具有一个不变的细胞目标的假设严重限制了之前 FBA 模型的适用性。同时，我们注意到，具有不同目标的细胞类型表现出不同程度的瓦博格效应。为了扩展之前模型的适用性并对不同细胞类型中不同细胞途径偏好进行建模，我们通过将三个关键目标项（ATP 生成速率、乳酸生成速率和 ATP 产率）通过线性标量化纳入一个目标函数中，构建了一个非线性多目标 FBA（NLMOFBA）模型。通过构建细胞目标图谱并迭代改变目标权重，我们展示了不同细胞类型表现出的不同细胞途径偏好是由其独特的细胞目标驱动的，并且我们深入了解了细胞目标与瓦博格效应之间的因果关系。此外，我们通过使用 NLMOFBA 模型获得了其他生物学上一致的结果。例如，通过增加与低效线粒体功能、低氧可用性或有限底物相关的约束，NLMOFBA 预测了生物学文献中支持的细胞途径。总的来说，我们的 NLMOFBA 模型可以帮助我们在不同细胞类型中建立对瓦博格效应的全面理解。最后，我们通过线性规划研究了与糖酵解密切相关的谷氨酰胺分解代谢对瓦博格效应发生的影响。
