Massucci Francesco Alessandro, Guimerà Roger, Amaral Luís A Nunes, Sales-Pardo Marta
Departament d'Enginyeria Química, Universitat Rovira i Virgili, 43007 Tarragona, Spain.
Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain.
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Jun;91(6):062703. doi: 10.1103/PhysRevE.91.062703. Epub 2015 Jun 8.
High-throughput experimental techniques and bioinformatics tools make it possible to obtain reconstructions of the metabolism of microbial species. Combined with mathematical frameworks such as flux balance analysis, which assumes that nutrients are used so as to maximize growth, these reconstructions enable us to predict microbial growth. Although such predictions are generally accurate, these approaches do not give insights on how different nutrients are used to produce growth, and thus are difficult to generalize to new media or to different organisms. Here, we propose a systems-level phenomenological model of metabolism inspired by the virial expansion. Our model predicts biomass production given the nutrient uptakes and a reduced set of parameters, which can be easily determined experimentally. To validate our model, we test it against in silico simulations and experimental measurements of growth, and find good agreement. From a biological point of view, our model uncovers the impact that individual nutrients and the synergistic interaction between nutrient pairs have on growth, and suggests that we can understand the growth maximization principle as the optimization of nutrient synergies.
高通量实验技术和生物信息学工具使获取微生物物种代谢重建成为可能。结合通量平衡分析等数学框架(该框架假设营养物质的使用是为了最大化生长),这些重建使我们能够预测微生物的生长。尽管此类预测通常是准确的,但这些方法并未深入揭示不同营养物质是如何用于促进生长的,因此难以推广到新的培养基或不同的生物体。在此,我们提出了一个受维里展开启发的代谢系统层面的现象学模型。我们的模型在给定营养物质摄取量和一组简化参数的情况下预测生物量的产生,这些参数可以很容易地通过实验确定。为了验证我们的模型,我们将其与生长的计算机模拟和实验测量结果进行对比,发现吻合度良好。从生物学角度来看,我们的模型揭示了单个营养物质以及营养物质对之间的协同相互作用对生长的影响,并表明我们可以将生长最大化原则理解为营养协同作用的优化。