缩放和最佳协同作用：决定复杂介质中微生物生长的两个原则
Scaling and optimal synergy: Two principles determining microbial growth in complex media
摘要：
高通量的实验技术和生物信息学工具使得微生物物种代谢的重建成为可能。结合数学框架，如通量平衡分析，假设营养物质的使用，以最大限度地提高增长，这些重建使我们能够预测微生物的生长。虽然这种预测通常是准确的，但这些方法并没有提供关于如何使用不同营养素来产生生长的见解，因此很难推广到新媒体或不同的生物体。在这里，我们提出了一个系统级的现象学模型的代谢的维里膨胀的启发。我们的模型预测生物质产量的营养吸收和减少的参数，这可以很容易地通过实验确定。为了验证我们的模型，我们测试它对硅模拟和实验测量的增长，并找到很好的协议。从生物学的角度来看，我们的模型揭示了单个营养素和营养素对之间的协同作用对生长的影响，并建议我们可以将生长最大化原则理解为营养素协同作用的优化。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
