在营养限制的连续培养中推断代谢通量：最小信息的最大熵方法
Inferring metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy Approach with minimum information
摘要：
我们提出了一个新的计划来推断在恒化器中的细胞培养物的代谢通量。我们的方法是基于最大熵原理，并利用恒化器动力学的理解及其与细胞的实际代谢的联系。我们表明，在连续培养与限制营养素，推断可以做{\it有限的信息的文化}：恒化器的稀释率，在饲料中的限制营养素的浓度和细胞浓度在稳态。此外，我们注意到，我们的技术提供的信息，不仅在文化中的通量的平均值，而且其异质性。我们首先提出这些研究结果的计算模型的恒化器。通过控制这个模型，我们可以精确地测试推理的质量，并揭示我们方法成功背后的机制。然后，我们将我们的方法应用于E。大肠杆菌的实验数据从文献中，并表明它优于替代配方，其余的通量平衡分析框架。
英文摘要：
We propose a new scheme to infer the metabolic fluxes of cell cultures in a chemostat. Our approach is based on the Maximum Entropy Principle and exploits the understanding of the chemostat dynamics and its connection with the actual metabolism of cells. We show that, in continuous cultures with limiting nutrients, the inference can be done with {\it limited information about the culture}: the dilution rate of the chemostat, the concentration in the feed media of the limiting nutrient and the cell concentration at steady state. Also, we remark that our technique provides information, not only about the mean values of the fluxes in the culture, but also its heterogeneity. We first present these results studying a computational model of a chemostat. Having control of this model we can test precisely the quality of the inference, and also unveil the mechanisms behind the success of our approach. Then, we apply our method to E. coli experimental data from the literature and show that it outperforms alternative formulations that rest on a Flux Balance Analysis framework.
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