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We propose a new scheme to infer the metabolic fluxes of cell cultures in achemostat. Our approach is based on the Maximum Entropy Principle and exploitsthe understanding of the chemostat dynamics and its connection with the actualmetabolism of cells. We show that, in continuous cultures with limitingnutrients, the inference can be done with {\it limited information about theculture}: the dilution rate of the chemostat, the concentration in the feedmedia of the limiting nutrient and the cell concentration at steady state.Also, we remark that our technique provides information, not only about themean values of the fluxes in the culture, but also its heterogeneity. We firstpresent these results studying a computational model of a chemostat. Havingcontrol of this model we can test precisely the quality of the inference, andalso unveil the mechanisms behind the success of our approach. Then, we applyour method to E. coli experimental data from the literature and show that itoutperforms alternative formulations that rest on a Flux Balance Analysisframework.

Inferring metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy Approach with minimum information