Abstract
Abstract A novel modeling approach for the description of bioprocesses is proposed, linking microbial growth kinetics to gene regulation. An example is given with the development and experimental validation of a dynamic mathematical model of the TOL plasmid of Pseudomonas putida mt-2, which is used for the metabolism of m-xylene. The model of this genetic circuit is coupled to a growth kinetic model through predictions of rate-limiting enzyme concentrations that control biomass growth and substrate consumption. Batch cultures of mt-2 fed with m-xylene were performed to estimate model parameters and to confirm that the combined model successfully describes the bioprocess, through mRNA, biomass and m-xylene concentration measurements. However, mathematical models developed exclusively based on macroscopic measurements failed to predict the process variables, highlighting the importance of gene regulation for the development of advanced biological models.
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