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dc.contributor.authorKoutinas, Michalis
dc.contributor.authorKiparissides, Alexandros
dc.contributor.authorSilva-Rocha, Rafael
dc.contributor.authorLam, Ming-Chi
dc.contributor.authorMartins Dos Santos, Vitor A P
dc.contributor.authorde Lorenzo, Victor
dc.contributor.authorPistikopoulos, Efstratios N
dc.contributor.authorMantalaris, Athanasios
dc.date.accessioned2011-12-07T14:02:51Z
dc.date.available2011-12-07T14:02:51Z
dc.date.issued2011-07
dc.identifier.citationLinking genes to microbial growth kinetics: an integrated biochemical systems engineering approach. 2011, 13 (4):401-13 Metab. Eng.en
dc.identifier.issn1096-7184
dc.identifier.pmid21315172
dc.identifier.doi10.1016/j.ymben.2011.02.001
dc.identifier.urihttp://hdl.handle.net/10033/196310
dc.description.abstractThe majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is proposed, linking biomass growth and substrate consumption rates to the gene regulatory programmes that control these processes. A dynamic model of the TOL (pWW0) plasmid of Pseudomonas putida mt-2 has been developed, describing the molecular interactions that lead to the transcription of the upper and meta operons, known to produce the enzymes for the oxidative catabolism of m-xylene. The genetic circuit model was combined with a growth kinetic model decoupling biomass growth and substrate consumption rates, which are expressed as independent functions of the rate-limiting enzymes produced by the operons. Estimation of model parameters and validation of the model's predictive capability were successfully performed in batch cultures of mt-2 fed with different concentrations of m-xylene, as confirmed by relative mRNA concentration measurements of the promoters encoded in TOL. The growth formation and substrate utilisation patterns could not be accurately described by traditional Monod-type models for a wide range of conditions, demonstrating the critical importance of gene regulation for the development of advanced models closely predicting complex bioprocesses. In contrast, the proposed strategy, which utilises quantitative information pertaining to upstream molecular events that control the production of rate-limiting enzymes, predicts the catabolism of a substrate and biomass formation and could be of central importance for the design of optimal bioprocesses.
dc.language.isoenen
dc.subject.meshGene Expression Regulation, Bacterialen
dc.subject.meshGene Expression Regulation, Enzymologicen
dc.subject.meshKineticsen
dc.subject.meshModels, Biologicalen
dc.subject.meshOxidation-Reductionen
dc.subject.meshPlasmidsen
dc.subject.meshPseudomonas putidaen
dc.subject.meshTranscription, Geneticen
dc.subject.meshXylenesen
dc.titleLinking genes to microbial growth kinetics: an integrated biochemical systems engineering approach.en
dc.typeArticleen
dc.contributor.departmentCentre for Process Systems Engineering, Department of Chemical Engineering, South Kensington Campus, Imperial College London, UK.en
dc.identifier.journalMetabolic engineeringen
refterms.dateFOA2018-06-13T05:42:13Z
html.description.abstractThe majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is proposed, linking biomass growth and substrate consumption rates to the gene regulatory programmes that control these processes. A dynamic model of the TOL (pWW0) plasmid of Pseudomonas putida mt-2 has been developed, describing the molecular interactions that lead to the transcription of the upper and meta operons, known to produce the enzymes for the oxidative catabolism of m-xylene. The genetic circuit model was combined with a growth kinetic model decoupling biomass growth and substrate consumption rates, which are expressed as independent functions of the rate-limiting enzymes produced by the operons. Estimation of model parameters and validation of the model's predictive capability were successfully performed in batch cultures of mt-2 fed with different concentrations of m-xylene, as confirmed by relative mRNA concentration measurements of the promoters encoded in TOL. The growth formation and substrate utilisation patterns could not be accurately described by traditional Monod-type models for a wide range of conditions, demonstrating the critical importance of gene regulation for the development of advanced models closely predicting complex bioprocesses. In contrast, the proposed strategy, which utilises quantitative information pertaining to upstream molecular events that control the production of rate-limiting enzymes, predicts the catabolism of a substrate and biomass formation and could be of central importance for the design of optimal bioprocesses.


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