Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14869
Title: Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach
Authors: Koutinas, Michalis 
Kiparissides, Alexandros 
Silva-Rocha, Rafael 
Lam, Ming Chi 
Martins dos Santos, Vitor A.P. 
de Lorenzo, Victor 
Pistikopoulos, Efstratios N. 
Mantalaris, Athanasios A. 
Major Field of Science: Natural Sciences
Field Category: Biological Sciences
Keywords: Metabolic engineering;Genetic circuit;PWW0 (TOL) plasmid;Pseudomonas putida;M-Xylene;Dynamic model
Issue Date: Jul-2011
Source: Metabolic Engineering, 2011, vol. 13, no. 4, pp. 401-413
Volume: 13
Issue: 4
Start page: 401
End page: 413
Journal: Metabolic engineering 
Abstract: The 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.
URI: https://hdl.handle.net/20.500.14279/14869
ISSN: 10967184
DOI: 10.1016/j.ymben.2011.02.001
Rights: © Elsevier
Type: Article
Affiliation : Imperial College London 
Centro Nacional de Biotecnología 
Helmholtz Center for Infection Research 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

CORE Recommender
Show full item record

SCOPUSTM   
Citations

26
checked on Nov 9, 2023

WEB OF SCIENCETM
Citations

22
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s)

318
Last Week
1
Last month
11
checked on Nov 21, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.