Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο: https://hdl.handle.net/20.500.14279/14864
Τίτλος: Improving the prediction of Pseudomonas putida mt-2 growth kinetics with the use of a gene expression regulation model of the TOL plasmid
Συγγραφείς: Koutinas, Michalis 
Kiparissides, Alexandros 
Lam, Ming Chi 
Silva-Rocha, Rafael 
Godinho, Miguel 
de Lorenzo, Victor 
Martins dos Santos, Vitor A.P. 
Pistikopoulos, Efstratios N. 
Mantalaris, Athanasios A. 
Major Field of Science: Natural Sciences
Field Category: Biological Sciences
Λέξεις-κλειδιά: Dynamic modelling;PWW0 (TOL) plasmid;Genetic circuit;Pseudomonas putida;M-Xylene
Ημερομηνία Έκδοσης: 15-Ιου-2011
Πηγή: Biochemical Engineering Journal, 2011, vol. 55, no. 2, pp. 108-118
Volume: 55
Issue: 2
Start page: 108
End page: 118
Περιοδικό: Biochemical Engineering Journal 
Περίληψη: The molecular and genetic events responsible for the growth kinetics of a microorganism can be extensively influenced by the presence of mixtures of substrates leading to unusual growth patterns, which cannot be accurately predicted by mathematical models developed using analogies to enzyme kinetics. Towards this end, we have combined a dynamic mathematical model of the Ps/. Pr promoters of the TOL (pWW0) plasmid of Pseudomonas putida mt-2, involved in the metabolism of m-xylene, with the growth kinetics of the microorganism to predict the biodegradation of m-xylene and succinate in batch cultures. The substrate interactions observed in mixed-substrate experiments could not be accurately described by models without directly specifying the type of interaction even when accounting for enzymatic interactions. The structure of the genetic circuit-growth kinetic model was validated with batch cultures of mt-2 fed with m-xylene and succinate and its predictive capability was confirmed by successfully predicting independent sets of experimental data. Our combined genetic circuit-growth kinetic modelling approach exemplifies the critical importance of the molecular interactions of key genetic circuits in predicting unusual growth patterns. Such strategy is more suitable in describing bioprocess performance, which current models fail to predict.
URI: https://hdl.handle.net/20.500.14279/14864
ISSN: 1369703X
DOI: 10.1016/j.bej.2011.03.012
Rights: © Elsevier
Type: Article
Affiliation: Imperial College London 
Helmholtz Center for Infection Research 
Centro Nacional de Biotecnología 
Wageningen University 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Εμφανίζεται στις συλλογές:Άρθρα/Articles

CORE Recommender
Δείξε την πλήρη περιγραφή του τεκμηρίου

SCOPUSTM   
Citations

12
checked on 9 Νοε 2023

WEB OF SCIENCETM
Citations

10
Last Week
0
Last month
0
checked on 29 Οκτ 2023

Page view(s)

320
Last Week
1
Last month
2
checked on 6 Νοε 2024

Google ScholarTM

Check

Altmetric


Όλα τα τεκμήρια του δικτυακού τόπου προστατεύονται από πνευματικά δικαιώματα