Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726899
Title: Connecting transcriptional regulation and microbial growth kinetics in cultures of Pseudomonas putida
Author: Tsipa, Argyro
ISNI:       0000 0004 6422 680X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Abstract:
Bioprocesses performance is monitored using microbial growth kinetics models. However most of them are empirical and unstructured ignoring molecular and transcriptional interactions thus failing in accurate prediction. Pseudomonas putida mt-2, which harbours the TOL plasmid, is a strain of great biotechnological potential. M-xylene and toluene are commonly utilised by TOL pathway while toluene enables chromosomal ortho-cleavage pathway activation. Herein, the transcriptional kinetics of TOL and key ortho-cleavage promoters which control substrate bioconversion resulting in biomass formation was consistently studied. Thus, revealing the interconnection of the two pathways and promoters’ specific expression patterns. The experimental observations lead to a dynamic model coupling transcriptional regulation to microbial growth kinetics by providing upstream quantitative information. This model enables adequate predicition capability of substrate utilisation and biomass growth under a wide range of initial conditions. However in nature it is uncommon for bacteria to degrade a sole substrate. Therefore P. putida mt-2 cells induction with succinate-toluene, m-xylene-toluene mixtures is studied. The transcriptional kinetics revealed promoters’ bi-modal expression pattern and carbon catabolite repression regardless of the growth conditions. Transcriptional regulation upon entry of m-xylene-toluene mixture was modelled resulting in a mechanistic microbial growth kinetic model development which accurately predicts substrate(s) utilisation and biomass growth patterns. The current double substrate microbial growth kinetic model can more accurately predict the macroscopic phenomena compared to the Monod, Monod-type and competitive enzymatic interaction models.
Supervisor: Mantalaris, Sakis ; Pistikopoulos, Stratos Sponsor: European Union
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.726899  DOI: Not available
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