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Constraint-based modelling of mixed microbial populations: Application to polyhydroxyalkanoates production

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Resumo:The combined use of mixed microbial cultures (MMC) and fermented feedstock as substrate may significantly decrease polyhydroxyalkanoates (PHA) production costs and make them more competitive in relation to conventional petroleum-based polymers. However, there still exists a lack of knowledge at metabolic level that limits the development of strategies to make this process more effective. In this thesis, system biology computational tools were developed and applied to PHA production by MMC from fermented sugar cane molasses, rich in volatile fatty acids (VFA). Firstly, a metabolic network able to describe the uptake of complex mixtures of VFA and PHA production was defined. This metabolic network was applied to metabolic flux analysis (MFA) to describe substrate uptake and PHA production fluxes over the enrichment time of a culture submitted to the feast and famine regimen. Then, the minimization of the tricarboxylic acid cycle (TCA) fluxes was identified as the key metabolic objective of a MMC subjected to this regimen by flux balance analysis (FBA). This model enabled to predict, with an acceptable accuracy, the PHA fluxes and biopolymer composition. Subsequently, data gathered from microautoradiography-fluorescence in situ hybridization (MAR-FISH) was used to develop a segregated FBA model able to predict the flux distribution for the three populations identified in the enriched culture. These results were slightly better than those obtained by the non-segregated FBA and were consistent with MFA results. Finally, a dynamic metabolic model was proposed based on the previous models and on a regulatory factor for VFA uptake and PHA production. This model allowed to identify the dynamics of the process and regulatory factor as well as to validate the previous results. Globally, this thesis enabled to demonstrate the potential of using computational tools to understand and optimize PHA production by MMC.
Autores principais:Pardelha, Filipa Alexandra Guerreiro
Assunto:Polyhydroxyalkanoates (PHA) Mixed microbial culture (MMC) Fermented feedstock Constraint based modelling Flux balance analysis (FBA) Metabolic flux analysis (MFA)
Ano:2013
País:Portugal
Tipo de documento:tese de doutoramento
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:The combined use of mixed microbial cultures (MMC) and fermented feedstock as substrate may significantly decrease polyhydroxyalkanoates (PHA) production costs and make them more competitive in relation to conventional petroleum-based polymers. However, there still exists a lack of knowledge at metabolic level that limits the development of strategies to make this process more effective. In this thesis, system biology computational tools were developed and applied to PHA production by MMC from fermented sugar cane molasses, rich in volatile fatty acids (VFA). Firstly, a metabolic network able to describe the uptake of complex mixtures of VFA and PHA production was defined. This metabolic network was applied to metabolic flux analysis (MFA) to describe substrate uptake and PHA production fluxes over the enrichment time of a culture submitted to the feast and famine regimen. Then, the minimization of the tricarboxylic acid cycle (TCA) fluxes was identified as the key metabolic objective of a MMC subjected to this regimen by flux balance analysis (FBA). This model enabled to predict, with an acceptable accuracy, the PHA fluxes and biopolymer composition. Subsequently, data gathered from microautoradiography-fluorescence in situ hybridization (MAR-FISH) was used to develop a segregated FBA model able to predict the flux distribution for the three populations identified in the enriched culture. These results were slightly better than those obtained by the non-segregated FBA and were consistent with MFA results. Finally, a dynamic metabolic model was proposed based on the previous models and on a regulatory factor for VFA uptake and PHA production. This model allowed to identify the dynamics of the process and regulatory factor as well as to validate the previous results. Globally, this thesis enabled to demonstrate the potential of using computational tools to understand and optimize PHA production by MMC.