Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/58395

TitleMapping Salmonella typhimurium pathways using 13C Metabolic Flux Analysis
Author(s)Correia, Daniela M.
Sargo, C.
Silva, A.
Santos, Sophia Torres
Giordano, Roberto C.
Ferreira, Eugénio C.
Zangirolami, Teresa C.
Ribeiro, Marcelo P. A.
Rocha, Isabel
KeywordsSalmonella typhimurium
Chemostat culture
C-MFA
Genome-scale metabolic model
simulation
C-13-MFA
In silico simulation
13 C-MFA
Issue dateMar-2019
PublisherElsevier
JournalMetabolic Engineering
CitationCorreia, Daniela M.; Sargo, C.; Silva, A.; Santos, Sophia T.; Giordano, Roberto C.; Ferreira, Eugénio C.; Zangirolami, Teresa C.; Ribeiro, Marcelo P. A.; Rocha, Isabel, Mapping Salmonella typhimurium pathways using 13C Metabolic Flux Analysis. Metabolic Engineering, 52, 303-314, 2019
Abstract(s)In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a 13C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% 13C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genome-scale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.
TypeArticle
URIhttp://hdl.handle.net/1822/58395
DOI10.1016/j.ymben.2018.11.011
ISSN1096-7176
e-ISSN1096-7184
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S1096717618300703
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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