RESUMO
Metabolic engineering strategies applied over the last two decades to produce shikimate (SA) in Escherichia coli have resulted in a battery of strains bearing many expression systems. However, the effects that these systems have on the host physiology and how they impact the production of SA are still not well understood. In this work we utilized an engineered E. coli strain to determine the consequences of carrying a vector that promotes SA production from glucose with a high-yield but that is also expected to impose a significant cellular burden. Kinetic comparisons in fermentors showed that instead of exerting a negative effect, the sole presence of the plasmid increased glucose consumption without diminishing the growth rate. By constitutively expressing a biosynthetic operon from this vector, the more active glycolytic metabolism was exploited to redirect intermediates toward the production of SA, which further increased the glucose consumption rate and avoided excess acetate production. Fluxomics and metabolomics experiments revealed a global remodeling of the carbon and energy metabolism in the production strain, where the increased SA production reduced the carbon available for oxidative and fermentative pathways. Moreover, the results showed that the production of SA relies on a specific setup of the pentose phosphate pathway, where both its oxidative and non-oxidative branches are strongly activated to supply erythrose-4-phosphate and balance the NADPH requirements. This work improves our understanding of the metabolic reorganization observed in E. coli in response to the plasmid-based expression of the SA biosynthetic pathway. Biotechnol. Bioeng. 2017;114: 1319-1330. © 2017 Wiley Periodicals, Inc.
Assuntos
Escherichia coli/fisiologia , Melhoramento Genético/métodos , Glucose/metabolismo , Plasmídeos/genética , Proteínas Recombinantes/genética , Ácido Chiquímico/metabolismo , Simulação por Computador , Engenharia Metabólica/métodos , Análise do Fluxo Metabólico , Modelos Biológicos , Proteínas Recombinantes/metabolismo , Transfecção/métodosRESUMO
We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions.