Stoichiometric growth model for riboflavin‐producing <i>Bacillus subtilis</i>

Dauner, Michael; Sauer, Uwe

doi:10.1002/bit.1153

Cited by 125 publications

(141 citation statements)

References 64 publications

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“…Strains and Growth Conditions-E. coli MG1655 ( Ϫ F Ϫ rph-1; Deutsche Sammlung von Mikroorganismen und Zellkulturen, Germany) cultures of 0.8 liter were grown in a 2-liter bioreactor (LH-Inceltech) under fully aerobic conditions at 37°C and pH 7.0 (18). Labeling experiments with a phosphoglucose isomerase deletion mutant of MG1655 2 were done with fully aerobic 50-ml cultures in 500-ml shake flasks on a rotary shaker at 37°C.…”

Section: Methodsmentioning

confidence: 99%

“…Analytical Procedures-Cellular dry weight, glucose, acetate, CO 2 , and O 2 concentrations were determined as described before (18). Crude cell extracts for in vitro enzyme assays were prepared from pellets of 10-ml culture aliquots.…”

Section: Methodsmentioning

confidence: 99%

“…Hence, specific consumption and production rates were determined from the concentration difference in the feed medium (or air) and the culture (or gas) effluent, normalized to the steady-state biomass concentration. The macromolecular biomass composition for metabolic flux analysis was calculated from the linear correlation of cellular protein and RNA content with growth rate (18). The corresponding fractions were extrapolated from the experimental data of E. coli in glucose-limited chemostat cultures (12).…”

Section: Methodsmentioning

confidence: 99%

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A Novel Metabolic Cycle Catalyzes Glucose Oxidation and Anaplerosis in Hungry Escherichia coli

Fischer

Sauer

2003

Journal of Biological Chemistry

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182

172

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Complete oxidation of carbohydrates to CO 2 is considered to be the exclusive property of the ubiquitous tricarboxylic acid cycle, the central process in cellular energy metabolism of aerobic organisms. Based on metabolism-wide in vivo quantification of intracellular carbon fluxes, we describe here complete oxidation of carbohydrates via the novel P-enolpyruvate (PEP)-glyoxylate cycle, in which two PEP molecules are oxidized by means of acetyl coenzyme A, citrate, glyoxylate, and oxaloacetate to CO 2 , and one PEP is regenerated. Key reactions are the constituents of the glyoxylate shunt and PEP carboxykinase, whose conjoint operation in this bi-functional catabolic and anabolic cycle is in sharp contrast to their generally recognized functions in anaplerosis and gluconeogenesis, respectively. Parallel operation of the PEP-glyoxylate cycle and the tricarboxylic acid cycle was identified in the bacterium Escherichia coli under conditions of glucose hunger in a slow-growing continuous culture. Because the PEPglyoxylate cycle was also active in glucose excess batch cultures of an NADPH-overproducing phosphoglucose isomerase mutant, one function of this new central pathway may be the decoupling of catabolism from NADPH formation that would otherwise occur in the tricarboxylic acid cycle.Structuring of cellular networks into pathways with distinct functions is pivotal for comprehension of "textbook" biochemistry. The ability of existing model pathways to portray flux through complex metabolic networks, however, is an open question that is just beginning to be addressed theoretically (1-3) and experimentally (4, 5). Microbial growth on the most abundant carbon-source glucose represses transcription of metabolic functions that are required on alternative carbon sources. This universal phenomenon is referred to as catabolite repression and includes a number of mechanistically distinguishable but physiologically related regulation mechanisms (6, 7). Although catabolite repression is strong under conditions of feast with excess glucose, microbes typically thrive under conditions of starvation (absence of nutrients) or hunger (suboptimal supply of nutrients) in their natural environments (8,9). This metabolic state of hunger, between optimal growth and starvation, can be studied in glucose-limited continuous (chemostat) cultures with very low glucose concentrations at a rate of growth that is controlled by the experimenter. Catabolite repression is absent under the severe glucose limitation in slow growing chemostat cultures (9 -11), and, as a consequence, increased in vivo activity of repressed metabolic enzymes is often observed with advanced methods of metabolic flux analyses based on 13 C-labeling experiments (4, 5, 12, 13).Here we elucidate metabolic impacts of severe and absent catabolite repression during growth of Escherichia coli in glucose-excess batch cultures and glucose-limited chemostat cultures. Direct analytical interpretation of 13 C-labeling patterns in proteinogenic amino acids was used to establish the ...

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Metabolic Cycle Catalyzes Glucose Oxidation and Anaplerosis in Hungry Escherichia coli

Fischer

Sauer

2003

Journal of Biological Chemistry

Self Cite

182

172

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“…E. coli (11)), and eukarya (i.e. Saccharomyces cerevisiae (12)).For B. subtilis, a stoichiometric model consisting of around 35 reactions in the central metabolism and the purine metabolism has been constructed previously (13,14). The model has been used to obtain information on the intracellular flux distribution based on fractional carbon isotope labeling (15) and for the estimation of the P/O ratio (16) and the prediction of maximum theoretical yields of commercial biochemical products (14).…”

mentioning

confidence: 99%

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Oh¹,

Palsson²,

Park

et al. 2007

Journal of Biological Chemistry

402

356

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In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genomescale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.Bacillus subtilis has been the organism of choice for the production of several important industrial products, including antibiotics, enzymes, nucleosides, and vitamins. Several aspects of the biochemistry, genetics, and physiology of B. subtilis have been studied extensively making B. subtilis the best characterized prokaryote second only to Escherichia coli (1, 2). In addition various "-omics" data sets such as transcriptomic (3), proteomic (4), and metabolomic (5) are available for B. subtilis. This wealth of experimental data enables the development of a genome-scale metabolic in silico model that can be used not only for quantitative interpretation and structured integration of such extensive data sets but also as a tool for hypothesis generation and engineering of B. subtilis metabolism.To date, constraint-based reconstruction and analysis (COBRA) 4 of cellular metabolism has been employed successfully to develop organism-specific genome-scale in silico models that have enabled numerous applications (6). Unlike other modeling strategies such as kinetic (7), stochastic (8), and cybernetic (9) methods, the COBRA approach does not attempt to compute precisely what a biochemical network does; rather, it seeks to distinguish between the network states that are achievable from those that are not, based on a detailed reconstruction of...

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“…Others [16][17][18] follow this assumption but DNA and RNA levels were determined using UV absorbance at 260nm.…”

mentioning

confidence: 99%

Comparison of DNA and RNA quantification methods suitable for parameter estimation in metabolic modeling of microorganisms

Mey

Lequeux

Maertens

et al. 2006

Analytical Biochemistry

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Recent developments in cellular and molecular biology require the accurate quantification of DNA and RNA in large numbers of samples at a sensitivity that enables determination on small quantities. Five current methods for nucleic acid quantification have been compared: 1) UV absorbance spectroscopy at 260nm, 2) Colorimetric reaction with the orcinol reagent, 3)Colorimetric reaction based on diphenylamine, 4) Fluorescence detection with reagent Hoechst 33258 and 5) Fluorescence detection with thiazole orange reagent. Genomic DNA of three different microbial species (with widely different G+C content) was used as well as two different types of yeast RNA and a mixture of equal quantities of DNA and RNA.We can conclude that for nucleic acid quantification a standard curve with DNA of the microbial strain under study is the best reference. Fluorescence detection with reagent Hoechst 33258 ® is a sensitive and precise method for DNA quantification if the G+C content is lower than 50%. In addition this method allows quantification of very low levels of DNA (ng-scale). Moreover, the samples can be crude cell extracts. Also UV absorbance at 260nm and fluorescence detection with thiazole orange reagent are sensitive methods for nucleic acid detection, but only if purified nucleic acids have to be measured.

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Stoichiometric growth model for riboflavin‐producing Bacillus subtilis

Cited by 125 publications

References 64 publications

A Novel Metabolic Cycle Catalyzes Glucose Oxidation and Anaplerosis in Hungry Escherichia coli

A Novel Metabolic Cycle Catalyzes Glucose Oxidation and Anaplerosis in Hungry Escherichia coli

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Comparison of DNA and RNA quantification methods suitable for parameter estimation in metabolic modeling of microorganisms

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