Multi‐way analysis of flux distributions across multiple conditions

Verouden, Maikel P. H.; Notebaart, Richard A.; Westerhuis, Johan A.; Werf, M.J. van der; Teusink, Bas; Smilde, Age K.

doi:10.1002/cem.1238

Cited by 16 publications

(13 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The apparent catabolic and total carbon balances were around 80–90% (Table ). To obtain a complete view, we calculated the ATP production using a genome‐scale stoichiometric network model (Verouden et al ., ; Flahaut et al ., ) as described by Teusink et al . ().…”

Section: Resultsmentioning

confidence: 98%

Protein costs do not explain evolution of metabolic strategies and regulation of ribosomal content: does protein investment explain an anaerobic bacterial Crabtree effect?

Goel

Eckhardt

Puri

et al. 2015

Molecular Microbiology

Self Cite

View full text Add to dashboard Cite

SummaryProtein investment costs are considered a major driver for the choice of alternative metabolic strategies. We tested this premise in Lactococcus lactis, a bacterium that exhibits a distinct, anaerobic version of the bacterial Crabtree/Warburg effect; with increasing growth rates it shifts from a high yield metabolic mode [mixed-acid fermentation; 3 adenosine triphosphate (ATP) per glucose] to a low yield metabolic mode (homolactic fermentation; 2 ATP per glucose). We studied growth rate-dependent relative transcription and protein ratios, enzyme activities, and fluxes of L. lactis in glucose-limited chemostats, providing a high-quality and comprehensive data set. A three-to fourfold higher growth rate rerouted metabolism from acetate to lactate as the main fermentation product. However, we observed hardly any changes in transcription, protein levels and enzyme activities. Even levels of ribosomal proteins, constituting a major investment in cellular machinery, changed only slightly. Thus, contrary to the original hypothesis, central metabolism in this organism appears to be hardly regulated at the level of gene expression, but rather at the metabolic level. We conclude that L. lactis is either poorly adapted to growth at low and constant glucose concentrations, or that protein costs play a less important role in fitness than hitherto assumed.

show abstract

Section: Resultsmentioning

confidence: 98%

Protein costs do not explain evolution of metabolic strategies and regulation of ribosomal content: does protein investment explain an anaerobic bacterial Crabtree effect?

Goel

Eckhardt

Puri

et al. 2015

Molecular Microbiology

Self Cite

View full text Add to dashboard Cite

show abstract

“…This method uses orthology searches against existing genome-scale models to predict genes in a genome sequence that code for metabolic reactions and their respective metabolic function. Identification of "metabolic" genes and the respective function predictions were based on the existing, well-curated genome-scale models of L. plantarum, L. lactis, Bacillus subtilis, and Escherichia coli (7,(29)(30)(31). A genome-scale model of L. plantarum served as the template model for setting up the individual reaction equations of each metabolic reaction that are common in both lactic acid bacteria.…”

Section: Resultsmentioning

confidence: 99%

“…In E. faecalis, changes in the ATP levels are sensed by HPr-kinase/phosphatase (hprK, EF1749), a kinase that phosphorylates or dephosphorylates the phosphocarrier protein (HPr; ptsH, EF0709) at Ser-46 (P-SerHPr), a component of the phosphoenolpyruvate-carbohydrate phosphotransferase system, depending on the intracellular ATP level (57). A complex of P-Ser-HPr and the transcriptional regulatory protein CcpA (ccpA, EF1741) were reported to increase the expression of lldh1 (29,30). A kinetic inhibition of the PFL in combination with increased lldh expression might therefore explain high L-lactate production rates at high glucose concentrations.…”

Section: Discussionmentioning

confidence: 99%

Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism

Veith

Solheim

Grinsven

et al. 2015

Appl Environ Microbiol

Self Cite

View full text Add to dashboard Cite

dIncreasing antibiotic resistance in pathogenic bacteria necessitates the development of new medication strategies. Interfering with the metabolic network of the pathogen can provide novel drug targets but simultaneously requires a deeper and more detailed organism-specific understanding of the metabolism, which is often surprisingly sparse. In light of this, we reconstructed a genome-scale metabolic model of the pathogen Enterococcus faecalis V583. The manually curated metabolic network comprises 642 metabolites and 706 reactions. We experimentally determined metabolic profiles of E. faecalis grown in chemically defined medium in an anaerobic chemostat setup at different dilution rates and calculated the net uptake and product fluxes to constrain the model. We computed growth-associated energy and maintenance parameters and studied flux distributions through the metabolic network. Amino acid auxotrophies were identified experimentally for model validation and revealed seven essential amino acids. In addition, the important metabolic hub of glutamine/glutamate was altered by constructing a glutamine synthetase knockout mutant. The metabolic profile showed a slight shift in the fermentation pattern toward ethanol production and increased uptake rates of multiple amino acids, especially L-glutamine and L-glutamate. The model was used to understand the altered flux distributions in the mutant and provided an explanation for the experimentally observed redirection of the metabolic flux. We further highlighted the importance of gene-regulatory effects on the redirection of the metabolic fluxes upon perturbation. The genome-scale metabolic model presented here includes gene-protein-reaction associations, allowing a further use for biotechnological applications, for studying essential genes, proteins, or reactions, and the search for novel drug targets. Enterococcus faecalis plays an important role in both biotechnology and medicine (1, 2). Some strains are used in the dairy industry for food fermentation and flavor production. At the same time, other strains play an increasingly important role as pathogens, especially in hospital-acquired infections (1). E. faecalis strains show multiple antibiotic resistances and are therefore the cause of serious complications. Alternative strategies for combating multiple resistant bacteria such as E. faecalis are urgently needed. Targeting vulnerable points in the bacterial metabolism could offer such an alternative route and has been discussed as a promising strategy (3, 4). However, surprisingly little is known about the detailed metabolism of E. faecalis, and it is therefore mandatory to explore this in a more elaborate fashion than previously reported.E. faecalis shows a high stress tolerance and is adapted to a variety of different native environments ranging from soil up to human or animal digestive tracts (1, 2). This environmental variability requires a highly flexible metabolic system to quickly adapt to diverse and changing environmental conditions. Therefore, strategies...

show abstract

“…GEMs have primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions (McCloskey et al, 2013). Initially, these models only considered well -characterized organisms; nevertheless, the interest in the generation of metabolic models of less characterized and complex biological systems has progressively increased, including the GEMs of several lactic acid bacteria, such as Lactococcus lactis (Oliveira et al, 2005; Oddone et al, 2009; Verouden et al, 2009; Flahaut et al, 2013), Lactobacillus plantarum (Teusink et al, 2006) and Streptococcus thermophilus (Pastink et al, 2009). …”

Section: Introductionmentioning

confidence: 99%

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

et al. 2017

View full text Add to dashboard Cite

Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche.

show abstract

Multi‐way analysis of flux distributions across multiple conditions

Cited by 16 publications

References 34 publications

Protein costs do not explain evolution of metabolic strategies and regulation of ribosomal content: does protein investment explain an anaerobic bacterial Crabtree effect?

Protein costs do not explain evolution of metabolic strategies and regulation of ribosomal content: does protein investment explain an anaerobic bacterial Crabtree effect?

Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

Contact Info

Product

Resources

About