Evidence map›Paper›PMID 25527553›Full record

ArticleApplied and environmental microbiology2015

Using a genome-scale metabolic model of Enterococcus faecalis V583 to assess amino acid uptake and its impact on central metabolism.

Nadine Veith, Margrete Solheim, Koen W A van Grinsven, Brett G Olivier, Jennifer Levering, Ruth Grosseholz, Jeroen Hugenholtz, Helge Holo, Ingolf Nes, Bas Teusink and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 44 citations in OpenAlex.

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  11. Reconstruction and Analysis of a Genome-Scale Metabolic Model ofInternational journal of molecular sciences · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 3 countries.

Nadine VeithDepartment of Modeling Biological Processes, Center for Organismal Studies/Bioquant, Heidelberg University, Heidelberg, Germany nadine.veith@bioquant.uni-heidelberg.de.
Margrete SolheimDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
Koen W A van GrinsvenMolecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam and Netherlands Institute of Systems Biology, Amsterdam, The Netherlands.
Brett G OlivierSystems Bioinformatics, Amsterdam Institute for Molecules, Medicines, and Systems, VU University of Amsterdam, Amsterdam, The Netherlands.
Jennifer LeveringDepartment of Modeling Biological Processes, Center for Organismal Studies/Bioquant, Heidelberg University, Heidelberg, Germany.
Ruth GrosseholzDepartment of Modeling Biological Processes, Center for Organismal Studies/Bioquant, Heidelberg University, Heidelberg, Germany.
Jeroen HugenholtzMolecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam and Netherlands Institute of Systems Biology, Amsterdam, The Netherlands.
Helge HoloDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
Ingolf NesDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
Bas TeusinkSystems Bioinformatics, Amsterdam Institute for Molecules, Medicines, and Systems, VU University of Amsterdam, Amsterdam, The Netherlands.
Ursula KummerDepartment of Modeling Biological Processes, Center for Organismal Studies/Bioquant, Heidelberg University, Heidelberg, Germany.
Heidelberg University · DEUniversity of Amsterdam · NLNorwegian University of Life Sciences · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing 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.

Indexed as

Computer SimulationAmino AcidsEnergy MetabolismEnterococcus faecalisMetabolic Flux AnalysisMetabolic Networks and PathwaysModels, BiologicalAmino Acids

Identifiers

PMID25527553
PMCPMC4325170
OpenAlexW2054016222

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.