Literature DB >> 25527553

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

Nadine Veith1, Margrete Solheim2, Koen W A van Grinsven3, Brett G Olivier4, Jennifer Levering5, Ruth Grosseholz5, Jeroen Hugenholtz3, Helge Holo2, Ingolf Nes2, Bas Teusink4, Ursula Kummer5.   

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.
Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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Year:  2014        PMID: 25527553      PMCID: PMC4325170          DOI: 10.1128/AEM.03279-14

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  54 in total

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2.  Modelling cellular systems with PySCeS.

Authors:  Brett G Olivier; Johann M Rohwer; Jan-Hendrik S Hofmeyr
Journal:  Bioinformatics       Date:  2004-09-28       Impact factor: 6.937

3.  A general system for generating unlabelled gene replacements in bacterial chromosomes.

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Journal:  Mol Gen Genet       Date:  1996-11-27

4.  Generation of restriction map of Enterococcus faecalis OG1 and investigation of growth requirements and regions encoding biosynthetic function.

Authors:  B E Murray; K V Singh; R P Ross; J D Heath; G M Dunny; G M Weinstock
Journal:  J Bacteriol       Date:  1993-08       Impact factor: 3.490

Review 5.  Regulation of nitrogen metabolism in Bacillus subtilis: vive la différence!

Authors:  S H Fisher
Journal:  Mol Microbiol       Date:  1999-04       Impact factor: 3.501

6.  Control of the shift from homolactic acid to mixed-acid fermentation in Lactococcus lactis: predominant role of the NADH/NAD+ ratio.

Authors:  C Garrigues; P Loubiere; N D Lindley; M Cocaign-Bousquet
Journal:  J Bacteriol       Date:  1997-09       Impact factor: 3.490

7.  Catabolism of branched-chain alpha-keto acids in Enterococcus faecalis: the bkd gene cluster, enzymes, and metabolic route.

Authors:  D E Ward; R P Ross; C C van der Weijden; J L Snoep; A Claiborne
Journal:  J Bacteriol       Date:  1999-09       Impact factor: 3.490

8.  The hprK gene of Enterococcus faecalis encodes a novel bifunctional enzyme: the HPr kinase/phosphatase.

Authors:  M Kravanja; R Engelmann; V Dossonnet; M Blüggel; H E Meyer; R Frank; A Galinier; J Deutscher; N Schnell; W Hengstenberg
Journal:  Mol Microbiol       Date:  1999-01       Impact factor: 3.501

9.  Flux balance analysis of mycolic acid pathway: targets for anti-tubercular drugs.

Authors:  Karthik Raman; Preethi Rajagopalan; Nagasuma Chandra
Journal:  PLoS Comput Biol       Date:  2005-10-14       Impact factor: 4.475

10.  Open questions: microbes, metabolism and host-pathogen interactions.

Authors:  Malcolm McConville
Journal:  BMC Biol       Date:  2014-03-28       Impact factor: 7.431

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  12 in total

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Authors:  Elena G Lara; Isabelle van der Windt; Douwe Molenaar; Marjon G J de Vos; Chrats Melkonian
Journal:  Genes (Basel)       Date:  2021-08-06       Impact factor: 4.096

2.  SteadyCom: Predicting microbial abundances while ensuring community stability.

Authors:  Siu Hung Joshua Chan; Margaret N Simons; Costas D Maranas
Journal:  PLoS Comput Biol       Date:  2017-05-15       Impact factor: 4.475

3.  Traceability, reproducibility and wiki-exploration for "à-la-carte" reconstructions of genome-scale metabolic models.

Authors:  Méziane Aite; Marie Chevallier; Clémence Frioux; Camille Trottier; Jeanne Got; María Paz Cortés; Sebastián N Mendoza; Grégory Carrier; Olivier Dameron; Nicolas Guillaudeux; Mauricio Latorre; Nicolás Loira; Gabriel V Markov; Alejandro Maass; Anne Siegel
Journal:  PLoS Comput Biol       Date:  2018-05-23       Impact factor: 4.475

4.  Single amino acid utilization for bacterial categorization.

Authors:  Yi-Kai Liu; Hung-Chih Kuo; Chih-Ho Lai; Chi-Chung Chou
Journal:  Sci Rep       Date:  2020-07-29       Impact factor: 4.379

5.  GapMind: Automated Annotation of Amino Acid Biosynthesis.

Authors:  Morgan N Price; Adam M Deutschbauer; Adam P Arkin
Journal:  mSystems       Date:  2020-06-23       Impact factor: 6.496

6.  A riboswitch gives rise to multi-generational phenotypic heterogeneity in an auxotrophic bacterium.

Authors:  Jhonatan A Hernandez-Valdes; Jordi van Gestel; Oscar P Kuipers
Journal:  Nat Commun       Date:  2020-03-05       Impact factor: 14.919

7.  Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen Enterococcus faecalis.

Authors:  Ruth Großeholz; Ching-Chiek Koh; Nadine Veith; Tomas Fiedler; Madlen Strauss; Brett Olivier; Ben C Collins; Olga T Schubert; Frank Bergmann; Bernd Kreikemeyer; Ruedi Aebersold; Ursula Kummer
Journal:  NPJ Syst Biol Appl       Date:  2016-09-08

8.  Mapping the Physiological Response of Oenococcus oeni to Ethanol Stress Using an Extended Genome-Scale Metabolic Model.

Authors:  Angela Contreras; Magdalena Ribbeck; Guillermo D Gutiérrez; Pablo M Cañon; Sebastián N Mendoza; Eduardo Agosin
Journal:  Front Microbiol       Date:  2018-03-01       Impact factor: 5.640

9.  Metabolic Modeling of Streptococcus mutans Reveals Complex Nutrient Requirements of an Oral Pathogen.

Authors:  Kenan Jijakli; Paul A Jensen
Journal:  mSystems       Date:  2019-10-29       Impact factor: 6.496

10.  Inspecting the Solution Space of Genome-Scale Metabolic Models.

Authors:  Seyed Babak Loghmani; Nadine Veith; Sven Sahle; Frank T Bergmann; Brett G Olivier; Ursula Kummer
Journal:  Metabolites       Date:  2022-01-05
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