Repository » Data AccessID 111

Detail View - Data AccessID 111

Backimage Back

General Information info

Manuscript title Time-dependent regulation of yeast glycolysis upon nitrogen starvation depends on cell history.
PubMed ID 20232995
Journal IET Systems Biology
Year 2010
Authors van Eunen K, Dool P, Canelas AB, Kiewiet J, Bouwman J, van Gulik WM, Westerhoff HV, Bakker BM
Affiliations Vrije Universiteit Amsterdam, Department of Molecular Cell Physiology, Amsterdam, The Netherlands.
Keywords yeast, glycolysis, glucose-limited chemostat, nitrogen starvation
Full text article Downloadarticle vanEunen_2010.pdf
Project name not specified

Experiment Description info

Organism Saccharomyces cerevisiae
Strain CEN.PK113-7D
Data type metabolites at steady-state
Data units mM
Execution date not specified

Experimental Details info

Temperature (0C) 30
pH 5.0 ± 0.1
Carbon source glucose,
Culture mode chemostat
Process condition aerobic
Dilution rate (h-1) 0.1 and 0.35
Working volume (L) 1.0
Biomass concentration (g/L) Yieldglu,X (g/g) = 0.45 ± 0.02 (D = 0.1h-1) and 0.29 ± 0.01 (D = 0.35h-1)
Medium composition

Defined mineral medium [1] in which glucose (42 mM) was the growth-limiting nutrient.

General protocol information Sampling method: Samples were taken 15 min after the start of the fermentative capacity assay to the protocol described by Canelas et al. [2].

Quenching procedure: Quenching and washing of the sample was done with 100% and 80% (v/v) methanol/water, respectively, at -40ºC.

Extraction technique: boiling ethanol

Sample analyzing method: LC-ESI-MS

Methods description - Notes

Intracellular metabolite extraction was carried out using the boiling ethanol method [3], as described in Lange et al. [4]. U-13C-labelled cell extract was added to the pellets just before the extraction, as internal standard. Sample concentration was accomplished by evaporation under vacuum, as described by Mashego et al. [5]. The concentrations of the intracellular metabolites were determined by electrospray-ionisation liquid-chromatography mass spectrometry/mass spectrometry (ESI-LC-MS/MS) [6] and the quantification was based on isotope dilution mass spectrometry (IDMS) [5, 7]. Adenosine triphosphate (ATP), adenosine diphosphate (ADP) and adenosine monophosphate (AMP) were analysed by ion-pairing reversed-phase ESI-LC-MS/MS as described in [8]. ---------------------------------------References--------------------------------------
[1] VERDUYN C., POSTMA E., SCHEFFERS W.A., VAN DIJKEN J.P.: Yeast, 1992, 8, (7), pp. 501–517.
[2] CANELAS A.B., RAS C., TEN PIERICK A., VAN DAM J.C., HEIJNEN J.J., VAN GULIK W.M., Metabolomics, 2008, 4, (3), pp. 226–239.
[3] GONZALEZ B., FRANCOIS J., RENAUD M., Yeast, 1997, 13, (14), pp. 1347–1355.
[4] LANGE H.C., EMAN M., VAN ZUIJLEN G., ET AL., Biotechnol. Bioeng., 2001, 75, (4), pp. 406–415.
[5] MASHEGO M.R., WU L., VAN DAM J.C., ET AL., Biotechnol. Bioeng., 2004, 85, (6), pp. 620–628.
[6] VAN DAM J.C., EMAN M.R., FRANK J., LANGE H.C., VAN DEDEM G.W.K., HEIJNEN S.J., Anal. Chim. Acta, 2002, 460, (2), pp. 209–218.
[7] WU L., MASHEGO M.R., VAN DAM J.C., ET AL., Anal. Biochem., 2005, 336, (2), pp. 164–171.
[8] SEIFAR R.M., RAS C., VAN DAM J.C., VAN GULIK W.M., HEIJNEN J.J., VAN WINDEN W.A., Anal. Biochem., 2009, 388, (2), pp. 213–219.

Data file
Downloadmetabolites KIMODATAID111_v1.xlsx
Alternative format(s)
no file uploaded


Related Data: AccessID 61 | AccessID 62 | AccessID 69 | AccessID 70 | AccessID 93 | AccessID 97 | AccessID 98 | AccessID 99 | AccessID 100 | AccessID 115 | AccessID 117 | AccessID 120 | AccessID 121 | AccessID 122 | AccessID 123 | AccessID 124

Submission and curation info

Entered by Administrator KiMoSysFirst name: Administrator
Affiliation: INESC-ID/IST
Interests: mathematical modeling, accessible data, use of data

Created 2018-07-30 14:53:24 UTC

Updated 2018-07-30 14:58:24 UTC

Version 1

Status (reviewed) 2018-07-30 14:58:34 UTC

Associated Models

Here we can find relevant models associated with Data EntryID 111:

Model name Category Model Type Data used for Access Json
Authors: Karen van Eunen, José A. L. Kiewiet, Hans V. Westerhoff, Barbara M. Bakker

Original paper: Testing Biochemistry Revisited: How In Vivo Metabolism Can Be Understood from In Vitro Enzyme Kinetics

vanEunen2012 - Yeast Glycolysis (glucose upshift) Metabolism ordinary differential equations Model building and Model validation Visto4 {"affiliation":"Department of Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands","article_file_name":null,"authors":"Karen van Eunen, Jos\u00e9 A. L. Kiewiet, Hans V. Westerhoff, Barbara M. Bakker","biomodels_id":"BIOMD1403250001","category":"Metabolism","combine_archive_content_type":null,"combine_archive_file_name":null,"combine_archive_file_size":null,"combine_archive_updated_at":null,"comments":"Original model source: in BioModels database.","control":null,"dilution_rate":"","id":46,"journal":"PLoS Computational Biology","keywords":"yeast glycolysis, In Vivo and in Vitro Enzyme Kinetics, computational model","main_organism":"Saccharomyces cerevisiae","manuscript_title":"Testing Biochemistry Revisited: How In Vivo Metabolism Can Be Understood from In Vitro Enzyme Kinetics","model_name":"vanEunen2012 - Yeast Glycolysis (glucose upshift)","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"22570597","review_journal_id":null,"sbml_file_name":"vanEunen_2012.pdf","software":"MATLAB (MathWorks)","used_for":"---\n- Model building\n- Model validation\n","year":2012} Administrator KiMoSys

Associate models to data

- Several models can be associated.

Add New Model

Backimage Back | Top