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General Information
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 vanEunen_2010.pdf
Project name not specified


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


Experimental Details
Temperature (°C) 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 evapora ...

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Submission and curation

Entered by: Administrator KiMoSysFirst name: Administrator
Affiliation: INESC-ID/IST
Homepage: http://kdbio.inesc-id.pt/kimosys
Interests: mathematical modeling, accessible data, use of data

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

Updated: 2020-04-24 16:10:36 UTC

Version: 1

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

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



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