DataEntryID 128
    General information
      Manuscript title: Transcriptional regulation of respiration in yeast metabolizing differently repressive carbon substrates
      PubMed ID: http://www.ncbi.nlm.nih.gov/pubmed/20167065
      Journal: BMC Systems Biology
      Year: 2010
      Authors: Sarah-Maria Fendt, Uwe Sauer
      Affiliations: Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
      Keywords: Saccharomyces cerevisiae, Flux Analysis, FY4, Yeast
      Full text article: https://kimosys.org/rails/active_storage/blobs/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBak1HIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--ad46f7ab65a067b1c4406eddaabf8dcb7d8033ce/Fluxes_Yeast_Fendt_2010.pdf
      Project name: not specified

    Experiment description
      Organism: Saccharomyces cerevisiae
      Strain: FY4
      Data type: flux measurements
      Data units: mmol/g*h
      Execution date: 2009-03-09

    Experimental details
      Temperature (°C): 30
      pH: not applicable
      Carbon source: glucose, galactose, mannose, pyruvate
      Culture mode: batch
      Process condition: aerobic
      Dilution rate (h⁻¹): not applicable
      Working volume: 0,0012 L
      Biomass concentration (g/L): see Table 1
      Medium composition: minimal medium with either glucose, mannose, galactose or pyruvate as sole carbon source
      General protocol information: Type analysis list: , 13C constrained MFA; Platform list: , GC-MS;
      Methods description: Strains, medium and cultivation conditions - Allliquid cultivations were carried out using minimal medium as described in Blank and Sauer (2004) [1]. The pre-cultures were always cultured in glucose minimal medium. Other carbon sources or labeled substrates were only added t o the experiment culture at 10 g/l each.
Determination of growth rate, uptake and secretion rates - Growth rates were determined in eight independent experiments on the naturally labeled carbon sources. To determine the growth rate, the optical density at a wavelength of 600 nm was measured in a spectra-photometer (Molecular Devices, Sunnyvale, USA) for 8 to 12 times over the whole growth curve of FY4. Specific growth rates were determined by linear regression of the logarithmic OD600 values over time from at least 6 data points at maximum rate.
Flux analysis - The labeled cultures were inoculated with an OD600 of 0.015 or less. 1 ml of culture was harvested during midexponential growth (OD600 0.5 - 1.2). The cells were washed three times with ddH2O and stored at -20°C for GC-MS analysis. The supernatant was stored for determining uptake and secretion rates of glucose, mannose, galactose, pyruvate, ethanol, acetate, glycerol and succinate at -20°C. The experiment was repeated at least two times.
Protein abundance measurement - The enzyme expression level was calculated from the slope between the biomass signal (light scattering) [2] (excitation at 620 nm) and the GFP signal (excitation at 486 nm, emission at 510 nm) gained from the protein GFP-fusion strains [3].
Prediction of involved transcription factors - Transcription factors are more often associated with a subset of differentially expressed proteins than expected by chance were determined by a statistical analysis adopted from Boyle et al. [4] as outlined in Kümmel et al. [5]: The likelihood is calculated with the hypergeometric distribution that a transcription factor is associated with the differential expressed enzymes between two conditions compared to all enzymes.
-----------References------------
[1] Blank LM, Sauer U: TCA cycle activity in Saccharomyces cerevisiae is a function of the environmentally determined specific growth and glucose uptake rates. Microbiol 2004, 150:1085-1093. https://doi.org/cq4g5w
[2] Kensy F, Büchs J: Online-Monitoring von Microfermentationen. Laborwelt 2006, 7.
[3] Huh WK, Flavo JV, Gerke LC, Carroll AS, Howson RW, Weissman JS, O’Shea EK: Global analysis of protein localization in budding yeast. Nature 2003, 425:686-691. https://doi.org/fvhxr7
[4] Boyle EI, Weng S, Gollub J, Jin H, Botstein D, Cherry JM, Sherlock G: GO: TermFinder - open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes. Bioinformatics 2004, 20(18):3710-3715. https://doi.org/cpcms8
[5] Kümmel A, Ewald JC, Fendt SM, Jol S, Picotti P, Aebersold R, Sauer U, Zamboni N, Heinemann M: Differential glucose repression in common yeast strains in response to HXK2 deletions. FEMS Yeast Res 2010. https://doi.org/fjfnjr 

      Data file: http://kimosys.org/repository/128/download?parameter=1579; http://kimosys.org/repository/128/download?parameter=1578; http://kimosys.org/repository/128/download?parameter=1577; 
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    Submission and curation
      Entered by: Hugo Mochão
      Created: 2020-11-23 18:16:21 UTC
      Updated: 2020-11-24 14:22:56 UTC
      Version: 2
      Status: (unreviewed)
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