Glucose/Malate shift experiment - data in openBIS database


Experimental data, descriptions of materials and methods, and scripts for analysis are stored in the public database openBIS. To retrieve data files, click on the links on this page. For more information on the data formats, please see the descriptions of column headers and data validators.

Original data

Dynamic shift experiments

Data Description Technology Glc → Glc+Mal shift Mal → Glc+Mal shift
Optical density OD600 GM1 GM2 GM3 MG1 MG2 MG3
Metabolomics (extracellular) Description HPLC GM1 GM2 GM3 MG1 MG2 MG3
Metabolomics Description LC-MS, absolute GM1a GM1b GM2 GM3 MG1a MG1b MG2 MG3
LC-MS, relative GM1a GM1b GM2 GM3 MG1a MG1b MG2 MG3
Proteomics Description 2D-PAGE GM1 GM2 GM3 MG1 MG2 MG3
Transcriptomics Description Two-color microarray GM1 GM2 GM3 MG1 MG2 MG3
Tiling array GM1 GM2 GM3 MG1 MG2 MG3
Proteomics* Description Absolute quantification by GFP GM1 GM2 MG1 MG2
Live cell array* Description GFP promoter fusions GM/OD GM/GFP MG/OD MG/GFP

Remarks: The abbreviation GM1a means "shift experiment GM", first biological replicate experiment (1), first technical quantification (a). Small letters "a" and "b" denote repeated technical quantifications of the same biological samples. Data set GM1 was discarded due to technical problems. Data sets marked with a star (*) were not obtained in the bioreactor, but from downscaled experiments.

Genome-wide identification of DNA binding sites by ChIP on chip

Data Data files
CcpA binding
Processed data in M9 malate Rep1 Rep2
Processed data in M9 glucose plus malate Rep1 Rep2
CcpC binding sites, ChIP on chip (raw data) Rep1 and Rep2
CggR binding sites, ChIP on chip (raw data) Rep1 Rep2
CcpN binding sites, ChIP on chip (raw data) Rep1 Rep2
CcpN , CcpC, CggR processed data (M9 malate or glucose) Rep1 and Rep2

Remarks: A description can be found here. Rep1 and Rep2 denote biological replicates.

Processed data

Interpolated measured data

Data Technology Processing Glc → Glc+Mal shift Mal → Glc+Mal shift
Metabolomics (extracellular) HPLC Interpolation GM1 GM2 GM3 MG1 MG2 MG3
Metabolomics (absolute) MS Kalman Mean StdDev Mean StdDev
Metabolomics (relative) MS Kalman Mean StdDev Mean StdDev
Metabolomics (absolute) MS MCR GM MG
Proteomics 2D PAGE and LC-MS MCR GM MG
Transcriptomics Two-color microarray MCR GM MG
Transcriptomics (QQnorm) Tiling array MCR GM MG

Remarks: Data processing methods are described in SOM 1.

Inferred data

Data Calculation method Description Shift data Additional files
Metabolic rates Least squares interpolation SOM 3 GM MG Movie visualization
TF activities Network component analysis SOM 2 GM MG
Flux response half times Fit by sigmoid curve Description
response half times public.xls
Promoter activities Polynomial fitting Description GM MG Live_Cell_Array_data.xls
Live Cell Array.pdf
Post-transcriptional regulation.pdf

Models, predictions, and genome annotation

Data Description File
Stoichiometric metabolic model
Gene functional classification Description Confidence assessment
Model files, result tables and alternative classifier versions
Correlation of promoter activity, transcript level and protein abundance Description Correlation
Predicted TF targets Description predictedTFtargets.txt
Transcription network and weights inferred by NCA SOM 2 Network structure and influence weights
High resolution graphics

Method descriptions

Construction of strain Description
Cell size and cell concentration for conversion to absolute concentrations Description
Verification of population homogeneity assumption with GFP reporter strains Description
Integration of different omics data in openBIS database Description
Detection of unannotated transcripts exhibiting differential expression Description
Identification of differentially expressed genes and detailed assignment of putative functions by clustering Description
Bayesian classification of gene function from nutritional shift Description
Systematic prediction of transcription factor target genes Description
Genome-wide identification of DNA binding sites for the transcription factors CcpA, CcpC, CcpN, and CggR by ChIP-chip analysis Description
Response half times of metabolites, transcripts, proteins, and metabolic fluxes Description
Impact of transcriptional regulation of metabolic flux reorganization estimated by global flux sensitivity analysis Description
Identification of post-transcriptional regulation by correlation of promoter activity, mRNA abundance, and protein abundance time profiles Description

MATLAB code for data processing

Processing/estimation task Description File
Matlab import/export of openBIS tables Description openBISread.m
Dynamic data preprocessing SOM 1
Multi-curve regression SOM 1
Dynamic intracellular flux estimation SOM 3
Metabolic rates SOM 3
Interpolation of extracellular concentrations and rates SOM 1
Metabolic flux sensitivity Description sensitivity_scripts.tar.gz
Network component analysis SOM 2


HPLC High pressure liquid chromatography
MS Mass spectrometry
2D PAGE 2-dimensional gel
LC-MS Liquid chromatography + mass spectrometry
GM Glc → Glc+Mal shift
MG Mal → Glc+Mal shift
NCA Network component analysis
MCR Multi-curve regression
TF Transcription factor
GFP Green fluorescent protein

Original data as standalone packages

These packages contain the raw data and can be installed locally. You need a Unix based system with PostgreSQL 9.0 and Java JRE 1.6. When you untar the packages a README file describes all the steps which are needed to setup the sytem.
Big Experiment
Reannotation Experiment


For scientific questions, please contact:
Jörg Stelling, Stéphane Aymerich, or Uwe Sauer.

For technical questions, please contact:
Jörg Büscher (jrb [at] or Wolfram Liebermeister (wolfram.liebermeister [at]