Overview
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 |
| LC-MS | 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 | CcpA_CHIP_CHIP_raw_data.zip |
| 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
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.zip | |
| response half times public.xls | ||||
| Promoter activities | Polynomial fitting | Description | GM MG | Live_Cell_Array_data.xls |
| Live Cell Array.pdf | ||||
| LCA-Tiling-Protein_correlations.xls | ||||
| Post-transcriptional regulation.pdf |
Models, predictions, and genome annotation
| Data | Description | File |
|---|---|---|
| Stoichiometric metabolic model | model-consensus-B.zip | |
| 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 analysis.zip |
| 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
| Method | Description |
|---|---|
| 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 | consensusDataProcess.zip |
| Multi-curve regression | SOM 1 | multicurve_regression.zip |
| Dynamic intracellular flux estimation | SOM 3 | dynamic_flux_estimation.zip |
| Metabolic rates | SOM 3 | metabolic_fluxes.zip |
| Interpolation of extracellular concentrations and rates | SOM 1 | physiology_scripts.zip |
| Metabolic flux sensitivity | Description | sensitivity_scripts.tar.gz |
| Network component analysis | SOM 2 | nca.zip |
Abbreviations
| 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
Contact
For scientific questions, please contact:
Jörg Stelling, Stéphane Aymerich, or Uwe Sauer.
Jörg Büscher (jrb [at] brain-biotech.de) or Wolfram Liebermeister (wolfram.liebermeister [at] charite.de)