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Dataset Identifier

Metadata
datasetIdentifierPASS00273
datasetTypeMSMS
submitterMyriam Ferro <myriam.ferro@cea.fr>
submitter_organization
lab_head_full_name
lab_head_email
lab_head_organization
lab_head_country
datasetTagecoli_identif
datasetTitleMass spectrometry-based workflow for accurate quantification of E. coli enzymes: how proteomics can play a key role in metabolic engineering
publicReleaseDate2013-12-20 00:00:00
finalizedDate2013-07-19 02:43:53
summaryMetabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics and proteomics may be required to model the metabolism of potential cell factories.
Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study we developed a quantification workflow to analyse enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labelled standards with Selected Reaction Monitoring (SRM) analysis. First, full-length 15N labelled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimised for reproducibility and multiplexing capabilities over a single 30-minute LC-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimised for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and activity. This provides information which can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering.
contributorsMathieu Trauchessec , Michel Jaquinod, Aline Bonvalot, Virginie Brun, Christophe Bruley, Delphine Ropers, Hidde de Jong, Jérôme Garin, Gwenaëlle Bestel-Corre, Myriam Ferro
publicationunpublished
growthCultures were performed in minimal media containing 5 g/L glucose
Cells were harvested during the exponential growth phase, based on OD at 600 nm.
treatment
extractionCultures were centrifuged 5 min at 8000 g, supernatant was discarded, and cells were washed in the same volume of fresh PBS. Cells were resuspended in 100 mM KPO4, pH 7.6 buffer for sonication. Lysates were centrifuged 10 min at 12,000 g and supernatant was filtered through 0.22 µm membranes.
separation
digestionProteins or E. coli lysates were solubilised in 8 M urea, 50 mM NH4HC03 buffer, reduced for 30 min at room temperature with 10 mM DTT and alkylated for 45 min at room temperature in the dark with 100 mM iodoacetamide. Samples were diluted with 50 mM NH4HC03 to reach a final urea concentration of 2 M. LysC digestion was performed for 2 hours at 37 °C at an enzyme/protein ratio of 1/100 (w/w). Samples were diluted once again with 50 mM NH4HC03 to reduce urea to 0.5 M final concentration before performing trypsin digestion for 2 hours at 37 °C at an enzyme/protein ratio of 1/20 (w/w). Peptide samples were finally desalted on Sep-Pack tC18 1cc vacuum cartridges.
acquisitionMS/MS analyses were performed on a hybrid triple quadrupole/ion trap mass spectrometer (4000 QTRAP; ABSciex, Les Ulis, France). Liquid chromatography (LC) separation was performed on an ultimate 3000 LC-chromatography system (Dionex, Voisins le Bretonneux, France) coupled to a Kinetex XB-C18 column, 2.1 x 150 mm, 2.6 µm, 100Å (Phenomenex, Torrance, CA 90501). Peptides were separated using a linear 4% to 45% acetonitrile gradient over 30 min at a flow rate of 50 µL/min.
For MS/MS experiments, peptides were analysed on a 4000 QTRAP hybrid triple quadrupole mass spectrometer (ABSciex, Les Ulis, France) operated using a Turbo V source in Electrospray Ionisation (ESI) mode, operated in "Information Dependent Acquisition" (IDA) mode under Analyst version 1.5.1 software (AB SCIEX). A precursor ion scan between m/z 400-1400 was performed as a survey scan for the IDA method. Enhanced product ion (EPI) spectra were acquired with a scan speed of 4000 amu/s using a dynamic fill time for optimal MS/MS and rolling collision energy settings. Precursor and product ion accuracies were 1.2 and 0.6 Da, respectively, which is in line with the specifications of the 4000 QTRAP.
Data were acquired in positive mode with the ion spray voltage at 5500 V, curtain gas 15 (arbitrary units), interface heater temperature 350 °C. Collision exit, entrance and declustering potential were set to 27, 12 and 50 volts, respectively.
informaticsMS/MS spectra were assigned to peptides using a sequence database search strategy performed using the Ecoli_K12_decoy protein sequence databank (release July 28, 2011, 25096 sequences) and Mascot (version 2.4). Trypsin was used to generate peptides allowing 1 miss-cleavage; cystein carbamidomethyl was set as a fixed modification while mono and di-oxidation of methionine was set as a variable modification. Mass tolerance for precursors and fragments ions was 1.2 and 0.6 Da respectively. No contaminants were excluded. Peptide charge was set at 1, 2 and 3 and instrument was ESI-TRAP.
instrumentsQTRAP 4000
speciesE. coli
massModificationsC+57.021464

Official URL for this dataset: http://www.peptideatlas.org/PASS/PASS00273
To access files via FTP, use credentials:
Servername: ftp.peptideatlas.org
Username: PASS00273
Password: GE8477eeg

Or use your browser's FTP mode: ftp://PASS00273:GE8477eeg@ftp.peptideatlas.org/


Listing of files:

 5.4K Jul 19  2013 PASS00273_DESCRIPTION.txt
 6.1M Jul 19  2013 QTRAP10691.dat
  11M Jul 19  2013 QTRAP10691.wiff
 6.1M Jul 19  2013 QTRAP10719.dat
 9.4M Jul 19  2013 QTRAP10719.wiff
 5.1M Jul 19  2013 QTRAP10721.dat
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 4.6M Jul 19  2013 QTRAP10723.dat
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 844K Jul 19  2013 QTRAP5118.dat
 4.6M Jul 19  2013 QTRAP5118.wiff
 1.1M Jul 19  2013 QTRAP5118.wiff.scan
 1.1M Jul 19  2013 QTRAP5120.dat
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 1.2M Jul 19  2013 QTRAP5120.wiff.scan
 736K Jul 19  2013 QTRAP5122.dat
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 923K Jul 19  2013 QTRAP5124.dat
 4.6M Jul 19  2013 QTRAP5124.wiff
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 527K Jul 19  2013 QTRAP5126.dat
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 912K Jul 19  2013 QTRAP5126.wiff.scan
 542K Jul 19  2013 QTRAP6150.dat
 5.5M Jul 19  2013 QTRAP6150.wiff
 1.2M Jul 19  2013 QTRAP6561.dat
 5.7M Jul 19  2013 QTRAP6561.wiff
 3.4M Jul 19  2013 QTRAP6953.dat
 5.8M Jul 19  2013 QTRAP6953.wiff
 2.1M Jul 19  2013 QTRAP6955.dat
 5.6M Jul 19  2013 QTRAP6955.wiff
 1.6M Jul 19  2013 QTRAP7249.dat
 5.5M Jul 19  2013 QTRAP7249.wiff
 1.6M Jul 19  2013 QTRAP7251.dat
 5.5M Jul 19  2013 QTRAP7251.wiff
 2.1M Jul 19  2013 QTRAP7502.dat
 5.6M Jul 19  2013 QTRAP7502.wiff
 2.1M Jul 19  2013 QTRAP7504.dat
 5.7M Jul 19  2013 QTRAP7504.wiff
 1.8M Jul 19  2013 QTRAP7506.dat
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 6.0M Jul 19  2013 QTRAP9928.dat
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 4.5M Jul 19  2013 QTRAP9933.dat
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 4.5M Jul 19  2013 QTRAP9937.dat
 6.0M Jul 19  2013 QTRAP9937.wiff
 3.2M Jul 19  2013 QTRAP9939.dat
 5.8M Jul 19  2013 QTRAP9939.wiff
  14K Jul 19  2013 search_parameters_database_Ecoli.docx

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