Peer-reviewed dataset: The quantitative and condition-dependent Escherichia coli proteome

  • Alexander Schmidt (Creator)
  • Karl Kochanowski (Creator)
  • Silke Bonsing-Vedelaar (Creator)
  • Erik Ahrne (Creator)
  • Benjamin Volkmer (Creator)
  • Luciano Callipo (Creator)
  • Kèvin Knoops (Creator)
  • Manuel Bauer (Creator)
  • Ruedi Aebersold (Creator)
  • Matthias Heinemann (Creator)



Measuring precise concentrations of proteins can provide insights into biological processes. Here we use efficient protein extraction and sample fractionation, as well as state-of-the-art quantitative mass spectrometry techniques to generate a comprehensive, condition-dependent protein-abundance map for Escherichia coli. We measure cellular protein concentrations for 55% of predicted E. coli genes (>2,300 proteins) under 22 different experimental conditions and identify methylation and N-terminal protein acetylations previously not known to be prevalent in bacteria. We uncover system-wide proteome allocation, expression regulation and post-translational adaptations. These data provide a valuable resource for the systems biology and broader E. coli research communities.
SpeciesList: scientific name: Escherichia coli; NCBI TaxID: 562;
ModificationList: Oxidation; Acetyl; Carbamidomethyl
Instrument: LTQ Orbitrap Elite

Cell Type: permanent cell line cell
Instrument: LTQ Orbitrap Elite
Software: Mascot Parser, Mascot Server 2.4.1
Modification: Acetyl; Oxidation; Carbamidomethyl
Quantification: TIC
Experiment Type: Shotgun proteomics
Date made available8-Dec-2015
PublisherEuropean Bioinformatics Institute (EMBL-EBI)

Keywords on Datasets

  • Escherichia coli
  • proteome
  • Absolute quantiifcation
  • iBAQ
  • mass spectreomtry
  • E. coli
  • NCBI TaxID: 562

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