Evidence map›Paper›PMID 18304323›Full record

ArticleBMC genomics2008

Protein abundance profiling of the Escherichia coli cytosol.

Yasushi Ishihama, Thorsten Schmidt, Juri Rappsilber, Matthias Mann, F Ulrich Hartl, Michael J Kerner, Dmitrij Frishman

Abstract read
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 255 papers.

0numbers the graph read from it
0cells of the map it votes in
255citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

255 citing papers in PubMed.

  1. A Draft Map of E. coli Proteoforms.Analytical chemistry · 2026
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  6. The selfish ribosome.PLoS biology · 2026
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  11. Structural and Binding Properties of Dps - A Nucleoid Associated Protein.bioRxiv : the preprint server for biology · 2025
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  14. StageTip: a little giant unveiling the potential of mass spectrometry-based proteomics.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
    Review
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  17. From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation.Computational and structural biotechnology journal · 2025
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  18. First comparative proteomic andFrontiers in veterinary science · 2025
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  19. Endogenous Cu(II) Labeling for Distance Measurements on Proteins by EPR.Chemistry (Weinheim an der Bergstrasse, Germany) · 2024
    Article
  20. Article

195 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yasushi IshihamaInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. y-ishi@ttck.keio.ac.jp
Thorsten Schmidt
Juri Rappsilber
Matthias Mann
F Ulrich Hartl
Michael J Kerner
Dmitrij Frishman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge about the abundance of molecular components is an important prerequisite for building quantitative predictive models of cellular behavior. Proteins are central components of these models, since they carry out most of the fundamental processes in the cell. Thus far, protein concentrations have been difficult to measure on a large scale, but proteomic technologies have now advanced to a stage where this information becomes readily accessible.

resultsHere, we describe an experimental scheme to maximize the coverage of proteins identified by mass spectrometry of a complex biological sample. Using a combination of LC-MS/MS approaches with protein and peptide fractionation steps we identified 1103 proteins from the cytosolic fraction of the Escherichia coli strain MC4100. A measure of abundance is presented for each of the identified proteins, based on the recently developed emPAI approach which takes into account the number of sequenced peptides per protein. The values of abundance are within a broad range and accurately reflect independently measured copy numbers per cell. As expected, the most abundant proteins were those involved in protein synthesis, most notably ribosomal proteins. Proteins involved in energy metabolism as well as those with binding function were also found in high copy number while proteins annotated with the terms metabolism, transcription, transport, and cellular organization were rare. The barrel-sandwich fold was found to be the structural fold with the highest abundance. Highly abundant proteins are predicted to be less prone to aggregation based on their length, pI values, and occurrence patterns of hydrophobic stretches. We also find that abundant proteins tend to be predominantly essential. Additionally we observe a significant correlation between protein and mRNA abundance in E. coli cells.

conclusionAbundance measurements for more than 1000 E. coli proteins presented in this work represent the most complete study of protein abundance in a bacterial cell so far. We show significant associations between the abundance of a protein and its properties and functions in the cell. In this way, we provide both data and novel insights into the role of protein concentration in this model organism.

Indexed as

Chromatography, LiquidCytosolEscherichia coliEscherichia coli ProteinsMass SpectrometryProteomicsEscherichia coli Proteins

Identifiers

PMID18304323
PMCPMC2292177

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.