Evidence map›Paper›PMID 18629082›Full record

ArticleComparative and functional genomics2003

Functional genomics via metabolic footprinting: monitoring metabolite secretion by Escherichia coli tryptophan metabolism mutants using FT-IR and direct injection electrospray mass spectrometry.

Naheed N Kaderbhai, David I Broadhurst, David I Ellis, Royston Goodacre, Douglas B Kell

Abstract read
In one paragraph

Article in Comparative and functional genomics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Metabolic profiling analysis of cytochrome bMetabolomics : Official journal of the Metabolomic Society · 2026
    Article
  2. Plant and microbial sciences as key drivers in the development of metabolomics research.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Review
  3. Article
  4. Metabolic Fingerprint Analysis of CytochromeFrontiers in microbiology · 2022
    Article
  5. Article
  6. Review
  7. The metabolome 18 years on: a concept comes of age.Metabolomics : Official journal of the Metabolomic Society · 2016
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Metabolomic studies of human gastric cancer: review.World journal of gastroenterology · 2014
    Review
  13. Metabolomic analysis of the food-borne pathogenMetabolomics : Official journal of the Metabolomic Society · 2014
    Article
  14. Review
  15. Emergent cooperation in microbial metabolism.Molecular systems biology · 2010
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review
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

5 authors.

Naheed N KaderbhaiInstitute of Biological Sciences, University of Wales, Aberystwyth, Wales Ceredigion SY23 3DD, UK.
David I Broadhurst
David I Ellis
Royston Goodacre
Douglas B Kell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We sought to test the hypothesis that mutant bacterial strains could be discriminated from each other on the basis of the metabolites they secrete into the medium (their 'metabolic footprint'), using two methods of 'global' metabolite analysis (FT-IR and direct injection electrospray mass spectrometry). The biological system used was based on a published study of Escherichia coli tryptophan mutants that had been analysed and discriminated by Yanofsky and colleagues using transcriptome analysis. Wild-type strains supplemented with tryptophan or analogues could be discriminated from controls using FT-IR of 24 h broths, as could each of the mutant strains in both minimal and supplemented media. Direct injection electrospray mass spectrometry with unit mass resolution could also be used to discriminate the strains from each other, and had the advantage that the discrimination required the use of just two or three masses in each case. These were determined via a genetic algorithm. Both methods are rapid, reagentless, reproducible and cheap, and might beneficially be extended to the analysis of gene knockout libraries.

Identifiers

PMID18629082
PMCPMC2447367

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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.