Evidence map›Paper›PMID 18665227›Full record

ArticlePloS one2008

Classification and identification of bacteria by mass spectrometry and computational analysis.

Sascha Sauer, Anja Freiwald, Thomas Maier, Michael Kube, Richard Reinhardt, Markus Kostrzewa, Klaus Geider

Abstract read
In one paragraph

Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 2 pooled it
–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

112 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  10. Detection ofPathogens (Basel, Switzerland) · 2025
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  11. Accurate identification ofJournal of medical microbiology · 2025
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  13. Re-evaluation of boundaries ofInternational journal of systematic and evolutionary microbiology · 2025
    Article
  14. Unmasking Methicillin-resistantFrontiers in microbiology · 2025
    Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

52 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.

Sascha SauerMax Planck Institute for Molecular Genetics, Berlin, Germany. sauer@molgen.mpg.de
Anja Freiwald
Thomas Maier
Michael Kube
Richard Reinhardt
Markus Kostrzewa
Klaus Geider

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications. METHODOLOGY: We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection.

conclusionsWith the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.

Indexed as

Gene Expression Regulation, BacterialAlgorithmsBacteriaComputational BiologyDatabases, ProteinErwiniaGenotypeMass SpectrometryMicrobiologyModels, BiologicalPhylogenyProteomicsSequence Analysis, DNASoftwareSpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Identifiers

PMID18665227
PMCPMC2475672

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.