Evidence map›Paper›PMID 22615938›Full record

ArticlePloS one2012

In situ identification of plant-invasive bacteria with MALDI-TOF mass spectrometry.

Dominik Ziegler, Anna Mariotti, Valentin Pflüger, Maged Saad, Guido Vogel, Mauro Tonolla, Xavier Perret

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
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  10. Deletion of rRNA Operons ofFrontiers in microbiology · 2019
    Article
  11. Cowpea (Agriculture, ecosystems & environment · 2018
    Article
  12. Article
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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.

Dominik ZieglerDepartment of Botany and Plant Biology, University of Geneva, Geneva, Switzerland.
Anna Mariotti
Valentin Pflüger
Maged Saad
Guido Vogel
Mauro Tonolla
Xavier Perret

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rhizobia form a disparate collection of soil bacteria capable of reducing atmospheric nitrogen in symbiosis with legumes. The study of rhizobial populations in nature involves the collection of large numbers of nodules found on roots or stems of legumes, and the subsequent typing of nodule bacteria. To avoid the time-consuming steps of isolating and cultivating nodule bacteria prior to genotyping, a protocol of strain identification based on the comparison of MALDI-TOF MS spectra was established. In this procedure, plant nodules were considered as natural bioreactors that amplify clonal populations of nitrogen-fixing bacteroids. Following a simple isolation procedure, bacteroids were fingerprinted by analysing biomarker cellular proteins of 3 to 13 kDa using Matrix Assisted Laser Desorption/Ionization Time of Flight (MALDI-TOF) mass spectrometry. In total, bacteroids of more than 1,200 nodules collected from roots of three legumes of the Phaseoleae tribe (cowpea, soybean or siratro) were examined. Plants were inoculated with pure cultures of a slow-growing Bradyrhizobium japonicum strain G49, or either of two closely related and fast-growing Sinorhizobium fredii strains NGR234 and USDA257, or with mixed inoculants. In the fully automatic mode, correct identification of bacteroids was obtained for >97% of the nodules, and reached 100% with a minimal manual input in processing of spectra. These results showed that MALDI-TOF MS is a powerful tool for the identification of intracellular bacteria taken directly from plant tissues.

Indexed as

BacteriaBacteriological TechniquesFabaceaeRhizomeRoot Nodules, PlantSinorhizobium frediiSpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Identifiers

PMID22615938
PMCPMC3355115

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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.