Evidence map›Paper›PMID 26911658›Full record

ArticleScientific reports2016

Evaluation of Parameters for High Efficiency Transformation of Acinetobacter baumannii.

Suleyman Yildirim, Mitchell G Thompson, Anna C Jacobs, Daniel V Zurawski, Benjamin C Kirkup

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Variations in plasmid transfer inMicrobiology spectrum · 2026
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  5. Microbiology (Reading, England) · 2023
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  11. Review
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  13. Next Generation of TnApplied and environmental microbiology · 2019
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  18. Antimicrobial Activity of Gallium Compounds on ESKAPE Pathogens.Frontiers in cellular and infection microbiology · 2018
    Article
  19. Article
  20. Article
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.

Suleyman YildirimDepartment of Wound Infections, Bacterial Diseases Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.
Mitchell G ThompsonDepartment of Wound Infections, Bacterial Diseases Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.
Anna C JacobsDepartment of Wound Infections, Bacterial Diseases Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.
Daniel V ZurawskiDepartment of Wound Infections, Bacterial Diseases Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.
Benjamin C KirkupDepartment of Wound Infections, Bacterial Diseases Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acinetobacter baumannii is an emerging, nosocomial pathogen that is poorly characterized due to a paucity of genetic tools and methods. While whole genome sequence data from several epidemic and environmental strains have recently become available, the functional characterization of genes is significantly lagging. Efficient transformation is one of the first steps to develop molecular tools that can be used to address these shortcomings. Here we report parameters allowing high efficiency transformation of A. baumannii. Using a multi-factorial experimental design we found that growth phase, voltage, and resistance all significantly contribute to transformation efficiency. The highest efficiency (4.3 × 10(8) Transformants/μg DNA) was obtained at the stationary growth phase of the bacterium (OD 6.0) using 25 ng of plasmid DNA under 100 Ohms resistance and 1.7 kV/cm voltage. The optimized electroporation parameters reported here provide a useful tool for genetic manipulation of A. baumannii.

Indexed as

Transformation, BacterialAcinetobacter baumanniiDNA, BacterialElectroporationPlasmidsDNA, Bacterial

Identifiers

PMID26911658
PMCPMC4766488

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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.