Evidence map›Paper›PMID 27507962›Full record

ArticleFrontiers in microbiology2016

Antibiotic Susceptibility Testing of the Gram-Negative Bacteria Based on Flow Cytometry.

Claude Saint-Ruf, Steve Crussard, Christine Franceschi, Sylvain Orenga, Jasmine Ouattara, Mahendrasingh Ramjeet, Jérémy Surre, Ivan Matic

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.3field-weighted citation impact, top 6% of its field
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

21 citing papers in PubMed, 48 citations in OpenAlex.

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  9. The Autofluorescence Patterns ofPathogens (Basel, Switzerland) · 2021
    Article
  10. Rapid Determination of Antibiotic Resistance inFrontiers in microbiology · 2021
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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

8 authors at 4 institutions in 1 country.

Claude Saint-RufInstitut National de la Santé et de la Recherche Médicale, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Université Paris Descartes Paris, France.
Steve CrussardInstitut National de la Santé et de la Recherche Médicale, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Université Paris Descartes Paris, France.
Christine FranceschiMicrobiology Unit, R&D Microbiology, BioMérieux SA La Balme Les Grottes, France.
Sylvain OrengaMicrobiology Unit, R&D Microbiology, BioMérieux SA La Balme Les Grottes, France.
Jasmine OuattaraInstitut National de la Santé et de la Recherche Médicale, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Université Paris Descartes Paris, France.
Mahendrasingh RamjeetMicrobiology Unit, R&D Microbiology, BioMérieux SA La Balme Les Grottes, France.
Jérémy SurreInstitut National de la Santé et de la Recherche Médicale, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Université Paris DescartesParis, France; Microbiology Unit, R&D Microbiology, BioMérieux SALa Balme Les Grottes, France.
Ivan MaticInstitut National de la Santé et de la Recherche Médicale, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Université Paris Descartes Paris, France.
bioMérieux (France) · FRSorbonne Paris Cité · FRInserm · FRUniversité Paris Cité · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapidly treating infections with adequate antibiotics is of major importance. This requires a fast and accurate determination of the antibiotic susceptibility of bacterial pathogens. The most frequently used methods are slow because they are based on the measurement of growth inhibition. Faster methods, such as PCR-based detection of determinants of antibiotic resistance, do not always provide relevant information on susceptibility, particularly that which is not genetically based. Consequently, new methods, such as the detection of changes in bacterial physiology caused by antibiotics using flow cytometry and fluorescent viability markers, are being explored. In this study, we assessed whether Alexa Fluor® 633 Hydrazide (AFH), which targets carbonyl groups, can be used for antibiotic susceptibility testing. Carbonylation of cellular macromolecules, which increases in antibiotic-treated cells, is a particularly appropriate to assess for this purpose because it is irreversible. We tested the susceptibility of clinical isolates of Gram-negative bacteria, Escherichia coli and Pseudomonas aeruginosa, to antibiotics from the three classes: β-lactams, aminoglycosides, and fluoroquinolones. In addition to AFH, we used TO-PRO®-3, which enters cells with damaged membranes and binds to DNA, and DiBAC4 (3), which enters cells with depolarized membranes. We also monitored antibiotic-induced morphological alterations of bacterial cells by analyzing light scattering signals. Although all tested dyes and light scattering signals allowed for the detection of antibiotic-sensitive cells, AFH proved to be the most suitable for the fast and reliable detection of antibiotic susceptibility.

Indexed as

antibiotic susceptibility testingbacteriaflow cytometryfluorescent hydrazideprotein carbonylation

Identifiers

PMID27507962
PMCPMC4960253
OpenAlexW2495691041

What OpenQuestion holds

Textmetadata
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.