Evidence map›Paper›PMID 29556218›Full record

ArticleFrontiers in microbiology2018

Multiparametric Profiling for Identification of Chemosensitizers against Gram-Negative Bacteria.

Vincent Lôme, Jean-Michel Brunel, Jean-Marie Pagès, Jean-Michel Bolla

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Rapid quantitative detection ofFrontiers in bioengineering and biotechnology · 2023
    Article
  3. Review
  4. Article
  5. Antibiotics (Basel, Switzerland) · 2020
    Article
  6. Review
  7. 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

4 authors.

Vincent LômeUMR MD1, Aix-Marseille University, IRBA, TMCD2, Facultés de Médecine et de Pharmacie, Marseille, France.
Jean-Michel BrunelCentre de Recherche en Cancérologie de Marseille (CRCM), CNRS, UMR7258, Institut Paoli Calmettes, Aix-Marseille Université, UM 105, Inserm, U1068, Faculté de Pharmacie, Marseille, France.
Jean-Marie PagèsUMR MD1, Aix-Marseille University, IRBA, TMCD2, Facultés de Médecine et de Pharmacie, Marseille, France.
Jean-Michel BollaUMR MD1, Aix-Marseille University, IRBA, TMCD2, Facultés de Médecine et de Pharmacie, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance is now a worldwide therapeutic problem. Since the beginning of anti-infectious treatment bacteria have rapidly shown an incredible ability to develop and transfer resistance mechanisms. In the last decades, the design variation of pioneer bioactive molecules has strongly improved their activity and the pharmaceutical companies partly won the race against the clock. Since the 1980s, the new classes of antibiotics that emerged were mainly directed to Gram-positive bacteria. Thus, we are now facing to multidrug-resistant Gram-negative bacteria, with no therapeutic options to deal with them. These bacteria are mainly resistant because of their double membrane that conjointly impairs antibiotic accumulation and extrudes these molecules when entered. The main challenge is to allow antibiotics to cross the impermeable envelope and reach their targets. One promising solution would be to associate, in a combination therapy, a usual antibiotic with a non-antibiotic chemosensitizer. Nevertheless, for effective drug discovery, there is a prominent lack of tools required to understand the rules of permeation and accumulation into Gram-negative bacteria. By the use of a multidrug-resistant enterobacteria, we introduce a high-content screening procedure for chemosensitizers discovery by quantitative assessment of drug accumulation, alteration of barriers, and deduction of their activity profile. We assembled and analyzed a control chemicals library to perform the proof of concept. The analysis was based on real-time monitoring of the efflux alteration and measure of the influx increase in the presence of studied compounds in an automatized bio-assay. Then, synergistic activity of compounds with an antibiotic was studied and kinetic data reduction was performed which led to the calculation of a score for each barrier to be altered.

Indexed as

antibiotic resistanceautomated platformcombination therapyhit-to-leadwhole-cell screening

Identifiers

PMID29556218
PMCPMC5845390

What OpenQuestion holds

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LicenceCC BY
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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.