Multiparametric Profiling for Identification of Chemosensitizers against Gram-Negative Bacteria - Aix-Marseille Université Access content directly
Journal Articles Frontiers in Microbiology Year : 2018

Multiparametric Profiling for Identification of Chemosensitizers against Gram-Negative Bacteria


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.
Fichier principal
Vignette du fichier
fmicb-09-00204.pdf (1.67 Mo) Télécharger le fichier
Origin Publisher files allowed on an open archive

Dates and versions

hal-01824504 , version 1 (27-06-2018)




Vincent Lôme, Jean-Michel Brunel, Jean-Marie Pagès, Jean-Michel Michel Bolla. Multiparametric Profiling for Identification of Chemosensitizers against Gram-Negative Bacteria. Frontiers in Microbiology, 2018, 9, ⟨10.3389/fmicb.2018.00204⟩. ⟨hal-01824504⟩


158 View
171 Download



Gmail Mastodon Facebook X LinkedIn More