Evaluation of the capacity of bacteria to develop antimicrobial resistance
To fight antibiotic resistance, to better understand the mechanisms set up by bacteria, to prevent and to fight them, Smaltis offers its know-how and expertise in the assessment and analysis of resistance phenomena.
Our offer
Epidemiological monitoring
Among its services, Smaltis proposes to study the evolution of bacterial resistance to antibiotics on the market. This epidemiological monitoring makes it possible to track the increase in the proportion of bacteria resistant to a given molecule and the associated resistance mechanisms. This analysis is based on the determination of the Minimum Inhibitory Concentration (MIC) of commonly used antibiotics on clinical strains, as well as on the analysis of mechanisms already described for strains presenting resistance.
Smaltis is thus involved in various projects related to human health, in collaboration with the CNR – National Reference Center for Antibiotic Resistance of the CHRU Jean Minjoz.
On the other hand, in the context of animal health, Smaltis carries out epidemiological surveillance on a collection of more than 5000 isolates and for 14 antibiotics. This project brings together the main players in the market.
Management of antibiotic resistance risk
The management of the risk of antibiotic resistance to an antibacterial compound under development requires the performance of different experiments providing essential and complementary information. The results of these studies make it possible to predict the frequency of appearance of resistant mutants after exposure to the antimicrobial agent and thus to anticipate future resistance that will emerge in clinical isolates. On the other hand, they allow to highlight the resistance mechanisms, known or not, that these isolates will use to adapt.
To manage the risk of antibiotic resistance in your compounds, Smaltis proposes to:
- Study the evolution of resistance by successive exposure (several passages) of the targeted bacterial species to your anti-infective molecules
- Determine the frequency of appearance of resistant mutants by exposure to the antimicrobial agent at concentrations higher than the MIC
- Determine the resistance mechanisms involved by characterizing spontaneous mutantsto
Evolution of the resistance by successive passages
From an antibiotic molecule, Smaltis offers you to assess the evolution of bacterial resistance, after successive contacts (passages) of the strains with the antibacterial compound. Repeated series of MICs are thus performed. This evaluation gives an idea of the risk and speed of resistance emergence over time.
Frequency of occurrence of resistant mutants
The determination of the spontaneous mutation frequency is based on a single contact of the bacteria of interest with the anti-infective molecule: the strains are grown on a medium containing 4 to 8 times the MIC of the antibiotic. The population of clones possessing a mutation allowing them to be resistant and therefore to survive is then selected and quantified.
This one-step method also makes it possible to determine the Mutation Prevention Concentration (MPC) for a molecule, i.e. the concentration above which the selection of resistant mutants within a bacterial population is not possible.
Mechanisms of resistance involved
Through the generation and selection of spontaneous mutants, Smaltis assists you in identifying resistance mechanisms and expressed regulatory pathways. This analysis is based on:
- Characterization of the resistance mechanisms involved
- Identification of mutations
- Reconstruction of the regulatory pathways leading to increased resistance
Generation of spontaneous resistant mutant strains
Selection of different mutants on the basis of phenotype and resistance level
Identification of mutations by sequencing
Construction of KO/KI mutants to validate the mechanism of action
In-depth understanding of resistance mechanisms through molecular biology
The evaluation of the antibiotic resistance profile can be performed on your strains. We can also use reference strains, or a collection of characterized clinical strains including more than 70,000 isolates from different pathologies.
Resistance mechanisms in Pseudomonas aeruginosa
In addition, in the case of anti-Pseudomonas aeruginosa compounds, Smaltis can help you anticipate the most prevalent clinical resistance mechanisms. This service is carried out on a P. aeruginosa mutant bank built from the PAO1 strain. These mutants have been developed to present totally characterized resistance profiles. This tool allows you to know at a very early stage if these mechanisms can participate or not in the resistance of the pyocyanic bacillus to your molecules in development.
Example of achievement
Description and characterization of new odilorhabdine resistance mechanisms in Klebsiella pneumoniae, in collaboration with Nosopharm: Missense Mutations in the CrrB Protein Mediate Odilorhabdin Derivative Resistance in Klebsiella pneumoniae
References
- Mechanisms of Resistance to Ceftolozane/Tazobactam in Pseudomonas aeruginosa: Results of the GERPA Multicenter Study, Fournier et al., 2020
- Reassessment of the cooperativity between efflux system MexAB-OprM and cephalosporinase AmpC in the resistance of Pseudomonas aeruginosa to β-lactams, Grosjean et al., 2020
- Constitutive Activation of MexT by Amino Acid Substitutions Results in MexEF-OprN Overproduction in Clinical Isolates of Pseudomonas aeruginosa, Juarez et al, 2018
- Toxic Electrophiles Induce Expression of the Multidrug Efflux Pump MexEF-OprN in Pseudomonas aeruginosa through a Novel Transcriptional Regulator, CmrA, Juarez et al, 2017
- Amino Acid Substitutions Account for Most MexS Alterations in Clinical nfxC Mutants of Pseudomonas aeruginosa, Richardot et al, 2016
- Multiple mutations lead to MexXY-OprM-dependent aminoglycoside resistance in clinical strains of Pseudomonas aeruginosa, Guenard et al, 2014
- Role of MexAB-OprM in intrinsic resistance of Pseudomonas aeruginosa to temocillin and impact on the susceptibility of strains isolated from patients suffering from cystic fibrosis, Buick et al, 2012
- A two-component regulatory system interconnects resistance to polymyxins, aminoglycosides, fluoroquinolones, and β-lactams in Pseudomonas aeruginosa, Muller et al, 2011
- Efflux unbalance in Pseudomonas aeruginosa isolates from cystic fibrosis patients, Vettoretti et al, 2009
