Dataset Information

A platform for detecting cross-resistance in antibacterial drug discovery.

ABSTRACT:

Background

To address the growing antibiotic resistance problem, new antibacterial drugs must exert activity against pathogens resistant to agents already in use. With a view to providing a rapid means for deselecting antibacterial drug candidates that fail to meet this requirement, we report here the generation and application of a platform for detecting cross-resistance between established and novel antibacterial agents.

Methods

This first iteration of the cross-resistance platform (CRP) consists of 28 strains of defined resistance genotype, established in a uniform genetic background (the SH1000 strain of the clinically significant pathogen Staphylococcus aureus). Most CRP members were engineered through introduction of constitutively expressed resistance determinants on a low copy-number plasmid, with a smaller number selected as spontaneous resistant mutants.

Results

Members of the CRP collectively exhibit resistance to many of the major classes of antibacterial agent in use. We employed the CRP to test two antibiotics that have been proposed in the literature as potential drug candidates: γ-actinorhodin and batumin. No cross-resistance was detected for γ-actinorhodin, whilst a CRP member resistant to triclosan exhibited a 32-fold reduction in susceptibility to batumin. Thus, a resistance phenotype that already exists in clinical strains mediates profound resistance to batumin, implying that this compound is not a promising antibacterial drug candidate.

Conclusions

By detecting cross-resistance between established and novel antibacterial agents, the CRP offers the ability to deselect compounds whose activity is substantially impaired by existing resistance mechanisms. The CRP therefore represents a useful addition to the antibacterial drug discovery toolbox.

SUBMITTER: Galarion LH

PROVIDER: S-EPMC8843079 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Publications

A platform for detecting cross-resistance in antibacterial drug discovery.

Galarion Luiza H LH Mohamad Merianne M Alzeyadi Zeyad Z Randall Christopher P CP O'Neill Alex J AJ

The Journal of antimicrobial chemotherapy 20210501 6

<h4>Background</h4>To address the growing antibiotic resistance problem, new antibacterial drugs must exert activity against pathogens resistant to agents already in use. With a view to providing a rapid means for deselecting antibacterial drug candidates that fail to meet this requirement, we report here the generation and application of a platform for detecting cross-resistance between established and novel antibacterial agents.<h4>Methods</h4>This first iteration of the cross-resistance platf ...[more]

PMID: 33755133

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Project description:Objective: A Tag Array chip was used to detect plasmids of different template concentration, and then analyzed for sensitivity and specificity. Drug resistance genes from tuberculosis clinical specimens were detected, giving comparative phenotypic resistance results to explore the feasibility and value of clinical applications. Methods: Twenty-four strains of Mycobacterium Tuberculosis (MTB) having sequence differences in extracted plasmids of mutant strains. The plasmid was diluted into different concentrations, and then was performed to analyze the sensitivity and specificity of the chip system. A total of 427 clinical specimens (including spinal tuberculosis and pulmonary tuberculosis) were collected from patients who came from seven hospitals. Design, optimization and preparation of the chip detection system, sequencing and phenotypic drug susceptibility results were analyzed to evaluate the sensitivity and specificity of the gene chip. Results: In the template, concentrations of 1 × 103 copies/μL and above were consistent with sequencing results in the mutant. The sensitivity and specificity in spine Tuberculosis specimen of rifampicin (RFP) were 94.40 and 92.86%; isoniazide (INH) were 92.37 and 87.50%; ethambutol (EMB) were 61.36 and 89.29%; fluoroquinolones (FQS) were 79.41 and 92.86%; streptomycin (SM) were 90.18 and 89.29%; second line drugs (SLD) were 77.61 and 83.93%. In Pulmonary Tuberculosis specimen, the sensitivity and specificity respectively were RFP: 92.74%; 93.75%; INH: 91.26%; 87.50%; EMB: 54.17%; 89.58%; FQS: 84.87%; 93.75%; SM: 86.73%; 85.42%; SLD: 80.9%; 91.67%. The RFP, INH, FQs and SM resistance genes was highly sensitive and specific: however, for detection of amikacin (AMK), capreomycin (CPM), kanamycin (KM), specificity was higher, but sensitivity was lower. Sensitivity for the detection of a mutation in the eis promoter region could be improved. Conclusion: Tag Array chip can achieve rapid, accurate detection of tuberculosis resistance, which has important clinical significance and feasibility.

Dataset Information

A platform for detecting cross-resistance in antibacterial drug discovery.

Background

Methods

Results

Conclusions

Publications

A platform for detecting cross-resistance in antibacterial drug discovery.

Similar Datasets

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