Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Heteroresistance in Mycobacterium tuberculosis.

Authors: H, Rinder; K T, Mieskes; T, Löscher;

Heteroresistance in Mycobacterium tuberculosis.

Abstract

Drug resistance in Mycobacterium tuberculosis is often linked to specific mutations in a limited number of resistance genes. Detection of these mutations in a cultured isolate can predict the resistant phenotype. Genotypic analysis of the mycobacteria directly in a clinical specimen would result in considerable time saving for resistance prediction.To find out whether resistance-predicting genotypes of mycobacteria found after cultivation always give a good reflection of those in the original clinical sample.Restriction fragment length polymorphisms of repetitive polymerase chain reaction (PCR) amplification and cloning of PCR products were used as nonintegrative methods to describe the composition of katG, rpsL and embB genotypes involved in resistance to isoniazid, streptomycin and ethambutol, respectively, in the original sample. This result was then compared to the phenotypic resistance profile after cultivation.Using both methods, mixed, heteroresistant populations could be detected in almost every fifth analyzed sample (katG: 5 of 16; rpsL: 3 of 17; embB: 1 of 21). Direct sequencing, a widely used integrative method, repeatedly failed to detect heteroresistance.Heteroresistance is a valid phenomenon in clinical tuberculosis. It is not rare and not restricted to a particular resistance gene, and is obscured by cultivation as well as by some, not all, culture-independent resistance prediction tests.

Related Organizations
Keywords

Base Sequence, Molecular Sequence Data, Antitubercular Agents, Sputum, Microbial Sensitivity Tests, Mycobacterium tuberculosis, DNA Fingerprinting, Polymerase Chain Reaction, Sensitivity and Specificity, Drug Resistance, Multiple, Sampling Studies, Tuberculosis, Multidrug-Resistant, Humans

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    89
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
89
Top 10%
Top 1%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!