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Mixed-strain mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control.

ABSTRACT: Numerous studies have reported that individuals can simultaneously harbor multiple distinct strains of Mycobacterium tuberculosis. To date, there has been limited discussion of the consequences for the individual or the epidemiological importance of mixed infections. Here, we review studies that documented mixed infections, highlight challenges associated with the detection of mixed infections, and discuss possible implications of mixed infections for the diagnosis and treatment of patients and for the community impact of tuberculosis control strategies. We conclude by highlighting questions that should be resolved in order to improve our understanding of the importance of mixed-strain M. tuberculosis infections.

SUBMITTER: Cohen T

PROVIDER: S-EPMC3485752 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Mixed-strain mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control.

Cohen Ted T van Helden Paul D PD Wilson Douglas D Colijn Caroline C McLaughlin Megan M MM Abubakar Ibrahim I Warren Robin M RM

Clinical microbiology reviews 20121001 4

Numerous studies have reported that individuals can simultaneously harbor multiple distinct strains of Mycobacterium tuberculosis. To date, there has been limited discussion of the consequences for the individual or the epidemiological importance of mixed infections. Here, we review studies that documented mixed infections, highlight challenges associated with the detection of mixed infections, and discuss possible implications of mixed infections for the diagnosis and treatment of patients and ...[more]

PMID: 23034327

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Project description:BACKGROUND: Molecular genotyping methods have shown infection with more than one Mycobacterium tuberculosis strain genotype in a single sputum culture, indicating mixed infection. AIM: This study aimed to develop a PCR-based genotyping tool to determine the population structure of M. tuberculosis strain genotypes in primary Mycobacterial Growth Indicator Tubes (MGIT) and Löwenstein-Jensen (LJ) cultures to identify mixed infections and to establish whether the growth media influenced the recovery of certain strain genotypes. METHOD: A convenience sample of 206 paired MGIT and LJ M. tuberculosis cultures from pulmonary tuberculosis patients resident in Khayelitsha, South Africa were genotyped using an in-house PCR-based method to detect defined M. tuberculosis strain genotypes. RESULTS: The sensitivity and specificity of the PCR-based method for detecting Beijing, Haarlem, S-family, and LAM genotypes was 100%, and 75% and 50% for detecting the Low Copy Clade, respectively. Thirty-one (15%) of the 206 cases showed the presence of more than one M. tuberculosis strain genotype. Strains of the Beijing and Haarlem genotypes were significantly more associated with a mixed infection (on both media) when compared to infections with a single strain (Beijing MGIT p = 0.02; LJ, p<0.01) and (Haarlem: MGIT p<0.01; LJ, p = 0.01). Strains with the Beijing genotype were less likely to be with "other genotype" strains (p<0.01) while LAM, Haarlem, S-family and LCC occurred independently with the Beijing genotype. CONCLUSION: The PCR-based method was able to identify mixed infection in at least 15% of the cases. LJ media was more sensitive in detecting mixed infections than MGIT media, implying that the growth characteristics of M. tuberculosis on different media may influence our ability to detect mixed infections. The Beijing and Haarlem genotypes were more likely to occur in a mixed infection than any of the other genotypes tested suggesting pathogen-pathogen compatibility.

Project description:BACKGROUND:Mixed infections of Mycobacterium tuberculosis and antibiotic heteroresistance continue to complicate tuberculosis (TB) diagnosis and treatment. Detection of mixed infections has been limited to molecular genotyping techniques, which lack the sensitivity and resolution to accurately estimate the multiplicity of TB infections. In contrast, whole genome sequencing offers sensitive views of the genetic differences between strains of M. tuberculosis within a sample. Although metagenomic tools exist to classify strains in a metagenomic sample, most tools have been developed for more divergent species, and therefore cannot provide the sensitivity required to disentangle strains within closely related bacterial species such as M. tuberculosis. Here we present QuantTB, a method to identify and quantify individual M. tuberculosis strains in whole genome sequencing data. QuantTB uses SNP markers to determine the combination of strains that best explain the allelic variation observed in a sample. QuantTB outputs a list of identified strains, their corresponding relative abundances, and a list of drugs for which resistance-conferring mutations (or heteroresistance) have been predicted within the sample. RESULTS:We show that QuantTB has a high degree of resolution and is capable of differentiating communities differing by less than 25 SNPs and identifying strains down to 1× coverage. Using simulated data, we found QuantTB outperformed other metagenomic strain identification tools at detecting strains and quantifying strain multiplicity. In a real-world scenario, using a dataset of 50 paired clinical isolates from a study of patients with either reinfections or relapses, we found that QuantTB could detect mixed infections and reinfections at rates concordant with a manually curated approach. CONCLUSION:QuantTB can determine infection multiplicity, identify hetero-resistance patterns, enable differentiation between relapse and re-infection, and clarify transmission events across seemingly unrelated patients - even in low-coverage (1×) samples. QuantTB outperforms existing tools and promises to serve as a valuable resource for both clinicians and researchers working with clinical TB samples.

Dataset Information

Mixed-strain mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control.

Publications

Mixed-strain mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control.

Similar Datasets

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