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Advanced immune suppression is associated with increased prevalence of mixed-strain Mycobacterium tuberculosis infections among persons at high risk for drug-resistant tuberculosis in Botswana.

ABSTRACT: We examined factors associated with mixed-strain Mycobacterium tuberculosis infections among patients at high risk for drug-resistant tuberculosis in Botswana. Thirty-seven (10.0%) of 370 patients with tuberculosis had mixed M. tuberculosis infections, based on 24-locus mycobacterial interspersed repetitive unit-variable number of tandem repeats genotyping. In log-binomial regression analysis, age <37 years (adjusted prevalence ratio [PR], 1.92; 95% confidence interval [CI], 1.01-3.57) and prior tuberculosis treatment (adjusted PR, 2.31; 95% CI, 1.09-4.89) were associated with mixed M. tuberculosis infections. Among human immunodeficiency virus-infected patients, prior tuberculosis treatment (adjusted PR, 2.11; 95% CI, 1.04-4.31) and CD4(+) T-cell count of <100 cells/?l (adjusted PR, 10.18; 95% CI, 2.48-41.71) were associated with mixed M. tuberculosis infections. Clinical suspicion of mixed M. tuberculosis infections should be high for patients with advanced immunosuppression and a prior history of tuberculosis treatment.

SUBMITTER: Shin SS

PROVIDER: S-EPMC4351373 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Advanced immune suppression is associated with increased prevalence of mixed-strain Mycobacterium tuberculosis infections among persons at high risk for drug-resistant tuberculosis in Botswana.

Shin Sanghyuk S SS Modongo Chawangwa C Ncube Ronald R Sepako Enoch E Klausner Jeffrey D JD Zetola Nicola M NM

The Journal of infectious diseases 20140728 3

We examined factors associated with mixed-strain Mycobacterium tuberculosis infections among patients at high risk for drug-resistant tuberculosis in Botswana. Thirty-seven (10.0%) of 370 patients with tuberculosis had mixed M. tuberculosis infections, based on 24-locus mycobacterial interspersed repetitive unit-variable number of tandem repeats genotyping. In log-binomial regression analysis, age <37 years (adjusted prevalence ratio [PR], 1.92; 95% confidence interval [CI], 1.01-3.57) and prior ...[more]

PMID: 25070941

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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

Advanced immune suppression is associated with increased prevalence of mixed-strain Mycobacterium tuberculosis infections among persons at high risk for drug-resistant tuberculosis in Botswana.

Publications

Advanced immune suppression is associated with increased prevalence of mixed-strain Mycobacterium tuberculosis infections among persons at high risk for drug-resistant tuberculosis in Botswana.

Similar Datasets

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