Dataset Information

Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection.

ABSTRACT: High resolution tests for genetic variation reveal that individuals may simultaneously host more than one distinct strain of Mycobacterium tuberculosis. Previous studies find that this phenomenon, which we will refer to as "mixed infection", may affect the outcomes of treatment for infected individuals and may influence the impact of population-level interventions against tuberculosis. In areas where the incidence of TB is high, mixed infections have been found in nearly 20% of patients; these studies may underestimate the actual prevalence of mixed infection given that tests may not be sufficiently sensitive for detecting minority strains. Specific reasons for failing to detect mixed infections would include low initial numbers of minority strain cells in sputum, stochastic growth in culture and the physical division of initial samples into parts (typically only one of which is genotyped). In this paper, we develop a mathematical framework that models the study designs aimed to detect mixed infections. Using both a deterministic and a stochastic approach, we obtain posterior estimates of the prevalence of mixed infection. We find that the posterior estimate of the prevalence of mixed infection may be substantially higher than the fraction of cases in which it is detected. We characterize this bias in terms of the sensitivity of the genotyping method and the relative growth rates and initial population sizes of the different strains collected in sputum.

SUBMITTER: Plazzotta G

PROVIDER: S-EPMC7011203 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection.

Plazzotta Giacomo G Cohen Ted T Colijn Caroline C

Journal of theoretical biology 20141229

High resolution tests for genetic variation reveal that individuals may simultaneously host more than one distinct strain of Mycobacterium tuberculosis. Previous studies find that this phenomenon, which we will refer to as "mixed infection", may affect the outcomes of treatment for infected individuals and may influence the impact of population-level interventions against tuberculosis. In areas where the incidence of TB is high, mixed infections have been found in nearly 20% of patients; these s ...[more]

PMID: 25553967

Similar Datasets

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.

Dataset Information

Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection.

Publications

Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure