Dataset Information

A model-based Bayesian estimation of the rate of evolution of VNTR loci in Mycobacterium tuberculosis.

ABSTRACT: Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around 10?? to 10?² per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is 10?²·?? (95% CI: 10?²·?¹,10?¹·??)and under the linear model, the mean mutation rate per locus per repeat unit is 10?²·?? (95% CI: 10?³·??,10?¹·??). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future.

SUBMITTER: Aandahl RZ

PROVIDER: S-EPMC3386166 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A model-based Bayesian estimation of the rate of evolution of VNTR loci in Mycobacterium tuberculosis.

Aandahl R Zachariah RZ Reyes Josephine F JF Sisson Scott A SA Tanaka Mark M MM

PLoS computational biology 20120628 6

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around 10⁻⁵ to 10⁻² per locus per year. Resolving this issue using more detailed models and statistical methods would lead t ...[more]

PMID: 22761563

Similar Datasets

Project description:Background:Tuberculosis (TB) resulted in an estimated 1.7 million deaths in the year 2016. The disease is caused by the members of Mycobacterium tuberculosis complex, which includes Mycobacterium tuberculosis, Mycobacterium bovis and other closely related TB causing organisms. In order to understand the epidemiological dynamics of TB, national TB control programs often conduct standardized genotyping at 24 Mycobacterial-Interspersed-Repetitive-Units (MIRU)-Variable-Number-of-Tandem-Repeats (VNTR) loci. With the advent of next generation sequencing technology, whole-genome sequencing (WGS) has been widely used for studying TB transmission. However, an open-source software that can connect WGS and MIRU-VNTR typing is currently unavailable, which hinders interlaboratory communication. In this manuscript, we introduce the MIRU-profiler program which could be used for prediction of MIRU-VNTR profile from WGS of M. tuberculosis. Implementation:The MIRU-profiler is implemented in shell scripting language and depends on EMBOSS software. The in-silico workflow of MIRU-profiler is similar to those described in the laboratory manuals for genotyping M. tuberculosis. Given an input genome sequence, the MIRU-profiler computes alleles at the standard 24-loci based on in-silico PCR amplicon lengths. The final output is a tab-delimited text file detailing the 24-loci MIRU-VNTR pattern of the input sequence. Validation:The MIRU-profiler was validated on four datasets: complete genomes from NCBI-GenBank (n = 11), complete genomes for locally isolated strains sequenced using PacBio (n = 4), complete genomes for BCG vaccine strains (n = 2) and draft genomes based on 250 bp paired-end Illumina reads (n = 106). Results:The digital MIRU-VNTR results were identical to the experimental genotyping results for complete genomes of locally isolated strains, BCG vaccine strains and five out of 11 genomes from the NCBI-GenBank. For draft genomes based on short Illumina reads, 21 out of 24 loci were inferred with a high accuracy, while a number of inaccuracies were recorded for three specific loci (ETRA, QUB11b and QUB26). One of the unique features of the MIRU-profiler was its ability to process multiple genomes in a batch. This feature was tested on all complete M. tuberculosis genome (n = 157), for which results were successfully obtained in approximately 14 min. Conclusion:The MIRU-profiler is a rapid tool for inference of digital MIRU-VNTR profile from the assembled genome sequences. The tool can accurately infer repeat numbers at the standard 24 or 21/24 MIRU-VNTR loci from the complete or draft genomes respectively. Thus, the tool is expected to bridge the communication gap between the laboratories using WGS and those using the conventional MIRU-VNTR typing.

Project description:INTRODUCTION:Recurrent tuberculosis (TB) is one of the main challenges in TB control. Genotyping based on Mycobacterial Interspersed Repetitive Units-Variable Tandem Repeats (MIRU-VNTR) has been widely used to differentiate between relapse and reinfection, which are the two main causes of recurrent TB. There is a lack of data regarding the causes of TB recurrence in Georgia, and while differentiating between relapse and reinfection plays a key role in defining appropriate interventions, the required genotyping methodologies have not been implemented. The objective of this study was to implement MIRU-VNTR genotyping at the National Center for Tuberculosis and Lung Diseases (NCTBLD) and differentiate between relapse and reinfection in multidrug resistant (MDR-) TB patients from Tbilisi, Georgia. METHODS:Recurrent MDR tuberculosis cases from 2014-2016 diagnosed at NCTLD were included in the study when bacterial samples from both episodes were available. Genotyping based on the MIRU-VNTR 24 loci was implemented and used for differentiating between relapse and reinfection. Paired samples showing the same MIRU-VNTR pattern or one locus difference were classified as relapse, while two and more loci differences were treated as reinfection. Exact logistic regression was used to identify predictors of recurrence. RESULTS:Thirty two MDR-TB patients (64 samples) were included and MIRU-VNTR 24 typing was performed on the corresponding paired samples. Of the 32 patients, 25 (83.3%) were identified as relapse while 5 (16.7%) were due to re-infection. Patients with a history of incarceration were significantly associated with TB reinfection (p< 0.05). CONCLUSION:Recurrent TB in MDR patients in Georgia are mainly caused by relapse, raising concerns on the efficacy of the TB control program. An association between incarceration and reinfection likely reflects high levels of ongoing TB transmission in prisons, indicating the need for better TB infection control measures in these settings. Our results add to the rationale for implementing genotypic surveillance of TB more broadly to support TB control in Georgia.

Dataset Information

A model-based Bayesian estimation of the rate of evolution of VNTR loci in Mycobacterium tuberculosis.

Publications

A model-based Bayesian estimation of the rate of evolution of VNTR loci in Mycobacterium tuberculosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets