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Title: The Within-Host Population Dynamics Of Mycobacterium Tuberculosis Vary With Treatment Efficacy.      
dateReleased:
03-16-2017
privacy:
information not avaiable
aggregation:
instance of dataset
dateCreated:
03-02-2017
refinement:
raw
ID:
doi:10.5281/ZENODO.322377
creators:
Trauner, Andrej
Liu, Qingyun
Via, Laura E.
Liu, Xin
Ruan, Xianglin
Liang, Lili
She, Huimin
Chen, Ying
Wang, Ziling
Liang, Ruixia
Zhang, Wei
Wei, Wang
Gao, Jingcai
Sun, Gang
Brites, Daniela
England, Kathleen
Zhang, Guolong
Gagneux, Sebastien
Barry, Clifton E.
Gao, Qian
availability:
available
types:
other
description:
Data used for the publication of a paper entitled: The within-host population dynamics of Mycobacterium tuberculosis vary with treatment efficacy. The data were derived from: 1. the deep sequencing of serial sputum samples from 12 TB patients, 2. the deep sequencing of liquid cultures derived from the expansion of individual colonies in vitro, 3. In silico simulations of DNA sequencing, populations and mutagenesis. The analytical scripts associated with the generation of the data can be found at: https://github.com/swisstph/TBRU_serialTB/ Paper Abstract: Background: Combination therapy is one of the most effective tools for limiting the emergence of drug resistance. Despite the widespread adoption of combination therapy across diseases, drug resistance rates continue to rise, leading to failing treatment regimens. The mechanisms underlying treatment failure are well studied, but the processes governing successful combination therapy are poorly understood. We addressed this question by studying the population dynamics of Mycobacterium tuberculosis within tuberculosis patients undergoing treatment with different combinations of antibiotics. Results: By combining very deep whole genome sequencing (~1,000-fold genome-wide coverage) with sequential sputum sampling, we were able to detect transient genetic diversity driven by the apparently continuous turnover of minor alleles, which could serve as the source of drug-resistant bacteria. However, we report that treatment efficacy had a clear impact on the population dynamics: sufficient drug pressure bore a clear signature of purifying selection leading to apparent genetic stability. In contrast, M. tuberculosis populations subject to less drug pressure showed markedly different dynamics, including cases of acquisition of additional drug resistance. Conclusions: Our findings show that for a pathogen like M. tuberculosis, which is well adapted to the human host, purifying selection constrains the evolutionary trajectory to resistance in effectively treated individuals. Nonetheless, we also report a continuous turnover of minor variants, which could give rise to the emergence of drug resistance in cases of drug pressure weakening. Monitoring bacterial population dynamics could therefore provide an informative metric for assessing the efficacy of novel drug combinations.
accessURL: https://doi.org/10.5281/ZENODO.322377
storedIn:
Zenodo
qualifier:
not compressed
format:
HTML
accessType:
landing page
authentication:
none
authorization:
none
abbreviation:
ZENODO
homePage: https://zenodo.org/
ID:
SCR:004129
name:
ZENODO

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