Literature DB >> 30172045

Use of whole-genome sequencing to predict Mycobacterium tuberculosis drug resistance in Indonesia.

Lidya Chaidir1, Carolien Ruesen2, Bas E Dutilh3, Ahmad R Ganiem4, Anggriani Andryani5, Lika Apriani6, Martijn A Huynen3, Rovina Ruslami4, Philip C Hill7, Reinout van Crevel2, Bachti Alisjahbana4.   

Abstract

OBJECTIVES: Whole-genome sequencing (WGS) is rarely used for drug resistance testing of Mycobacterium tuberculosis in high-endemic settings. Here we present the first study from Indonesia, which has the third highest tuberculosis (TB) burden worldwide, with <50% of drug-resistant cases currently detected.
METHODS: WGS was applied for strains from 322 human immunodeficiency virus (HIV)-negative adult TB patients. Phenotypic drug susceptibility testing (DST) was performed for a proportion of the patients.
RESULTS: Using WGS, mutations associated with drug resistance to any TB drug were identified in 51 (15.8%) of the 322 patients, including 42 patients (13.0%) with no prior TB treatment (primary resistance). Eight isolates (2.5%) were multidrug-resistant (MDR) and one was extensively drug-resistant (XDR). Most mutations were found in katG (n=18), pncA (n=18), rpoB (n=10), fabG1 (n=9) and embB (n=9). Agreement of WGS-based resistance and phenotypic DST to first-line drugs was high for isoniazid and rifampicin but was lower for ethambutol and streptomycin. Drug resistance was more common in Indo-Oceanic lineage strains (37.5%) compared with Euro-American (18.2%) and East-Asian lineage strains (10.3%) (P=0.044), but combinations of multiple mutations were most common among East-Asian lineage strains (P=0.054).
CONCLUSIONS: These data support the potential use of WGS for more rapid and comprehensive prediction of drug-resistant TB in Indonesia. Future studies should address potential barriers to implementing WGS, the distribution of specific resistance mutations, and the association of particular mutations with endemic M. tuberculosis lineages in Indonesia.
Copyright © 2018 International Society for Chemotherapy of Infection and Cancer. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Drug resistance; Mycobacterium tuberculosis; Resistance mutations; Whole-genome sequencing

Mesh:

Substances:

Year:  2018        PMID: 30172045     DOI: 10.1016/j.jgar.2018.08.018

Source DB:  PubMed          Journal:  J Glob Antimicrob Resist        ISSN: 2213-7165            Impact factor:   4.035


  5 in total

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Authors:  Andre Marolop Pangihutan Siahaan; Steven Tandean; Rr Suzy Indharty; Bahagia Willibrodus Maria Nainggolan; Martin Susanto
Journal:  Int J Surg Case Rep       Date:  2022-09-08

2.  Use of Whole-Genome Sequencing to Predict Mycobacterium tuberculosis Complex Drug Resistance from Early Positive Liquid Cultures.

Authors:  Xiaocui Wu; Guangkun Tan; Wei Sha; Haican Liu; Jinghui Yang; Yinjuan Guo; Xin Shen; Zheyuan Wu; Hongbo Shen; Fangyou Yu
Journal:  Microbiol Spectr       Date:  2022-03-21

3.  Resistance To First-Line Antituberculosis Drugs And Prevalence Of pncA Mutations In Clinical Isolates Of Mycobacterium tuberculosis From Zunyi, Guizhou Province Of China.

Authors:  Zhimin Cao; Yuanbo Lan; Ling Chen; Min Xiang; Zhiyuan Peng; Jianyong Zhang; Hong Zhang
Journal:  Infect Drug Resist       Date:  2019-09-30       Impact factor: 4.003

4.  Evaluation of whole-genome sequence to predict drug resistance of nine anti-tuberculosis drugs and characterize resistance genes in clinical rifampicin-resistant Mycobacterium tuberculosis isolates from Ningbo, China.

Authors:  Yang Che; Yi Lin; Tianchi Yang; Tong Chen; Guoxin Sang; Qin Chen; Tianfeng He
Journal:  Front Public Health       Date:  2022-08-18

5.  Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors.

Authors:  Rydberg Roman Supo-Escalante; Aldhair Médico; Eduardo Gushiken; Gustavo E Olivos-Ramírez; Yaneth Quispe; Fiorella Torres; Melissa Zamudio; Ricardo Antiparra; L Mario Amzel; Robert H Gilman; Patricia Sheen; Mirko Zimic
Journal:  PLoS One       Date:  2020-07-31       Impact factor: 3.240

  5 in total

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