Genomic profiling and drug resistance patterns of Mycobacterium tuberculosis in Indonesia: whole-genome sequencing of isolates from the 2017–2018 national Tuberculosis Drug Resistance Survey
11 affiliations
- 1National Health Biology Laboratory, Ministry of Health
- 2Doctoral Program in Biomedical Sciences, Faculty of Medicine, University of Indonesia
- 3The Health Policy Agency, Ministry of Health
- 4Directorate General of Primary and Community Health, Ministry of Health
- 5National Research and Innovation Agency
- 6Integrated Laboratory, Faculty of Medicine, University of Indonesia
- 7National Tuberculosis Expert Committee of Indonesia
- 8World Health Organization
- 9Vital Strategies
- 10IRCCS San Raffaele Scientific Institute
- 11Vita-Salute San Raffaele University
Abstract
Objective: Drug-resistant tuberculosis remains a major public health challenge in Indonesia. This study aimed to characterize the genetic diversity, lineage distribution, and genotypic resistance profiles of Mycobacterium tuberculosis isolates across the Indonesian archipelago using whole-genome sequencing.
Methods: A cross-sectional study was conducted using 1,281 analyzed MTB isolates derived from the 2017–2018 National Tuberculosis Drug Resistance Survey (DRS TB). Samples were screened via Xpert MTB/RIF and phenotypic drug susceptibility testing using the MGIT 960 system. Genomic DNA was extracted using the CTAB protocol. Whole-genome sequencing (WGS) libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA). Sequencing was performed on an Illumina MiSeq platform using the MiSeq Reagent Kit v3 (600 cycles), generating paired-end reads of 2 × 300 bp. To identify drug resistance-associated mutations and determine strain lineage/sub-lineages, raw sequencing reads were initially processed with Trimmomatic. The filtered reads were subsequently aligned to the Mycobacterium tuberculosis H37Rv reference genome (ATCC 27294;NC_000962.3) using the MTBseq pipeline, which the BWA-MEM algorithm (v0.7.17) for sequence mapping. Variant calling was carried out with Samtools mpileup (v1.6).
Results: Four major MTB lineages were identified: Lineage 4 (43.1%) was dominant, followed by Lineage 2 (30.4%) and Lineage 1 (26.3%), while Lineage 3 was rare, with only 0.16% detected. At the sub-lineage level, L2.2.1 (18.5%), L1.2.1 (11.3%), and L4.1.2.1 (9.7%) were the most prevalent. Resistance to first-line drugs was the most frequent, primarily driven by mutations in the katG p.Ser315Thr (7.5%) and rpoB p.Ser450Leu (5%), conferring isoniazid and rifampicin resistance, respectively. Second-line resistance was highest for Fluoroquinolones (2.03%). Notably, four pre-XDR strains (0.31%) were identified and validated across Java-Bali and Sumatera, all harboring critical gyrA mutations and rpoB mutations (p.Asp435Tyr, p.Asn437Asp, p.Ser450Leu, and p.Ser450Trp).
Conclusion: The study confirms a high prevalence of L2 and L4 in Indonesia. The identification of pre-XDR-TB isolates among the national survey samples highlights an urgent need for expanded molecular surveillance. While newer drugs like Bedaquiline remain effective, the presence of specific gyrA mutations underscores the necessity of integrating WGS into national TB control programs to proactively manage resistance and optimize treatment regimens.
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BibTeX
@article{rukminiati2026genomic,
title = {{Genomic profiling and drug resistance patterns of Mycobacterium tuberculosis in Indonesia: whole-genome sequencing of isolates from the 2017–2018 national Tuberculosis Drug Resistance Survey}},
author = {Yuni Rukminiati and Lamria Pangaribuan and Kindi Adam and Fauzul Muna and Dian Perwitasari and Kristina L. Tobing and Heri Wibowo and Susan Rahayu and Muhammad N. Farid and Maria Regina L. Christian and Jonathan M. M. Marbun and Andrea M. Cabibbe and Arash Ghodousi and Pratiwi P. Sudarmono and Felix Mesak and Dina Bisara Lolong},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1844150},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1844150/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Genomic profiling and drug resistance patterns of Mycobacterium tuberculosis in Indonesia: whole-genome sequencing of isolates from the 2017–2018 national Tuberculosis Drug Resistance Survey
AU - Yuni Rukminiati
AU - Lamria Pangaribuan
AU - Kindi Adam
AU - Fauzul Muna
AU - Dian Perwitasari
AU - Kristina L. Tobing
AU - Heri Wibowo
AU - Susan Rahayu
AU - Muhammad N. Farid
AU - Maria Regina L. Christian
AU - Jonathan M. M. Marbun
AU - Andrea M. Cabibbe
AU - Arash Ghodousi
AU - Pratiwi P. Sudarmono
AU - Felix Mesak
AU - Dina Bisara Lolong
PY - 2026
DA - 2026/10/27
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1844150
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1844150/full
AB - Objective: Drug-resistant tuberculosis remains a major public health challenge in Indonesia. This study aimed to characterize the genetic diversity, lineage distribution, and genotypic resistance profiles of Mycobacterium tuberculosis isolates across the Indonesian archipelago using whole-genome sequencing. Methods: A cross-sectional study was conducted using 1,281 analyzed MTB isolates derived from the 2017–2018 National Tuberculosis Drug Resistance Survey (DRS TB). Samples were screened via Xpert MTB/RIF and phenotypic drug susceptibility testing using the MGIT 960 system. Genomic DNA was extracted using the CTAB protocol. Whole-genome sequencing (WGS) libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA). Sequencing was performed on an Illumina MiSeq platform using the MiSeq Reagent Kit v3 (600 cycles), generating paired-end reads of 2 × 300 bp. To identify drug resistance-associated mutations and determine strain lineage/sub-lineages, raw sequencing reads were initially processed with Trimmomatic. The filtered reads were subsequently aligned to the Mycobacterium tuberculosis H37Rv reference genome (ATCC 27294;NC_000962.3) using the MTBseq pipeline, which the BWA-MEM algorithm (v0.7.17) for sequence mapping. Variant calling was carried out with Samtools mpileup (v1.6). Results: Four major MTB lineages were identified: Lineage 4 (43.1%) was dominant, followed by Lineage 2 (30.4%) and Lineage 1 (26.3%), while Lineage 3 was rare, with only 0.16% detected. At the sub-lineage level, L2.2.1 (18.5%), L1.2.1 (11.3%), and L4.1.2.1 (9.7%) were the most prevalent. Resistance to first-line drugs was the most frequent, primarily driven by mutations in the katG p.Ser315Thr (7.5%) and rpoB p.Ser450Leu (5%), conferring isoniazid and rifampicin resistance, respectively. Second-line resistance was highest for Fluoroquinolones (2.03%). Notably, four pre-XDR strains (0.31%) were identified and validated across Java-Bali and Sumatera, all harboring critical gyrA mutations and rpoB mutations (p.Asp435Tyr, p.Asn437Asp, p.Ser450Leu, and p.Ser450Trp). Conclusion: The study confirms a high prevalence of L2 and L4 in Indonesia. The identification of pre-XDR-TB isolates among the national survey samples highlights an urgent need for expanded molecular surveillance. While newer drugs like Bedaquiline remain effective, the presence of specific gyrA mutations underscores the necessity of integrating WGS into national TB control programs to proactively manage resistance and optimize treatment regimens.
SN - 2296-2565
ER -