Molecular identification of non-tuberculous mycobacteria using sodA and ITS 16S-23S rRNA

Background: Several studies have shown that the level of NTM species isolation is increasing worldwide and rapidly becoming a major problem in public health. Therefore, identifying NTM bacteria at the species level is an urgent necessity because the treatment is based on the specific species of NTM as the etiology of the infection. Methods: Thirty-four frozen clinical isolates of suspected NTM were extracted, amplified, and sequenced using superoxide dismutase (sodA) and Internal Transcribed Spacer 16S-23S rRNA (ITS) target genes. The GenBank database was utilized to analyze and identify the sequencing results at the NCBI. Results: Based on sequencing and classification into group/complex categories, amplification using the sodA and ITS gene fragments revealed that the Mycobacterium fortuitum complex was the most prevalent (34.78%), followed by the Mycobacterium abscessus complex (17.39%). Four discrepancies were observed, in addition to five isolates identified as Mycobacterium tuberculosis (MTB) and one isolate that remained unidentified. Conclusion: This study showed that the distribution of NTM species causes lung infection in West Java and was expected to raise awareness of TB-like infection and develop new strategies to establish a better diagnosis and appropriate treatment.

Authors

Institutions

Publication Details

Journal
Indonesia Journal of Biomedical Science
Published
2024-10-25
DOI
https://doi.org/10.15562/ijbs.v18i2.587
Citations
1
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
0.39

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecular identification of non-tuberculous mycobacteria using sodA and ITS 16S-23S rRNA

Mohadese Kamali, Nabilla Ghina Zavitri, Dyshelly Nurkartika Pascapurnama, Muti'ah Nurul Jihadah et al.
1 citations
Indonesia Journal of Biomedical Science
Mycobacterium research and diagnosis
0.39
article

Molecular identification of non-tuberculous mycobacteria using sodA and ITS 16S-23S rRNA

Mohadese Kamali, Nabilla Ghina Zavitri, Dyshelly Nurkartika Pascapurnama, Muti'ah Nurul Jihadah, Ramdan Panigoro, Lidya Chaidir, Yoopie Setiawan
article en
1 citations

Abstract

Background: Several studies have shown that the level of NTM species isolation is increasing worldwide and rapidly becoming a major problem in public health. Therefore, identifying NTM bacteria at the species level is an urgent necessity because the treatment is based on the specific species of NTM as the etiology of the infection. Methods: Thirty-four frozen clinical isolates of suspected NTM were extracted, amplified, and sequenced using superoxide dismutase (sodA) and Internal Transcribed Spacer 16S-23S rRNA (ITS) target genes. The GenBank database was utilized to analyze and identify the sequencing results at the NCBI. Results: Based on sequencing and classification into group/complex categories, amplification using the sodA and ITS gene fragments revealed that the Mycobacterium fortuitum complex was the most prevalent (34.78%), followed by the Mycobacterium abscessus complex (17.39%). Four discrepancies were observed, in addition to five isolates identified as Mycobacterium tuberculosis (MTB) and one isolate that remained unidentified. Conclusion: This study showed that the distribution of NTM species causes lung infection in West Java and was expected to raise awareness of TB-like infection and develop new strategies to establish a better diagnosis and appropriate treatment.

Indonesia Journal of Biomedical ScienceVol. 18(2)
Padjadjaran University (ID)
Universitas Katolik Parahyangan, Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi
Openalex Percentile: Top 30%
Mycobacterium research and diagnosis
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.