Background: Tuberculosis (TB) is still a major health problem in Malaysia with thousands of cases reported yearly. This is further burdened with the emergence of multidrug-resistant TB (MDR-TB). Whole-genome sequencing (WGS) provides high-resolution molecular epidemiological data for the accurate determination of Mycobacterium tuberculosis complex (MTBC) lineages and prediction of the drug-resistance patterns. This study aimed to investigate the diversity of MTBC in Malaysia in terms of lineage and drug-resistance patterns of the clinical MTBC isolates using WGS approach.
Methods: The genomes of 24 MTBC isolated from sputum and pus samples were sequenced. The phenotypic drug susceptibility testing (DST) of the isolates was determined for ten anti-TB drugs. Bioinformatic analysis comprising genome assembly and annotation and single-nucleotide polymorphism (SNP) analysis in genes associated with resistance to the ten anti-TB drugs were done on each sequenced genome.
Results: The draft assemblies covered an average of 97% of the expected genome size. Eleven isolates were aligned to the Indo-Oceanic lineage, eight were East-Asian lineage, three were East African-Indian lineage, and one was of Euro-American and Bovis lineages, respectively. Twelve of the 24 MTBC isolates were phenotypically MDR M. tuberculosis: one is polyresistance and another one is monoresistance. Twenty-six SNPs across nine genes associated with resistance toward ten anti-TB drugs were detected where some of the mutations were found in isolates that were previously reported as pan-susceptible using DST. A haplotype consisting of 65 variants was also found among the MTBC isolates with drug-resistance traits.
Conclusions: This study is the first effort done in Malaysia to utilize 24 genomes of the local clinical MTBC isolates. The high-resolution molecular epidemiological data obtained provide valuable insights into the mechanistic and epidemiological qualities of TB within the vicinity of Southeast Asia.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.