The whole-genome sequencing in predicting Mycobacterium tuberculosis drug susceptibility and resistance in Papua, Indonesia.

BACKGROUND: Tuberculosis is one of the deadliest disease caused by Mycobacterium tuberculosis. Its treatment still becomes a burden for many countries including Indonesia. Drug resistance is one of the problems in TB treatment. However, a development in the molecular field through Whole-genome sequencing (WGS) can be used as a solution in detecting mutations associated with TB- drugs. This investigation intended to implement this data for supporting the scientific community in deeply understanding any TB epidemiology and evolution in Papua along with detecting any mutations in genes associated with TB-Drugs. RESULT: A whole-genome sequencing was performed on the random samples from TB Referral Laboratory in Papua utilizing MiSeq 600 cycle Reagent Kit (V3). Furthermore, TBProfiler was used for genome analysis, RAST Server was employed for annotation, while Gview server was applied for BLAST genome mapping and a Microscope server was implemented for Regions of Genomic Plasticity (RGP). The largest genome of M. tuberculosis obtained was at the size of 4,396,040 bp with subsystems number at 309 and the number of coding sequences at 4326. One sample (TB751) contained one RGP. The drug resistance analysis revealed that several mutations associated with TB-drug resistance existed. In details, mutations of rpoB gene which were identified as S450L, D435Y, H445Y, L430P, and Q432K had caused the reduced effectiveness of rifampicin; while the mutases in katG (S315T), kasA (312S), inhA (I21V), and Rv1482c-fabG1 (C-15 T) genes had contributed to the resistance in isoniazid. In streptomycin, the resistance was triggered by the mutations in rpsL (K43R) and rrs (A514C, A514T) genes, and, in Amikacin, its resistance was led by mutations in rrs (A514C) gene. Additionally, in Ethambutol and Pyrazinamide, their reduced effectiveness was provoked by embB gene mutases (M306L, M306V, D1024N) and pncA (W119R). CONCLUSIONS: The results from whole-genome sequencing of TB clinical sample in Papua, Indonesia could contribute to the surveillance of TB-drug resistance. In the drug resistance profile, there were 15 Multi Drugs Resistance (MDR) samples. However, Extensively Drug-resistant (XDR) samples have not been found, but samples were resistant to only Amikacin, a second-line drug.

Validation study of HLA-B*13:01 as a biomarker of dapsone hypersensitivity syndrome in leprosy patients in Indonesia.

Leprosy is a stigmatizing, chronic infection which degenerates the nervous system and often leads to incapacitation. Multi-drug therapy which consists of dapsone, rifampicin and clofazimine has been effective to combat this disease. In Indonesia, especially in Papua Island, leprosy is still a problem. Furthermore, there had been higher reports of Dapsone Hypersensitivity Syndrome (DHS) which also challenges leprosy elimination in certain aspects. Globally, DHS has a prevalence rate of 1.4% and a fatality rate up to 13%. The aim of this study is to validate HLA-B*13:01, a previously discovered biomarker for DHS in the Chinese population, as a biomarker for DHS in the Papua population.This is a case-control study of 34 leprosy patients who presented themselves with DHS (case subjects) and 52 leprosy patients without DHS (control subjects). Patients were recruited from 2 provinces: Papua and West Papua. DNA was extracted from 3 ml blood specimens. HLA-B alleles were typed using the gold-standard sequence based typing method. Results were then analysed using logistic regression and risk assessment was carried out. The results of HLA-typing showed that HLA-B*13:01 was the most significant allele associated with DHS, with odds ratio = 233.64 and P-value = 7.11×10-9, confirming the strong association of HLA-B*13:01 to DHS in the Papua population. The sensitivity of this biomarker is 91.2% and specificity is 96.2%, with an area under the curve of 0.95. HLA-B*13:01 is validated as a biomarker for DHS in leprosy patients in Papua, Indonesia, and can potentially be a good predictor of DHS to help prevent this condition in the future.