# Whole-Genome Sequencing and Phenotypic Drug Susceptibility Testing of Bedaquilin, Delamanid, Pretomanid, and Linezolid in Drug-Resistant Mycobacterium tuberculosis from a Single Institute in South Korea

## TL;DR

This study explores drug resistance in tuberculosis bacteria from South Korea using genetic and drug testing to better understand resistance patterns.

## Contribution

The study identifies discrepancies between genetic and phenotypic resistance in drug-resistant tuberculosis isolates in South Korea.

## Key findings

- Phenotypic testing showed elevated MICs for BDQ, DLM, PMD, and LZD in some isolates.
- No Group 1 or 2 mutations were detected in isolates with elevated MICs for BDQ, PMD, or LZD.
- Discrepancies suggest resistance mechanisms not captured by current WHO mutation catalogs.

## Abstract

Multidrug-resistant tuberculosis is a major global health concern. Newer agents, including bedaquiline (BDQ), delamanid (DLM), pretomanid (PMD), and linezolid (LZD), are essential for treatment; however, the resistance mechanisms of these drugs remain poorly understood in South Korea. This study aimed to investigate correlations between phenotypic and genotypic resistance to these drugs using 49 clinical Mycobacterium tuberculosis isolates collected in South Korea between 2017 and 2022. The minimum inhibitory concentrations were determined using the 7H9 broth microdilution method, and whole-genome sequencing (WGS) results were compared with the May 2024 World Health Organization (WHO) mutation catalogue. Phenotypic drug susceptibility testing (pDST) revealed elevated MICs to BDQ in 12 isolates (24.5%), DLM in nine (18.4%), and PMD and LZD in two each (4.1%). No Group 1 or 2 resistance-associated mutations were detected in BDQ-, PMD-, or LZD-elevated-MIC isolates. A Group 2 mutation (fbiC_LoF) was observed in one DLM-elevated-MIC isolate, whereas fbiC_p.Ala855fs (WHO Group 2) mutations occurred in four susceptible isolates. These findings suggest resistance mechanisms beyond the current WHO catalog. Discrepancies between pDST and WGS highlight the need for integrated diagnostics and reinforce the importance of ongoing surveillance and refinement of mutation classification systems to improve genotypic resistance prediction.