Pulmonary tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB). Whole-genome sequencing (WGS) holds great promise as an advanced technology for accurately predicting anti-TB drug resistance. The development of a reliable method for detecting drug resistance is crucial in order to standardize anti-TB treatments, enhance patient prognosis, and effectively reduce the risk of transmission. In this study, our primary objective was to explore and determine the potential of WGS for assessing drug resistance based on genetic variants recommended by the World Health Organization (WHO). A total of 1105 MTB strains were selected from samples collected from 2014–2018 in Zhejiang Province, China. Phenotypic drug sensitivity tests (DST) of the anti-TB drugs were conducted for isoniazid (INH), rifampicin (RFP), streptomycin, ethambutol, fluoroquinolones (levofloxacin and moxifloxacin), amikacin, kanamycin, and capreomycin, and the drug-resistance rates were calculated. The clean WGS data of the 1105 strains were acquired and analyzed. The predictive performance of WGS was evaluated by the comparison between genotypic and phenotypic DST results. For all anti-TB drugs, WGS achieved good specificity values (>90%). The sensitivity values for INH and RFP were 91.78% and 82.26%, respectively; however, they were ≤60% for other drugs. The positive predictive values for anti-TB drugs were >80%, except for ethambutol and moxifloxacin, and the negative predictive values were >90% for all drugs. In light of the findings from our study, we draw the conclusion that WGS is a valuable tool for identifying genome-wide variants. Leveraging the genetic variants recommended by the WHO, WGS proves to be effective in detecting resistance to RFP and INH, enabling the identification of multi-drug resistant TB patients. However, it is evident that the genetic variants recommended for predicting resistance to other anti-TB drugs require further optimization and improvement.

The global spread of rifampicin-resistant tuberculosis (RR-TB) presents a significant challenge to tuberculosis control, with compensatory mutations hypothesized to offset the fitness cost of drug resistance, thereby facilitating transmission. However, the characteristics and epidemiological impact of these mutations in coastal regions of Eastern China remain inadequately understood. This study aimed to characterize the spectrum of compensatory mutations in RR-TB isolates and to assess their association with transmission dynamics in a well-developed coastal region of Eastern China. We collected RR-TB cases identified through drug-resistance surveillance in Ningbo, China, from 2021 to 2024. Whole-genome sequencing (WGS) was performed on 180 RR-TB isolates to identify resistance-conferring and compensatory mutations, particularly in the rpoA, rpoB, and rpoC genes. Transmission clusters were inferred using single nucleotide polymorphism (SNP) analysis, and the association between compensatory mutations and the risk of RR-TB clustering was evaluated using logistic regression. Among the 180 RR-TB isolates analyzed, 28.9% harbored putative compensatory mutations, predominantly in rpoC. Isolates with compensatory mutations were significantly more likely to be part of genomic transmission clusters than those without such mutations (odds ratio: 4.28, 95% CI: 2.07–8.85). No significant differences in demographic or clinical characteristics were observed between clustered and non-clustered cases. Phylogenetic analysis indicated ongoing local transmission of compensated RR-TB strains. Compensatory mutations are prevalent among RR-TB strains in coastal Eastern China and are strongly associated with increased transmission, underscoring their role in sustaining the RR-TB epidemic in this region. Enhanced molecular surveillance and targeted interventions are warranted to curb the spread of compensated RR-TB.

Background. The Mycobacterium tuberculosis H37Rv reference genome (Lineage 4), sequenced in 1998, may be incomplete and inaccurate due to earlier technology. Moreover, its use is problematic in regions like East Asia where the dominant Beijing lineage (Lineage 2) is prevalent, as it may introduce biases due to lineage-specific genetic differences. Methods. We performed hybrid sequencing to generate high-quality assemblies of a clinically isolated Beijing family strain (A2018772) and a Chinese laboratory-adapted H37Rv strain (H37Rv_CN). Comparative genomic analysis was conducted against the standard H37Rv reference. The impact of reference genome choice on transmission clustering was evaluated using a dataset of 3,359 M. tuberculosis Lineage 2 strains from China. Results. Comprehensive genomic analysis revealed substantial differences between both studied strains and H37Rv_ref. The Chinese laboratory-adapted H37Rv_CN strain differed by 145 SNPs, 49 InDels and 14 structural variants from the reference genome. The Beijing family clinical isolated strain A2018772 showed even greater divergence with 2,277 SNPs, 373 InDels and 219 structural variants compared to H37Rv_ref, with particular enrichment in PE/PPE genes and metabolic pathways. Among these variations, a 9.2 kb deletion was prevalent in 89.7% of 78 publicly available Lineage 2 genomes. When applied to transmission analysis of 3,359 Chinese Lineage 2 strains, the A2018772 as a reference genome demonstrated superior performance with higher mapping rates (99.52% vs. 98.72%) and coverage (99.73% vs. 98.50%) compared to H37Rv_ref. This improved resolution resulted in fewer transmission clusters (273 vs. 285) at the 5-SNP threshold, indicating that H37Rv_ref consistently overestimates transmission events in Lineage 2-dominated populations. Conclusion. Our study demonstrates the incompleteness of the H37Rv reference genome and also finds that using a lineage-specific reference genome could significantly improve transmission inference accuracy for Lineage 2 strains, highlighting the need for region-specific genomic references to enhance tuberculosis control strategies in high-burden areas.