Distribution of Common and Rare Genetic Markers of Second-Line-Injectable-Drug Resistance in Mycobacterium tuberculosis Revealed by a Genome-Wide Association Study

Drug-resistant Mycobacterium tuberculosis among Nepalese patients at a tuberculosis referral center

BACKGROUND

Multidrug-resistant tuberculosis (MDR-TB), characterized by isoniazid and rifampicin resistance, is caused by chromosomal mutations that restrict treatment options and complicate tuberculosis management. This study sought to investigate the prevalence of pre-extensively drug-resistant (pre-XDR) and extensively drug-resistant (XDR) tuberculosis, as well as mutation pattern, in Nepalese patients with MDR/rifampicin-resistant (RR)-TB strains.

METHODS

A cross-sectional study was conducted on MDR/RR-TB patients at the German Nepal Tuberculosis Project from June 2017 to June 2018. The MTBDRsl line probe assay identified pre-XDR-TB and XDR-TB. Pre-XDR-TB included MDR/RR-TB with resistance to any fluoroquinolone (FLQ), while XDR-TB included MDR/RR-TB with resistance to any FLQ and at least one additional group A drug. Mutation status was determined by comparing bands on reaction zones [gyrA and gyrB for FLQ resistance, rrs for SILD resistance, and eis for low-level kanamycin resistance, according to the GenoType MTBDRsl VER 2.0, Hain Lifescience GmbH, Nehren, Germany definition of pre-XDR and XDR] to the evaluation sheet. SPSS version 17.0 was used for data analysis.

RESULTS

Out of a total of 171 patients with MDR/RR-TB, 160 had (93.57%) had MTBC, of whom 57 (35.63%) had pre-XDR-TB and 10 (6.25%) had XDR-TB. Among the pre-XDR-TB strains, 56 (98.25%) were FLQ resistant, while 1 (1.75%) was SLID resistant. The most frequent mutations were found at codons MUT3C (57.14%, 32/56) and MUT1 (23.21%, 13/56) of the gyrA gene. One patient had SLID resistant genotype at the MUT1 codon of the rrs gene (100%, 1/1). XDR-TB mutation bands were mostly detected on MUT1 (30%, 3/10) of the gyrA and rrs, MUT3C (30%, 3/10) of the gyrA, and MUT1 (30%, 3/10) of the rrs.

CONCLUSIONS

Pre-XDR-TB had a significantly higher likelihood than XDR-TB, with different specific mutation bands present in gyrA and rrs genes.

Whole-genome sequencing of clinical isolates from tuberculosis patients in India: real-world data indicates a high proportion of pre-XDR cases

Treatment decisions for tuberculosis (TB) in the absence of full drug-susceptibility data can result in amplifying resistance and may compromise treatment outcomes. Genomics of Mycobacterium tuberculosis (M.tb) from clinical samples enables detection of drug resistance to multiple drugs. We performed whole-genome sequencing (WGS) for 600 clinical samples from patients with tuberculosis to identify the drug-resistance profile and mutation spectrum. We documented the reasons reported by clinicians for referral. WGS identified a high proportion (51%) of pre-extensively drug-resistant (pre-XDR) cases followed by multidrug-resistant tuberculosis (MDR-TB) (15.5%). This correlates with the primary reason for referral, as non-response to the first-line treatment (67%) and treatment failure or rifampicin resistance (14%). Multivariate analysis indicated that all young age groups (P < 0.05), male gender (P < 0.05), and Beijing strain (P < 0.01) were significant independent predictors of MDR-TB or MDR-TB+ [pre-extensively drug-resistant tuberculosis (XDR-TB) and XDR-TB]. Ser315Thr (72.5%) in the inhA gene and Ser450Leu in the rpoB gene (65.5%) were the most prevalent mutations, as were resistance-conferring mutations to pyrazinamide (41%) and streptomycin (61.33%). Mutations outside the rifampicin resistance-determining region (RRDR), Ile491Phe and Val170Phe, were seen in 1.3% of cases; disputed mutations in rpoB (Asp435Tyr, His445Asn, His445Leu, and Leu430Pro) were seen in 6% of cases, and mutations to newer drugs such as bedaquiline and linezolid in 1.0% and 7.5% of cases, respectively. This study on clinical samples highlights that there is a high proportion of pre-XDR cases and emerging resistance to newer drugs; ongoing transmission of these strains can cause serious threat to public health; and whole-genome sequencing can effectively identify and support precision medicine for TB.

IMPORTANCE

The current study is based on real-world data on the TB drug-resistance profile by whole-genome sequencing of 600 clinical samples from patients with TB in India. This study indicates the clinicians' reasons for sending samples for WGS, which is for difficult-to-treat cases and/or relapse and treatment failure. The study reports a significant proportion of cases with pre-XDR-TB strains that warrant policy makers' attention. It reflects the current iterative nature of the diagnostic tests under programmatic conditions that leads to delays in appropriate diagnosis and empirical treatment. India had an estimated burden of 2.95 million TB cases in 2020 and 135,000 multidrug-resistant cases. However, WGS profiles of M.tb from India remains disproportionately poorly represented. This study adds a significant body of data on the mutation profiles seen in M.tb isolated from patients with TB in India, mutations outside the RRDR, disputed mutations, and resistance-conferring mutations to newer drugs such as bedaquiline and linezolid.

Comparison of the MeltPro TB assay and whole-genome sequencing assay for rapid molecular diagnosis of drug resistant tuberculosis in guangdong province

BACKGROUND

Rifampicin (RIF) and multidrug-resistant tuberculosis (TB) are major public health threats. As conventional phenotypic drug susceptibility testing requires two-eight weeks, molecular diagnostic assays are widely used to determine drug resistance.

METHODS

Clinical Mycobacterium tuberculosis isolates with consistent drug susceptibility results, tested using microbroth dilution and proportion methods in Löwenstein-Jensen medium from patients with TB in Guangdong province were utilized to evaluate MeltPro TB and whole-genome sequencing (WGS) assays in detecting resistance to RIF, isoniazid (INH), ethambutol (EMB), fluoroquinolones (FQ), and streptomycin (SM). Solid phenotypic drug susceptibility testing was used as the gold standard to evaluate the detection capacity of MeltPro TB on clinical sputum samples of patients with TB.

RESULTS

Similar to WGS, MeltPro TB successfully detected RIF, INH, and SM resistance with sensitivities of 86.3, 84.8, and 86.6 %, respectively. However, the resistant isolate detection rates were only 58.1 and 69.6 % for EMB and FQ-resistant strains. For clinical specimens, MeltPro TB still showed good detectable rates of RIF and INH resistance, with sensitivities of 82.4 % and 95.2 %, respectively. Detectable rates of FQ and EMB resistance were low: 77.8 % and 35.3 %, respectively.

CONCLUSIONS

MeltPro TB can detect known DNA mutations associated with drug resistance in Mycobacterium tuberculosis strains with comparable efficacy to WGS. For FQ and EMB resistance testing, MeltPro TB requires optimization and is unsuitable for general use. MeltPro TB can be used for diagnosis of RIF and multidrug-resistant tuberculosis to rapidly initiate appropriate anti-TB drug therapy.

Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review

Antibiotic resistance is a significant threat to public health worldwide. Genome-wide association studies (GWAS) have emerged as a powerful tool to identify genetic variants associated with this antibiotic resistance. By analyzing large datasets of bacterial genomes, GWAS can provide valuable insights into the resistance mechanisms and facilitate the discovery of new drug targets. The present study aimed to undertake a systematic review of different GWAS approaches used for detecting genetic variants associated with antibiotic resistance. We comprehensively searched the PubMed and Scopus databases to identify relevant studies published from 2013 to February 2023. A total of 40 studies met our inclusion criteria. These studies explored a wide range of bacterial species, antibiotics, and study designs. Notably, most of the studies were centered around human pathogens such as Mycobacterium tuberculosis, Escherichia coli, Neisseria gonorrhoeae, and Staphylococcus aureus. The review seeks to explore the several GWAS approaches utilized to investigate the genetic mechanisms associated with antibiotic resistance. Furthermore, it examines the contributions of GWAS approaches in identifying resistance-associated genetic variants through binary and continuous phenotypes. Overall, GWAS holds great potential to enhance our understanding of bacterial resistance and improve strategies to combat infectious diseases.