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Whole genome sequencing (WGS) can provide insight into drug-resistance, transmission chains and the identification of outbreaks, but data analysis remains an obstacle to its routine clinical use. Although several drug-resistance prediction tools have appeared, until now no website integrates drug-resistance prediction with strain genetic relationships and species identification of nontuberculous mycobacteria (NTM). We have established a free, function-rich, user-friendly online platform for MTB WGS data analysis (SAM-TB, http://samtb.szmbzx.com) that integrates drug-resistance prediction for 17 antituberculosis drugs, detection of variants, analysis of genetic relationships and NTM species identification. The accuracy of SAM-TB in predicting drug-resistance was assessed using 3177 sequenced clinical isolates with results of phenotypic drug-susceptibility tests (pDST). Compared to pDST, the sensitivity of SAM-TB for detecting multidrug-resistant tuberculosis was 93.9% [95% confidence interval (CI) 92.6–95.1%] with specificity of 96.2% (95% CI 95.2–97.1%). SAM-TB also analyzes the genetic relationships between multiple strains by reconstructing phylogenetic trees and calculating pairwise single nucleotide polymorphism (SNP) distances to identify genomic clusters. The incorporated mlstverse software identifies NTM species with an accuracy of 98.2% and Kraken2 software can detect mixed MTB and NTM samples. SAM-TB also has the capacity to share both sequence data and analysis between users. SAM-TB is a multifunctional integrated website that uses WGS raw data to accurately predict antituberculosis drug-resistance profiles, analyze genetic relationships between multiple strains and identify NTM species and mixed samples containing both NTM and MTB. SAM-TB is a useful tool for guiding both treatment and epidemiological investigation. [ABSTRACT FROM AUTHOR]

The development and implementation of rapid molecular diagnostics for tuberculosis (TB) drug-susceptibility testing is critical to inform treatment of patients and to prevent the emergence and spread of resistance. Optimal trial planning for existing tests and those in development will be critical to rapidly gather the evidence necessary to inform World Health Organization review and to support potential policy recommendations. The evidence necessary includes an assessment of the performance for TB and resistance detection as well as an assessment of the operational characteristics of these platforms. The performance assessment should include analytical studies to confirm the limit of detection and assay ability to detect mutations conferring resistance across globally representative strains. The analytical evaluation is typically followed by multisite clinical evaluation studies to confirm diagnostic performance in sites and populations of intended use. This paper summarizes the considerations for the design of these analytical and clinical studies. [ABSTRACT FROM AUTHOR]

Objectives Kanamycin is an important second-line drug used to treat multidrug-resistant (MDR) tuberculosis (TB). Molecular analysis of the rrs gene seems to be not enough to identify every case of kanamycin resistance. In the present study we evaluated the incidence of eis mutations in kanamycin-resistant Mycobacterium tuberculosis isolates. Methods We analysed 70 MDR M. tuberculosis clinical isolates. All isolates were screened for rrs and eis mutations using single-strand conformation polymorphism and sequencing. Phenotypic drug susceptibility testing was performed using Bactec MGIT 960 and the absolute concentration method on Lowenstein–Jensen medium. Results eis mutations were found in 10 isolates. The most prevalent mutations were the A1401G substitution in the rrs gene and the C14T substitution in the eis promoter region. Conclusions Our study shows that the eis promoter region is a useful molecular marker of kanamycin resistance in the Moscow region. Complex analysis of rrs and eis mutations will significantly reduce the time to diagnose kanamycin resistance in TB patients, compared with phenotypic drug resistance testing. [ABSTRACT FROM PUBLISHER]