SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission

Abstract

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.

Comparative genomics of drug-resistant strains of Mycobacterium tuberculosis in Ecuador

“…In our results, web-based tools enabled an effective and user-friendly identification of resistanceassociated mutations in M. tuberculosis. The recently developed SAM-TB platform [21] is the most capable of determining the mutations present in the isolates of our study, which, when used in conjunction with web-based tools Mykrobe and PhyReSse, would allow rapid screening of M tuberculosis isolates. These tools could easily be implemented in surveillance programs based on microbiological procedures to obtain results efficiently and cheaply [84,87,88].…”

“…Although these methods are rapid and straightforward, Mtb continuously evolves through the genomic acquisition of single nucleotide polymorphisms (SNPs), insertions, and deletions (indels), impacting the ability to discriminate strains without the classic regions used for resistance detection [ 20 ]. Whole-genome sequencing (WGS), as a molecular diagnostic tool, has been greatly developed in TB research and is clinically useful for predicting drug resistance, lineage, tracing transmission, and defining outbreaks [ 21 – 26 ]. Furthermore, WGS has the potential to determine drug resistance much faster than traditional phenotypic drug susceptibility testing (DST) [ 27 ] and does not require biological safety infrastructure [ 28 , 29 ].…”

Genomic analysis ofMycobacterium brumaesustains its nonpathogenic and immunogenic phenotype

“…However, the low cell wall permeability of mycobacteria and the different efflux pump systems or porin channels, could also play a crucial role in intrinsic drug resistance in NTMs such as M. fortuitum or M. smegmatis (van Ingen et al, 2012; Bakuła et al, 2018) and could explain the intrinsic resistance to isoniazid found in M. brumae . Finally, similar to isolates of M. fortuitum and M. avium complex (Cheng et al, 2017), M. brumae is also resistant to p-aminosalicylic acid, although the mutations responsible for resistance have not been specifically identified (Yang et al, 2022). Thus, due to the differences in drug resistance genetic determinants among Mycobacterium species, additional efforts are needed to determine drug susceptibility by molecular approaches in NTM as M. brumae .…”

Whole-Genome Sequencing for Resistance Level Prediction in Multidrug-Resistant Tuberculosis

“…The MDR-TB strains were recultured and sequenced as previously described ( 20 ). The raw data were uploaded to the Mycobacterium tuberculosis WGS data analysis platform (SAM-TB) ( 21 ) for quality control, detection of known resistance-associated mutations, lineage identification, pairwise single-nucleotide polymorphism (SNP) distance calculation, and construction of phylogenetic trees. For molecular DST, SAM-TB integrates drug-resistance mutation sets from the CRyPTIC Consortium/100,000 Genomes Project and the TB-Profiler tool ( 22 , 23 ).…”