TGS-TB

TGS-TB provides comprehensive genotyping of Mycobacterium tuberculosis by extracting spoligotypes, core-genome single nucleotide variations (SNVs), IS6110 insertion sites, VNTR profiles (43 loci), and KvarQ-based lineage and antimicrobial-resistance predictions from next-generation sequencing reads to support phylogenetic and epidemiological analyses.

Key Features:

• Multi-platform genotyping: Integrates NGS-derived spoligotyping and core-genome phylogenetic analysis for Mycobacterium tuberculosis complex (MTBC).
• Core genomic SNV detection: Identifies core-genome single nucleotide variations for molecular-evolution and phylogenetic inference.
• IS6110 insertion site analysis: Detects IS6110 insertion sites as additional genetic markers for strain differentiation.
• VNTR profiling (43 loci): Performs variable number tandem repeat analysis using a customized set of 43 loci to increase genotyping resolution.
• KvarQ-based lineage and resistance prediction: Uses a KvarQ script to predict MTBC lineages, sublineages, and potential antimicrobial resistance markers.
• Median-joining network analysis: Employs median-joining network analysis based on unique SNVs for discrimination of isolates.
• Read-length considerations: Supports genotyping from short NGS reads (~100-mer) and indicates that longer reads (≥300-mer) enable fuller genotyping capabilities.

Scientific Applications:

• Clinical and epidemiological investigations: Enables strain typing and lineage/resistance prediction to inform clinical and public-health analyses.
• Outbreak investigation and surveillance: Supports discrimination of related isolates and transmission inference through core-genome phylogeny and SNV analysis.
• Resolution of identical VNTR profiles: Differentiates multiple Mtb strains that share identical VNTR profiles by using core-genome SNVs and IS6110 insertion data.

Methodology:

Computational steps explicitly stated include SNV calling to identify core-genome SNVs, detection of IS6110 insertion sites, VNTR profiling at 43 loci, spoligotyping from NGS reads, lineage and resistance prediction via a KvarQ script, and median-joining network analysis based on unique SNVs.