QuantTB

QuantTB identifies and quantifies individual Mycobacterium tuberculosis strains and resistance-associated variants from whole-genome sequencing datasets to resolve mixed infections and heteroresistance.

Key Features:

• SNP-Based Methodology: QuantTB utilizes single nucleotide polymorphism (SNP) markers to identify and quantify individual strains within whole genome sequencing samples.
• High Resolution and Sensitivity: Capable of distinguishing communities differing by fewer than 25 SNPs and detecting strains in samples with coverage as low as 1×.
• Strain Identification and Quantification: Provides lists of identified Mycobacterium tuberculosis strains with relative abundances and predicts resistance-conferring mutations and heteroresistance for drugs present in the sample.
• Performance Validation: Validated on simulated datasets and on 50 paired clinical isolates, outperforming other metagenomic strain identification tools in detection and quantification and yielding results concordant with manual curation.

Scientific Applications:

• Detection of Mixed Infections: By leveraging whole-genome sequencing and SNP markers, detects and quantifies mixed Mycobacterium tuberculosis infections.
• Differentiation Between Relapse and Re-infection: Analyzes strain multiplicity and genomic differences to distinguish relapse from reinfection.
• Heteroresistance Pattern Identification: Identifies heteroresistance patterns and resistance-conferring mutations within samples to inform antibiotic resistance dynamics.

Methodology:

QuantTB employs SNP markers to determine the combination of strains that best explain the allelic variation observed in a sample.