Resistance Sniffer

Resistance Sniffer: Drug resistance prediction from Mycobacterium tuberculosis whole genome sequencing data

Resistance Sniffer predicts antibiotic resistance patterns of Mycobacterium tuberculosis isolates using next-generation sequencing data. It analyzes whole genome sequencing datasets to detect genetic polymorphisms associated with resistance to thirteen anti-TB drugs and generates probabilistic resistance profiles.

Key Features:

• Whole Genome Sequencing Integration: Identifies resistance-associated genetic polymorphisms from whole genome sequencing (WGS) data, including raw Illumina fastq read files and partial or complete genome datasets.
• Clade-Specific Genetic Polymorphism Catalogue: Uses a curated catalogue of clade-specific genetic determinants linked to resistance against thirteen anti-TB drugs to improve prediction accuracy.
• Computational Algorithm: Applies an algorithm to detect diagnostic polymorphisms in sequencing data and generate probabilistic resistance predictions.

Scientific Applications:

• Rapid Drug Resistance Profiling: Supports identification of multidrug-resistant tuberculosis (MDR-TB) strains for treatment planning and surveillance.
• Large-Scale Genomic Analysis: Processes extensive sequencing datasets for epidemiological studies and tuberculosis outbreak monitoring.

Methodology:

Analyzes next-generation sequencing data to identify clade-specific resistance-associated polymorphisms in Mycobacterium tuberculosis. Validated using sequenced isolates from antibiotic resistance trials, including datasets from the GMTV database and the TB Platform of the South African Medical Research Council (SAMRC), Pretoria, for individual strain and large-scale sequence evaluation.