SnackNTM

SnackNTM performs species-level identification of nontuberculous mycobacteria (NTM) from Sanger sequencing trace files using 16S rRNA and rpoB gene analyses.

Key Features:

• Trace-file processing: Automates sequence trimming, consensus sequence generation, and public database searches from Sanger chromatogram (trace) files.
• Diagnostic algorithm: Applies 16S rRNA–based identification following Clinical and Laboratory Standards Institute (CLSI) guidelines and incorporates an rpoB gene region to refine species calls.
• Programming language: Implemented in Java.
• Validation and accuracy: Validated on trace files from 234 clinical cases, achieving 95.9% (208/217) identification success for consecutive clinical cases, 99.0% agreement (206/208) with manual classification, and correct identification of all 17 unique-species cases.
• Time efficiency: Demonstrated a reduction in analysis and reporting time for 30 cases from 150 minutes (manual) to 40 minutes (automated).

Scientific Applications:

• Clinical NTM identification: Species-level identification of nontuberculous mycobacteria in clinical microbiology laboratories using Sanger sequencing data.
• Diagnostic reporting and management: Supports timely and accurate microbial identification to inform patient management and treatment decisions.

Methodology:

Processes Sanger trace files with sequence trimming and consensus sequence generation, performs public database searches, and applies a diagnostic algorithm based on 16S rRNA (CLSI-guided) with an rpoB gene region; implemented in Java.