GAMBIT

GAMBIT performs k-mer–based taxonomic identification and genomic distance estimation of bacterial pathogens from whole genome sequencing (WGS) of clinical bacterial isolates for rapid clinical and public health diagnostics and tracking.

Key Features:

• k-mer–based genomic distance metrics: Uses k-mer–based strategies as efficient genomic distance metrics to identify bacteria from WGS reads in seconds.
• Curated reference genome database: Integrates a highly curated reference database containing 48,224 genomes derived from NCBI RefSeq.
• Confidence thresholds: Establishes confidence thresholds for identification results.
• Reference database curation: Applies a rigorous curation process to the reference database to maintain quality standards.
• Validation in public health laboratories: Has been validated in studies at two public health laboratories where it was deployed as a laboratory-developed test.
• Application to clinical isolates: Processes whole genome sequencing data from clinical bacterial isolates for taxonomic identification and tracking.

Scientific Applications:

• Clinical diagnostics: Identification of bacterial pathogens from clinical WGS data to inform diagnostic interpretation.
• Public health surveillance: Tracking and identification of infectious agents for outbreak investigation and surveillance by public health laboratories.
• Laboratory-developed test deployment: Use as a validated laboratory-developed test in public health laboratory settings.
• Microbial pathogen identification in research: Precise taxonomic identification of bacterial isolates for research applications requiring high-resolution genomic comparison.

Methodology:

Computational methods comprise k-mer–based strategies to compute genomic distances against a curated database of 48,224 NCBI RefSeq genomes, application of confidence thresholds for identifications, and a rigorous reference database curation process.