KARGAMobile

KARGAMobile performs real-time identification of antibiotic resistance genes (ARGs) from nanopore sequencing data to support point-of-care and environmental surveillance.

Key Features:

• Mobile-optimized computational engine: Adaptation of the KARGA algorithm with a compressed ARG reference database and efficient internal data structures to minimize RAM usage.
• Memory footprint: Maintains peak RAM usage below 500 MB regardless of input file sizes.
• Throughput for targeted and metagenomic data: Processes on average 1 GB of nanopore sequencing data every 23–48 minutes for both targeted sequencing and metagenomics applications.
• Output post-processing: Post-processes output files to generate visual reports for interpretation of ARG findings.
• Classification performance: Achieves a classification f-measure of 96.2% compared to 96.9% for KARGA on semi-synthetic datasets containing 1 million reads with known resistance ground truth.
• Operational thermal profile: Maintains an average device temperature of 49°C during continuous data processing for one hour.

Scientific Applications:

• Point-of-care clinical analysis: Rapid identification of ARGs to inform treatment strategies for bacterial infections.
• Environmental surveillance: Real-time monitoring of antibiotic resistance outbreaks in ecological contexts.

Methodology:

Processes nanopore sequencing data using an algorithmic foundation derived from KARGA with optimizations (compressed ARG reference database and efficient internal data structures) to reduce computational resource demands; implemented in Java.