ARDaP

ARDaP detects and predicts antimicrobial resistance (AMR) determinants from whole-genome sequencing (WGS) data to identify single-nucleotide polymorphisms (SNPs), insertions–deletions (indels), copy-number variations (CNVs), and functional gene loss underlying resistance in pathogens such as Burkholderia pseudomallei.

Key Features:

• Comprehensive variant detection: Identifies SNPs, indels, CNVs, and functional gene loss associated with AMR from WGS data.
• Low-frequency variant detection: Detects AMR determinants present at low allelic frequencies in mixed strain datasets (as low as ~5%).
• Prediction of novel determinants: Predicts previously undescribed AMR-conferring mutations.
• Pathogen-specific application: Tuned to detect chromosomal mutation-driven AMR in Burkholderia pseudomallei.
• Database flexibility: Supports construction of customizable, species-specific AMR databases.
• Addresses limits of existing tools: Targets detection gaps reported for tools such as ARIBA and CARD in identifying clinically relevant AMR determinants.

Scientific Applications:

• Genetic basis of AMR: Enables identification and characterization of genetic determinants driving antimicrobial resistance.
• Clinical guidance: Informs treatment strategy decisions by detecting resistance determinants from pathogen genomes.
• Surveillance and public health: Supports genomic surveillance and intervention planning by detecting and predicting AMR in pathogen populations.
• Mixed-infection analysis: Facilitates early detection of resistant subpopulations in mixed-strain samples.

Methodology:

Evaluated using whole-genome sequencing data from wild-type and AMR-acquired strains of Burkholderia pseudomallei; computationally identifies SNPs, indels, CNVs, and functional gene loss and detects low-frequency alleles (~5%) in mixed strain datasets.