qnr

qnr detects qnr genes associated with fluoroquinolone antibiotic resistance in large metagenomic nucleotide sequence datasets to characterize their diversity and distribution.

Key Features:

• Implementation: Python-based implementation for analysis of nucleotide sequence data from large metagenomic datasets.
• Identification of QNR Genes: Detects qnr genes that confer resistance to fluoroquinolone antibiotics and can disseminate via horizontal gene transfer.
• High Sensitivity and Specificity: Validated using cross-validation, demonstrating high sensitivity and specificity in classifying sequences from known and novel qnr classes.
• Short Fragment Detection: Effectively detects qnr genes in short nucleotide fragments as brief as 100 base pairs.
• Comprehensive Detection: Recapitulated all previously reported plasmid-mediated qnr genes from public sequence repositories and discovered multiple fragments indicative of novel putative qnr genes in metagenomic samples.
• Annotation Capability: Annotates chromosomal qnr variants, identifying 39 variants including 11 not previously documented.

Scientific Applications:

• Exploration of QNR Gene Diversity: Uses shotgun metagenomics to analyze diversity and distribution of qnr genes across environmental bacterial communities.
• Public Health Insights: Supports assessment of prevalence and variation of qnr genes to inform potential public health risks from fluoroquinolone-resistant bacteria.

Methodology:

Python-based implementation employing algorithms that distinguish known and novel qnr gene variants, validated by cross-validation, operating on nucleotide sequence data including fragments as short as 100 base pairs and performing chromosomal variant annotation.