# PaREx: an open-source pipeline for the automated analysis of Pseudomonas aeruginosa resistomes from whole-genome sequences

## TL;DR

PaREx is a new automated tool for analyzing antibiotic resistance in Pseudomonas aeruginosa using whole-genome sequencing data.

## Contribution

PaREx introduces an open-source pipeline and web tool for accurate resistome profiling in P. aeruginosa, including detection of mutation-driven resistance and AmpC variants.

## Key findings

- PaREx accurately analyzes P. aeruginosa resistomes using 221 chromosomal genes and horizontally acquired resistance mechanisms.
- The PDC analyzer web tool effectively designates PDCs and detects resistance to novel β-lactam antibiotics across thousands of genomes.
- PaREx's performance matches manual analysis when calculating genotypic resistance scores from 260 isolates.

## Abstract

Whole-genome sequencing (WGS) has become a valuable tool for bacterial typing and resistome analysis. However, most existing antibiotic resistance databases and bioinformatics tools are not useful for P. aeruginosa resistome profiling as they fail to detect mutation-driven antibiotic resistance mechanisms. In addition, the increasing diversity of AmpC variants (Pseudomonas-derived cephalosporinases [PDCs]) in recent years adds complexity to P. aeruginosa resistome profiling. To address these challenges, we have developed PaREx, an open-source automated pipeline specifically designed for the analysis of P. aeruginosa mutation-driven (221 chromosomal genes) and horizontally acquired resistome from whole-genome sequences, along with the PDC analyzer web tool, a user-friendly platform that designates PDCs and detects resistance to novel antipseudomonal β-lactams. The utility of Pseudomonas aeruginosa Resistome Explorer (PaREx) was demonstrated through the analysis of 260 P. aeruginosa isolates, using its output to calculate five previously defined genotypic resistance scores, achieving results comparable to that of manual bioinformatic analysis. Likewise, the PDC analyzer web tool was validated with more than 30,000 global P. aeruginosa genomes, demonstrating its utility for PDC designation and detection of mutations conferring resistance to novel BL/BLI. Both PaREx and the PDC analyzer web tool were shown to be user-friendly, accurate, and automated tools for resistome profiling in P. aeruginosa, enhancing current capabilities of existing tools. However, an ongoing refinement of these tools and its custom-built databases is needed to address remaining gaps and future challenges of whole-genome sequence-based resistance prediction.