Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID...

Area of Science:

• Bioinformatics
• Genomics
• Public Health

Background:

• Antimicrobial resistant (AMR) pathogens pose significant global health threats.
• Metagenomic next-generation sequencing (mNGS) is crucial for AMR surveillance.
• Existing bioinformatics tools struggle to simultaneously analyze microbial and AMR gene sequences.

Purpose of the Study:

• To develop an open-access, cloud-based bioinformatics workflow for integrated microbial and AMR gene detection.
• To enhance the capabilities of the Chan Zuckerberg ID (CZ ID) platform for pathogen surveillance.

Main Methods:

• Development of the CZ ID AMR module, integrating the Comprehensive Antibiotic Resistance Database and Resistance Gene Identifier.
• Application of the module to analyze mNGS and single-isolate whole-genome sequencing (WGS) data.
• Synergistic use with the CZ ID short-read mNGS module for comprehensive analysis of Illumina data.

Main Results:

• Demonstrated diverse applications across clinical cohorts and environmental surveillance.
• Enabled genomic investigations of sepsis, pneumonia, hospital outbreaks, and wastewater.
• Facilitated understanding of infectious agents, their resistomes, and phylogenetic relationships.
• Captured longitudinal dynamics of pathogens and AMR genes in hospital-acquired infections.

Conclusions:

• The CZ ID AMR module advances pathogen detection and AMR profiling from mNGS and WGS data.
• This open-access tool democratizes pathogen genomic analysis.
• Supports collaborative efforts to combat the growing threat of antimicrobial resistance.