Genome-based model for differentiating between infection and carriage Staphylococcus aureus

Area of Science:

• Microbiology
• Genomics
• Infectious Diseases

Background:

• Staphylococcus aureus (S. aureus) is a significant pathogen causing worldwide infections.
• Distinguishing S. aureus infection from asymptomatic carriage is challenging due to unknown genetic differences.
• Identifying genetic elements associated with S. aureus infection is crucial for disease control.

Purpose of the Study:

• To identify specific genetic elements (k-mers) associated with S. aureus infection.
• To differentiate between S. aureus isolates from clinical infections and nasal carriage.
• To explore the potential of these genetic elements for diagnostic and therapeutic targets.

Main Methods:

• Genome-wide association study (GWAS) comparing S. aureus infection (272 isolates) and carriage (240 isolates) genomes.
• Analysis of genetic variation, specifically k-mers, overrepresented in infection isolates.
• Development of a random forest (RF) model to predict disease status based on k-mers.

Main Results:

• Certain k-mers were significantly overrepresented in S. aureus infection isolates compared to carriage isolates.
• The RF model achieved 77% accuracy in classifying disease status (infection vs. carriage).
• A single highest-ranked k-mer predictor showed 68% accuracy, indicating a potential diagnostic marker.

Conclusions:

• S. aureus causing infection represents a pathogenic subpopulation with unique genomic variations.
• These identified genomic variations provide novel targets for clinical interventions against S. aureus infections.
• The findings support the development of early diagnostics for differentiating S. aureus infection from carriage.