# Genome co-adaptation and the evolution of methicillin resistant Staphylococcus aureus

## TL;DR

This study explores how Staphylococcus aureus integrates resistance genes into its genome, revealing new genetic interactions that support antibiotic resistance.

## Contribution

The study introduces GOLD-GWAS, a novel bioinformatics method to identify functional gene associations in bacterial genomes.

## Key findings

- GOLD-GWAS identified genes that covary with the SCCmec resistance cassette in S. aureus.
- The method uncovered both known and new gene–gene interactions linked to methicillin resistance.
- The findings highlight how resistance genes are integrated into coadapted bacterial genomes.

## Abstract

Antimicrobial resistance in bacterial pathogens is a major threat to global health, rendering standard treatments ineffective and increasing the risk of severe infection or death. Resistance is often conferred by genes that are transferred horizontally among species and strains. However, for many bacteria, little is known about the genetic variation that potentiates resistance gene acquisition and accommodates acquired genes in the coadapted recipient genome.

Here we introduce a new bioinformatics genome-wide association study approach, Guided Omission of Linkage Disequilibrium (GOLD-GWAS). This method masks covarying alleles explained by coinheritance and genome proximity to reveal loci where covarying sequence likely represents functional linkage, consistent with epistasis. Analysing 806 Staphylococcus aureus isolate genomes, including methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) strains, we identified genes that covary with the presence of the acquired staphylococcal cassette chromosome mec (SCCmec) that houses the mecA resistance gene.

By uncovering known and new gene–gene associations, we demonstrate how resistance can involve genetic coalitions beyond well-known antimicrobial resistance genes. Understanding how genomic changes, such as extrinsic resistance cassettes, are integrated within coadapted bacterial genomes is an important step towards mitigating antimicrobial resistance evolution and identifying novel genetic targets for risk prediction, diagnosis, and therapy.

The online version contains supplementary material available at 10.1186/s13059-026-04000-6.