Shotgun-Metagenomics Based Prediction Of Antibiotic Resistance And Virulence Determinants In Staphylococcus Aureus From Prosthetic Joint Tissue On Blood Culture Bottles

Shotgun-metagenomics may give valuable clinical information beyond the detection of potential pathogen(s). Identification of antimicrobial resistance (AMR), virulence genes and typing directly from clinical samples has been limited due to challenges arising from incomplete genome coverage. We assessed the performance of shotgun-metagenomics on positive blood culture bottles (n = 19) with prosthetic joint tissue for typing and prediction of AMR and virulence profiles in Staphylococcus aureus . We used different approaches to determine if sequence data from reads provides more information than from assembled contigs. Only 0.18% of total reads was derived from human DNA. Shotgun-metagenomics results and conventional method results were consistent in detecting S. aureus in all samples. AMR and known prosthetic joint infection virulence genes were predicted from S. aureus . Mean coverage depth, when predicting AMR genes was 209x. Resistance phenotypes could be explained by genes predicted in the sample in most of the cases. The choice of bioinformatic data analysis had a significant impact on the results. Read-based analysis was more accurate for pathogen identification, while contigs seemed better for AMR profiling. Our study demonstrates high genome coverage and potential for typing and prediction of AMR and virulence profiles in S. aureus from shotgun-metagenomics data.