Shotgun-metagenomics based prediction of antibiotic resistance and virulence determinants in Staphylococcus aureus from periprosthetic tissue on blood culture bottles

Adriana Maria Sanabria,Anne-Merethe Hanssen,Jessin Janice,Erik Hjerde,Gunnar Skov Simonsen

doi:10.1038/s41598-021-00383-7

Abstract

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 periprosthetic 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 periprosthetic joint infection virulence genes were predicted from S. aureus. Mean coverage depth, when predicting AMR genes was 209 ×. Resistance phenotypes could be explained by genes predicted in the sample in most of the cases. The choice of bioinformatic data analysis approach clearly influenced the results, i.e. 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.

Highlights

Shotgun-metagenomics may give valuable clinical information beyond the detection of potential pathogen(s)
We showed that SMg performed directly on positive blood culture bottles (BCBs) inoculated with periprosthetic tissue (PT), is a convenient method to identify potential pathogens causing PJI18
With metaSPAdes yielded a mean number of 232 contigs, with a mean total size of 3.1 Mb in the clinical samples and 213 contigs for a total length of 2.7 Mb in the sample spiked with S. aureus (Supplementary Table S5)

Summary

Introduction

Shotgun-metagenomics may give valuable clinical information beyond the detection of potential pathogen(s). The use of shotgun-metagenomics (SMg) for the analysis of clinical specimens has emerged as a promising approach for pathogen identification, antimicrobial resistance (AMR) identification and outbreak investigation in clinical microbiology laboratories This approach has been used for the analysis of different types of clinical specimens, including samples related to PJI, e.g. synovial fluid[9,10], sonication fluid[11,12,13,14] and tissue[15], mainly for the identification of pathogens. The use of SMg on samples from bone and joint infections has been used where they could predict antibiotic susceptibility in 94.1% (monomicrobial) and 76.5% (polymicrobial) of the c ases[15] In these studies, the main obstacle has been a high background of genetic material mainly derived from the host, which generates very few bacterial reads. This problem arises when coverage is too low to guarantee the presence of a read containing a given sequence in the targeted g enome[26]

Methods

Results

Conclusion