Evaluation of the cosmosid bioinformatics platform for prosthetic joint-associated sonicate fluid shotgun metagenomic data analysis

Qun Yan, Yu Mi Wi, Matthew J. Thoendel, Yash S. Raval, Kerryl E. Greenwood-Quaintance, Matthew Abdel, Patricio R. Jeraldo, Nicholas D Chia, Robin Patel

Research output: Contribution to journalArticle

Abstract

We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.

Original languageEnglish (US)
Article numbere01182
JournalJournal of Clinical Microbiology
Volume57
Issue number2
DOIs
StatePublished - Feb 1 2019

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Metagenomics
Firearms
Computational Biology
Joints
Bacterial Drug Resistance
Bacteria
Microbial Drug Resistance
Infection
Genes

Keywords

  • Antimicrobial resistance
  • Metagenomics
  • PJI
  • Prosthetic joint infection
  • Sonicate fluid

ASJC Scopus subject areas

  • Microbiology (medical)

Cite this

Evaluation of the cosmosid bioinformatics platform for prosthetic joint-associated sonicate fluid shotgun metagenomic data analysis. / Yan, Qun; Mi Wi, Yu; Thoendel, Matthew J.; Raval, Yash S.; Greenwood-Quaintance, Kerryl E.; Abdel, Matthew; Jeraldo, Patricio R.; Chia, Nicholas D; Patel, Robin.

In: Journal of Clinical Microbiology, Vol. 57, No. 2, e01182, 01.02.2019.

Research output: Contribution to journalArticle

Yan, Qun ; Mi Wi, Yu ; Thoendel, Matthew J. ; Raval, Yash S. ; Greenwood-Quaintance, Kerryl E. ; Abdel, Matthew ; Jeraldo, Patricio R. ; Chia, Nicholas D ; Patel, Robin. / Evaluation of the cosmosid bioinformatics platform for prosthetic joint-associated sonicate fluid shotgun metagenomic data analysis. In: Journal of Clinical Microbiology. 2019 ; Vol. 57, No. 2.
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