Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis

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 timeconsuming 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.

Comparison of Three Commercial Tools for Metagenomic Shotgun Sequencing Analysis

“…It should also be noted that the CosmosID interpretations were based on an algorithm that includes parameters of sequencing results that were developed by our laboratory (12) and slightly modified, whereas One Codex interpretations were provided automatically and IDbyDNA included a secondary human component for interpretation of results. Altering the settings for interpretive criteria for CosmosID could be expected to alter performance of the analysis, while the potential variability in interpretation by the other tools is not able to be assessed with this one data set.…”

“…The negative controls of Ringer's solution were processed in the same way as the sonicate fluid. The samples were collected under Mayo Clinic Internal Review Board protocol 09-00808 and have been previously described (11,12).…”

“…We previously published the results of metagenomic sequencing of a large sample set of resected joint arthroplasties consisting of both infected samples (prosthetic joint infection [PJI]) and uninfected samples (aseptic failure [AF]) (11). We also recently reported the use of the CosmosID platform for evaluation of this entire set of samples (12). In this study, a curated set of those previously characterized samples was selected to represent a range of sample complexity, including uninfected, monomicrobial, or polymicrobial infections, along with various signal strengths, from those that were weakly positive to those with a high percentage of microbial reads in a sample.…”

A New Whole Genome Culture-Independent Diagnostic Test (WG-CIDT) for Rapid Detection of Salmonella in Lettuce

“…The result is the taxonomic analysis of the organisms recovered from the lettuce and speciation of the microbial contaminant inferred from the contigs assembled from DNA fragments generated from extracts from the surface of the lettuce. For approach (d), unassembled sequence reads were directly analyzed by CosmosID metagenomic software as described elsewhere (Meisel et al, 2018;Yan et al, 2019) to reveal taxonomic composition of the community. Briefly, the system utilizes a high performance data-mining k-mer algorithm and highly curated dynamic comparator databases (GenBook R ) that rapidly disambiguate millions of short reads into the discrete genomes or genes engendering the particular sequences.…”

Current Clinical Methods for Detection of Peri-Prosthetic Joint Infection

“…More than half of these results came from patients who had received pre-operative antibiotic agents. Sequencing can detect bacteria even when a patient has already received antibiotics, which can adversely affect culturing results [34].…”