Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing

Ivy, Morgan; Thoendel, Matthew; Jeraldo, Patricio; Greenwood‐Quaintance, Kerryl E.; Hanssen, Arlen D.; Abdel, Matthew P.; Chia, Nicholas; Yao, Jingwen; Tande, Aaron J.; Mandrekar, Jayawant N.; Patel, Robin

doi:10.1128/jcm.00402-18

Cited by 139 publications

(153 citation statements)

References 47 publications

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“…Other sources that have either been validated or are close to clinical validation for metagenomics include respiratory specimens [64,74] and prosthetic joint specimens [75][76][77], respectively. Studies in these sample types also detect a number of questionable or insignificant positive results, highlighting the need for careful clinical interpretation.…”

Section: Next-generation Sequencing and Clinical Metagenomicsmentioning

confidence: 99%

Appropriate Use and Future Directions of Molecular Diagnostic Testing

Graf

Pancholi

2020

Curr Infect Dis Rep

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Purpose of Review Major technologic advances in two main areas of molecular infectious disease diagnostics have resulted in accelerated adoption or ordering, outpacing implementation, and clinical utility studies. Physicians must understand the limitations to and appropriate utilization of these technologies in order to provide cost-effective and well-informed care for their patients. Recent Findings Rapid molecular testing and, to a lesser degree, clinical metagenomics are now being routinely used in clinical practice. While these tests allow for a breadth of interrogation not possible with conventional microbiology, they pose new challenges for diagnostic and antimicrobial stewardship programs. This review will summarize the most recent literature on these two categories of technologic advances and discuss the few studies that have looked at utilization and stewardship approaches. This review also highlights the future directions for both of these technologies. Summary The appropriate utilization of rapid molecular testing and clinical metagenomics has not been well established. More studies are needed to assess their prospective impacts on patient management and antimicrobial stewardship efforts as the future state of infectious disease diagnostics will see continued expansion of these technologic advances.

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Section: Next-generation Sequencing and Clinical Metagenomicsmentioning

confidence: 99%

Appropriate Use and Future Directions of Molecular Diagnostic Testing

Graf

Pancholi

2020

Curr Infect Dis Rep

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“…Metagenomic shotgun sequencing is a method of sequencing all the nucleic acid in a specimen unbiasedly and then matching the sequences to those in databases to identify organisms and their genetic traits (e.g., antibiotic resistance genes and mutations). This approach has the potential to identify a variety of infectious agents, including bacteria, viruses, fungi, and protists, directly from various clinical samples, with applications being described for central nervous system specimens (12)(13)(14)(15)(16), respiratory tract specimens (17,18), blood (19)(20)(21)(22), urine (23,24), bile (25), stool (26), synovial fluid (27), and prosthesis sonicate fluid (28)(29)(30).…”

mentioning

confidence: 99%

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

Yan

Thoendel

et al. 2019

J Clin Microbiol

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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.

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“…Studies of the population structures of opportunistic pathogens have revealed extensive strain-level within-host variation (Stoesser et al 2015;Golubchik et al 2013;Paterson et al 2015;Greenblum et al 2015;Brodrick et al 2017;Lieberman et al 2014) with adverse implications for transmission analyses relying solely on isolate sequencing (Worby et al 2014;Stoesser et al 2015) and longitudinal studies reporting the absence or re-emergence of strains in a host based on colony picks (Paterson et al 2015;Brodrick et al 2016Brodrick et al , 2017 . While whole-genome shotgun metagenomics solves these issues to some extent (Gu et al 2019;Forbes et al 2017) , the culture-free nature suffers from issues with both bacterial and host DNA contamination particularly affecting the sensitivity for detecting strains in low abundance (Whelan et al 2020;Ivy et al 2018;McArdle and Kaforou 2020;Salter et al 2014) . Using mGEMS in conjunction with plate sweep sequencing data avoids these issues altogether, paving way for more representative studies of pathogen population structure and providing higher-resolution data for more complex models of transmission dynamics incorporating within-host variation and evolution (Maio et al 2018;Worby et al 2017;Skums et al 2018) .…”

Section: Discussionmentioning

confidence: 99%

“…In practice, natural strain-level variation is harbored ubiquitously in epidemiologically relevant samples (Greenblum et al 2015;The Human Microbiome Project Consortium 2012;Ellegaard and Engel 2016) and it is reflected by the transmission events occurring between individuals and their environment (Stoesser et al 2015) . Although some sample types may be dominated by one or two strains (Truong et al 2017) , direct environmental sequencing may result in an overabundance of host DNA (Whelan et al 2020;Ivy et al 2018;Gu et al 2019) , or lack detection power for strains with low abundance in environments with high species diversity (Whelan et al 2020;Quince et al 2017;Vollmers et al 2017) . These challenges are overcome in genomic epidemiology by enriching the target species through the use of plate cultures.…”

Section: Introductionmentioning

confidence: 99%

Genomic Epidemiology with Mixed Samples

Mäklin

Kallonen

Alanko

et al. 2020

Preprint

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Genomic epidemiology is an established tool for investigation of outbreaks of infectious diseases and wider public health applications. It traces transmission of pathogens based on whole-genome sequencing of colony picks from culture plates enriching the target organism(s). In this article, we introduce the mGEMS pipeline for performing genomic epidemiology directly with plate sweeps representing mixed samples of the target pathogen in a culture plate, skipping the colony pick step entirely. By requiring only a single culturing and library preparation step per analyzed sample, we address several key issues in the current approach relating to its cost, practical application and sensitivity. Our pipeline significantly improves upon the state-of-the-art in analysing mixed short-read sequencing data from bacteria, reaching accuracy levels in downstream analyses closely resembling colony pick sequencing data that allow reliable SNP calling and subsequent phylogenetic analyses. The fundamental novel parts enabling these analyses are the mGEMS read binner for probabilistic assignments of sequencing reads and the high-throughput exact pseudoaligner Themisto. In conjunction with recent advances in probabilistic modelling of mixed bacterial samples and genome assembly techniques, these tools form the mGEMS pipeline. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting for the three major pathogens Enterococcus faecalis , Escherichia coli and Staphylococcus aureus . Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

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Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing

Abstract: 43 44 45 23Background: Metagenomic shotgun sequencing has the potential to transform how serious

Cited by 139 publications

References 47 publications

Appropriate Use and Future Directions of Molecular Diagnostic Testing

Appropriate Use and Future Directions of Molecular Diagnostic Testing

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

Genomic Epidemiology with Mixed Samples

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