The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Identification of Prosthetic Joint Infection Pathogens Using a Shotgun Metagenomics Approach
Open accessAbstract
Background: Metagenomic shotgun sequencing has the potential to change how many infections, particularly those caused by difficult-to-culture organisms, are diagnosed. Metagenomics was used to investigate prosthetic joint infections (PJIs), where pathogen detection can be challenging. Methods: Four hundred eight sonicate fluid samples generated from resected hip and knee arthroplasties were tested, including 213 from subjects with infections and 195 from subjects without infection. Samples were enriched for microbial DNA using the MolYsis basic kit, whole-genome amplified, and sequenced using Illumina HiSeq 2500 instruments. A pipeline was designed to screen out human reads and analyze remaining sequences for microbial content using the Livermore Metagenomics Analysis Toolkit and MetaPhlAn2 tools. Results: When compared to sonicate fluid culture, metagenomics was able to identify known pathogens in 94.8% (109/115) of culture-positive PJIs, with additional potential pathogens detected in 9.6% (11/115). New potential pathogens were detected in 43.9% (43/98) of culture-negative PJIs, 21 of which had no other positive culture sources from which these microorganisms had been detected. Detection of microorganisms in samples from uninfected aseptic failure cases was conversely rare (7/195 [3.6%] cases). The presence of human and contaminant microbial DNA from reagents was a challenge, as previously reported. Conclusions: Metagenomic shotgun sequencing is a powerful tool to identify a wide range of PJI pathogens, including difficult-to-detect pathogens in culture-negative infections.
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Self-citationEconomic Burden of Periprosthetic Joint Infection in the United States
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Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids
Gu, W., Deng, X., Lee, M., Sucu, Y. D., Arevalo, S., Stryke, D., Federman, S., Gopez, A., Reyes, K., Zorn, K., et al. (2021) · Nature Medicine · doi:10.1038/s41591-020-1105-z · Cited by 689
Metadata
- Authors
- Thoendel, M. J., Jeraldo, P. R., Greenwood-Quaintance, K. E., Yao, J. Z., Chia, N., Hanssen, A. D., Abdel, M. P., & Patel, R.
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-04-10
- Volume
- 67
- Issue
- 9
- Pages
- 1333-1338
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- OpenAlex
- W2800650583
- Cited by
- 253
- References
- 21
- FWCI
- 22.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Thoendel, M. J., Jeraldo, P. R., Greenwood-Quaintance, K. E., Yao, J. Z., Chia, N., Hanssen, A. D., Abdel, M. P., & Patel, R. (2018). Identification of Prosthetic Joint Infection Pathogens Using a Shotgun Metagenomics Approach. Clinical Infectious Diseases. https://doi.org/10.1093/cid/ciy303
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