Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.

16S rRNA gene sequencing of DNA extracted from clinically uninfected hip and knee implant samples has revealed polymicrobial populations. However, previous studies assessed 16S rRNA gene sequencing as a technique for the diagnosis of periprosthetic joint infections, leaving the microbiota of presume...

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Autores principales:	Charles Carr, Hannah Wilcox, Jeremy P Burton, Sharanya Menon, Kait F Al, David O'Gorman, Brent A Lanting, Edward M Vasarhelyi, Michael Neufeld, Matthew G Teeter
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/91fd2eddefbe4f2da652830e118b5a35
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spelling	oai:doaj.org-article:91fd2eddefbe4f2da652830e118b5a352021-12-02T20:14:37ZDeciphering the low abundance microbiota of presumed aseptic hip and knee implants.1932-620310.1371/journal.pone.0257471https://doaj.org/article/91fd2eddefbe4f2da652830e118b5a352021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257471https://doaj.org/toc/1932-620316S rRNA gene sequencing of DNA extracted from clinically uninfected hip and knee implant samples has revealed polymicrobial populations. However, previous studies assessed 16S rRNA gene sequencing as a technique for the diagnosis of periprosthetic joint infections, leaving the microbiota of presumed aseptic hip and knee implants largely unstudied. These communities of microorganisms might play important roles in aspects of host health, such as aseptic loosening. Therefore, this study sought to characterize the bacterial composition of presumed aseptic joint implant microbiota using next generation 16S rRNA gene sequencing, and it evaluated this method for future investigations. 248 samples were collected from implants of 41 patients undergoing total hip or knee arthroplasty revision for presumed aseptic failure. DNA was extracted using two methodologies-one optimized for high throughput and the other for human samples-and amplicons of the V4 region of the 16S rRNA gene were sequenced. Sequencing data were analyzed and compared with ancillary specific PCR and microbiological culture. Computational tools (SourceTracker and decontam) were used to detect and compensate for environmental and processing contaminants. Microbial diversity of patient samples was higher than that of open-air controls and differentially abundant taxa were detected between these conditions, possibly reflecting a true microbiota that is present in clinically uninfected joint implants. However, positive control-associated artifacts and DNA extraction methodology significantly affected sequencing results. As well, sequencing failed to identify Cutibacterium acnes in most culture- and PCR-positive samples. These challenges limited characterization of bacteria in presumed aseptic implants, but genera were identified for further investigation. In all, we provide further support for the hypothesis that there is likely a microbiota present in clinically uninfected joint implants, and we show that methods other than 16S rRNA gene sequencing may be ideal for its characterization. This work has illuminated the importance of further study of microbiota of clinically uninfected joint implants with novel molecular and computational tools to further eliminate contaminants and artifacts that arise in low bacterial abundance samples.Charles CarrHannah WilcoxJeremy P BurtonSharanya MenonKait F AlDavid O'GormanBrent A LantingEdward M VasarhelyiMichael NeufeldMatthew G TeeterPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257471 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Charles Carr Hannah Wilcox Jeremy P Burton Sharanya Menon Kait F Al David O'Gorman Brent A Lanting Edward M Vasarhelyi Michael Neufeld Matthew G Teeter Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
description	16S rRNA gene sequencing of DNA extracted from clinically uninfected hip and knee implant samples has revealed polymicrobial populations. However, previous studies assessed 16S rRNA gene sequencing as a technique for the diagnosis of periprosthetic joint infections, leaving the microbiota of presumed aseptic hip and knee implants largely unstudied. These communities of microorganisms might play important roles in aspects of host health, such as aseptic loosening. Therefore, this study sought to characterize the bacterial composition of presumed aseptic joint implant microbiota using next generation 16S rRNA gene sequencing, and it evaluated this method for future investigations. 248 samples were collected from implants of 41 patients undergoing total hip or knee arthroplasty revision for presumed aseptic failure. DNA was extracted using two methodologies-one optimized for high throughput and the other for human samples-and amplicons of the V4 region of the 16S rRNA gene were sequenced. Sequencing data were analyzed and compared with ancillary specific PCR and microbiological culture. Computational tools (SourceTracker and decontam) were used to detect and compensate for environmental and processing contaminants. Microbial diversity of patient samples was higher than that of open-air controls and differentially abundant taxa were detected between these conditions, possibly reflecting a true microbiota that is present in clinically uninfected joint implants. However, positive control-associated artifacts and DNA extraction methodology significantly affected sequencing results. As well, sequencing failed to identify Cutibacterium acnes in most culture- and PCR-positive samples. These challenges limited characterization of bacteria in presumed aseptic implants, but genera were identified for further investigation. In all, we provide further support for the hypothesis that there is likely a microbiota present in clinically uninfected joint implants, and we show that methods other than 16S rRNA gene sequencing may be ideal for its characterization. This work has illuminated the importance of further study of microbiota of clinically uninfected joint implants with novel molecular and computational tools to further eliminate contaminants and artifacts that arise in low bacterial abundance samples.
format	article
author	Charles Carr Hannah Wilcox Jeremy P Burton Sharanya Menon Kait F Al David O'Gorman Brent A Lanting Edward M Vasarhelyi Michael Neufeld Matthew G Teeter
author_facet	Charles Carr Hannah Wilcox Jeremy P Burton Sharanya Menon Kait F Al David O'Gorman Brent A Lanting Edward M Vasarhelyi Michael Neufeld Matthew G Teeter
author_sort	Charles Carr
title	Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
title_short	Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
title_full	Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
title_fullStr	Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
title_full_unstemmed	Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
title_sort	deciphering the low abundance microbiota of presumed aseptic hip and knee implants.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/91fd2eddefbe4f2da652830e118b5a35
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Deciphering the low abundance microbiota of presumed aseptic hip and knee implants.

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