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Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation

AIMS: Periprosthetic joint infection (PJI) is one of the most serious complications after total joint arthroplasty (TJA) but the characterization of the periprosthetic environment microbiome after TJA remains unknown. Here, we performed a prospective study based on metagenomic next-generation sequen...

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Autores principales: Li, Hao, Fu, Jun, Erlong, Niu, LI, Rui, Xu, Chi, Hao, Libo, Chen, Jiying, Chai, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286366/
https://www.ncbi.nlm.nih.gov/pubmed/37349686
http://dx.doi.org/10.1186/s12879-023-08390-x
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author Li, Hao
Fu, Jun
Erlong, Niu
LI, Rui
Xu, Chi
Hao, Libo
Chen, Jiying
Chai, Wei
author_facet Li, Hao
Fu, Jun
Erlong, Niu
LI, Rui
Xu, Chi
Hao, Libo
Chen, Jiying
Chai, Wei
author_sort Li, Hao
collection PubMed
description AIMS: Periprosthetic joint infection (PJI) is one of the most serious complications after total joint arthroplasty (TJA) but the characterization of the periprosthetic environment microbiome after TJA remains unknown. Here, we performed a prospective study based on metagenomic next-generation sequencing to explore the periprosthetic microbiota in patients with suspected PJI. METHODS: We recruited 28 patients with culture-positive PJI, 14 patients with culture-negative PJI, and 35 patients without PJI, which was followed by joint aspiration, untargeted metagenomic next-generation sequencing (mNGS), and bioinformatics analysis. Our results showed that the periprosthetic environment microbiome was significantly different between the PJI group and the non-PJI group. Then, we built a “typing system” for the periprosthetic microbiota based on the RandomForest Model. After that, the ‘typing system’ was verified externally. RESULTS: We found the periprosthetic microbiota can be classified into four types generally: “Staphylococcus type,” “Pseudomonas type,” “Escherichia type,” and “Cutibacterium type.” Importantly, these four types of microbiotas had different clinical signatures, and the patients with the former two microbiota types showed obvious inflammatory responses compared to the latter ones. Based on the 2014 Musculoskeletal Infection Society (MSIS) criteria, clinical PJI was more likely to be confirmed when the former two types were encountered. In addition, the Staphylococcus spp. with compositional changes were correlated with C-reactive protein levels, the erythrocyte sedimentation rate, and the synovial fluid white blood cell count and granulocyte percentage. CONCLUSIONS: Our study shed light on the characterization of the periprosthetic environment microbiome in patients after TJA. Based on the RandomForest model, we established a basic “typing system” for the microbiota in the periprosthetic environment. This work can provide a reference for future studies about the characterization of periprosthetic microbiota in periprosthetic joint infection patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08390-x.
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spelling pubmed-102863662023-06-23 Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation Li, Hao Fu, Jun Erlong, Niu LI, Rui Xu, Chi Hao, Libo Chen, Jiying Chai, Wei BMC Infect Dis Research AIMS: Periprosthetic joint infection (PJI) is one of the most serious complications after total joint arthroplasty (TJA) but the characterization of the periprosthetic environment microbiome after TJA remains unknown. Here, we performed a prospective study based on metagenomic next-generation sequencing to explore the periprosthetic microbiota in patients with suspected PJI. METHODS: We recruited 28 patients with culture-positive PJI, 14 patients with culture-negative PJI, and 35 patients without PJI, which was followed by joint aspiration, untargeted metagenomic next-generation sequencing (mNGS), and bioinformatics analysis. Our results showed that the periprosthetic environment microbiome was significantly different between the PJI group and the non-PJI group. Then, we built a “typing system” for the periprosthetic microbiota based on the RandomForest Model. After that, the ‘typing system’ was verified externally. RESULTS: We found the periprosthetic microbiota can be classified into four types generally: “Staphylococcus type,” “Pseudomonas type,” “Escherichia type,” and “Cutibacterium type.” Importantly, these four types of microbiotas had different clinical signatures, and the patients with the former two microbiota types showed obvious inflammatory responses compared to the latter ones. Based on the 2014 Musculoskeletal Infection Society (MSIS) criteria, clinical PJI was more likely to be confirmed when the former two types were encountered. In addition, the Staphylococcus spp. with compositional changes were correlated with C-reactive protein levels, the erythrocyte sedimentation rate, and the synovial fluid white blood cell count and granulocyte percentage. CONCLUSIONS: Our study shed light on the characterization of the periprosthetic environment microbiome in patients after TJA. Based on the RandomForest model, we established a basic “typing system” for the microbiota in the periprosthetic environment. This work can provide a reference for future studies about the characterization of periprosthetic microbiota in periprosthetic joint infection patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08390-x. BioMed Central 2023-06-22 /pmc/articles/PMC10286366/ /pubmed/37349686 http://dx.doi.org/10.1186/s12879-023-08390-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Li, Hao
Fu, Jun
Erlong, Niu
LI, Rui
Xu, Chi
Hao, Libo
Chen, Jiying
Chai, Wei
Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title_full Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title_fullStr Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title_full_unstemmed Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title_short Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
title_sort characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286366/
https://www.ncbi.nlm.nih.gov/pubmed/37349686
http://dx.doi.org/10.1186/s12879-023-08390-x
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