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

Authors :
Hao Li
Jun Fu
Niu Erlong
Rui LI
Chi Xu
Libo Hao
Jiying Chen
Wei Chai
Source :
BMC Infectious Diseases, Vol 23, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14712334
Volume :
23
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.f70d9a3a3c449979ddbf92f1322a16e
Document Type :
article
Full Text :
https://doi.org/10.1186/s12879-023-08390-x