Cargando…

Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing

OBJECTIVES: Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Mei-Feng, Chang, Chih-Hsiang, Chiang-Ni, Chuan, Hsieh, Pang-Hsin, Shih, Hsin-Nung, Ueng, Steve W. N., Chang, Yuhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719533/
https://www.ncbi.nlm.nih.gov/pubmed/31537994
http://dx.doi.org/10.1302/2046-3758.88.BJR-2019-0003.R2
_version_ 1783447956393820160
author Chen, Mei-Feng
Chang, Chih-Hsiang
Chiang-Ni, Chuan
Hsieh, Pang-Hsin
Shih, Hsin-Nung
Ueng, Steve W. N.
Chang, Yuhan
author_facet Chen, Mei-Feng
Chang, Chih-Hsiang
Chiang-Ni, Chuan
Hsieh, Pang-Hsin
Shih, Hsin-Nung
Ueng, Steve W. N.
Chang, Yuhan
author_sort Chen, Mei-Feng
collection PubMed
description OBJECTIVES: Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect unculturable, unsuspected, and unviable pathogens. In this study, we investigated the use of 16S rRNA metagenomics for detection of bacterial pathogens in synovial fluid (SF) from patients with hip or knee PJI. METHODS: We analyzed the bacterial composition of 22 SF samples collected from 11 patients with PJIs (first- and second-stage surgery). The V3 and V4 region of bacteria was assessed by comparing the taxonomic distribution of the 16S rDNA amplicons with microbiome sequencing analysis. We also compared the results of bacterial detection from different methods including 16S metagenomics, traditional cultures, and targeted Sanger sequencing. RESULTS: Polymicrobial infections were not only detected, but also characterized at different timepoints corresponding to first- and second-stage exchange arthroplasty. Similar taxonomic distributions were obtained by matching sequence data against SILVA, Greengenes, and The National Center for Biotechnology Information (NCBI). All bacteria isolated from the traditional culture could be further identified by 16S metagenomics and targeted Sanger sequencing. CONCLUSION: The data highlight 16S rRNA metagenomics as a suitable and promising method to detect and identify infecting bacteria, most of which may be uncultivable. Importantly, the method dramatically reduces turnaround time to two days rather than approximately one week for conventional cultures. Cite this article: M-F. Chen, C-H. Chang, C. Chiang-Ni, P-H. Hsieh, H-N. Shih, S. W. N. Ueng, Y. Chang. Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing. Bone Joint Res 2019;8:367–377. DOI: 10.1302/2046-3758.88.BJR-2019-0003.R2.
format Online
Article
Text
id pubmed-6719533
institution National Center for Biotechnology Information
language English
publishDate 2019
record_format MEDLINE/PubMed
spelling pubmed-67195332019-09-19 Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing Chen, Mei-Feng Chang, Chih-Hsiang Chiang-Ni, Chuan Hsieh, Pang-Hsin Shih, Hsin-Nung Ueng, Steve W. N. Chang, Yuhan Bone Joint Res Infection OBJECTIVES: Prosthetic joint infection (PJI) is the most common cause of arthroplasty failure. However, infection is often difficult to detect by conventional bacterial cultures, for which false-negative rates are 23% to 35%. In contrast, 16S rRNA metagenomics has been shown to quantitatively detect unculturable, unsuspected, and unviable pathogens. In this study, we investigated the use of 16S rRNA metagenomics for detection of bacterial pathogens in synovial fluid (SF) from patients with hip or knee PJI. METHODS: We analyzed the bacterial composition of 22 SF samples collected from 11 patients with PJIs (first- and second-stage surgery). The V3 and V4 region of bacteria was assessed by comparing the taxonomic distribution of the 16S rDNA amplicons with microbiome sequencing analysis. We also compared the results of bacterial detection from different methods including 16S metagenomics, traditional cultures, and targeted Sanger sequencing. RESULTS: Polymicrobial infections were not only detected, but also characterized at different timepoints corresponding to first- and second-stage exchange arthroplasty. Similar taxonomic distributions were obtained by matching sequence data against SILVA, Greengenes, and The National Center for Biotechnology Information (NCBI). All bacteria isolated from the traditional culture could be further identified by 16S metagenomics and targeted Sanger sequencing. CONCLUSION: The data highlight 16S rRNA metagenomics as a suitable and promising method to detect and identify infecting bacteria, most of which may be uncultivable. Importantly, the method dramatically reduces turnaround time to two days rather than approximately one week for conventional cultures. Cite this article: M-F. Chen, C-H. Chang, C. Chiang-Ni, P-H. Hsieh, H-N. Shih, S. W. N. Ueng, Y. Chang. Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing. Bone Joint Res 2019;8:367–377. DOI: 10.1302/2046-3758.88.BJR-2019-0003.R2. 2019-09-03 /pmc/articles/PMC6719533/ /pubmed/31537994 http://dx.doi.org/10.1302/2046-3758.88.BJR-2019-0003.R2 Text en © 2019 Author(s) et al. https://creativecommons.org/licenses/by-nc/4.0/ Open Access This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (CC BY-NC 4.0) licence (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed.
spellingShingle Infection
Chen, Mei-Feng
Chang, Chih-Hsiang
Chiang-Ni, Chuan
Hsieh, Pang-Hsin
Shih, Hsin-Nung
Ueng, Steve W. N.
Chang, Yuhan
Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title_full Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title_fullStr Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title_full_unstemmed Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title_short Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing
title_sort rapid analysis of bacterial composition in prosthetic joint infection by 16s rrna metagenomic sequencing
topic Infection
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719533/
https://www.ncbi.nlm.nih.gov/pubmed/31537994
http://dx.doi.org/10.1302/2046-3758.88.BJR-2019-0003.R2
work_keys_str_mv AT chenmeifeng rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT changchihhsiang rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT chiangnichuan rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT hsiehpanghsin rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT shihhsinnung rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT uengstevewn rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing
AT changyuhan rapidanalysisofbacterialcompositioninprostheticjointinfectionby16srrnametagenomicsequencing