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

Bone & Joint Research

article

Mei-Feng Chen¹  Chih-Hsiang Chang¹  Chuan Chiang-Ni⁴  Pang-Hsin Hsieh¹  Hsin-Nung Shih¹  Steve W. N. Ueng¹  Yuhan Chang¹ 

[1] Bone and Joint Research Center, Chang Gung Memorial Hospital;Department of Orthopaedic Surgery, Chang Gung Memorial Hospital;Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University. Taoyuan;Department of Microbiology and Immunology, College of Medicine, Chang Gung University;Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital. Taoyuan

关键词: Prosthetic joint infection;    16S metagenomics;    Synovial fluid;    Bacterial composition;    Polymicrobial infection;   

DOI  :  10.1302/2046-3758.88.BJR-2019-0003.R2

学科分类：骨科学

来源: British Editorial Society Of Bone And Joint Surgery

【 摘 要 】

ObjectivesProsthetic 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.MethodsWe 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.ResultsPolymicrobial 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.ConclusionThe 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.

【 授权许可】

CC BY-NC