Aims. The aim of this study was to evaluate the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens from synovial fluid of prosthetic joint infection (PJI) patients. Methods. A group of 75 patients who underwent revision knee or hip arthroplasties were enrolled prospectively. Ten patients with primary arthroplasties were included as negative controls. Synovial fluid was collected for mNGS analysis. Optimal thresholds were determined to distinguish pathogens from background microbes. Synovial fluid, tissue, and sonicate fluid were obtained for culture. Results. A total of 49 PJI and 21 noninfection patients were finally included. Of the 39 culture-positive PJI cases, mNGS results were positive in 37 patients (94.9%), and were consistent with culture results at the genus level in 32 patients (86.5%) and at the species level in 27 patients (73.0%). Metagenomic next-generation sequencing additionally identified 15 pathogens from five culture-positive and all ten culture-negative PJI cases, and even one pathogen from one noninfection patient, while yielding no positive findings in any primary arthroplasty. However, seven pathogens identified by culture were missed by mNGS. The sensitivity of mNGS for diagnosing PJI was 95.9%, which was significantly higher than that of comprehensive culture (79.6%; p = 0.014). The specificity is similar between mNGS and comprehensive culture (95.2% and 95.2%, respectively; p = 1.0). Conclusion. Metagenomic next-generation sequencing can effectively identify pathogens from synovial fluid of PJI patients, and demonstrates high accuracy in diagnosing PJI. Cite this article: Bone Joint Res 2020;9(7):440–449

Aims. This aim of this study was to analyze the detection rate of rare pathogens in bone and joint infections (BJIs) using metagenomic next-generation sequencing (mNGS), and the impact of mNGS on clinical diagnosis and treatment. Methods. A retrospective analysis was conducted on 235 patients with BJIs who were treated at our hospital between January 2015 and December 2021. Patients were divided into the no-mNGS group (microbial culture only) and the mNGS group (mNGS testing and microbial culture) based on whether mNGS testing was used or not. Results. A total of 147 patients were included in the no-mNGS group and 88 in the mNGS group. The mNGS group had a higher detection rate of rare pathogens than the no-mNGS group (21.6% vs 10.2%, p = 0.016). However, the mNGS group had lower rates of antibiotic-related complications, shorter hospital stays, and higher infection control rates compared with the no-mNGS group (p = 0.017, p = 0.003, and p = 0.028, respectively), while there was no significant difference in the duration of antibiotic use (p = 0.957). In culture-negative cases, the mNGS group had lower rates of antibiotic-related complications, shorter hospital stays, and a higher infection control rate than the no-mNGS group (p = 0.036, p = 0.033, p = 0.022, respectively), while there was no significant difference in the duration of antibiotic use (p = 0.748). Conclusion. mNGS improves detection of rare pathogens in BJIs. mNGS testing reduces antibiotic-related complications, shortens hospital stay and antibiotic use duration, and improves treatment success rate, benefits which are particularly evident in culture-negative cases. Cite this article: Bone Joint Res 2024;13(8):401–410

Aims. Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity. Next-generation sequencing (NGS) is a potentially powerful tool that is now commercially available. The purpose of this study was to compare the diagnostic accuracy of NGS, polymerase chain reaction (PCR), conventional culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al in the diagnosis of PJI. Methods. In this retrospective study, aspirates or tissue samples were collected in 30 revision and 86 primary arthroplasties for routine diagnostic investigation for PJI and sent to the laboratory for NGS and PCR. Concordance along with statistical differences between diagnostic studies were calculated. Results. Using the MSIS criteria to diagnose PJI as the reference standard, the sensitivity and specificity of NGS were 60.9% and 89.9%, respectively, while culture resulted in sensitivity of 76.9% and specificity of 95.3%. PCR had a low sensitivity of 18.4%. There was no significant difference based on sample collection method (tissue swab or synovial fluid) (p = 0.760). There were 11 samples that were culture-positive and NGS-negative, of which eight met MSIS criteria for diagnosing infection. Conclusion. In our series, NGS did not provide superior sensitivity or specificity results compared to culture. PCR has little utility as a standalone test for PJI diagnosis with a sensitivity of only 18.4%. Currently, several laboratory tests for PJI diagnosis should be obtained along with the overall clinical picture to help guide decision-making for PJI treatment. Cite this article: Bone Joint J 2021;103-B(1):26–31

Aim. Surgical management of PJI remains challenging with patients failing treatment despite the best efforts. An important question is whether these later failures reflect reinfection or the persistence of infection. Proponents of reinfection believe hosts are vulnerable to developing infection and new organisms emerge. The alternative hypothesis is that later failure is a result of an organism that was present in the joint but was not picked up by initial culture or was not a pathogen initially but became so under antibiotic pressure. This multicenter study explores the above dilemma. Utilizing next-generation sequencing (NGS), we hypothesize that failures after two-stage exchange arthroplasty can be caused by an organism that was present at the time of initial surgery but not isolated by culture. Method. This prospective study involving 15 institutions collected samples from 635 revision total hip(n=310) and knee(n=325) arthroplasties. Synovial fluid, tissue and swabs were obtained intraoperatively for NGS analysis. Patients were classified per 2018 Consensus definition of PJI. Treatment failure was defined as reoperation for infection that yielded positive cultures, during minimum 1-year follow-up. Concordance of the infecting pathogen cultured at failure with NGS analysis at initial revision was determined. Results. Among the total cohort, 203 revisions were considered infected and 432 were aseptic (based on ICM-criteria). Of the infected cases, 157 were NGS-positive and 46 NGS-negative. Twenty-nine ICM-positive patients (29/157;18.5%) failed by reoperation with an organism confirmed on culture. In 23 of these (23/29;79.3%), the organism at failure was present on NGS at initial revision. The remaining 6 cases detected discordant organisms between initial NGS and culture at failure. Of the 432 ICM-negative patients, NGS identified microbes in 48.1% (208/432) of “aseptic” revisions, and 17 of these failed. Thirteen of the 17 failures (76.5%) were due to an organism previously detected by NGS at initial revision. Conclusion. Our collaborative findings suggest that most failures (79.3%) by infection recurrence could be attributed to an organism previously detected by NGS at index revision surgery

Aim. metagenomic next-generation sequencing (mNGS) has shown to be a useful method for pathogen detection in prosthetic joint infections (PJI). The technique promises to minimize the PJIs without the known causative agent. Our study aimed to compare diagnostic accuracies of cultures and mNGS. Method. In this study, a meta-analysis following PRISMA recommendations was performed. PubMed and OVID Medline databases were used for article search. The studies using mNGS whole-genome sequencing method and the ones where PJI diagnosis was based on one of the currently recognized criteria were included. Studies were excluded if they comprised less than twenty cases, the ones with insufficient data for the analyses (true positive, true negative, false positive and false negative values for both mNGS and culture results) and publications with strong duplication bias. Univariate metanalysis using a random-effect model has been performed in R studio with a “meta” package. Pooled sensitivity and pooled specificity were calculated. Results. Seven studies with a total of 822 cases were included in the meta-analysis, 476 cases defined as PJI and 346 controls. Two studies used IDSA (Infectious Diseases Society of America) diagnostic criteria and the Illumina HiSeq 2500 platform for sequencing and five studies used MSIS (MusculoSkeletal Infection society). Four of those used the BGISEQ-500 sequencing platform. For one study there was no data available. Studies were performed on prosthetic hip and knee joints. Through meta-analysis, it was observed that mNGS technique is more sensitive than cultures with 90% (CI 79%– 95%) and 74% (CI 68%-79%) respectively (p=0.006). The specificity between methods was similar, for mNGS reaching 94% (CI 89%-96%) and for cultures 97% (CI 90%-99%) (p=0.285). In the PJI group, 117 new possible pathogens that were not isolated by microbiological culture were detected by the mNGS, most frequently anaerobes and coagulase-negative staphylococci both in 20/117 (17.1%) cases. Fourteen new organisms were detected in the control group and were mostly regarded as contaminants. Conclusions. Metagenomic sequencing has shown to be more sensitive than microbiological cultures in pathogen detection and thus has a great potential to improve the diagnosis and treatment of PJI. More studies on different prosthetic joints and comparing different diagnostic criteria for PJI would be needed to better understand the true diagnostic power of this method

Aim. The clinical relevance of microbial DNA detected via next-generation sequencing (NGS) remains unknown. This multicenter study was conceived to: 1) identify species on NGS that may predict periprosthetic joint infection (PJI), then 2) build a predictive model for PJI in a developmental cohort, and 3) validate predictive utility of the model in a separate multi-institutional cohort. Method. Fifteen institutions prospectively collected samples from 194 revision TKA and 184 revision THA between 2017–2019. Synovial fluid, tissue and swabs were obtained intraoperatively and sent to MicrogenDx (Lubbock, TX) for NGS analysis. Reimplantations were excluded. Patients were classified per the 2018 ICM definition of PJI. DNA analysis of community similarities (ANCOM) was used to identify 17 bacterial species of 294 (W-value>50) for differentiating infected vs. noninfected cases. Logistic regression with LASSO selection and random-forest algorithms were then used to build a model for predicting PJI. ICM classification was the response variable (gold-standard) and species identified through ANCOM were predictors. Patients were randomly allocated 1:1 into training and validation sets. Using the training set, a model for PJI diagnosis was generated. The entire model-building procedure and validation was iterated 1000 times. Results. The model's assignment accuracy was 75.9%. There was high accuracy in true-negative and false-negative classification using this model, which has previously been a criticism of NGS. Specificity was 97.1%, PPV 75.0% and NPV 76.2%. On comparison of abundance between ICM-positive and ICM-negative patients, Staphylococcus aureus was the strongest contributor (F=0.99) to model predictive power. In contrast, Cutibacterium acnes was less predictive (F=0.309) and abundant across infected and noninfected revisions. Discussion. This is the first study to utilize predictive algorithms on a large multicenter dataset to transform analytic NGS data into a clinically relevant diagnostic model. Our collaborative findings suggest NGS may be an independent adjunct for PJI diagnosis, while also facilitating pathogen identification. Future work applying machine-learning will improve accuracy and utility of NGS

Next-generation sequencing (NGS) is a well-established technique for amplification and sequencing of DNA and has recently gained much attention in many fields of medicine. Our aim was to evaluate the ability of NGS in identifying the causative organism(s) in patients with periprosthetic joint infection (PJI). In this prospective study samples were collected from 78 revision total hip arthroplasties. Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to the laboratory for NGS analysis. Deep tissue specimens were also sent to the institutional lab for culture. PJI was diagnosed using the Musculoskeletal infection society (MSIS) definition of PJI. Thirty-four revisions were considered infected; culture was positive in 25 of these (25/34, 73.5%), while NGS was positive in 26 (26/34, 76.4%). Among the positive cultures, complete concordance between NGS and culture in 21 cases (21/25, 84.0%). 4 cases were discordant. Among these cases, 3 cases were culture-positive and NGS-negative, while 1 was both positive on NGS and culture for disparate organisms. Among the 9 cases of culture-negative PJI(CN-PJI), NGS was able to identify an organism in 4 cases (4/9, 44.4%). The remaining 5 cases were negative on both NGS and culture (5/9, 55.6%). Forty-four revisions were considered to be aseptic; NGS exclusively identified microbes in 7 of 44 “aseptic” revisions (15.9%) and culture exclusively isolated an organism in 3 of 44 cases (6.8%). Both NGS and culture were positive in 1 of case however the result was discordant. The remaining cases (33/44, 75.0%) were both NGS and culture negative. NGS detected several organisms in most positive samples, with a greater number of organisms detected in aseptic compared to septic cases (7 vs. 3.7, respectively). NGS may be a promising technique for identifying the infecting organism in PJI. Our findings suggest that some cases of PJI may be polymicrobial that escape detection using conventional culture

Aim

To date, no ultimate diagnostic gold standard for prosthetic joint infections (PJI) has been established. In recent years, next generation sequencing (NGS) has emerged as a promising new tool, especially in culture-negative samples. In this prospective study, we performed metagenomic analysis using 16S rRNA V3-V4 amplicon NGS in samples from patients with suspected PJI.

Introduction

Identification of the causative pathogen in musculoskeletal infection is critical as it directs further treatment. Fracture-related infection is often associated with ‘no growth’ in standard culture. We investigated the efficiency of two alternate methods to identify the causative pathogen, namely extended bacterial culture and 16Sr RNA gene sequence analysis with next generation sequencing (NGS) in ‘culture negative’ fracture related infections.

Introduction

Despite recent advances in the diagnosis of periprosthetic joint infection(PJI), identifying the infecting organism continues to be a challenge, with up to a third of PJIs reported to have negative cultures. Current molecular techniques have thus far been unable to replace culture as the gold standard for isolation of the infecting pathogen. Next- generation sequencing(NGS) is a well-established technique for comprehensively sequencing the entire pathogen DNA in a given sample and has recently gained much attention in many fields of medicine. Our aim was to evaluate the ability of NGS in identifying the causative organism(s) in patients with PJI.

Background

Recent reports demonstrate that Next Generation Sequencing (NGS) facilitates pathogen identification in the context of culture-negative PJI; however the clinical relevance of the polymicrobial genomic signal often generated remains unknown. This study was conceived to explore: (1) the ability of NGS to identify pathogens in culture-negative PJI; and (2) determine whether organisms detected by NGS, as part of a prospective observational study, had any role in later failure of patients undergoing surgical treatment for PJI.

Aim

Periprosthetic joint infection is an increasing reason for revision surgery. Tissue cultures are a standard (std.) diagnostic procedure but may be hindered by bacteria that are difficult to cultivate. The use of dithiothreitol (DTT) to detach the formed biofilm has been proposed to improve the diagnostic security. The aim was to compare the diagnosis results using the microDTTect device with the routine PJI diagnostics and next generation sequencing (NGS) from DTT treated explants.

Introduction

Next generation sequencing (NGS) has been shown to facilitate detection of microbes in a clinical sample, particularly in the setting of culture-negative periprosthetic joint infection (PJI). However, it is unknown whether every microbial DNA signal detected by NGS is clinically relevant. This multi-institutional study was conceived to 1) identify species detected by NGS that may predict PJI, then 2) build a predictive model for PJI in a developmental cohort; and 3) validate the predictive utility of the model in a separate multi-institutional cohort.

Introduction

Recent focus has queried whether of deoxyribonucleic acid (DNA) sequencing modalities of bacterial DNA found in periarticular fluid and tissues will improve in periprosthetic joint infection (PJI) diagnosis and organism identification diagnostic accuracy for periprosthetic joint infection The purpose of this study was to compare the diagnostic accuracy of next generation sequencing (NGS) to polymerase chain reaction (PCR) multiplex, and culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al. [1] in the diagnosis of periprosthetic knee infections.

Introduction

Recent focus has shifted towards the utilization of deoxyribonucleic acid (DNA) sequencing modalities in periprosthetic joint infection (PJI) diagnosis and organism identification. The purpose of this study was to compare the diagnostic accuracy of next generation sequencing (NGS) to polymerase chain reaction (PCR) multiplex, culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al. [1] in the diagnosis of periprosthetic hip infections.

Aims. The diagnosis of periprosthetic joint infection can be difficult due to the high rate of culture-negative infections. The aim of this study was to assess the use of next-generation sequencing for detecting organisms in synovial fluid. Materials and Methods. In this prospective, single-blinded study, 86 anonymized samples of synovial fluid were obtained from patients undergoing aspiration of the hip or knee as part of the investigation of a periprosthetic infection. A panel of synovial fluid tests, including levels of C-reactive protein, human neutrophil elastase, total neutrophil count, alpha-defensin, and culture were performed prior to next-generation sequencing. Results. Of these 86 samples, 30 were alpha-defensin-positive and culture-positive (Group I), 24 were alpha-defensin-positive and culture-negative (Group II) and 32 were alpha-defensin-negative and culture-negative (Group III). Next-generation sequencing was concordant with 25 results for Group I. In four of these, it detected antibiotic resistant bacteria whereas culture did not. In another four samples with relatively low levels of inflammatory biomarkers, culture was positive but next-generation sequencing was negative. A total of ten samples had a positive next-generation sequencing result and a negative culture. In five of these, alpha-defensin was positive and the levels of inflammatory markers were high. In the other five, alpha-defensin was negative and the levels of inflammatory markers were low. While next-generation sequencing detected several organisms in each sample, in most samples with a higher probability of infection, there was a predominant organism present, while in those presumed not to be infected, many organisms were identified with no predominant organism. Conclusion. Pathogens causing periprosthetic infection in both culture-positive and culture-negative samples of synovial fluid could be identified by next-generation sequencing. Cite this article: Bone Joint J 2018;100-B:127–33

Aims. The decrease in the number of satellite cells (SCs), contributing to myofibre formation and reconstitution, and their proliferative capacity, leads to muscle loss, a condition known as sarcopenia. Resistance training can prevent muscle loss; however, the underlying mechanisms of resistance training effects on SCs are not well understood. We therefore conducted a comprehensive transcriptome analysis of SCs in a mouse model. Methods. We compared the differentially expressed genes of SCs in young mice (eight weeks old), middle-aged (48-week-old) mice with resistance training intervention (MID+ T), and mice without exercise (MID) using next-generation sequencing and bioinformatics. Results. After the bioinformatic analysis, the PI3K-Akt signalling pathway and the regulation of actin cytoskeleton in particular were highlighted among the top ten pathways with the most differentially expressed genes involved in the young/MID and MID+ T/MID groups. The expression of Gng5, Atf2, and Rtor in the PI3K-Akt signalling pathway was higher in the young and MID+ T groups compared with the MID group. Similarly, Limk1, Arhgef12, and Araf in the regulation of the actin cytoskeleton pathway had a similar bias. Moreover, the protein expression profiles of Atf2, Rptor, and Ccnd3 in each group were paralleled with the results of NGS. Conclusion. Our results revealed that age-induced muscle loss might result from age-influenced genes that contribute to muscle development in SCs. After resistance training, age-impaired genes were reactivated, and age-induced genes were depressed. The change fold in these genes in the young/MID mice resembled those in the MID + T/MID group, suggesting that resistance training can rejuvenate the self-renewing ability of SCs by recovering age-influenced genes to prevent sarcopenia. Cite this article: Bone Joint Res 2022;11(2):121–133

Aims. As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients. Methods. In this prospective study, 177 specimens were collected from 59 revision arthroplasties, including periprosthetic tissues, synovial fluid, and prosthetic sonicate fluid. Each specimen was divided into two, one for mNGS and one for culture. The criteria of the Musculoskeletal Infection Society were used to define PJI (40 cases) and aseptic failure (19 cases). Results. The sensitivity and specificity of mNGS in the diagnosis of PJI were 95% and 94.7%, respectively, for all types of specimen. The sensitivity and specificity were 65% and 100%, respectively, for periprosthetic tissues, 87.5% and 94.7%, respectively, for synovial fluid, and 92.5% and 94.7%, respectively, for prosthetic sonicate fluid. The mNGS of prosthetic sonicate fluid outperformed that for other types of specimen in the rates of detection of pathogens (84.6%), sequencing reads (> ten-fold) and the rate of genome coverage (> five-fold). Conclusion. mNGS could serve as an accurate diagnostic tool in the detection of pathogens in patients with a PJI using three types of specimen. Due to its superior perfomance in identifying a pathogen, mNGS of prosthetic sonicate fluid provides the most value and may partly replace traditional tests such as bacteriological culture in these patients. Cite this article: Bone Joint J 2021;103-B(5):923–930

Aims. Metagenomic next-generation sequencing (mNGS) is useful in the diagnosis of infectious disease. However, while it is highly sensitive at identifying bacteria, it does not provide information on the sensitivity of the organisms to antibiotics. The purpose of this study was to determine whether the results of mNGS can be used to guide optimization of culture methods to improve the sensitivity of culture from intraoperative samples. Methods. Between July 2014 and October 2019, patients with suspected joint infection (JI) from whom synovial fluid (SF) was obtained preoperatively were enrolled. Preoperative aspirated SF was analyzed by conventional microbial culture and mNGS. In addition to samples taken for conventional microbial culture, some samples were taken for intraoperative culture to optimize the culture method according to the preoperative mNGS results. The demographic characteristics, medical history, laboratory examination, mNGS, and culture results of the patients were recorded, and the possibility of the optimized culture methods improving diagnostic efficiency was evaluated. Results. A total of 56 cases were included in this study. There were 35 cases of JI and 21 cases of non-joint infection (NJI). The sensitivity, specificity, and accuracy of intraoperative microbial culture after optimization of the culture method were 94.29%, 76.19%, and 87.5%, respectively, while those of the conventional microbial culture method were 60%, 80.95%, and 67.86%, respectively. Conclusion. Preoperative aspirated SF detected via mNGS can provide more aetiological information than preoperative culture, which can guide the optimization and improve the sensitivity of intraoperative culture. Cite this article: Bone Joint J 2021;103-B(1):39–45