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. 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. 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

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.

Osteoarthritis is a global problem and the treatment of early disease is a clear area of unmet clinical need. Treatment strategies include cell therapies utilising chondrocytes e.g. autologous chondrocyte implantation and mesenchymal stem/stromal cells (MSCs) e.g. microfracture. The result of repair is often considered suboptimal as the goal of treatment is a more accurate regeneration of the tissue, hyaline cartilage, which requires a more detailed understanding of relevant biological signalling pathways. In this study, we describe a modulator of regulatory pathways common to both chondrocytes and MSCs. The chondrocytes thought to be cartilage progenitors are reported to reside in the superficial zone of articular cartilage and are considered to have the same developmental origin as MSCs present in the synovium. They are relevant to cartilage homeostasis and, like MSCs, are increasingly identified as candidates for joint repair and regenerative cell therapy. Both chondrocytes and MSCs can be regulated by the Wnt and TGFβ pathways. Dishevelled Binding Antagonist of Beta-Catenin (Dact) family of proteins is an important modulator of Wnt and TGFβ pathways. These pathways are key to MSC and chondrocyte function but, to our knowledge, the role of DACT protein has not been studied in these cells. DACT1 and DACT2 were localised by immunohistochemistry in the developing joints of mouse embryos and in adult human cartilage obtained from knee replacement. RNAi of DACT1 and DACT2 was performed on isolated chondrocytes and MSCs from human bone marrow. Knockdown efficiency and cell morphology was confirmed by qPCR and immunofluorescence. To understand which pathways are affected by DACT1, we performed next-generation sequencing gene expression analysis (RNAseq) on cells where DACT1 had been reduced by RNAi. Top statistically significant (p < 0 .05) 200 up and downregulated genes were analysed with Ingenuity® Pathway Analysis software. We observed DACT1 and DACT2 in chondrocytes throughout the osteoarthritic tissue, including in chondrocytes forming cell clusters. On the non-weight bearing and visually undamaged cartilage, DACT1 and DACT2 was localised to the articular surface. Furthermore, in mouse embryos (E.15.5), we observed DACT2 at the interzones, sites of developing synovial joints, suggesting that DACT2 has a role in cartilage progenitor cells. We subsequently analysed the expression of DACT1 and DACT2 in MSCs and found that both are expressed in synovial and bone marrow-derived MSCs. We then performed an RNAi knockdown experiment. DACT1 knockdown in both chondrocyte and MSCs caused the cells to undergo apoptosis within 24 hours. The RNA-seq study of DACT1 silenced bone marrow-derived MSCs, from 4 different human subjects, showed that loss of DACT1 has an effect on the expression of genes involved in both TGFβ and Wnt pathways and putative link to relevant cell regulatory pathways. In summary, we describe for the first time, the presence and biological relevance of DACT1 and DACT2 in chondrocytes and MSCs. Loss of DACT1 induced cell death in both chondrocytes and MSCs, with RNA-seq analysis revealing a direct impact on transcript levels of genes involved in the Wnt and TFGβ signalling, key regulatory pathways in skeletal development and repair