Better choice of the type of specimen used for untargeted metagenomic sequencing in the diagnosis of periprosthetic joint infections

Diagnostic accuracy of 16S rDNA PCR, multiplex PCR and metagenomic next-generation sequencing in periprosthetic joint infections: a systematic review and meta-analysis

BACKGROUND

The diagnostic accuracy of 16S rDNA PCR, multiplex PCR (mPCR), and metagenomic next-generation sequencing (mNGS) in periprosthetic joint infections (PJIs) remains unclear.

OBJECTIVES

This study aims to evaluate the diagnostic accuracy of 16S rDNA PCR, mPCR, and mNGS in PJI.

METHODS

Data sources: Data sources included PubMed and Embase (January 1, 2000-March 1, 2024), with no language restrictions.

STUDY ELIGIBILITY CRITERIA

Studies containing sufficient data to construct a 2 × 2 contingency table allowing for sensitivity and specificity calculation were considered.

PARTICIPANTS

Participants included adults (≥18 years) with PJI and appropriate control groups.

TESTS

Tests included 16S rDNA PCR, mPCR, and mNGS.

REFERENCE STANDARD

Diagnosis required adherence to Musculoskeletal Infection Society, Infectious Diseases Society of America, International Consensus Meeting, European Bone and Joint Infection Society criteria. Studies employing alternative author-defined criteria were included only if they did not rely solely on positive cultures to define PJI.

ASSESSMENT OF RISK OF BIAS

Quality Assessment of Diagnostic Accuracy Studies 2 was used.

METHODS OF DATA SYNTHESIS

A bivariate model calculated pooled diagnostic odds ratios (DORs), sensitivities, and specificities, each with 95% CIs.

RESULTS

Seventy-nine studies were included, comprising 3940 PJI cases and 4700 uninfected controls. Pooled sensitivity/specificity were 80.0% (95% CI, 75.4-84.3%)/94.0% (95% CI, 91-96%) for 16S rDNA PCR; 62.2% (52.5-70.9%)/96.2% (93.2-97.9%) for mPCR; and 88.6% (83.3-92.4%)/93.2% (89.5-95.6%) for mNGS. Notably, mNGS had the highest DOR (105.9; 95% CI, 60-186.9). A sensitivity analysis excluding lower-quality studies resulted in increased DORs for all methods.

DISCUSSION

These molecular techniques display strong diagnostic accuracy for identifying PJI. Although mNGS yielded the highest DOR, numerous technical and practical challenges preclude its routine use for PJI diagnosis. Significant heterogeneity across studies warrants cautious interpretation and underscores the need for future comparative research.

State-of-the-Art Metagenomic Sequencing and Its Role in the Diagnosis of Periprosthetic Joint Infections

Metagenomic next-generation sequencing (mNGS) is increasingly being recognized as a valuable diagnostic tool for periprosthetic joint infections (PJIs). This study reviews the diagnostic utility of mNGS, highlighting its improved sensitivity in detecting pathogens, particularly in culture-negative and polymicrobial infections. However, the clinical application of this method is hindered by challenges such as the prevalence of host DNA, the necessity for extensive bioinformatic analysis, and the potential for contamination, which can lead to misinterpretation of results. As mNGS continues to evolve, it holds significant potential to improve the management of PJI and enhance the application of precision medicine in orthopedic infections.

Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases

Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput sequencing to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines the fundamental principles, sequencing workflow, and platforms utilized in mNGS technology. The methodological backbone involves shotgun sequencing of total nucleic acids extracted from diverse sample types, enabling simultaneous detection of bacteria, viruses, fungi, and parasites without prior knowledge of the infectious agent. Key advantages of mNGS include its capability to identify rare, novel, or unculturable pathogens, providing a more comprehensive view of microbial communities compared to traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, and the need for optimized sample preparation protocols remain significant hurdles. The application of mNGS across various systemic infections highlights its clinical utility. Case studies discussed in this review illustrate its efficacy in diagnosing respiratory tract infections, bloodstream infections, central nervous system infections, gastrointestinal infections, and others. By rapidly identifying pathogens and their genomic characteristics, mNGS facilitates timely and targeted therapeutic interventions, thereby improving patient outcomes and infection control measures. Looking ahead, the future of mNGS in infectious disease diagnostics appears promising. Advances in bioinformatics tools and sequencing technologies are anticipated to streamline data analysis, enhance sensitivity and specificity, and reduce turnaround times. Integration with clinical decision support systems promises to further optimize mNGS utilization in routine clinical practice. In conclusion, mNGS represents a paradigm shift in the field of infectious disease diagnostics, offering unparalleled insights into microbial diversity and pathogenesis. While challenges persist, ongoing technological advancements hold immense potential to consolidate mNGS as a pivotal tool in the armamentarium of modern medicine, empowering clinicians with precise, rapid, and comprehensive pathogen detection capabilities.

Higher diagnostic value of next-generation sequencing versus culture in periprosthetic joint infection: A systematic review and meta-analysis

BACKGROUND

The next-generation sequencing (NGS) has developed rapidly in the past decade and is becoming a promising diagnostic tool for periprosthetic infection (PJI). However, its diagnostic value for PJI is still uncertain. The purpose of this systematic review and meta-analysis was to evaluate the diagnostic value of NGS compared to culture.

METHODS

In this systematic review and meta-analysis, electronic databases including PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science and clinicaltrials.gov were searched for studies from inception to 12 November 2023. Diagnostic parameters, such as sensitivity, specificity, diagnostic odds ratio and area under the summary receiver-operating characteristic (SROC) curve (AUC), were calculated for the included studies. A systematic review and meta-analysis was performed.

RESULTS

A total of 22 studies with 2461 patients were included in our study. The pooled sensitivity, specificity and diagnostic odds ratio of NGS were 87% (95% confidence interval [CI]: 83-90), 94% (95% CI: 91-96) and 111 (95% CI: 70-177), respectively. On the other hand, the pooled sensitivity, specificity and diagnostic odds ratio of culture were 63% (95% CI: 58-67), 98% (95% CI: 96-99) and 93 (95% CI: 40-212), respectively. The SROC curve for NGS and culture showed that the AUCs are 0.96 (95% CI: 0.94-0.98) and 0.82 (95% CI: 0.79-0.86), respectively.

CONCLUSION

This systematic review and meta-analysis found NGS had higher sensitivity and diagnostic accuracy but slightly lower specificity than culture. Based on the pooled results, we suggested NGS may have the potential to be a new tool for the diagnosis of PJI.

LEVEL OF EVIDENCE

Level IV.

Detection of rare microorganisms in bone and joint infections by metagenomic next-generation sequencing

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.

Will previous antimicrobial therapy reduce the positivity rate of metagenomic next-generation sequencing in periprosthetic joint infections? A clinical study

Background

Metagenomic next-generation sequencing (mNGS) is a culture-independent massively parallel DNA sequencing technology and it has been widely used for rapid etiological diagnosis with significantly high positivity rate. Currently, clinical studies on evaluating the influence of previous antimicrobial therapy on positivity rate of mNGS in PJIs are rarely reported. The present study aimed to investigate whether the positivity rate of mNGS is susceptible to previous antimicrobial therapy.

Methods

We performed a prospective trial among patients who undergone hip or knee surgery due to periprosthetic joint infection (PJI) to compare the positivity rate of culture and mNGS between cases with and without previous antimicrobial therapy, and the positivity rates between cases with different antimicrobial-free intervals were also analysed.

Results

Among 131 included PJIs, 91 (69.5%) had positive cultures and 115 (87.8%) had positive mNGS results. There was no significant difference in the positivity rate of deep-tissue culture and synovial fluid mNGS between cases with and without previous antimicrobial therapy. The positivity rate of synovial fluid culture was higher in cases with previous antimicrobial therapy. The positivity rates of mNGS in synovial fluid decreased as the antimicrobial-free interval ranged from 4 to 14 days to 0 to 3 days.

Conclusion

mNGS is more advantageous than culture with a higher pathogen detection rate. However, our data suggested that antimicrobial agents may need to be discontinued more than 3 days before sampling to further increase the positivity rate of mNGS for PJIs.

The Clinical Impact of Metagenomic Next-Generation Sequencing for the Diagnosis of Periprosthetic Joint Infection

Background

Synovial fluid metagenomic next-generation sequencing was introduced into the diagnosis of periprosthetic joint infection (PJI) in recent years. However, the clinical impact of mNGS remains unknown. Therefore, we performed a prospective cohort study to evaluate the clinical impact of mNGS for PJI diagnosis.

Materials and Methods

Between April 2019 and April 2021, a total of 201 patients with suspected PJI were recruited in a high-volume PJI revision center. All patients underwent joint aspiration before surgeries and the obtained synovial fluids were sent to tests for the diagnosis of PJI. Based on the clinical evaluation of these patients, the patients were categorized into three groups: Group A: the mNGS reports were not acted upon. Group B: mNGS confirmed the standard diagnostic tests of PJI and generated identical clinical impact compared to standard diagnostic tests. Group C: mNGS results guided clinical therapy. Then, the concordance between synovial mNGS and cultures was analyzed. After that, multivariate regressions were performed to explore the "targeted populations" of mNGS tests.

Results

A total of 107 patients were diagnosed with PJI based on the 2014 MSIS criteria and there were 33, 123, 45 patients in the group A, B, C respectively. The predictive factors of mNGS inducing clinical impact compared to standard diagnostic tests were negative culture results (adjusted OR: 5.88), previous history of joint infection (adjusted OR: 5.97), polymicrobial PJI revealed by culture (adjusted OR: 4.39) and PJI identified by MSIS criteria (adjusted OR: 17.06).

Conclusion

When standard diagnostic tests for PJI were performed, about 22% of synovial fluid mNGS tests can change the treatment protocols built on standard diagnostic tests and affect the clinical practice. Thus, the use of synovial fluid mNGS in some "target" populations is more valuable compared to others such as patients with previous joint infection, polymicrobial PJI, and culture-negative PJI.

Evidence Level

Level I.

Higher sensitivity and accuracy of synovial next-generation sequencing in comparison to culture in diagnosing periprosthetic joint infection: a systematic review and meta-analysis

PURPOSE

The purpose of this meta-analysis was to compare the diagnostic parameters of synovial next-generation sequencing (NGS) and cultures in diagnosing periprosthetic joint infections (PJI).

METHODS

PubMed, Web of Science, Cochrane, and Google Scholar were searched from inception until 8 Jan 2022 for literature investigating the role of NGS in comparison to culture in the diagnosis of PJI. The studies were included if they investigated the diagnostic value of culture and NGS in diagnosing PJIs against the Musculoskeletal Infection Society (MSIS) criteria. Diagnostic parameters, such as sensitivity, specificity, positive predictive value, negative predictive value, positive-likelihood ratio, negative-likelihood ratio, accuracy, and area under the curve (AUC), were calculated for the included studies to evaluate the performance of NGS in comparison to culture in PJI diagnosis.

RESULTS

The total number of the included patients was 341 from seven articles. The pooled sensitivity, specificity, and diagnostic odds ratio of NGS were 94% (95% CI 91-97%), 89% (95% CI 82-95%), and 138.5 (95% CI 49.1-390.5), respectively. NGS has positive- and negative-likelihood ratios of 7.9 (95% CI 3.99-15.6) and 0.1 (95% CI 0.0-0.1), respectively. On the other hand, the pooled sensitivity, specificity, and diagnostic odds ratio of culture were 70% (95% CI 61-79%), 94% (95% CI 88-98%), and 28.0 (95% CI 12.6-62.2), respectively. The SROC curve for NGS showed that the accuracy (AUC) was 91.9%, and that the positive and negative predictive values were 8.6 (95% CI 5.0-19.5) and 0.1 (95% CI 0.0-0.1), respectively. While, culture SROC curve demonstrated that the accuracy (AUC) was 80.5% and the positive- and negative-likelihood ratio were 12.1 (95% CI 4.5-49.6) and 0.3 (95% CI 0.2-0.4).

CONCLUSIONS

NGS has a potential role in diagnosing hip and knee PJIs due to its high sensitivity, specificity, and accuracy. However, the sensitivity and specificity reported by the studies varied according to the time of synovial sampling (preoperative, postoperative, or mixed).

Comparison of microbial detection rates in microbial culture methods versus next-generation sequencing in patients with prosthetic joint infection: a systematic review and meta-analysis

BACKGROUND

Accurate diagnosis of prosthetic joint infection (PJI) enables early and effective treatment. However, there is currently no gold standard test for microbial detection of PJI and traditional synovial fluid culture is relatively insensitive. Recently, it has been reported that sonicating fluid culture and next-generation sequencing (NGS) improve microbial detection rates. Hence, we performed a systematic review and meta-analysis to compare microbial detection rates in microbial culture methods with and without sonication versus NGS.

METHODS

We systematically searched EMBASE, PubMed, Scopus, CINAHL, and Ichushi databases and other sources (previous reviews) until August 2022. We evaluated the detection rates of pathogens in NGS and microbial cultures using samples of synovial or sonicated fluid.

RESULTS

Of the 170 citations identified for screening, nine studies were included. Pooled analysis indicated that NGS had the highest detection rate among the microbial detection methods (NGS vs. sonicated, odds ratios [OR] 5.09, 95% confidential interval [CI] 1.67-15.50; NGS vs. synovial, OR 4.52, 95% CI 2.86-7.16). Sonicated fluid culture showed a higher detection rate than synovial fluid culture (OR 2.11, 95% CI 1.23-3.62).

CONCLUSION

NGS might be useful as a screening tool for culture-negative patients. In clinical settings, sonicated fluid culture is a practical method for diagnosing PJI.

Shotgun sequencing of sonication fluid for the diagnosis of orthopaedic implant-associated infections with Cutibacterium acnes as suspected causative agent

Orthopaedic implant-associated infections (OIAIs) due to Cutibacterium acnes can be difficult to diagnose. The aim of this pilot study was to determine if metagenomic next-generation sequencing (mNGS) can provide additional information to improve the diagnosis of C. acnes OIAIs. mNGS was performed on sonication fluid (SF) specimens derived from 24 implants. These were divided into three groups, based on culture results: group I, culture-negative (n = 4); group II, culture-positive for C. acnes (n = 10); and group III, culture-positive for other bacteria (n = 10). In group I, sequence reads from C. acnes were detected in only one SF sample, originating from a suspected case of OIAIs, which was SF and tissue culture-negative. In group II, C. acnes sequences were detected in 7/10 samples. In group III, C. acnes sequence reads were found in 5/10 samples, in addition to sequence reads that matched the bacterial species identified by culture. These samples could represent polymicrobial infections that were missed by culture. Taken together, mNGS was able to detect C. acnes DNA in more samples compared to culture and could be used to identify cases of suspected C. acnes OIAIs, in particular regarding possible polymicrobial infections, where the growth of C. acnes might be compromised due to a fast-growing bacterial species. However, since SF specimens are usually low-biomass samples, mNGS is prone to DNA contamination, possibly introduced during DNA extraction or sequencing procedures. Thus, it is advisable to set a sequence read count threshold, taking into account project- and NGS-specific criteria.

Direct detection and identification of periprosthetic joint infection pathogens by metagenomic next-generation sequencing

This study assessed the application of metagenomic next-generation sequencing in pathogen detection of periprosthetic joint infections. A total of 95 cases who previously had undergone hip and knee replacement undergoing revision from January 2018 to January 2021 were included in this study. Specimens of synovial fluid and deep-tissue were collected for culture and metagenomic next-generation sequencing, and patients were retrospectively categorized as infected or aseptic using the Musculoskeletal Infection Society criteria after revision surgery. The sensitivity, specificity, positive and negative predictive values were compared. A total of 36 cases had positive culture results and 59 cases had positive metagenomic next-generation sequencing results. Culture was positive in 34 infected cases (58.6%) and 2 aseptic cases (5.4%). Metagenomic next-generation sequencing was positive in 55 infected cases (94.8%) and 4 aseptic cases (10.8%). Five cases diagnosed with infection had other potential pathogens detected by metagenomic next-generation sequencing. Among the 24 culture-negative periprosthetic joint infections, metagenomic next-generation sequencing was able to identify potential pathogens in 21 cases (87.5%). From sampling to reporting, the average time needed for culture was 5.2 (95% CI 3.1-7.3) days, while that for metagenomic next-generation sequencing was 1.3 (95% CI 0.9-1.7) days. Metagenomic next-generation sequencing is more advantageous in pathogen detection of periprosthetic joint infection after total joint replacement, especially in patients with multiple infections or negative culture results.

Metagenomic Next-Generation Sequencing for Periprosthetic Joint Infections

Periprosthetic joint infection (PJI) after arthroplasty is a major complication, which requires significant resources, resulting in high costs for the medical system. In recent years, significant progress has been made in the diagnosis and treatment of periprosthetic infections, the identification of the pathogen being the central element in the establishment of targeted antibiotic therapy. Next-generation sequencing (NGS) or metagenomic NGS (mNGS) represents a promising, fast alternative, with increased specificity and sensitivity compared to identification methods using conventional culture media, thus enabling an increased rate of identification of pathogenic microorganisms and antibiotic resistance genes (ARG). The purpose of this article was to highlight new molecular diagnostic methods for periprosthetic joint infections and their involvement in treatment efficiency. NGS technologies are cutting-edge techniques that may challenge the PJI diagnostic model.

Single-cell transcriptome reveals Staphylococcus aureus modulating fibroblast differentiation in the bone-implant interface

BACKGROUND

This study aimed to delineate the cell heterogeneity in the bone-implant interface and investigate the fibroblast responses to implant-associated S. aureus infection.

METHODS

Single-cell RNA sequencing of human periprosthetic tissues from patients with periprosthetic joint infection (PJI, n = 3) and patients with aseptic loosening (AL, n = 2) was performed. Cell type identities and gene expression profiles were analyzed to depict the single-cell landscape in the periprosthetic environment. In addition, 11 publicly available human scRNA-seq datasets were downloaded from GSE datasets and integrated with the in-house sequencing data to identify disease-specific fibroblast subtypes. Furthermore, fibroblast pseudotime trajectory analysis and Single-cell regulatory network inference and clustering (SCENIC) analysis were combined to identify transcription regulators responsible for fibroblast differentiation. Immunofluorescence was performed on the sequenced samples to validate the protein expression of the differentially expressed transcription regulators.

RESULTS

Eight major cell types were identified in the human bone-implant interface by analyzing 36,466 cells. Meta-analysis of fibroblasts scRNA-seq data found fibroblasts in the bone-implant interface express a high level of CTHRC1. We also found fibroblasts could differentiate into pro-inflammatory and matrix-producing phenotypes, each primarily presented in the PJI and AL groups, respectively. Furthermore, NPAS2 and TFEC which are activated in PJI samples were suggested to induce pro-inflammatory polarization in fibroblasts, whereas HMX1, SOX5, SOX9, ZIC1, ETS2, and FOXO1 are matrix-producing regulators. Meanwhile, we conducted a CMap analysis and identified forskolin as a potential regulator for fibroblast differentiation toward matrix-producing phenotypes.

CONCLUSIONS

In this study, we discovered the existence of CTHRC1⁺ fibroblast in the bone-implant interface. Moreover, we revealed a bipolar mode of fibroblast differentiation and put forward the hypothesis that infection could modulate fibroblast toward a pro-inflammatory phenotype through NPAS2 and TFEC.

Diagnostic Role of mNGS in Polymicrobial Periprosthetic Joint Infection

OBJECTIVES

The purpose of this study was to explore the clinical value of metagenomic next-generation sequencing (mNGS) in the diagnosis of polymicrobial periprosthetic joint infection (PJI).

METHODS

Patients with complete data who underwent surgery at our hospital between July 2017 and January 2021 for suspected periprosthetic joint infection (PJI), according to the 2018 ICE diagnostic criteria, were enrolled, and all patients underwent microbial culture and mNGS detection, which were performed on the BGISEQ-500 platform. Microbial cultures were performed on two samples of synovial fluid, six samples of tissue, and two samples of prosthetic sonicate fluid for each patient. The mNGS was performed on 10 tissues, 64 synovial fluid samples, and 17 prosthetic sonicate fluid samples. The results of mNGS testing were based on the interpretation of mNGS results in the previous literature and the assertions of microbiologists and orthopedic surgeons. The diagnostic efficacy of mNGS in polymicrobial PJI was assessed by comparing the results of conventional microbial cultures and mNGS.

RESULTS

A total of 91 patients were finally enrolled in this study. The sensitivity, specificity, and accuracy of conventional culture for the diagnosis of PJI were 71.0%, 95.4%, and 76.9%, respectively. The sensitivity, specificity, and accuracy of mNGS for the diagnosis of PJI were 91.3%, 86.3%, and 90.1%, respectively. The sensitivity, specificity, and accuracy of conventional culture for the diagnosis of polymicrobial PJI were 57.1%, 100%, and 91.3%, respectively. mNGS had a sensitivity, specificity, and accuracy of 85.7%, 60.0%, and 65.2%, respectively, for the diagnosis of polymicrobial PJI.

CONCLUSIONS

mNGS can improve the diagnosis efficiency of polymicrobial PJI, and the combination of culture and mNGS is a promising method to diagnose polymicrobial PJI.

The Effectiveness of Metagenomic Next-Generation Sequencing in the Diagnosis of Prosthetic Joint Infection: A Systematic Review and Meta-Analysis

Background

A prosthetic joint infection (PJI) is a devastating complication following total joint arthroplasties with poor prognosis. Identifying an accurate and prompt diagnostic method is particularly important for PJI. Recently, the diagnostic value of metagenomic next-generation sequencing (mNGS) in detecting PJI has attracted much attention, while the evidence of its accuracy is quite limited. Thus, this study aimed to evaluate the accuracy of mNGS for the diagnosis of PJI.

Methods

We summarized published studies to identify the potential diagnostic value of mNGS for PJI patients by searching online databases using keywords such as “prosthetic joint infection”, “PJI”, and “metagenomic sequencing”. Ten of 380 studies with 955 patients in total were included. The included studies provided sufficient data for the completion of 2-by-2 tables. We calculated the sensitivity, specificity, and area under the SROC curve (AUC) to evaluate mNGS for PJI diagnosis.

Results

We found that the pooled diagnostic sensitivity and specificity of mNGS for PJI were 0.93 (95% CI, 0.83 to 0.97) and 0.95 (95% CI, 0.92 to 0.97), respectively. Positive and negative likelihood ratios were 18.3 (95% CI, 10.9 to 30.6) and 0.07 (95% CI, 0.03 to 0.18), respectively. The area under the curve was 0.96 (95% CI, 0.93 to 0.97).

Conclusion

Metagenomic next-generation sequencing displays high accuracy in the diagnosis of PJI, especially for culture-negative cases.