ABSTRACT
The diagnosis of periprosthetic joint infection (PJI) is challenging, often requiring multiple clinical specimens and diagnostic techniques, some with prolonged result turnaround times. Here, the diagnostic performance of the Investigational Use Only (IUO) BioFire Joint Infection (JI) Panel was compared to 16S rRNA gene-based targeted metagenomic sequencing (tMGS) applied to synovial fluid for PJI diagnosis. Sixty synovial fluid samples from knee arthroplasty failure archived at −80°C were tested. Infectious Diseases Society of America (IDSA) diagnostic criteria were used to classify PJI. For culture-positive PJI with pathogens targeted by the JI panel, JI panel sensitivity was 91% (21/23; 95% confidence interval [CI], 73 to 98%), and tMGS sensitivity was 96% (23/24; 95% CI, 80 to 99%) (P = 0.56). Overall sensitivities of the JI panel and tMGS for PJI diagnosis were 56% (24/43; 95% CI, 41 to 70%) and 93% (41/44; 95% CI, 82 to 98%), respectively (P < 0.001). JI panel and tMGS overall specificities were 100% (16/16; 95% CI, 81 to 100%) and 94% (15/16; 95% CI, 72 to 99%), respectively. While the clinical sensitivity of the JI panel was excellent for on-panel microorganisms, overall sensitivity for PJI diagnosis was low due to the absence of Staphylococcus epidermidis, a common causative pathogen of PJI, on the panel. A PJI diagnostic algorithm for the use of both molecular tests is proposed.
KEYWORDS: periprosthetic joint infection, rapid diagnostic, PCR, next-generation sequencing
INTRODUCTION
Joint replacement surgery has revolutionized clinical care of patients with osteoarthritis and other joint diseases. Periprosthetic joint infection (PJI) complicates approximately 1 to 2% of primary joint replacement surgeries, with devastating clinical and economic ramifications (1–3). Indeed, the sequelae of PJI include recurrent infections, repeat surgical revisions, prolonged antimicrobial courses, and a high burden on both patient quality of life and overall health care costs (4).
The first step in treating PJI is to achieve an accurate and rapid diagnosis. No single test can diagnose PJI with high accuracy. PJI diagnosis is challenging and often requires a combination of clinical, intraoperative, radiologic, and histopathologic findings, as well as standard culture—and more recently, molecular—techniques. The current proposed gold standard for PJI diagnosis is to culture multiple periprosthetic tissue and/or fluid specimens (5–7). However, culture-negative PJI can account for up to approximately 40% of infections (8–12). Although enhanced culture-based techniques such as the implant sonication and inoculation of synovial fluid and periprosthetic tissues into blood culture bottles have improved sensitivity (13, 14), there remain culture-negative cases; furthermore, time to diagnosis and, therefore, prompt administration of targeted therapy remain imperfect with culture-based diagnostics. Rapid culture-independent techniques for microbiologic PJI diagnosis have the potential to provide a rapid diagnosis.
The use of metagenomic sequencing has been shown to improve sensitivity by detecting fastidious organisms as well as pathogens in cases where presampling antimicrobial therapy is given (15–20). Previously, we described a targeted metagenomic sequencing (tMGS) approach which uses Sanger sequencing and/or next-generation sequencing (NGS) after 16S rRNA gene PCR amplification (with sequencing type dependent upon obtained cycle threshold [CT] values) for the detection of bacteria in normally sterile human specimens (21, 22). This cost-effective NGS approach (23) to bacterial detection has been shown to identify causative pathogens and/or change antibiotic decision-making in challenging cases and is a tool for PJI diagnosis.
Multiplex PCR-based assays offer rapid turnaround times and can detect pathogens and resistance gene targets in parallel; however, their role in the diagnosis of PJI remains incompletely defined (24–30). The BioFire Joint Infection (JI) Panel, a multiplex PCR-based test which simultaneously detects 15 Gram-positive bacteria, 14 Gram-negative bacteria, 2 yeast, and 8 antimicrobial resistance gene targets in less than 1 h was recently approved by the U.S. Food and Drug Administration (FDA) (Table 1).
TABLE 1.
Organisms and resistance genes detected by the BioFire Joint Infection (JI) Panel
| Organism or gene group | Organism or gene type |
|---|---|
| Gram-positive bacteria | Anaerococcus prevotii / Anaerococcus vaginalis |
| Clostridium perfringens | |
| Cutibacterium avidum / Cutibacterium granulosum | |
| Enterococcus faecalis | |
| Enterococcus faecium | |
| Finegoldia magna | |
| Parvimonas micra | |
| Peptoniphilus species | |
| Peptostreptococcus anaerobius | |
| Staphylococcus aureus | |
| Staphylococcus lugdunensis | |
| Streptococcus species | |
| Streptococcus agalactiae | |
| Streptococcus pneumoniae | |
| Streptococcus pyogenes | |
| Gram-negative bacteria | Bacteroides fragilis |
| Citrobacter species | |
| Enterobacter cloacae complex | |
| Escherichia coli | |
| Haemophilus influenzae | |
| Kingella kingae | |
| Klebsiella aerogenes | |
| Klebsiella pneumoniae group | |
| Morganella morganii | |
| Neisseria gonorrhoeae | |
| Proteus species | |
| Pseudomonas aeruginosa | |
| Salmonella species | |
| Serratia marcescens | |
| Yeast | Candida species |
| Candida albicans | |
| Carbapenemases | bla IMP |
| bla KPC | |
| bla NDM | |
| bla OXA-48-like | |
| bla VIM | |
| Methicillin resistance genes | mecA/C and MREJ |
| Extended-spectrum β-lactamase genes | bla CTX-M |
| Vancomycin resistance genes | vanA/B |
Here, the diagnostic performance of the IUO JI panel was compared to tMGS in the diagnosis of PJI applied to 60 archived synovial fluid samples from patients with knee arthroplasty failure.
MATERIALS AND METHODS
Synovial fluid samples.
Synovial fluid was collected with informed consent under Mayo Clinic Institutional Review Board protocol 10-005574 at the time of routine clinical arthrocentesis from adult patients (>18 years old) with knee arthroplasty failure. Arthrocentesis was performed at the discretion of managing clinicians. Synovial fluid was placed in gamma-irradiated vials (to minimize DNA contamination) and archived at −80°C. From this archive, 60 synovial fluid samples collected between December 1998 and June 2021 of sufficient volume for the study were selected; 41 were culture positive and 18 culture negative (1 culture was not performed). Patient demographics (age, gender) and culture results were collected through retrospective review of the electronic medical records. Infectious Diseases Society of America (IDSA) diagnostic criteria for PJI (6) were used to diagnose PJI; in addition to periprosthetic culture results and number of samples taken, synovial fluid analysis (total nucleated cell count, neutrophil percentage), clinical and intraoperative findings (presence of a sinus tract, gross purulence, and extent of infection), and histopathologic findings (acute inflammation) were collected. In total, 44 cases met IDSA criteria for PJI.
DNA extraction and PCR amplification for tMGS.
A total of 100 μL of synovial fluid was added, along with 20 μL of proteinase K to an autoclaved lysis tube containing 160 μL of proteinase K buffer and 20-μL volume, 0.1-mm silica/zirconium beads. Digestion was performed at 60°C with shaking at 300 rpm for 60 min, followed by 2,000 rpm at 100°C for 5 min. Samples were cooled with no shaking at room temperature for 5 min. The tubes were centrifuged at 10,000 rpm for 30 s, and 200 μL of lysed specimen was extracted using a MagnaPure 96 (Roche Diagnostics, Risch-Rotkreuz, Switzerland). Primers used targeted the V1-V3 region of the bacterial 16S rRNA and used a dual-priming oligonucleotide (DPO) design as follows: Forward_V1-V3_DPO, 5′-AGAGTTTGATCMTGGCTCAIIIIIAACGC-3′; Reverse(1)_V1-V3_DPO, 5′-CGGCTGCTGGCAIIIAITTDGC-3′; and Reverse(2)_V1-V3_DPO, 5′-CGGCTGCTGGCAIIIAITTDGT-3′. PCR was performed on a LightCycler 480II instrument (Roche Diagnostics) to amplify ~530 bp of the bacterial 16S rRNA gene. Each reaction consisted of 15 μL of master mix combined with 5 μL of extracted DNA. A positive control (Corynebacterium glutamicum DNA) along with a negative control (autoclaved Tris elution buffer [TEB]; Qiagen) were included in each run.
Next-generation sequencing (NGS).
For this study, all samples underwent NGS using library preparation, normalization, and sequencing according to the 16S metagenomic sequencing library preparation protocol from Illumina (San Diego) (31). DNA concentrations were determined using a QuantiFluor One double-stranded DNA (dsDNA) kit on a Quantus fluorometer (Promega, Madison, WI). Samples were then diluted to 5 ng/μL with 10 mM Tris, pH 8.5 (Teknova, Hollister, CA) and adaptors attached to amplified DNA using the following primers: forward, 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG AGAGTTTGATCMTGGCTCAG-3′, and reverse, 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG CGGCTGCTGGCA-3′.
Each reaction consisted of 12.5 μL of master mix with 2.5 μL of each 5 ng/μL sample plus 5 μL of each adaptor. Adaptor PCR was performed on a thermal cycler (Bio-Rad, Hercules, CA) using the following program: 95°C for 3 min, 25 cycles of (i) 95°C for 30 s, (ii) 55°C for 30 s, and (iii) 72°C for 30 s, and then 72°C for 5 min. The first PCR cleanup was done by adding 20 μL of AMPure XP beads (Beckman Coulter, Brea, CA) to each sample, followed by washing (twice) with 200 μL of freshly prepared 80% ethanol and resuspension in 52.5 μL of sterile 10 mM Tris, pH 8.5, as per the Illumina protocol. Cleaned supernatant (5 μL) from each sample was transferred to a new 96-well 0.2-mL PCR plate in which 10 μL of unique dual-index primers from IDT (Corallville, IA), 10 μL of PCR-grade water, and 25 μL of mastermix were added. The plate was sealed and centrifuged (1,000 × g at room temperature for 1 min) before performing index PCR on a thermal cycler using the following program: 95°C for 3 min, 8 cycles of (i) 95°C for 30 s, (ii) 55°C for 30 s, and (iii) 72°C for 30 s, and then 72°C for 5 min. After PCR, a second cleanup was done by adding 56 μL of AMPure XP beads (Beckman) to each sample, followed by washing twice with 200 μL of freshly prepared 80% ethanol and resuspension in 27.5 μL of sterile 10 mM Tris, pH 8.5. Library concentrations were assessed using the QuantiFluor One dsDNA kit (Promega), and each sample was diluted to a 4-nM concentration using 10 mM Tris, pH 8.5.
Each sample was pooled (5 μL per sample) to create a library and denatured with an equal volume (5 μL) 0.2N NaOH. Denatured libraries were diluted with 990 μL prechilled hybridization buffer HT1 to reach a concentration of 20 pM. A second dilution was performed by mixing 140 μL of the 20-pM denatured library with 460 μL of prechilled HT1 buffer to form a 6-pM final library concentration. 570 μL of the 6 pM DNA library with 30 μL denatured and diluted 5% PhiX as per the Illumina protocol. The final library (600 μL) was combined with paired-end reads on an Illumina MiSeq with a 500-cycle V2 Nano kit (Illumina).
Analysis of tMGS sequencing data.
Onboard Illumina processing included adapter trimming, index demultiplexing, and fastq generation. Files were processed using Pathogenomix RipSeq NGS software (Santa Cruz, CA). Before clustering into operational taxonomic units (OTUs), quality settings were set to ensure that only high-quality base calls (Q > 30) and sequences ≥210 bases in length were used for analysis. Sequences with <100 reads were rejected. Species-level identification was set to ≥99.2% homology, and between 98.0 and 99.1% homology, the organism was qualified for genus-level identification. Forward and reverse reads were uploaded separately, nonmerged, and queried against the Pathogenomix PRIME database with approximately 54,000 clinically relevant 16S rRNA gene references. Forward sequences were used for analysis; sequences with <98% ID to PRIME database entries were rerun against a broader database that included environmental contaminants. Interpretation of sequence data was performed by the clinical laboratory director blinded to results of culture and the JI panel. Organisms detected in the negative control with >99.5% sequence similarity to results were highlighted bioinformatically and not reported in the interpreted patient results.
JI panel testing.
Synovial fluid samples were tested using the JI panel (IUO reagents) according to the manufacturer’s protocol. The JI panel is a single-use nested multiplex PCR-based system which employs endpoint melting curve analysis on the FilmArray 2.0 Torch system instrument. Two hundred microliters of archived synovial fluid was mixed in dilution buffer and injected into the BioFire JI panel pouch for nucleic acid extraction, amplification, and detection. An invalid result was determined as a test not completed due to a software or hardware error.
Statistical analysis.
McNemar’s test was used to compare diagnostic performance of the JI panel and tMGS assay; 95% confidence intervals were estimated using Wilson’s method.
RESULTS
A total of 60 synovial fluid samples from knee arthroplasty failure were analyzed: 44 samples were IDSA criteria positive for PJI, among which there was 1 invalid JI panel result (a synovial fluid sample that had been culture-positive for Staphylococcus aureus). Table 2 outlines the detected organisms, as well as overall sensitivities and specificities of the JI panel and tMGS assay for the 39 PJI cases with positive synovial fluid cultures.
TABLE 2.
Organism-specific findings of the BioFire JI panel and targeted metagenomic sequencing (tMGS) in PJI cases with culture-positive synovial fluid samples (n = 39)a
| Organism or group | No. of culture-positive cases/total no. of cases by: |
|
|---|---|---|
| JI panel | tMGS | |
| On panel | ||
| Staphylococcus aureusb | 11/11 | 12/12 |
| Enterococcus species | 1/1 | 1/1 |
| Staphylococcus lugdunensis | 2/2 | 2/2 |
| Streptococcus species | ||
| Streptococcus salivarius group | 0/1 | 1/1 |
| Streptococcus mitis group | 2/2 | 2/2 |
| Group C Streptococcus species | 1/1 | 1/1 |
| Pseudomonas aeruginosa | 1/1 | 1/1 |
| Serratia marcescens | 2/2 | 2/2 |
| Enterobacter cloacae complex | 0/1 | 1/1 |
| Candida albicans | 1/1 | 0/1 |
| Off panel | ||
| Staphylococcus epidermidis | 0/12 | 12/12 |
| Corynebacterium striatum | 0/1 | 1/1 |
| Lelliottia species | 0/1 | 1/1 |
| Haemophilus parainfluenzae | 0/1 | 1/1 |
In addition to the cases listed, there were five culture-negative PJI cases.
One JI panel invalid error.
The overall sensitivities for PJI diagnosis of the JI panel and tMGS assay were 56% (24/43; 95% confidence interval [CI], 41 to 70%) and 93% (41/44; 95% CI, 82 to 98%), respectively (P < 0.001). For culture-positive PJI with organisms detected by the JI panel, sensitivities of the JI panel and tMGS tests were 91% (21/23; 95% CI, 73 to 98%) and 96% (23/24; 95% CI, 80 to 99%), respectively (P = 0.56). There were five cases which met IDSA criteria for PJI for which synovial fluid cultures were either negative or not performed: S. aureus was detected by JI panel and tMGS in three (two of which were negative by synovial fluid culture but tissue culture positive for S. aureus), whereas the other two were negative by both molecular tests. Overall specificities for the JI panel and tMGS assay were 100% (16/16; 95% CI, 81 to 100%) and 94% (15/16; 95% CI, 72 to 99%), respectively (P value not calculable). Antibiotic resistance determinants were not detected by the JI panel; the 12 S. aureus PJI cases were associated with oxacillin-susceptible S. aureus.
DISCUSSION
The diagnostic performance of the JI panel was compared to a tMGS assay for PJI diagnosis using archived synovial fluid samples from patients with arthroplasty failure. Both molecular tests performed well for detection of organisms targeted by the JI panel, with sensitivities and specificities ≥91%. Although sensitivity of the JI panel for on-panel organisms was 91%, sensitivity was 56% with the inclusion of off-panel organisms. Among culture-positive synovial fluid samples, 29% of organisms identified by synovial fluid culture were S. aureus, and 29% were Staphylococcus epidermidis. These two organisms are common causes of PJI, with S. epidermidis estimated to cause up to 40% of PJI (32, 33). That S. epidermidis is not detected by the JI panel largely accounts for the low sensitivity of the JI panel found in this study.
Of the five synovial fluid samples which met criteria for PJI per IDSA criteria for which synovial fluid cultures were either negative or not performed, S. aureus was detected by both molecular tests in three, two of which were negative by synovial fluid culture but tissue culture positive for S. aureus. Further, for one of these PJI cases, a sinus tract was present; tissue cultures yielded S. aureus, alongside the Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa, and Bacteroides fragilis group, although none of the organisms beyond S. aureus were detected in synovial fluid or by either molecular test. For this case, it is possible that the presence of a sinus tract explains the polymicrobial nature of the tissue cultures.
Of the 60 total synovial fluid samples, two had >1 bacterial species recovered from synovial fluid. Only one was associated with PJI per IDSA criteria. In this case, synovial fluid culture yielded Streptococcus mitis group with the cocultured organism (Cutibacterium acnes) considered a contaminant; S. mitis group was isolated from multiple intraoperative tissue specimens, and both molecular tests detected Streptococcus species, with Streptococcus sanguinis specifically identified by tMGS. The other polymicrobial synovial fluid sample was not associated with PJI: viridans group Streptococcus species and Acinetobacter species were recovered in culture (both of which were considered contaminants, and neither of which was detected by the molecular tests).
Of the synovial fluid samples culture positive for streptococci, both the JI panel and tMGS assay detected the S. mitis group and group C Streptococcus species, although only the tMGS assay identified these organisms to the species or species group level. For one case that did not meet criteria for PJI, tMGS detected Streptococcus australis from synovial fluid—likely a false-positive result—with the JI panel resulting as negative. Overall, the JI panel detected Streptococcus species in synovial fluids culture positive for the S. mitis group and group C Streptococcus species (further identified as Streptococcus dysgalactiae by tMGS), but not the Streptococcus salivarius group; all of these were detected by tMGS.
Of the six Gram-negative PJI cases which were synovial fluid culture positive, both molecular tests accurately detected Pseudomonas aeruginosa (1/1; 100%) and Serratia marcescens (2/2; 100%); however, the JI panel did not detect one Enterobacter cloacae complex PJI case and, unsurprisingly, did not detect two off-panel Gram-negative bacteria (Haemophilus parainfluenzae and Lelliottia species). There was only one yeast PJI (Candida albicans), which was detected by the JI panel and not by tMGS (which does not detect fungi).
Previously, we demonstrated that a tMGS approach could serve as an adjunctive diagnostic test in the diagnosis of challenging infections, such as those caused by fastidious pathogens, and in patients where presampling antibiotics are given (21). The JI panel (and to some extent, tMGS) offers rapid time to diagnosis, potentially informing targeted antimicrobial therapy and/or surgical decision-making, which may, in turn, affect patient outcomes and health care-associated costs. Future studies that include the investigation of the clinical utility of these molecular tests are warranted. For example, the use of the JI panel in an emergency department-type setting in patients with a rapid onset and/or severe symptoms would be an interesting application of this test for study of patient-centered outcomes. Unlike the JI panel, tMGS does not test for antimicrobial resistance. Although rapid characterization of antimicrobial resistance of detected PJI pathogens may be helpful, in this study, none of the targeted resistance genes were detected (34, 35).
tMGS interpretation requires a trained microbiologist for results interpretation, whereas the JI panel is simple to report and can be set to autoreport. The issue of detection of common contaminant organisms in PJI, such as a C. acnes and S. epidermidis requires careful consideration when employing molecular tests (an evolving area of research which certainly requires further work), and notably, neither of these is part of the JI panel.
A possible diagnostic testing algorithm is proposed in Fig. 1. Up-front molecular testing is not necessarily advised; synovial fluid may be retained in the laboratory for a period of time for future molecular testing, if needed. Should there be positive cultures and a clear diagnosis, specific management may be pursued. If not, synovial fluid may be subjected to adjunctive molecular testing, including the JI panel and, if that is negative, tMGS testing.
FIG 1.
Proposed algorithm for use of the BioFire Joint Infection (JI) Panel and targeted metagenomic sequencing (tMGS) for the diagnosis of periprosthetic joint infection (PJI). *, symptoms consistent with PJI may include joint pain, erythema, and swelling; wound drainage or dehiscence; fever; and difficulty weight bearing on the affected joint; **, synovial fluid analysis includes aerobic and anaerobic cultures, total cell count with differential, and microscopic analysis for crystals; the interpretation should be made in conjunction with clinical presentation, and timing of infection, with or without additional diagnostic markers, such as synovial fluid alpha defensin and/or leukocyte esterase.
Limitations to this study include small sample size, nonrandom sample selection, and age of some of the synovial fluid samples tested. The 60 synovial fluid samples studied were selected to allow for enough sample volume to undergo both JI panel and tMGS testing; given the rarity of PJI as a disease, two samples were selected which were initially archived from 1998 to 1999. However, freeze-thaw cycles were minimized, and most samples were from 2013 to 2021. In addition, IDSA criteria for PJI diagnosis were used in this study given that additional diagnostic criteria were not always available, particularly for some of the older samples. Further, this study only involved knee arthroplasty failure; whether results apply to other joints is unknown. C. acnes, which is more commonly found in shoulder than knee (or hip) PJI, is not included in the JI panel and is challenging to diagnose with tMGS due to frequent presence of the C. acnes sequence in the assay background. Future studies should test synovial fluid samples from failed hip, shoulder, and elbow arthroplasties. The performance of both molecular tests on polymicrobial synovial fluid samples is also an area that warrants further study, as is the application of both to other specimen types such as periprosthetic tissue (although, notably, the JI panel is only approved by the FDA to test synovial fluid).
In summary, the JI panel is a novel multiplex PCR test which has excellent sensitivity and specificity for on-panel organisms and offers a turnaround time of less than 1 h, with the added benefit of detecting some antimicrobial resistance determinants in parallel. Overall sensitivity of the JI panel for PJI diagnosis was low, however, in large part due to the absence of S. epidermidis on the panel. This is the first study to evaluate its diagnostic performance in comparison to a tMGS approach in the diagnosis of PJI using synovial fluid samples from patients with knee arthroplasty failure.
ACKNOWLEDGMENTS
BioFire (bioMérieux) supplied 60 single-use BioFire JI panels for this study.
M.A.A., M.J.W., A.P.S., M.L.D., J.C.S., A.D.D., M.P.A., and K.E.G.-Q. have no conflicts of interests to declare. R.P. reports grants from ContraFect, TenNor Therapeutics Limited, and BioFire. R.P. is a consultant to Curetis, Next Gen Diagnostics, PathoQuest, Selux Diagnostics, 1928 Diagnostics, PhAST, Torus Biosystems, Day Zero Diagnostics, Mammoth Biosciences, and Qvella; money is paid to Mayo Clinic. Mayo Clinic and R.P. have a relationship with Pathogenomix. R.P. has research supported by Adaptive Phage Therapeutics. Mayo Clinic has a royalty-bearing know-how agreement and equity in Adaptive Phage Therapeutics. R.P. is also a consultant to Netflix and CARB-X. In addition, R.P. has a patent on Bordetella pertussis/Bordetella parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, and a patent on an antibiofilm substance issued. R.P. receives honoraria from the NBME, Up-to-Date, and the Infectious Diseases Board Review Course.
Contributor Information
Robin Patel, Email: patel.robin@mayo.edu.
Nathan A. Ledeboer, Medical College of Wisconsin
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