Next-generation sequencing for diagnosis of infection: is more sensitive really better?

Rao, Allison J.; MacLean, Ian S.; Naylor, Amanda J.; Garrigues, Grant E.; Verma, Nikhil N.; Nicholson, Gregory P.

doi:10.1016/j.jse.2019.07.039

Cited by 27 publications

(12 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…in 20 of those samples was less than 5% (less than 1% in 16 samples), so they would not be considered positive for Cutibacterium sp. according to even the most lenient proportional abundance thresholds (one study used 10% [ 39 ] and another reported that 59.5% was optimal [ 40 ]). The two samples with the highest proportional abundance of Cutibacterium sp.…”

Section: Resultsmentioning

confidence: 99%

Deciphering the low abundance microbiota of presumed aseptic hip and knee implants

et al. 2021

View full text Add to dashboard Cite

16S rRNA gene sequencing of DNA extracted from clinically uninfected hip and knee implant samples has revealed polymicrobial populations. However, previous studies assessed 16S rRNA gene sequencing as a technique for the diagnosis of periprosthetic joint infections, leaving the microbiota of presumed aseptic hip and knee implants largely unstudied. These communities of microorganisms might play important roles in aspects of host health, such as aseptic loosening. Therefore, this study sought to characterize the bacterial composition of presumed aseptic joint implant microbiota using next generation 16S rRNA gene sequencing, and it evaluated this method for future investigations. 248 samples were collected from implants of 41 patients undergoing total hip or knee arthroplasty revision for presumed aseptic failure. DNA was extracted using two methodologies—one optimized for high throughput and the other for human samples—and amplicons of the V4 region of the 16S rRNA gene were sequenced. Sequencing data were analyzed and compared with ancillary specific PCR and microbiological culture. Computational tools (SourceTracker and decontam) were used to detect and compensate for environmental and processing contaminants. Microbial diversity of patient samples was higher than that of open-air controls and differentially abundant taxa were detected between these conditions, possibly reflecting a true microbiota that is present in clinically uninfected joint implants. However, positive control-associated artifacts and DNA extraction methodology significantly affected sequencing results. As well, sequencing failed to identify Cutibacterium acnes in most culture- and PCR-positive samples. These challenges limited characterization of bacteria in presumed aseptic implants, but genera were identified for further investigation. In all, we provide further support for the hypothesis that there is likely a microbiota present in clinically uninfected joint implants, and we show that methods other than 16S rRNA gene sequencing may be ideal for its characterization. This work has illuminated the importance of further study of microbiota of clinically uninfected joint implants with novel molecular and computational tools to further eliminate contaminants and artifacts that arise in low bacterial abundance samples.

show abstract

Section: Resultsmentioning

confidence: 99%

Deciphering the low abundance microbiota of presumed aseptic hip and knee implants

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Recent studies have evaluated the use of new technologies, such as polymerase chain reaction and next-generation sequencing (NGS), as adjuncts in the organism-identification process. However, their utilities remain unknown with several studies reporting no increase in sensitivity or specificity compared to traditional tissue cultures and NGS demonstrating a false positive rate of up to 35% and 25% in primary and revision arthroplasties, respectively, [ [35] , [36] , [37] , [38] ]. In addition, intrahospital and interhospital variations in protocols and incubation times may affect the accuracy and capability of cultures to identify organisms, especially lower-virulence and slower-replicating organisms [ [39] , [40] , [41] , [42] ].…”

Section: Discussionmentioning

confidence: 99%

Recurrent Failures After 2-Stage Exchanges are Secondary to New Organisms Not Previously Covered by Antibiotics

Egbulefu¹,

Yang²,

Segreti³

et al. 2022

Arthroplasty Today

View full text Add to dashboard Cite

“…Even with bacterial load thresholds set for these specific pathogens, it is difficult to differentiate between true pathogens and contaminants. Therefore, we need a comprehensive analysis combining multiple factors, such as a higher proportion of prosthetic shoulder joint infections caused by D. acnes compared to other joints [24] .…”

Section: Discussionmentioning

confidence: 99%

Influence of residual microbial nucleic acid in instruments for hip joint arthroplasty on false-positive results of metagenomic sequencing

Yin

Wang

et al. 2022

Preprint

View full text Add to dashboard Cite

The purpose of this study was to analyze the effect of residual microbial nucleic acid in instruments for hip joint arthroplasty on false-positive sequencing results. Samples were taken from 3 different acetabular reamer for hip arthroplasty in 7 different hospitals. The whole process was strictly aseptic, metagenomic next-generation sequencing (mNGS) was performed according to standard operating procedures. The sterility of instruments was confirmed by culture method. The sequencing results of specimens from different hospitals were compared to analyze the difference of background bacteria. Bioinformatics analysis and visualization were presented through R language. A total of 26 samples were processed by mNGS, including 24 instrument swab samples, 1 blank swab control, and 1 blank water control. 254,314,707 reads were sequenced in all samples. The results showed that 1.13% of Clean Reads can be matched to pathogenic microorganism genomes, of which bacterial sequences account for 87.48%, fungal sequences account for 11.18%, parasite sequences account for 1.26%, and virus sequences account for 0.06%. The results of PCA (Principal Component Analysis) demonstrated that the distribution of bacteria on the surface of instruments was significantly different between medical institutions. Through the Venn diagram, it was found that 465 species of bacteria in all region hospitals, Liaocheng People's Hospital had a maximum of 340 species of bacteria, followed by Guanxian County People's Hospital with 169 species. The clustering heat map illustrated that the distribution of bacterial groups in three different instrument samples in the same hospital was basically the same, and the bacterial genera varied significantly among hospitals. The residual microbial nucleic acid fragments are mainly bacterial DNA and represent differences in different medical institutions, The establishment of independent background bacterial libraries in different medical institutions can effectively improve the accuracy of mNGS diagnosis and help to exclude background microorganisms interference.

show abstract

Next-generation sequencing for diagnosis of infection: is more sensitive really better?

Cited by 27 publications

References 37 publications

Deciphering the low abundance microbiota of presumed aseptic hip and knee implants

Deciphering the low abundance microbiota of presumed aseptic hip and knee implants

Recurrent Failures After 2-Stage Exchanges are Secondary to New Organisms Not Previously Covered by Antibiotics

Influence of residual microbial nucleic acid in instruments for hip joint arthroplasty on false-positive results of metagenomic sequencing

Contact Info

Product

Resources

About