Sequencing Shows Promise for Diagnosing Prosthetic Joint Infections
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By LabMedica International staff writers Posted on 07 May 2019 |

Image: The MinION is the only portable real-time device for DNA and RNA sequencing (Photo courtesy of Oxford Nanopore).
A method is being developed for diagnosing infections associated with prosthetic joint implants that promises to provide results in a matter of hours as opposed to a week or more. The current gold standard is bacterial culture from periprosthetic tissue samples collected during surgery, although another option is culturing from sonicated explanted prostheses in saline.
Of approximately 113,000 total knee replacement surgeries performed in the UK in 2017, 6,500, or about 6%, were revision surgeries, and nearly a quarter of those surgeries took place because of an infection or suspicion of infection. Elbow replacement surgeries showed similar rates of infection-related revision surgeries, while shoulder and hip replacements were around 17%and 16% respectively.
A team of scientists associated with the University of Oxford (Oxford, UK) devised a workflow involved removing a prosthetic device during surgery then placing it in saline and sonicating it to obtain approximately 40 mL of sonication fluid, which is essentially the largest volume they can easily handle in the laboratory, which is allowed them to maximize the number of cells they can extract DNA from. The sonication step potentially increases the number of bacterial cells available in the sample because it disrupts the bacterial biofilm. The DNA is extracted from the sonicated samples, cleaned, and prepared into libraries, which are then sequenced. The work leveraged Oxford Nanopore sequencing technologies.
Teresa Street, PhD, a postdoctoral research student at Nuffield Department of Clinical Medicine (Oxford, UK) and a co-author of the study said, discussed her group's attempts to validate the technology as part of a completely culture-free method for diagnosing prosthetic joint implant infections. She said “That the current gold standard is bacterial culture from periprosthetic tissue samples collected during surgery, although another option is culturing from sonicated explanted prostheses in saline. However, culture from tissue samples is relatively insensitive, with detection rates around 65% and is a very busy process with many steps.”
Their analyses using this improved protocol have a high degree of concordance with culture testing, and in fact they have been able to detect positives for certain species that were culture-negative. In addition, in a few Staphylococcus-positive cases so far they have been able to identify antimicrobial resistance genes. In one sample, they were able to detect two different Staphylococcus organisms, one of which they could identify (S. haemolyticus) and one of which they could not.
They later used MALDI-ToF mass spectrometry to identify this organism as S. caprae, and realized they couldn't initially detect it because it was not in their reference database, underscoring the fact that metagenomic sequencing is only as good as the reference database being used. The study was presented at the European Congress of Clinical Microbiology and Infectious Diseases held April 13-16, 2019, in Amsterdam, The Netherlands.
Related Links:
University of Oxford
Nuffield Department of Clinical Medicine
Of approximately 113,000 total knee replacement surgeries performed in the UK in 2017, 6,500, or about 6%, were revision surgeries, and nearly a quarter of those surgeries took place because of an infection or suspicion of infection. Elbow replacement surgeries showed similar rates of infection-related revision surgeries, while shoulder and hip replacements were around 17%and 16% respectively.
A team of scientists associated with the University of Oxford (Oxford, UK) devised a workflow involved removing a prosthetic device during surgery then placing it in saline and sonicating it to obtain approximately 40 mL of sonication fluid, which is essentially the largest volume they can easily handle in the laboratory, which is allowed them to maximize the number of cells they can extract DNA from. The sonication step potentially increases the number of bacterial cells available in the sample because it disrupts the bacterial biofilm. The DNA is extracted from the sonicated samples, cleaned, and prepared into libraries, which are then sequenced. The work leveraged Oxford Nanopore sequencing technologies.
Teresa Street, PhD, a postdoctoral research student at Nuffield Department of Clinical Medicine (Oxford, UK) and a co-author of the study said, discussed her group's attempts to validate the technology as part of a completely culture-free method for diagnosing prosthetic joint implant infections. She said “That the current gold standard is bacterial culture from periprosthetic tissue samples collected during surgery, although another option is culturing from sonicated explanted prostheses in saline. However, culture from tissue samples is relatively insensitive, with detection rates around 65% and is a very busy process with many steps.”
Their analyses using this improved protocol have a high degree of concordance with culture testing, and in fact they have been able to detect positives for certain species that were culture-negative. In addition, in a few Staphylococcus-positive cases so far they have been able to identify antimicrobial resistance genes. In one sample, they were able to detect two different Staphylococcus organisms, one of which they could identify (S. haemolyticus) and one of which they could not.
They later used MALDI-ToF mass spectrometry to identify this organism as S. caprae, and realized they couldn't initially detect it because it was not in their reference database, underscoring the fact that metagenomic sequencing is only as good as the reference database being used. The study was presented at the European Congress of Clinical Microbiology and Infectious Diseases held April 13-16, 2019, in Amsterdam, The Netherlands.
Related Links:
University of Oxford
Nuffield Department of Clinical Medicine
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