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Molecular diagnosis of orthopaedic infections may soon be based on the detection of bacterial genetic molecules.
Courtesy of Rocky S. Tuan, PhD

AAOS Now

Published 5/1/2011
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Patrick F. Bergin, MD; Rocky S. Tuan, PhD

New technologies for diagnosing orthopaedic infection

Molecular biology techniques under development may detect bacterial infection

Postoperative infections are one of the most common and severe complications facing orthopaedic patients. Despite the frequent evaluation of patients suspected of harboring infections, diagnostic criteria are not universally established.

Culture of tissue or fluid remains the closest test to a gold standard for diagnosing infections, but in some cases, antibiotics are prescribed empirically and surgical débridements are performed without proof of an infecting organism(s). Although blood-based tests—such as C-reactive protein levels and cell counts—can suggest the presence of infection, they cannot determine the species or antibiotic sensitivities of infecting organisms. The rapid and accurate diagnosis of an infection can still be the most difficult aspect of treatment.

Recent advances in the diagnosis and treatment of orthopaedic infections are beginning to work their way from basic research to clinical reality. In arthroplasty, fractures, and wound management, technologic advances are redefining how infections are diagnosed and, in some cases, expanding knowledge of what organisms are involved in colonizing and infecting wounds and prostheses.

Finding biofilm infections
Molecular detection methods, for example, have found evidence of bacterial colonization in more than 60 percent of retrieved arthroplasty samples, although standard microbiologic tests diagnosed infection in less than one quarter of these patients. This increased diagnostic accuracy was achieved by using ultrasound to agitate the components and release clumps of bacteria containing up to 300 cells. Since 1999, biofilm detection and the observation of nonculturable bacteria have become emerging areas of bench-to-bedside research in orthopaedic surgery.

Although modern antibiotics are adept at controlling infections with standard planktonic bacteria, organisms in biofilm infections are difficult to detect and treat. Some bacteria can live within human cells while others live in colonies encased in thick layers of glycoproteins. Culturing organisms under these conditions is difficult. Biofilms also prevent circulating antibiotics from reaching the sheltered bacteria. Empirically, surgeons have found that only aggressive removal of all foreign material (ie, two-stage revision arthroplasty) can adequately treat chronic biofilm infections.

The diagnosis of the causative organisms, however, is still a concern. Molecular techniques have been used clinically to detect infections and determine the causative organisms in presumed biofilm cases. In contrast to traditional methods, these techniques generally target and rely on fragments of bacteria instead of viable culturable cells to make a diagnosis.

Initial efforts centered on the amplification of bacterial DNA material with polymerase chain reaction (PCR). Although this technique has high sensitivity, its validity is limited by the number of false positives. This is due to both the power of DNA amplification and the persistence of bacterial DNA long after bacterial death. Therefore, a detection target whose status better reflects the viability of the bacteria is needed.

Identifying infection markers
Recently, it has been shown that messenger RNA (mRNA) could be used as a marker of infection in simulated infections. As a transient carrier of the genetic material in the bacterial cells, mRNA quickly degrades after cell death and is therefore only present in active infections. However, the low copy numbers of mRNA and the lack of a universal target sequence for all bacteria limit its utility as a marker of infection.

The use of ribosomal RNA (rRNA) as the marker of infection has also been explored. Ribosomes, integral structural subunits inside the bacterial cell, are both abundant in number and involved in protein synthesis. As a detection target, rRNA, because of its abundance, offers sensitivity near that of DNA but disappears with cell death.

In addition to having universal components common to nearly all bacteria species, rRNA also has segments that are unique to specific bacteria and can be utilized in PCR-based identification. In clinical samples, as a diagnostic test, rRNA detection in periprosthetic joint infections had accuracy similar to cell counts with differentials and was more accurate than intraoperative cultures. Importantly, this test was positive in culture-negative cases in which infection was present, and it also had the potential for bacterial identification on the basis of DNA sequencing. Several research groups are currently exploring molecular methods to detect periprosthetic infection with both experimental and clinical success.

PCR-based amplification technology may be coupled with other molecular technologies for more efficient bacterial diagnosis, including quantification of bacterial load in open fractures. For example, coupling this technology with mass spectrometry analysis should enable direct determination of the types and quantities of bacterial colonization. This approach exploits the ability of mass spectrometry to sequence, identify, and quantify the amplified DNA fragments, thereby permitting bacterial speciation without a lengthy DNA sequencing step. In the future, such information may be prospectively compared to treatment outcomes to evaluate how molecular diagnosis may be applied to assess antibiotic regimen and débridement courses for these wounds.

Nature and biology of infections
The molecular detection of infection has also led to an increased understanding of the nature and biology of periprosthetic infections. For example, Propionibacterium acnes has recently been isolated from more than one third of infected shoulder arthroplasties. This organism can take up to 2 weeks to culture and is thus particularly amenable as a candidate for molecular detection because molecular detection has a significantly higher sensitivity compared to traditional techniques.

The recognition of atypical, difficult-to-culture bacteria species as infecting organisms has led researchers to suggest long-term (2-week) cultures of specimens as standard practice. Using mole-cular detection, however, additional infecting organisms can be identified that may be missed with traditional cultures of shorter duration.

The detection and identification of bacterial orthopaedic infections are ongoing biomedical challenges. Culture-positive cases may represent only a small percentage of infecting organisms, and knowing the proper species and antibiotic sensitivity is crucial for effective treatment. Molecular techniques have shown exciting early promise, but before they are widely adopted, they will need to be proven useful and cost-effective in everyday clinical situations.

Dr. Bergin is a fellow in orthopaedic trauma at Orthopaedics Indianapolis. He can be reached at patbergin@gmail.com

Dr. Tuan is director of the Center for Cellular and Molecular Engineering; professor and executive vice chair for orthopaedic research, department of orthopaedic surgery; and professor of bioengineering at the University of Pittsburgh School of Medicine. He can be reached at rst13@pitt.edu

Disclosure information: Dr. Bergin—no conflicts; Dr. Tuan—Alacer Technologies; Wiley; Journal of Arthroplasty; Osteoarthritis and Cartilage; Birth Defects Research Part C: Embryo Today; Stem Cell Research and Therapy; Biomaterials; American Society for Matrix Biology; Tissue Engineering and Regenerative Medicine International Society.

References:

  1. Tunney MM, Patrick S, Curran MD, Ramage G, Hanna D, Nixon JR, Gorman SP, Davis RI, Anderson N. Detection of prosthetic hip infection at revision arthroplasty by immunofluorescence microscopy and PCR amplification of the bacterial 16S rRNA gene. J Clin Microbiol. 1999; 37: 3281-90.
  2. Mariani BD, Tuan RS. Advances in the diagnosis of infection in prosthetic joint implants. Mol Med Today. 1998; 4: 207-13.
  3. Birmingham P, Helm JM, Manner PA, Tuan RS. Simulated joint infection assessment by rapid detection of live bacteria with real-time reverse transcription polymerase chain reaction. J Bone Joint Surg Am. 2008; 90: 602-8.
  4. Bergin PF, Doppelt JD, Hamilton WG, Mirick GE, Jones AE, Sritulanondha S, Helm JM, Tuan RS. Detection of periprosthetic infections with use of ribosomal RNA-based polymerase chain reaction. J Bone Joint Surg Am. 2010; 92: 654-63.
  5. Dodson CC, Craig EV, Cordasco FA, Dines DM, Dines JS, Dicarlo E, Brause BD, Warren RF. Propionibacterium acnes infection after shoulder arthroplasty: a diagnostic challenge. J Shoulder Elbow Surg. 2010; 19: 303-7.