Identification of the Causative Bacteria in Musculoskeletal Infections Using 16s rDNA - Denaturing Gradient Gel Electrophoresis Analysis

Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

Suppression of peripheral blood mononuclear cell proliferation by a periodontopathic bacteria {\it Actinobacillus actinomycetemcomitans\/}

Actinobacillus actinomycetemcomitans (Aa) is a gram-negative coccobacillus implicated as a major pathogen in juvenile periodontitis. The immunosuppressive activity of a sonic extract (designated 100SN) derived from Aa was investigated. 100SN suppressed spontaneous proliferation as well as proliferative response to the mitogens, PHA and PWM, of human peripheral blood mononuclear cells (PBMC). 100SN-induced suppression of PHA-stimulated proliferation was heat-sensitive, inactivated by pronase and trypsin, dose-dependent and non-cytotoxic. There were no significant changes in the CD4$\sp+$ or CD8$\sp+$ subsets of PBMC after 7-day incubation with 100SN. There was a trend toward increased levels of the CD4$\sp+$CD45R$\sp{\rm hi}$CDw29$\sp{\rm lo}$ (naive cells, associated with suppressor-inducer activity) and CD4$\sp+$CDw29$\sp{\rm hi}$CD45R$\sp{\rm lo}$ (memory cells, associated with helper-inducer activity) subsets. The target of 100SN appeared to be the non-adherent cells and suppression by 100SN could not be reversed by indomethacin (IDM), the cyclo-oxygenase inhibitor of prostaglandin (PG) synthesis. The mechanism of 100SN-induced suppression was studied in terms of inhibition involving IL-2-regulated T cell proliferation and the results point to the possibility that suppression occurred subsequent to IL-2 receptor binding.^ The suppressive activity observed could occur through multiple mechanisms including cell-cell; contact or release of soluble factors. Supernatants derived from 7-day cultures of PBMC and 100SN (designated CSN-A) were able to suppress proliferative response of PBMC to PHA without affecting cell viability. Analysis of CSN-A showed that it contained PGE2 and soluble IL-2 receptors. Suppression by CSN-A could be partially overcome by either IDM or exogenous IL-2. Significant suppression was also maintained when both IDM and exogenous IL-2 were added at the same time. These findings suggest that PGE2 and soluble IL-2 receptors contribute to the suppression observed but other suppressive cytokine(s) may be involved. Collectively, the data indicate that a factor derived from oral bacteria associated with juvenile periodontitis have profound effects on cellular immune responses, and that these effects may be partially mediated by secondary factors produced by the host in response to the bacteria. ^

Systematic interpretation of molecular beacon polymerase chain reaction for identifying rpoB mutations in Mycobacterium tuberculosis isolates with mixed resistant and susceptible bacteria

Detection of multidrug-resistant tuberculosis (MDR-TB), a frequent cause of treatment failure, takes 2 or more weeks to identify by culture. RIF-resistance is a hallmark of MDR-TB, and detection of mutations in the rpoB gene of Mycobacterium tuberculosis using molecular beacon probes with real-time quantitative polymerase chain reaction (qPCR) is a novel approach that takes ≤2 days. However, qPCR identification of resistant isolates, particularly for isolates with mixed RIF-susceptible and RIF-resistant bacteria, is reader dependent and limits its clinical use. The aim of this study was to develop an objective, reader-independent method to define rpoB mutants using beacon qPCR. This would facilitate the transition from a research protocol to the clinical setting, where high-throughput methods with objective interpretation are required. For this, DNAs from 107 M. tuberculosis clinical isolates with known susceptibility to RIF by culture-based methods were obtained from 2 regions where isolates have not previously been subjected to evaluation using molecular beacon qPCR: the Texas–Mexico border and Colombia. Using coded DNA specimens, mutations within an 81-bp hot spot region of rpoB were established by qPCR with 5 beacons spanning this region. Visual and mathematical approaches were used to establish whether the qPCR cycle threshold of the experimental isolate was significantly higher (mutant) compared to a reference wild-type isolate. Visual classification of the beacon qPCR required reader training for strains with a mixture of RIF-susceptible and RIF-resistant bacteria. Only then had the visual interpretation by an experienced reader had 100% sensitivity and 94.6% specificity versus RIF-resistance by culture phenotype and 98.1% sensitivity and 100% specificity versus mutations based on DNA sequence. The mathematical approach was 98% sensitive and 94.5% specific versus culture and 96.2% sensitive and 100% specific versus DNA sequence. Our findings indicate the mathematical approach has advantages over the visual reading, in that it uses a Microsoft Excel template to eliminate reader bias or inexperience, and allows objective interpretation from high-throughput analyses even in the presence of a mixture of RIF-resistant and RIF-susceptible isolates without the need for reader training.^