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.

Interview with Anna Steinberger

An oral interview with Dr. Anna Steinberger, who taught and conducted basic research in Reproductive Biology and served as Assistant Dean for Faculty Affairs at UT Medical School-Houston. Her research yielded over 250 scientific articles, books, and book chapters for which she received numerous awards and recognitions in the USA and abroad.

Risk factors for Clostridium difficile nosocomial diarrhea in patients at the Michael E. Debakey Veterans Affairs Medical Center, Houston, Texas

Background. Clostridium difficile is the leading cause of hospital associated infectious diarrhea and colitis. About 3 million cases of Clostridium difficile diarrhea occur each year with an annual cost of $1 billion. ^ About 20% of patients acquire C. difficile during hospitalization. Infection with Clostridium difficile can result in serious complications, posing a threat to the patient's life. ^ Purpose. The aim of this research was to demonstrate the uniqueness in the characteristics of C. difficile positive nosocomial diarrhea cases compared with C. difficile negative nosocomial diarrhea controls admitted to a local hospital. ^ Methods. One hundred and ninety patients with a positive test and one hundred and ninety with a negative test for Clostridium difficile nosocomial diarrhea, selected from patients tested between January 1, 2002 and December 31, 2003, comprised the study population. Demographic and clinical data were collected from medical records. Logistic regression analyses were conducted to determine the associated odds between selected variables and the outcome of Clostridium difficile nosocomial diarrhea. ^ Results. For the antibiotic classes, cephalosporins (OR, 1.87; CI 95, 1.23 to 2.85), penicillins (OR, 1.57; CI 95, 1.04 to 2.37), fluoroquinolones (OR, 1.65; CI 95, 1.09 to 2.48) and antifungals (OR, 2.17; CI 95, 1.20 to 3.94), were significantly associated with Clostridium difficile nosocomial diarrhea Ceftazidime (OR, 1.95; CI 95, 1.25 to 3.03, p=0.003), gatifloxacin (OR, 1.97; CI 95, 1.31 to 2.97, p=0.001), clindamycin (OR, 3.13; CI 95, 1.99 to 4.93, p<0.001) and vancomycin (OR, 1.77; CI 95, 1.18 to 2.66, p=0.006, were also significantly associated with the disease. Vancomycin was not statistically significant when analyzed in a multivariable model. Other significantly associated drugs were, antacids, laxatives, narcotics and ranitidine. Prolong use of antibiotics and an increased number of comorbid conditions were also associated with C. difficile nosocomial diarrhea. ^ Conclusion. The etiology for C. difficile diarrhea is multifactorial. Exposure to antibiotics and other drugs, prolonged antibiotic usage, the presence and severity of comorbid conditions and prolonged hospital stay were shown to contribute to the development of the disease. It is imperative that any attempt to prevent the disease, or contain its spread, be done on several fronts. ^