A COMPARISON OF TWO METHODS FOR THE DETECTION OF FECAL POLLUTION IN DRINKING WATER (HYDROGEN SULFIDE, INDICATOR, MODIFICATION)

A new technique for the detection of microbiological fecal pollution in drinking and in raw surface water has been modified and tested against the standard multiple-tube fermentation technique (most-probable-number, MPN). The performance of the new test in detecting fecal pollution in drinking water has been tested at different incubation temperatures. The basis for the new test was the detection of hydrogen sulfide produced by the hydrogen sulfide producing bacteria which are usually associated with the coliform group. The positive results are indicated by the appearance of a brown to black color in the contents of the fermentation tube within 18 to 24 hours of incubation at 35 (+OR-) .5(DEGREES)C. For this study 158 water samples of different sources have been used. The results were analyzed statistically with the paired t-test and the one-way analysis of variance. No statistically significant difference was noticed between the two methods, when tested 35 (+OR-) .5(DEGREES)C, in detecting fecal pollution in drinking water. The new test showed more positive results with raw surface water, which could be due to the presence of hydrogen sulfide producing bacteria of non-fecal origin like Desulfovibrio and Desulfomaculum. The survival of the hydrogen sulfide producing bacteria and the coliforms was also tested over a 7-day period, and the results showed no significant difference. The two methods showed no significant difference when used to detect fecal pollution at a very low coliform density. The results showed that the new test is mostly effective, in detecting fecal pollution in drinking water, when used at 35 (+OR-) .5(DEGREES)C. The new test is effective, simple, and less expensive when used to detect fecal pollution in drinking water and raw surface water at 35 (+OR-) .5(DEGREES)C. The method can be used for qualitative and/or quantitative analysis of water in the field and in the laboratory. ^

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.