3 resultados para Electrophoresis

em DigitalCommons@The Texas Medical Center


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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.

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Theoretical and empirical studies were conducted on the pattern of nucleotide and amino acid substitution in evolution, taking into account the effects of mutation at the nucleotide level and purifying selection at the amino acid level. A theoretical model for predicting the evolutionary change in electrophoretic mobility of a protein was also developed by using information on the pattern of amino acid substitution. The specific problems studied and the main results obtained are as follows: (1) Estimation of the pattern of nucleotide substitution in DNA nuclear genomes. The pattern of point mutations and nucleotide substitutions among the four different nucleotides are inferred from the evolutionary changes of pseudogenes and functional genes, respectively. Both patterns are non-random, the rate of change varying considerably with nucleotide pair, and that in both cases transitions occur somewhat more frequently than transversions. In protein evolution, substitution occurs more often between amino acids with similar physico-chemical properties than between dissimilar amino acids. (2) Estimation of the pattern of nucleotide substitution in RNA genomes. The majority of mutations in retroviruses accumulate at the reverse transcription stage. Selection at the amino acid level is very weak, and almost non-existent between synonymous codons. The pattern of mutation is very different from that in DNA genomes. Nevertheless, the pattern of purifying selection at the amino acid level is similar to that in DNA genomes, although selection intensity is much weaker. (3) Evaluation of the determinants of molecular evolutionary rates in protein-coding genes. Based on rates of nucleotide substitution for mammalian genes, the rate of amino acid substitution of a protein is determined by its amino acid composition. The content of glycine is shown to correlate strongly and negatively with the rate of substitution. Empirical formulae, called indices of mutability, are developed in order to predict the rate of molecular evolution of a protein from data on its amino acid sequence. (4) Studies on the evolutionary patterns of electrophoretic mobility of proteins. A theoretical model was constructed that predicts the electric charge of a protein at any given pH and its isoelectric point from data on its primary and quaternary structures. Using this model, the evolutionary change in electrophoretic mobilities of different proteins and the expected amount of electrophoretically hidden genetic variation were studied. In the absence of selection for the pI value, proteins will on the average evolve toward a mildly basic pI. (Abstract shortened with permission of author.) ^

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Background. Pulsed-field gel electrophoresis (PFGE) is a laboratory technique in which Salmonella DNA banding patterns are used as molecular fingerprints for epidemiologic study for "PFGE clusters". State and national health departments (CDC) use PFGE to detect clusters of related cases and to discover common sources of bacteria in outbreaks. ^ Objectives. Using Houston Department of Health and Human Services (HDHHS) data, the study sought: (1) to describe the epidemiology of Salmonella in Houston, with PFGE subtype as a variable; and (2) to determine whether PFGE patterns and clusters detected in Houston were local appearances of PFGE patterns or clusters that occurred statewide. ^ Methods. During the years 2002 to 2005, the HDHHS collected and analyzed data from routine surveillance of Salmonella. We implemented a protocol, between May 1, 2007 and December 31, 2007, in which PFGE patterns from local cases were sent via e-mail to the Texas Department of State Health Services, to verify whether the local PFGE patterns were also part of statewide clusters. PFGE was performed from 106 patients providing a sample from which Salmonella was isolated in that time period. Local PFGE clusters were investigated, with the enhanced picture obtained by linking local PFGE patterns to PFGE patterns at the state and national level. ^ Results. We found that, during the years 2002 to 2005, there were 66 PFGE clusters, ranging in size from 2 to 22 patients within each cluster. Between different serotypes, there were marked differences in the sizes of PFGE clusters. A common source or risk factor was found in fewer than 5 of the 66 PFGE clusters. With the revised protocol, we found that 19 of 66 local PFGE patterns were indistinguishable from PFGE patterns at Texas DSHS. During the eight months, we identified ten local PFGE clusters with a total of 42 patients. The PFGE pattern for eight of the ten clusters matched the PFGE patterns for cases reported to Texas DSHS from other geographic areas. Five of the ten PFGE patterns matched PFGE patterns for clusters under investigation at PulseNet at the national level. HDHHS epidemiologists identified a mode of transmission in two of the ten local clusters and a common risk factor in a third local cluster. ^ Conclusion. In the extended-study protocol, Houston PFGE patterns were linked to patterns seen at the state and national level. The investigation of PFGE clusters was more efficacious in detecting a common transmission when local data were linked to state and national data. ^