49 research outputs found
Comparison of DNA extraction kits for PCR-DGGE analysis of human intestinal microbial communities from fecal specimens
<p>Abstract</p> <p>Background</p> <p>The influence of diet on intestinal microflora has been investigated mainly using conventional microbiological approaches. Although these studies have advanced knowledge on human intestinal microflora, it is imperative that new methods are applied to facilitate scientific progress. Culture-independent molecular fingerprinting method of Polymerase Chain Reaction and Denaturing Gradient Gel Electrophoresis (PCR-DGGE) has been used to study microbial communities in a variety of environmental samples. However, these protocols must be optimized prior to their application in order to enhance the quality and accuracy of downstream analyses. In this study, the relative efficacy of four commercial DNA extraction kits (Mobio Ultra Clean<sup>® </sup>Fecal DNA Isolation Kit, M; QIAamp<sup>® </sup>DNA Stool Mini Kit, Q; FastDNA<sup>® </sup>SPIN Kit, FSp; FastDNA<sup>® </sup>SPIN Kit for Soil, FSo) were evaluated. Further, PCR-DGGE technique was also assessed for its feasibility in detecting differences in human intestinal bacterial fingerprint profiles.</p> <p>Method</p> <p>Total DNA was extracted from varying weights of human fecal specimens using four different kits, followed by PCR amplification of bacterial 16S rRNA genes, and DGGE separation of the amplicons.</p> <p>Results</p> <p>Regardless of kit, maximum DNA yield was obtained using 10 to 50 mg (wet wt) of fecal specimens and similar DGGE profiles were obtained. However, kits FSp and FSo extracted significantly larger amounts of DNA per g dry fecal specimens and produced more bands on their DGGE profiles than kits M and Q due to their use of bead-containing lysing matrix and vigorous shaking step. DGGE of 16S rRNA gene PCR products was suitable for capturing the profiles of human intestinal microbial community and enabled rapid comparative assessment of inter- and intra-subject differences.</p> <p>Conclusion</p> <p>We conclude that extraction kits that incorporated bead-containing lysing matrix and vigorous shaking produced high quality DNA from human fecal specimens (10 to 50 mg, wet wt) that can be resolved as bacterial community fingerprints using PCR-DGGE technique. Subsequently, PCR-DGGE technique can be applied for studying variations in human intestinal microbial communities.</p
Molecular techniques for pathogen identification and fungus detection in the environment
Many species of fungi can cause disease in plants, animals and humans. Accurate and robust detection and quantification of fungi is essential for diagnosis, modeling and surveillance. Also direct detection of fungi enables a deeper understanding of natural microbial communities, particularly as a great many fungi are difficult or impossible to cultivate. In the last decade, effective amplification platforms, probe development and various quantitative PCR technologies have revolutionized research on fungal detection and identification. Examples of the latest technology in fungal detection and differentiation are discussed here
Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators
BACKGROUND: Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. METHODOLOGY/PRINCIPAL FINDINGS: Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and alpha-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. CONCLUSIONS/SIGNIFICANCE: This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health
Analysis of Bacterial Community Composition by Oligonucleotide Fingerprinting of rRNA Genes
One of the first steps in characterizing an ecosystem is to describe the organisms inhabiting it. For microbial studies, experimental limitations have hindered the ability to depict diverse communities. Here we describe oligonucleotide fingerprinting of rRNA genes (OFRG), a method that permits identification of arrayed rRNA genes (rDNA) through a series of hybridization experiments using small DNA probes. To demonstrate this strategy, we examined the bacteria inhabiting two different soils. Analysis of 1,536 rDNA clones revealed 766 clusters grouped into five major taxa: Bacillus, Actinobacteria, Proteobacteria, and two undefined assemblages. Soil-specific taxa were identified and then independently confirmed through cluster-specific PCR of the original soil DNA. Near-species-level resolution was obtained by this analysis as clones with average sequence identities of 97% were grouped in the same cluster. A comparison of these OFRG results with the results obtained in a denaturing gradient gel electrophoresis analysis of the same two soils demonstrated the significance of this methodological advance. OFRG provides a cost-effective means to extensively analyze microbial communities and should have applications in medicine, biotechnology, and ecosystem studies