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Dissecting Species Mixtures in Oral Bacterial Floras Using T-RFLP Analysis
Workflow for Applied Biosystems 3130 Genetic Analyzer, software, and standards. |
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Applying Molecular Techniques for Better Identification
Bacteria inhabiting the human mouth comprise a complex mixture of species. Prior to 1990, oral bacteria were primarily analyzed by labor intensive culture methods, which required experienced technical staff to isolate single colonies, identify bacterial forms, and observe physiological and biochemical characteristics. These methods suffered from several drawbacks, including the requirement for various selection media and complicated culture techniques. In addition, because several oral bacterial species require undefined nutrient sources or extremely anaerobic environments for growth, it is thought that only about 50% of oral bacterial species could be isolated and identified using culture methods.
Figure 1. Overview of T-RFLP Fragment Analysis.
The accuracy and ease with which bacterial species are identified have been improved through the use of molecular biology-based analysis methods. One such method targets the small subunit of ribosomal RNA (SSU rRNA). SSU rRNA is present in every organism, and one of the genes encoding it, 16S RNA contains several highly conserved regions, making cloning 16S rRNA from new organisms relatively easy. For these reasons, 16S rRNA is a very valuable marker for identification and evolution studies in all organisms, including bacteria. Terminal restriction fragment length polymorphism (T-RFLP) is a PCR-based method used to characterize the 16S rRNA gene, and was first employed in the analysis of a variety of samples containing mixed bacterial species, including activated sludge, bioreactor sludge, aquifer sand, and termite guts by Liu and others [1] in 1997. Sakamoto et al. applied the technique for the first time in the analysis of the oral bacterial floras in human [2], and it was later used to evaluate the effectiveness of periodontal disease treatments [3]. This article outlines the method and workflow of a T-RFLP study of oral bacterial flora using the Applied Biosystems 310 Genetic Analyzer, GeneScan™ size standards, and fragment analysis software.
Overview of the T-RFLP Method
The T-RFLP method is a multiple-fragment analysis method that can be performed on mixtures of bacteria. First, the 16S rRNA genes in the mixture are amplified using gene-specific primers that are tagged with a fluorescent label. The amplified products are then cut with one (or more) restriction enzymes, and the fragments separated by capillary electrophoresis.The data collected corresponds to the fragments that were still attached to a fluorescent tag after the restriction digest, hence the term "terminal restriction fragment" or T-RF. Various parameters are evaluated including (1) fluorescence intensity (taken from the peak height of the fragment, which can be used as a rough guide to the relative abundance of a particular species in the mixture); (2) fragment size (position of the peak with respect to a size standard); (3) and the number of fragments produced (usually only one fragment per bacterial species). The T-RFLP is particularly suited to 16S rRNA analysis and is highly reproducible because it lacks the cloning steps required for the creation of an 16S rRNA library. It is simpler than the DGGE/TGGE methods because the T-RFLP data can be stored in databases for easy comparison.
Figure 2. Workflow of Bacterial Floral Analysis Using T-RFLP.
Processing Samples on an Applied Biosystems Genetic Analyzer
First, using DNA extracted from saliva, and the bottom plaque of gingival margin as templates, PCR amplification of the 5' end is performed using the universal primer 27F (5'-AGAGTTTGATCCTGGCTCAG-3' labeled with 6-FAM™ dye label attached) and primer 1492R (5'-GGTTACCTTGTTACGACTT-3' with no dye label attached). The amplified products are cleaned up and used in separate restriction reactions with 4-base cutters (HhaI, MspI, AluI, HaeIII, or RsaI), according to the method of Sakamoto et al. [4]. A 1 µL aliquot of the digested product is mixed with 1 µL of size standard (equal volumes of GeneScan™ 500 ROX™ and GeneScan™ 1000 ROX™ Size Standards) and 8 µL of Hi-Di™ formamide. The sample is heat denatured (95°C for 2 minutes) and analyzed using an Applied Biosystems 310 (using a 47 cm capillary and POP-4™ polymer). Processing time is generally around 48 minutes.
This method is easily adapted to the 3130 Genetic Analyzer. Using the newer GeneScan 1200 LIZ Size Standard, mixing of the GeneScan 500 and 1000 ROX Size Sandards is no longer required. See the sidebar, Further T-RFLP Workflow Enhancements, for additional benefits.
Protocol Refinements for Improved Data Accuracy
The size calling of T-RFs depends on the analysis platform used. In the analysis of large numbers of samples, it is necessary to standardize the instrument, capillary, polymer, and size standard used. There is a certain amount of deviation that can occur between the predicted value and the measured value of the size of the T-RFs, and this should be taken into consideration when making species assignments based on T-RFLP analysis. In order to improve the accuracy of species identification, T-RFLP analysis using two different restriction enzymes (HhaI and MspI) and 16S rRNA cloned library analysis were performed to estimate the bacterial species at each peak. Using multiple restriction enzymes in the T-RFLP analysis (for example, HhaI, MspI, AluI, HaeIII, or RsaI) and simultaneously performing 16S rRNA cloned library analysis early on in the experiment is an effective validation step. As data is accumulated, species identifications using T-RFLP data alone can be carried out with more confidence.
More Accurate Identification of Bacteria in Less Time
T-RFLP analysis using the 310 Genetic Analyzer, fragment analysis software, and GeneScan™ Size Standards provides a way to quickly and easily identify bacteria in complex samples and evaluate the effects of various environmental factors on bacterial populations compared to conventional methods like polyacrylamide gels.
Acknowledgements: We would like to acknowledge Dr. Mitsuo Sakamoto, from RIKEN BioResource Center,
Wako, Japan, for allowing us to share his study and protocol for this article.
References
1. Liu W-T, Marsh TL, Cheng H, Forney LJ (1997) Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol 63:4516-4522.
2. Sakamoto M, Takeuchi Y, Umeda M, Ishikawa I, Benno Y. (2003). Application of terminal RFLP analysis to characterize oral bacterial flora in saliva of healthy subjects and patients with periodontitis. J Med Microbiol 52:79-89.
3. Sakamoto M, Huang Y, Ohnishi M, Umeda M, Ishikawa I, Benno Y. (2004) Changes in oral microbial profiles after periodontal treatment as determined by molecular analysis of 16S rRNA genes. J Med Microbiol 53:563-571.
4. Sakamoto M, Rôças IN, Siqueira JF Jr, Benno Y (2006) Molecular analysis of bacteria in asymptomatic and symptomatic endodontic infections. Oral Microbiol Immunol 21:112-122.
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Using Gene Expression Signatures to Predict Biomarkers for Non-genotoxic Carcinogenesis
TaqMan® Gene Expression Assays and Custom TaqMan® Arrays
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TaqMan® Gene Expression Assays and Arrays can be used to generate gene expression signatures that define a particular biological [process/disease], and to identify specific biomarkers affecting that process. Recently the Carcinogenicity Working Group of The Critical Path Institute's Predictive Safety Testing Consortium (PSTC)—a collaboration of industry, academia, and government research groups aimed at evaluating and qualifying biomarkers for a variety of toxicological endpoints—used TaqMan® Gene Expression Assays and Arrays to both validate and extend existing microarray data generated to predict non-genotoxic carcinogens that chemically induce hepatic tumorigenicity in rats.
While the microarray data seemed capable of classifying specific gene products as potential carcinogens; variation in treatment protocols, measurement platform, and data analysis revealed a need for assay standardization. This prompted the PSTC to re-derive the gene expression signatures on a higher throughput and more cost-effective measurement platform (quantitative PCR arrays) and begin standardizing the treatment protocol to enable robust/analogous predictions/results across laboratories.
Gene expression signatures were therefore repeated on a quantitative real-time PCR platform using liver RNA from rats treated with various carcinogens. Individual TaqMan® Gene Expression Assays (probe/primer sets) were designed to 26 genes from the original signatures that showed potential for classification as carcinogens. RNA samples were re-isolated from rats treated with over 70 non-genotoxic carcinogens and non-carcinogens. High throughput real-time PCR was performed on the Applied Biosystems 7900HT Fast Real-Time PCR System. The TaqMan® Arrays were run by the licensed Service Provider, Asuragen who also undertook the data analysis (www.asuragenservices.com/corporate/about_us.aspx).
TaqMan® Gene Expression Assays for the individual predictive genes showed good concordance with the microarray data, prompting efforts to replicate the predictive signature on a Custom TaqMan® Array. Current efforts are underway to further evaluate the accuracy and precision of the quantitative PCR signature, and the optimal protocol for maximizing predictivity in short-term in vivo rat studies.
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TaqMan® Arrays for Gene Expression Analysis
TaqMan® Arrays use pre-selected or custom TaqMan® Gene Expression Assay sets arrayed onto a 384-well micro fluidic card. Choose from over 20 pre-defined TaqMan® Array Gene Signature micro fluidic cards, or customize your own using any of over 50,000 pre-designed TaqMan® Gene Expression Assays for human, mouse, rat, Arabidopsis, Drospophila, C. elegans, Rhesus macaque, or canine genes.
The card format streamlines reaction set-up time, eliminates the need for liquid-handling robotics, and provides standardization across multiple users and/or multiple labs. This format is ideal for analyzing many samples across a fixed number of targets, such as for biomarker screening. TaqMan® Arrays arrive ready to use, with your selected TaqMan® Gene Expression Assays pre-loaded into each of the 384 reaction wells. Simply add 100 mL sample mix (sample cDNA and TaqMan® PCR Master Mix) to each of the eight sample ports and run on an Applied Biosystems 7900HT Fast Real-Time PCR System.
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Reliable Aneuploidy Detection with QF-PCR Analysis of STR Markers
3500xL Genetic Analyzer • GeneScan™ 600 LIZ® Size Standard v2.0 • GeneMapper® Software v4.1
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Aneuploidy is the term used to describe cells, which have nuclei that do not have an exact multiple of a haploid chromosome set. These alterations in chromosome number give rise to serious genetic diseases such as Turner Syndrome, Down Syndrome, and Klinefelter Syndrome; therefore early detection of these anomalies is critical. Quantitative fluorescent PCR (QF-PCR) of short tandem repeat (STR) genetic markers is commonly used to detect aneuploidy, and laboratories that routinely perform these types of analyses demand high-throughput, efficient, and highly automated solutions. Applied Biosystems meets this demand with the 3500xL Genetic Analyzer, the GeneScan™ 600 LIZ® Size Standard v2.0, the corresponding instrument run module and Data Collection Software v1.0, and GeneMapper® Software v4.1 for data analysis. This platform delivers increased throughput and a combination of hardware, software, and consumable innovations result in improved data quality that is critical for aneuploidy analysis.
The QF-PCR Assay for Aneuploidy Detection
Aneuploidy detection by QF-PCR is rapid and informative and relies on the amplification and analysis of short tandem repeat (STR) genetic markers. STRs, also known as microsatellites, are polymorphic DNA loci that contain a repeat sequence of 2 to 6 bases. The number of repeats for a given locus may vary, leading to allele length differences among individuals. To achieve a number of informative markers for aneuploidy analysis, the relative quantitation of multiple STRs must be determined.
A 19-plex STR assay was developed by the laboratory of Dr Roland Achmann, genteQ (Hamburg, Germany), and was used for the aneuploidy analysis presented here. The assay amplifies genomic DNA (isolated from amniotic fluid samples) using PCR primer pairs—one of the two primers for each locus is labeled with FAM®, VIC™, NED®, or PET™ dyes (fluorescent dyes comprising the Applied Biosystems G5 dye set). Following the completion of the PCR, aliquots of the resulting dye-labeled amplicons were combined with the GeneScan™ 600 LIZ Size Standard v2.0. Samples were electrophoresed on the 3500xL Genetic Analyzer using a 50 cm capillary array and 3500 POP-7™ Polymer. The instrument protocol used was the FragmentAnalysis50_POP7 run module in combination with the G5 dye set.
Rapid and Reproducible Aneuploidy Analysis Capabilities
The advanced capabilities of 3500xL Series Genetic Analyzer, including new thermal control systems, enhanced optical detection, and new consumables designs provide an easy-to-use platform for the detection and analysis of multiplexed QF-PCR assays. The use of an optional normalization reagent (the GeneScan™ 600 LIZ® Size Standard v2.0), associated Instrument Protocol, with new normalization algorthims enable increased reproduciblity in peak height determinations, which is particularly important in DNA fragment sizing applications such as aneuploidy analysis by QF-PCR. In addition, the flexible GeneMapper® Software v4.1 can be configured to provide reports and calculations to give user-configured tools for reporting multiplexed QF-PCR assay results.
Introducing the Applied Biosystems 3500xL Genetic Analyzer
The Applied Biosystems 3500xL Genetic Analyzer provides researchers with powerful multiplexing capabilities when analyzing STR samples, increasing throughput and data accuracy. By labeling different STR amplicons with unique dyes, fragments of the same size (or overlapping sizes) can be run in the same capillary. Finally, by employing both the in-lane GeneScan™ 600 LIZ® Size Standard v2.0 and the corresponding primary analysis protocol, researchers can take advantage of the normalization feature of the 3500xL Genetic Analyzer. This is of particular benefit in aneuploidy analysis, which relies on detecting small but significant differences in peak height to correctly assign ploidy status. |
Data Analysis Using GeneMapper® Software v4.1
Accurate allele scoring, a critical requirement for aneuploidy studies and other STR-based experiments, relies on the efficient collection and analysis of large amounts of data from highly automated workflows. New Windows Vista® compatible GeneMapper® software v4.1 offers flexible and highly customizable data display and analysis functions for the consistent and accurate QF-PCR sample processing.
In addition to advanced algorithms that recognize and filter amplification chemistry artifacts, such as stutter peaks, GeneMapper® Software contains a convenient Report Manager feature that can automatically calculate and report various experimental parameters using default or user-defined equations. For example, the Report Manager feature can be used to specify and automate the typical multistep calculations that are necessary to determine values for allelic peak-area ratios (A1/A2), and to alert the user when possible aneuploidy is detected: trisomy exhibiting three alleles for a single locus (1:1:1 allelic ratio) or trisomy exhibiting unbalanced allelic ratios (2:1 allelic ratio).
In the present study, the Report Manager feature flagged various markers from chromosome 21 as potential aneuploidy candidates. The data shown in Figure 1 highlight the well-resolved peaks that were obtained for all aneuploidy markers on the Applied Biosystems 3500xL Genetic Analyzer, and these electropherogram plot views were vital for the confirmation of the peak area calculation results.
Figure 1. Electropherograms of Aneuploidy Markers Run on the Applied Biosystems 3500xL Genetic Analyzer and Separated by Dye Color. Tri-allelic loci are indicated by arrows A, B, and D, and Di-allelic loci with non-normal peak area ratios are indicated by arrows C and E.
Acknowledgement
Applied Biosystems would like to acknowledge the generous contribution of QF-PCR aneuploidy samples from Dr Roland Achmann, genteQ (Hamburg, Germany), which were used to generate the data shown in Figure 1.
Take a closer look at the 3500 Genetic Analyzers at
www.appliedbiosystems.com/3500Series.
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