Optimization of terminal restriction fragment polymorphism (TRFLP) analysis of human gut microbiota
Introduction
Many studies have shown that commensal gut microbes play a significant role in human health (Adlercreutz, 1998, Hart et al., 2002, Hooper and Gordon, 2001). The microorganisms in the adult human intestine, which include at least 800 species of bacteria, metabolize compounds that might otherwise be unavailable for human nutrition (Cummings and Macfarlane, 1997, Eckburg et al., 2005). Bacterial consortia, consisting of numerous species, have the potential to produce bioactive agents from the diet. However, certain conversions are only observed in part of the population suggesting that some people lack the necessary microbiota to convert these compounds to chemopreventive molecules (Adlercreutz, 1998, Atkinson et al., 2004, Atkinson et al., 2005). Thus, inter-individual variation in the gut microbial community may be linked to inter-individual variation in the risk of cancer or other diseases (Adlercreutz, 1998, Atkinson et al., 2005, Duncan et al., 2000).
Gut community fingerprinting techniques, such as terminal restriction fragment polymorphism (TRFLP) analysis (Liu et al., 1997), potentially offer a rapid overview of inter-individual differences in gut microbial communities. When comparing the TRFLP data generated from different communities, variation can be found in the number and size of peaks and can be evaluated by adapting community parameters such as richness and evenness (Dunbar et al., 2000, Margalef, 1958). These data provide quantitative information on the compositional differences of gut microbial communities (Osborn et al., 2000) with the potential to serve as a biomarker in high-throughput population-based studies.
To be useful as a biomarker, TRFLP data need to be highly reproducible and reflect gut microbial community composition. Methodological parameters such as sampling technique and DNA extraction, have the potential to influence the TRFLP fingerprint of microbial community (Burgmann et al., 2001). Therefore, obtaining microbial genomic DNA that accurately represents the gut microbial community is important (Osborn et al., 2000). When extracting genomic DNA from a complex matrix such as feces, not only is extraction efficiency of genomic DNA from a wide variety of bacteria a consideration but removal of contaminants that co-elute with the DNA that may interfere with further molecular analyses is important as well. Several studies have explored different DNA extraction and molecular typing methods for application to human fecal microflora characterization (Li et al., 2003, McOrist et al., 2002, Sicinschi et al., 2003, Subrungruang et al., 2004, Yu and Morrison, 2004), however, few studies have evaluated the TRFLP method for large-scale, human population-based study (Sakamoto et al., 2003, Wang et al., 2004).
Here, we report a study designed to optimize tRFLP analysis of the fecal microbial community associated with human population-based studies. We evaluated the efficiency of DNA extraction from human feces using two commercial kits. These kits were chosen because previous studies have shown that they lysed fecal bacterial cells efficiently resulting in a representative genomic community DNA and they both have been shown to remove environmental organic contaminants which otherwise interfere with down-stream molecular analyses (Li et al., 2003, Yu and Morrison, 2004). In addition, we analyzed the effect of homogenization on variation in DNA extraction and tRFLP fingerprints and the effect of temperature and physical disruption during the cell lysis procedure on TRFLP fingerprints. Once the TRFLP fingerprint was optimized, we applied the approach to evaluate methodological and inter-individual variation in fecal microbial community fingerprints that showed the reliability of this biomarker for use in human population-based studies. These data can be used to estimate the sample size needed to characterize the fecal microbiota in human-population based studies.
Section snippets
Human subject and sample collection
Three healthy women, aged 32 to 48, donated fecal samples for this study. First, we collected a fecal sample from one woman to explore the best method to extract representative fecal bacterial genomic DNA for TRFLP fingerprinting of the fecal microbiota. To compare the methodological and inter-individual variation as related to tRFLP analysis, we obtained fecal samples from two additional women. All activities were approved by the Institutional Review Board of the Fred Hutchinson Cancer
The effect of extraction variables on quality and quantity of fecal genomic DNA
The effect of physical disruption of bacterial cells on the quality of genomic DNA extracted was evaluated by gel electrophoresis (Fig. 1). DNA was sheared more severely by longer bead beating although 30-s and 1-min bead beating treatments did not notably affect DNA quality. DNA yield varied significantly between different extraction techniques (Fig. 2). In general, more DNA was obtained using the stool kit than the soil kit. Both bead beating and higher incubation temperature treatments
Discussion
We investigated the effectiveness of TRFLP as a biomarker of the human fecal microbial community. We chose TRFLP of the 16S rRNA gene over other fingerprinting techniques because it has the advantage of being rapid and reproducible (Dunbar et al., 2000, Osborn et al., 2000). As in other molecular typing methods, there are many variables that could potentially bias the outcome of TRFLP analysis. Here, we tested various DNA extraction parameters that influenced the TRFLP peak composition in
References (38)
- et al.
In vitro incubation of human feces with daidzein and antibiotics suggests interindividual differences in the bacteria responsible for equal production
J. Nutr.
(2004) - et al.
A strategy for optimizing quality and quantity of DNA extracted from soil
J. Microbiol. Methods
(2001) - et al.
Colonic microflora: nutrition and health
Nutrition
(1997) - et al.
Post-amplification Klenow fragment treatment alleviates PCR bias caused by partially single-stranded amplicons
J. Microbiol. Methods
(2005) - et al.
Evaluation of QIAamp DNA stool mini kit for ecological studies of gut microbiota
J. Microbiol. Methods
(2003) - et al.
A comparison of five methods for extraction of bacterial DNA from human faecal samples
J. Microbiol. Methods
(2002) - et al.
A comparison of DNA profiling techniques for monitoring nutrient impact on microbial community composition during bioremediation of petroleum contaminated soils
J. Microbiol. Methods
(2003) - et al.
Detection and typing of Helicobacter pylori cagA/vacA genes by radioactive, one-step polymerase chain reaction in stool samples from children
J. Microbiol. Methods
(2003) - et al.
T-RFLP combined with principal component analysis and 16S rRNA gene sequencing: an effective strategy for comparison of fecal microbiota in infants of different ages
J. Microbiol. Methods
(2004) - et al.
DNA isolation protocols affect the detection limit of PCR approaches to bacteria in samples for the human gastrointestinal tract
Syst. Appl. Microbiol.
(2001)
Evolution, nutrition, intestinal microflora, and prevention of cancer: a hypothesis
Gut bacterial metabolism of the soy isoflavone daidzein: exploring the relevance to human health
Exp. Biol. Med. (Maywood)
Phylum- and class-specific PCR primers for general microbial community analysis
Appl. Environ. Microbiol.
Assessment of microbial diversity in four southwestern United States soils by 16S rRNA gene terminal restriction fragment analysis
Appl. Environ. Microbiol.
Premenopausal equal excretors show plasma hormone profiles associated with lowered risk of breast cancer
Cancer Epidemiol. Biomark. Prev.
Diversity of the human intestinal microbial flora
Sci. Total Environ.
Formation of pseudo-terminal restriction fragments, a PCR-related bias affecting terminal restriction fragment length polymorphism analysis of microbial community structure
Appl. Environ. Microbiol.
The role of the gut flora in health and disease, and its modification as therapy
Aliment. Pharmacol. Ther.
Commensal host-bacterial relationships in the gut
Science
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