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Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.

ABSTRACT: AIM:To design and validate broad-range 16S rRNA primers for use in high throughput sequencing to classify bacteria isolated from the human foregut microbiome. METHODS:A foregut microbiome dataset was constructed using 16S rRNA gene sequences obtained from oral, esophageal, and gastric microbiomes produced by Sanger sequencing in previous studies represented by 219 bacterial species. Candidate primers evaluated were from the European rRNA database. To assess the effect of sequence length on accuracy of classification, 16S rRNA genes of various lengths were created by trimming the full length sequences. Sequences spanning various hypervariable regions were selected to simulate the amplicons that would be obtained using possible primer pairs. The sequences were compared with full length 16S rRNA genes for accuracy in taxonomic classification using online software at the Ribosomal Database Project (RDP). The universality of the primer set was evaluated using the RDP 16S rRNA database which is comprised of 433 306 16S rRNA genes, represented by 36 phyla. RESULTS:Truncation to 100 nucleotides (nt) downstream from the position corresponding to base 28 in the Escherichia coli 16S rRNA gene caused misclassification of 87 (39.7%) of the 219 sequences, compared with misclassification of only 29 (13.2%) sequences with truncation to 350 nt. Among 350-nt sequence reads within various regions of the 16S rRNA gene, the reverse read of an amplicon generated using the 343F/798R primers had the least (8.2%) effect on classification. In comparison, truncation to 900 nt mimicking single pass Sanger reads misclassified 5.0% of the 219 sequences. The 343F/798R amplicon accurately assigned 91.8% of the 219 sequences at the species level. Weighted by abundance of the species in the esophageal dataset, the 343F/798R amplicon yielded similar classification accuracy without a significant loss in species coverage (92%). Modification of the 343F/798R primers to 347F/803R increased their universality among foregut species. Assuming that a typical polymerase chain reaction can tolerate 2 mismatches between a primer and a template, the modified 347F and 803R primers should be able to anneal 98% and 99.6% of all 16S rRNA genes in the RDP database. CONCLUSION:347F/803R is the most suitable pair of primers for classification of foregut 16S rRNA genes but also possess universality suitable for analyses of other complex microbiomes.

SUBMITTER: Nossa CW

PROVIDER: S-EPMC2932916 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.

Nossa Carlos W CW Oberdorf William E WE Yang Liying L Aas Jørn A JA Paster Bruce J BJ Desantis Todd Z TZ Brodie Eoin L EL Malamud Daniel D Poles Michael A MA Pei Zhiheng Z

World journal of gastroenterology 20100901 33

<h4>Aim</h4>To design and validate broad-range 16S rRNA primers for use in high throughput sequencing to classify bacteria isolated from the human foregut microbiome.<h4>Methods</h4>A foregut microbiome dataset was constructed using 16S rRNA gene sequences obtained from oral, esophageal, and gastric microbiomes produced by Sanger sequencing in previous studies represented by 219 bacterial species. Candidate primers evaluated were from the European rRNA database. To assess the effect of sequence ...[more]

PMID: 20806429

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Project description:The microorganisms inhabiting many petroleum reservoirs are multi-extremophiles capable of surviving in environments with high temperature, pressure and salinity. Their activity influences oil quality and they are an important reservoir of enzymes of industrial interest. To study these microbial assemblages and to assess any modifications that may be caused by industrial practices, the bacterial and archaeal communities in waters from four Algerian oilfields were described and compared. Three different types of samples were analyzed: production waters from flooded wells, production waters from non-flooded wells and injection waters used for flooding (water-bearing formations). Microbial communities of production and injection waters appeared to be significantly different. From a quantitative point of view, injection waters harbored roughly ten times more microbial cells than production waters. Bacteria dominated in injection waters, while Archaea dominated in production waters. Statistical analysis based on the relative abundance and bacterial community composition (BCC) revealed significant differences between production and injection waters at both OTUs0.03 and phylum level. However, no significant difference was found between production waters from flooded and non-flooded wells, suggesting that most of the microorganisms introduced by the injection waters were unable to survive in the production waters. Furthermore, a Venn diagram generated to compare the BCC of production and injection waters of one flooded well revealed only 4% of shared bacterial OTUs. Phylogenetic analysis of bacterial sequences indicated that Alpha-, Beta- and Gammaproteobacteria were the main classes in most of the water samples. Archaeal sequences were only obtained from production wells and each well had a unique archaeal community composition, mainly belonging to Methanobacteria, Methanomicrobia, Thermoprotei and Halobacteria classes. Many of the bacterial genera retrieved had already been reported as degraders of complex organic molecules and pollutants. Nevertheless, a large number of unclassified bacterial and archaeal sequences were found in the analyzed samples, indicating that subsurface waters in oilfields could harbor new and still-non-described microbial species.

Project description:BACKGROUND: Sample storage conditions, extraction methods, PCR primers, and parameters are major factors that affect metagenomics analysis based on microbial 16S rRNA gene sequencing. Most published studies were limited to the comparison of only one or two types of these factors. Systematic multi-factor explorations are needed to evaluate the conditions that may impact validity of a microbiome analysis. This study was aimed to improve methodological options to facilitate the best technical approaches in the design of a microbiome study. Three readily available mock bacterial community materials and two commercial extraction techniques, Qiagen DNeasy and MO BIO PowerSoil DNA purification methods, were used to assess procedures for 16S ribosomal DNA amplification and pyrosequencing-based analysis. Primers were chosen for 16S rDNA quantitative PCR and amplification of region V3 to V1. Swabs spiked with mock bacterial community cells and clinical oropharyngeal swabs were incubated at respective temperatures of -80°C, -20°C, 4°C, and 37°C for 4 weeks, then extracted with the two methods, and subjected to pyrosequencing and taxonomic and statistical analyses to investigate microbiome profile stability. RESULTS: The bacterial compositions for the mock community DNA samples determined in this study were consistent with the projected levels and agreed with the literature. The quantitation accuracy of abundances for several genera was improved with changes made to the standard Human Microbiome Project (HMP) procedure. The data for the samples purified with DNeasy and PowerSoil methods were statistically distinct; however, both results were reproducible and in good agreement with each other. The temperature effect on storage stability was investigated by using mock community cells and showed that the microbial community profiles were altered with the increase in incubation temperature. However, this phenomenon was not detected when clinical oropharyngeal swabs were used in the experiment. CONCLUSIONS: Mock community materials originated from the HMP study are valuable controls in developing 16S metagenomics analysis procedures. Long-term exposure to a high temperature may introduce variation into analysis for oropharyngeal swabs, suggestive of storage at 4°C or lower. The observed variations due to sample storage temperature are in a similar range as the intrapersonal variability among different clinical oropharyngeal swab samples.

Dataset Information

Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.

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Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome.

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