Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome
- PMID: 20806429
- PMCID: PMC2932916
- DOI: 10.3748/wjg.v16.i33.4135
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.
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