Concatenated 16S rRNA sequence analysis improves bacterial taxonomy
Document Type
Article
Publication Title
F1000Research
Abstract
Background: Microscopic, biochemical, molecular, and computer-based approaches are extensively used to identify and classify bacterial populations. Advances in DNA sequencing and bioinformatics workflows have facilitated sophisticated genome-based methods for microbial taxonomy although sequencing of the 16S rRNA gene is widely employed to identify and classify bacterial communities as a cost-effective and single-gene approach. However, the 16S rRNA sequence-based species identification accuracy is limited because of the occurrence of multiple copies of the 16S rRNA gene and higher sequence identity between closely related species. The availability of the genomes of several bacterial species provided an opportunity to develop comprehensive species-specific 16S rRNA reference libraries. Methods: Sequences of the 16S rRNA genes were retrieved from the whole genomes available in the Genome databases. With defined criteria, four 16S rRNA gene copy variants were concatenated to develop a species-specific reference library. The sequence similarity search was performed with a web-based BLAST program, and MEGA software was used to construct the phylogenetic tree. Results: Using this approach, species-specific 16S rRNA gene libraries were developed for four closely related Streptococcus species (S. gordonii, S. mitis, S. oralis, and S. pneumoniae). Sequence similarity and phylogenetic analysis using concatenated 16S rRNA copies yielded better resolution than single gene copy approaches. Conclusions: The approach is very effective in classifying genetically closely related bacterial species and may reduce misclassification of bacterial species and genome assemblies.
DOI
10.12688/f1000research.128320.3
Publication Date
1-1-2023
Recommended Citation
Paul, Bobby, "Concatenated 16S rRNA sequence analysis improves bacterial taxonomy" (2023). Open Access archive. 9157.
https://impressions.manipal.edu/open-access-archive/9157