Integrative 16S rRNA Gene Sequencing Characterization of Four Bacterial Isolates: Phylogenetic Placement, Comparative ATGC Content Analysis and BLAST–EzBioCloud–VSEARCH Bioinformatics Pipeline
Description
For decades, the 16S rRNA gene has been a cornerstone of bacterial taxonomy and community analysis. Modern long-read sequencing is accurate enough to detect subtle single-nucleotide differences among multiple 16S gene copies within the same genome (though small insertion/deletion variants remain challenging to resolve). These findings highlight that microbiome analyses must account for intragenomic 16S variation. By leveraging full-length 16S intragenomic sequence variants, it is possible to resolve bacterial community composition at the species and even strain level. In this study, the nearly full-length 16S rRNA gene sequences (~1.2-1.5 kb) of four bacterial isolates (ASW5, SED11, A13, and S14) were analyzed to determine their taxonomic identities and evolutionary relationships. BLAST analysis via the EzBioCloud database identified isolates SED11, A13, and S14 as members of the genus Bacillus, with 16S sequence similarities of 99.54%, 100%, 100%, and 99.8% to the type strains of Bacillus thuringiensis, Bacillus paranthracis, Bacillus halotolerans, and Bacillus velezensis, respectively. These high identity values indicate that each isolate’s 16S sequence is nearly identical to a known species sequence, facilitating confident species-level assignment (typically, ≥98.7% 16S similarity is considered indicative of the same species). Quality filtering and chimera checking using VSEARCH v2.21.1 (with the GOLD/UCHIME database) revealed no chimeric sequences (0% chimera detected) in any of the four 16S rRNA genes, confirming that each sequence was suitable for downstream analysis. Nucleotide composition analysis showed that the sequences ranged from 1,235 to 1,500 bp in length and had very similar base frequency profiles. Each 16S rRNA Gene comprised approximately 20–21% Adenine (A), 24-26% Thymine (T), 22-24% Guanine (G), and 30-32% Cytosine (C). Accordingly, all four isolates exhibited a relatively high GC content in the ~53-55% range. Notably, Isolate ASW5 had a 16S GC content (~53%) comparable to those of the Bacillus isolates (~53-55%), indicating only minor variation in 16S GC content despite the organisms’ distinct genera. In silico secondary structure prediction of each 16S rRNA (using the RNAfold tool) yielded the typical bacterial 16S rRNA stem-loop structure for all isolates. Phylogenetic analysis was performed using MEGA X to construct 16S rRNA gene trees. The resulting neighbor-joining phylogeny clustered the three Bacillus isolates (ASW5, SED11, A13, S14) together within the Bacillus clade. This clustering aligns with the taxonomic identifications and the high 16S sequence similarities to the respective type strains. In summary, all four isolates were unambiguously identified by full-length 16S rRNA sequencing. They showed high GC contents and conserved 16S secondary structures, and each isolate grouped phylogenetically with the expected genus-underscoring the consistency between their molecular composition and phylogenetic affiliations.
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Steps to reproduce
To reproduce the taxonomic and phylogenetic data for the bacterial isolates ASW5, SED11, A13, and S14, follow this standardized bioinformatics and analytical pipeline: 1. Acquisition and Preparation of 16S rRNA Gene Sequences Obtain nearly full-length 16S rRNA gene sequences (approximately 1.2–1.5 kb) derived from high-throughput long-read sequencing platforms like PacBio or Oxford Nanopore. Ensure these sequences represent the isolates' genetic material, accounting for potential intragenomic variation among multiple gene copies. 2. Quality Control and Chimera Screening Verify the integrity of the sequences using the VSEARCH v2.21.1 tool. Run a chimera detection analysis against a high-quality reference database, such as the GOLD (UCHIME DB). A sequence is considered suitable for downstream analysis only if it is confirmed to be 100% non-chimeric (0% chimeras detected). 3. Taxonomic Identification via BLAST Analysis Submit the processed 16S rRNA gene sequences to the EzBioCloud database for BLAST analysis. Compare the query sequences against established type strains to determine the closest biological neighbor. Follow the standard taxonomic threshold where a similarity value of ≥98.7% is indicative of a same-species assignment. Record the specific percentage similarities—such as 99.54% for Bacillus thuringiensis (ASW5) and 100% for Bacillus paranthracis (SED11). 4. Nucleotide Composition (ATGC) and GC Content Analysis Perform a detailed base frequency analysis to determine the percentage of Adenine (A), Thymine (T), Guanine (G), and Cytosine (C) in each sequence. Typically, these isolates will exhibit an Adenine content of ~20–21% and a Cytosine content of ~30–32%. Calculate the GC content, which should fall within a relatively high range of ~53–55% for these Bacillus species. 5. In Silico Secondary Structure Prediction Predict the folding and stability of the 16S rRNA sequences using the RNAfold tool. This step should yield a typical bacterial stem-loop structure. Use color-gradient modeling (blue to red) to visualize base-pairing probability, where blue indicates highly stable regions and red indicates less stable or unpaired regions. 6. Phylogenetic Tree Construction Utilize the MEGA X software to construct phylogenetic trees. Apply the Neighbor-Joining method to align the isolates with their closest relatives and outgroups. Ensure the robustness of the tree branches by calculating bootstrap values and displaying them at the nodes. Verify that the isolates (ASW5, SED11, A13, and S14) cluster correctly within the expected Bacillus clade according to their molecular and taxonomic affiliations.
Institutions
- The Charutar Vidya Mandal (CVM) UniversityGujarat, Vallabh Vidyanagar