Reduced ribosome activity influences the non-uniform evolution of 16S rRNA hypervariable regions
bioRxiv, ISSN: 2692-8205
2022
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
16S rRNA gene sequences are commonly analyzed for taxonomic and phylogenetic studies because they contain hypervariable regions that can help distinguish different genera. However, intragenus distinction is often difficult due to high sequence identities among closely related species. Although common tools for 16S sequence taxonomic classification weight residue variations equally during comparisons, specific residues within hypervariable regions have not drifted evenly through evolution, suggesting that portions of them may be biologically important. We developed an in vivo test system where 16S variants coexisted among natural ribosome populations which allowed their fitness to be evaluated. We found that versions with evolutionarily disparate hypervariable regions were underpopulated in ribosomes and active translation pools, even for a single nucleotide polymorphism (SNP), which indicates functional constraints to the free evolutionary drift of hypervariable regions. Using an in silico method (positional relative entropy), we analyzed over 12,000 16S V3-V4 sequences across Escherichia and Shigella strains and identified species that can be distinguished by position-specific SNPs present in multiple 16S alleles in a genome. When we evaluated these informative SNPs with our in vivo system, we discovered that ribosomes harboring them were compromised, suggesting that their evolution is indeed biologically constrained. Overall, this study demonstrates that SNPs within hypervariable regions are not necessarily inconsequential and that common computational approaches for taxonomic 16S rRNA sequence classification should not assume an even probability of residues at each position.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know