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Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs.

ABSTRACT: The 16 S rRNA sequence has long been used uncritically as a molecular clock to infer phylogenetic relationships among prokaryotes without fully elucidating the evolutionary changes that this molecule undergoes. In this study, we investigated the functional evolvability of 16?S rRNA, using comparative RNA function analyses between the 16?S rRNAs of Escherichia coli (Proteobacteria) and Acidobacteria (78% identity, 334 nucleotide differences) in the common genetic background of E. coli. While the growth phenotype of an E. coli mutant harboring the acidobacterial gene was disrupted significantly, it was restored almost completely following introduction of a 16?S rRNA sequence with a single base-pair variation in helix 44; the remaining 332 nucleotides were thus functionally similar to those of E. coli. Our results suggest that 16?S rRNAs share an inflexible cradle structure formed by ribosomal proteins and have evolved by accumulating species-specific yet functionally similar mutations. While this experimental evidence suggests the neutral evolvability of 16?S rRNA genes and hence satisfies the necessary requirements to use the sequence as a molecular clock, it also implies the promiscuous nature of the 16?S rRNA gene, i.e., the occurrence of horizontal gene transfer among bacteria.

SUBMITTER: Tsukuda M

PROVIDER: S-EPMC5577257 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs.

Tsukuda Miyuki M Kitahara Kei K Miyazaki Kentaro K

Scientific reports 20170830 1

The 16 S rRNA sequence has long been used uncritically as a molecular clock to infer phylogenetic relationships among prokaryotes without fully elucidating the evolutionary changes that this molecule undergoes. In this study, we investigated the functional evolvability of 16 S rRNA, using comparative RNA function analyses between the 16 S rRNAs of Escherichia coli (Proteobacteria) and Acidobacteria (78% identity, 334 nucleotide differences) in the common genetic background of E. coli. While the ...[more]

PMID: 28855596

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Project description:BackgroundPredicting protein function from primary sequence is an important open problem in modern biology. Not only are there many thousands of proteins of unknown function, current approaches for predicting function must be improved upon. One problem in particular is overly-specific function predictions which we address here with a new statistical model of the relationship between protein sequence similarity and protein function similarity.MethodologyOur statistical model is based on sets of proteins with experimentally validated functions and numeric measures of function specificity and function similarity derived from the Gene Ontology. The model predicts the similarity of function between two proteins given their amino acid sequence similarity measured by statistics from the BLAST sequence alignment algorithm. A novel aspect of our model is that it predicts the degree of function similarity shared between two proteins over a continuous range of sequence similarity, facilitating prediction of function with an appropriate level of specificity.SignificanceOur model shows nearly exact function similarity for proteins with high sequence similarity (bit score >244.7, e-value >1e(-62), non-redundant NCBI protein database (NRDB)) and only small likelihood of specific function match for proteins with low sequence similarity (bit score <54.6, e-value <1e(-05), NRDB). For sequence similarity ranges in between our annotation model shows an increasing relationship between function similarity and sequence similarity, but with considerable variability. We applied the model to a large set of proteins of unknown function, and predicted functions for thousands of these proteins ranging from general to very specific. We also applied the model to a data set of proteins with previously assigned, specific functions that were electronically based. We show that, on average, these prior function predictions are more specific (quite possibly overly-specific) compared to predictions from our model that is based on proteins with experimentally determined function.

Dataset Information

Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs.

Publications

Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs.

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