Guanine riboswitch variants from Mesoplasma florum selectively recognize 2′-deoxyguanosine

Abstract

Several mRNA aptamers have been identified in Mesoplasma florum that have sequence and structural features resembling those of guanine and adenine riboswitches. Two features distinguish these RNAs from established purine-sensing riboswitches. All possess shortened hairpin-loop sequences expected to alter tertiary contacts known to be critical for aptamer folding. The RNAs also carry nucleotide changes in the core of each aptamer that otherwise is strictly conserved in guanine and adenine riboswitches. Some aptamers retain the ability to selectively bind guanine or adenine despite these mutations. However, one variant type exhibits selective and highaffinity binding of 2-deoxyguanosine, which is consistent with its occurrence in the 5 untranslated region of an operon containing ribonucleotide reductase genes. The identification of riboswitch variants that bind nucleosides and reject nucleobases reveals that natural metabolite-sensing RNA motifs can accrue mutations that expand the diversity of ligand detection in bacteria.allosteric RNA ͉ aptamer ͉ metabolite ͉ ribonucleotide reductase ͉ transcription termination G ene-control elements called riboswitches (1) are mRNA motifs typically found in the 5Ј untranslated regions of bacterial mRNAs. Riboswitches selectively bind small molecules, and structural changes within the 5Ј untranslated regions are usually harnessed to control the expression of the adjoining ORF. The architectures of these RNAs are commonly formed from a metabolite-binding aptamer domain and an expression platform (2-5), although more diverse assemblies of aptamers and expression platforms have been found that yield more complex gene-control characteristics (6 -9).Each aptamer adopts a complex secondary-and tertiarystructured fold to form a conserved receptor for the ligand (10-17). This demand for precise structure formation and specific molecular recognition causes the aptamer domains to be highly conserved even among distantly related species. In contrast, the expression platform can adopt a variety of different structures provided it maintains its responsiveness to the occupation state of the aptamer domain.Computer-aided searches based on conserved RNA sequences and structures have been used to identify representatives of numerous riboswitch classes (18-24). However, these bioinformatics algorithms can fail to identify variants of known riboswitch classes that differ substantially from the established aptamer consensus. Furthermore, there could be exceedingly rare classes of riboswitch aptamers or exceptionally small aptamers that will be missed by existing bioinformatics algorithms because there are too few representatives for comparison or they have too few conserved features. Given these limitations, many new riboswitch classes might remain undiscovered, and the true number of metabolite-sensing aptamer folds could greatly exceed the many types published to date (25).Indications that there are many variant, small, or rare riboswitch classes to be discovered come from several recent reports...

Structural basis for diversity in the SAM clan of riboswitches

“…One of the best-characterized examples is the purine family of riboswitches, which bind three distinct effector molecules: guanine, adenine, and 2′-deoxyguanosine (3). These RNAs are highly similar at all structural levels, with only two nucleotides in the binding pocket required to alter binding selectivity, indicating that these three distinct subfamilies likely diverged from a common ancestor (4,5). Conversely, the two known families of riboswitches that bind cyclic diguanylate or pre-Q 1 are structurally distinct and recognize the effector in different fashions, pointing to independent evolutionary origins (3).…”

Riboswitch diversity and distribution

“…As noted above, these searches can uncover the existence of variants of a known riboswitch class by identifying RNAs that closely correspond to the consensus sequence and secondary structure model of the predominant class (e.g., Kim et al 2007;McCown et al 2014). Moreover, bioinformatics algorithms can be used to find numerous new candidate riboswitches (e.g., Barrick et al 2004;Weinberg et al 2007Weinberg et al , 2010) that must be subsequently validated by genetic, biochemical, and biophysical studies.…”

An expanded collection and refined consensus model of glmS ribozymes

“…In this work, we sought to identify all glmS ribozyme representatives encoded in existing bacterial DNA sequence databases, including any distant variants that would reveal natural changes to the catalytic core or to structural support architectures. We utilized a bioinformatics search strategy that has previously yielded different types of riboswitch or ribozyme structural variants (Barrick et al 2005;Kim et al 2007;Weinberg et al 2008;Weinberg and Breaker 2011;Perreault et al 2011). We also used a different search strategy that has previously uncovered several new noncoding RNAs (ncRNAs) as well as a new class of S-adenosylmethionine-binding riboswitches Poiata et al 2009).…”