RNomics in Archaea reveals a further link between splicing of archaeal introns and rRNA processing

The bulge–helix–bulge (BHB) motif recognised by the archaeal splicing endonuclease is also found in the long processing stems of archaeal rRNA precursors in which it is cleaved to generate pre-16S and pre-23S rRNAs. We show that in two species, Archaeoglobus fulgidus and Sulfolobus solfataricus, representatives from the two major archaeal kingdoms Euryarchaeota and Crenarchaeota, respectively, the pre-rRNA spacers cleaved at the BHB motifs surrounding pre-16S and pre-23S rRNAs subsequently become ligated. In addition, we present evidence that this is accompanied by circularisation of ribosomal pre-16S and pre-23S rRNAs in both species. These data reveal a further link between intron splicing and pre-rRNA processing in Archaea, which might reflect a common evolutionary origin of the two processes. One spliced RNA species designated 16S-D RNA, resulting from religation at the BHB motif of 16S pre-rRNA, is a highly abundant and stable RNA which folds into a three-stem structure interrupted by two single-stranded regions as assessed by chemical probing. It spans a region of the pre-rRNA 5′ external transcribed spacer exhibiting a highly conserved folding pattern in Archaea. Surprisingly, 16S-D RNA contains structural motifs found in archaeal C/D box small RNAs and binds to the L7Ae protein, a core component of archaeal C/D box RNPs. This supports the notion that it might have an important but still unknown role in pre-rRNA biogenesis or might even target RNA molecules other than rRNA.     

Composite structure of the chloroplast 23 S ribosomal RNA genes of Chlamydomonas reinhardii: Evolutionary and functional implications

The chloroplast ribosomal unit of Chlamydomonas reinhardii displays two features which are not shared by other chloroplast ribosomal units. These include the presence of an intron in the 23 S ribosomal RNA gene and of two small genes coding for 3 S and 7 S rRNA in the spacer between the 16 S and 23 S rRNA genes (Rochaix & Malnoë, 1978). Sequencing of the 7 S and 3 S rRNAs as well as their genes and neighbouring regions has shown that: (1) the 7 S and 3 S rRNA genes are 282 and 47 base-pairs long, respectively, and are separated by a 23 base-pair A + T-rich spacer. (2) A sequence microheterogeneity exists within the 3 S RNA genes. (3) The sequences of the 7 S and 3 S rRNAs are homologous to the 5′ termini of prokaryotic and other chloroplast 23 S rRNAs, indicating that the C. reinhardii counterparts of 23 S rRNA have a composite structure. (4) The sequences of the 7 S and 3 S rRNAs are related to that of cytoplasmic 5.8 S rRNA, suggesting that these RNAs may perform similar functions in the ribosome. (5) Partial nucleotide sequence complementarity is observed between the 5′ ends of the 7 S and 3 S RNAs on one hand and the 23 S rRNA sequences which flank the ribosomal intron on the other. These data are compatible with the idea that these small rRNAs may play a role in the processing of the 23 S rRNA precursor.     

Genetic and structural analysis of base substitutions in the central pseudoknot of Thermus thermophilus 16S ribosomal RNA

Characterization of base substitutions in rRNAs has provided important insights into the mechanism of protein synthesis. Knowledge of the structural effects of such alterations is limited, and could be greatly expanded with the development of a genetic system based on an organism amenable to both genetics and structural biology. Here, we describe the genetic analysis of base substitutions in 16S ribosomal RNA of the extreme thermophile Thermus thermophilus, and an analysis of the conformational effects of these substitutions by structure probing with base-specific modifying agents. Gene replacement methods were used to construct a derivative of strain HB8 carrying a single 16S rRNA gene, allowing the isolation of spontaneous streptomycin-resistant mutants and subsequent genetic mapping of mutations by recombination. The residues altered to give streptomycin resistance reside within the central pseudoknot structure of 16S rRNA comprised of helices 1 and 27, and participate in the U13–U20–A915 base triple, the G21–A914 type II sheared G–A base pair, or the G885–C912 Watson–Crick base pair closing helix 27. Substitutions at any of the three residues engaged in the base triple were found to confer resistance. Results from structure probing of the pseudoknot are consistent with perturbation of RNA conformation by these substitutions, potentially explaining their streptomycin-resistance phenotypes.     

Accurate and efficient reconstruction of deep phylogenies from structured RNAs

Ribosomal RNA (rRNA) genes are probably the most frequently used data source in phylogenetic reconstruction. Individual columns of rRNA alignments are not independent as a consequence of their highly conserved secondary structures. Unless explicitly taken into account, these correlation can distort the phylogenetic signal and/or lead to gross overestimates of tree stability. Maximum likelihood and Bayesian approaches are of course amenable to using RNA-specific substitution models that treat conserved base pairs appropriately, but require accurate secondary structure models as input. So far, however, no accurate and easy-to-use tool has been available for computing structure-aware alignments and consensus structures that can deal with the large rRNAs. The RNAsalsa approach is designed to fill this gap. Capitalizing on the improved accuracy of pairwise consensus structures and informed by a priori knowledge of group-specific structural constraints, the tool provides both alignments and consensus structures that are of sufficient accuracy for routine phylogenetic analysis based on RNA-specific substitution models. The power of the approach is demonstrated using two rRNA data sets: a mitochondrial rRNA set of 26 Mammalia, and a collection of 28S nuclear rRNAs representative of the five major echinoderm groups.     

Sampled ensemble neutrality as a feature to classify potential structured RNAs

Background

Structured RNAs have many biological functions ranging from catalysis of chemical reactions to gene regulation. Yet, many homologous structured RNAs display most of their conservation at the secondary or tertiary structure level. As a result, strategies for structured RNA discovery rely heavily on identification of sequences sharing a common stable secondary structure. However, correctly distinguishing structured RNAs from surrounding genomic sequence remains challenging, especially during de novo discovery. RNA also has a long history as a computational model for evolution due to the direct link between genotype (sequence) and phenotype (structure). From these studies it is clear that evolved RNA structures, like protein structures, can be considered robust to point mutations. In this context, an RNA sequence is considered robust if its neutrality (extent to which single mutant neighbors maintain the same secondary structure) is greater than that expected for an artificial sequence with the same minimum free energy structure.

Results

In this work, we bring concepts from evolutionary biology to bear on the structured RNA de novo discovery process. We hypothesize that alignments corresponding to structured RNAs should consist of neutral sequences. We evaluate several measures of neutrality for their ability to distinguish between alignments of structured RNA sequences drawn from Rfam and various decoy alignments. We also introduce a new measure of RNA structural neutrality, the structure ensemble neutrality (SEN). SEN seeks to increase the biological relevance of existing neutrality measures in two ways. First, it uses information from an alignment of homologous sequences to identify a conserved biologically relevant structure for comparison. Second, it only counts base-pairs of the original structure that are absent in the comparison structure and does not penalize the formation of additional base-pairs.

Conclusion

We find that several measures of neutrality are effective at separating structured RNAs from decoy sequences, including both shuffled alignments and flanking genomic sequence. Furthermore, as an independent feature classifier to identify structured RNAs, SEN yields comparable performance to current approaches that consider a variety of features including stability and sequence identity. Finally, SEN outperforms other measures of neutrality at detecting mutational robustness in bacterial regulatory RNA structures.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-014-1203-8) contains supplementary material, which is available to authorized users.     

Dynamics of Ribosomal RNA Structure

Abstract

The structural dynamics of ribosomal 5S RNAs have been investigated by probing single strandedness through enzymatic cleavage and chemical modification. This comparative study includes 5S rRNAs from E. coli, B. stearothermophilus, T. thermophilics, H. cutirubrum, spinach chloroplast, spinach cytomplasm, and Artemia salina. The structural studies support a unique tertiary interaction in eubacterial 5S rRNAs, involving nucleotides around positions 43 and 75. In addition long range structural effects are demonstrated in E. coli 5S rRNA due to the conversion of C to U at position 92.     

Ribosomal RNAs are tolerant toward genetic insertions: evolutionary origin of the expansion segments

Ribosomal RNAs (rRNAs), assisted by ribosomal proteins, form the basic structure of the ribosome, and play critical roles in protein synthesis. Compared to prokaryotic ribosomes, eukaryotic ribosomes contain elongated rRNAs with several expansion segments and larger numbers of ribosomal proteins. To investigate architectural evolution and functional capability of rRNAs, we employed a Tn5 transposon system to develop a systematic genetic insertion of an RNA segment 31 nt in length into Escherichia coli rRNAs. From the plasmid library harboring a single rRNA operon containing random insertions, we isolated surviving clones bearing rRNAs with functional insertions that enabled rescue of the E. coli strain (Δ7rrn) in which all chromosomal rRNA operons were depleted. We identified 51 sites with functional insertions, 16 sites in 16S rRNA and 35 sites in 23S rRNA, revealing the architecture of E. coli rRNAs to be substantially flexible. Most of the insertion sites show clear tendency to coincide with the regions of the expansion segments found in eukaryotic rRNAs, implying that eukaryotic rRNAs evolved from prokaryotic rRNAs suffering genetic insertions and selections.     

Simultaneous characterization of cellular RNA structure and function with in-cell SHAPE-Seq

Many non-coding RNAs form structures that interact with cellular machinery to control gene expression. A central goal of molecular and synthetic biology is to uncover design principles linking RNA structure to function to understand and engineer this relationship. Here we report a simple, high-throughput method called in-cell SHAPE-Seq that combines in-cell probing of RNA structure with a measurement of gene expression to simultaneously characterize RNA structure and function in bacterial cells. We use in-cell SHAPE-Seq to study the structure–function relationship of two RNA mechanisms that regulate translation in Escherichia coli. We find that nucleotides that participate in RNA–RNA interactions are highly accessible when their binding partner is absent and that changes in RNA structure due to RNA–RNA interactions can be quantitatively correlated to changes in gene expression. We also characterize the cellular structures of three endogenously expressed non-coding RNAs: 5S rRNA, RNase P and the btuB riboswitch. Finally, a comparison between in-cell and in vitro folded RNA structures revealed remarkable similarities for synthetic RNAs, but significant differences for RNAs that participate in complex cellular interactions. Thus, in-cell SHAPE-Seq represents an easily approachable tool for biologists and engineers to uncover relationships between sequence, structure and function of RNAs in the cell.     

Studies on compartmentation of uridine 5'-triphosphate during synthesis of cytoplasmic and plastid ribosomal RNA's in Euglena gracilis

• 1.1. Compartmentation of uridine 5'-triphosphate (UTP) was studied during synthesis of cytoplasmic ribosomal RNA (cyt-rRNA) and plastid ribosomal RNA (pl-rRNA) in photoorganotrophically grown cells of Euglena gracilis Z.
• 2.2. Using the approach of Wiegers et al. (1976) the steady state specific radioactivity of UTP was compared with that ofcyt-20S rRNA, cyt-25S rRNA, pl-16S rRNA and pl-23S rRNA under low and at 100-fold higher specific radioactivity of exogenously fed pHl-uracil.
• 3.3. The equal steady state specific radioactivities of all rRNAs at both feeding conditions argue against compartmentation of UTP during their synthesis.
• 4.4. At high specific radioactivity of exogenous [³H]-uracil the salvage-derived labelled UMP was shown to be diluted 15,000-fold by unlabelled UMP formed de novo, whereas this dilution factor was 100-fold lower at low specific radioactivity of [³H]-uracil indicating inhibition of the de novo synthesis of UMP.
• 5.5. Transport is suggested of uridine nucleotides into chloroplasts by the 15-fold higher specific radioactivity of intracellular [³H]-uracil than that of UTP as well as UMP residues in pl-rRNA.

     

Structure and topology of 16S ribosomal RNA. An analysis of the pattern of psoralen crosslinking.

All of the eleven psoralen crosslinking features previously mapped by electron microscopy of the 16S rRNA can be matched by energetically stable duplex regions found by a computer search of the sequence. One additional particularly stable duplex found in the sequence has subsequently been seen in the microscope. There is no indication that a best or unique fit of the sequence to the crosslinking data has been found. However, it is encouraging that all twelve assignments involve non-overlapping regions of the sequence which allows their simultaneous construction. The resulting general pattern of secondary structure is very different from previous suggestions for rRNAs or other complex RNAs. It is an RNA chain folded in space much like a typical protein chain. Because of the interwound nature of double helices, base pairing between distant regions of the sequence might result in topologically knotted structures. However, examination of available electron microscopic data suggests that the 16S rRNA does not contain any knots.     

Modular RNA architecture revealed by computational analysis of existing pseudoknots and ribosomal RNAs

Modular architecture is a hallmark of RNA structures, implying structural, and possibly functional, similarity among existing RNAs. To systematically delineate the existence of smaller topologies within larger structures, we develop and apply an efficient RNA secondary structure comparison algorithm using a newly developed two-dimensional RNA graphical representation. Our survey of similarity among 14 pseudoknots and subtopologies within ribosomal RNAs (rRNAs) uncovers eight pairs of structurally related pseudoknots with non-random sequence matches and reveals modular units in rRNAs. Significantly, three structurally related pseudoknot pairs have functional similarities not previously known: one pair involves the 3′ end of brome mosaic virus genomic RNA (PKB134) and the alternative hammerhead ribozyme pseudoknot (PKB173), both of which are replicase templates for viral RNA replication; the second pair involves structural elements for translation initiation and ribosome recruitment found in the viral internal ribosome entry site (PKB223) and the V4 domain of 18S rRNA (PKB205); the third pair involves 18S rRNA (PKB205) and viral tRNA-like pseudoknot (PKB134), which probably recruits ribosomes via structural mimicry and base complementarity. Additionally, we quantify the modularity of 16S and 23S rRNAs by showing that RNA motifs can be constructed from at least 210 building blocks. Interestingly, we find that the 5S rRNA and two tree modules within 16S and 23S rRNAs have similar topologies and tertiary shapes. These modules can be applied to design novel RNA motifs via build-up-like procedures for constructing sequences and folds.     

Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

Background

A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1.

Results

The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases.

Conclusion

Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.     

RoboOligo: software for mass spectrometry data to support manual and de novo sequencing of post-transcriptionally modified ribonucleic acids

Ribosomal ribonucleic acid (RNA), transfer RNA and other biological or synthetic RNA polymers can contain nucleotides that have been modified by the addition of chemical groups. Traditional Sanger sequencing methods cannot establish the chemical nature and sequence of these modified-nucleotide containing oligomers. Mass spectrometry (MS) has become the conventional approach for determining the nucleotide composition, modification status and sequence of modified RNAs. Modified RNAs are analyzed by MS using collision-induced dissociation tandem mass spectrometry (CID MS/MS), which produces a complex dataset of oligomeric fragments that must be interpreted to identify and place modified nucleosides within the RNA sequence. Here we report the development of RoboOligo, an interactive software program for the robust analysis of data generated by CID MS/MS of RNA oligomers. There are three main functions of RoboOligo: (i) automated de novo sequencing via the local search paradigm. (ii) Manual sequencing with real-time spectrum labeling and cumulative intensity scoring. (iii) A hybrid approach, coined ‘variable sequencing’, which combines the user intuition of manual sequencing with the high-throughput sampling of automated de novo sequencing.     

Isolation and characterization of the RNA of membrane-bound ribosomes in Dictyostelium discoideum

The RNA of membrane-bound ribosomes, isolated from Dictyostelium discoideum, represented 13 to 16% of the total ribosomal RNA (rRNA) present throughout growth and development. Membrane-bound ribosomes were released by treatment with sodium deoxycholate and Brij 58. There were no obvious differences in size and base composition between RNAs derived from membrane-bound or free ribosomes. The 17S membrane-bound rRNA and free rRNAs appeared to have similar methyl contents. However, the 25S membrane-bound rRNA contained about 16 to 20% fewer methyl groups than the 17S membrane-bound rRNA and free rRNAs. Free rRNAs turned over rapidly during early development but not during the disaggregation and reaggregation processes. Membrane-bound rRNAs showed very little turnover during the early stages of morphogenesis, but showed rapid turnover during the late stages of development; this class of rRNAs did not turn over during early stages of reaggregation but turned over rapidly during later stages of reaggregation.     

Nucleotide sequence of 5S ribosomal RNA from rainbow trout (Salmo gairdnerii) liver.

Staring from low molecular weight RNA obtained from rainbow trout (Salmo gairdnerii) liver, 5S ribosomal RNA (rRNA) was highly purified by successive chromatography on columns of DEAE-Sephadex A50 and Sephadex G100. Products of complete and partial digestions on this RNA with pancreatic ribonuclease (RNase A) [EC 3.1.4.22] and RNase T [EC 3.1.4.8] were isolated and sequenced by conventional and high-performance liquid chromatography (HPLC) procedures. The nucleotide sequence of this RNA thus established was compared with those of five other vertebrae 5S rRNAs, and the rates of base substitution per site per year were found to be nearly constant in these RNAs. The analyses of the partial digests of the trout 5S rRNA revealed several sites susceptible to RNase attack, which could be accounted for by the secondary structure model for eukaryotic 5S rRNAs proposed by Nishikawa and Takemura (1).     

Specific contacts between protein S4 and ribosomal RNA are required at multiple stages of ribosome assembly

Assembly of bacterial 30S ribosomal subunits requires structural rearrangements to both its 16S rRNA and ribosomal protein components. Ribosomal protein S4 nucleates 30S assembly and associates rapidly with the 5′ domain of the 16S rRNA. In vitro, transformation of initial S4–rRNA complexes to long-lived, mature complexes involves refolding of 16S helix 18, which forms part of the decoding center. Here we use targeted mutagenesis of Geobacillus stearothermophilus S4 to show that remodeling of S4–rRNA complexes is perturbed by ram alleles associated with reduced translational accuracy. Gel mobility shift assays, SHAPE chemical probing, and in vivo complementation show that the S4 N-terminal extension is required for RNA binding and viability. Alanine substitutions in Y47 and L51 that interact with 16S helix 18 decrease S4 affinity and destabilize the helix 18 pseudoknot. These changes to the protein–RNA interface correlate with no growth (L51A) or cold-sensitive growth, 30S assembly defects, and accumulation of 17S pre-rRNA (Y47A). A third mutation, R200A, over-stabilizes the helix 18 pseudoknot yet results in temperature-sensitive growth, indicating that complex stability is finely tuned by natural selection. Our results show that early S4–RNA interactions guide rRNA folding and impact late steps of 30S assembly.