Modeling RNA tertiary structure motifs by graph-grammars

A new approach, graph-grammars, to encode RNA tertiary structure patterns is introduced and exemplified with the classical sarcin-ricin motif. The sarcin-ricin motif is found in the stem of the crucial ribosomal loop E (also referred to as the sarcin-ricin loop), which is sensitive to the alpha-sarcin and ricin toxins. Here, we generate a graph-grammar for the sarcin-ricin motif and apply it to derive putative sequences that would fold in this motif. The biological relevance of the derived sequences is confirmed by a comparison with those found in known sarcin-ricin sites in an alignment of over 800 bacterial 23S ribosomal RNAs. The comparison raised alternative alignments in few sarcin-ricin sites, which were assessed using tertiary structure predictions and 3D modeling. The sarcin-ricin motif graph-grammar was built with indivisible nucleotide interaction cycles that were recently observed in structured RNAs. A comparison of the sequences and 3D structures of each cycle that constitute the sarcin-ricin motif gave us additional insights about RNA sequence-structure relationships. In particular, this analysis revealed the sequence space of an RNA motif depends on a structural context that goes beyond the single base pairing and base-stacking interactions.     

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomic-resolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, “Find RNA 3D” (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and base-stacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose geometric discrepancy with respect to the query motif falls below a user-specified cutoff discrepancy. This technique can be applied to RMSD searches. Candidate motifs identified geometrically may be further screened symbolically to identify those that contain particular basepair types or base-stacking arrangements or that conform to sequence continuity or nucleotide identity constraints. Purely symbolic searches for motifs containing user-defined sequence, continuity and interaction constraints have also been implemented. We demonstrate that FR3D finds all occurrences, both local and composite and with nucleotide substitutions, of sarcin/ricin and kink-turn motifs in the 23S and 5S ribosomal RNA 3D structures of the H. marismortui 50S ribosomal subunit and assigns the lowest discrepancy scores to bona fide examples of these motifs. The search algorithms have been optimized for speed to allow users to search the non-redundant RNA 3D structure database on a personal computer in a matter of minutes.     

The lonepair triloop: a new motif in RNA structure

The lonepair triloop (LPTL) is an RNA structural motif that contains a single ("lone") base-pair capped by a hairpin loop containing three nucleotides. The two nucleotides immediately outside of this motif (5' and 3' to the lonepair) are not base-paired to one another, restricting the length of this helix to a single base-pair. Four examples of this motif, along with three tentative examples, were initially identified in the 16S and 23S rRNAs with covariation analysis. An evaluation of the recently determined crystal structures of the Thermus thermophilus 30S and Haloarcula marismortui 50S ribosomal subunits revealed the authenticity for all of these proposed interactions and identified 16 more LPTLs in the 5S, 16S and 23S rRNAs. This motif is found in the T loop in the tRNA crystal structures. The lonepairs are positioned, in nearly all examples, immediately 3' to a regular secondary structure helix and are stabilized by coaxial stacking onto this flanking helix. In all but two cases, the nucleotides in the triloop are involved in a tertiary interaction with another section of the rRNA, establishing an overall three-dimensional function for this motif. Of these 24 examples, 14 occur in multi-stem loops, seven in hairpin loops and three in internal loops. While the most common lonepair, U:A, occurs in ten of the 24 LPTLs, the remaining 14 LPTLs contain seven different base-pair types. Only a few of these lonepairs adopt the standard Watson-Crick base-pair conformations, while the majority of the base-pairs have non-standard conformations. While the general three-dimensional conformation is similar for all examples of this motif, characteristic differences lead to several subtypes present in different structural environments. At least one triloop nucleotide in 22 of the 24 LPTLs in the rRNAs and tRNAs forms a tertiary interaction with another part of the RNA. When a LPTL containing the GNR or UYR triloop sequence forms a tertiary interaction with the first (and second) triloop nucleotide, it recruits a fourth nucleotide to mediate stacking and mimic the tetraloop conformation. Approximately half of the LPTL motifs are in close association with proteins. The majority of these LPTLs are positioned at sites in rRNAs that are conserved in the three phylogenetic domains; a few of these occur in regions of the rRNA associated with ribosomal function, including the presumed site of peptidyl transferase activity in the 23S rRNA.     

Model-Free RNA Sequence and Structure Alignment Informed by SHAPE Probing Reveals a Conserved Alternate Secondary Structure for 16S rRNA

Discovery and characterization of functional RNA structures remains challenging due to deficiencies in de novo secondary structure modeling. Here we describe a dynamic programming approach for model-free sequence comparison that incorporates high-throughput chemical probing data. Based on SHAPE probing data alone, ribosomal RNAs (rRNAs) from three diverse organisms – the eubacteria E. coli and C. difficile and the archeon H. volcanii – could be aligned with accuracies comparable to alignments based on actual sequence identity. When both base sequence identity and chemical probing reactivities were considered together, accuracies improved further. Derived sequence alignments and chemical probing data from protein-free RNAs were then used as pseudo-free energy constraints to model consensus secondary structures for the 16S and 23S rRNAs. There are critical differences between these experimentally-informed models and currently accepted models, including in the functionally important neck and decoding regions of the 16S rRNA. We infer that the 16S rRNA has evolved to undergo large-scale changes in base pairing as part of ribosome function. As high-quality RNA probing data become widely available, structurally-informed sequence alignment will become broadly useful for de novo motif and function discovery.     

The adenosine wedge: A new structural motif in ribosomal RNA

Here, we present a new recurrent RNA arrangement, the so-called adenosine wedge (A-wedge), which is found in three places of the ribosomal RNA in both ribosomal subunits. The arrangement has a hierarchical structure, consisting of elements previously described as recurrent motifs, namely, the along-groove packing motif, the A-minor and the hook-turn. Within the A-wedge, these elements are involved in different types of cause–effect relationships, providing together for the particular tertiary structure of the motif.     

Degenerate RNA packaging signals in the genome of Satellite Tobacco Necrosis Virus: implications for the assembly of a T=1 capsid

Using a recombinant, T = 1 Satellite Tobacco Necrosis Virus (STNV)-like particle expressed in Escherichia coli, we have established conditions for in vitro disassembly and reassembly of the viral capsid. In vivo assembly is dependent on the presence of the coat protein (CP) N-terminal region, and in vitro assembly requires RNA. Using immobilised CP monomers under reassembly conditions with “free” CP subunits, we have prepared a range of partially assembled CP species for RNA aptamer selection. SELEX directed against the RNA-binding face of the STNV CP resulted in the isolation of several clones, one of which (B3) matches the STNV-1 genome in 16 out of 25 nucleotide positions, including across a statistically significant 10/10 stretch. This 10-base region folds into a stem-loop displaying the motif ACAA and has been shown to bind to STNV CP. Analysis of the other aptamer sequences reveals that the majority can be folded into stem-loops displaying versions of this motif. Using a sequence and secondary structure search motif to analyse the genomic sequence of STNV-1, we identified 30 stem-loops displaying the sequence motif AxxA. The implication is that there are many stem-loops in the genome carrying essential recognition features for binding STNV CP. Secondary structure predictions of the genomic RNA using Mfold showed that only 8 out of 30 of these stem-loops would be formed in the lowest-energy structure. These results are consistent with an assembly mechanism based on kinetically driven folding of the RNA.     

An in vitro-selected RNA receptor for the GAAC loop: modular receptor for non–GNRA-type tetraloop

Although artificial RNA motifs that can functionally replace the GNRA/receptor interaction, a class of RNA–RNA interacting motifs, were isolated from RNA libraries and used to generate designer RNA structures, receptors for non-GNRA tetraloops have not been found in nature or selected from RNA libraries. In this study, we report successful isolation of a receptor motif interacting with GAAC, a non-GNRA tetraloop, from randomized sequences embedded in a catalytic RNA. Biochemical characterization of the GAAC/receptor interacting motif within three structural contexts showed its binding affinity, selectivity and structural autonomy. The motif has binding affinity comparable with that of a GNRA/receptor, selectivity orthogonal to GNRA/receptors and structural autonomy even in a large RNA context. These features would be advantageous for usage of the motif as a building block for designer RNAs. The isolated motif can also be used as a query sequence to search for unidentified naturally occurring GANC receptor motifs.     

Experimental investigation of an RNA sequence space

Modern rRNAs are the historic consequence of an ongoing evolutionary exploration of a sequence space. These extant sequences belong to a special subset of the sequence space that is comprised only of those primary sequences that can validly perform the biological function(s) required of the particular RNA. If it were possible to readily identify all such valid sequences, stochastic predictions could be made about the relative likelihood of various evolutionary pathways available to an RNA. Herein an experimental system which can assess whether a particular sequence is likely to have validity as a eubacterial 5S rRNA is described. A total of ten naturally occurring, and hence known to be valid, sequences and two point mutants of unknown validity were used to test the usefulness of the approach. Nine of the ten valid sequences tested positive whereas both mutants tested as clearly defective. The tenth valid sequence gave results that would be interpreted as reflecting a borderline status were the answer not known. These results demonstrate that it is possible to experimentally determine which sequences in local regions of the sequence space are potentially valid 5S rRNAs. This approach will allow direct study of the constraints governing RNA evolution and allow inquiry into how the last common ancestor of extant life apparently came to have very complex ribosomal RNAs that subsequently were very conserved.     

S6:S18 ribosomal protein complex interacts with a structural motif present in its own mRNA

Prokaryotic ribosomal protein genes are typically grouped within highly conserved operons. In many cases, one or more of the encoded proteins not only bind to a specific site in the ribosomal RNA, but also to a motif localized within their own mRNA, and thereby regulate expression of the operon. In this study, we computationally predicted an RNA motif present in many bacterial phyla within the 5′ untranslated region of operons encoding ribosomal proteins S6 and S18. We demonstrated that the S6:S18 complex binds to this motif, which we hereafter refer to as the S6:S18 complex-binding motif (S6S18CBM). This motif is a conserved CCG sequence presented in a bulge flanked by a stem and a hairpin structure. A similar structure containing a CCG trinucleotide forms the S6:S18 complex binding site in 16S ribosomal RNA. We have constructed a 3D structural model of a S6:S18 complex with S6S18CBM, which suggests that the CCG trinucleotide in a specific structural context may be specifically recognized by the S18 protein. This prediction was supported by site-directed mutagenesis of both RNA and protein components. These results provide a molecular basis for understanding protein-RNA recognition and suggest that the S6S18CBM is involved in an auto-regulatory mechanism.     

A computational pipeline for high- throughput discovery of cis-regulatory noncoding RNA in prokaryotes

Noncoding RNAs (ncRNAs) are important functional RNAs that do not code for proteins. We present a highly efficient computational pipeline for discovering cis-regulatory ncRNA motifs de novo. The pipeline differs from previous methods in that it is structure-oriented, does not require a multiple-sequence alignment as input, and is capable of detecting RNA motifs with low sequence conservation. We also integrate RNA motif prediction with RNA homolog search, which improves the quality of the RNA motifs significantly. Here, we report the results of applying this pipeline to Firmicute bacteria. Our top-ranking motifs include most known Firmicute elements found in the RNA family database (Rfam). Comparing our motif models with Rfam's hand-curated motif models, we achieve high accuracy in both membership prediction and base-pair–level secondary structure prediction (at least 75% average sensitivity and specificity on both tasks). Of the ncRNA candidates not in Rfam, we find compelling evidence that some of them are functional, and analyze several potential ribosomal protein leaders in depth.     

RNAMotif, an RNA secondary structure definition and search algorithm

RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures are assembled from a collection of RNA structural motifs. These basic building blocks are used repeatedly, and in various combinations, to form different RNA types and define their unique structural and functional properties. Identification of recurring RNA structural motifs will therefore enhance our understanding of RNA structure and help associate elements of RNA structure with functional and regulatory elements. Our goal was to develop a computer program that can describe an RNA structural element of any complexity and then search any nucleotide sequence database, including the complete prokaryotic and eukaryotic genomes, for these structural elements. Here we describe in detail a new computational motif search algorithm, RNAMotif, and demonstrate its utility with some motif search examples. RNAMotif differs from other motif search tools in two important aspects: first, the structure definition language is more flexible and can specify any type of base–base interaction; second, RNAMotif provides a user controlled scoring section that can be used to add capabilities that patterns alone cannot provide.     

Plasticity of the RNA kink turn structural motif

The kink turn (K-turn) is an RNA structural motif found in many biologically significant RNAs. While most examples of the K-turn have a similar fold, the crystal structure of the Azoarcus group I intron revealed a novel RNA conformation, a reverse kink turn bent in the direction opposite that of a consensus K-turn. The reverse K-turn is bent toward the major grooves rather than the minor grooves of the flanking helices, yet the sequence differs from the K-turn consensus by only a single nucleotide. Here we demonstrate that the reverse bend direction is not solely defined by internal sequence elements, but is instead affected by structural elements external to the K-turn. It bends toward the major groove under the direction of a tetraloop–tetraloop receptor. The ability of one sequence to form two distinct structures demonstrates the inherent plasticity of the K-turn sequence. Such plasticity suggests that the K-turn is not a primary element in RNA folding, but instead is shaped by other structural elements within the RNA or ribonucleoprotein assembly.     

Crystal structure of a luteoviral RNA pseudoknot and model for a minimal ribosomal frameshifting motif

To understand the role of structural elements of RNA pseudoknots in controlling the extent of -1-type ribosomal frameshifting, we determined the crystal structure of a high-efficiency frameshifting mutant of the pseudoknot from potato leaf roll virus (PLRV). Correlations of the structure with available in vitro frameshifting data for PLRV pseudoknot mutants implicate sequence and length of a stem-loop linker as modulators of frameshifting efficiency. Although the sequences and overall structures of the RNA pseudoknots from PLRV and beet western yellow virus (BWYV) are similar, nucleotide deletions in the linker and adjacent minor groove loop abolish frameshifting only with the latter. Conversely, mutant PLRV pseudoknots with up to four nucleotides deleted in this region exhibit nearly wild-type frameshifting efficiencies. The crystal structure helps rationalize the different tolerances for deletions in the PLRV and BWYV RNAs, and we have used it to build a three-dimensional model of the PRLV pseudoknot with a four-nucleotide deletion. The resulting structure defines a minimal RNA pseudoknot motif composed of 22 nucleotides capable of stimulating -1-type ribosomal frameshifts.     

Activation of RegB endoribonuclease by S1 ribosomal protein requires an 11 nt conserved sequence

The T4 RegB endoribonuclease cleaves specifically in the middle of the -GGAG- sequence, leading to inactivation and degradation of early phage mRNAs. In vitro, RegB activity is very weak but can be enhanced 10- to 100-fold by the Escherichia coli ribosomal protein S1. Not all RNAs carrying the GGAG motif are cleaved by RegB, suggesting that additional information is required to obtain a complete RegB target site. In this work, we find that in the presence of S1, the RegB target site is an 11 nt long single-stranded RNA carrying the 100% conserved GGA triplet at the 5′ end and a degenerate, A-rich, consensus sequence immediately downstream. Our data support the notion that RegB alone recognizes only the trinucleotide GGA, which it cleaves very inefficiently, and that stimulation of RegB activity by S1 depends on the nucleotide immediately 3′ to -GGA-.     

The nucleotide sequence of the chloroplast 5S ribosomal RNA from spinach.

Spinacia oleracia cholorplast 5S ribosomal RNA was end-labeled with [32P] and the complete nucleotide sequence was determined. The sequence is: pUAUUCUGGUGUCCUAGGCGUAGAGGAACCACACCAAUCCAUCCCGAACUUGGUGGUUAAACUCUACUGCGGUGACGAU ACUGUAGGGGAGGUCCUGCGGAAAAAUAGCUCGACGCCAGGAUGOH. This sequence can be fitted to the secondary structural model proposed for prokaryotic 5S ribosomal RNAs by Fox and Woese (1). However, the lengths of several single- and double-stranded regions differ from those common to prokaryotes. The spinach chloroplast 5S ribosomal RNA is homologous to the 5S ribosomal RNA of Lemna chloroplasts with the exception that the spinach RNA is longer by one nucleotide at the 3' end and has a purine base substitution at position 119. The sequence of spinach chloroplast 5S RNA is identical to the chloroplast 5S ribosomal RNA gene of tobacco. Thus the structures of the chloroplast 5S ribosomal RNAs from some of the higher plants appear to be almost totally conserved. This does not appear to be the case for the higher plant cytoplasmic 5S ribosomal RNAs.     

Core sequence in the RNA motif recognized by the ErmE methyltransferase revealed by relaxing the fidelity of the enzyme for its target.

Under physiological conditions, the ErmE methyltransferase specifically modifies a single adenosine within ribosomal RNA (rRNA), and thereby confers resistance to multiple antibiotics. The adenosine (A2058 in Escherichia coli 23S rRNA) lies within a highly conserved structure, and is methylated efficiently, and with equally high fidelity, in rRNAs from phylogenetically diverse bacteria. However, the fidelity of ErmE is reduced when magnesium is removed, and over twenty new sites of ErmE methylation appear in E. coli 16S and 23S rRNAs. These sites show widely different degrees of reactivity to ErmE. The canonical A2058 site is largely unaffected by magnesium depletion and remains the most reactive site in the rRNA. This suggests that methylation at the new sites results from changes in the RNA substrate rather than the methyltransferase. Chemical probing confirms that the rRNA structure opens upon magnesium depletion, exposing potential new interaction sites to the enzyme. The new ErmE sites show homology with the canonical A2058 site, and have the consensus sequence aNNNcgGAHAg (ErmE methylation occurs exclusively at adenosines (underlined); these are preceded by a guanosine, equivalent to G2057; there is a high preference for the adenosine equivalent to A2060; H is any nucleotide except G; N is any nucleotide; and there are slight preferences for the nucleotides shown in lower case). This consensus is believed to represent the core of the motif that Erm methyltransferases recognize at their canonical A2058 site. The data also reveal constraints on the higher order structure of the motif that affect methyltransferase recognition.