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Finding aptamers and small ribozymes in unexpected places

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Abstract The discovery of the catalytic properties of RNAs was a milestone for our view of how life emerged and forced us to reformulate many of our dogmas. The urge to grasp the whole spectrum of potential activities of RNA molecules stimulated two decades of fervent research resulting in a deep understanding of RNA‐based phenomena. Most ribozymes were discovered by serendipity during the analysis of chemical processes, whereas RNA aptamers were identified through meticulous design and selection even before their discovery in nature. The desire to obtain aptamers led to the development of sophisticated technology and the design of efficient strategies. With the new notion that transcriptomes cover a major part of genomes and determine the identity of cells, it is reasonable to speculate that many more aptamers and ribozymes are awaiting their discovery in unexpected places. Now, in the genomic era with the development of powerful bioinformatics and sequencing methods, we are overwhelmed with tools for studying the genomes of all living and possibly even extinct organisms. Genomic SELEX (systematic evolution of ligands by exponential enrichment) coupled with deep sequencing and sophisticated computational analysis not only gives access to unexplored parts of sequenced genomes but also allows screening metagenomes in an unbiased manner. WIREs RNA 2012, 3:73–91. doi: 10.1002/wrna.105 This article is categorized under: RNA-Based Catalysis > Miscellaneous RNA-Catalyzed Reactions Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs Regulatory RNAs/RNAi/Riboswitches > Riboswitches

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Varieties of systematic evolution of ligands by exponential enrichment (SELEX). At its core, SELEX denotes a cyclical evolutionary screen for sequences conferring a specific activity, typically binding, as is in the case for aptamers. Choice of initial library depends on the application. When searching for artificial aptamers, a short, random section of nucleotides are flanked by fixed sequences. Genomic SELEX enables the screening of genomes for aptamers, and has the added benefit of reducing the complexity of the library. Several different methods can be used for partitioning, and it is informative to use multiple methods and perform technical duplicates in parallel. SELEX for RNAs usually requires rounds of transcription and amplification for pool maintenance. However, capillary electrophoresis SELEX bypasses these extra steps. High‐throughput sequencing and bioinformatic analysis follow once sufficient enrichment is detected.

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Selection of Diels‐Alder ribozymes by in vitro compartmentalization. A randomized dsDNA library of genes encoding potential ribozymes was fused to anthracene through a polyethylene glycol (PEG) linker. The genes were compartmentalized within droplets of a water‐in‐oil emulsion so that there was less than one molecule per compartment. The genes were transcribed and then Mg2+ and biotin‐maleimide were added so that they diffused into the compartments. The active ribozymes carried out the Diels‐Alder reaction, which fused the biotin to the gene of interest. The active genes are isolated by binding to streptavidin beads and amplified for further rounds of selection.129

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RNABOB search for hammerhead ribozymes. RNABOB (Eddy, Janelia Farms, unpublished) has been used to scan genomes for complicated, flexible structures which otherwise could not be predicted with alignment algorithms, thermodynamical algorithms such as the Zucker algorithm (ViennaRNA, mfold) or covariance models. Instead of inputting a sequence and finding a homolog with a similar structure, the user inputs a specific pattern with a flexible framework for insertions. Panel (a) shows the descriptors used to search hammerhead ribozymes in the human microbiome.106 The elements are depicted in the canonical hammerhead structure cartoon in (b). ‘s’s are single‐stranded elements and they are identified by a sequence constraint on the right. ‘N’s mean any character, and ambiguity codes are allowed as well (e.g., ‘H’ indicates an ‘A’, ‘C’, or ‘T’). Numbers in brackets (e.g., ‘[46]’) indicate an insertion of up to that many characters with no constraint on the content of the sequence. Therefore, s3 and s5 may be 4–50 nucleotides long; ‘r’s are relational elements, which is a generalized form of a hairpin. It allows the user to specify the required base pairing in the fourth field in the parts of the pattern in the third field (‘***NNN:NNN***’) where only ‘N’s are specified. Here ‘TGCA’ indicates that T may pair with A and G with C, i.e., all pairs are allowed but GU. (To allow them ‘TGYR’ would be input instead.) The ‘*’s indicate an optional character, so in the case shown, all ‘r’ elements are allowed to be 3–6 pairs long. To specify the topology, the features are input in order. In this case, it would be ‘s1 r1 s2 r2 s3 r2′ s4 r3 s5 r3′ s6 r1′ s7’.

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Genomic systematic evolution of ligands by exponential enrichment (SELEX) for ribozymes. Human genomic DNA was partially digested and size selected to 150 base pairs and ligated to double‐stranded hairpin primers. The loops were digested and then amplified by performing PCR to add the T7 promoter. A biotinylated primer was used to amplify and then used to extract one strand of single‐stranded DNA (ssDNA). The ssDNA was ligated and then incubated with primers, Taq Pol, and dNTPs to produce nicked, circular, double‐stranded DNA (dsDNA). Rolling circle transcription produced long transcripts with many potential cleavage sites (red arrows). Mg2+ induced cleavage produced singular, dimer, and multimer units. The dimers were isolated because they contain the full sequence, and then they were reverse transcribed (RT) and amplified [polymerase chain reaction (PCR)] for the next round of selection.101

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Structures of four self‐cleaving ribozymes. (a) The hairpin ribozyme, (b) the hammerhead ribozyme (c) the glmS ribozyme‐riboswitch, and (d) the hepatitis delta virus (HDV) ribozyme. Active site residues are colored in red, green, and magenta. (Reprinted with permission from Ref 90. Copyright 2010 Cold Spring Harbor Laboratory Press) see reference for more information.

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Genomic systematic evolution of ligands by exponential enrichment (SELEX) high‐throughput analysis. (a) Unlike RNomics, genomic SELEX regions are not bona fide transcripts. Instead, the reads cluster into regions where binding fitness is enhanced. The aligned reads (bottom left, not all are pictured) can be represented in a signal map showing the number of sequences recovered at each region. This nucleotide‐level enrichment clarifies which parts of the sequence are most involved in the binding. The enriched part of this Hfq aptamer was selected for DMS footprinting analysis (b). The green circles indicate nucleotides protected upon Hfq binding, and orange diamonds indicate the nucleotides that were hydrolyzed in the presence of Hfq and not in the absence, indicating a conformational change. All the Hfq‐protected bases are in the region of most enrichment as indicated using the high‐throughput analysis.

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Screening for novel riboswitches. Riboswitches are the elements of RNAs that undergo conformational change upon interaction with a specific ligand. They can be involved in transcriptional regulation as shown in (a). The binding of a metabolite induces a conformational change that allows the RNA to form a terminator structure, thereby aborting transcription short of the downstream open reading frame. Transcriptional regulation is one of the many modes of activity for riboswitches. (b) Many computational approaches to identify riboswitches are tailored specifically to detect features of known riboswitches. A reduced set of candidates is chosen based on the locations relative to an open reading frame (e.g., 5′ UTR, intergenic region on polycistronic gene) and targeted gene function (e.g., metabolite biosynthesis). Next, the candidates are selected for the necessary structure, in this case, a three‐way junction. Finally, the functional domain (blue) is identified based on the most highly conserved nucleotides of riboswitch being matched. In some approaches, the functional region is detected before examining the structure. These approaches require knowledge of previously discovered riboswitches, whereas (c) detecting novel riboswitches, as is done with the CMFinder pipeline,44–47 involves the iterative refinement of alignments of homologous regions. Initially, candidate sequences are aligned, followed by assignment of the motif locations. A consensus secondary structure among the sequences is then predicted and used to generate a covariance model (CM). This CM motif profile contains states which model paired regions (‘P’) and single nucleotide regions (‘L’eft and ‘R’ight). Insertions and deletions in the form of bulges are more easily allowed when considering structure in the alignment. The profile can then be aligned back to the candidates to generate a structure‐aware estimate of the motif positions, which can then be used to improve the model itself. Iterative updates to the model halt after the updates ‘converge’, or show no sign of major changes.

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RNA-Based Catalysis > Miscellaneous RNA-Catalyzed Reactions
Regulatory RNAs/RNAi/Riboswitches > Riboswitches
Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs

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