Direct testing of natural twister ribozymes from over a thousand organisms reveals a broad tolerance for structural imperfections.

Twister ribozymes are an extensively studied class of nucleolytic RNAs. Thousands of natural twisters have been proposed using sequence homology and structural descriptors. Yet, most of these candidates have not been validated experimentally. To address this gap, we developed CHiTA (Cleavage High-Throughput Assay), a high-throughput pipeline utilizing massively parallel oligonucleotide synthesis and next-generation sequencing to test putative ribozymes en masse in a scarless fashion. As proof of principle, we applied CHiTA to a small set of known active and mutant ribozymes. We then used CHiTA to test two large sets of naturally occurring twister ribozymes: over 1, 600 previously reported putative twisters and ∼1, 000 new candidate twisters. The new candidates were identified computationally in ∼1, 000 organisms, representing a massive increase in the number of ribozyme-harboring organisms. Approximately 94% of the twisters we tested were active and cleaved site-specifically. Analysis of their structural features revealed that many substitutions and helical imperfections can be tolerated. We repeated our computational search with structural descriptors updated from this analysis, whereupon we identified and confirmed the first intrinsically active twister ribozyme in mammals. CHiTA broadly expands the number of active twister ribozymes found in nature and provides a powerful method for functional analyses of other RNAs.

Flanking Sequence Cotranscriptionally Regulates Twister Ribozyme Activity.

Small nucleolytic ribozymes are RNAs that cleave their own phosphodiester backbone. While proteinaceous enzymes are regulated by a variety of known mechanisms, methods of regulation for ribozymes remain unclear. Twister is one ribozyme class for which many structural and catalytic properties have been elucidated. However, few studies have analyzed the activity of twister ribozymes in the context of a native flanking sequence, even though ribozymes as transcribed in nature do not exist in isolation. Interactions between the ribozyme and its neighboring sequences can induce conformational changes that inhibit self-cleavage, providing a regulatory mechanism that could naturally determine ribozyme activity in vivo and in synthetic applications. To date, eight twister ribozymes have been identified within the staple crop rice (Oryza sativa). Herein, we select several twister ribozymes from rice and show that they are differentially regulated by their flanking sequence using published RNA-seq data sets, structure probing, and cotranscriptional cleavage assays. We found that the Osa 1-2 ribozyme does not interact with its flanking sequences. However, sequences flanking the Osa 1-3 and Osa 1-8 ribozymes form inactive conformations, referred to here as "ribozymogens", that attenuate ribozyme self-cleavage activity. For the Osa 1-3 ribozyme, we show that activity can be rescued upon addition of a complementary antisense oligonucleotide, suggesting ribozymogens can be controlled via external signals. In all, our data provide a plausible mechanism wherein flanking sequence differentially regulates ribozyme activity in vivo. More broadly, the ability to regulate ribozyme behavior locally has potential applications in control of gene expression and synthetic biology.

The Metabolome Weakens RNA Thermodynamic Stability and Strengthens RNA Chemical Stability.

We examined the complex network of interactions among RNA, the metabolome, and divalent Mg2+ under conditions that mimic the Escherichia coli cytoplasm. We determined Mg2+ binding constants for the top 15 E. coli metabolites, comprising 80% of the metabolome by concentration at physiological pH and monovalent ion concentrations. These data were used to inform the development of an artificial cytoplasm that mimics in vivo E. coli conditions, which we term "Eco80". We empirically determined that the mixture of E. coli metabolites in Eco80 approximated single-site binding behavior toward Mg2+ in the biologically relevant free Mg2+ range of ∼0.5 to 3 mM Mg2+, using a Mg2+-sensitive fluorescent dye. Effects of Eco80 conditions on the thermodynamic stability, chemical stability, structure, and catalysis of RNA were examined. We found that Eco80 conditions lead to opposing effects on the thermodynamic and chemical stabilities of RNA. In particular, the thermodynamic stability of RNA helices was weakened by 0.69 ± 0.12 kcal/mol, while the chemical stability was enhanced ∼2-fold, which can be understood using the speciation of Mg2+ between weak and strong Mg2+-metabolite complexes in Eco80. Overall, the use of Eco80 reflects RNA function in vivo and enhances the biological relevance of mechanistic studies of RNA.

Genome Sequences of Six Cluster N Mycobacteriophages, Kevin1, Nenae, Parmesanjohn, ShrimpFriedEgg, Smurph, and SpongeBob, Isolated on Mycobacterium smegmatis mc2155.

The annotation of six cluster N Mycobacterium smegmatis phages (Kevin1, Nenae, Parmesanjohn, ShrimpFriedEgg, Smurph, and SpongeBob) reveals regions of genomic diversity, particularly within the central region of the genome. The genome of Kevin1 includes two orphams (genes with no similarity to other phage genes), with one predicted to encode an AAA-ATPase.

Genome Sequences of Chancellor, Mitti, and Wintermute, Three Subcluster K4 Phages Isolated Using Mycobacterium smegmatis mc2155.

Mycobacteriophages Chancellor, Mitti, and Wintermute infect Mycobacterium smegmatis mc2155 and are closely related to phages Cheetobro and Fionnbharth in subcluster K4. Genome sizes range from 57,697 bp to 58,046 bp. Phages are predicted to be temperate and to infect the pathogen Mycobacterium tuberculosis.

Semantic distance norms computed from an electronic dictionary (WordNet).

WordNet, an electronic dictionary (or lexical database), is a valuable resource for computational and cognitive scientists. Recent work on the computing of semantic distances among nodes (synsets) in WordNet has made it possible to build a large database of semantic distances for use in selecting word pairs for psychological research. The database now contains nearly 50,000 pairs of words that have values for semantic distance, associative strength, and similarity based on co-occurrence. Semantic distance was found to correlate weakly with these other measures but to correlate more strongly with another measure of semantic relatedness, featural similarity. Hierarchical clustering analysis suggested that the knowledge structure underlying semantic distance is similar in gross form to that underlying featural similarity. In experiments in which semantic similarity ratings were used, human participants were able to discriminate semantic distance. Thus, semantic distance as derived from WordNet appears distinct from other measures of word pair relatedness and is psychologically functional. This database may be downloaded from www.psychonomic.org/archive/.