Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection ( in vitro evolution). Improving a ribozyme-based system often requires several mutations to achieve the desired function, but extensive pairwise and higher-order epistasis prevent a simple prediction of the effect of multiple mutations that is needed for rational design. Recently, high-throughput sequencing-based approaches have produced data sets on the effects of numerous mutations in different ribozymes (RNA fitness landscapes). Here we used such high-throughput experimental data from variants of the CPEB3 self-cleaving ribozyme to train a predictive model through machine learning approaches. We trained models using either a random forest or long short-term memory (LSTM) recurrent neural network approach. We found that models trained on a comprehensive set of pairwise mutant data could predict active sequences at higher mutational distances, but the correlation between predicted and experimentally observed self-cleavage activity decreased with increasing mutational distance. Adding sequences with increasingly higher numbers of mutations to the training data improved the correlation at increasing mutational distances. Systematically reducing the size of the training data set suggests that a wide distribution of ribozyme activity may be the key to accurate predictions. Because the model predictions are based only on sequence and activity data, the results demonstrate that this machine learning approach allows readily obtainable experimental data to be used for RNA design efforts even for RNA molecules with unknown structures. The accurate prediction of RNA functions will enable a more comprehensive understanding of RNA fitness landscapes for studying evolution and for guiding RNA-based engineering efforts.
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Self-cleaving ribozymes: substrate specificity and synthetic biology applications
Various self-cleaving ribozymes appearing in nature catalyze the sequence-specific intramolecular cleavage of RNA and can be engineered to catalyze cleavage of appropriate substrates in an intermolecular fashion, thus acting as true catalysts. The mechanisms of the small, self-cleaving ribozymes have been extensively studied and reviewed previously. Self-cleaving ribozymes can possess high catalytic activity and high substrate specificity; however, substrate specificity is also engineerable within the constraints of the ribozyme structure. While these ribozymes share a common fundamental catalytic mechanism, each ribozyme family has a unique overall architecture and active site organization, indicating that several distinct structures yield this chemical activity. The multitude of catalytic structures, combined with some flexibility in substrate specificity within each family, suggests that such catalytic RNAs, taken together, could access a wide variety of substrates. Here, we give an overview of 10 classes of self-cleaving ribozymes and capture what is understood about their substrate specificity and synthetic applications. Evolution of these ribozymes in an RNA world might be characterized by the emergence of a new ribozyme family followed by rapid adaptation or diversification for specific substrates.
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- Award ID(s):
- 1935087
- NSF-PAR ID:
- 10294101
- Date Published:
- Journal Name:
- RSC Chemical Biology
- ISSN:
- 2633-0679
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Self-cleaving ribozymes are RNA molecules that catalyze the cleavage of their own phosphodiester backbones. These ribozymes are found in all domains of life and are also a tool for biotechnical and synthetic biology applications. Self-cleaving ribozymes are also an important model of sequence-to-function relationships for RNA because their small size simplifies synthesis of genetic variants and self-cleaving activity is an accessible readout of the functional consequence of the mutation. Here, we used a high-throughput experimental approach to determine the relative activity for every possible single and double mutant of five self-cleaving ribozymes. From this data, we comprehensively identified non-additive effects between pairs of mutations (epistasis) for all five ribozymes. We analyzed how changes in activity and trends in epistasis map to the ribozyme structures. The variety of structures studied provided opportunities to observe several examples of common structural elements, and the data was collected under identical experimental conditions to enable direct comparison. Heatmap-based visualization of the data revealed patterns indicating structural features of the ribozymes including paired regions, unpaired loops, non-canonical structures, and tertiary structural contacts. The data also revealed signatures of functionally critical nucleotides involved in catalysis. The results demonstrate that the data sets provide structural information similar to chemical or enzymatic probing experiments, but with additional quantitative functional information. The large-scale data sets can be used for models predicting structure and function and for efforts to engineer self-cleaving ribozymes.more » « less
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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 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 datasets, structure probing, and co-transcriptional 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.more » « less
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Abstract Systems of catalytic RNAs presumably gave rise to important evolutionary innovations, such as the genetic code. Such systems may exhibit particular tolerance to errors (error minimization) as well as coding specificity. While often assumed to result from natural selection, error minimization may instead be an emergent by-product. In an RNA world, a system of self-aminoacylating ribozymes could enforce the mapping of amino acids to anticodons. We measured the activity of thousands of ribozyme mutants on alternative substrates (activated analogs for tryptophan, phenylalanine, leucine, isoleucine, valine, and methionine). Related ribozymes exhibited shared preferences for substrates, indicating that adoption of additional amino acids by existing ribozymes would itself lead to error minimization. Furthermore, ribozyme activity was positively correlated with specificity, indicating that selection for increased activity would also lead to increased specificity. These results demonstrate that by-products of ribozyme evolution could lead to adaptive value in specificity and error tolerance.
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Harris, Kelley (Ed.)Abstract Self-cleaving ribozymes are genetic elements found in all domains of life, but their evolution remains poorly understood. A ribozyme located in the second intron of the cytoplasmic polyadenylation binding protein 3 gene (CPEB3) shows high sequence conservation in mammals, but little is known about the functional conservation of self-cleaving ribozyme activity across the mammalian tree of life or during the course of mammalian evolution. Here, we use a phylogenetic approach to design a mutational library and a deep sequencing assay to evaluate the in vitro self-cleavage activity of numerous extant and resurrected CPEB3 ribozymes that span over 100 My of mammalian evolution. We found that the predicted sequence at the divergence of placentals and marsupials is highly active, and this activity has been conserved in most lineages. A reduction in ribozyme activity appears to have occurred multiple different times throughout the mammalian tree of life. The in vitro activity data allow an evaluation of the predicted mutational pathways leading to extant ribozyme as well as the mutational landscape surrounding these ribozymes. The results demonstrate that in addition to sequence conservation, the self-cleavage activity of the CPEB3 ribozyme has persisted over millions of years of mammalian evolution.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/D0CB00207K
