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1. Cofactors are Remnants of Life’s Origin and Early Evolution

   https://doi.org/10.1007/s00239-020-09988-4  

   Goldman, Aaron D.; Kacar, Betul (April 2021, Journal of Molecular Evolution)

   null (Ed.)

   Abstract The RNA World is one of the most widely accepted hypotheses explaining the origin of the genetic system used by all organisms today. It proposes that the tripartite system of DNA, RNA, and proteins was preceded by one consisting solely of RNA, which both stored genetic information and performed the molecular functions encoded by that genetic information. Current research into a potential RNA World revolves around the catalytic properties of RNA-based enzymes, or ribozymes. Well before the discovery of ribozymes, Harold White proposed that evidence for a precursor RNA world could be found within modern proteins in the form of coenzymes, the majority of which contain nucleobases or nucleoside moieties, such as Coenzyme A and S-adenosyl methionine, or are themselves nucleotides, such as ATP and NADH (a dinucleotide). These coenzymes, White suggested, had been the catalytic active sites of ancient ribozymes, which transitioned to their current forms after the surrounding ribozyme scaffolds had been replaced by protein apoenzymes during the evolution of translation. Since its proposal four decades ago, this groundbreaking hypothesis has garnered support from several different research disciplines and motivated similar hypotheses about other classes of cofactors, most notably iron-sulfur cluster cofactors as remnants of the geochemical setting of the origin of life. Evidence from prebiotic geochemistry, ribozyme biochemistry, and evolutionary biology, increasingly supports these hypotheses. Certain coenzymes and cofactors may bridge modern biology with the past and can thus provide insights into the elusive and poorly-recorded period of the origin and early evolution of life. 

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2. Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data

   https://doi.org/10.3389/fmolb.2022.893864  

   Beck, James D.; Roberts, Jessica M.; Kitzhaber, Joey M.; Trapp, Ashlyn; Serra, Edoardo; Spezzano, Francesca; Hayden, Eric J. (August 2022, Frontiers in Molecular Biosciences)

   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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3. Light-controlled twister ribozyme with single-molecule detection resolves RNA function in time and space

   https://doi.org/10.1073/pnas.2003425117  

   Korman, Arthur; Sun, Huabing; Hua, Boyang; Yang, Haozhe; Capilato, Joseph N.; Paul, Rakesh; Panja, Subrata; Ha, Taekjip; Greenberg, Marc M.; Woodson, Sarah A. (May 2020, Proceedings of the National Academy of Sciences)

   Small ribozymes such asOryza sativatwister spontaneously cleave their own RNA when the ribozyme folds into its active conformation. The coupling between twister folding and self-cleavage has been difficult to study, however, because the active ribozyme rapidly converts to product. Here, we describe the synthesis of a photocaged nucleotide that releases guanosine within microseconds upon photosolvolysis with blue light. Application of this tool toO. sativatwister achieved the spatial (75 µm) and temporal (≤30 ms) control required to resolve folding and self-cleavage events when combined with single-molecule fluorescence detection of the ribozyme folding pathway. Real-time observation of single ribozymes after photo-deprotection showed that the precleaved folded state is unstable and quickly unfolds if the RNA does not react. Kinetic analysis showed that Mg²⁺and Mn²⁺ions increase ribozyme efficiency by making transitions to the high energy active conformation more probable, rather than by stabilizing the folded ground state or the cleaved product. This tool for light-controlled single RNA folding should offer precise and rapid control of other nucleic acid systems. 

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4. Flanking Sequence Cotranscriptionally Regulates Twister Ribozyme Activity

   https://doi.org/10.1021/acs.biochem.3c00506  

   McKinley, Lauren N.; Kern, Reuben G.; Assmann, Sarah M.; Bevilacqua, Philip C. (January 2024, Biochemistry)

   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. 

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5. Experimental Resurrection of Ancestral Mammalian CPEB3 Ribozymes Reveals Deep Functional Conservation

   https://doi.org/10.1093/molbev/msab074  

   Bendixsen, Devin P; Pollock, Tanner B; Peri, Gianluca; Hayden, Eric J (March 2021, Molecular Biology and Evolution)

   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. 

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