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Enzymes made of RNA catalyze reactions that are essential for protein synthesis and RNA processing. However, such natural ribozymes are exceedingly rare, as evidenced by the fact that the discovery rate for new classes has dropped to one per decade from about one per year during the 1980s. Indeed, only 11 distinct ribozyme classes have been experimentally validated to date. Recently, we recognized that self-cleaving ribozymes frequently associate with certain types of genes from bacteria. Herein we exploited this association to identify divergent architectures for two previously known ribozyme classes and to discover additional noncoding RNA motifs that are self-cleaving RNA candidates. We identified three new self-cleaving classes, which we named twister sister, pistol and hatchet, from this collection, suggesting that even more ribozymes remain hidden in modern cells.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4509812 | PMC |
http://dx.doi.org/10.1038/nchembio.1846 | DOI Listing |
Methods
December 2024
Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA; Center for RNA and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA; Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA. Electronic address:
Small self-cleaving ribozymes are catalytic RNAs that cleave their phosphodiester backbone rapidly and site-specifically, without the assistance of proteins. Their catalytic properties make them ideal targets for applications in RNA pharmaceuticals and bioengineering. Consequently, computational pipelines that predict or design thousands of self-cleaving ribozyme candidates have been developed.
View Article and Find Full Text PDFElife
December 2024
Institute for Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, China.
Cell
November 2024
Stanford University, Department of Genetics, Stanford, CA, USA; Stanford University, Department of Pathology, Stanford, CA, USA. Electronic address:
Here, we describe "obelisks," a class of heritable RNA elements sharing several properties: (1) apparently circular RNA ∼1 kb genome assemblies, (2) predicted rod-like genome-wide secondary structures, and (3) open reading frames encoding a novel "Oblin" protein superfamily. A subset of obelisks includes a variant hammerhead self-cleaving ribozyme. Obelisks form their own phylogenetic group without detectable similarity to known biological agents.
View Article and Find Full Text PDFGenomics Proteomics Bioinformatics
September 2024
State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen 361102, China.
Accurate identification of the correct, biologically relevant RNA structures is critical to understanding various aspects of RNA biology since proper folding represents the key to the functionality of all types of RNA molecules and plays pivotal roles in many essential biological processes. Thus, a plethora of approaches have been developed to predict, identify, or solve RNA structures based on various computational, molecular, genetic, chemical, or physicochemical strategies. Purely computational approaches hold distinct advantages over all other strategies in terms of the ease of implementation, time, speed, cost, and throughput, but they strongly underperform in terms of accuracy that significantly limits their broader application.
View Article and Find Full Text PDFNat Neurosci
July 2024
Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, USA.
As discovery of cellular diversity in the brain accelerates, so does the need for tools that target cells based on multiple features. Here we developed Conditional Viral Expression by Ribozyme Guided Degradation (ConVERGD), an adeno-associated virus-based, single-construct, intersectional targeting strategy that combines a self-cleaving ribozyme with traditional FLEx switches to deliver molecular cargo to specific neuronal subtypes. ConVERGD offers benefits over existing intersectional expression platforms, such as expanded intersectional targeting with up to five recombinase-based features, accommodation of larger and more complex payloads and a vector that is easy to modify for rapid toolkit expansion.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!