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Functional design of ribosomes with mutant ribosomal RNA (rRNA) can expand opportunities for understanding molecular translation, building cells from the bottom-up, and engineering ribosomes with altered capabilities. However, such efforts are hampered by cell viability constraints, an enormous combinatorial sequence space, and limitations on large-scale, 3D design of RNA structures and functions. To address these challenges, we develop an integrated community science and experimental screening approach for rational design of ribosomes. This approach couples Eterna, an online video game that crowdsources RNA sequence design to community scientists in the form of puzzles, with in vitro ribosome synthesis, assembly, and translation in multiple design-build-test-learn cycles. We apply our framework to discover mutant rRNA sequences that improve protein synthesis in vitro and cell growth in vivo, relative to wild type ribosomes, under diverse environmental conditions. This work provides insights into rRNA sequence-function relationships and has implications for synthetic biology. While the ribosome has been harnessed for synthetic biology, designing ribosomes has remained challenging. Here, the authors demonstrate a community science approach for rational design of ribosomes with beneficial properties. [ABSTRACT FROM AUTHOR]

Single-particle cryogenic electron microscopy (cryo-EM) has become a standard technique for determining protein structures at atomic resolution1–3. However, cryo-EM studies of protein-free RNA are in their early days. The Tetrahymena thermophila group I self-splicing intron was the first ribozyme to be discovered and has been a prominent model system for the study of RNA catalysis and structure–function relationships4, but its full structure remains unknown. Here we report cryo-EM structures of the full-length Tetrahymena ribozyme in substrate-free and bound states at a resolution of 3.1 Å. Newly resolved peripheral regions form two coaxially stacked helices; these are interconnected by two kissing loop pseudoknots that wrap around the catalytic core and include two previously unforeseen (to our knowledge) tertiary interactions. The global architecture is nearly identical in both states; only the internal guide sequence and guanosine binding site undergo a large conformational change and a localized shift, respectively, upon binding of RNA substrates. These results provide a long-sought structural view of a paradigmatic RNA enzyme and signal a new era for the cryo-EM-based study of structure–function relationships in ribozymes.Cryo-electron microscopy has been used to determine the structure of the Tetrahymena ribozyme (a catalytic RNA) at sufficiently high resolution to model side chains and metal ions. [ABSTRACT FROM AUTHOR]

Telomerase adds telomeric repeats at chromosome ends to compensate for the telomere loss that is caused by incomplete genome end replication1. In humans, telomerase is upregulated during embryogenesis and in cancers, and mutations that compromise the function of telomerase result in disease2. A previous structure of human telomerase at a resolution of 8 Å revealed a vertebrate-specific composition and architecture3, comprising a catalytic core that is flexibly tethered to an H and ACA (hereafter, H/ACA) box ribonucleoprotein (RNP) lobe by telomerase RNA. High-resolution structural information is necessary to develop treatments that can effectively modulate telomerase activity as a therapeutic approach against cancers and disease. Here we used cryo-electron microscopy to determine the structure of human telomerase holoenzyme bound to telomeric DNA at sub-4 Å resolution, which reveals crucial DNA- and RNA-binding interfaces in the active site of telomerase as well as the locations of mutations that alter telomerase activity. We identified a histone H2A–H2B dimer within the holoenzyme that was bound to an essential telomerase RNA motif, which suggests a role for histones in the folding and function of telomerase RNA. Furthermore, this structure of a eukaryotic H/ACA RNP reveals the molecular recognition of conserved RNA and protein motifs, as well as interactions that are crucial for understanding the molecular pathology of many mutations that cause disease. Our findings provide the structural details of the assembly and active site of human telomerase, which paves the way for the development of therapeutic agents that target this enzyme.A high-resolution structure of human telomerase bound to telomeric DNA reveals details of telomerase assembly and its active site, and sheds light on how mutations alter telomerase function. [ABSTRACT FROM AUTHOR]

Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis-regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code. The RNA sequence and secondary structure regulate RNA editing by ADAR. Here the authors employ a CRISPR/Cas9-mediated saturation mutagenesis and machine learning to predict RNA editing efficiency of specific substrates. [ABSTRACT FROM AUTHOR]

The molecular mechanisms of exon definition and back-splicing are fundamental unanswered questions in pre-mRNA splicing. Here we report cryo-electron microscopy structures of the yeast spliceosomal E complex assembled on introns, providing a view of the earliest event in the splicing cycle that commits pre-mRNAs to splicing. The E complex architecture suggests that the same spliceosome can assemble across an exon, and that it either remodels to span an intron for canonical linear splicing (typically on short exons) or catalyses back-splicing to generate circular RNA (on long exons). The model is supported by our experiments, which show that an E complex assembled on the middle exon of yeast EFM5 or HMRA1 can be chased into circular RNA when the exon is sufficiently long. This simple model unifies intron definition, exon definition, and back-splicing through the same spliceosome in all eukaryotes and should inspire experiments in many other systems to understand the mechanism and regulation of these processes. The cryo-electron microscopy structures of an early spliceosome complex in yeast reveal a unified mechanism for defining introns and exons and also for back-splicing to generate circular RNA. [ABSTRACT FROM AUTHOR]

Emerging evidence suggests that the ribosome has a regulatory function in directing how the genome is translated in time and space. However, how this regulation is encoded in the messenger RNA sequence remains largely unknown. Here we uncover unique RNA regulons embedded in homeobox (Hox) 5′ untranslated regions (UTRs) that confer ribosome-mediated control of gene expression. These structured RNA elements, resembling viral internal ribosome entry sites (IRESs), are found in subsets of Hox mRNAs. They facilitate ribosome recruitment and require the ribosomal protein RPL38 for their activity. Despite numerous layers of Hox gene regulation, these IRES elements are essential for converting Hox transcripts into proteins to pattern the mammalian body plan. This specialized mode of IRES-dependent translation is enabled by an additional regulatory element that we term the translation inhibitory element (TIE), which blocks cap-dependent translation of transcripts. Together, these data uncover a new paradigm for ribosome-mediated control of gene expression and organismal development. [ABSTRACT FROM AUTHOR]

Structured noncoding RNAs underlie fundamental cellular processes, but determining their three-dimensional structures remains challenging. We demonstrate that integrating 1H NMR chemical shift data with Rosetta de novo modeling can be used to consistently determine high-resolution RNA structures. On a benchmark set of 23 noncanonical RNA motifs, including 11 'blind' targets, chemical-shift Rosetta for RNA (CS-Rosetta-RNA) recovered experimental structures with high accuracy (0.6-2.0 Å all-heavy-atom r.m.s. deviation) in 18 cases. [ABSTRACT FROM AUTHOR]

Non-coding RNAs fold into precise base-pairing patterns to carry out critical roles in genetic regulation and protein synthesis, but determining RNA structure remains difficult. Here, we show that coupling systematic mutagenesis with high-throughput chemical mapping enables accurate base-pair inference of domains from ribosomal RNA, ribozymes and riboswitches. For a six-RNA benchmark that has challenged previous chemical/computational methods, this 'mutate-and-map' strategy gives secondary structures that are in agreement with crystallography (helix error rates, 2%), including a blind test on a double-glycine riboswitch. Through modelling of partially ordered states, the method enables the first test of an interdomain helix-swap hypothesis for ligand-binding cooperativity in a glycine riboswitch. Finally, the data report on tertiary contacts within non-coding RNAs, and coupling to the Rosetta/FARFAR algorithm gives nucleotide-resolution three-dimensional models (helix root-mean-squared deviation, 5.7 Å) of an adenine riboswitch. These results establish a promising two-dimensional chemical strategy for inferring the secondary and tertiary structures that underlie non-coding RNA behaviour. [ABSTRACT FROM AUTHOR]

We present fragment assembly of RNA with full-atom refinement (FARFAR), a Rosetta framework for predicting and designing noncanonical motifs that define RNA tertiary structure. In a test set of thirty-two 6–20-nucleotide motifs, FARFAR recapitulated 50% of the experimental structures at near-atomic accuracy. Sequence redesign calculations recovered native bases at 65% of residues engaged in noncanonical interactions, and we experimentally validated mutations predicted to stabilize a signal recognition particle domain. [ABSTRACT FROM AUTHOR]

The finite-element approach to lattice field theory is both highly accurate (relative errors ∼1/ N, where N is the number of lattice points) and exactly unitary (in the sense that canonical commutation relations are exactly preserved at the lattice sites). In this Letter, we construct matrix elements for the time evolution operator for the anharmonic oscillator, for which the continuum Hamiltonian is H=p/ 2+λq/ 2k. Construction of such matrix elements does not require solving the implicit equations of motion. Low-order approximations turn out to be quite accurate. For example, the matrix element of the time evolution operator in the harmonic oscillator groundstate gives a result for the k=2 anharmonic oscillator groundstate energy accurate to better than 1% while a two-state approximation reduces the error to less than 0.1%. Accurate wavefunctions are also extracted. Analogous results may be obtained in the continuum, but there the computation is more difficult, and not generalizable to field theories in more dimensions. [ABSTRACT FROM AUTHOR]

Three-dimensional RNA models fitted into crystallographic density maps exhibit pervasive conformational ambiguities, geometric errors and steric clashes. To address these problems, we present enumerative real-space refinement assisted by electron density under Rosetta (ERRASER), coupled to Python-based hierarchical environment for integrated 'xtallography' (PHENIX) diffraction-based refinement. On 24 data sets, ERRASER automatically corrects the majority of MolProbity-assessed errors, improves the average Rfree factor, resolves functionally important discrepancies in noncanonical structure and refines low-resolution models to better match higher-resolution models. [ABSTRACT FROM AUTHOR]

Specimens below 50 kDa have generally been considered too small to be analyzed by single-particle cryo-electron microscopy (cryo-EM). The high flexibility of pure RNAs makes it difficult to obtain high-resolution structures by cryo-EM. In bacteria, riboswitches regulate sulfur metabolism through binding to the S-adenosylmethionine (SAM) ligand and offer compelling targets for new antibiotics. SAM-I, SAM-I/IV, and SAM-IV are the three most commonly found SAM riboswitches, but the structure of SAM-IV is still unknown. Here, we report the structures of apo and SAM-bound SAM-IV riboswitches (119-nt, ~40 kDa) to 3.7 Å and 4.1 Å resolution, respectively, using cryo-EM. The structures illustrate homologies in the ligand-binding core but distinct peripheral tertiary contacts in SAM-IV compared to SAM-I and SAM-I/IV. Our results demonstrate the feasibility of resolving small RNAs with enough detail to enable detection of their ligand-binding pockets and suggest that cryo-EM could play a role in structure-assisted drug design for RNA. The conformational heterogeneity of RNA molecules makes their structure determination by X-ray crystallography and NMR challenging. Here the authors show that RNA structures can be solved by cryo-EM and present the structures of a 40 kDa SAM-IV riboswitch in the apo form and bound to its ligand S-adenosylmethionine. [ABSTRACT FROM AUTHOR]

Picornaviral IRES elements are essential for initiating the cap-independent viral translation. However, three-dimensional structures of these elements remain elusive. Here, we report a 2.84-Å resolution crystal structure of hepatitis A virus IRES domain V (dV) in complex with a synthetic antibody fragment—a crystallization chaperone. The RNA adopts a three-way junction structure, topologically organized by an adenine-rich stem-loop motif. Despite no obvious sequence homology, the dV architecture shows a striking similarity to a circularly permuted form of encephalomyocarditis virus J-K domain, suggesting a conserved strategy for organizing the domain architecture. Recurrence of the motif led us to use homology modeling tools to compute a 3-dimensional structure of the corresponding domain of foot-and-mouth disease virus, revealing an analogous domain organizing motif. The topological conservation observed among these IRESs and other viral domains implicates a structured three-way junction as an architectural scaffold to pre-organize helical domains for recruiting the translation initiation machinery. Picornaviruses use modular RNA domains in their internal ribosome entry sites (IRESs) for translation through non-canonical, cap-independent mechanisms. Here the authors report the crystal structure of domain V from the IRES of hepatitis A virus (HAV) ssRNA genome, suggesting that the functional homology among different types of picornaviral IRESs is structure-based. [ABSTRACT FROM AUTHOR]

Structured RNA elements, programmed RNA conformational changes, and interactions between different RNA domains underlie many modes of regulating gene expression, mandating studies to understand the foundational principles that govern these phenomena. Exploring the structured 3′ untranslated region (UTR) of a viral RNA, we discovered that different contexts of the 3′-UTR confer different abilities to enhance translation of an associated open reading frame. In one context, ribosome-induced conformational changes in a 'sensor' RNA domain affect a separate RNA 'functional' domain, altering translation efficiency. The structure of the entire 3′-UTR reveals that structurally distinct domains use a spine of continuously stacked bases and a strut-like linker to create a conduit for communication within the higher-order architecture. Thus, this 3′-UTR RNA illustrates how RNA can use programmed conformational changes to sense the translation status of an upstream open reading frame, then create a tuned functional response by communicating that information to other RNA elements. Complex RNA three-dimensional structures undergo functionally important programmed conformational changes. Here, the authors report how two structurally and functionally coupled RNA domains within a viral 3′-UTR sense the ribosome through conformational changes and respond by modulating translation. [ABSTRACT FROM AUTHOR]

Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition ('Stanford OpenVaccine') on Kaggle, involving single-nucleotide resolution measurements on 6,043 diverse 102-130-nucleotide RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1,588 nucleotides) with improved accuracy compared with previously published models. These results indicate that such models can represent in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for dataset creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales., Competing Interests: Competing interestsD.S.K., W.K. and R.D. hold equity in a new venture seeking to stabilize mRNA molecules, and D.S.K. and W.K. are employees of that venture. W.R. and M.D. are employees of Kaggle. The remaining authors declare no competing interests., (© The Author(s) 2022.)