RNA structure-wide discovery of functional interactions with multiplexed RNA motif library

AbstractBiochemical assays and computational analyses have discovered RNA structures throughout various transcripts. However, the roles of these structures are mostly unknown. Here we develop folded RNA element profiling with structure library (FOREST), a multiplexed affinity assay system to identify functional interactions from transcriptome-wide RNA structure datasets. We generate an RNA structure library by extracting validated or predicted RNA motifs from gene-annotated RNA regions. The RNA structure library with an affinity enrichment assay allows for the comprehensive identification of target-binding RNA sequences and structures in a high-throughput manner. As a proof-of-concept, FOREST discovers multiple RNA-protein interaction networks with quantitative scores, including translational regulatory elements that function in living cells. Moreover, FOREST reveals different binding landscapes of RNA G-quadruplex (rG4) structures-binding proteins and discovers rG4 structures in the terminal loops of precursor microRNAs. Overall, FOREST serves as a versatile platform to investigate RNA structure-function relationships on a large scale.

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An antibiotic-sensing leader peptide regulates translation and premature Rho-dependent transcription termination of thetopAIgene inEscherichia coli

10.1101/682021 ◽

2019 ◽

Cited By ~ 2

Author(s):

Gabriele Baniulyte ◽

Joseph T. Wade

Keyword(s):

Conformational Changes ◽

Rna Structure ◽

Transcription Termination ◽

Regulatory Elements ◽

Growth Conditions ◽

Translational Repression ◽

Leader Peptide ◽

Rna Structures ◽

Ribosome Stalling ◽

Specific Manner

AbstractLong 5′ UTRs in bacteria often contain regulatory elements that modulate expression of the downstream gene in response to environmental stimuli. In most examples of such regulation, the mechanism involves switching between alternative 5′ UTR RNA structures that impact transcription, stability, or translation of the mRNA. Here, we show that transcription of theEscherichia coli topAIgene is prematurely terminated by the termination factor Rho under standard laboratory growth conditions, and that this occurs as a result of translational repression. Regulation oftopAItranslation is controlled by a sensory ORF,toiL, located within thetopAI5′ UTR. We show that ribosomes translatingtoiLstall in a sequence-specific manner in the presence of specific ribosome-targeting antibiotics. Ribosome stalling attoiLinduces conformational changes in the RNA structure of thetopAI5′ UTR, unmasking thetopAIribosome-binding site, thereby relieving translational repression and preventing premature transcription termination. Thus,toiLacts as a sensor of translation stress, leading to regulation oftopAIat both the translational and transcriptional levels.

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An efficient algorithm for planar drawing of RNA structures with pseudoknots of any type

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720016500098 ◽

2016 ◽

Vol 14 (03) ◽

pp. 1650009 ◽

Cited By ~ 1

Author(s):

Yanga Byun ◽

Kyungsook Han

Keyword(s):

Rna Structure ◽

Large Scale ◽

Structural Elements ◽

Rna Structures ◽

Structural Element ◽

Rna Pseudoknots ◽

Number Of Stems ◽

Rna Pseudoknot ◽

Aesthetic Structure ◽

Planar Drawing

An RNA pseudoknot is a tertiary structural element in which bases of a loop pair with complementary bases are outside the loop. A drawing of RNA secondary structures is a tree, but a drawing of RNA pseudoknots is a graph that has an inner cycle within a pseudoknot and possibly outer cycles formed between the pseudoknot and other structural elements. Visualizing a large-scale RNA structure with pseudoknots as a planar drawing is challenging because a planar drawing of an RNA structure requires both pseudoknots and an entire structure enclosing the pseudoknots to be embedded into a plane without overlapping or crossing. This paper presents an efficient heuristic algorithm for visualizing a pseudoknotted RNA structure as a planar drawing. The algorithm consists of several parts for finding crossing stems and page mapping the stems, for the layout of stem-loops and pseudoknots, and for overlap detection between structural elements and resolving it. Unlike previous algorithms, our algorithm generates a planar drawing for a large RNA structure with pseudoknots of any type and provides a bracket view of the structure. It generates a compact and aesthetic structure graph for a large pseudoknotted RNA structure in O([Formula: see text]) time, where n is the number of stems of the RNA structure.

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A database of flavivirus RNA structures with a search algorithm for pseudoknots and triple base interactions

Bioinformatics ◽

10.1093/bioinformatics/btaa759 ◽

2020 ◽

Cited By ~ 1

Author(s):

Alan Zammit ◽

Leon Helwerda ◽

René C L Olsthoorn ◽

Fons J Verbeek ◽

Alexander P Gultyaev

Keyword(s):

Rna Structure ◽

Yellow Fever Virus ◽

Search Algorithm ◽

General Pattern ◽

Pattern Search ◽

Supplementary Information ◽

Untranslated Regions ◽

Rna Structures ◽

Rna Sequences ◽

Structure Database

Abstract Motivation The Flavivirus genus includes several important pathogens, such as Zika, dengue and yellow fever virus. Flavivirus RNA genomes contain a number of functionally important structures in their 3′ untranslated regions (3′UTRs). Due to the diversity of sequences and topologies of these structures, their identification is often difficult. In contrast, predictions of such structures are important for understanding of flavivirus replication cycles and development of antiviral strategies. Results We have developed an algorithm for structured pattern search in RNA sequences, including secondary structures, pseudoknots and triple base interactions. Using the data on known conserved flavivirus 3′UTR structures, we constructed structural descriptors which covered the diversity of patterns in these motifs. The descriptors and the search algorithm were used for the construction of a database of flavivirus 3′UTR structures. Validating this approach, we identified a number of domains matching a general pattern of exoribonuclease Xrn1-resistant RNAs in the growing group of insect-specific flaviviruses. Availability and implementation The Leiden Flavivirus RNA Structure Database is available at https://rna.liacs.nl. The search algorithm is available at https://github.com/LeidenRNA/SRHS. Supplementary information Supplementary data are available at Bioinformatics online.

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Repurposing Ribo-Seq to provide insights into structured RNAs

10.1101/2020.05.18.103374 ◽

2020 ◽

Author(s):

Brayon J. Fremin ◽

Ami S. Bhatt

Keyword(s):

Secondary Structure ◽

Rna Structure ◽

Large Scale ◽

Structural Information ◽

Ribosome Profiling ◽

Rna Structures ◽

Size Selection ◽

Bacterial Ribosome ◽

Powerful Approach

AbstractRibosome profiling (Ribo-Seq) is a powerful method to study translation in bacteria. However, this method can enrich RNAs that are not bound by ribosomes, but rather, are protected from degradation in another way. For example, Escherichia coli Ribo-Seq libraries also capture reads from most non-coding RNAs (ncRNAs). These fragments of ncRNAs pass all size selection steps of the Ribo-Seq protocol and survive hours of MNase treatment, presumably without protection from the ribosome or other macromolecules or proteins. Since bacterial ribosome profiling does not directly isolate ribosomes, but instead uses broad size range cutoffs to fractionate actively translated RNAs, it is understandable that some ncRNAs are retained after size selection. However, how these ‘contaminants’ survive MNase treatment is unclear. Through analyzing metaRibo-Seq reads across ssrS, a well established structured RNA in E. coli, and structured direct repeats from Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) arrays in Ruminococcus lactaris, we observed that these RNAs are protected from MNase treatment by virtue of their secondary structure. Therefore, large volumes of data previously discarded as contaminants in bacterial Ribo-Seq experiments can, in fact, be used to gain information regarding the in vivo secondary structure of ncRNAs, providing unique insight into their native functional structures.ImportanceWe observe that ‘contaminant’ signals in bacterial Ribo-Seq experiments that are often disregarded and discarded, in fact, strongly overlap with structured regions of ncRNAs. Structured ncRNAs are pivotal mediators of bioregulation in bacteria and their functions are often reliant on their specific structures. We present an approach to access important RNA structural information through merely repurposing ‘contaminant’ signals in bacterial Ribo-Seq experiments. This powerful approach enables us to partially resolve RNA structures, identify novel structured RNAs, and elucidate RNA structure-function relationships in bacteria at a large-scale and in vivo.

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Structured RNA Contaminants in Bacterial Ribo-Seq

mSphere ◽

10.1128/msphere.00855-20 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Brayon J. Fremin ◽

Ami S. Bhatt

Keyword(s):

Rna Structure ◽

Large Scale ◽

Partial Information ◽

Ribosome Profiling ◽

Micrococcal Nuclease ◽

Data Sets ◽

Rna Structures ◽

Content Type ◽

Sequencing Library

ABSTRACT Ribosome profiling (Ribo-Seq) is a powerful method to study translation in bacteria. However, Ribo-Seq signal can be observed across RNAs that one would not expect to be bound by ribosomes. For example, Escherichia coli Ribo-Seq libraries also capture reads from most noncoding RNAs (ncRNAs). While some of these ncRNAs may overlap coding regions, this alone does not explain the majority of observed signal across ncRNAs. These fragments of ncRNAs in Ribo-Seq data pass all size selection steps of the Ribo-Seq protocol and survive hours of micrococcal nuclease (MNase) treatment. In this work, we specifically focus on Ribo-Seq signal across ncRNAs and provide evidence to suggest that RNA structure, as opposed to ribosome binding, protects them from degradation and allows them to persist in the Ribo-Seq sequencing library preparation. By inspecting these “contaminant reads” in bacterial Ribo-Seq, we show that data previously disregarded in bacterial Ribo-Seq experiments may, in fact, be used to gain partial information regarding the in vivo secondary structure of ncRNAs. IMPORTANCE Structured ncRNAs are pivotal mediators of bioregulation in bacteria, and their functions are often reliant on their specific structures. Here, we first inspect Ribo-Seq reads across noncoding regions, identifying contaminant reads in these libraries. We observe that contaminant reads in bacterial Ribo-Seq experiments that are often disregarded, in fact, strongly overlap with structured regions of ncRNAs. We then perform several bioinformatic analyses to determine why these contaminant reads may persist in Ribo-Seq libraries. Finally, we highlight some structured RNA contaminants in Ribo-Seq and support the hypothesis that structures in the RNA protect them from MNase digestion. We conclude that researchers should be cautious when interpreting Ribo-Seq signal as coding without considering signal distribution. These findings also may enable us to partially resolve RNA structures, identify novel structured RNAs, and elucidate RNA structure-function relationships in bacteria at a large scale and in vivo through the reanalysis of existing Ribo-Seq data sets.

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Computational modeling of RNA 3D structure based on experimental data

Bioscience Reports ◽

10.1042/bsr20180430 ◽

2019 ◽

Vol 39 (2) ◽

Cited By ~ 13

Author(s):

Almudena Ponce-Salvatierra ◽

Astha ◽

Katarzyna Merdas ◽

Chandran Nithin ◽

Pritha Ghosh ◽

...

Keyword(s):

Experimental Data ◽

Computational Methods ◽

Rna Structure ◽

Structure Prediction ◽

3D Structure ◽

Rna Structures ◽

Data Types ◽

Rna Sequences ◽

Rna Molecules

Abstract RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.

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Predicting pseudoknotted structures across two RNA sequences

Bioinformatics ◽

10.1093/bioinformatics/bts575 ◽

2012 ◽

Vol 28 (23) ◽

pp. 3058-3065 ◽

Cited By ~ 4

Author(s):

Jana Sperschneider ◽

Amitava Datta ◽

Michael J. Wise

Keyword(s):

Secondary Structure ◽

Rna Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Prediction Method ◽

Supplementary Information ◽

Rna Structures ◽

Rna Sequences ◽

Test Set ◽

Comparative Structure

Abstract Motivation Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accurate. RNA pseudoknots are functional elements, which have highly conserved structures. However, few comparative structure prediction methods can handle pseudoknots due to the computational complexity. Results A comparative pseudoknot prediction method called DotKnot-PW is introduced based on structural comparison of secondary structure elements and H-type pseudoknot candidates. DotKnot-PW outperforms other methods from the literature on a hand-curated test set of RNA structures with experimental support. Availability DotKnot-PW and the RNA structure test set are available at the web site http://dotknot.csse.uwa.edu.au/pw. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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An algorithm for template-based prediction of secondary structures of individual RNA sequences

10.1101/171108 ◽

2017 ◽

Author(s):

Josef Pánek ◽

Martin Černý

Keyword(s):

Rna Structure ◽

Structure Prediction ◽

De Novo ◽

Secondary Structures ◽

Rna Structures ◽

Rna Sequences ◽

Biologically Relevant ◽

Rna Molecules ◽

Rna Structure Prediction ◽

Limited Applicability

ABSTRACTWhile understanding the structure of RNA molecules is vital for deciphering their functions, determining RNA structures experimentally is exceptionally hard. At the same time, extant approaches to computational RNA structure prediction have limited applicability and reliability. In this paper we provide a method to solve a simpler yet still biologically relevant problem: prediction of secondary RNA structure using structure of different molecules as a template.Our method identifies conserved and unconserved subsequences within an RNA molecule. For conserved subsequences, the template structure is directly transferred into the generated structure and combined with de-novo predicted structure for the unconserved subsequences with low evolutionary conservation. The method also determines, when the generated structure is unreliable.The method is validated using experimentally identified structures. The accuracy of the method exceeds that of classical prediction algorithms and constrained prediction methods. This is demonstrated by comparison using large number of heterogeneous RNAs. The presented method is fast and robust, and useful for various applications requiring knowledge of secondary structures of individual RNA sequences.

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Large-Scale, High-Throughput Validation of Short Hairpin RNA Sequences for RNA Interference

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057105284342 ◽

2006 ◽

Vol 11 (3) ◽

pp. 236-246 ◽

Cited By ~ 6

Author(s):

Laurence H. Lamarcq ◽

Bradley J. Scherer ◽

Michael L. Phelan ◽

Nikolai N. Kalnine ◽

Yen H. Nguyen ◽

...

Keyword(s):

High Throughput ◽

Large Scale ◽

Strong Support ◽

Gc Content ◽

Rapid Identification ◽

Hairpin Rna ◽

Rna Sequences ◽

Short Hairpin ◽

Short Hairpin Rnas ◽

Interfering Rna

A method for high-throughput cloning and analysis of short hairpin RNAs (shRNAs) is described. Using this approach, 464 shRNAs against 116 different genes were screened for knockdown efficacy, enabling rapid identification of effective shRNAs against 74 genes. Statistical analysis of the effects of various criteria on the activity of the shRNAs confirmed that some of the rules thought to govern small interfering RNA (siRNA) activity also apply to shRNAs. These include moderate GC content, absence of internal hairpins, and asymmetric thermal stability. However, the authors did not find strong support for positionspecific rules. In addition, analysis of the data suggests that not all genes are equally susceptible to RNAinterference (RNAi).

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RNA thermoswitches modulate Staphylococcus aureus adaptation to ambient temperatures

Nucleic Acids Research ◽

10.1093/nar/gkab117 ◽

2021 ◽

Vol 49 (6) ◽

pp. 3409-3426

Author(s):

Arancha Catalan-Moreno ◽

Marta Cela ◽

Pilar Menendez-Gil ◽

Naiara Irurzun ◽

Carlos J Caballero ◽

...

Keyword(s):

Staphylococcus Aureus ◽

Rna Structure ◽

Cold Shock ◽

Mrna Translation ◽

Site Directed Mutagenesis ◽

Rna Structures ◽

Double Stranded Rna ◽

Ambient Temperatures ◽

Shock Proteins ◽

Rna Hairpin

Abstract Thermoregulation of virulence genes in bacterial pathogens is essential for environment-to-host transition. However, the mechanisms governing cold adaptation when outside the host remain poorly understood. Here, we found that the production of cold shock proteins CspB and CspC from Staphylococcus aureus is controlled by two paralogous RNA thermoswitches. Through in silico prediction, enzymatic probing and site-directed mutagenesis, we demonstrated that cspB and cspC 5′UTRs adopt alternative RNA structures that shift from one another upon temperature shifts. The open (O) conformation that facilitates mRNA translation is favoured at ambient temperatures (22°C). Conversely, the alternative locked (L) conformation, where the ribosome binding site (RBS) is sequestered in a double-stranded RNA structure, is folded at host-related temperatures (37°C). These structural rearrangements depend on a long RNA hairpin found in the O conformation that sequesters the anti-RBS sequence. Notably, the remaining S. aureus CSP, CspA, may interact with a UUUGUUU motif located in the loop of this long hairpin and favour the folding of the L conformation. This folding represses CspB and CspC production at 37°C. Simultaneous deletion of the cspB/cspC genes or their RNA thermoswitches significantly decreases S. aureus growth rate at ambient temperatures, highlighting the importance of CspB/CspC thermoregulation when S. aureus transitions from the host to the environment.

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