scholarly journals Correcting a SHAPE-directed RNA structure by a mutate-map-rescue approach

2014 ◽  
Author(s):  
Siqi Tian ◽  
Pablo Cordero ◽  
Wipapat Kladwang ◽  
Rhiju Das
Keyword(s):  
Secondary Structure ◽  
Conformational Change ◽  
High Throughput ◽  
Rna Structure ◽  
Three Dimensional ◽  
Dynamic Structure ◽  
Chemical Mapping ◽  
Computational Support ◽  
Shape Inference ◽  
Shape Selective

ABSTRACTThe three-dimensional conformations of non-coding RNAs underpin their biochemical functions but have largely eluded experimental characterization. Here, we report that integrating a classic mutation/rescue strategy with high-throughput chemical mapping enables rapid RNA structure inference with unusually strong validation. We revisit a paradigmatic 16S rRNA domain for which SHAPE (selective 2′-hydroxyl acylation with primer extension) suggested a conformational change between apo-and holo-ribosome conformations. Computational support estimates, data from alternative chemical probes, and mutate-and-map (M2) experiments expose limitations of prior methodology and instead give a near-crystallographic secondary structure. Systematic interrogation of single base pairs via a high-throughput mutation/rescue approach then permits incisive validation and refinement of the M2-based secondary structure and further uncovers the functional conformation as an excited state (25±5% population) accessible via a single-nucleotide register shift. These results correct an erroneous SHAPE inference of a ribosomal conformational change and suggest a general mutate-map-rescue approach for dissecting RNA dynamic structure landscapes.

scholarly journals RAG-Web: RNA structure prediction/design using RNA-As-Graphs

2019 ◽  
Author(s):  
Grace Meng ◽  
Marva Tariq ◽  
Swati Jain ◽  
Shereef Elmetwaly ◽  
Tamar Schlick
Keyword(s):  
Secondary Structure ◽  
Rna Structure ◽  
Structure Prediction ◽  
Rna Secondary Structure ◽  
Three Dimensional ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Tree Graph ◽  
Rna Structure Prediction ◽  
Tree Graphs

Abstract Summary We launch a webserver for RNA structure prediction and design corresponding to tools developed using our RNA-As-Graphs (RAG) approach. RAG uses coarse-grained tree graphs to represent RNA secondary structure, allowing the application of graph theory to analyze and advance RNA structure discovery. Our webserver consists of three modules: (a) RAG Sampler: samples tree graph topologies from an RNA secondary structure to predict corresponding tertiary topologies, (b) RAG Builder: builds three-dimensional atomic models from candidate graphs generated by RAG Sampler, and (c) RAG Designer: designs sequences that fold onto novel RNA motifs (described by tree graph topologies). Results analyses are performed for further assessment/selection. The Results page provides links to download results and indicates possible errors encountered. RAG-Web offers a user-friendly interface to utilize our RAG software suite to predict and design RNA structures and sequences. Availability and implementation The webserver is freely available online at: http://www.biomath.nyu.edu/ragtop/. Supplementary information Supplementary data are available at Bioinformatics online.

Secondary structure model of the naked segment 7 influenza A virus genomic RNA

2016 ◽  
Vol 473 (23) ◽  
pp. 4327-4348 ◽  
Author(s):  
Agnieszka Ruszkowska ◽  
Elzbieta Lenartowicz ◽  
Walter N. Moss ◽  
Ryszard Kierzek ◽  
Elzbieta Kierzek
Keyword(s):  
Secondary Structure ◽  
Influenza A Virus ◽  
Rna Structure ◽  
Influenza A ◽  
Comparative Sequence Analysis ◽  
Rnase H ◽  
Structure Model ◽  
Chemical Mapping ◽  
Secondary Structure Model ◽  
Negative Sense

The influenza A virus (IAV) genome comprises eight negative-sense viral (v)RNA segments. The seventh segment of the genome encodes two essential viral proteins and is specifically packaged alongside the other seven vRNAs. To gain insights into the possible roles of RNA structure both within and without virions, a secondary structure model of a naked (protein-free) segment 7 vRNA (vRNA7) has been determined using chemical mapping and thermodynamic energy minimization. The proposed structure model was validated using microarray mapping, RNase H cleavage and comparative sequence analysis. Additionally, the detailed structures of three vRNA7 fragment constructs — comprising independently folded subdomains — were determined. Much of the proposed vRNA7 structure is preserved between IAV strains, suggesting their importance in the influenza replication cycle. Possible structure rearrangements, which allow or preclude long-range RNA interactions, are also proposed.

scholarly journals Structural relation matching: an algorithm to identify structural patterns into RNAs and their interactions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michela Quadrini
Keyword(s):  
Hydrogen Bonding ◽  
Secondary Structure ◽  
Nucleotide Sequence ◽  
Thermus Thermophilus ◽  
Three Dimensional ◽  
Secondary Structures ◽  
Structural Effect ◽  
Biological Processes ◽  
Structural Pattern ◽  
Rna Molecules

Abstract RNA molecules play crucial roles in various biological processes. Their three-dimensional configurations determine the functions and, in turn, influences the interaction with other molecules. RNAs and their interaction structures, the so-called RNA–RNA interactions, can be abstracted in terms of secondary structures, i.e., a list of the nucleotide bases paired by hydrogen bonding within its nucleotide sequence. Each secondary structure, in turn, can be abstracted into cores and shadows. Both are determined by collapsing nucleotides and arcs properly. We formalize all of these abstractions as arc diagrams, whose arcs determine loops. A secondary structure, represented by an arc diagram, is pseudoknot-free if its arc diagram does not present any crossing among arcs otherwise, it is said pseudoknotted. In this study, we face the problem of identifying a given structural pattern into secondary structures or the associated cores or shadow of both RNAs and RNA–RNA interactions, characterized by arbitrary pseudoknots. These abstractions are mapped into a matrix, whose elements represent the relations among loops. Therefore, we face the problem of taking advantage of matrices and submatrices. The algorithms, implemented in Python, work in polynomial time. We test our approach on a set of 16S ribosomal RNAs with inhibitors of Thermus thermophilus, and we quantify the structural effect of the inhibitors.

scholarly journals Special Issue: Application of Extracellular Matrix in Regenerative Medicine

2021 ◽  
Vol 11 (7) ◽  
pp. 3262
Author(s):  
Neill J. Turner
Keyword(s):  
Extracellular Matrix ◽  
Regenerative Medicine ◽  
Wound Repair ◽  
Three Dimensional ◽  
Dynamic Structure ◽  
Scaffold Material ◽  
Special Issue ◽  
Organ Regeneration ◽  
Scaffold Materials ◽  
The Many

The present Special Issue comprises a collection of articles addressing the many ways in which extracellular matrix (ECM), or its components parts, can be used in regenerative medicine applications. ECM is a dynamic structure, composed of a three-dimensional architecture of fibrous proteins, proteoglycans, and glycosaminoglycans, synthesized by the resident cells. Consequently, ECM can be considered as nature’s ideal biologic scaffold material. The articles in this Special Issue cover a range of topics from the use of ECM components to manufacture scaffold materials, understanding how changes in ECM composition can lead to the development of disease, and how decellularization techniques can be used to develop tissue-derived ECM scaffolds for whole organ regeneration and wound repair. This editorial briefly summarizes the most interesting aspects of these articles.

scholarly journals FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing

2010 ◽  
Vol 7 (12) ◽  
pp. 995-1001 ◽  
Author(s):  
Jason G Underwood ◽  
Andrew V Uzilov ◽  
Sol Katzman ◽  
Courtney S Onodera ◽  
Jacob E Mainzer ◽  
...  
Keyword(s):  
High Throughput ◽  
Rna Structure ◽  
High Throughput Sequencing ◽  
Structure Probing

scholarly journals Three-dimensional scaffolds of acellular human and porcine lungs for high throughput studies of lung disease and regeneration

Biomaterials ◽  
2014 ◽  
Vol 35 (9) ◽  
pp. 2664-2679 ◽  
Author(s):  
Darcy E. Wagner ◽  
Nicholas R. Bonenfant ◽  
Dino Sokocevic ◽  
Michael J. DeSarno ◽  
Zachary D. Borg ◽  
...  
Keyword(s):  
Lung Disease ◽  
High Throughput ◽  
Three Dimensional ◽  
Porcine Lungs

scholarly journals Parallel, linear, and subnanometric 3D tracking of microparticles with Stereo Darkfield Interferometry

2021 ◽  
Vol 7 (6) ◽  
pp. eabe3902
Author(s):  
Martin Rieu ◽  
Thibault Vieille ◽  
Gaël Radou ◽  
Raphaël Jeanneret ◽  
Nadia Ruiz-Gutierrez ◽  
...  
Keyword(s):  
High Precision ◽  
High Throughput ◽  
Single Molecule ◽  
Particle Tracking ◽  
Focal Plane ◽  
Tracking System ◽  
Three Dimensional ◽  
3D Tracking ◽  
Single Molecule Force Spectroscopy ◽  
A New Technique

While crucial for force spectroscopists and microbiologists, three-dimensional (3D) particle tracking suffers from either poor precision, complex calibration, or the need of expensive hardware, preventing its massive adoption. We introduce a new technique, based on a simple piece of cardboard inserted in the objective focal plane, that enables simple 3D tracking of dilute microparticles while offering subnanometer frame-to-frame precision in all directions. Its linearity alleviates calibration procedures, while the interferometric pattern enhances precision. We illustrate its utility in single-molecule force spectroscopy and single-algae motility analysis. As with any technique based on back focal plane engineering, it may be directly embedded in a commercial objective, providing a means to convert any preexisting optical setup in a 3D tracking system. Thanks to its precision, its simplicity, and its versatility, we envision that the technique has the potential to enhance the spreading of high-precision and high-throughput 3D tracking.

In Silico Study of Secondary Structure of Hemoglobin Protein

2021 ◽  
pp. 6245-6249
Author(s):  
Roma Chandra
Keyword(s):  
Secondary Structure ◽  
Protein Sequence ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Protein Secondary Structure ◽  
Alpha Helix ◽  
Prediction Methods ◽  
Protein Secondary Structures

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.

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