Solving the structure of PTB in complex with pyrimidine tracts: an NMR study of protein-RNA complexes of weak affinities

NMR spectroscopy has proven to be a powerful tool for the structure determination of protein/RNA complexes. However, the quality of these structures depends critically on the number of unambiguous intermolecular and intra-RNA nuclear Overhauser effect (NOE) constraints that can be derived. This number is often limited due to exchange phenomena that can cause signal line broadening and the fact that unambiguous NOE assignments are challenging in systems that exchange between different conformations in the intermediate to fast exchange limit. These exchange processes can include exchange between free and bound form, as well as exchange of the ligand between different binding sites on the protein. Furthermore, for the large class of RNA metabolizing proteins that bind repetitive low-complexity RNA sequences in multiple register, exchange of the protein between these overlapping binding sites introduces additional exchange pathways. Here, we describe the strategy we used to overcome these exchange processes and to reduce significantly the line width of the RNA resonances in complexes of the RNA recognition motifs (RRMs) of the polypyrimidine tract-binding protein (PTB) in complex with pyrimidine tracts and hence allowed a highly precise structure determination. This method could be employed to derive structures of other protein/single-stranded nucleic acid complexes by NMR spectroscopy. Furthermore, we have determined the affinities of the individual RRMs of PTB for pyrimidine tracts of different length and sequence. These measurements show that PTB binds preferentially to long pyrimidine tracts that contain cytosine and hence confirm the structure of PTB in complex with RNA. Furthermore, they provide quantitative insight into the question of which pyrimidine sequences within alternatively spliced pre-mRNAs will be preferentially bound by PTB.     

Crystallization of RNA and RNA-protein complexes

RNA plays a direct role in a variety of cellular activities, and in many cases its biological function is conferred by the RNA three-dimensional structure. X-ray crystallography is the method of choice for determining high resolution structures of large RNA molecules, and can also be used to compare related RNAs and identify conformational changes that may accompany biochemical activity. However, crystallization remains the rate-limiting step in RNA structure determination due to the difficulty in obtaining well-ordered crystals for X-ray diffraction analysis. Several approaches to sample preparation, crystallization, and crystal handling are presented that have been used successfully in the structure determination of RNA and RNA-protein complexes in our laboratory, and should be generally applicable to RNAs in other systems.     

Prediction of RNA secondary structure based on helical regions distribution

MOTIVATION: RNAs play an important role in many biological processes and knowing their structure is important in understanding their function. Due to difficulties in the experimental determination of RNA secondary structure, the methods of theoretical prediction for known sequences are often used. Although many different algorithms for such predictions have been developed, this problem has not yet been solved. It is thus necessary to develop new methods for predicting RNA secondary structure. The most-used at present is Zuker's algorithm which can be used to determine the minimum free energy secondary structure. However many RNA secondary structures verified by experiments are not consistent with the minimum free energy secondary structures. In order to solve this problem, a method used to search a group of secondary structures whose free energy is close to the global minimum free energy was developed by Zuker in 1989. When considering a group of secondary structures, if there is no experimental data, we cannot tell which one is better than the others. This case also occurs in combinatorial and heuristic methods. These two kinds of methods have several weaknesses. Here we show how the central limit theorem can be used to solve these problems. RESULTS: An algorithm for predicting RNA secondary structure based on helical regions distribution is presented, which can be used to find the most probable secondary structure for a given RNA sequence. It consists of three steps. First, list all possible helical regions. Second, according to central limit theorem, estimate the occurrence probability of every helical region based on the Monte Carlo simulation. Third, add the helical region with the biggest probability to the current structure and eliminate the helical regions incompatible with the current structure. The above processes can be repeated until no more helical regions can be added. Take the current structure as the final RNA secondary structure. In order to demonstrate the confidence of the program, a test on three RNA sequences: tRNAPhe, Pre-tRNATyr, and Tetrahymena ribosomal RNA intervening sequence, is performed. AVAILABILITY: The program is written in Turbo Pascal 7.0. The source code is available upon request. CONTACT: Wujj@nic.bmi.ac.cn or Liwj@mail.bmi.ac.cn      

Abstract shapes of RNA

The function of a non-protein-coding RNA is often determined by its structure. Since experimental determination of RNA structure is time-consuming and expensive, its computational prediction is of great interest, and efficient solutions based on thermodynamic parameters are known. Frequently, however, the predicted minimum free energy structures are not the native ones, leading to the necessity of generating suboptimal solutions. While this can be accomplished by a number of programs, the user is often confronted with large outputs of similar structures, although he or she is interested in structures with more fundamental differences, or, in other words, with different abstract shapes. Here, we formalize the concept of abstract shapes and introduce their efficient computation. Each shape of an RNA molecule comprises a class of similar structures and has a representative structure of minimal free energy within the class. Shape analysis is implemented in the program RNAshapes. We applied RNAshapes to the prediction of optimal and suboptimal abstract shapes of several RNAs. For a given energy range, the number of shapes is considerably smaller than the number of structures, and in all cases, the native structures were among the top shape representatives. This demonstrates that the researcher can quickly focus on the structures of interest, without processing up to thousands of near-optimal solutions. We complement this study with a large-scale analysis of the growth behaviour of structure and shape spaces. RNAshapes is available for download and as an online version on the Bielefeld Bioinformatics Server.     

Interpreting oligonucleotide microarray data to determine RNA secondary structure: application to the 3' end of Bombyx mori R2 RNA

A method to deduce RNA secondary structure on the basis of data from microarrays of 2'-O-methyl RNA 9-mers immobilized in agarose film on glass slides is tested with a 249 nucleotide RNA from the 3' end of the R2 retrotransposon from Bombyx mori. Various algorithms incorporating binding data and free-energy minimization calculations were compared for interpreting the data to provide possible secondary structures. Two different methods give structures with 100 and 87% of the base pairs determined by sequence comparison. In contrast, structures predicted by free-energy minimization alone by Mfold and RNAstructure contain 52 and 72% of the known base pairs, respectively. This combination of high throughput microarray techniques with algorithms using free-energy calculations has potential to allow for fast determination of RNA secondary structure. It should also facilitate the design of antisense and siRNA oligonucleotides.     

Single-stranded-RNA binding proteins

Our knowledge of protein interactions with RNA molecules has been, so far, largely restricted to cases in which the RNA itself is folded into a secondary and/or tertiary structure stabilised by intramolecular base pairing and stacking. Until recently, only limited structural information has been available about protein interactions with single-stranded RNA. A breakthrough in our understanding of these interactions came in 1999, with the determination of four crystal structures of protein complexes with extended single-stranded RNA molecules. These structures revealed wonderfully satisfying patterns of the ability of proteins to accommodate RNA bases, with the sugar-phosphate backbone often adopting conformations that are different from the classical double helix.     

Microarrays for identifying binding sites and probing structure of RNAs

Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure–function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs.     

Multiple RNA structure alignment

Ribonucleic Acid (RNA) structures can be viewed as a special kind of strings where characters in a string can bond with each other. The question of aligning two RNA structures has been studied for a while, and there are several successful algorithms that are based upon different models. In this paper, by adopting the model introduced in Wang and Zhang,(19) we propose two algorithms to attack the question of aligning multiple RNA structures. Our methods are to reduce the multiple RNA structure alignment problem to the problem of aligning two RNA structure alignments. Meanwhile, we will show that the framework of sequence center star alignment algorithm can be applied to the problem of multiple RNA structure alignment, and if the triangle inequality is met in the scoring matrix, the approximation ratio of the algorithm remains to be 2-2(over)n, where n is the total number of structures.     

RNA secondary structure prediction using stochastic context-free grammars and evolutionary history.

MOTIVATION: Many computerized methods for RNA secondary structure prediction have been developed. Few of these methods, however, employ an evolutionary model, thus relevant information is often left out from the structure determination. This paper introduces a method which incorporates evolutionary history into RNA secondary structure prediction. The method reported here is based on stochastic context-free grammars (SCFGs) to give a prior probability distribution of structures. RESULTS: The phylogenetic tree relating the sequences can be found by maximum likelihood (ML) estimation from the model introduced here. The tree is shown to reveal information about the structure, due to mutation patterns. The inclusion of a prior distribution of RNA structures ensures good structure predictions even for a small number of related sequences. Prediction is carried out using maximum a posteriori estimation (MAP) estimation in a Bayesian approach. For small sequence sets, the method performs very well compared to current automated methods.     

Crystallographic studies of DNA and RNA

Our knowledge of nucleic acid structure grew rapidly over the past decade with the determination to high resolution of larger structures of great biological significance. Advances in sample preparation, crystallization techniques, cryocrystallography, access to synchrotron radiation, and crystallographic software continue to accelerate the structure determination of nucleic acids. Crystallographic studies of DNA and RNA molecules share many considerations that we outline here. The application of crystallography to RNA is illustrated with the structure determination of the CUG repeat that is linked to type I myotonic dystrophy.     

RNA helical packing in solution: NMR structure of a 30 kDa GAAA tetraloop-receptor complex

Tertiary interactions are critical for proper RNA folding and ribozyme catalysis. RNA tertiary structure is often condensed through long-range helical packing interactions mediated by loop-receptor motifs. RNA structures displaying helical packing by loop-receptor interactions have been solved by X-ray crystallography, but not by NMR. Here, we report the NMR structure of a 30 kDa GAAA tetraloop-receptor RNA complex. In order to stabilize the complex, we used a modular design in which the RNA was engineered to form a homodimer, with each subunit containing a GAAA tetraloop phased one helical turn apart from its cognate 11-nucleotide receptor domain. The structure determination utilized specific isotopic labeling patterns (2H, 13C and 15N) and refinement against residual dipolar couplings. We observe a unique and highly unusual chemical shift pattern for an adenosine platform interaction that reveals a spectroscopic fingerprint for this motif. The structure of the GAAA tetraloop-receptor interaction is well defined solely from experimental NMR data, shows minor deviations from previously solved crystal structures, and verifies the previously inferred hydrogen bonding patterns within this motif. This work demonstrates the feasibility of using engineered homodimers as modular systems for the determination of RNA tertiary interactions by NMR.     

Comparative analysis of hairpin ribozyme structures and interference data

Great strides in understanding the molecular underpinnings of RNA catalysis have been achieved with advances in RNA structure determination by NMR spectroscopy and X-ray crystallography. Despite these successes the functional relevance of a given structure can only be assessed upon comparison with biochemical studies performed on functioning RNA molecules. The hairpin ribozyme presents an excellent case study for such a comparison. The active site is comprised of two stems each with an internal loop that forms a series of non-canonical base pairs. These loops dock into each other to create an active site for catalysis. Recently, three independent structures have been determined for this catalytic RNA, including two NMR structures of the isolated loop A and loop B stems and a high-resolution crystal structure of both loops in a docked conformation. These structures differ significantly both in their tertiary fold and the nature of the non-canonical base pairs formed within each loop. Several of the chemical groups required to achieve a functioning hairpin ribozyme have been determined by nucleotide analog interference mapping (NAIM). Here we compare the three hairpin structures with previously published NAIM data to assess the convergence between the structural and functional data. While there is significant disparity between the interference data and the individual NMR loop structures, there is almost complete congruity with the X-ray structure. The only significant differences cluster around an occluded pocket adjacent to the scissile phosphate. These local differences may suggest a role for these atoms in the transition state, either directly in chemistry or via a local structural rearrangement.     

RNAPack: an integrated NMR approach to RNA structure determination

Over the last decade, a vast number of useful nuclear magnetic resonance (NMR) experiments have been developed and successfully employed to determine the structure and dynamics of RNA oligonucleotides. Despite this progress, high-resolution RNA structure determination by NMR spectroscopy still remains a lengthy process and requires programming and extensive calibrations to perform NMR experiments successfully. To accelerate RNA structure determination by NMR spectroscopy, we have designed and programmed a package of RNA NMR experiments, called RNAPack. The user-friendly package contains a set of semiautomated single, double, and triple resonance NMR experiments, which are fully optimized for high-resolution RNA solution structure determination on Varian NMR spectrometers. RNAPack provides an autocalibration feature that allows rapid calibration of all NMR experiments in a single step and thereby speeds up the NMR data collection and eliminates user errors. In our laboratory, we have successfully employed this technology to solve RNA solution structures of domains of the internal ribosome entry site of the genomic hepatitis C viral RNA in less than 3 months. RNAPack therefore makes NMR spectroscopy an attractive and rapid structural tool and allows integration of atomic resolution structural information into biochemical studies of large RNA systems.     

R-CHIE: a web server and R package for visualizing RNA secondary structures

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems.     

An algebraic representation of RNA secondary structures.

This paper develops mathematical methods for describing and analyzing RNA secondary structures. It was motivated by the need to develop rigorous yet efficient methods to treat transitions from one secondary structure to another, which we propose here may occur as motions of loops within RNAs having appropriate sequences. In this approach a molecular sequence is described as a vector of the appropriate length. The concept of symmetries between nucleic acid sequences is developed, and the 48 possible different types of symmetries are described. Each secondary structure possible for a particular nucleotide sequence determines a symmetric, signed permutation matrix. The collection of all possible secondary structures is comprised of all matrices of this type whose left multiplication with the sequence vector leaves that vector unchanged. A transition between two secondary structures is given by the product of the two corresponding structure matrices. This formalism provides an efficient method for describing nucleic acid sequences that allows questions relating to secondary structures and transitions to be addressed using the powerful methods of abstract algebra. In particular, it facilitates the determination of possible secondary structures, including those containing pseudoknots. Although this paper concentrates on RNA structure, this formalism also can be applied to DNA.     

An Algebraic Representation of RNA Secondary Structures

Abstract

This paper develops mathematical methods for describing and analyzing RNA secondary structures. It was motivated by the need to develop rigorous yet efficient methods to treat transitions from one secondary structure to another, which we propose here may occur as motions of loops within RNAs having appropriate sequences. In this approach a molecular sequence is described as a vector of the appropriate length. The concept of symmetries between nucleic acid sequences is developed, and the 48 possible different types of symmetries are described. Each secondary structure possible for a particular nucleotide sequence determines a symmetric, signed permutation matrix. The collection of all possible secondary structures is comprised of all matrices of this type whose left multiplication with the sequence vector leaves that vector unchanged. A transition between two secondary structures is given by the product of the two corresponding structure matrices. This formalism provides an efficient method for describing nucleic acid sequences that allows questions relating to secondary structures and transitions to be addressed using the powerful methods of abstract algebra. In particular, it facilitates the determination of possible secondary structures, including those containing pseudoknots. Although this paper concentrates on RNA structure, this formalism also can be applied to DNA     

An algorithm for searching RNA motifs in genomic sequences

RNA molecules, which are found in all living cells, fold into characteristic structures that account for their diverse functional activities. Many of these RNA structures consist of a collection of fundamental RNA motifs. The various combinations of RNA basic components form different RNA classes and define their unique structural and functional properties. The availability of many genome sequences makes it possible to search computationally for functional RNAs. Biological experiments indicate that functional RNAs have characteristic RNA structural motifs represented by specific combinations of base pairings and conserved nucleotides in the loop regions. The searching for those well-ordered RNA structures and their homologues in genomic sequences is very helpful for the understanding of RNA-based gene regulation. In this paper, we consider the following problem: given an RNA sequence with a known secondary structure, efficiently determine candidate segments in genomic sequences that can potentially form RNA secondary structures similar to the given RNA secondary structure. Our new bottom-up approach searches all potential stem-loops similar to ones of the given RNA secondary structure first, and then based on located stem-loops, detects potential homologous structural RNAs in genomic sequences.