Slow formation of a pseudoknot structure is rate limiting in the productive co-transcriptional folding of the self-splicing Candida intron

Regulation of the ThiM riboswitch is facilitated by the trapped structure formed during transcription of the wild-type sequence

The ThiM riboswitch from Escherichia coli is a typical mRNA device that modulates downstream gene expression by sensing TPP. The helix-based RNA folding theory is used to investigate its detailed regulatory behaviors in cells. This RNA molecule is transcriptionally trapped in a state with the unstructured SD sequence in the absence of TPP, which induces downstream gene expression. As a key step to turn on gene expression, formation of this trapped state (the genetic ON state) highly depends on the co-transcriptional folding of its wild-type sequence. Instead of stabilities of the genetic ON and OFF states, the transcription rate, pause, and ligand levels are combined to affect the ThiM riboswitch-mediated gene regulation, which is consistent with a kinetic control model.

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.

Mimicking Ribosomal Unfolding of RNA Pseudoknot in a Protein Channel

Pseudoknots are a fundamental RNA tertiary structure with important roles in regulation of mRNA translation. Molecular force spectroscopic approaches such as optical tweezers can track the pseudoknot's unfolding intermediate states by pulling the RNA chain from both ends, but the kinetic unfolding pathway induced by this method may be different from that in vivo, which occurs during translation and proceeds from the 5' to 3' end. Here we developed a ribosome-mimicking, nanopore pulling assay for dissecting the vectorial unfolding mechanism of pseudoknots. The pseudoknot unfolding pathway in the nanopore, either from the 5' to 3' end or in the reverse direction, can be controlled by a DNA leader that is attached to the pseudoknot at the 5' or 3' ends. The different nanopore conductance between DNA and RNA translocation serves as a marker for the position and structure of the unfolding RNA in the pore. With this design, we provided evidence that the pseudoknot unfolding is a two-step, multistate, metal ion-regulated process depending on the pulling direction. Most notably, unfolding in both directions is rate-limited by the unzipping of the first helix domain (first step), which is Helix-1 in the 5' → 3' direction and Helix-2 in the 3' → 5' direction, suggesting that the initial unfolding step in either pulling direction needs to overcome an energy barrier contributed by the noncanonical triplex base-pairs and coaxial stacking interactions for the tertiary structure stabilization. These findings provide new insights into RNA vectorial unfolding mechanisms, which play an important role in biological functions including frameshifting.

Detecting riboSNitches with RNA folding algorithms: a genome-wide benchmark

Ribonucleic acid (RNA) secondary structure prediction continues to be a significant challenge, in particular when attempting to model sequences with less rigidly defined structures, such as messenger and non-coding RNAs. Crucial to interpreting RNA structures as they pertain to individual phenotypes is the ability to detect RNAs with large structural disparities caused by a single nucleotide variant (SNV) or riboSNitches. A recently published human genome-wide parallel analysis of RNA structure (PARS) study identified a large number of riboSNitches as well as non-riboSNitches, providing an unprecedented set of RNA sequences against which to benchmark structure prediction algorithms. Here we evaluate 11 different RNA folding algorithms’ riboSNitch prediction performance on these data. We find that recent algorithms designed specifically to predict the effects of SNVs on RNA structure, in particular remuRNA, RNAsnp and SNPfold, perform best on the most rigorously validated subsets of the benchmark data. In addition, our benchmark indicates that general structure prediction algorithms (e.g. RNAfold and RNAstructure) have overall better performance if base pairing probabilities are considered rather than minimum free energy calculations. Although overall aggregate algorithmic performance on the full set of riboSNitches is relatively low, significant improvement is possible if the highest confidence predictions are evaluated independently.

RNA folding: structure prediction, folding kinetics and ion electrostatics

Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

Understanding the role of three-dimensional topology in determining the folding intermediates of group I introns

Many RNA molecules exert their biological function only after folding to unique three-dimensional structures. For long, noncoding RNA molecules, the complexity of finding the native topology can be a major impediment to correct folding to the biologically active structure. An RNA molecule may fold to a near-native structure but not be able to continue to the correct structure due to a topological barrier such as crossed strands or incorrectly stacked helices. Achieving the native conformation thus requires unfolding and refolding, resulting in a long-lived intermediate. We investigate the role of topology in the folding of two phylogenetically related catalytic group I introns, the Twort and Azoarcus group I ribozymes. The kinetic models describing the Mg(2+)-mediated folding of these ribozymes were previously determined by time-resolved hydroxyl (∙OH) radical footprinting. Two intermediates formed by parallel intermediates were resolved for each RNA. These data and analytical ultracentrifugation compaction analyses are used herein to constrain coarse-grained models of these folding intermediates as we investigate the role of nonnative topology in dictating the lifetime of the intermediates. Starting from an ensemble of unfolded conformations, we folded the RNA molecules by progressively adding native constraints to subdomains of the RNA defined by the ∙OH time-progress curves to simulate folding through the different kinetic pathways. We find that nonnative topologies (arrangement of helices) occur frequently in the folding simulations despite using only native constraints to drive the reaction, and that the initial conformation, rather than the folding pathway, is the major determinant of whether the RNA adopts nonnative topology during folding. From these analyses we conclude that biases in the initial conformation likely determine the relative flux through parallel RNA folding pathways.

Toward a molecular understanding of RNA remodeling by DEAD-box proteins

DEAD-box proteins are superfamily 2 helicases that function in all aspects of RNA metabolism. They employ ATP binding and hydrolysis to generate tight, yet regulated RNA binding, which is used to unwind short RNA helices non-processively and promote structural transitions of RNA and RNA-protein substrates. In the last few years, substantial progress has been made toward a detailed, quantitative understanding of the structural and biochemical properties of DEAD-box proteins. Concurrently, progress has been made toward a physical understanding of the RNA rearrangements and folding steps that are accelerated by DEAD-box proteins in model systems. Here, we review the recent progress on both of these fronts, focusing on the mitochondrial DEAD-box proteins Mss116 and CYT-19 and their mechanisms in promoting the splicing of group I and group II introns.

Cotranscriptional folding kinetics of ribonucleic acid secondary structures

We develop a systematic helix-based computational method to predict RNA folding kinetics during transcription. In our method, the transcription is modeled as stepwise process, where each step is the transcription of a nucleotide. For each step, the kinetics algorithm predicts the population kinetics, transition pathways, folding intermediates, and the transcriptional folding products. The folding pathways, rate constants, and the conformational populations for cotranscription folding show contrastingly different features than the refolding kinetics for a fully transcribed chain. The competition between the transcription speed and rate constants for the transitions between the different nascent structures determines the RNA folding pathway and the end product of folding. For example, fast transcription favors the formation of branch-like structures than rod-like structures and chain elongation in the folding process may reduce the probability of the formation of misfolded structures. Furthermore, good theory-experiment agreements suggest that our method may provide a reliable tool for quantitative prediction for cotranscriptional RNA folding, including the kinetics for the population distribution for the whole conformational ensemble.

Fast folding of RNA pseudoknots initiated by laser temperature-jump

RNA pseudoknots are examples of minimal structural motifs in RNA with tertiary interactions that stabilize the structures of many ribozymes. They also play an essential role in a variety of biological functions that are modulated by their structure, stability, and dynamics. Therefore, understanding the global principles that determine the thermodynamics and folding pathways of RNA pseudoknots is an important problem in biology, both for elucidating the folding mechanisms of larger ribozymes as well as addressing issues of possible kinetic control of the biological functions of pseudoknots. We report on the folding/unfolding kinetics of a hairpin-type pseudoknot obtained with microsecond time-resolution in response to a laser temperature-jump perturbation. The kinetics are monitored using UV absorbance as well as fluorescence of extrinsically attached labels as spectroscopic probes of the transiently populated RNA conformations. We measure folding times of 1-6 ms at 37 °C, which are at least 100-fold faster than previous observations of very slow folding pseudoknots that were trapped in misfolded conformations. The measured relaxation times are remarkably similar to predictions of a computational study by Thirumalai and co-workers (Cho, S. S.; Pincus, D.L.; Thirumalai, D. Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 17349-17354). Thus, these studies provide the first observation of a fast-folding pseudoknot and present a benchmark against which computational models can be refined.

Roles of DEAD-box proteins in RNA and RNP Folding

RNAs and RNA-protein complexes (RNPs) traverse rugged energy landscapes as they fold to their native structures, and many continue to undergo conformational rearrangements as they function. Due to the inherent stability of local RNA structure, proteins are required to assist with RNA conformational transitions during initial folding and in exchange between functional structures. DEAD-box proteins are superfamily 2 RNA helicases that are ubiquitously involved in RNA-mediated processes. Some of these proteins use an ATP-dependent cycle of conformational changes to disrupt RNA structure nonprocessively, accelerating structural transitions of RNAs and RNPs in a manner that bears a strong resemblance to the activities of certain groups of protein chaperones. This review summarizes recent work using model substrates and tractable self-splicing intron RNAs, which has given new insights into how DEAD-box proteins promote RNA folding steps and conformational transitions, and it summarizes recent progress in identifying sites and mechanisms of DEAD-box protein activity within more complex cellular targets.

TRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structures

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment.

Many non-coding genes exert their function via an RNA structure which starts emerging while the RNA sequence is being transcribed from the genome. The resulting folding pathway is known to depend on a variety of features such as the transcription speed, the concentration of various ions and the binding of proteins and other molecules. Not all of these influences can be adequately captured by the existing computational methods which try to replicate what happens in vivo. So far, it has been challenging to experimentally investigate co-transcriptional folding pathways in vivo and only little data from in vitro experiments exists. In order to investigate if functionally similar RNA sequences from different organisms fold in a similar way, we have developed a new computational method, called Transat, which does not require the detailed computational modeling of the cellular environment. We show in a comprehensive analysis that our method is capable of detecting known structural features and provide evidence that structural features of the in vivo folding pathways have been conserved for several biologically interesting classes of RNA sequences.