The interplay of long noncoding RNAs and hepatitis B virus.

Hepatitis B Virus (HBV) infections remain a major global health burden with an estimated 296 million people living with a chronic infection and 884,000 HBV-related deaths annually. Notably, patients with a chronic hepatitis B (CHB) infection are at a 30-fold greater risk of developing hepatocellular carcinoma (HCC), the most common type of primary liver cancer, which is the 3rd deadliest cancer worldwide. Several groups have assessed HBV-related aberrant expression of host-cell long noncoding RNAs (lncRNAs) and how altered expression of specific lncRNAs affects HBV replication and progression to associated disease states. Given the challenges in establishing effective HBV models and analyzing transcriptomic data, this review focuses on lncRNA expression data primarily collected from clinical patient samples and primary human hepatocytes, with the subsequent mechanism of action analysis in cell lines or other model systems. Ultimately, understanding HBV-induced lncRNA-expression dysregulation could lead to new treatments and biomarkers for HBV infection and its associated diseases.

Purification and Structural Characterization of the Long Noncoding RNAs.

Long noncoding RNAs (lncRNAs) are now accepted as key players in diverse cellular functions, yet the structure-function relationships of these novel RNAs remain mostly unknown. Homogenous purification of lncRNAs is a necessary first-step for downstream structural studies. The large size of lncRNAs (often more than 1 kb) presents many unique challenges during the purification process. Here, we detail the purification of lncRNAs, including strategies to identify proper folding conditions of the target lncRNA. Next, we discuss two recently developed RNA structure probing techniques, SHAPE-MaP (SHAPE probing followed by mutational profiling) and DMS-MaP (DMS probing followed by mutational profiling). These techniques couple traditional RNA chemical probing methods with next-generation sequencing and allow high-throughput determination of RNA structures. Using the datasets resulting from these orthogonal probing experiments, we lay out the steps to determine and validate the secondary structure of the target lncRNA. Overall, this chapter details an adaptable protocol that can lead to a better understanding of the structure-function relationships of lncRNAs.

Xist attenuates acute inflammatory response by female cells.

Biological sex influences inflammatory response, as there is a greater incidence of acute inflammation in men and chronic inflammation in women. Here, we report that acute inflammation is attenuated by X-inactive specific transcript (Xist), a female cell-specific nuclear long noncoding RNA crucial for X-chromosome inactivation. Lipopolysaccharide-mediated acute inflammation increased Xist levels in the cytoplasm of female mouse J774A.1 macrophages and human AML193 monocytes. In both cell types, cytoplasmic Xist colocalizes with the p65 subunit of NF-κB. This interaction was associated with reduced NF-κB nuclear migration, suggesting a novel mechanism to suppress acute inflammation. Further supporting this hypothesis, expression of 5' XIST in male cells significantly reduced IL-6 and NF-κB activity. Adoptive transfer of male splenocytes expressing Xist reduced acute paw swelling in male mice indicating that Xist can have a protective anti-inflammatory effect. These findings show that XIST has functions beyond X chromosome inactivation and suggest that XIST can contribute to sex-specific differences underlying inflammatory response by attenuating acute inflammation in women.

Replication protein A binds RNA and promotes R-loop formation.

Replication protein A (RPA), a major eukaryotic ssDNA-binding protein, is essential for all metabolic processes that involve ssDNA, including DNA replication, repair, and damage signaling. To perform its functions, RPA binds ssDNA tightly. In contrast, it was presumed that RPA binds RNA weakly. However, recent data suggest that RPA may play a role in RNA metabolism. RPA stimulates RNA-templated DNA repair in vitro and associates in vivo with R-loops, the three-stranded structures consisting of an RNA-DNA hybrid and the displaced ssDNA strand. R-loops are common in the genomes of pro- and eukaryotes, including humans, and may play an important role in transcription-coupled homologous recombination and DNA replication restart. However, the mechanism of R-loop formation remains unknown. Here, we investigated the RNA-binding properties of human RPA and its possible role in R-loop formation. Using gel-retardation and RNA/DNA competition assays, we found that RPA binds RNA with an unexpectedly high affinity (KD ≈ 100 pm). Furthermore, RPA, by forming a complex with RNA, can promote R-loop formation with homologous dsDNA. In reconstitution experiments, we showed that human DNA polymerases can utilize RPA-generated R-loops for initiation of DNA synthesis, mimicking the process of replication restart in vivo These results demonstrate that RPA binds RNA with high affinity, supporting the role of this protein in RNA metabolism and suggesting a mechanism of genome maintenance that depends on RPA-mediated DNA replication restart.

Visualizing group II intron dynamics between the first and second steps of splicing.

Group II introns are ubiquitous self-splicing ribozymes and retrotransposable elements evolutionarily and chemically related to the eukaryotic spliceosome, with potential applications as gene-editing tools. Recent biochemical and structural data have captured the intron in multiple conformations at different stages of catalysis. Here, we employ enzymatic assays, X-ray crystallography, and molecular simulations to resolve the spatiotemporal location and function of conformational changes occurring between the first and the second step of splicing. We show that the first residue of the highly-conserved catalytic triad is protonated upon 5'-splice-site scission, promoting a reversible structural rearrangement of the active site (toggling). Protonation and active site dynamics induced by the first step of splicing facilitate the progression to the second step. Our insights into the mechanism of group II intron splicing parallels functional data on the spliceosome, thus reinforcing the notion that these evolutionarily-related molecular machines share the same enzymatic strategy.

Identifying Structural Domains and Conserved Regions in the Long Non-Coding RNA lncTCF7.

Long non-coding RNA (lncRNA) biology is a rapidly growing area of study. Thousands of lncRNAs are implicated as key players in cellular pathways and cancer biology. However, the structure-function relationships of these novel biomolecules are not well understood. Recent structural studies suggest that lncRNAs contain modular structural domains, which play a crucial role in their function. Here, we hypothesized that such structural domains exist in lncTCF7, a conserved lncRNA implicated in the development and progression of several cancers. To understand the structure-function relationship of lncTCF7, we characterized its secondary structure using chemical probing methods. Our model revealed structural domains and conserved regions in lncTCF7. One of the modular domains identified here coincides with a known protein-interacting domain. The model reported herein is, to our knowledge, the first structural model of lncTCF7 and thus will serve to direct future studies that will provide fundamental insights into the function of this lncRNA.

Phylogenetic Analysis with Improved Parameters Reveals Conservation in lncRNA Structures.

The existence of evolutionary conservation in base pairing is strong evidence for functional elements of RNA structure, although available tools for rigorous identification of structural conservation are limited. R-scape is a recently developed program for statistical prediction of pairwise covariation from sequence alignments, but it initially showed limited utility on long RNAs, especially those of eukaryotic origin. Here we show that R-scape can be adapted for a more powerful analysis of structure conservation in long RNA molecules, including mammalian lncRNAs.

Visualizing the secondary and tertiary architectural domains of lncRNA RepA.

Long noncoding RNAs (lncRNAs) are important for gene expression, but little is known about their structures. RepA is a 1.6-kb mouse lncRNA comprising the same sequence as the 5' region of Xist, including A and F repeats. It has been proposed to facilitate the initiation and spread of X-chromosome inactivation, although its exact role is poorly understood. To gain insight into the molecular mechanism of RepA and Xist, we determined a complete phylogenetically validated secondary-structural map of RepA through SHAPE and DMS chemical probing of a homogeneously folded RNA in vitro. We combined UV-cross-linking experiments with RNA modeling methods to produce a three-dimensional model of RepA functional domains demonstrating that tertiary architecture exists within lncRNA molecules and occurs within specific functional modules. This work provides a foundation for understanding of the evolution and functional properties of RepA and Xist and offers a framework for exploring architectural features of other lncRNAs.

Progress and Current Challenges in Modeling Large RNAs.

Recent breakthroughs in next-generation sequencing technologies have led to the discovery of several classes of non-coding RNAs (ncRNAs). It is now apparent that RNA molecules are not only just carriers of genetic information but also key players in many cellular processes. While there has been a rapid increase in the number of ncRNA sequences deposited in various databases over the past decade, the biological functions of these ncRNAs are largely not well understood. Similar to proteins, RNA molecules carry out a function by forming specific three-dimensional structures. Understanding the function of a particular RNA therefore requires a detailed knowledge of its structure. However, determining experimental structures of RNA is extremely challenging. In fact, RNA-only structures represent just 1% of the total structures deposited in the PDB. Thus, computational methods that predict three-dimensional RNA structures are in high demand. Computational models can provide valuable insights into structure-function relationships in ncRNAs and can aid in the development of functional hypotheses and experimental designs. In recent years, a set of diverse RNA structure prediction tools have become available, which differ in computational time, input data and accuracy. This review discusses the recent progress and challenges in RNA structure prediction methods.

Native Purification and Analysis of Long RNAs.

The purification and analysis of long noncoding RNAs (lncRNAs) in vitro is a challenge, particularly if one wants to preserve elements of functional structure. Here, we describe a method for purifying lncRNAs that preserves the cotranscriptionally derived structure. The protocol avoids the misfolding that can occur during denaturation-renaturation protocols, thus facilitating the folding of long RNAs to a native-like state. This method is simple and does not require addition of tags to the RNA or the use of affinity columns. LncRNAs purified using this type of native purification protocol are amenable to biochemical and biophysical analysis. Here, we describe how to study lncRNA global compaction in the presence of divalent ions at equilibrium using sedimentation velocity analytical ultracentrifugation and analytical size-exclusion chromatography as well as how to use these uniform RNA species to determine robust lncRNA secondary structure maps by chemical probing techniques like selective 2'-hydroxyl acylation analyzed by primer extension and dimethyl sulfate probing.

HOTAIR forms an intricate and modular secondary structure.

Long noncoding RNAs (lncRNAs) have recently emerged as key players in fundamental cellular processes and diseases, but their functions are poorly understood. HOTAIR is a 2,148-nt-long lncRNA molecule involved in physiological epidermal development and in pathogenic cancer progression, where it has been demonstrated to repress tumor and metastasis suppressor genes. To gain insights into the molecular mechanisms of HOTAIR, we purified it in a stable and homogenous form in vitro, and we determined its functional secondary structure through chemical probing and phylogenetic analysis. The HOTAIR structure reveals a degree of structural organization comparable to well-folded RNAs, like the group II intron, rRNA, or lncRNA steroid receptor activator. It is composed of four independently folding modules, two of which correspond to predicted protein-binding domains. Secondary structure elements that surround protein-binding motifs are evolutionarily conserved. Our work serves as a guide for "navigating" through the lncRNA HOTAIR and ultimately for understanding its function.

Prediction of distal residue participation in enzyme catalysis.

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features. Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for Escherichia coli alkaline phosphatase (AP). The multilayer active sites of P. putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL log ZP scores, as is the single-layer active site of P. putida ketosteroid isomerase. The log ZP score cutoff utilized here results in over-prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for P. putida mandelate racemase and for human carbonic anhydrase II, the POOL log ZP scores properly predict the previously reported participation of distal residues.

Visualizing the ai5γ group IIB intron.

It has become apparent that much of cellular metabolism is controlled by large well-folded noncoding RNA molecules. In addition to crystallographic approaches, computational methods are needed for visualizing the 3D structure of large RNAs. Here, we modeled the molecular structure of the ai5γ group IIB intron from yeast using the crystal structure of a bacterial group IIC homolog. This was accomplished by adapting strategies for homology and de novo modeling, and creating a new computational tool for RNA refinement. The resulting model was validated experimentally using a combination of structure-guided mutagenesis and RNA structure probing. The model provides major insights into the mechanism and regulation of splicing, such as the position of the branch-site before and after the second step of splicing, and the location of subdomains that control target specificity, underscoring the feasibility of modeling large functional RNA molecules.

Solving nucleic acid structures by molecular replacement: examples from group II intron studies.

Structured RNA molecules are key players in ensuring cellular viability. It is now emerging that, like proteins, the functions of many nucleic acids are dictated by their tertiary folds. At the same time, the number of known crystal structures of nucleic acids is also increasing rapidly. In this context, molecular replacement will become an increasingly useful technique for phasing nucleic acid crystallographic data in the near future. Here, strategies to select, create and refine molecular-replacement search models for nucleic acids are discussed. Using examples taken primarily from research on group II introns, it is shown that nucleic acids are amenable to different and potentially more flexible and sophisticated molecular-replacement searches than proteins. These observations specifically aim to encourage future crystallographic studies on the newly discovered repertoire of noncoding transcripts.

Now on display: a gallery of group II intron structures at different stages of catalysis.

Group II introns are mobile genetic elements that self-splice and retrotranspose into DNA and RNA. They are considered evolutionary ancestors of the spliceosome, the ribonucleoprotein complex essential for pre-mRNA processing in higher eukaryotes. Over a 20-year period, group II introns have been characterized first genetically, then biochemically, and finally by means of X-ray crystallography. To date, 17 crystal structures of a group II intron are available, representing five different stages of the splicing cycle. This review provides a framework for classifying and understanding these new structures in the context of the splicing cycle. Structural and functional implications for the spliceosome are also discussed.

Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs).

BACKGROUND: The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and to predict function from structure would add tremendous value to structural genomics data. We report on a new method, Structurally Aligned Local Sites of Activity (SALSA), for the prediction of biochemical function based on a local structural match at the predicted catalytic or binding site. RESULTS: Implementation of the SALSA method is described. For the structural genomics protein PY01515 (PDB ID 2aqw) from Plasmodium yoelii, it is shown that the putative annotation, Orotidine 5'-monophosphate decarboxylase (OMPDC), is most likely correct. SALSA analysis of YP_001304206.1 (PDB ID 3h3l), a putative sugar hydrolase from Parabacteroides distasonis, shows that its active site does not bear close resemblance to any previously characterized member of its superfamily, the Concanavalin A-like lectins/glucanases. It is noted that three residues in the active site of the thermophilic beta-1,4-xylanase from Nonomuraea flexuosa (PDB ID 1m4w), Y78, E87, and E176, overlap with POOL-predicted residues of similar type, Y168, D153, and E232, in YP_001304206.1. The substrate recognition regions of the two proteins are rather different, suggesting that YP_001304206.1 is a new functional type within the superfamily. A structural genomics protein from Mycobacterium avium (PDB ID 3q1t) has been reported to be an enoyl-CoA hydratase (ECH), but SALSA analysis shows a poor match between the predicted residues for the SG protein and those of known ECHs. A better local structural match is obtained with Anabaena beta-diketone hydrolase (ABDH), a known ß-diketone hydrolase from Cyanobacterium anabaena (PDB ID 2j5s). This suggests that the reported ECH function of the SG protein is incorrect and that it is more likely a ß-diketone hydrolase. CONCLUSIONS: A local site match provides a more compelling function prediction than that obtainable from a simple 3D structure match. The present method can confirm putative annotations, identify misannotation, and in some cases suggest a more probable annotation.

POOL server: machine learning application for functional site prediction in proteins.

SUMMARY: We present an automated web server for partial order optimum likelihood (POOL), a machine learning application that combines computed electrostatic and geometric information for high-performance prediction of catalytic residues from 3D structures. Input features consist of THEMATICS electrostatics data and pocket information from ConCavity. THEMATICS measures deviation from typical, sigmoidal titration behavior to identify functionally important residues and ConCavity identifies binding pockets by analyzing the surface geometry of protein structures. Both THEMATICS and ConCavity (structure only) do not require the query protein to have any sequence or structure similarity to other proteins. Hence, POOL is applicable to proteins with novel folds and engineered proteins. As an additional option for cases where sequence homologues are available, users can include evolutionary information from INTREPID for enhanced accuracy in site prediction. AVAILABILITY: The web site is free and open to all users with no login requirements at http://www.pool.neu.edu. CONTACT: m.ondrechen@neu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A tale of two isomerases: compact versus extended active sites in ketosteroid isomerase and phosphoglucose isomerase.

Understanding the catalytic efficiency and specificity of enzymes is a fundamental question of major practical and conceptual importance in biochemistry. Although progress in biochemical and structural studies has enriched our knowledge of enzymes, the role in enzyme catalysis of residues that are not nearest neighbors of the reacting substrate molecule is largely unexplored experimentally. Here computational active site predictors, THEMATICS and POOL, were employed to identify functionally important residues that are not in direct contact with the reacting substrate molecule. These predictions then guided experiments to explore the active sites of two isomerases, Pseudomonas putida ketosteroid isomerase (KSI) and human phosphoglucose isomerase (PGI), as prototypes for very different types of predicted active sites. Both KSI and PGI are members of EC 5.3 and catalyze similar reactions, but they represent significantly different degrees of remote residue participation, as predicted by THEMATICS and POOL. For KSI, a compact active site of mostly first-shell residues is predicted, but for PGI, an extended active site in which residues in the first, second, and third layers around the reacting substrate are predicted. Predicted residues that have not been previously tested experimentally were investigated by site-directed mutagenesis and kinetic analysis. In human PGI, single-point mutations of the predicted second- and third-shell residues K362, H100, E495, D511, H396, and Q388 show significant decreases in catalytic activity relative to that of the wild type. The results of these experiments demonstrate that, as predicted, remote residues are very important in PGI catalysis but make only small contributions to catalysis in KSI.

Crystal structure of a metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis: Computational prediction and experimental validation of phosphoesterase activity.

The crystal structures of an unliganded and adenosine 5'-monophosphate (AMP) bound, metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis are reported at 2.4 and 1.94 Å, respectively. Functional characterization of this enzyme was guided by computational analysis and then confirmed by experiment. The structure consists of a polymerase and histidinol phosphatase (PHP, Pfam: PF02811) domain with a second domain (residues 105-178) inserted in the middle of the PHP sequence. The insert domain functions in binding AMP, but the precise function and substrate specificity of this domain are unknown. Initial bioinformatics analyses yielded multiple potential functional leads, with most of them suggesting DNA polymerase or DNA replication activity. Phylogenetic analysis indicated a potential DNA polymerase function that was somewhat supported by global structural comparisons identifying the closest structural match to the alpha subunit of DNA polymerase III. However, several other functional predictions, including phosphoesterase, could not be excluded. Theoretical microscopic anomalous titration curve shapes, a computational method for the prediction of active sites from protein 3D structures, identified potential reactive residues in YP_910028.1. Further analysis of the predicted active site and local comparison with its closest structure matches strongly suggested phosphoesterase activity, which was confirmed experimentally. Primer extension assays on both normal and mismatched DNA show neither extension nor degradation and provide evidence that YP_910028.1 has neither DNA polymerase activity nor DNA-proofreading activity. These results suggest that many of the sequence neighbors previously annotated as having DNA polymerase activity may actually be misannotated.