Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package

In silico investigation of riboswitches in fungi: structural and dynamical insights into TPP riboswitches in Aspergillus oryzae

Riboswitches are RNA sensors affecting post-transcriptional processes through their ability to bind to small molecules. Thiamine pyrophosphate (TPP) riboswitch plays a crucial role in regulating genes involved in synthesizing or transporting thiamine and phosphorylated derivatives in bacteria, archaea, plants, and fungi. Although TPP riboswitch is reasonably well known in bacteria, there is a gap in the knowledge of the fungal TPP riboswitches structure and dynamics, involving mainly sequence variation and TPP interaction with the aptamers. On the other hand, the increase of fungal infections and antifungal resistance raises the need for new antifungal therapies. In this work, we used computational approaches to build three-dimensional models for the three TPP riboswitches identified in Aspergillus oryzae, in which we studied their structure, dynamics, and binding free energy change (ΔG_bind) with TPP. Interaction patterns between the TPP and the surrounding nucleotides were conserved among the three models, evidencing high structural conservation. Furthermore, we show that the TPP riboswitch from the A. oryzae NMT1 gene behaves similarly to the E. coli thiA gene concerning the ΔG_bind. In contrast, mutations in the fungal TPP riboswitches from THI4 and the nucleoside transporter genes led to structural differences, affecting the binding-site volume, hydrogen bond occupancy, and ΔG_bind. Besides, the number of water molecules surrounding TPP influenced the ΔG_bind considerably. Notably, our ΔG_bind estimation agreed with previous experimental data, reinforcing the relationship between sequence conservation and TPP interaction.

Analyzing Secondary Structure Patterns in DNA Aptamers Identified via CompELS

In contrast to sophisticated high-throughput sequencing tools for genomic DNA, analytical tools for comparing secondary structure features between multiple single-stranded DNA sequences are less developed. For single-stranded nucleic acid ligands called aptamers, secondary structure is widely thought to play a pivotal role in driving recognition-based binding activity between an aptamer sequence and its specific target. Here, we employ a competition-based aptamer screening platform called CompELS to identify DNA aptamers for a colloidal target. We then analyze predicted secondary structures of the aptamers and a large population of random sequences to identify sequence features and patterns. Our secondary structure analysis identifies patterns ranging from position-dependent score matrixes of individual structural elements to position-independent consensus domains resulting from global alignment.

RMalign: an RNA structural alignment tool based on a novel scoring function RMscore

Background

RNA-protein 3D complex structure prediction is still challenging. Recently, a template-based approach PRIME is proposed in our team to build RNA-protein 3D complex structure models with a higher success rate than computational docking software. However, scoring function of RNA alignment algorithm SARA in PRIME is size-dependent, which limits its ability to detect templates in some cases.

Results

Herein, we developed a novel RNA 3D structural alignment approach RMalign, which is based on a size-independent scoring function RMscore. The parameter in RMscore is then optimized in randomly selected RNA pairs and phase transition points (from dissimilar to similar) are determined in another randomly selected RNA pairs. In tRNA benchmarking, the precision of RMscore is higher than that of SARAscore (0.88 and 0.78, respectively) with phase transition points. In balance-FSCOR benchmarking, RMalign performed as good as ESA-RNA with a non-normalized score measuring RNA structural similarity. In balance-x-FSCOR benchmarking, RMalign achieves much better than a state-of-the-art RNA 3D structural alignment approach SARA due to a size-independent scoring function. Take the advantage of RMalign, we update our RNA-protein modeling approach PRIME to version 2.0. The PRIME2.0 significantly improves about 10% success rate than PRIME.

Conclusion

Based on a size-independent scoring function RMscore, a novel RNA 3D structural alignment approach RMalign is developed and integrated into PRIME2.0, which could be useful for the biological community in modeling protein-RNA interaction.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5631-3) contains supplementary material, which is available to authorized users.

Molecular characterization and functional analysis of two phospholipid hydroperoxide isoforms from Larimichthys crocea under Vibrio parahaemolyticus challenge

Glutathione peroxidases family is a key role in the antioxidant system in oxybiotic organisms for cell redox homeostasis. One of their members, phospholipid hydroperoxide glutathione peroxidase (GPx4) have unique monomeric structure and can directly react with complex lipid and membrane-bound peroxides under the presence of glutathione(GSH). In this paper, two complete GPx4 cDNAs (designated as LcGPx4a and LcGPx4b) from Larimichthys crocea are identified by rapid amplification of cDNA ends. The cDNA of LcGPx4a was consisted of a 5'-untranslated region (UTR) of 258 bp, a 3'-UTR of 330 bp, and an open reading frame (ORF) of 561 bp encoding 186 amino acid (aa) polypeptides. And the full-length sequence of LcGPx4b was 1164 bp with a 5'-UTR of 34 bp, a 3'-UTR of 551 bp and an ORF of 576 bp encoding a polypeptide of 191 aa residues with a predicted signal peptide of 15 aa. The characteristic selenocysteine insertion (SECIS) sequence was detected in the 3'UTR of the two sequences with 78 bp in length. The conserved active site of selenocysteine (Sec) encoded by TGA was also identified and formed a tetrad functional structure with glutamine, tryptophan, and asparagine in LcGPx4a and LcGPx4b. Two signature site motifs ("LRILAFPSNQFGNQEPG" and "LRILGFPCNQFGGQEPG") were both conserved in the deduced amino acid of LcGPx4a and LcGPx4b. The genomic structure analysis revealed that the two sequences both had 7 exons and 6 introns, and the Sec opal codon and SECIS element were located at the third and seventh exons, respectively. LcGPx4a and LcGPx4b both have a wide distribution in 9 tissues with various relative expression levels and a highest expression pattern in the liver. Under Vibrio parahaemolyticus challenge, their relative expression levels were altered in the liver, spleen, kidney, and head kidney but with different magnitudes and response time. LcGPx4a and LcGPx4b showed a significantly up-regulated trend in the spleen during experimental period. Above results suggested that LcGPx4a and LcGPx4b were two conserved immune molecules and might play a role in the immune response of fish with a tissue-depemdent manners.

Identification and characterization of two selenium-dependent glutathione peroxidase 1 isoforms from Larimichthys crocea

Glutathione peroxidases, a vital family of antioxidant enzymes in oxybiotic organisms, are involved in anti-pathogen immune response. In this study, two complete selenium-dependent glutathione peroxidase 1 cDNAs (designated as LcGPx1a and LcGPx1b) were obtained from the large yellow croaker Larimichthys crocea by rapid amplification of cDNA ends. The full-length sequence of LcGPx1a was 917 bp with a 5'-untranslated region (UTR) of 52 bp, a 3'-UTR of 289 bp, and an open reading frame of 576 bp encoding 191 amino acid (aa) polypeptides. The cDNA of LcGPx1b was composed of 884 bp with a 5'-UTR of 59 bp, a 3'-UTR of 258 bp, and an open reading frame of 567 bp encoding 188 aa polypeptides. The conserved selenocysteine insertion sequence was detected in the 3'-UTR of both isoforms, which can classify types I and II. Protein sequence analysis revealed that both isoforms included a selenocysteine encoded by an opal codon (TGA) and formed the functioning tetrad site with glutamine, tryptophan, and asparagine. Three conservative motifs, including one active site motif ("GKVVLIENVASLUGTT") and two signature site motifs ("LVILGVPCNQFGHQENC" and "V(A/S)WNFEKFLI"), were conserved both in sequence and location. Multiple alignments revealed that they exhibited a high level of identities with GPx1 from other organisms, especially in the abovementioned conserved amino acid sequence motifs. Tissue expression analysis indicated that LcGPx1a and LcGPx1b had a wide distribution in nine tissues with various abundances. The transcript level of LcGPx1a was not significantly different among the nine tissues, whereas that of LcGPx1b was higher in the kidney and head kidney than in the other tissues. After Vibrio parahaemolyticus stimulation, the expression levels of LcGPx1a and LcGPx1b were unanimously altered in the liver, spleen, kidney, and head kidney but with different magnitudes and response time. LcGPx1a and LcGPx1b showed distinct expression trends in the liver, where LcGPx1b was induced and LcGPx1a was depressed in response to pathogen infection. These results indicate that LcGPx1a and LcGPx1b display functional diversities and play crucial roles in mediating the immune response of fish.

SupeRNAlign: a new tool for flexible superposition of homologous RNA structures and inference of accurate structure-based sequence alignments

RNA has been found to play an ever-increasing role in a variety of biological processes. The function of most non-coding RNA molecules depends on their structure. Comparing and classifying macromolecular 3D structures is of crucial importance for structure-based function inference and it is used in the characterization of functional motifs and in structure prediction by comparative modeling. However, compared to the numerous methods for protein structure superposition, there are few tools dedicated to the superimposing of RNA 3D structures. Here, we present SupeRNAlign (v1.3.1), a new method for flexible superposition of RNA 3D structures, and SupeRNAlign-Coffee—a workflow that combines SupeRNAlign with T-Coffee for inferring structure-based sequence alignments. The methods have been benchmarked with eight other methods for RNA structural superposition and alignment. The benchmark included 151 structures from 32 RNA families (with a total of 1734 pairwise superpositions). The accuracy of superpositions was assessed by comparing structure-based sequence alignments to the reference alignments from the Rfam database. SupeRNAlign and SupeRNAlign-Coffee achieved significantly higher scores than most of the benchmarked methods: SupeRNAlign generated the most accurate sequence alignments among the structure superposition methods, and SupeRNAlign-Coffee performed best among the sequence alignment methods.

RNA Systems Biology for Cancer: From Diagnosis to Therapy

It is due to the advances in high-throughput omics data generation that RNA species have re-entered the focus of biomedical research. International collaborate efforts, like the ENCODE and GENCODE projects, have spawned thousands of previously unknown functional non-coding RNAs (ncRNAs) with various but primarily regulatory roles. Many of these are linked to the emergence and progression of human diseases. In particular, interdisciplinary studies integrating bioinformatics, systems biology, and biotechnological approaches have successfully characterized the role of ncRNAs in different human cancers. These efforts led to the identification of a new tool-kit for cancer diagnosis, monitoring, and treatment, which is now starting to enter and impact on clinical practice. This chapter is to elaborate on the state of the art in RNA systems biology, including a review and perspective on clinical applications toward an integrative RNA systems medicine approach. The focus is on the role of ncRNAs in cancer.

Multiple sequence alignment modeling: methods and applications

This review provides an overview on the development of Multiple sequence alignment (MSA) methods and their main applications. It is focused on progress made over the past decade. The three first sections review recent algorithmic developments for protein, RNA/DNA and genomic alignments. The fourth section deals with benchmarks and explores the relationship between empirical and simulated data, along with the impact on method developments. The last part of the review gives an overview on available MSA local reliability estimators and their dependence on various algorithmic properties of available methods.

Network Properties of the Ensemble of RNA Structures

We describe the first dynamic programming algorithm that computes the expected degree for the network, or graph G = (V, E) of all secondary structures of a given RNA sequence a = a₁, …, a_n. Here, the nodes V correspond to all secondary structures of a, while an edge exists between nodes s, t if the secondary structure t can be obtained from s by adding, removing or shifting a base pair. Since secondary structure kinetics programs implement the Gillespie algorithm, which simulates a random walk on the network of secondary structures, the expected network degree may provide a better understanding of kinetics of RNA folding when allowing defect diffusion, helix zippering, and related conformation transformations. We determine the correlation between expected network degree, contact order, conformational entropy, and expected number of native contacts for a benchmarking dataset of RNAs. Source code is available at http://bioinformatics.bc.edu/clotelab/RNAexpNumNbors.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

MultiSETTER: web server for multiple RNA structure comparison

Background

Understanding the architecture and function of RNA molecules requires methods for comparing and analyzing their tertiary and quaternary structures. While structural superposition of short RNAs is achievable in a reasonable time, large structures represent much bigger challenge. Therefore, we have developed a fast and accurate algorithm for RNA pairwise structure superposition called SETTER and implemented it in the SETTER web server. However, though biological relationships can be inferred by a pairwise structure alignment, key features preserved by evolution can be identified only from a multiple structure alignment. Thus, we extended the SETTER algorithm to the alignment of multiple RNA structures and developed the MultiSETTER algorithm.

Results

In this paper, we present the updated version of the SETTER web server that implements a user friendly interface to the MultiSETTER algorithm. The server accepts RNA structures either as the list of PDB IDs or as user-defined PDB files. After the superposition is computed, structures are visualized in 3D and several reports and statistics are generated.

Conclusion

To the best of our knowledge, the MultiSETTER web server is the first publicly available tool for a multiple RNA structure alignment. The MultiSETTER server offers the visual inspection of an alignment in 3D space which may reveal structural and functional relationships not captured by other multiple alignment methods based either on a sequence or on secondary structure motifs.

Alignathon: a competitive assessment of whole-genome alignment methods

Multiple sequence alignments (MSAs) are a prerequisite for a wide variety of evolutionary analyses. Published assessments and benchmark data sets for protein and, to a lesser extent, global nucleotide MSAs are available, but less effort has been made to establish benchmarks in the more general problem of whole-genome alignment (WGA). Using the same model as the successful Assemblathon competitions, we organized a competitive evaluation in which teams submitted their alignments and then assessments were performed collectively after all the submissions were received. Three data sets were used: Two were simulated and based on primate and mammalian phylogenies, and one was comprised of 20 real fly genomes. In total, 35 submissions were assessed, submitted by 10 teams using 12 different alignment pipelines. We found agreement between independent simulation-based and statistical assessments, indicating that there are substantial accuracy differences between contemporary alignment tools. We saw considerable differences in the alignment quality of differently annotated regions and found that few tools aligned the duplications analyzed. We found that many tools worked well at shorter evolutionary distances, but fewer performed competitively at longer distances. We provide all data sets, submissions, and assessment programs for further study and provide, as a resource for future benchmarking, a convenient repository of code and data for reproducing the simulation assessments.

SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments

This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available. The server can be accessed from http://tcoffee.crg.cat/apps/tcoffee/do:saracoffee.