Search Results (13)

Viroids represent obligate plant pathogens composed exclusively of non-protein coding small single-stranded RNAs that cause high economic losses worldwide. A field survey was carried out to assess the incidence of the peach latent mosaic viroid (PLMVd) in southeastern Kazakhstan, the region of the country where fruit trees are mainly grown. Of 246 stone fruit trees, 20 (8.13%) were infected with the PLMVd. The incidence of the PLMVd in the peach (19.23%; 15/78) was significantly higher than that in the apricot (6.76%; 5/74; p = 0.0234). Eight of the detected viroids were cloned and used for full-genome sequencing. The nucleotide sequence similarity of the selected isolates found in Kazakhstan was 83.9–100%. A phylogenetic analysis indicated three clusters for the Kazakhstani isolates of the PLMVd. Three groups of Kazakhstani viroids differed in their predicted secondary structure. During the survey, the PLMVd was detected and genetically characterized for the first time in Kazakhstan. The obtained results indicate the need to develop state control measures for the PLMVd, including regular monitoring surveys. We identified several SNPs of the PLMVd that had not been previously described. The results may be useful in optimizing diagnostic approaches for detecting stone fruit viroids and preventing their spread through propagation material. Full article

Influenza A viruses (IAVs) possess a segmented genome consisting of eight viral RNAs (vRNAs) associated with multiple copies of viral nucleoprotein (NP) and a viral polymerase complex. Despite the crucial role of RNA structure in IAV replication, the impact of NP binding on vRNA structure is not well understood. In this study, we employed SHAPE chemical probing to compare the structure of NS and M vRNAs of WSN IAV in various states: before the addition of NP, in complex with NP, and after the removal of NP. Comparison of the RNA structures before the addition of NP and after its removal reveals that NP, while introducing limited changes, remodels local structures in both vRNAs and long-range interactions in the NS vRNA, suggesting a potentially biologically relevant RNA chaperone activity. In contrast, NP significantly alters the structure of vRNAs in vRNA/NP complexes, though incorporating experimental data into RNA secondary structure prediction proved challenging. Finally, our results suggest that NP not only binds single-stranded RNA but also helices with interruptions, such as bulges or small internal loops, with a preference for G-poor and C/U-rich regions. Full article

Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) is a widely used technique for RNA structure analysis using N-methylisatoic anhydride (NMIA) treatment that has been proven to be applicable to different types of RNA templates. In this study, we performed the structural analysis of the viral satellite RNA of cucumber mosaic virus TA-Tb (satCMV TA-Tb) using the SHAPE method. In the preliminary experiment, we optimized the protocol of SHAPE method for analyzing satCMV TA-Tb by determining a suitable quantity of template RNA. This optimization effectively reduced the appearance of a large number of intense bands in the NMIA-untreated sample lane, along with a strong overall background signal that prevented the clear elucidation of the RNA structure. SHAPE analysis indicated the presence of non-structured, single-stranded flexible regions throughout satCMV TA-Tb with prominent flexible stretches located around nucleotide positions 145 to 200. The positions of these flexible regions were particularly consistent with a secondary structure of satCMV TA-Tb predicted by mfold software v.2.3, which consisted of five 5′- and 3′-proximal stem-loops and one internal large multi-branched stem-loop. Sequence alignment and secondary RNA structure prediction of other satCMV sequences that are phylogenetically the same group with satCMV TA-Tb also suggested the presence of 5′- and 3′-proximal stem-loop structures. Our data provide the structural basis for elucidating the mechanism by which satCMV TA-Tb regulates the pathogenicity and replication of its helper virus. Full article

The accurate “base pairing” in RNA molecules, which leads to the prediction of RNA secondary structures, is crucial in order to explain unknown biological operations. Recently, COVID-19, a widespread disease, has caused many deaths, affecting humanity in an unprecedented way. SARS-CoV-2, a single-stranded RNA virus, has shown the significance of analyzing these molecules and their structures. This paper aims to create a pioneering framework in the direction of predicting specific RNA structures, leveraging syntactic pattern recognition. The proposed framework, Knotify+, addresses the problem of predicting H-type pseudoknots, including bulges and internal loops, by featuring the power of context-free grammar (CFG). We combine the grammar’s advantages with maximum base pairing and minimum free energy to tackle this ambiguous task in a performant way. Specifically, our proposed methodology, Knotify+, outperforms state-of-the-art frameworks with regards to its accuracy in core stems prediction. Additionally, it performs more accurately in small sequences and presents a comparable accuracy rate in larger ones, while it requires a smaller execution time compared to well-known platforms. The Knotify+ source code and implementation details are available as a public repository on GitHub. Full article

Enterovirus-D68 (EV-D68) is a positive-sense single-stranded RNA virus within the family Picornaviridae. EV-D68 was initially considered a respiratory virus that primarily affected children. However, in 2014, EV-D68 outbreaks occurred causing the expected increase in respiratory illness cases, but also an increase in acute flaccid myelitis cases (AFM). Sequencing of 2014 outbreak isolates revealed variations in the 5′ UTR of the genome compared to the historical Fermon strain. The structure of the 5′ UTR RNA contributes to enterovirus virulence, including neurovirulence in poliovirus, and could contribute to neurovirulence in contemporary EV-D68 strains. In this study, the secondary and tertiary structures of 5′ UTR RNA from the Fermon strain and 2014 isolate KT347251.1 are analyzed and compared. Secondary structures were determined using SHAPE-MaP and TurboFold II and tertiary structures were predicted using 3dRNAv2.0. Comparison of RNA structures between the EV-D68 strains shows significant remodeling at the secondary and tertiary levels. Notable secondary structure changes occurred in domains II, IV and V. Shifts in the secondary structure changed the tertiary structure of the individual domains and the orientation of the domains. Our comparative structural models for EV-D68 5′ UTR RNA highlight regions of the molecule that could be targeted for treatment of neurotropic enteroviruses. Full article

Introns are usually non-coding sequences interrupting open reading frames in pre-mRNAs [D1,2]. Stwintrons are nested spliceosomal introns, where an internal intron splits a second donor sequence into two consecutive splicing reactions leading to mature mRNA. In Hypoxylon sp. CO27-5, 36 highly sequence-similar [D1,2] stwintrons are extant (sister stwintrons). An additional 81 [D1,2] sequence-unrelated stwintrons are described here. Most of them are located at conserved gene positions rooted deep in the Hypoxylaceae. Absence of exonic sequence bias at the exon–stwintron junctions and a very similar phase distribution were noted for both groups. The presence of an underlying sequence symmetry in all 117 stwintrons was striking. This symmetry, more pronounced near the termini of most of the full-length sister stwintrons, may lead to a secondary structure that brings into close proximity the most distal splice sites, the donor of the internal and the acceptor of the external intron. The Hypoxylon stwintrons were overwhelmingly excised by consecutive splicing reactions precisely removing the whole intervening sequence, whereas one excision involving the distal splice sites led to a frameshift. Alternative (mis)splicing took place for both sister and uniquely occurring stwintrons. The extraordinary symmetry of the sister stwintrons thus seems dispensable for the infrequent, direct utilisation of the distal splice sites. Full article

Obtaining valuable clues for noncoding RNA (ribonucleic acid) subsequences remains a significant challenge, acknowledging that most of the human genome transcribes into noncoding RNA parts related to unknown biological operations. Capturing these clues relies on accurate “base pairing” prediction, also known as “RNA secondary structure prediction”. As COVID-19 is considered a severe global threat, the single-stranded SARS-CoV-2 virus reveals the importance of establishing an efficient RNA analysis toolkit. This work aimed to contribute to that by introducing a novel system committed to predicting RNA secondary structure patterns (i.e., RNA’s pseudoknots) that leverage syntactic pattern-recognition strategies. Having focused on the pseudoknot predictions, we formalized the secondary structure prediction of the RNA to be primarily a parsing and, secondly, an optimization problem. The proposed methodology addresses the problem of predicting pseudoknots of the first order (H-type). We introduce a context-free grammar (CFG) that affords enough expression power to recognize potential pseudoknot pattern. In addition, an alternative methodology of detecting possible pseudoknots is also implemented as well, using a brute-force algorithm. Any input sequence may highlight multiple potential folding patterns requiring a strict methodology to determine the single biologically realistic one. We conscripted a novel heuristic over the widely accepted notion of free-energy minimization to tackle such ambiguity in a performant way by utilizing each pattern’s context to unveil the most prominent pseudoknot pattern. The overall process features polynomial-time complexity, while its parallel implementation enhances the end performance, as proportional to the deployed hardware. The proposed methodology does succeed in predicting the core stems of any RNA pseudoknot of the test dataset by performing a 76.4% recall ratio. The methodology achieved a F1-score equal to 0.774 and MCC equal 0.543 in discovering all the stems of an RNA sequence, outperforming the particular task. Measurements were taken using a dataset of 262 RNA sequences establishing a performance speed of 1.31, 3.45, and 7.76 compared to three well-known platforms. The implementation source code is publicly available under knotify github repo. Full article

Synthetic biologists have applied biomolecular engineering approaches toward the goal of novel biological devices and have shown progress in diverse areas of medicine and biotechnology. Especially promising is the application of synthetic biological devices towards a novel class of molecular diagnostics. As an example, a de-novo-designed riboregulator called toehold switch, with its programmability and compatibility with field-deployable devices showed promising in vitro applications for viral RNA detection such as Zika and Corona viruses. However, the in vivo application of high-performance RNA sensors remains challenging due to the secondary structure of long mRNA species. Here, we introduced ‘Helper RNAs’ that can enhance the functionality of toehold switch sensors by mitigating the effect of secondary structures around a target site. By employing the helper RNAs, previously reported mCherry mRNA sensor showed improved fold-changes in vivo. To further generalize the Helper RNA approaches, we employed automatic design pipeline for toehold sensors that target the essential genes within the pks island, an important target of biomedical research in connection with colorectal cancer. The toehold switch sensors showed fold-changes upon the expression of full-length mRNAs that apparently depended sensitively on the identity of the gene as well as the predicted local structure within the target region of the mRNA. Still, the helper RNAs could improve the performance of toehold switch sensors in many instances, with up to 10-fold improvement over no helper cases. These results suggest that the helper RNA approaches can further assist the design of functional RNA devices in vivo with the aid of the streamlined automatic design software developed here. Further, our solutions for screening and stabilizing single-stranded region of mRNA may find use in other in vivo mRNA-sensing applications such as cas13 crRNA design, transcriptome engineering, and trans-cleaving ribozymes. Full article

The application of aptamers in biomedicine is emerging as an essential technology in the field of cancer research. As small single-stranded DNA or RNA ligands with high specificity and low immunogenicity for their targets, aptamers provide many advantages in cancer therapeutics over protein-based molecules, such as antibodies. Vimentin is an intermediate filament protein that is overexpressed in endothelial cells of cancerous tissue. High expression levels of vimentin have been associated with increased capacity for migration and invasion of the tumor cells. We have selected and identified thioated aptamers with high specificity for vimentin using human ovarian cancer tissues. Tentative binding motifs were chosen for two vimentin aptamers based on predicted secondary structures. Each of these shorter, tentative binding motifs was synthesized, purified, and characterized via cell binding assays. Two vimentin binding motifs with high fidelity binding were selected and further characterized via cell and tissue binding assays, as well as flow cytometric analysis. The equilibrium binding constants of these small thioated aptamer constructs were also determined. Future applications for the vimentin binding aptamer motifs include conjugation of the aptamers to synthetic dyes for use in targeted imaging and therapy, and ultimately more detailed and precise monitoring of treatment response and tumor progression in ovarian pathology. Full article

Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization. Full article

Influenza is an important research subject around the world because of its threat to humanity. Influenza A virus (IAV) causes seasonal epidemics and sporadic, but dangerous pandemics. A rapid antigen changes and recombination of the viral RNA genome contribute to the reduced effectiveness of vaccination and anti-influenza drugs. Hence, there is a necessity to develop new antiviral drugs and strategies to limit the influenza spread. IAV is a single-stranded negative sense RNA virus with a genome (viral RNA—vRNA) consisting of eight segments. Segments within influenza virion are assembled into viral ribonucleoprotein (vRNP) complexes that are independent transcription-replication units. Each step in the influenza life cycle is regulated by the RNA and is dependent on its interplay and dynamics. Therefore, viral RNA can be a proper target to design novel therapeutics. Here, we briefly described examples of anti-influenza strategies based on the antisense oligonucleotide (ASO), small interfering RNA (siRNA), microRNA (miRNA) and catalytic nucleic acids. In particular we focused on the vRNA structure-function relationship as well as presented the advantages of using secondary structure information in predicting therapeutic targets and the potential future of this field. Full article

Long noncoding RNAs (lncRNAs) play a key role in many cellular processes including chromatin regulation. To modify chromatin, lncRNAs often interact with DNA in a sequence-specific manner forming RNA:DNA triple helices. Computational tools for triple helix search do not always provide genome-wide predictions of sufficient quality. Here, we used four human lncRNAs (MEG3, DACOR1, TERC and HOTAIR) and their experimentally determined binding regions for evaluating triplex parameters that provide the highest prediction accuracy. Additionally, we combined triplex prediction with the lncRNA secondary structure and demonstrated that considering only single-stranded fragments of lncRNA can further improve DNA-RNA triplexes prediction. Full article

Viroids are small pathogenic circular single-stranded RNAs, present in two complementary sequences, named plus and minus, in infected plant cells. A high degree of complementarities between different regions of the RNAs allows them to adopt complex structures. Since viroids are naked non-coding RNAs, interactions with host factors appear to be closely related to their structural and catalytic characteristics. Avocado sunblotch viroid (ASBVd), a member of the family Avsunviroidae, replicates via a symmetric RNA-dependant rolling-circle process, involving self-cleavage via hammerhead ribozymes. Consequently, it is assumed that ASBVd plus and minus strands adopt similar structures. Moreover, by computer analyses, a quasi-rod-like secondary structure has been predicted. Nevertheless, secondary and tertiary structures of both polarities of ASBVd remain unsolved. In this study, we analyzed the characteristic of each strand of ASBVd through biophysical analyses. We report that ASBVd transcripts of plus and minus polarities exhibit differences in electrophoretic mobility under native conditions and in thermal denaturation profiles. Subsequently, the secondary structures of plus and minus polarities of ASBVd were probed using the RNA-selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method. The models obtained show that both polarities fold into different structures. Moreover, our results suggest the existence of a kissing-loop interaction within the minus strand that may play a role in in vivo viroid life cycle. Full article