In silico and in vitro analysis of the impact of single substitutions within EXO-motifs on Hsa-MiR-1246 intercellular transfer in breast cancer cell.

MiR-1246 has recently gained much attention and many studies have shown its oncogenic role in colorectal, breast, lung, and ovarian cancers. However, miR-1246 processing, stability, and mechanisms directing miR-1246 into neighbor cells remain still unclear. In this study, we aimed to determine the role of single-nucleotide substitutions within short exosome sorting motifs - so-called EXO-motifs: GGAG and GCAG present in miR-1246 sequence on its intracellular stability and extracellular transfer. We applied in silico methods such as 2D and 3D structure analysis and modeling of protein interactions. We also performed in vitro validation through the transfection of fluorescently labeled miRNA to MDA-MB-231 cells, which we analyzed by flow cytometry and fluorescent microscopy. Our results suggest that nucleotides alterations that disturbed miR-1246 EXO-motifs were able to modulate miRNA-1246 stability and its transfer level to the neighboring cells, suggesting that the molecular mechanism of RNA stability and intercellular transfer can be closely related.

RNAloops: a database of RNA multiloops.

MOTIVATION: Knowledge of the 3D structure of RNA supports discovering its functions and is crucial for designing drugs and modern therapeutic solutions. Thus, much attention is devoted to experimental determination and computational prediction targeting the global fold of RNA and its local substructures. The latter include multi-branched loops-functionally significant elements that highly affect the spatial shape of the entire molecule. Unfortunately, their computational modeling constitutes a weak point of structural bioinformatics. A remedy for this is in collecting these motifs and analyzing their features. RESULTS: RNAloops is a self-updating database that stores multi-branched loops identified in the PDB-deposited RNA structures. A description of each loop includes angular data-planar and Euler angles computed between pairs of adjacent helices to allow studying their mutual arrangement in space. The system enables search and analysis of multiloops, presents their structure details numerically and visually, and computes data statistics. AVAILABILITY AND IMPLEMENTATION: RNAloops is freely accessible at https://rnaloops.cs.put.poznan.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RNA World Modeling: A Comparison of Two Complementary Approaches.

The origin of life remains one of the major scientific questions in modern biology. Among many hypotheses aiming to explain how life on Earth started, RNA world is probably the most extensively studied. It assumes that, in the very beginning, RNA molecules served as both enzymes and as genetic information carriers. However, even if this is true, there are many questions that still need to be answered-for example, whether the population of such molecules could achieve stability and retain genetic information for many generations, which is necessary in order for evolution to start. In this paper, we try to answer this question based on the parasite-replicase model (RP model), which divides RNA molecules into enzymes (RNA replicases) capable of catalyzing replication and parasites that do not possess replicase activity but can be replicated by RNA replicases. We describe the aforementioned system using partial differential equations and, based on the analysis of the simulation, surmise general rules governing its evolution. We also compare this approach with one where the RP system is modeled and implemented using a multi-agent modeling technique. We show that approaching the description and analysis of the RP system from different perspectives (microscopic represented by MAS and macroscopic depicted by PDE) provides consistent results. Therefore, applying MAS does not lead to erroneous results and allows us to study more complex situations where many cases are concerned, which would not be possible through the PDE model.

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences.

We present an approach to discriminate SARS-CoV-2 virus types based on their RNA sequence descriptions avoiding a sequence alignment. For that purpose, sequences are preprocessed by feature extraction and the resulting feature vectors are analyzed by prototype-based classification to remain interpretable. In particular, we propose to use variants of learning vector quantization (LVQ) based on dissimilarity measures for RNA sequence data. The respective matrix LVQ provides additional knowledge about the classification decisions like discriminant feature correlations and, additionally, can be equipped with easy to realize reject options for uncertain data. Those options provide self-controlled evidence, i.e., the model refuses to make a classification decision if the model evidence for the presented data is not sufficient. This model is first trained using a GISAID dataset with given virus types detected according to the molecular differences in coronavirus populations by phylogenetic tree clustering. In a second step, we apply the trained model to another but unlabeled SARS-CoV-2 virus dataset. For these data, we can either assign a virus type to the sequences or reject atypical samples. Those rejected sequences allow to speculate about new virus types with respect to nucleotide base mutations in the viral sequences. Moreover, this rejection analysis improves model robustness. Last but not least, the presented approach has lower computational complexity compared to methods based on (multiple) sequence alignment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00521-021-06018-2.

Genome-scale de novo assembly using ALGA.

MOTIVATION: There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out. RESULTS: We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland. AVAILABILITY AND IMPLEMENTATION: ALGA is available at http://alga.put.poznan.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Virxicon: a lexicon of viral sequences.

MOTIVATION: Viruses are the most abundant biological entities and constitute a large reservoir of genetic diversity. In recent years, knowledge about them has increased significantly as a result of dynamic development in life sciences and rapid technological progress. This knowledge is scattered across various data repositories, making a comprehensive analysis of viral data difficult. RESULTS: In response to the need for gathering a comprehensive knowledge of viruses and viral sequences, we developed Virxicon, a lexicon of all experimentally acquired sequences for RNA and DNA viruses. The ability to quickly obtain data for entire viral groups, searching sequences by levels of taxonomic hierarchy-according to the Baltimore classification and ICTV taxonomy-and tracking the distribution of viral data and its growth over time are unique features of our database compared to the other tools. AVAILABILITYAND IMPLEMENTATION: Virxicon is a publicly available resource, updated weekly. It has an intuitive web interface and can be freely accessed at http://virxicon.cs.put.poznan.pl/.

Multi-agent approach to sequence structure simulation in the RNA World hypothesis.

The origins of life on Earth have been the subject of inquiry since the early days of philosophical thought and are still intensively investigated by the researchers around the world. One of the theories explaining the life emergence, that gained the most attention recently is the RNA World hypothesis, which assumes that life on Earth was sparked by replicating RNA chains. Since wet lab analysis is time-consuming, many mathematical and computational approaches have been proposed that try to explain the origins of life. Recently proposed one, based on the work by Takeuchi and Hogeweg, addresses the problem of interplay between RNA replicases and RNA parasitic species, which is crucial for understanding the first steps of prebiotic evolution. In this paper, the aforementioned model has been extended and modified by introducing RNA sequence (structure) information and mutation rate close to real one. It allowed to observe the simple evolution mechanisms, which could have led to the more complicated systems and eventually, to the formation of the first cells. The main goal of this study was to determine the conditions that allowed the spontaneous emergence and evolution of the prebiotic replicases equipped with simple functional domains within a large population. Here we show that polymerase ribozymes could have appeared randomly and then quickly started to copy themselves in order for the system to reach equilibrium. It has been shown that evolutionary selection works even in the simplest systems.

Prebiotic Soup Components Trapped in Montmorillonite Nanoclay Form New Molecules: Car-Parrinello Ab Initio Simulations.

The catalytic effects of complex minerals or meteorites are often mentioned as important factors for the origins of life. To assess the possible role of nanoconfinement within a catalyst consisting of montmorillonite (MMT) and the impact of local electric field on the formation efficiency of the simple hypothetical precursors of nucleic acid bases or amino acids, we performed ab initio Car-Parrinello molecular dynamics simulations. We prepared four condensed-phase systems corresponding to previously suggested prototypes of a primordial soup. We monitored possible chemical reactions occurring within gas-like bulk and MMT-confined four simulation boxes on a 20-ps time scale at 1 atm and 300 K, 400 K, and 600 K. Elevated temperatures did not affect the reactivity of the elementary components of the gas-like boxes considerably; however, the presence of the MMT nanoclay substantially increased the formation probability of new molecules. Approximately 20 different new compounds were found in boxes containing carbon monoxide or formaldehyde molecules. This observation and an analysis of the atom-atom radial distribution functions indicated that the presence of Ca2+ ions at the surface of the internal MMT cavities may be an important factor in the initial steps of the formation of complex molecules at the early stages of the Earth's history.

PUM1 and PUM2 exhibit different modes of regulation for SIAH1 that involve cooperativity with NANOS paralogues.

Pumilio (PUM) proteins are RNA-binding proteins that posttranscriptionally regulate gene expression in many organisms. Their PUF domain recognizes specific PUM-binding elements (PBE) in the 3' untranslated region of target mRNAs while engaging protein cofactors such as NANOS that repress the expression of target mRNAs through the recruitment of effector complexes. Although the general process whereby PUM recognizes individual mRNAs has been studied extensively, the particulars of the mechanism underlying PUM-NANOS cooperation in mRNA regulation and the functional overlap among PUM and NANOS paralogues in mammals have not been elucidated. Here, using the novel PUM1 and PUM2 mRNA target SIAH1 as a model, we show mechanistic differences between PUM1 and PUM2 and between NANOS1, 2, and 3 paralogues in the regulation of SIAH1. Specifically, unlike PUM2, PUM1 exhibited PBE-independent repression of SIAH1 3'UTR-dependent luciferase expression. Concordantly, the PUF domains of PUM1 and PUM2 showed different EMSA complex formation patterns with SIAH1 3'UTRs. Importantly, we show direct binding of NANOS3, but not NANOS2, to SIAH1 3'UTR, which did not require PBEs or the PUF domain. To the best of our knowledge, this is the first report, showing that an NANOS protein directly binds RNA. Finally, using NANOS1 and NANOS3 constructs carrying mutations identified in infertile patients, we show that these mutations disrupt repression of the SIAH1-luciferase reporter and that the central region in NANOS1 appears to contribute to the regulation of SIAH1. Our findings highlight the mechanistic versatility of the PUM/NANOS machinery in mammalian posttranscriptional regulation.

RNAvista: a webserver to assess RNA secondary structures with non-canonical base pairs.

Motivation: In the study of 3D RNA structure, information about non-canonical interactions between nucleobases is increasingly important. Specialized databases support investigation of this issue based on experimental data, and several programs can annotate non-canonical base pairs in the RNA 3D structure. However, predicting the extended RNA secondary structure which describes both canonical and non-canonical interactions remains difficult. Results: Here, we present RNAvista that allows predicting an extended RNA secondary structure from sequence or from the list enumerating canonical base pairs only. RNAvista is implemented as a publicly available webserver with user-friendly interface. It runs on all major web browsers. Availability and implementation: http://rnavista.cs.put.poznan.pl.

Detecting life signatures with RNA sequence similarity measures.

The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational 'life probe' for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means.

GRASShopPER-An algorithm for de novo assembly based on GPU alignments.

Next generation sequencers produce billions of short DNA sequences in a massively parallel manner, which causes a great computational challenge in accurately reconstructing a genome sequence de novo using these short sequences. Here, we propose the GRASShopPER assembler, which follows an approach of overlap-layout-consensus. It uses an efficient GPU implementation for the sequence alignment during the graph construction stage and a greedy hyper-heuristic algorithm at the fork detection stage. A two-part fork detection method allows us to identify repeated fragments of a genome and to reconstruct them without misassemblies. The assemblies of data sets of bacteria Candidatus Microthrix, nematode Caenorhabditis elegans, and human chromosome 14 were evaluated with the golden standard tool QUAST. In comparison with other assemblers, GRASShopPER provided contigs that covered the largest part of the genomes and, at the same time, kept good values of other metrics, e.g., NG50 and misassembly rate.

NPM1 alternative transcripts are upregulated in acute myeloid and lymphoblastic leukemia and their expression level affects patient outcome.

BACKGROUND: Expression of the NPM1 gene, encoding nucleophosmin, is upregulated in cancers. Although more than ten NPM1 transcripts are known, the reports were usually limited to one predominant transcript. In leukemia, the NPM1 expression has not been widely studied so far. In acute myeloid leukemia (AML), the mutational status of the gene seems to play a pivotal role in carcinogenesis. Therefore, the aim of the study was to quantify alternative NPM1 transcripts in two types of acute leukemia, AML and ALL (acute lymphoblastic leukemia). METHODS: Using droplet digital PCR, we analyzed the levels of three protein-coding NPM1 transcripts in 66 samples collected from AML and ALL patients and 16 control samples. Using RNA-seq, we detected 8 additional NPM1 transcripts, including non-coding splice variants with retained introns. For data analysis, Welch two sample t-test, Pearson's correlation and Kaplan-Meier analysis were applied. RESULTS: The levels of the particular NPM1 transcripts were significantly different but highly correlated with each other in both leukemia and control samples. Transcript NPM1.1, encoding the longest protein (294 aa), had the highest level of accumulation and was one of the most abundant transcripts in the cell. Comparing to NPM1.1, the levels of the NPM1.2 and NPM1.3 transcripts, encoding a 265-aa and 259-aa proteins, were 30 and 3 times lower, respectively. All three NPM1 transcripts were proportionally upregulated in both types of leukemia compared to control samples. In AML, the levels of NPM1 transcripts decreased in complete remission and increased again with relapse of the disease. Low levels of NPM1.1 and NPM1.3 were associated with better prognosis. The contribution of non-coding transcripts to the total level of NPM1 gene seemed to be marginal, except for one short 5-end transcript accumulated at high levels in AML and control cells. Aberrant proportions of particular NPM1 splice variants could be linked to abnormal expression of genes encoding alternative splicing factors. CONCLUSIONS: The levels of the studied NPM1 transcripts were different but highly correlated with each other. Their upregulation in AML and ALL, decrease after therapy and association with patient outcome suggests the involvement of elevated NPM1 expression in the acute leukemia pathogenesis.

RNApdbee 2.0: multifunctional tool for RNA structure annotation.

In the field of RNA structural biology and bioinformatics, an access to correctly annotated RNA structure is of crucial importance, especially in the secondary and 3D structure predictions. RNApdbee webserver, introduced in 2014, primarily aimed to address the problem of RNA secondary structure extraction from the PDB files. Its new version, RNApdbee 2.0, is a highly advanced multifunctional tool for RNA structure annotation, revealing the relationship between RNA secondary and 3D structure given in the PDB or PDBx/mmCIF format. The upgraded version incorporates new algorithms for recognition and classification of high-ordered pseudoknots in large RNA structures. It allows analysis of isolated base pairs impact on RNA structure. It can visualize RNA secondary structures-including that of quadruplexes-with depiction of non-canonical interactions. It also annotates motifs to ease identification of stems, loops and single-stranded fragments in the input RNA structure. RNApdbee 2.0 is implemented as a publicly available webserver with an intuitive interface and can be freely accessed at http://rnapdbee.cs.put.poznan.pl/.

Simulating the origins of life: The dual role of RNA replicases as an obstacle to evolution.

Despite years of study, it is still not clear how life emerged from inanimate matter and evolved into the complex forms that we observe today. One of the most recognized hypotheses for the origins of life, the RNA World hypothesis, assumes that life was sparked by prebiotic replicating RNA chains. In this paper, we address the problems caused by the interplay between hypothetical prebiotic RNA replicases and RNA parasitic species. We consider the coexistence of parasite RNAs and RNA replicases as well as the impact of parasites on the further evolution of replicases. For these purposes, we used multi-agent modeling techniques that allow for realistic assumptions regarding the movement and spatial interactions of modeled species. The general model used in this study is based on work by Takeuchi and Hogeweg. Our results confirm that the coexistence of parasite RNAs and replicases is possible in a spatially extended system, even if we take into consideration more realistic assumptions than Takeuchi and Hogeweg. However, we also showed that the presence of trade-off that takes into the account an RNA folding process could still pose a serious obstacle to the evolution of replication. We conclude that this might be a cause for one of the greatest transitions in life that took place early in evolution-the separation of the function between DNA templates and protein enzymes, with a central role for RNA species.

Modeling of the catalytic core of Arabidopsis thaliana Dicer-like 4 protein and its complex with double-stranded RNA.

Plant Dicer-like proteins (DCLs) belong to the Ribonuclease III (RNase III) enzyme family. They are involved in the regulation of gene expression and antiviral defense through RNA interference pathways. A model plant, Arabidopsis thaliana encodes four DCL proteins (AtDCL1-4) that produce different classes of small regulatory RNAs. Our studies focus on AtDCL4 that processes double-stranded RNAs (dsRNAs) into 21 nucleotide trans-acting small interfering RNAs. So far, little is known about the structures of plant DCLs and the complexes they form with dsRNA. In this work, we present models of the catalytic core of AtDCL4 and AtDCL4-dsRNA complex constructed by computational methods. We built a homology model of the catalytic core of AtDCL4 comprising Platform, PAZ, Connector helix and two RNase III domains. To assemble the AtDCL4-dsRNA complex two modeling approaches were used. In the first method, to establish conformations that allow building a consistent model of the complex, we used Normal Mode Analysis for both dsRNA and AtDCL4. The second strategy involved template-based approach for positioning of the PAZ domain and manual arrangement of the Connector helix. Our results suggest that the spatial orientation of the Connector helix, Platform and PAZ relative to the RNase III domains is crucial for measuring dsRNA of defined length. The modeled complexes provide information about interactions that may contribute to the relative orientations of these domains and to dsRNA binding. All these information can be helpful for understanding the mechanism of AtDCL4-mediated dsRNA recognition and binding, to produce small RNA of specific size.

Computational prediction of non-enzymatic RNA degradation patterns.

Since the beginning of the 21st century, an increasing interest in the research of ribonucleic acids has been observed in response to a surprising discovery of the role that RNA molecules play in the biological systems. It was demonstrated that they do not only take part in the protein synthesis (mRNA, rRNA, tRNA) but also are involved in the regulation of gene expression. Several classes of small regulatory RNAs have been discovered (e.g. microRNA, small interfering RNA, piwiRNA). Most of them are excised from specific double-stranded RNA precursors by enzymes that belong to the RNaseIII family (Drosha, Dicer or Dicer-like proteins). More recently, it has been shown that small regulatory RNAs are also generated as stable intermediates of RNA degradation (the so called RNA fragments originating from tRNA, snRNA, snoRNA etc.). Unfortunately, the mechanisms underlying biogenesis of the RNA fragments remain unclear. It is thought that several factors may be involved in the formation of the RNA fragments. The most important are the specific RNases, RNA-protein interactions and RNA structure. In this work, we focus on the RNA primary and secondary structures as factors influencing the RNA stability and consequently the pattern of RNA fragmentation. Earlier, we identified the major structural factors affecting non-enzymatic RNA degradation. Now, based on these data, we developed a new branch-and-cut algorithm that is able to predict the products of large RNA molecules' hydrolysis in vitro. We also present the experimental data that verify the results generated using this algorithm.

Automated RNA 3D Structure Prediction with RNAComposer.

RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure. RNAComposer method is especially suited for structural biology users. Since our initial report in 2012, both servers, freely available at http://rnacomposer.ibch.poznan.pl and http://rnacomposer.cs.put.poznan.pl have been often visited. Therefore this chapter provides guidance for using RNAComposer and discusses points that should be considered when predicting 3D RNA structure. An application example presents current scope and limitations of RNAComposer.

Structural alignment of protein descriptors - a combinatorial model.

BACKGROUND: Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. RESULTS: In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. CONCLUSIONS: All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).