The comparative RNA web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs

RiboVision2: A Web Server for Advanced Visualization of Ribosomal RNAs

RiboVision2 is a web server designed to visualize phylogenetic, structural, and evolutionary properties of ribosomal RNAs simultaneously at the levels of primary, secondary, and three-dimensional structure and in the context of full ribosomal complexes. RiboVision2 instantly computes and displays a broad variety of data; it has no login requirements, is open-source, free for all users, and available at https://ribovision2.chemistry.gatech.edu.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

A new reagent for in vivo structure probing of RNA G and U residues that improves RNA structure prediction alone and combined with DMS

A key to understanding the roles of RNA in regulating gene expression is knowing their structures in vivo. One way to obtain this information is through probing the structures of RNA with chemicals. To probe RNA structure directly in cells, membrane-permeable reagents that modify the Watson-Crick (WC) face of unpaired nucleotides can be used. Although dimethyl sulfate (DMS) has led to substantial insight into RNA structure, it has limited nucleotide specificity in vivo, with WC face reactivity only at adenine (A) and cytosine (C) at neutral pH. The reagent 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) was recently shown to modify the WC face of guanine (G) and uracil (U). Although useful at lower concentrations in experiments that measure chemical modifications by reverse transcription (RT) stops, at higher concentrations necessary for detection by mutational profiling (MaP), EDC treatment leads to degradation of RNA. Here, we demonstrate EDC-stimulated degradation of RNA in Gram-negative and Gram-positive bacteria. In an attempt to overcome these limitations, we developed a new carbodiimide reagent, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide methiodide (ETC), which we show specifically modifies unpaired Gs and Us in vivo without substantial degradation of RNA. We establish ETC as a probe for MaP and optimize the RT conditions and computational analysis in Escherichia coli Importantly, we demonstrate the utility of ETC as a probe for improving RNA structure prediction both alone and with DMS.

Genome-Wide Computational Prediction and Analysis of Noncoding RNAs in Oleidesulfovibrio alaskensis G20

Noncoding RNAs (ncRNAs) play key roles in the regulation of important pathways, including cellular growth, stress management, signaling, and biofilm formation. Sulfate-reducing bacteria (SRB) contribute to huge economic losses causing microbial-induced corrosion through biofilms on metal surfaces. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation. This study aimed to identify ncRNAs in the genome of a model SRB, Oleidesulfovibrio alaskensis G20 (OA G20). Three in silico approaches revealed genome-wide distribution of 37 ncRNAs excluding tRNAs in the OA G20. These ncRNAs belonged to 18 different Rfam families. This study identified riboswitches, sRNAs, RNP, and SRP. The analysis revealed that these ncRNAs could play key roles in the regulation of several pathways of biosynthesis and transport involved in biofilm formation by OA G20. Three sRNAs, Pseudomonas P10, Hammerhead type II, and sX4, which were found in OA G20, are rare and their roles have not been determined in SRB. These results suggest that applying various computational methods could enrich the results and lead to the discovery of additional novel ncRNAs, which could lead to understanding the "rules of life of OA G20" during biofilm formation.

18S rDNA sequence-structure phylogeny of the eukaryotes simultaneously inferred from sequences and their individual secondary structures

OBJECTIVE

The eukaryotic tree of life has been subject of numerous studies ever since the nineteenth century, with more supergroups and their sister relations being decoded in the last years. In this study, we reconstructed the phylogeny of eukaryotes using complete 18S rDNA sequences and their individual secondary structures simultaneously. After the sequence-structure data was encoded, it was automatically aligned and analyzed using sequence-only as well as sequence-structure approaches. We present overall neighbor-joining trees of 211 eukaryotes as well as the respective profile neighbor-joining trees, which helped to resolve the basal branching pattern. A manually chosen subset was further inspected using neighbor-joining, maximum parsimony, and maximum likelihood analyses. Additionally, the 75 and 100 percent consensus structures of the subset were predicted.

RESULTS

All sequence-structure approaches show improvements compared to the respective sequence-only approaches: the average bootstrap support per node of the sequence-structure profile neighbor-joining analyses with 90.3, was higher than the average bootstrap support of the sequence-only profile neighbor-joining analysis with 73.9. Also, the subset analyses using sequence-structure data were better supported. Furthermore, more subgroups of the supergroups were recovered as monophyletic and sister group relations were much more comparable to results as obtained by multi-marker analyses.

Highly Reactive Group I Introns Ubiquitous in Pathogenic Fungi

Systemic fungal infections are a growing public health threat, and yet viable antifungal drug targets are limited as fungi share a similar proteome with humans. However, features of RNA metabolism and the noncoding transcriptomes in fungi are distinctive. For example, fungi harbor highly structured RNA elements that humans lack, such as self-splicing introns within key housekeeping genes in the mitochondria. However, the location and function of these mitochondrial riboregulatory elements has largely eluded characterization. Here we used an RNA-structure-based bioinformatics pipeline to identify the group I introns interrupting key mitochondrial genes in medically relevant fungi, revealing their fixation within a handful of genetic hotspots and their ubiquitous presence across divergent phylogenies of fungi, including all highest priority pathogens such as Candida albicans, Candida auris, Aspergillus fumigatus and Cryptococcus neoformans. We then biochemically characterized two representative introns from C. albicans and C. auris, demonstrating their exceptionally efficient splicing catalysis relative to previously-characterized group I introns. Indeed, the C. albicans mitochondrial intron displays extremely rapid catalytic turnover, even at ambient temperatures and physiological magnesium ion concentrations. Our results unmask a significant new set of players in the RNA metabolism of pathogenic fungi, suggesting a promising new type of antifungal drug target.

The complete mitochondrial genome of Chibiraga houshuaii (Lepidoptera, Limacodidae) and its phylogenetic implications

Chibiraga is a mall East Asian genus in the family Limacodidae (slug-moths). The latter includes many agricultural pests. Mitochondrial genome analysis is an important tool for studying insect molecular identification and phylogenetics. However, there are very few mitogenome sequences available for Limacodidae species, and none for the genus Chibiraga at all. To explore the mitogenome features of Chibiraga and verify its phylogenetic position, the complete mitogenome of Chibiraga houshuaii was sequenced and annotated. The complete 15,487 bp genome encoded 37 mitochondrial genes, including 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, and a control region (CR). Most of the PCGs had typical ATN start codons and terminated with TAA or a single T residue. UUA (Leu2), AUU (Ile), UUU (Phe), AUA (Met) and AAU (Asn) were the five most frequently used codons. All tRNAs were folded into cloverleaf secondary structure, except for trnS1, which lacked the DHU arm. Phylogenetic analyses within the superfamily Zygaenoidea were performed based on multiple datasets from mitochondrial genes. The results showed that the families Phaudidae, Limacodidae and Zygaenidae were respectively recovered as monophyly; C. houshuaii was clustered in a clade with nettle type larvae in Limacodidae.

Three Biopolymers and Origin of Life Scenarios

To track down the possible roots of life, various models for the initial living system composed of different combinations of the three extant biopolymers, RNA, DNA, and proteins, are presented. The suitability of each molecular set is assessed according to its ability to emerge autonomously, sustain, and evolve continuously towards life as we know it. The analysis incorporates current biological knowledge gained from high-resolution structural data and large sequence datasets, together with experimental results concerned with RNA replication and with the activity demonstrated by standalone constructs of the ribosomal Peptidyl Transferase Center region. The scrutiny excludes the DNA-protein combination and assigns negligible likelihood to the existence of an RNA-DNA world, as well as to an RNA world that contained a replicase made of RNA. It points to the precedence of an RNA-protein system, whose model of emergence suggests specific processes whereby a coded proto-ribosome ribozyme, specifically aminoacylated proto-tRNAs and a proto-polymerase enzyme, could have autonomously emerged, cross-catalyzing the formation of each other. This molecular set constitutes a feasible starting point for a continuous evolutionary path, proceeding via natural processes from the inanimate matter towards life as we know it.

Minimization of the E. coli ribosome, aided and optimized by community science

The ribosome is a ribonucleoprotein complex found in all domains of life. Its role is to catalyze protein synthesis, the messenger RNA (mRNA)-templated formation of amide bonds between α-amino acid monomers. Amide bond formation occurs within a highly conserved region of the large ribosomal subunit known as the peptidyl transferase center (PTC). Here we describe the step-wise design and characterization of mini-PTC 1.1, a 284-nucleotide RNA that recapitulates many essential features of the Escherichia coli PTC. Mini-PTC 1.1 folds into a PTC-like structure under physiological conditions, even in the absence of r-proteins, and engages small molecule analogs of A- and P-site tRNAs. The sequence of mini-PTC 1.1 differs from the wild type E. coli ribosome at 12 nucleotides that were installed by a cohort of citizen scientists using the on-line video game Eterna. These base changes improve both the secondary structure and tertiary folding of mini-PTC 1.1 as well as its ability to bind small molecule substrate analogs. Here, the combined input from Eterna citizen-scientists and RNA structural analysis provides a robust workflow for the design of a minimal PTC that recapitulates many features of an intact ribosome.

Deciphering phylogenetic relationships of and delimiting species boundaries within the controversial ciliate genus Conchophthirus using an integrative morpho-evo approach

The phylum Ciliophora (ciliates) comprises about 2600 symbiotic and over 5500 free-living species. The inclusion of symbiotic ciliates in phylogenetic analyses often challenges traditional classification frameworks due to their morphological adaptions to the symbiotic lifestyle. Conchophthirus is such a controversial obligate endocommensal genus whose affinities to other symbiotic and free-living scuticociliates are still poorly understood. Using uni- and multivariate morphometrics as well as 2D-based molecular and phylogenetic analyses, we attempted to test for the monophyly of Conchophthirus, study the boundaries of Conchophthirus species isolated from various bivalves at mesoscale, and reveal the phylogenetic relationships of Conchophthirus to other scuticociliates. Multidimensional analyses of morphometric and cell geometric data generated the same homogenous clusters, as did phylogenetic analyses based on 144 new sequences of two mitochondrial and five nuclear molecular markers. Conchophthirus is not closely related to 'core' scuticociliates represented by the orders Pleuronematida and Philasterida, as assumed in the past using morphological data. Nuclear and mitochondrial markers consistently showed the free-living Dexiotricha and the mouthless endosymbiotic Haptophrya to be the nearest relatives of Conchophthirus. These three highly morphologically and ecologically dissimilar genera represent an orphan clade from the early radiation of scuticociliates in molecular phylogenies.

How Parameters Influence SHAPE-Directed Predictions

The structure of an RNA sequence encodes information about its biological function. Dynamic programming algorithms are often used to predict the conformation of an RNA molecule from its sequence alone, and adding experimental data as auxiliary information improves prediction accuracy. This auxiliary data is typically incorporated into the nearest neighbor thermodynamic model22 by converting the data into pseudoenergies. Here, we look at how much of the space of possible structures auxiliary data allows prediction methods to explore. We find that for a large class of RNA sequences, auxiliary data shifts the predictions significantly. Additionally, we find that predictions are highly sensitive to the parameters which define the auxiliary data pseudoenergies. In fact, the parameter space can typically be partitioned into regions where different structural predictions predominate.

Morphological and molecular phylogenetic characterization of Sarcocystis kani sp. nov. and other novel, closely related Sarcocystis spp. infecting small mammals and colubrid snakes in Asia

We investigated the morphology and phylogenetic relationships of novel and previously recognized Sarcocystis spp. infecting small mammals and colubrid snakes in Asia. The nuclear 18S rRNA and mitochondrial cox1 of Sarcocystis sp.1 from mangrove snakes (Boiga dendrophila) in Thailand and Sarcocystis sp.2 from a ricefield rat (Rattus argentiventer) in Sumatra were partially sequenced. Sporocysts of Sarcocystis sp.1 induced development of sarcocysts in experimentally infected rats, which showed a unique ultrastructure that was observed previously by S.P. Kan in rats from Malaysia; therefore, we describe this species as Sarcocystis kani sp. nov. Its integration into the 18S rRNA phylogeny of Sarcocystis spp. cycling between small mammals and colubrid snakes helped clarify relationships among the so-called S. zuoi-complex of molecularly cryptic species: Sarcocystis kani sp. nov., S. sp.2, S. attenuati, S. scandentiborneensis, and S. zuoi were all included in this clade. Tree topology was resolved into dichotomies congruent with the morphological disparities between the taxa. However, cox1 gene sequencing (including newly sequenced S. singaporensis and S. zamani) revealed that Sarcocystis kani, S. attenuati, and S. scandentiborneensis were identical suggesting a recent, common ancestry. To identify other distinctive features, lineage-specific molecular patterns within both genes were examined revealing that all 18S rRNA sequences of the S. zuoi - complex possess a unique, 7-nt long motif in helix 38 of domain V7 that was different in S. clethrionomyelaphis which branched off basally from the complex. Three-dimensional homology modelling of COX1 protein structure identified amino acid substitutions within the barcode area specific for the S. zuoi-complex and substantial divergence in structurally important amino acids between Sarcocystis species of snakes as definitive hosts and other lineages of the Sarcocystidae. We discuss the utility of selected genes for species delimitation of the Sarcocystis spp. under investigation, which probably evolved during recent radiations of their intermediate and definitive hosts.

Screening and evaluation of skin potential probiotic from high-altitude Tibetans to repair ultraviolet radiation damage

Human skin microbes play critical roles in skin health and diseases. Microbes colonizing on the skin of Tibetans living in the high-altitude area for generations may have a stronger ability to resist the harsh environment, such as high ultraviolet radiation (UV). Isolation of a potential probiotic from Tibetans skin is beneficial for resistance of skin disease for humans in the world. In this study, the signature microbiota for Tibetan skin were characterized compared to low-altitude humans. Next, using culture-omics, 118 species were isolated. The culturability of high-altitude of Tibetan skin microbiome reached approximate 66.8%. Next, we found that one strain, Pantoea eucrina, had the greatest ability to repair UV damage to the skin as the lowest pathological score was observed in this group. Interestingly, another animal trial found this bacterium resisted UV rather than its metabolites. Using whole genome sequencing, this strain P. eucrina KBFS172 was confirmed, and its functions were annotated. It might involve in the metabolic pathway of carotenoid biosynthesis with anti-oxidative stress properties, which plays critical roles in UV-damage repair. In conclusion, we characterized the signature microbes of skin in high-altitude Tibetans, isolated a skin bacterium of Pantoea eucrina KBFS172 which could repair UV damage via involving the metabolic pathway of carotenoid biosynthesis. Our results provide a new potential skin probiotic for skin disease prevention or sunburn.

In vivo structure probing of RNA in Archaea: novel insights into the ribosome structure of Methanosarcina acetivorans

Structure probing combined with next-generation sequencing (NGS) has provided novel insights into RNA structure-function relationships. To date, such studies have focused largely on bacteria and eukaryotes, with little attention given to the third domain of life, archaea. Furthermore, functional RNAs have not been extensively studied in archaea, leaving open questions about RNA structure and function within this domain of life. With archaeal species being diverse and having many similarities to both bacteria and eukaryotes, the archaea domain has the potential to be an evolutionary bridge. In this study, we introduce a method for probing RNA structure in vivo in the archaea domain of life. We investigated the structure of ribosomal RNA (rRNA) from Methanosarcina acetivorans, a well-studied anaerobic archaeal species, grown with either methanol or acetate. After probing the RNA in vivo with dimethyl sulfate (DMS), Structure-seq2 libraries were generated, sequenced, and analyzed. We mapped the reactivity of DMS onto the secondary structure of the ribosome, which we determined independently with comparative analysis, and confirmed the accuracy of DMS probing in M. acetivorans Accessibility of the rRNA to DMS in the two carbon sources was found to be quite similar, although some differences were found. Overall, this study establishes the Structure-seq2 pipeline in the archaea domain of life and informs about ribosomal structure within M. acetivorans.

Testing a Hypothesis of 12S rRNA Methylation by Putative METTL17 Methyltransferase

Mitochondrial ribosome assembly is a complex multi-step process involving many additional factors. Ribosome formation differs in various groups of organisms. However, there are universal steps of assembly and conservative factors that have been retained in evolutionarily distant taxa. METTL17, the object of the current study, is one of these conservative factors involved in mitochondrial ribosome assembly. It is present in both bacteria and the mitochondria of eukaryotes, in particular mice and humans. In this study, we tested a hypothesis of putative METTL17 methyltransferase activity. MALDI-TOF mass spectrometry was used to evaluate the methylation of a putative METTL17 target - a 12S rRNA region interacting with METTL17 during mitochondrial ribosome assembly. The investigation of METTL17 and other mitochondrial ribosome assembly factors is of both fundamental and practical significance, because defects in mitochondrial ribosome assembly are often associated with human mitochondrial diseases.

Epitranscriptomic subtyping, visualization, and denoising by global motif visualization

Advances in sequencing technologies have empowered epitranscriptomic profiling at the single-base resolution. Putative RNA modification sites identified from a single high-throughput experiment may contain one type of modification deposited by different writers or different types of modifications, along with false positive results because of the challenge of distinguishing signals from noise. However, current tools are insufficient for subtyping, visualization, and denoising these signals. Here, we present iMVP, which is an interactive framework for epitranscriptomic analysis with a nonlinear dimension reduction technique and density-based partition. As exemplified by the analysis of mRNA m5C and ModTect variant data, we show that iMVP allows the identification of previously unknown RNA modification motifs and writers and the discovery of false positives that are undetectable by traditional methods. Using putative m6A/m6Am sites called from 8 profiling approaches, we illustrate that iMVP enables comprehensive comparison of different approaches and advances our understanding of the difference and pattern of true positives and artifacts in these methods. Finally, we demonstrate the ability of iMVP to analyze an extremely large human A-to-I editing dataset that was previously unmanageable. Our work provides a general framework for the visualization and interpretation of epitranscriptomic data.

Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS

Chemical probing experiments have transformed RNA structure analysis, enabling high-throughput measurement of base-pairing in living cells. Dimethyl sulfate (DMS) is one of the most widely used structure probing reagents and has played a pivotal role in enabling next-generation single-molecule probing analyses. However, DMS has traditionally only been able to probe adenine and cytosine nucleobases. We previously showed that, using appropriate conditions, DMS can also be used to interrogate base-pairing of uracil and guanines in vitro at reduced accuracy. However, DMS remained unable to informatively probe guanines in cells. Here, we develop an improved DMS mutational profiling (MaP) strategy that leverages the unique mutational signature of N1-methylguanine DMS modifications to enable high-fidelity structure probing at all four nucleotides, including in cells. Using information theory, we show that four-base DMS reactivities convey greater structural information than current two-base DMS and SHAPE probing strategies. Four-base DMS experiments further enable improved direct base-pair detection by single-molecule PAIR analysis, and ultimately support RNA structure modeling at superior accuracy. Four-base DMS probing experiments are straightforward to perform and will broadly facilitate improved RNA structural analysis in living cells.

Pervasive downstream RNA hairpins dynamically dictate start-codon selection

Translational reprogramming allows organisms to adapt to changing conditions. Upstream start codons (uAUGs), which are prevalently present in mRNAs, have crucial roles in regulating translation by providing alternative translation start sites1-4. However, what determines this selective initiation of translation between conditions remains unclear. Here, by integrating transcriptome-wide translational and structural analyses during pattern-triggered immunity in Arabidopsis, we found that transcripts with immune-induced translation are enriched with upstream open reading frames (uORFs). Without infection, these uORFs are selectively translated owing to hairpins immediately downstream of uAUGs, presumably by slowing and engaging the scanning preinitiation complex. Modelling using deep learning provides unbiased support for these recognizable double-stranded RNA structures downstream of uAUGs (which we term uAUG-ds) being responsible for the selective translation of uAUGs, and allows the prediction and rational design of translating uAUG-ds. We found that uAUG-ds-mediated regulation can be generalized to human cells. Moreover, uAUG-ds-mediated start-codon selection is dynamically regulated. After immune challenge in plants, induced RNA helicases that are homologous to Ded1p in yeast and DDX3X in humans resolve these structures, allowing ribosomes to bypass uAUGs to translate downstream defence proteins. This study shows that mRNA structures dynamically regulate start-codon selection. The prevalence of this RNA structural feature and the conservation of RNA helicases across kingdoms suggest that mRNA structural remodelling is a general feature of translational reprogramming.

Machine learning modeling of RNA structures: methods, challenges and future perspectives

The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules' secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.

Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery

Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life sciences, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction in recent years. Historically, thermodynamics-based methods were widely employed for the prediction of RNA secondary structures; however, machine learning-based approaches have demonstrated remarkable advancements in recent years, enabling more accurate predictions. Consequently, the precision of sequence analysis pertaining to RNA secondary structures, such as RNA-protein interactions, has also been enhanced, making a substantial contribution to the field of RNA biology. Additionally, artificial intelligence and machine learning are also introducing technical innovations in the analysis of RNA-small molecule interactions for RNA-targeted drug discovery and in the design of RNA aptamers, where RNA serves as its own ligand. This review will highlight recent trends in the prediction of RNA secondary structure, RNA aptamers and RNA drug discovery using machine learning, deep learning and related technologies, and will also discuss potential future avenues in the field of RNA informatics.

Anionic G•U pairs in bacterial ribosomal rRNAs

Wobble GU pairs (or G•U) occur frequently within double-stranded RNA helices interspersed between standard G=C and A-U Watson-Crick pairs. Another type of G•U pair interacting via their Watson-Crick edges has been observed in the A site of ribosome structures between a modified U34 in the tRNA anticodon triplet and G + 3 in the mRNA. In such pairs, the electronic structure of the U is changed with a negative charge on N3(U), resulting in two H-bonds between N1(G)…O4(U) and N2(G)…N3(U). Here, we report that such pairs occur in other highly conserved positions in ribosomal RNAs of bacteria in the absence of U modification. An anionic cis Watson-Crick G•G pair is also observed and well conserved in the small subunit. These pairs are observed in tightly folded regions.

Our current understanding of the toxicity of altered mito-ribosomal fidelity during mitochondrial protein synthesis: What can it tell us about human disease?

Altered mito-ribosomal fidelity is an important and insufficiently understood causative agent of mitochondrial dysfunction. Its pathogenic effects are particularly well-known in the case of mitochondrially induced deafness, due to the existence of the, so called, ototoxic variants at positions 847C (m.1494C) and 908A (m.1555A) of 12S mitochondrial (mt-) rRNA. It was shown long ago that the deleterious effects of these variants could remain dormant until an external stimulus triggered their pathogenicity. Yet, the link from the fidelity defect at the mito-ribosomal level to its phenotypic manifestation remained obscure. Recent work with fidelity-impaired mito-ribosomes, carrying error-prone and hyper-accurate mutations in mito-ribosomal proteins, have started to reveal the complexities of the phenotypic manifestation of mito-ribosomal fidelity defects, leading to a new understanding of mtDNA disease. While much needs to be done to arrive to a clear picture of how defects at the level of mito-ribosomal translation eventually result in the complex patterns of disease observed in patients, the current evidence indicates that altered mito-ribosome function, even at very low levels, may become highly pathogenic. The aims of this review are three-fold. First, we compare the molecular details associated with mito-ribosomal fidelity to those of general ribosomal fidelity. Second, we gather information on the cellular and organismal phenotypes associated with defective translational fidelity in order to provide the necessary grounds for an understanding of the phenotypic manifestation of defective mito-ribosomal fidelity. Finally, the results of recent experiments directly tackling mito-ribosomal fidelity are reviewed and future paths of investigation are discussed.

Structural analysis of mitochondrial rRNA gene variants identified in patients with deafness

The last few years have witnessed dramatic advances in our understanding of the structure and function of the mammalian mito-ribosome. At the same time, the first attempts to elucidate the effects of mito-ribosomal fidelity (decoding accuracy) in disease have been made. Hence, the time is right to push an important frontier in our understanding of mitochondrial genetics, that is, the elucidation of the phenotypic effects of mtDNA variants affecting the functioning of the mito-ribosome. Here, we have assessed the structural and functional role of 93 mitochondrial (mt-) rRNA variants thought to be associated with deafness, including those located at non-conserved positions. Our analysis has used the structural description of the human mito-ribosome of the highest quality currently available, together with a new understanding of the phenotypic manifestation of mito-ribosomal-associated variants. Basically, any base change capable of inducing a fidelity phenotype may be considered non-silent. Under this light, out of 92 previously reported mt-rRNA variants thought to be associated with deafness, we found that 49 were potentially non-silent. We also dismissed a large number of reportedly pathogenic mtDNA variants, 41, as polymorphisms. These results drastically update our view on the implication of the primary sequence of mt-rRNA in the etiology of deafness and mitochondrial disease in general. Our data sheds much-needed light on the question of how mt-rRNA variants located at non-conserved positions may lead to mitochondrial disease and, most notably, provide evidence of the effect of haplotype context in the manifestation of some mt-rRNA variants.

Machine learning for RNA 2D structure prediction benchmarked on experimental data

Since the 1980s, dozens of computational methods have addressed the problem of predicting RNA secondary structure. Among them are those that follow standard optimization approaches and, more recently, machine learning (ML) algorithms. The former were repeatedly benchmarked on various datasets. The latter, on the other hand, have not yet undergone extensive analysis that could suggest to the user which algorithm best fits the problem to be solved. In this review, we compare 15 methods that predict the secondary structure of RNA, of which 6 are based on deep learning (DL), 3 on shallow learning (SL) and 6 control methods on non-ML approaches. We discuss the ML strategies implemented and perform three experiments in which we evaluate the prediction of (I) representatives of the RNA equivalence classes, (II) selected Rfam sequences and (III) RNAs from new Rfam families. We show that DL-based algorithms (such as SPOT-RNA and UFold) can outperform SL and traditional methods if the data distribution is similar in the training and testing set. However, when predicting 2D structures for new RNA families, the advantage of DL is no longer clear, and its performance is inferior or equal to that of SL and non-ML methods.

Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS

Chemical probing experiments have transformed RNA structure analysis, enabling high-throughput measurement of base-pairing in living cells. Dimethyl sulfate (DMS) is one of the most widely used structure probing reagents and has played a prominent role in enabling next-generation single-molecule probing analyses. However, DMS has traditionally only been able to probe adenine and cytosine nucleobases. We previously showed that, using appropriate conditions, DMS can also be used to interrogate base-pairing of uracil and guanines in vitro at reduced accuracy. However, DMS remained unable to informatively probe guanines in cells. Here, we develop an improved DMS mutational profiling (MaP) strategy that leverages the unique mutational signature of N 1 -methylguanine DMS modifications to enable robust, high-fidelity structure probing at all four nucleotides, including in cells. Using information theory, we show that four-base DMS reactivities convey greater structural information than comparable two-base DMS and SHAPE probing strategies. Four-base DMS experiments further enable improved direct base-pair detection by single-molecule PAIR analysis, and ultimately support RNA structure modeling at superior accuracy. Four-base DMS probing experiments are easily performed and will broadly facilitate improved RNA structural analysis in living cells.

Cooperative role of AtRsmD and AtRimM proteins in modification and maturation of 16S rRNA in plastids

Chloroplast pre-ribosomal RNA (rRNA) undergoes maturation, which is critical for ribosome assembly. While the central and auxiliary factors in rRNA maturation have been elucidated in bacteria, their mode of action remains largely unexplored in chloroplasts. We now reveal chloroplast-specific factors involved in 16S rRNA maturation, Arabidopsis thaliana orthologs of bacterial RsmD methyltransferase (AtRsmD) and ribosome maturation factor RimM (AtRimM). A forward genetic screen aimed to find suppressors of the Arabidopsis yellow variegated 2 (var2) mutant defective in photosystem II quality control found a causal nonsense mutation in AtRsmD. The substantially impaired 16S rRNA maturation and translation due to the mutation rescued the leaf variegation phenotype by lowering the levels of chloroplast-encoded proteins, including photosystem II core proteins, in var2. The subsequent co-immunoprecipitation coupled with mass spectrometry analyses and bimolecular fluorescence complementation assay found that AtRsmD interacts with AtRimM. Consistent with their interaction, loss of AtRimM also considerably impairs 16S rRNA maturation with decelerated m² G915 modification in 16S rRNA catalyzed by AtRsmD. The atrimM mutation also rescued var2 mutant phenotypes, corroborating the functional interplay between AtRsmD and AtRimM towards modification and maturation of 16S rRNA and chloroplast proteostasis. The maturation and post-transcriptional modifications of rRNA are critical to assembling ribosomes responsible for protein translation. Here, we revealed that the cooperative regulation of 16S rRNA m² G915 modifications by AtRsmD methyltransferase and ribosome assembly factor AtRimM contributes to 16S rRNA maturation, ribosome assembly, and proteostasis in chloroplasts.

UPP2: fast and accurate alignment of datasets with fragmentary sequences

MOTIVATION

Multiple sequence alignment (MSA) is a basic step in many bioinformatics pipelines. However, achieving highly accurate alignments on large datasets, especially those with sequence length heterogeneity, is a challenging task. Ultra-large multiple sequence alignment using Phylogeny-aware Profiles (UPP) is a method for MSA estimation that builds an ensemble of Hidden Markov Models (eHMM) to represent an estimated alignment on the full-length sequences in the input, and then adds the remaining sequences into the alignment using selected HMMs in the ensemble. Although UPP provides good accuracy, it is computationally intensive on large datasets.

RESULTS

We present UPP2, a direct improvement on UPP. The main advance is a fast technique for selecting HMMs in the ensemble that allows us to achieve the same accuracy as UPP but with greatly reduced runtime. We show that UPP2 produces more accurate alignments compared to leading MSA methods on datasets exhibiting substantial sequence length heterogeneity and is among the most accurate otherwise.

AVAILABILITY AND IMPLEMENTATION

https://github.com/gillichu/sepp.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Finding priority bacterial ribosomes for future structural and antimicrobial research based upon global RNA and protein sequence analysis

Ribosome-targeting antibiotics comprise over half of antibiotics used in medicine, but our fundamental knowledge of their binding sites is derived primarily from ribosome structures of non-pathogenic species. These include Thermus thermophilus, Deinococcus radiodurans and the archaean Haloarcula marismortui, as well as the commensal and sometimes pathogenic organism, Escherichia coli. Advancements in electron cryomicroscopy have allowed for the determination of more ribosome structures from pathogenic bacteria, with each study highlighting species-specific differences that had not been observed in the non-pathogenic structures. These observed differences suggest that more novel ribosome structures, particularly from pathogens, are required for a more accurate understanding of the level of diversity of the entire bacterial ribosome, with the potential of leading to innovative advancements in antibiotic research. In this study, high accuracy covariance and hidden Markov models were used to annotate ribosomal RNA and protein sequences respectively from genomic sequence, allowing us to determine the underlying ribosomal sequence diversity using phylogenetic methods. This analysis provided evidence that the current non-pathogenic ribosome structures are not sufficient representatives of some pathogenic bacteria, such as Campylobacter pylori, or of whole phyla such as Bacteroidota (Bacteroidetes).

Structures of the eukaryotic ribosome and its translational states in situ

Ribosomes translate genetic information into primary structure. During translation, various cofactors transiently bind to the ribosome that undergoes prominent conformational and structural changes. Different translational states of ribosomes have been well characterized in vitro. However, to which extent the known translational states are representative of the native situation inside cells has thus far only been addressed in prokaryotes. Here, we apply cryo-electron tomography to cryo-FIB milled Dictyostelium discoideum cells combined with subtomogram averaging and classification. We obtain an in situ structure that is locally resolved up to 3 Angstrom, the distribution of eukaryotic ribosome translational states, and unique arrangement of rRNA expansion segments. Our work demonstrates the use of in situ structural biology techniques for identifying distinct ribosome states within the cellular environment.

The Mitogenome of Sedum plumbizincicola (Crassulaceae): Insights into RNA Editing, Lateral Gene Transfer, and Phylogenetic Implications

As the largest family within the order Saxifragales, Crassulaceae contains about 34 genera with 1400 species. Mitochondria play a critical role in cellular energy production. Since the first land plant mitogenome was reported in Arabidopsis, more than 400 mitogenomic sequences have been deposited in a public database. However, no entire mitogenome data have been available for species of Crassulaceae to date. To better understand the evolutionary history of the organelles of Crassulaceae, we sequenced and performed comprehensive analyses on the mitogenome of Sedum plumbizincicola. The master mitogenomic circle is 212,159 bp in length, including 31 protein-coding genes (PCGs), 14 tRNA genes, and 3 rRNA genes. We further identified totally 508 RNA editing sites in PCGs, and demonstrated that the second codon positions of mitochondrial genes are most prone to RNA editing events. Notably, by neutrality plot analyses, we observed that the mitochondrial RNA editing events have large effects on the driving forces of plant evolution. Additionally, 4 MTPTs and 686 NUMTs were detected in the mitochondrial and nuclear genomes of S. plumbizincicola, respectively. Additionally, we conducted further analyses on gene transfer, secondary structures of mitochondrial RNAs, and phylogenetic implications. Therefore, the findings presented here will be helpful for future investigations on plant mitogenomes.

About the Analysis of 18S rDNA Sequence Data from Trypanosomes in Barcoding and Phylogenetics: Tracing a Continuation Error Occurring in the Literature

The variable regions (V1–V9) of the 18S rDNA are routinely used in barcoding and phylogenetics. In handling these data for trypanosomes, we have noticed a misunderstanding that has apparently taken a life of its own in the literature over the years. In particular, in recent years, when studying the phylogenetic relationship of trypanosomes, the use of V7/V8 was systematically established. However, considering the current numbering system for all other organisms (including other Euglenozoa), V7/V8 was never used. In Maia da Silva et al. [Parasitology 2004, 129, 549–561], V7/V8 was promoted for the first time for trypanosome phylogenetics, and since then, more than 70 publications have replicated this nomenclature and even discussed the benefits of the use of this region in comparison to V4. However, the primers used to amplify the variable region of trypanosomes have actually amplified V4 (concerning the current 18S rDNA numbering system).

rRNA expansion segment 7 in eukaryotes: from Signature Fold to tentacles

The ribosomal core is universally conserved across the tree of life. However, eukaryotic ribosomes contain diverse rRNA expansion segments (ESs) on their surfaces. Sites of ES insertions are predicted from sites of insertion of micro-ESs in archaea. Expansion segment 7 (ES7) is one of the most diverse regions of the ribosome, emanating from a short stem loop and ranging to over 750 nucleotides in mammals. We present secondary and full-atom 3D structures of ES7 from species spanning eukaryotic diversity. Our results are based on experimental 3D structures, the accretion model of ribosomal evolution, phylogenetic relationships, multiple sequence alignments, RNA folding algorithms and 3D modeling by RNAComposer. ES7 contains a distinct motif, the 'ES7 Signature Fold', which is generally invariant in 2D topology and 3D structure in all eukaryotic ribosomes. We establish a model in which ES7 developed over evolution through a series of elementary and recursive growth events. The data are sufficient to support an atomic-level accretion path for rRNA growth. The non-monophyletic distribution of some ES7 features across the phylogeny suggests acquisition via convergent processes. And finally, illustrating the power of our approach, we constructed the 2D and 3D structure of the entire LSU rRNA of Mus musculus.

In vivo single-molecule analysis reveals COOLAIR RNA structural diversity

Cellular RNAs are heterogeneous with respect to their alternative processing and secondary structures, but the functional importance of this complexity is still poorly understood. A set of alternatively processed antisense non-coding transcripts, which are collectively called COOLAIR, are generated at the Arabidopsis floral-repressor locus FLOWERING LOCUS C (FLC)1. Different isoforms of COOLAIR influence FLC transcriptional output in warm and cold conditions2-7. Here, to further investigate the function of COOLAIR, we developed an RNA structure-profiling method to determine the in vivo structure of single RNA molecules rather than the RNA population average. This revealed that individual isoforms of the COOLAIR transcript adopt multiple structures with different conformational dynamics. The major distally polyadenylated COOLAIR isoform in warm conditions adopts three predominant structural conformations, the proportions and conformations of which change after cold exposure. An alternatively spliced, strongly cold-upregulated distal COOLAIR isoform6 shows high structural diversity, in contrast to proximally polyadenylated COOLAIR. A hyper-variable COOLAIR structural element was identified that was complementary to the FLC transcription start site. Mutations altering the structure of this region changed FLC expression and flowering time, consistent with an important regulatory role of the COOLAIR structure in FLC transcription. Our work demonstrates that isoforms of non-coding RNA transcripts adopt multiple distinct and functionally relevant structural conformations, which change in abundance and shape in response to external conditions.

Conjugates of Desmycosin with Fragments of Antimicrobial Peptide Oncocin: Synthesis, Antibacterial Activity, Interaction with Ribosome

Design and synthesis of conjugates consisting of the macrolide antibiotic desmycosin and fragments of the antibacterial peptide oncocin were performed in attempt to develop new antimicrobial compounds. New compounds were shown to bind to the E. coli 70S ribosomes, to inhibit bacterial protein synthesis in vitro, as well as to suppress bacterial growth. The conjugates of N-terminal hexa- and tripeptide fragments of oncocin and 3,2',4''-triacetyldesmycosin were found to be active against some strains of macrolide-resistant bacteria. By simulating molecular dynamics of the complexes of these compounds with the wild-type bacterial ribosomes and with ribosomes, containing A2059G 23S RNA mutation, the specific structural features of their interactions were revealed.

Deep learning models for RNA secondary structure prediction (probably) do not generalize across families

MOTIVATION

The secondary structure of RNA is of importance to its function. Over the last few years, several papers attempted to use machine learning to improve de novo RNA secondary structure prediction. Many of these papers report impressive results for intra-family predictions but seldom address the much more difficult (and practical) inter-family problem.

RESULTS

We demonstrate that it is nearly trivial with convolutional neural networks to generate pseudo-free energy changes, modelled after structure mapping data that improve the accuracy of structure prediction for intra-family cases. We propose a more rigorous method for inter-family cross-validation that can be used to assess the performance of learning-based models. Using this method, we further demonstrate that intra-family performance is insufficient proof of generalization despite the widespread assumption in the literature and provide strong evidence that many existing learning-based models have not generalized inter-family.

AVAILABILITY AND IMPLEMENTATION

Source code and data are available at https://github.com/marcellszi/dl-rna.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Caveats to Deep Learning Approaches to RNA Secondary Structure Prediction

Machine learning (ML) and in particular deep learning techniques have gained popularity for predicting structures from biopolymer sequences. An interesting case is the prediction of RNA secondary structures, where well established biophysics based methods exist. The accuracy of these classical methods is limited due to lack of experimental parameters and certain simplifying assumptions and has seen little improvement over the last decade. This makes RNA folding an attractive target for machine learning and consequently several deep learning models have been proposed in recent years. However, for ML approaches to be competitive for de-novo structure prediction, the models must not just demonstrate good phenomenological fits, but be able to learn a (complex) biophysical model. In this contribution we discuss limitations of current approaches, in particular due to biases in the training data. Furthermore, we propose to study capabilities and limitations of ML models by first applying them on synthetic data (obtained from a simplified biophysical model) that can be generated in arbitrary amounts and where all biases can be controlled. We assume that a deep learning model that performs well on these synthetic, would also perform well on real data, and vice versa. We apply this idea by testing several ML models of varying complexity. Finally, we show that the best models are capable of capturing many, but not all, properties of RNA secondary structures. Most severely, the number of predicted base pairs scales quadratically with sequence length, even though a secondary structure can only accommodate a linear number of pairs.

Hyper-swivel head domain motions are required for complete mRNA-tRNA translocation and ribosome resetting

Translocation of messenger RNA (mRNA) and transfer RNA (tRNA) substrates through the ribosome during protein synthesis, an exemplar of directional molecular movement in biology, entails a complex interplay of conformational, compositional, and chemical changes. The molecular determinants of early translocation steps have been investigated rigorously. However, the elements enabling the ribosome to complete translocation and reset for subsequent protein synthesis reactions remain poorly understood. Here, we have combined molecular simulations with single-molecule fluorescence resonance energy transfer imaging to gain insights into the rate-limiting events of the translocation mechanism. We find that diffusive motions of the ribosomal small subunit head domain to hyper-swivelled positions, governed by universally conserved rRNA, can maneuver the mRNA and tRNAs to their fully translocated positions. Subsequent engagement of peptidyl-tRNA and disengagement of deacyl-tRNA from mRNA, within their respective small subunit binding sites, facilitate the ribosome resetting mechanism after translocation has occurred to enable protein synthesis to resume.

Comparative mitochondrial genomes of the Rhus gall aphid Kaburagia rhusicola subspecies with variable gall shapes

Rhus gall aphids (Hemiptera: Aphididae: Eriosomatinae) stimulate the formation of galls on their primary host plants (sumacs: Rhus spp., Anacardiaceae). The shapes of galls are often used as an extended phenotype to identify the aphid species and subspecies. We collected four Rhus galls with conspicuously different shapes formed by Kaburagia rhusicola aphids, whose sequences of the complete mitochondrial genomes (mitogenomes) were obtained by high-throughput sequencing. Each mitogenome was assembled into a circular molecule containing 13 protein-coding genes, two rRNAs, 22 tRNAs and one control region. All the protein-coding genes had a typical ATN initiation codon and TAA termination codon except for cox1 and nad4, which had a single T as stop codon. All the tRNAs could be folded as a typical clover-leaf secondary structure, except for trnS1 lacking a dihydrouridine (DHU) arm. The relative synonymous codon usage and ratio of nonsynonymous to synonymous substitution rates showed that the four K. rhusicola samples were highly similar to the subspecies K. r. ovogallis. The phylogenetic analyses grouped these samples with K. r. ovogallis in a clade sister to K. r. rhusicola. All these molecular analyses demonstrated that our current samples represented one subspecies of Kaburagia rhusicola, i.e., K. r. ovogallis, and the gall shape was variable even at the subspecies level in Kaburagia gall aphids.

WITCH: Improved Multiple Sequence Alignment Through Weighted Consensus Hidden Markov Model Alignment

Accurate multiple sequence alignment is challenging on many data sets, including those that are large, evolve under high rates of evolution, or have sequence length heterogeneity. While substantial progress has been made over the last decade in addressing the first two challenges, sequence length heterogeneity remains a significant issue for many data sets. Sequence length heterogeneity occurs for biological and technological reasons, including large insertions or deletions (indels) that occurred in the evolutionary history relating the sequences, or the inclusion of sequences that are not fully assembled. Ultra-large alignments using Phylogeny-Aware Profiles (UPP) (Nguyen et al. 2015) is one of the most accurate approaches for aligning data sets that exhibit sequence length heterogeneity: it constructs an alignment on the subset of sequences it considers "full-length," represents this "backbone alignment" using an ensemble of hidden Markov models (HMMs), and then adds each remaining sequence into the backbone alignment based on an HMM selected for that sequence from the ensemble. Our new method, WeIghTed Consensus Hmm alignment (WITCH), improves on UPP in three important ways: first, it uses a statistically principled technique to weight and rank the HMMs; second, it uses k>1 HMMs from the ensemble rather than a single HMM; and third, it combines the alignments for each of the selected HMMs using a consensus algorithm that takes the weights into account. We show that this approach provides improved alignment accuracy compared with UPP and other leading alignment methods, as well as improved accuracy for maximum likelihood trees based on these alignments.

The universally conserved nucleotides of the small subunit ribosomal RNAs

The ribosomal RNAs, along with their substrates the transfer RNAs, contain the most highly conserved nucleotides in all of biology. We have assembled a database containing structure-based alignments of sequences of the small-subunit rRNAs from organisms that span the entire phylogenetic spectrum, to identify the nucleotides that are universally conserved. In its simplest (bacterial and archaeal) forms, the small-subunit rRNA has ∼1500 nt, of which we identify 140 that are absolutely invariant among the 1961 species in our alignment. We examine the positions and detailed structural and functional interactions of these universal nucleotides in the context of a half century of biochemical and genetic studies and high-resolution structures of ribosome functional complexes. The vast majority of these nucleotides are exposed on the subunit interface surface of the small subunit, where the functional processes of the ribosome take place. However, only 40 of them have been directly implicated in specific ribosomal functions, such as contacting the tRNAs, mRNA, or translation factors. The roles of many other invariant nucleotides may serve to constrain the positions and orientations of those nucleotides that are directly involved in function. Yet others can be rationalized by participation in unusual noncanonical tertiary structures that may uniquely allow correct folding of the rRNA to form a functional ribosome. However, there remain at least 50 nt whose universal conservation is not obvious, serving as a metric for the incompleteness of our understanding of ribosome structure and function.

CHAPAO: Likelihood and hierarchical reference-based representation of biomolecular sequences and applications to compressing multiple sequence alignments

Background

High-throughput experimental technologies are generating tremendous amounts of genomic data, offering valuable resources to answer important questions and extract biological insights. Storing this sheer amount of genomic data has become a major concern in bioinformatics. General purpose compression techniques (e.g. gzip, bzip2, 7-zip) are being widely used due to their pervasiveness and relatively good speed. However, they are not customized for genomic data and may fail to leverage special characteristics and redundancy of the biomolecular sequences.

Results

We present a new lossless compression method CHAPAO (COmpressing Alignments using Hierarchical and Probabilistic Approach), which is especially designed for multiple sequence alignments (MSAs) of biomolecular data and offers very good compression gain. We have introduced a novel hierarchical referencing technique to represent biomolecular sequences which combines likelihood based analyses of the sequence similarities and graph theoretic algorithms. We performed an extensive evaluation study using a collection of real biological data from the avian phylogenomics project, 1000 plants project (1KP), and 16S and 23S rRNA datasets. We report the performance of CHAPAO in comparison with general purpose compression techniques as well as with MFCompress and Nucleotide Archival Format (NAF)—two of the best known methods especially designed for FASTA files. Experimental results suggest that CHAPAO offers significant improvements in compression gain over most other alternative methods. CHAPAO is freely available as an open source software at https://github.com/ashiq24/CHAPAO.

Conclusion

CHAPAO advances the state-of-the-art in compression algorithms and represents a potential alternative to the general purpose compression techniques as well as to the existing specialized compression techniques for biomolecular sequences.

Nuclear and Mitochondrial SSU rRNA Genes Reveal Hidden Diversity of Haptophrya Endosymbionts in Freshwater Planarians and Challenge Their Traditional Classification in Astomatia

Like many other aquatic animals, freshwater planarians have also become partners of symbiotic ciliates from the class Oligohymenophorea. In the present study, we explored the hidden diversity and addressed the questionable systematic position of mouthless obligatory gut endosymbionts of freshwater planarians, using the nuclear and mitochondrial SSU rRNA genes. Although all isolated ciliates morphologically corresponded to a single species, molecular analyses suggested the existence of three genetically distinct entities: Haptophrya planariarum, Haptophrya dugesiarum nov. spec., and Haptophrya schmidtearum nov. spec. The two former species share the same planarian host, which indicates a speciation model involving one duplication event without host switching. Such a diversification pattern was recognized also in astome ciliates inhabiting megascolecid and glossoscolecid earthworms. The present multi-gene phylogenies along with the secondary structure of the mitochondrial 16S rRNA molecule, however, challenge the traditional classification of Haptophrya within the subclass Astomatia. Haptophrya very likely evolved from an orphan scuticociliate lineage by the loss of oral apparatus and by the transformation of the thigmotactic field into an adhesive sucker. Since astomy evolved multiple times independently within the Oligohymenophorea, the loss of cell mouth cannot be used as a sole argument for the assignment of Haptophrya to the Astomatia anymore.

16S rRNA Methyltransferases as Novel Drug Targets Against Tuberculosis

Tuberculosis (TB) is an airborne infectious disease caused by Mycobacterium tuberculosis (M.tb) whose natural history traces back to 70,000 years. TB remains a major global health burden. Methylation is a type of post-replication, post-transcriptional and post-translational epi-genetic modification involved in transcription, translation, replication, tissue specific expression, embryonic development, genomic imprinting, genome stability and chromatin structure, protein protein interactions and signal transduction indicating its indispensable role in survival of a pathogen like M.tb. The pathogens use this epigenetic mechanism to develop resistance against certain drug molecules and survive the lethality. Drug resistance has become a major challenge to tackle and also a major concern raised by WHO. Methyltransferases are enzymes that catalyze the methylation of various substrates. None of the current TB targets belong to methyltransferases which provides therapeutic opportunities to develop novel drugs through studying methyltransferases as potential novel targets against TB. Targeting 16S rRNA methyltransferases serves two purposes simultaneously: a) translation inhibition and b) simultaneous elimination of the ability to methylate its substrates hence stopping the emergence of drug resistance strains. There are ~ 40 different rRNA methyltransferases and 13 different 16S rRNA specific methyltransferases which are unexplored and provide a huge opportunity for treatment of TB.

Length-Dependent Deep Learning Model for RNA Secondary Structure Prediction

Deep learning methods for RNA secondary structure prediction have shown higher performance than traditional methods, but there is still much room to improve. It is known that the lengths of RNAs are very different, as are their secondary structures. However, the current deep learning methods all use length-independent models, so it is difficult for these models to learn very different secondary structures. Here, we propose a length-dependent model that is obtained by further training the length-independent model for different length ranges of RNAs through transfer learning. 2dRNA, a coupled deep learning neural network for RNA secondary structure prediction, is used to do this. Benchmarking shows that the length-dependent model performs better than the usual length-independent model.

Three critical regions of the erythromycin resistance methyltransferase, ErmE, are required for function supporting a model for the interaction of Erm family enzymes with substrate rRNA

6-Methyladenosine modification of DNA and RNA is widespread throughout the three domains of life and often accomplished by a Rossmann-fold methyltransferase domain which contains conserved sequence elements directing S-adenosylmethionine cofactor binding and placement of the target adenosine residue into the active site. Elaborations to the conserved Rossman-fold and appended domains direct methylation to diverse DNA and RNA sequences and structures. Recently, the first atomic-resolution structure of a ribosomal RNA adenine dimethylase (RRAD) family member bound to rRNA was solved, TFB1M bound to helix 45 of 12S rRNA. Since erythromycin resistance methyltransferases are also members of the RRAD family, and understanding how these enzymes recognize rRNA could be used to combat their role in antibiotic resistance, we constructed a model of ErmE bound to a 23S rRNA fragment based on the TFB1M-rRNA structure. We designed site-directed mutants of ErmE based on this model and assayed the mutants by in vivo phenotypic assays and in vitro assays with purified protein. Our results and additional bioinformatic analyses suggest our structural model captures key ErmE-rRNA interactions and indicate three regions of Erm proteins play a critical role in methylation: the target adenosine binding pocket, the basic ridge, and the α4-cleft.

Experimental confirmation that an uncommon rrs gene mutation (g878a) of Mycobacterium tuberculosis confers resistance to streptomycin

The effective treatment of patients diagnosed with drug resistant tuberculosis is highly dependent upon the ability to rapidly and accurately determine the antibiotic susceptibility profile of the Mycobacterium tuberculosis isolate(s) involved. Thus, as more clinical microbiology laboratories advance towards the use of DNA sequence-based diagnostics, it is imperative that their predictive functions extend beyond the well-known resistance mutations, in order to also encompass as many of the lower-frequency mutations as possible. However, in most cases, the fundamental experimental proof that links these uncommon mutations with phenotypic resistance is lacking. One such example is the g878a polymorphism within the rrs 16s rRNA gene. We, and others, have identified this mutation within a small number of drug-resistant isolates, although a consensus regarding exactly which aminoglycoside antibiotic(s) it confers resistance toward has not previously been reached. Here we have employed oligo-mediated recombineering to introduce the g878a polymorphism into the rrs gene of M. bovis BCG - a close relative of M. tuberculosis - and demonstrate that it confers low-level resistance to streptomycin alone. It does not confer cross-resistance towards amikacin, capreomycin, nor kanamycin. We also demonstrate that the rrs g878a mutation exerts a substantial fitness defect in vitro , that may at least in part explain why clinical isolates bearing this mutation appear to be quite rare. Overall, this study provides clarity to the phenotype attributable to the rrs g878a mutation and is relevant to the future implementation of genomics-based diagnostics, as well as the clinical management of patients where this particular polymorphism is encountered.

A Comparative Perspective on Ribosome Biogenesis: Unity and Diversity Across the Tree of Life

Ribosomes are universally conserved ribonucleoprotein complexes involved in the decoding of the genetic information contained in messenger RNAs into proteins. Accordingly, ribosome biogenesis is a fundamental cellular process required for functional ribosome homeostasis and to preserve satisfactory gene expression capability.Although the ribosome is universally conserved, its biogenesis shows an intriguing degree of variability across the tree of life . These differences also raise yet unresolved questions. Among them are (a) what are, if existing, the remaining ancestral common principles of ribosome biogenesis ; (b) what are the molecular impacts of the evolution history and how did they contribute to (re)shape the ribosome biogenesis pathway across the tree of life ; (c) what is the extent of functional divergence and/or convergence (functional mimicry), and in the latter case (if existing) what is the molecular basis; (d) considering the universal ribosome conservation, what is the capability of functional plasticity and cellular adaptation of the ribosome biogenesis pathway?In this review, we provide a brief overview of ribosome biogenesis across the tree of life and try to illustrate some potential and/or emerging answers to these unresolved questions.

An Aggregation Method to Identify the RNA Meta-Stable Secondary Structure and its Functionally Interpretable Structure Ensemble

RNA can provide vital cellular functions through its secondary or tertiary structure. Due to the low-throughput nature of experimental approaches, studies on RNA structures mainly resort to computational methods. However, current existing tools fail to consider RNA structure ensembles and do not provide ways to decipher functional hypotheses for the new predictions. In this research, a novel method was proposed to identify the functionally interpretable structure ensemble of a given RNA sequence and provide the meta-stable structure, or the most frequently observed functional RNA cellular conformation, based on the ensemble. In the prediction of meta-stable structures, the proposed method outperformed existing tools on a yeast test set. The inferred functional aspects were then manually checked and demonstrated a micro-averaging F1 value of 0.92. Further, a biological example of the yeast ASH1-E1 element was discussed to articulate that these functional aspects can also suggest testable hypotheses. Then the proposed method was verified to be well applicable to other species through a human test set. Finally, the proposed method was demonstrated to show resistance to sequence length-dependent performance deterioration.