Enzymatic characterization and mutational studies of TruD--the fifth family of pseudouridine synthases

RNA Sequencing Unveils Very Small RNAs With Potential Regulatory Functions in Bacteria

RNA sequencing (RNA-seq) is the gold standard for the discovery of small non-coding RNAs. Following a long-standing approach, reads shorter than 16 nucleotides (nt) are removed from the small RNA sequencing libraries or datasets. The serendipitous discovery of an eukaryotic 12 nt-long RNA species capable of modulating the microRNA from which they derive prompted us to challenge this dogma and, by expanding the window of RNA sizes down to 8 nt, to confirm the existence of functional very small RNAs (vsRNAs <16 nt). Here we report the detailed profiling of vsRNAs in Escherichia coli, E. coli-derived outer membrane vesicles (OMVs) and five other bacterial strains (Pseudomonas aeruginosa PA7, P. aeruginosa PAO1, Salmonella enterica serovar Typhimurium 14028S, Legionella pneumophila JR32 Philadelphia-1 and Staphylococcus aureus HG001). vsRNAs of 8–15 nt in length [RNAs (8-15 nt)] were found to be more abundant than RNAs of 16–30 nt in length [RNAs (16–30 nt)]. vsRNA biotypes were distinct and varied within and across bacterial species and accounted for one third of reads identified in the 8–30 nt window. The tRNA-derived fragments (tRFs) have appeared as a major biotype among the vsRNAs, notably Ile-tRF and Ala-tRF, and were selectively loaded in OMVs. tRF-derived vsRNAs appear to be thermodynamically stable with at least 2 G-C basepairs and stem-loop structure. The analyzed tRF-derived vsRNAs are predicted to target several human host mRNAs with diverse functions. Bacterial vsRNAs and OMV-derived vsRNAs could be novel players likely modulating the intricate relationship between pathogens and their hosts.

PseUdeep: RNA Pseudouridine Site Identification with Deep Learning Algorithm

Background: Pseudouridine (Ψ) is a common ribonucleotide modification that plays a significant role in many biological processes. The identification of Ψ modification sites is of great significance for disease mechanism and biological processes research in which machine learning algorithms are desirable as the lab exploratory techniques are expensive and time-consuming. Results: In this work, we propose a deep learning framework, called PseUdeep, to identify Ψ sites of three species: H. sapiens, S. cerevisiae, and M. musculus. In this method, three encoding methods are used to extract the features of RNA sequences, that is, one-hot encoding, K-tuple nucleotide frequency pattern, and position-specific nucleotide composition. The three feature matrices are convoluted twice and fed into the capsule neural network and bidirectional gated recurrent unit network with a self-attention mechanism for classification. Conclusion: Compared with other state-of-the-art methods, our model gets the highest accuracy of the prediction on the independent testing data set S-200; the accuracy improves 12.38%, and on the independent testing data set H-200, the accuracy improves 0.68%. Moreover, the dimensions of the features we derive from the RNA sequences are only 109,109, and 119 in H. sapiens, M. musculus, and S. cerevisiae, which is much smaller than those used in the traditional algorithms. On evaluation via tenfold cross-validation and two independent testing data sets, PseUdeep outperforms the best traditional machine learning model available. PseUdeep source code and data sets are available at https://github.com/dan111262/PseUdeep.

MU-PseUDeep: A deep learning method for prediction of pseudouridine sites

Pseudouridine synthase binds to uridine sites and catalyzes the conversion of uridine to pseudouridine (Ψ). This binding takes place in a specific context and in the conformation of nucleotides. Most machine-learning methods for Ψ site classification use nucleotide frequency as a feature, which may not fully depict the relevant conformation around a Ψ site. Using the power of deep learning and raw sequence, as well as secondary structure features, our tool MU-PseUDeep is designed to capture both the sequence and secondary structure context, which inputs the raw RNA sequence and the predicted secondary structure to two sets of convolutional neural networks. It has shown considerable improvement in Ψ site prediction over existing tools, XG-PseU, PseUI, and iRNA-PseU for both balanced and imbalanced datasets. To the best of our knowledge, this is the most accurate tool for Ψ site prediction. We also used MU-PseUDeep to scan the human transcriptome, which shows that the genes with predicted Ψ sites are enriched in nucleotide and protein binding, as well as in neurodegeneration pathways. The tool is open source, available at https://github.com/smk5g5/MU-PseUDeep.

Evolution of Eukaryal and Archaeal Pseudouridine Synthase Pus10

In archaea, pseudouridine (Ψ) synthase Pus10 modifies uridine (U) to Ψ at positions 54 and 55 of tRNA. In contrast, Pus10 is not found in bacteria, where modifications at those two positions are carried out by TrmA (U54 to m⁵U54) and TruB (U55 to Ψ55). Many eukaryotes have an apparent redundancy; their genomes contain orthologs of archaeal Pus10 and bacterial TrmA and TruB. Although eukaryal Pus10 genes share a conserved catalytic domain with archaeal Pus10 genes, their biological roles are not clear for the two reasons. First, experimental evidence suggests that human Pus10 participates in apoptosis induced by the tumor necrosis factor-related apoptosis-inducing ligand. Whether the function of human Pus10 is in place or in addition to of Ψ synthesis in tRNA is unknown. Second, Pus10 is found in earlier evolutionary branches of fungi (such as chytrid Batrachochytrium) but is absent in all dikaryon fungi surveyed (Ascomycetes and Basidiomycetes). We did a comprehensive analysis of sequenced genomes and found that orthologs of Pus10, TrmA, and TruB were present in all the animals, plants, and protozoa surveyed. This indicates that the common eukaryotic ancestor possesses all the three genes. Next, we examined 116 archaeal and eukaryotic Pus10 protein sequences to find that Pus10 existed as a single copy gene in all the surveyed genomes despite ancestral whole genome duplications had occurred. This indicates a possible deleterious gene dosage effect. Our results suggest that functional redundancy result in gene loss or neofunctionalization in different evolutionary lineages.

The Evolution of Substrate Specificity by tRNA Modification Enzymes

All types of nucleic acids in cells undergo naturally occurring chemical modifications, including DNA, rRNA, mRNA, snRNA, and most prominently tRNA. Over 100 different modifications have been described and every position in the purine and pyrimidine bases can be modified; often the sugar is also modified [1]. In tRNA, the function of modifications varies; some modulate global and/or local RNA structure, and others directly impact decoding and may be essential for viability. Whichever the case, the overall importance of modifications is highlighted by both their evolutionary conservation and the fact that organisms use a substantial portion of their genomes to encode modification enzymes, far exceeding what is needed for the de novo synthesis of the canonical nucleotides themselves [2]. Although some modifications occur at exactly the same nucleotide position in tRNAs from the three domains of life, many can be found at various positions in a particular tRNA and their location may vary between and within different tRNAs. With this wild array of chemical diversity and substrate specificities, one of the big challenges in the tRNA modification field has been to better understand at a molecular level the modes of substrate recognition by the different modification enzymes; in this realm RNA binding rests at the heart of the problem. This chapter will focus on several examples of modification enzymes where their mode of RNA binding is well understood; from these, we will try to draw general conclusions and highlight growing themes that may be applicable to the RNA modification field at large.

The Fungal Cell-Wall Integrity MAPK Cascade Is Crucial for Hyphal Network Formation and Maintenance of Restrictive Growth of Epichloë festucae in Symbiosis With Lolium perenne

Epichloë festucae is a mutualistic symbiont that systemically colonizes the intercellular spaces of Lolium perenne leaves to form a highly structured and interconnected hyphal network. In an Agrobacterium tumefaciens T-DNA forward genetic screen, we identified a mutant TM1066 that had a severe host interaction phenotype, causing stunting and premature senescence of the host. Molecular analysis revealed that the mutation responsible for this phenotype was in the cell-wall integrity (CWI) mitogen-activated protein kinase kinase (MAPKK), mkkA. Mutants generated by targeted deletion of the mkkA or the downstream mpkA kinase recapitulated the phenotypes observed for TM1066. Both mutants were defective in hyphal cell–cell fusion, formed intrahyphal hyphae, had enhanced conidiation, and showed microcyclic conidiation. Transmission electron microscopy and confocal microscopy analysis of leaf tissue showed that mutant hyphae were more abundant than the wild type in the intercellular spaces and colonized the vascular bundles. Hyphal branches failed to fuse but, instead, grew past one another to form bundles of convoluted hyphae. Mutant hyphae showed increased fluorescence with AF488-WGA, indicative of increased accessibility of chitin, a hypothesis supported by changes in the cell-wall ultrastructure. These results show that the CWI MAPK pathway is a key signaling pathway for controlling the mutualistic symbiotic interaction between E. festucae and L. perenne.

An arginine-aspartate network in the active site of bacterial TruB is critical for catalyzing pseudouridine formation

Pseudouridine synthases introduce the most common RNA modification and likely use the same catalytic mechanism. Besides a catalytic aspartate residue, the contributions of other residues for catalysis of pseudouridine formation are poorly understood. Here, we have tested the role of a conserved basic residue in the active site for catalysis using the bacterial pseudouridine synthase TruB targeting U55 in tRNAs. Substitution of arginine 181 with lysine results in a 2500-fold reduction of TruB's catalytic rate without affecting tRNA binding. Furthermore, we analyzed the function of a second-shell aspartate residue (D90) that is conserved in all TruB enzymes and interacts with C56 of tRNA. Site-directed mutagenesis, biochemical and kinetic studies reveal that this residue is not critical for substrate binding but influences catalysis significantly as replacement of D90 with glutamate or asparagine reduces the catalytic rate 30- and 50-fold, respectively. In agreement with molecular dynamics simulations of TruB wild type and TruB D90N, we propose an electrostatic network composed of the catalytic aspartate (D48), R181 and D90 that is important for catalysis by fine-tuning the D48-R181 interaction. Conserved, negatively charged residues similar to D90 are found in a number of pseudouridine synthases, suggesting that this might be a general mechanism.

Pseudouridine: still mysterious, but never a fake (uridine)!

Pseudouridine (Ψ) is the most abundant of >150 nucleoside modifications in RNA. Although Ψ was discovered as the first modified nucleoside more than half a century ago, neither the enzymatic mechanism of its formation, nor the function of this modification are fully elucidated. We present the consistent picture of Ψ synthases, their substrates and their substrate positions in model organisms of all domains of life as it has emerged to date and point out the challenges that remain concerning higher eukaryotes and the elucidation of the enzymatic mechanism.