Bypassing rRNA methylation by RsmA/Dim1during ribosome maturation in the hyperthermophilic archaeon Nanoarchaeum equitans

The role of m5C methyltransferases in cardiovascular diseases

The global leading cause of death is cardiovascular disease (CVD). Although advances in prevention and treatment have been made, the role of RNA epigenetics in CVD is not fully understood. Studies have found that RNA modifications regulate gene expression in mammalian cells, and m5C (5-methylcytosine) is a recently discovered RNA modification that plays a role in gene regulation. As a result of these developments, there has been renewed interest in elucidating the nature and function of RNA "epitranscriptomic" modifications. Recent studies on m5C RNA methylomes, their functions, and the proteins that initiate, translate and manipulate this modification are discussed in this review. This review improves the understanding of m5C modifications and their properties, functions, and implications in cardiac pathologies, including cardiomyopathy, heart failure, and atherosclerosis.

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.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Ribosome Biogenesis in Archaea

Making ribosomes is a major cellular process essential for the maintenance of functional ribosome homeostasis and to ensure appropriate gene expression. Strikingly, although ribosomes are universally conserved ribonucleoprotein complexes decoding the genetic information contained in messenger RNAs into proteins, their biogenesis shows an intriguing degree of variability across the tree of life. In this review, we summarize our knowledge on the least understood ribosome biogenesis pathway: the archaeal one. Furthermore, we highlight some evolutionary conserved and divergent molecular features of making ribosomes across the tree of life.

Insights into synthesis and function of KsgA/Dim1-dependent rRNA modifications in archaea

Ribosomes are intricate molecular machines ensuring proper protein synthesis in every cell. Ribosome biogenesis is a complex process which has been intensively analyzed in bacteria and eukaryotes. In contrast, our understanding of the in vivo archaeal ribosome biogenesis pathway remains less characterized. Here, we have analyzed the in vivo role of the almost universally conserved ribosomal RNA dimethyltransferase KsgA/Dim1 homolog in archaea. Our study reveals that KsgA/Dim1-dependent 16S rRNA dimethylation is dispensable for the cellular growth of phylogenetically distant archaea. However, proteomics and functional analyses suggest that archaeal KsgA/Dim1 and its rRNA modification activity (i) influence the expression of a subset of proteins and (ii) contribute to archaeal cellular fitness and adaptation. In addition, our study reveals an unexpected KsgA/Dim1-dependent variability of rRNA modifications within the archaeal phylum. Combining structure-based functional studies across evolutionary divergent organisms, we provide evidence on how rRNA structure sequence variability (re-)shapes the KsgA/Dim1-dependent rRNA modification status. Finally, our results suggest an uncoupling between the KsgA/Dim1-dependent rRNA modification completion and its release from the nascent small ribosomal subunit. Collectively, our study provides additional understandings into principles of molecular functional adaptation, and further evolutionary and mechanistic insights into an almost universally conserved step of ribosome synthesis.

The hyperthermophilic partners Nanoarchaeum and Ignicoccus stabilize their tRNA T-loops via different but structurally equivalent modifications

The universal L-shaped tertiary structure of tRNAs is maintained with the help of nucleotide modifications within the D- and T-loops, and these modifications are most extensive within hyperthermophilic species. The obligate-commensal Nanoarchaeum equitans and its phylogenetically-distinct host Ignicoccus hospitalis grow physically coupled under identical hyperthermic conditions. We report here two fundamentally different routes by which these archaea modify the key conserved nucleotide U54 within their tRNA T-loops. In N. equitans, this nucleotide is methylated by the S-adenosylmethionine-dependent enzyme NEQ053 to form m⁵U54, and a recombinant version of this enzyme maintains specificity for U54 in Escherichia coli. In N. equitans, m⁵U54 is subsequently thiolated to form m⁵s²U54. In contrast, I. hospitalis isomerizes U54 to pseudouridine prior to methylating its N1-position and thiolating the O4-position of the nucleobase to form the previously uncharacterized nucleotide m¹s⁴Ψ. The methyl and thiol groups in m¹s⁴Ψ and m⁵s²U are presented within the T-loop in a spatially identical manner that stabilizes the 3′-endo-anti conformation of nucleotide-54, facilitating stacking onto adjacent nucleotides and reverse-Hoogsteen pairing with nucleotide m¹A58. Thus, two distinct structurally-equivalent solutions have evolved independently and convergently to maintain the tertiary fold of tRNAs under extreme hyperthermic conditions.

PCOSKBR2: a database of genes, diseases, pathways, and networks associated with polycystic ovary syndrome

PolyCystic Ovary Syndrome KnowledgeBase (PCOSKBR2) is a manually curated database with information on 533 genes, 145 SNPs, 29 miRNAs, 1,150 pathways, and 1,237 diseases associated with PCOS. This data has been retrieved based on evidence gleaned by critically reviewing literature and related records available for PCOS in databases such as KEGG, DisGeNET, OMIM, GO, Reactome, STRING, and dbSNP. Since PCOS is associated with multiple genes and comorbidities, data mining algorithms for comorbidity prediction and identification of enriched pathways and hub genes are integrated in PCOSKBR2, making it an ideal research platform for PCOS. PCOSKBR2 is freely accessible at http://www.pcoskb.bicnirrh.res.in/ .

RbfA and IF3 couple ribosome biogenesis and translation initiation to increase stress tolerance

Bacterial ribosome biogenesis and translation occur in the same cellular compartment. Therefore, a biochemical gate-keeping step is required to prevent error-prone immature ribosomes from engaging in protein synthesis. Here, we provide evidence for a previously unknown quality control mechanism in which the abundant ribosome assembly factor, RbfA, suppresses protein synthesis by immature Escherichia coli 30S subunits. After 30S maturation, RbfA is displaced by initiation factor 3 (IF3), which promotes translation initiation. Genetic interactions between RbfA and IF3 show that RbfA release by IF3 is important during logarithmic growth as well as during stress encountered during stationary phase, low nutrition, low temperature, and antibiotics. By gating the transition from 30S biogenesis to translation initiation, RbfA and IF3 maintain the fidelity of bacterial protein synthesis.

Cryo-EM study of an archaeal 30S initiation complex gives insights into evolution of translation initiation

Archaeal translation initiation occurs within a macromolecular complex containing the small ribosomal subunit (30S) bound to mRNA, initiation factors aIF1, aIF1A and the ternary complex aIF2:GDPNP:Met-tRNA_i^Met. Here, we determine the cryo-EM structure of a 30S:mRNA:aIF1A:aIF2:GTP:Met-tRNA_i^Met complex from Pyrococcus abyssi at 3.2 Å resolution. It highlights archaeal features in ribosomal proteins and rRNA modifications. We find an aS21 protein, at the location of eS21 in eukaryotic ribosomes. Moreover, we identify an N-terminal extension of archaeal eL41 contacting the P site. We characterize 34 N⁴-acetylcytidines distributed throughout 16S rRNA, likely contributing to hyperthermostability. Without aIF1, the 30S head is stabilized and initiator tRNA is tightly bound to the P site. A network of interactions involving tRNA, mRNA, rRNA modified nucleotides and C-terminal tails of uS9, uS13 and uS19 is observed. Universal features and domain-specific idiosyncrasies of translation initiation are discussed in light of ribosomal structures from representatives of each domain of life.

Structural and evolutionary insights into ribosomal RNA methylation

Methylation of nucleotides in ribosomal RNAs (rRNAs) is a ubiquitous feature that occurs in all living organisms. Identification of all enzymes responsible for rRNA methylation, as well as mapping of all modified rRNA residues, is now complete for a number of model species, such as Escherichia coli and Saccharomyces cerevisiae. Recent high-resolution structures of bacterial ribosomes provided the first direct visualization of methylated nucleotides. The structures of ribosomes from various organisms and organelles have also lately become available, enabling comparative structure-based analysis of rRNA methylation sites in various taxonomic groups. In addition to the conserved core of modified residues in ribosomes from the majority of studied organisms, structural analysis points to the functional roles of some of the rRNA methylations, which are discussed in this Review in an evolutionary context.

Structural basis for substrate binding and catalytic mechanism of a human RNA:m5C methyltransferase NSun6

5-methylcytosine (m⁵C) modifications of RNA are ubiquitous in nature and play important roles in many biological processes such as protein translational regulation, RNA processing and stress response. Aberrant expressions of RNA:m⁵C methyltransferases are closely associated with various human diseases including cancers. However, no structural information for RNA-bound RNA:m⁵C methyltransferase was available until now, hindering elucidation of the catalytic mechanism behind RNA:m⁵C methylation. Here, we have solved the structures of NSun6, a human tRNA:m⁵C methyltransferase, in the apo form and in complex with a full-length tRNA substrate. These structures show a non-canonical conformation of the bound tRNA, rendering the base moiety of the target cytosine accessible to the enzyme for methylation. Further biochemical assays reveal the critical, but distinct, roles of two conserved cysteine residues for the RNA:m⁵C methylation. Collectively, for the first time, we have solved the complex structure of a RNA:m5C methyltransferase and addressed the catalytic mechanism of the RNA:m⁵C methyltransferase family, which may allow for structure-based drug design toward RNA:m⁵C methyltransferase–related diseases.