Naturally Occurring tRNAs With Non-canonical Structures

Evolving Escherichia coli to use a tRNA with a non-canonical fold as an adaptor of the genetic code

All known bacterial tRNAs adopt the canonical cloverleaf 2D and L-shaped 3D structures. We aimed to explore whether alternative tRNA structures could be introduced in bacterial translation. To this end, we crafted a vitamin-based genetic system to evolve Escherichia coli toward activity of structurally non-canonical tRNAs. The system reliably couples (escape frequency <10-12) growth with the activities of a novel orthogonal histidine suppressor tRNA (HisTUAC) and of the cognate ARS (HisS) via suppression of a GTA valine codon in the mRNA of an enzyme in thiamine biosynthesis (ThiN). Suppression results in the introduction of an essential histidine and thereby confers thiamine prototrophy. We then replaced HisTUAC in the system with non-canonical suppressor tRNAs and selected for growth. A strain evolved to utilize mini HisT, a tRNA lacking the D-arm, and we identified the responsible mutation in an RNase gene (pnp) involved in tRNA degradation. This indicated that HisS, the ribosome, and EF-Tu accept mini HisT ab initio, which we confirmed genetically and through in vitro translation experiments. Our results reveal a previously unknown flexibility of the bacterial translation machinery for the accepted fold of the adaptor of the genetic code and demonstrate the power of the vitamin-based suppression system.

Associations of mitochondrial genomic variation with successful neurological aging

Mitochondrial health is an integral factor in aging, with mitochondrial dysfunction known to increase with age and contribute to the development of age-related neurodegenerative disorders. Additionally, the mitochondrial genome (mtDNA) has been shown to acquire potentially damaging somatic variation as part of the aging process, while mtDNA single nucleotide polymorphism (SNPs) have been shown to be both protective and detrimental for various neurodegenerative diseases. Yet, little is known about the involvement of mtDNA variation in longevity and successful neurological aging. In this study, we examined the association of mtDNA SNPs, in the form of mitochondrial haplogroups, with successful neurological aging in 1,405 unrelated neurologically healthy subjects. Although not quite significant after correcting for multiple testing (P < 0.0017 considered as significant), we detected a nominally significant association between the I haplogroup (N = 45, 3.2 %) and a younger age (β: -5.00, P = 0.006), indicating that this haplogroup is observed less frequently in older neurologically healthy individuals and may be associated with decreased survival. Replication of this finding in independent neurologically healthy cohorts will be imperative for shaping our understanding of the biological processes underlying healthy neurological aging.

The central role of transfer RNAs in mistranslation

Transfer RNAs (tRNA) are essential small non-coding RNAs that enable the translation of genomic information into proteins in all life forms. The principal function of tRNAs is to bring amino acid building blocks to the ribosomes for protein synthesis. In the ribosome, tRNAs interact with messenger RNA (mRNA) to mediate the incorporation of amino acids into a growing polypeptide chain following the rules of the genetic code. Accurate interpretation of the genetic code requires tRNAs to carry amino acids matching their anticodon identity and decode the correct codon on mRNAs. Errors in these steps cause the translation of codons with the wrong amino acids (mistranslation), compromising the accurate flow of information from DNA to proteins. Accumulation of mutant proteins due to mistranslation jeopardizes proteostasis and cellular viability. However, the concept of mistranslation is evolving, with increasing evidence indicating that mistranslation can be used as a mechanism for survival and acclimatization to environmental conditions. In this review, we discuss the central role of tRNAs in modulating translational fidelity through their dynamic and complex interplay with translation factors. We summarize recent discoveries of mistranslating tRNAs and describe the underlying molecular mechanisms and the specific conditions and environments that enable and promote mistranslation.

RNAscape: geometric mapping and customizable visualization of RNA structure

Analyzing and visualizing the tertiary structure and complex interactions of RNA is essential for being able to mechanistically decipher their molecular functions in vivo. Secondary structure visualization software can portray many aspects of RNA; however, these layouts are often unable to preserve topological correspondence since they do not consider tertiary interactions between different regions of an RNA molecule. Likewise, quaternary interactions between two or more interacting RNA molecules are not considered in secondary structure visualization tools. The RNAscape webserver produces visualizations that can preserve topological correspondence while remaining both visually intuitive and structurally insightful. RNAscape achieves this by designing a mathematical structural mapping algorithm which prioritizes the helical segments, reflecting their tertiary organization. Non-helical segments are mapped in a way that minimizes structural clutter. RNAscape runs a plotting script that is designed to generate publication-quality images. RNAscape natively supports non-standard nucleotides, multiple base-pairing annotation styles and requires no programming experience. RNAscape can also be used to analyze RNA/DNA hybrid structures and DNA topologies, including G-quadruplexes. Users can upload their own three-dimensional structures or enter a Protein Data Bank (PDB) ID of an existing structure. The RNAscape webserver allows users to customize visualizations through various settings as desired. URL: https://rnascape.usc.edu/.

Tuning tRNAs for improved translation

Transfer RNAs have been extensively explored as the molecules that translate the genetic code into proteins. At this interface of genetics and biochemistry, tRNAs direct the efficiency of every major step of translation by interacting with a multitude of binding partners. However, due to the variability of tRNA sequences and the abundance of diverse post-transcriptional modifications, a guidebook linking tRNA sequences to specific translational outcomes has yet to be elucidated. Here, we review substantial efforts that have collectively uncovered tRNA engineering principles that can be used as a guide for the tuning of translation fidelity. These principles have allowed for the development of basic research, expansion of the genetic code with non-canonical amino acids, and tRNA therapeutics.

Genomic factors shaping codon usage across the Saccharomycotina subphylum

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. The biased use of synonymous codons has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. The Saccharomycotina, the fungal subphylum containing the yeasts Saccharomyces cerevisiae and Candida albicans , has been a model system for studying codon usage. We characterized codon usage across 1,154 strains from 1,051 species to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns across the subphylum. We found evidence of a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is also distinct between the 12 orders within the subphylum to such a degree that yeasts can be classified into orders with an accuracy greater than 90% using a machine learning algorithm trained on codon usage. We also characterized the degree to which codon usage bias is impacted by translational selection. Interestingly, the degree of translational selection was influenced by a combination of genome features and assembly metrics that included the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs. The order contains 24 species, and 23 are computationally predicted to lack tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that extreme avoidance of the CGN codons is associated with a decline in arginine tRNA function. Codon usage bias within the Saccharomycotina is generally consistent with previous investigations in fungi, which show a role for both genomic features and GC bias in shaping codon usage. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

MILIP Binding to tRNAs Promotes Protein Synthesis to Drive Triple-Negative Breast Cancer

Patients with triple-negative breast cancer (TNBC) have a poor prognosis due to the lack of effective molecular targets for therapeutic intervention. Here we found that the long noncoding RNA (lncRNA) MILIP supports TNBC cell survival, proliferation, and tumorigenicity by complexing with transfer RNAs (tRNA) to promote protein production, thus representing a potential therapeutic target in TNBC. MILIP was expressed at high levels in TNBC cells that commonly harbor loss-of-function mutations of the tumor suppressor p53, and MILIP silencing suppressed TNBC cell viability and xenograft growth, indicating that MILIP functions distinctively in TNBC beyond its established role in repressing p53 in other types of cancers. Mechanistic investigations revealed that MILIP interacted with eukaryotic translation elongation factor 1 alpha 1 (eEF1α1) and formed an RNA-RNA duplex with the type II tRNAs tRNALeu and tRNASer through their variable loops, which facilitated the binding of eEF1α1 to these tRNAs. Disrupting the interaction between MILIP and eEF1α1 or tRNAs diminished protein synthesis and cell viability. Targeting MILIP inhibited TNBC growth and cooperated with the clinically available protein synthesis inhibitor omacetaxine mepesuccinate in vivo. Collectively, these results identify MILIP as an RNA translation elongation factor that promotes protein production in TNBC cells and reveal the therapeutic potential of targeting MILIP, alone and in combination with other types of protein synthesis inhibitors, for TNBC treatment.

SIGNIFICANCE

LncRNA MILIP plays a key role in supporting protein production in TNBC by forming complexes with tRNAs and eEF1α1, which confers sensitivity to combined MILIP targeting and protein synthesis inhibitors.

The complete mitochondrial genome of 3 species of allocreadiids (Digenea, Allocreadiidae): characterization and phylogenetic position within the order Plagiorchiida

Trematodes of the family Allocreadiidae are primarily found in the intestines of freshwater fishes around the world. The family includes 15 genera and c. 130 species. The last 2 decades have witnessed an increase in the genetic library of its species. Molecular data have been crucial for species delimitation and species description within Allocreadiidae and for understanding their evolutionary and biogeographical history and classification. Here, the mitogenomes of 3 species of allocreadiids were obtained using high throughput sequencing methods. Mitogenomes were compared with other members of the order Plagiorchiida to determine their molecular composition, gene rearrangement and phylogenetic interrelationships. The complete circular mitogenomes of Allocreadium lobatum, Creptotrematina aguirrepequenoi and Wallinia mexicana were 14 424, 13 769 and 13 924 bp long respectively, comprising 12 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes and 2 non-coding regions. Gene arrangements were identical to other Xiphidiatan trematodes. Phylogenetic analyses using the mitogenomes revealed Allocreadiidae as a monophyletic group closely related to other members of the suborder Xiphidiata; A. lobatum was yielded as the sister taxon of C. aguirrepequenoi + W. mexicana. Our study increases the complete mitochondrial genome library of trematodes and strengthens our understanding of the phylogenetic relationships and classification of this parasite group.

Biosynthesis, Engineering, and Delivery of Selenoproteins

Selenocysteine (Sec) was discovered as the 21st genetically encoded amino acid. In nature, site-directed incorporation of Sec into proteins requires specialized biosynthesis and recoding machinery that evolved distinctly in bacteria compared to archaea and eukaryotes. Many organisms, including higher plants and most fungi, lack the Sec-decoding trait. We review the discovery of Sec and its role in redox enzymes that are essential to human health and important targets in disease. We highlight recent genetic code expansion efforts to engineer site-directed incorporation of Sec in bacteria and yeast. We also review methods to produce selenoproteins with 21 or more amino acids and approaches to delivering recombinant selenoproteins to mammalian cells as new applications for selenoproteins in synthetic biology.

Identification of over ten thousand candidate structured RNAs in viruses and phages

Structured RNAs play crucial roles in viruses, exerting influence over both viral and host gene expression. However, the extensive diversity of structured RNAs and their ability to act in cis or trans positions pose challenges for predicting and assigning their functions. While comparative genomics approaches have successfully predicted candidate structured RNAs in microbes on a large scale, similar efforts for viruses have been lacking. In this study, we screened over 5 million DNA and RNA viral sequences, resulting in the prediction of 10,006 novel candidate structured RNAs. These predictions are widely distributed across taxonomy and ecosystem. We found transcriptional evidence for 206 of these candidate structured RNAs in the human fecal microbiome. These candidate RNAs exhibited evidence of nucleotide covariation, indicative of selective pressure maintaining the predicted secondary structures. Our analysis revealed a diverse repertoire of candidate structured RNAs, encompassing a substantial number of putative tRNAs or tRNA-like structures, Rho-independent transcription terminators, and potentially cis-regulatory structures consistently positioned upstream of genes. In summary, our findings shed light on the extensive diversity of structured RNAs in viruses, offering a valuable resource for further investigations into their functional roles and implications in viral gene expression and pave the way for a deeper understanding of the intricate interplay between viruses and their hosts at the molecular level.

Deciphering the Role of Selenoprotein M

Selenocysteine (Sec), the 21st amino acid, is structurally similar to cysteine but with a sulfur to selenium replacement. This single change retains many of the chemical properties of cysteine but often with enhanced catalytic and redox activity. Incorporation of Sec into proteins is unique, requiring additional translation factors and multiple steps to insert Sec at stop (UGA) codons. These Sec-containing proteins (selenoproteins) are found in all three domains of life where they often are involved in cellular homeostasis (e.g., reducing reactive oxygen species). The essential role of selenoproteins in humans requires us to maintain appropriate levels of selenium, the precursor for Sec, in our diet. Too much selenium is also problematic due to its toxic effects. Deciphering the role of Sec in selenoproteins is challenging for many reasons, one of which is due to their complicated biosynthesis pathway. However, clever strategies are surfacing to overcome this and facilitate production of selenoproteins. Here, we focus on one of the 25 human selenoproteins, selenoprotein M (SELENOM), which has wide-spread expression throughout our tissues. Its thioredoxin motif suggests oxidoreductase function; however, its mechanism and functional role(s) are still being uncovered. Furthermore, the connection of both high and low expression levels of SELENOM to separate diseases emphasizes the medical application for studying the role of Sec in this protein. In this review, we aim to decipher the role of SELENOM through detailing and connecting current evidence. With multiple proposed functions in diverse tissues, continued research is still necessary to fully unveil the role of SELENOM.

Recoding UAG to selenocysteine in Saccharomyces cerevisiae

Unique chemical and physical properties are introduced by inserting selenocysteine (Sec) at specific sites within proteins. Recombinant and facile production of eukaryotic selenoproteins would benefit from a yeast expression system; however, the selenoprotein biosynthetic pathway was lost in the evolution of the kingdom Fungi as it diverged from its eukaryotic relatives. Based on our previous development of efficient selenoprotein production in bacteria, we designed a novel Sec biosynthesis pathway in Saccharomyces cerevisiae using Aeromonas salmonicida translation components. S. cerevisiae tRNASer was mutated to resemble A. salmonicida tRNASec to allow recognition by S. cerevisiae seryl-tRNA synthetase as well as A. salmonicida selenocysteine synthase (SelA) and selenophosphate synthetase (SelD). Expression of these Sec pathway components was then combined with metabolic engineering of yeast to enable the production of active methionine sulfate reductase enzyme containing genetically encoded Sec. Our report is the first demonstration that yeast is capable of selenoprotein production by site-specific incorporation of Sec.

New insights into RNA processing by the eukaryotic tRNA splicing endonuclease

Through its role in intron cleavage, tRNA splicing endonuclease (TSEN) plays a critical function in the maturation of intron-containing pre-tRNAs. The catalytic mechanism and core requirement for this process is conserved between archaea and eukaryotes, but for decades, it has been known that eukaryotic TSENs have evolved additional modes of RNA recognition, which have remained poorly understood. Recent research identified new roles for eukaryotic TSEN, including processing or degradation of additional RNA substrates, and determined the first structures of pre-tRNA-bound human TSEN complexes. These recent discoveries have changed our understanding of how the eukaryotic TSEN targets and recognizes substrates. Here, we review these recent discoveries, their implications, and the new questions raised by these findings.

Surfactants or scaffolds? RNAs of varying lengths control the thermodynamic stability of condensates differently

Biomolecular condensates, thought to form via liquid-liquid phase separation of intracellular mixtures, are multicomponent systems that can include diverse types of proteins and RNAs. RNA is a critical modulator of RNA-protein condensate stability, as it induces an RNA concentration-dependent reentrant phase transition-increasing stability at low RNA concentrations and decreasing it at high concentrations. Beyond concentration, RNAs inside condensates can be heterogeneous in length, sequence, and structure. Here, we use multiscale simulations to understand how different RNA parameters interact with one another to modulate the properties of RNA-protein condensates. To do so, we perform residue/nucleotide resolution coarse-grained molecular dynamics simulations of multicomponent RNA-protein condensates containing RNAs of different lengths and concentrations, and either FUS or PR25 proteins. Our simulations reveal that RNA length regulates the reentrant phase behavior of RNA-protein condensates: increasing RNA length sensitively rises the maximum value that the critical temperature of the mixture reaches, and the maximum concentration of RNA that the condensate can incorporate before beginning to become unstable. Strikingly, RNAs of different lengths are organized heterogeneously inside condensates, which allows them to enhance condensate stability via two distinct mechanisms: shorter RNA chains accumulate at the condensate's surface acting as natural biomolecular surfactants, while longer RNA chains concentrate inside the core to saturate their bonds and enhance the density of molecular connections in the condensate. Using a patchy particle model, we additionally demonstrate that the combined impact of RNA length and concentration on condensate properties is dictated by the valency, binding affinity, and polymer length of the various biomolecules involved. Our results postulate that diversity on RNA parameters within condensates allows RNAs to increase condensate stability by fulfilling two different criteria: maximizing enthalpic gain and minimizing interfacial free energy; hence, RNA diversity should be considered when assessing the impact of RNA on biomolecular condensates regulation.

Rediscovery of Bipalium admarginatum de Beauchamp, 1933 (Platyhelminthes, Tricladida, Geoplanidae) in Malaysia, with molecular characterisation including the mitogenome

We present here the first observation of Bipalium admarginatum de Beauchamp, 1933 since its original description 90 years ago. Three specimens were found on Perhentian Kecil Island, off Terengganu State, Malaysia and photographed in the field, and two were collected. This report thus includes the first colour photographs published for this species, from a locality close to the type-locality, Tioman Island (which is ca. 200 km south of the locality in this study, on the east coast of Peninsula Malaysia). We describe the external morphology and colour pattern of the species, which correspond well to the original description, itself based only on two preserved specimens. We performed an in-depth molecular characterisation of the species, including its complete mitochondrial genome, the 18S sequence and elongation 1-alpha (EF1-α) sequence. In addition, EF1-α sequences were also retrieved for 5 additional geoplanid species. No tRNA-Thr could be detected in the mitogenome of B. admarginatum, a lack already reported in several species of geoplanids, but we found a 13 bp sequence that contains the anticodon loop and seems to be conserved among geoplanids and might thus possibly represent a non-canonical undetected tRNA. We discuss the difficulties encountered in trying to reconstruct the cluster of nuclear ribosomal genes, a problem already mentioned for other Triclads. Three phylogenies, based respectively on all mitochondrial proteins, 18S, and EF1-α, were computed; the position of B. admarginatum within the Bipaliinae was confirmed in each tree, as sister-group to various bipaliine species according to the sequences available for each tree. In the mitochondrial proteins tree, which had high support, B. admarginatum was sister to Bipalium kewense and Diversibipalium multilineatum.

The tRNA identity landscape for aminoacylation and beyond

tRNAs are key partners in ribosome-dependent protein synthesis. This process is highly dependent on the fidelity of tRNA aminoacylation by aminoacyl-tRNA synthetases and relies primarily on sets of identities within tRNA molecules composed of determinants and antideterminants preventing mischarging by non-cognate synthetases. Such identity sets were discovered in the tRNAs of a few model organisms, and their properties were generalized as universal identity rules. Since then, the panel of identity elements governing the accuracy of tRNA aminoacylation has expanded considerably, but the increasing number of reported functional idiosyncrasies has led to some confusion. In parallel, the description of other processes involving tRNAs, often well beyond aminoacylation, has progressed considerably, greatly expanding their interactome and uncovering multiple novel identities on the same tRNA molecule. This review highlights key findings on the mechanistics and evolution of tRNA and tRNA-like identities. In addition, new methods and their results for searching sets of multiple identities on a single tRNA are discussed. Taken together, this knowledge shows that a comprehensive understanding of the functional role of individual and collective nucleotide identity sets in tRNA molecules is needed for medical, biotechnological and other applications.

tRNA derived small RNAs—Small players with big roles

In the past 2 decades, small non-coding RNAs derived from tRNA (tsRNAs or tRNA derived fragments; tRFs) have emerged as new powerful players in the field of small RNA mediated regulation of gene expression, translation, and epigenetic control. tRFs have been identified from evolutionarily divergent organisms from Archaea, the higher plants, to humans. Recent studies have confirmed their roles in cancers and other metabolic disorders in humans and experimental models. They have been implicated in biotic and abiotic stress responses in plants as well. In this review, we summarize the current knowledge on tRFs including types of tRFs, their biogenesis, and mechanisms of action. The review also highlights recent studies involving differential expression profiling of tRFs and elucidation of specific functions of individual tRFs from various species. We also discuss potential considerations while designing experiments involving tRFs identification and characterization and list the available bioinformatics tools for this purpose.

RNA-As-Graphs Motif Atlas—Dual Graph Library of RNA Modules and Viral Frameshifting-Element Applications

RNA motif classification is important for understanding structure/function connections and building phylogenetic relationships. Using our coarse-grained RNA-As-Graphs (RAG) representations, we identify recurrent dual graph motifs in experimentally solved RNA structures based on an improved search algorithm that finds and ranks independent RNA substructures. Our expanded list of 183 existing dual graph motifs reveals five common motifs found in transfer RNA, riboswitch, and ribosomal 5S RNA components. Moreover, we identify three motifs for available viral frameshifting RNA elements, suggesting a correlation between viral structural complexity and frameshifting efficiency. We further partition the RNA substructures into 1844 distinct submotifs, with pseudoknots and junctions retained intact. Common modules are internal loops and three-way junctions, and three submotifs are associated with riboswitches that bind nucleotides, ions, and signaling molecules. Together, our library of existing RNA motifs and submotifs adds to the growing universe of RNA modules, and provides a resource of structures and substructures for novel RNA design.

Uncovering translation roadblocks during the development of a synthetic tRNA

Ribosomes are remarkable in their malleability to accept diverse aminoacyl-tRNA substrates from both the same organism and other organisms or domains of life. This is a critical feature of the ribosome that allows the use of orthogonal translation systems for genetic code expansion. Optimization of these orthogonal translation systems generally involves focusing on the compatibility of the tRNA, aminoacyl-tRNA synthetase, and a non-canonical amino acid with each other. As we expand the diversity of tRNAs used to include non-canonical structures, the question arises as to the tRNA suitability on the ribosome. Specifically, we investigated the ribosomal translation of allo-tRNAUTu1, a uniquely shaped (9/3) tRNA exploited for site-specific selenocysteine insertion, using single-molecule fluorescence. With this technique we identified ribosomal disassembly occurring from translocation of allo-tRNAUTu1 from the A to the P site. Using cryo-EM to capture the tRNA on the ribosome, we pinpointed a distinct tertiary interaction preventing fluid translocation. Through a single nucleotide mutation, we disrupted this tertiary interaction and relieved the translation roadblock. With the continued diversification of genetic code expansion, our work highlights a targeted approach to optimize translation by distinct tRNAs as they move through the ribosome.

Machine Learning Algorithms Highlight tRNA Information Content and Chargaff’s Second Parity Rule Score as Important Features in Discriminating Probiotics from Non-Probiotics

Simple Summary

Probiotics are a group of beneficial microorganisms that are symbionts of the human gut microbiome. The identification of new probiotics is therefore of paramount importance from both public health and commercial perspectives. In this study, we show for the first time that Artificial Intelligence algorithms can identify novel probiotics and also discriminate them from pathogenic organisms in the human gut. We were also able to determine the information content within tRNA sequences as the key genomic features capable of characterizing probiotics.

Abstract

Probiotic bacteria are microorganisms with beneficial effects on human health and are currently used in numerous food supplements. However, no selection process is able to effectively distinguish probiotics from non-probiotic organisms on the basis of their genomic characteristics. In the current study, four Machine Learning algorithms were employed to accurately identify probiotic bacteria based on their DNA characteristics. Although the prediction accuracies of all algorithms were excellent, the Neural Network returned the highest scores in all the evaluation metrics, managing to discriminate probiotics from non-probiotics with an accuracy greater than 90%. Interestingly, our analysis also highlighted the information content of the tRNA sequences as the most important feature in distinguishing the two groups of organisms probably because tRNAs have regulatory functions and might have allowed probiotics to evolve faster in the human gut environment. Through the methodology presented here, it was also possible to identify seven promising new probiotics that have a higher information content in their tRNA sequences compared to non-probiotics. In conclusion, we prove for the first time that Machine Learning methods can discriminate human probiotic from non-probiotic organisms underlining information within tRNA sequences as the most important genomic feature in distinguishing them.

tiRNAs: Insights into Their Biogenesis, Functions, and Future Applications in Livestock Research

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) belong to a group of transfer ribonucleic acid (tRNA)-derived fragments that have recently gained interest as molecules with specific biological functions. Their involvement in the regulation of physiological processes and pathological phenotypes suggests molecular roles similar to those of miRNAs. tsRNA biogenesis under specific physiological conditions will offer new perspectives in understanding diseases, and may provide new sources for biological marker design to determine and monitor the health status of farm animals. In this review, we focus on the latest discoveries about tsRNAs and give special attention to molecules initially thought to be mainly associated with tRNA-derived stress-induced RNAs (tiRNAs). We present an outline of their biological functions, offer a collection of useful databases, and discuss future research perspectives and applications in livestock basic and applied research.

The bacterial yjdF riboswitch regulates translation through its tRNA-like fold

Unlike most riboswitches, which have one cognate effector, the bacterial yjdF riboswitch binds to diverse azaaromatic compounds, only a subset of which cause it to activate translation. We examined the yjdF aptamer domain by small-angle X-ray scattering, and found that in the presence of activating ligands, the RNA adopts an overall shape similar to that of tRNA. Sequence analyses suggested that the yjdF aptamer is a homolog of tRNA^Lys, and that two of the conserved loops of the riboswitch are equivalent to the D- and T-loops of tRNA, associating to form an elbow-like tertiary interaction. Chemical probing indicated that this association is promoted by activating ligands such as chelerythrine and harmine. In its native mRNA context, activator ligands stabilize the tRNA-like fold of the yjdF aptamer, outcompeting the attenuated state in which its T-loop base-pairs to the Shine-Dalgarno element of the mRNA. Moreover, we demonstrate that the liganded aptamer itself activates translation, as authentic tRNAs, when grafted into mRNA, can potently activate translation. Taken together, our data demonstrate the ability of tRNA to function as a small-molecule responsive cis regulatory element.

Harnessing selenocysteine to enhance microbial cell factories for hydrogen production

Hydrogen is a clean, renewable energy source, that when combined with oxygen, produces heat and electricity with only water vapor as a biproduct. Furthermore, it has the highest energy content by weight of all known fuels. As a result, various strategies have engineered methods to produce hydrogen efficiently and in quantities that are of interest to the economy. To approach the notion of producing hydrogen from a biological perspective, we take our attention to hydrogenases which are naturally produced in microbes. These organisms have the machinery to produce hydrogen, which when cleverly engineered, could be useful in cell factories resulting in large production of hydrogen. Not all hydrogenases are efficient at hydrogen production, and those that are, tend to be oxygen sensitive. Therefore, we provide a new perspective on introducing selenocysteine, a highly reactive proteinogenic amino acid, as a strategy towards engineering hydrogenases with enhanced hydrogen production, or increased oxygen tolerance.

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.

The Evolutionary Fate of Mitochondrial Aminoacyl-tRNA Synthetases in Amitochondrial Organisms

During the endosymbiotic evolution of mitochondria, the genes for aminoacyl-tRNA synthetases were transferred to the ancestral nucleus. A further reduction of mitochondrial function resulted in mitochondrion-related organisms (MRO) with a loss of the organelle genome. The fate of the now redundant ancestral mitochondrial aminoacyl-tRNA synthetase genes is uncertain. The derived protein sequence for arginyl-tRNA synthetase from thirty mitosomal organisms have been classified as originating from the ancestral nuclear or mitochondrial gene and compared to the identity element at position 20 of the cognate tRNA that distinguishes the two enzyme forms. The evolutionary choice between loss and retention of the ancestral mitochondrial gene for arginyl-tRNA synthetase reflects the coevolution of arginyl-tRNA synthetase and tRNA identity elements.

Characterization of the complete mitochondrial genome of the swine kidney worm Stephanurus dentatus (Nematoda: Syngamidae) and phylogenetic implications

Swine stephanuriasis caused by kidney worm Stephanurus dentatus is a parasitic disease in tropical and subtropical countries, leading to economic losses. Despite its significance as a pathogen, the phylogenetic position and taxonomic status of this nematode remain poorly understood. Mitochondrial (mt) genome sequences are known to provide useful genetic markers for investigations in these areas, but mt genome sequences are lacking for S. dentatus. In the present study, we determined the complete mt genome sequences of S. dentatus with an Illumina platform and compared it with the mt genomes of other closely related species. The circular mt genome was 13,735 bp in size with 36 genes. All genes are transcribed in the same direction and the mt gene arrangement is identified as a GA3 pattern, that is the most common pattern of gene arrangement observed in nematodes to date. Phylogenetic analysis using concatenated amino acid sequences of 12 protein-coding genes supported the hypothesis that S. dentatus was closely related to the family Chabertiidae. Our results provided insights into the phylogenetic relationship of the family Syngamidae within the superfamily Strongyloidea.