An improved estimation of tRNA expression to better elucidate the coevolution between tRNA abundance and codon usage in bacteria

Selective and non-selective evolutionary signatures found in the simplest replicative biological entities

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

Differential Selection for Translation Efficiency Shapes Translation Machineries in Bacterial Species

Different bacterial species have dramatically different generation times, from 20-30 min in Escherichia coli to about two weeks in Mycobacterium leprae. The translation machinery in a cell needs to synthesize all proteins for a new cell in each generation. The three subprocesses of translation, i.e., initiation, elongation, and termination, are expected to be under stronger selection pressure to optimize in short-generation bacteria (SGB) such as Vibrio natriegens than in the long-generation Mycobacterium leprae. The initiation efficiency depends on the start codon decoded by the initiation tRNA, the optimal Shine-Dalgarno (SD) decoded by the anti-SD (aSD) sequence on small subunit rRNA, and the secondary structure that may embed the initiation signals and prevent them from being decoded. The elongation efficiency depends on the tRNA pool and codon usage. The termination efficiency in bacteria depends mainly on the nature of the stop codon and the nucleotide immediately downstream of the stop codon. By contrasting SGB with long-generation bacteria (LGB), we predict (1) SGB to have more ribosome RNA operons to produce ribosomes, and more tRNA genes for carrying amino acids to ribosomes, (2) SGB to have a higher percentage of genes using AUG as the start codon and UAA as the stop codon than LGB, (3) SGB to exhibit better codon and anticodon adaptation than LGB, and (4) SGB to have a weaker secondary structure near the translation initiation signals than LGB. These differences between SGB and LGB should be more pronounced in highly expressed genes than the rest of the genes. We present empirical evidence in support of these predictions.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

The distinct translational landscapes of gram-negative Salmonella and gram-positive Listeria

Translational control in pathogenic bacteria is fundamental to gene expression and affects virulence and other infection phenotypes. We used an enhanced ribosome profiling protocol coupled with parallel transcriptomics to capture accurately the global translatome of two evolutionarily distant pathogenic bacteria-the Gram-negative bacterium Salmonella and the Gram-positive bacterium Listeria. We find that the two bacteria use different mechanisms to translationally regulate protein synthesis. In Salmonella, in addition to the expected correlation between translational efficiency and cis-regulatory features such as Shine-Dalgarno (SD) strength and RNA secondary structure around the initiation codon, our data reveal an effect of the 2nd and 3rd codons, where the presence of tandem lysine codons (AAA-AAA) enhances translation in both Salmonella and E. coli. Strikingly, none of these features are seen in efficiently translated Listeria transcripts. Instead, approximately 20% of efficiently translated Listeria genes exhibit 70 S footprints seven nt upstream of the authentic start codon, suggesting that these genes may be subject to a novel translational initiation mechanism. Our results show that SD strength is not a direct hallmark of translational efficiency in all bacteria. Instead, Listeria has evolved additional mechanisms to control gene expression level that are distinct from those utilised by Salmonella and E. coli.

Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions

The Sc2.0 project is building a eukaryotic synthetic genome from scratch. A major milestone has been achieved with all individual Sc2.0 chromosomes assembled. Here, we describe the consolidation of multiple synthetic chromosomes using advanced endoreduplication intercrossing with tRNA expression cassettes to generate a strain with 6.5 synthetic chromosomes. The 3D chromosome organization and transcript isoform profiles were evaluated using Hi-C and long-read direct RNA sequencing. We developed CRISPR Directed Biallelic URA3-assisted Genome Scan, or "CRISPR D-BUGS," to map phenotypic variants caused by specific designer modifications, known as "bugs." We first fine-mapped a bug in synthetic chromosome II (synII) and then discovered a combinatorial interaction associated with synIII and synX, revealing an unexpected genetic interaction that links transcriptional regulation, inositol metabolism, and tRNASerCGA abundance. Finally, to expedite consolidation, we employed chromosome substitution to incorporate the largest chromosome (synIV), thereby consolidating >50% of the Sc2.0 genome in one strain.

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

cdsBERT - Extending Protein Language Models with Codon Awareness

Recent advancements in Protein Language Models (pLMs) have enabled high-throughput analysis of proteins through primary sequence alone. At the same time, newfound evidence illustrates that codon usage bias is remarkably predictive and can even change the final structure of a protein. Here, we explore these findings by extending the traditional vocabulary of pLMs from amino acids to codons to encapsulate more information inside CoDing Sequences (CDS). We build upon traditional transfer learning techniques with a novel pipeline of token embedding matrix seeding, masked language modeling, and student-teacher knowledge distillation, called MELD. This transformed the pretrained ProtBERT into cdsBERT; a pLM with a codon vocabulary trained on a massive corpus of CDS. Interestingly, cdsBERT variants produced a highly biochemically relevant latent space, outperforming their amino acid-based counterparts on enzyme commission number prediction. Further analysis revealed that synonymous codon token embeddings moved distinctly in the embedding space, showcasing unique additions of information across broad phylogeny inside these traditionally "silent" mutations. This embedding movement correlated significantly with average usage bias across phylogeny. Future fine-tuned organism-specific codon pLMs may potentially have a more significant increase in codon usage fidelity. This work enables an exciting potential in using the codon vocabulary to improve current state-of-the-art structure and function prediction that necessitates the creation of a codon pLM foundation model alongside the addition of high-quality CDS to large-scale protein databases.

The organellar genomes of Pellidae (Marchantiophyta): the evidence of cryptic speciation, conflicting phylogenies and extraordinary reduction of mitogenomes in simple thalloid liverwort lineage

Organellar genomes of liverworts are considered as one of the most stable among plants, with rare events of gene loss and structural rearrangements. However, not all lineages of liverworts are equally explored in the field of organellar genomics, and subclass Pellidae is one of the less known. Hybrid assembly, using both short- and long-read technologies enabled the assembly of repeat-rich mitogenomes of Pellia and Apopellia revealing extraordinary reduction of length in the latter which impacts only intergenic spacers. The mitogenomes of Apopellia were revealed to be the smallest among all known liverworts-109 k bp, despite retaining all introns. The study also showed the loss of one tRNA gene in Apopellia mitogenome, although it had no impact on the codon usage pattern of mitochondrial protein coding genes. Moreover, it was revealed that Apopellia and Pellia differ in codon usage by plastome CDSs, despite identical tRNA gene content. Molecular identification of species is especially important where traditional taxonomic methods fail, especially within Pellidae where cryptic speciation is well recognized. The simple morphology of these species and a tendency towards environmental plasticity make them complicated in identification. Application of super-barcodes, based on complete mitochondrial or plastid genomes sequences enable identification of all cryptic lineages within Apopellia and Pellia genera, however in some particular cases, mitogenomes were more efficient in species delimitation than plastomes.

Ribonucleosides from tRNA in hyperglycemic mammalian cells and diabetic murine cardiac models

AIMS

Cardiomyopathy is a diabetic comorbidity with few molecular targets. To address this, we evaluated transfer RNA (tRNA) modifications in the diabetic heart because tRNA modifications have been implicated in diabetic etiologies.

MAIN METHODS

tRNA was isolated from aorta, apex, and atrial tissue of healthy and diabetic murine hearts and related hyperglycemic cell models. tRNA modifications and canonical ribonucleosides were quantified by liquid-chromatography tandem mass spectrometry (LC-MS/MS) using stable isotope dilution. Correlations between ribonucleosides and diabetic comorbidity pathology were assessed using statistical analyses.

KEY FINDINGS

Total tRNA ribonucleoside levels were analyzed from cell types and healthy and diabetic murine heart tissue. Each heart structure had characteristic ribonucleoside profiles and quantities. Several ribonucleosides were observed as significantly different in hyperglycemic cells and diabetic tissues. In hyperglycemic models, ribonucleosides N4-acetylcytidine (ac4C), 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U), 5-methylcytidine (m5C), and N1-methylguanosine (m1G) were anomalous. Specific tRNA modifications known to be on murine tRNAIni(CAU) were higher in diabetic heart tissue which suggests that tRNA modifications could be regulating translation in diabetes.

SIGNIFICANCE

We identified tRNA ribonucleosides and tRNA species associated with hyperglycemia and diabetic etiology.

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Protein abundance is crucial for the majority of genetically regulated cell functions to act properly in prokaryotic organisms. Therefore, developing bioinformatic methods for assessing the efficiency of different stages of gene expression is of great importance for predicting the actual protein abundance. One of these steps is the evaluation of translation elongation efficiency based on mRNA sequence features, such as codon usage bias and mRNA secondary structure properties. In this study, we have evaluated correlation coefficients between experimentally measured protein abundance and predicted elongation efficiency characteristics for 26 prokaryotes, including non-model organisms, belonging to diverse taxonomic groups The algorithm for assessing elongation efficiency takes into account not only codon bias, but also number and energy of secondary structures in mRNA if those demonstrate an impact on predicted elongation efficiency of the ribosomal protein genes. The results show that, for a number of organisms, secondary structures are a better predictor of protein abundance than codon usage bias. The bioinformatic analysis has revealed several factors associated with the value of the correlation coefficient. The first factor is the elongation efficiency optimization type-the organisms whose genomes are optimized for codon usage only have significantly higher correlation coefficients. The second factor is taxonomical identity-bacteria that belong to the class Bacilli tend to have higher correlation coefficients among the analyzed set. The third is growth rate, which is shown to be higher for the organisms with higher correlation coefficients between protein abundance and predicted translation elongation efficiency. The obtained results can be useful for further improvement of methods for protein abundance prediction.

tRNA methylation resolves codon usage bias at the limit of cell viability

Codon usage of each genome is closely correlated with the abundance of tRNA isoacceptors. How codon usage bias is resolved by tRNA post-transcriptional modifications is largely unknown. Here we demonstrate that the N¹-methylation of guanosine at position 37 (m¹G37) on the 3′-side of the anticodon, while not directly responsible for reading of codons, is a neutralizer that resolves differential decoding of proline codons. A genome-wide suppressor screen of a non-viable Escherichia coli strain, lacking m¹G37, identifies proS suppressor mutations, indicating a coupling of methylation with tRNA prolyl-aminoacylation that sets the limit of cell viability. Using these suppressors, where prolyl-aminoacylation is decoupled from tRNA methylation, we show that m¹G37 neutralizes differential translation of proline codons by the major isoacceptor. Lack of m¹G37 inactivates this neutralization and exposes the need for a minor isoacceptor for cell viability. This work has medical implications for bacterial species that exclusively use the major isoacceptor for survival.

Masuda et al. show that loss of m¹G37 from the 3′ side of the tRNA anticodon renders a modified wobble nucleotide of the anticodon insufficient to decode a set of rare codons, providing a functional underpinning for the “modification circuit” between position 37 and the wobble position of the tRNA anticodon.

Translation Comes First: Ancient and Convergent Selection of Codon Usage Bias Across Prokaryotic Genomes

Codon usage is the outcome of different evolutionary processes and can inform us about the conditions in which organisms live and evolve. Here, we present R_ENC', which is an improvement to the original S index developed by dos Reis et al. (2004). Our index is less sensitive to G+C content, which greatly affects synonymous codon usage in prokaryotes, making it better suited to detect selection acting on codon usage. We used R_ENC' to estimate the extent of selected codon usage bias in 1800 genomes representing 26 prokaryotic phyla. We found that Gammaproteobacteria, Betaproteobacteria, Actinobacteria, and Firmicutes are the phyla/subphyla showing more genomes with selected codon usage bias. In particular, we found that several lineages within Gammaproteobacteria and Firmicutes show a similar set of functional terms enriched in genes under selected codon usage bias, indicating convergent evolution. We also show that selected codon usage bias tends to evolve in genes coding for the translation machinery before other functional GO terms. Finally, we discuss the possibility to use R_ENC' to predict whether lineages evolved in copiotrophic or oligotrophic environments.

Setting Up a Better Infection: Overexpression of the Early Bacteriophage T4 Gene motB During Infection Results in a More Favorable tRNA Pool for the Phage

BACKGROUND

: Although many bacteriophage T4 early genes are nonessential with unknown functions, they are believed to aid in the takeover of the Escherichia coli host. Understanding the functions of these genes could be helpful to develop novel antibacterial strategies. MotB, encoded by a previously uncharacterized T4 early gene, is a DNA-binding protein that compacts the host nucleoid and alters host gene expression.

METHODS

: MotB structure was predicted by AlphaFold 2. RNA-seq and mass spectrometry (MS) analyses were performed to determine RNA and protein changes when motB was overexpressed in E. coli BL21(DE3) ±5 min T4 infection.

RESULTS

: MotB structure is predicted to be a two-domain protein with N-terminal Kyprides-Onzonis-Woese and C-terminal oligonucleotide/oligosaccharide-fold domains. In E. coli B, motB overexpression during infection does not affect T4 RNAs, but affects the expression of host genes, including the downregulation of 21 of the 84 chargeable host tRNAs. Many of these tRNAs are used less frequently by T4 or have a counterpart encoded within the T4 genome. The MS analyses indicate that the levels of multiple T4 proteins are changed by motB overexpression.

CONCLUSION

: Our results suggest that in this E. coli B host, motB is involved in establishing a more favorable tRNA pool for the phage during infection.

Preferred synonymous codons are translated more accurately: Proteomic evidence, among-species variation, and mechanistic basis

A commonly stated cause of unequal uses of synonymous codons is their differential translational accuracies. A key prediction of this long-standing translational accuracy hypothesis (TAH) of codon usage bias is higher translational accuracies of more frequently used synonymous codons, which, however, has had no direct evidence beyond case studies. Analyzing proteomic data from Escherichia coli, we present direct, global evidence for this prediction. The experimentally measured codon-specific translational accuracies validate a sequence-based proxy; this proxy provides support for the TAH from the vast majority of over 1000 taxa surveyed in all domains of life. We find that the relative translational accuracies of synonymous codons vary substantially among taxa and are strongly correlated with the amounts of cognate transfer RNAs (tRNAs) relative to those of near-cognate tRNAs. These and other observations suggest a model in which selections for translational efficiency and accuracy drive codon usage bias and its coevolution with the tRNA pool.

Genome-wide analysis of the in vivo tRNA structurome reveals RNA structural and modification dynamics under heat stress

RNA structure plays roles in myriad cellular events including transcription, translation, and RNA processing. Genome-wide analyses of RNA secondary structure in vivo by chemical probing have revealed critical structural features of mRNAs and long ncRNAs. Here, we examine the in vivo secondary structure of a small RNA class, tRNAs. Study of tRNA structure is challenging because tRNAs are heavily modified and strongly structured. We introduce "tRNA structure-seq," a new workflow that accurately determines in vivo secondary structures of tRNA. The workflow combines dimethyl sulfate (DMS) probing, ultra-processive RT, and mutational profiling (MaP), which provides mutations opposite DMS and natural modifications thereby allowing multiple modifications to be identified in a single read. We applied tRNA structure-seq to E. coli under control and stress conditions. A leading folding algorithm predicts E. coli tRNA structures with only ∼80% average accuracy from sequence alone. Strikingly, tRNA structure-seq, by providing experimental restraints, improves structure prediction under in vivo conditions to ∼95% accuracy, with more than 14 tRNAs predicted completely correctly. tRNA structure-seq also quantifies the relative levels of tRNAs and their natural modifications at single nucleotide resolution, as validated by LC-MS/MS. Our application of tRNA structure-seq yields insights into tRNA structure in living cells, revealing that it is not immutable but has dynamics, with partial unfolding of secondary and tertiary tRNA structure under heat stress that is correlated with a loss of tRNA abundance. This method is applicable to other small RNAs, including those with natural modifications and highly structured regions.

Identification and functional implications of pseudouridine RNA modification on small noncoding RNAs in the mammalian pathogen Trypanosoma brucei

Trypanosoma brucei, the parasite that causes sleeping sickness, cycles between an insect and a mammalian host. However, the effect of RNA modifications such as pseudouridinylation on its ability to survive in these two different host environments is unclear. Here, two genome-wide approaches were applied for mapping pseudouridinylation sites (Ψs) on small nucleolar RNA (snoRNA), 7SL RNA, vault RNA, and tRNAs from T. brucei. We show using HydraPsiSeq and RiboMeth-seq that the Ψ on C/D snoRNA guiding 2'-O-methylation increased the efficiency of the guided modification on its target, rRNA. We found differential levels of Ψs on these noncoding RNAs in the two life stages (insect host and mammalian host) of the parasite. Furthermore, tRNA isoform abundance and Ψ modifications were characterized in these two life stages demonstrating stage-specific regulation. We conclude that the differential Ψ modifications identified here may contribute to modulating the function of noncoding RNAs involved in rRNA processing, rRNA modification, protein synthesis, and protein translocation during cycling of the parasite between its two hosts.

Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon

Synonymous codons translate into chemically identical amino acids. Once considered inconsequential to the formation of the protein product, there is evidence to suggest that codon usage affects co-translational protein folding and the final structure of the expressed protein. Here we develop a method for computing and comparing codon-specific Ramachandran plots and demonstrate that the backbone dihedral angle distributions of some synonymous codons are distinguishable with statistical significance for some secondary structures. This shows that there exists a dependence between codon identity and backbone torsion of the translated amino acid. Although these findings cannot pinpoint the causal direction of this dependence, we discuss the vast biological implications should coding be shown to directly shape protein conformation and demonstrate the usefulness of this method as a tool for probing associations between codon usage and protein structure. Finally, we urge for the inclusion of exact genetic information into structural databases.

Characterization of tRNA expression profiles in large offspring syndrome

Background

Assisted Reproductive Technologies (ART) use can increase the risk of congenital overgrowth syndromes, such as large offspring syndrome (LOS) in ruminants. Epigenetic variations are known to influence gene expression and differentially methylated regions (DMRs) were previously determined to be associated with LOS in cattle. We observed DMRs overlapping tRNA clusters which could affect tRNA abundance and be associated with tissue specificity or overgrowth. Variations in tRNA expression have been identified in several disease pathways suggesting an important role in the regulation of biological processes. Understanding the role of tRNA expression in cattle offers an opportunity to reveal mechanisms of regulation at the translational level. We analyzed tRNA expression in the skeletal muscle and liver tissues of day 105 artificial insemination-conceived, ART-conceived with a normal body weight, and ART-conceived bovine fetuses with a body weight above the 97^th percentile compared to Control-AI.

Results

Despite the centrality of tRNAs to translation, in silico predictions have revealed dramatic differences in the number of tRNA genes between humans and cattle (597 vs 1,659). Consistent with reports in human, only a fraction of predicted tRNA genes are expressed. We detected the expression of 474 and 487 bovine tRNA genes in the muscle and liver with the remainder being unexpressed. 193 and 198 unique tRNA sequences were expressed in all treatment groups within muscle and liver respectively. In addition, an average of 193 tRNA sequences were expressed within the same treatment group in different tissues. Some tRNA isodecoders were differentially expressed between treatment groups. In the skeletal muscle and liver, we categorized 11 tRNA isoacceptors with undetected expression as well as an isodecoder that was unexpressed in the liver (Ser^GGA). Our results identified variation in the proportion of tRNA gene copies expressed between tissues and differences in the highest contributing tRNA anticodon within an amino acid family due to treatment and tissue type. Out of all amino acid families, roughly half of the most highly expressed tRNA isoacceptors correlated to their most frequent codon in the bovine genome.

Conclusion

Although the number of bovine tRNA genes is nearly triple of that of the tRNA genes in human, there is a shared occurrence of transcriptionally inactive tRNA genes in both species. We detected differential expression of tRNA genes as well as tissue- and treatment- specific tRNA transcripts with unique sequence variations that could modulate translation during protein homeostasis or cellular stress, and give rise to regulatory products targeting genes related to overgrowth in the skeletal muscle and/or tumor development in the liver of LOS individuals. While the absence of certain isodecoders may be relieved by wobble base pairing, missing tRNA species could increase the likelihood of mistranslation or mRNA degradation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08496-7.

Ionizing radiation and chemical oxidant exposure impacts on Cryptococcus neoformans transfer RNAs

Cryptococcus neoformans is a fungus that is able to survive abnormally high levels of ionizing radiation (IR). The radiolysis of water by IR generates reactive oxygen species (ROS) such as H₂O₂ and OH^-. C. neoformans withstands the damage caused by IR and ROS through antioxidant production and enzyme-catalyzed breakdown of ROS. Given these particular cellular protein needs, questions arise whether transfer ribonucleic acids molecules (tRNAs) undergo unique chemical modifications to maintain their structure, stability, and/or function under such environmental conditions. Here, we investigated the effects of IR and H₂O₂ exposure on tRNAs in C. neoformans. We experimentally identified the modified nucleosides present in C. neoformans tRNAs and quantified changes in those modifications upon exposure to oxidative conditions. To better understand these modified nucleoside results, we also evaluated tRNA pool composition in response to the oxidative conditions. We found that regardless of environmental conditions, tRNA modifications and transcripts were minimally affected. A rationale for the stability of the tRNA pool and its concomitant profile of modified nucleosides is proposed based on the lack of codon bias throughout the C. neoformans genome and in particular for oxidative response transcripts. Our findings suggest that C. neoformans can rapidly adapt to oxidative environments as mRNA translation/protein synthesis are minimally impacted by codon bias.

Production of a Novel Superoxide Dismutase by Escherichia coli and Pichia pastoris and Analysis of the Thermal Stability of the Enzyme

Previously, a new copper-zinc SOD (CuZnSOD) isolated from chestnut rose (Rosa roxburghii) with good stability was described. In this study, the biosynthetic approach was used to create recombinant CuZnSOD. RACE PCR was also used to amplify the full-length CuZnSOD gene from chestnut rose, and the ORF segment was expressed in E. coli BL21 and P. pastoris GS115. For characterization, the enzyme was isolated in two steps in E. coli and one step in P. pastoris. The biochemical properties of the two recombinant enzymes were similar, and their optimal reaction pH and temperature were 6.0 and 50°C, respectively. According to molecular dynamics simulation, the CuZnSOD showed high stability from 70 to 90°C, and eight amino acids are important for enzyme thermal stability at high temperatures. This study set the stage for industrial manufacture by filling gaps in the link between conformational changes and the thermal stability of the new CuZnSOD.

Plasma cell-free RNA characteristics in COVID-19 patients

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)–related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

Evolutionary characteristics and phylogeny of cotton chloroplast tRNAs

The novel structural variations were identified in cotton chloroplast tRNAs and gene loss events were more obvious than duplications in chloroplast tRNAs. Transfer RNAs (tRNA) have long been believed an evolutionary-conserved molecular family, which play the key roles in the process of protein biosynthesis in plant life activities. In this study, we detected the evolutionary characteristics and phylogeny of chloroplast tRNAs in cotton plants, an economic and fibered important taxon in the world. We firstly annotated the chloroplast tRNAs of 27 Gossypium species to analyze their genetic composition, structural characteristics and evolution. Compared with the traditional view of evolutionary conservation of tRNA, some novel tRNA structural variations were identified in cotton plants. I.g., tRNA^Val-UAC and tRNA^Ile-GAU only contained one intron in the anti-condon loop region of tRNA secondary structure, respectively. In the variable region, some tRNAs contained a circle structure with a few nucleotides. Interestingly, the calculation result of free energy indicated that the variation of novel tRNAs contributed to the stability of tRNA structure. Phylogenetic analysis suggested that chloroplast tRNAs have evolved from multiple common ancestors, and the tRNA^Met seemed to be an ancestral tRNA, which can be duplicated and diversified to produce other tRNAs. The chloroplast tRNAs contained a group I intron in cotton plants, and the evolutionary analysis of introns indicated that group I intron of chloroplast tRNA originated from cyanobacteria. Analysis of gene duplication and loss events showed that gene loss events were more obvious than duplications in Gossypium chloroplast tRNAs. Additionally, we found that the rate of transition was higher than the ones of transversion in cotton chloroplast tRNAs. This study provided new insights into the structural characteristics and evolution of chloroplast tRNAs in cotton plants.

Direct Nanopore Sequencing of Individual Full Length tRNA Strands

We describe a method for direct tRNA sequencing using the Oxford Nanopore MinION. The principal technical advance is custom adapters that facilitate end-to-end sequencing of individual transfer RNA (tRNA) molecules at subnanometer precision. A second advance is a nanopore sequencing pipeline optimized for tRNA. We tested this method using purified E. coli tRNA^fMet, tRNA^Lys, and tRNA^Phe samples. 76-92% of individual aligned tRNA sequence reads were full length. As a proof of concept, we showed that nanopore sequencing detected all 43 expected isoacceptors in total E. coli MRE600 tRNA as well as isodecoders that further define that tRNA population. Alignment-based comparisons between the three purified tRNAs and their synthetic controls revealed systematic nucleotide miscalls that were diagnostic of known modifications. Systematic miscalls were also observed proximal to known modifications in total E. coli tRNA alignments, including a highly conserved pseudouridine in the T loop. This work highlights the potential of nanopore direct tRNA sequencing as well as improvements needed to implement tRNA sequencing for human healthcare applications.

Direct Nanopore Sequencing of Individual Full Length tRNA Strands

We describe a method for direct tRNA sequencing using the Oxford Nanopore MinION. The principal technical advance is custom adapters that facilitate end-to-end sequencing of individual transfer RNA (tRNA) molecules at subnanometer precision. A second advance is a nanopore sequencing pipeline optimized for tRNA. We tested this method using purified E. coli tRNA^fMet, tRNA^Lys, and tRNA^Phe samples. 76-92% of individual aligned tRNA sequence reads were full length. As a proof of concept, we showed that nanopore sequencing detected all 43 expected isoacceptors in total E. coli MRE600 tRNA as well as isodecoders that further define that tRNA population. Alignment-based comparisons between the three purified tRNAs and their synthetic controls revealed systematic nucleotide miscalls that were diagnostic of known modifications. Systematic miscalls were also observed proximal to known modifications in total E. coli tRNA alignments, including a highly conserved pseudouridine in the T loop. This work highlights the potential of nanopore direct tRNA sequencing as well as improvements needed to implement tRNA sequencing for human healthcare applications.

Growth-coupled evolution and high-throughput screening assisted rapid enhancement for amylase-producing Bacillus licheniformis

Bacillus licheniformis α-amylase is a thermostable enzyme used in industrial starch hydrolysis. However, difficulties in the genetic manipulation of B. licheniformis hamper further enhancement of α-amylase production. In this regard, adaptive evolution is a useful strategy for promoting the productivity of microbial hosts, although the success of this approach requires the application of suitable evolutionary stress. In this study, we designed a growth-coupled adaptive evolution model to enrich B. licheniformis strains with enhanced amylase productivity and utilization capacity of starch substrates. Single cells of high α-amylase-producing B. licheniformis were isolated using a droplet-based microfluidic platform. Clones with 67% higher α-amylase yield were obtained and analyzed by genome resequencing. Our findings confirmed that growth-coupled evolution combined with high-throughput screening is an efficient strategy for enhanced α-amylase production. In addition, we identified several potential target genes to guide further modification of the B. licheniformis host for efficient protein expression.

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Transfer tRNAs (tRNAs) are small non-coding RNAs that are highly conserved in all kingdoms of life. Originally discovered as the molecules that deliver amino acids to the growing polypeptide chain during protein synthesis, tRNAs have been believed for a long time to play exclusive role in translation. However, recent studies have identified key roles for tRNAs and tRNA-derived small RNAs in multiple other processes, including regulation of transcription and translation, posttranslational modifications, stress response, and disease. These emerging roles suggest that tRNAs may be central players in the complex machinery of biological regulatory pathways. Here we overview these non-canonical roles of tRNA in normal physiology and disease, focusing largely on eukaryotic and mammalian systems.

Comparative analysis of codon usage between Gossypium hirsutum and G. barbadense mitochondrial genomes

Gossypium hirsutum and G. barbadense mitochondrial genomes were analyzed to understand the factors shaping codon usage. While most analyses of codon usage suggest minimal to no bias, nucleotide composition, specifically GC content, was significantly correlated with codon usage. In general, both mitochondrial genomes favor codons that end in A or U, with a secondary preference for pyrimidine rich codons. These observations are similar to previous reports of codon usage in cotton nuclear genomes, possibly suggestive of a general bias spanning genomic compartment. Although evidence for codon usage bias is weak for most genes, we identified six genes (i.e. atp8, atp9, sdh3, sdh4, mttB and rpl2) with significant nonrandom codon usage. In general, we find multiple factors that influence cotton mitochondrial genome codon usage, which may include selection in a subset of genes.

BpForms and BcForms: a toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks

Non-canonical residues, caps, crosslinks, and nicks are important to many functions of DNAs, RNAs, proteins, and complexes. However, we do not fully understand how networks of such non-canonical macromolecules generate behavior. One barrier is our limited formats for describing macromolecules. To overcome this barrier, we develop BpForms and BcForms, a toolkit for representing the primary structure of macromolecules as combinations of residues, caps, crosslinks, and nicks. The toolkit can help omics researchers perform quality control and exchange information about macromolecules, help systems biologists assemble global models of cells that encompass processes such as post-translational modification, and help bioengineers design cells.