Translational Efficiency Research Articles

RNAirport: a deep neural network-based database characterizing representative gene models in plants

A 5′-leader, known initially as the 5′-untranslated region, contains multiple isoforms due to alternative splicing (aS) and alternative transcription start site (aTSS). Therefore, a representative 5′-leader is demanded to examine the embedded RNA regulatory elements in controlling translation efficiency. Here, we develop a ranking algorithm and a deep-learning model to annotate representative 5′-leaders for five plant species. We rank the intra-sample and inter-sample frequency of aS-mediated transcript isoforms using the Kruskal–Wallis test-based algorithm and identify the representative aS-5′-leader. To further assign a representative 5′-end, we train the deep-learning model 5′leaderP to learn aTSS-mediated 5′-end distribution patterns from cap-analysis gene expression data. The model accurately predicts the 5′-end, confirmed experimentally in Arabidopsis and rice. The representative 5′-leader-contained gene models and 5′leaderP can be accessed at RNAirport (http://www.rnairport.com/leader5P/). The Stage 1 annotation of 5′-leader records 5′-leader diversity and will pave the way to Ribo-Seq open-reading frame annotation, identical to the project recently initiated by human GENCODE.

Identification of an N-terminal tag (580N) that improves the biosynthesis of fluorescent proteins in Francisella tularensis and other Gram-negative bacteria

Utilization of fluorescent proteins is widespread for the study of microbial pathogenesis and host-pathogen interactions. Here, we discovered that linkage of the 36 N-terminal amino acids of FTL_0580 (a hypothetical protein of Francisella tularensis) to fluorescent proteins increases the fluorescence emission of bacteria that express these recombinant fusions. This N-terminal peptide will be referred to as 580N. Western blotting revealed that the linkage of 580N to Emerald Green Fluorescent Protein (EmGFP) in F. tularensis markedly improved detection of this protein. We therefore hypothesized that transcripts containing 580N may be translated more efficiently than those lacking the coding sequence for this leader peptide. In support, expression of emGFPFt that had been codon-optimized for F. tularensis, yielded significantly enhanced fluorescence than its non-optimized counterpart. Furthermore, fusing emGFP with coding sequence for a small N-terminal peptide (Serine-Lysine-Isoleucine-Lysine), which had previously been shown to inhibit ribosomal stalling, produced robust fluorescence when expressed in F. tularensis. These findings support the interpretation that 580N enhances the translation efficiency of fluorescent proteins in F. tularensis. Interestingly, expression of non-optimized 580N-emGFP produced greater fluorescence intensity than any other construct. Structural predictions suggested that RNA secondary structure also may be influencing translation efficiency. When expressed in Escherichia coli and Klebsiella pneumoniae bacteria, 580N-emGFP produced increased green fluorescence compared to untagged emGFP (neither allele was codon optimized for these bacteria). In conclusion, fusing the coding sequence for the 580N leader peptide to recombinant genes might serve as an economical alternative to codon optimization for enhancing protein expression in bacteria.

Translation efficiency driven by CNOT3 subunit of the CCR4-NOT complex promotes leukemogenesis

Protein synthesis is frequently deregulated during tumorigenesis. However, the precise contexts of selective translational control and the regulators of such mechanisms in cancer is poorly understood. Here, we uncovered CNOT3, a subunit of the CCR4-NOT complex, as an essential modulator of translation in myeloid leukemia. Elevated CNOT3 expression correlates with unfavorable outcomes in patients with acute myeloid leukemia (AML). CNOT3 depletion induces differentiation and apoptosis and delayed leukemogenesis. Transcriptomic and proteomic profiling uncovers c-MYC as a critical downstream target which is translationally regulated by CNOT3. Global analysis of mRNA features demonstrates that CNOT3 selectively influences expression of target genes in a codon usage dependent manner. Furthermore, CNOT3 associates with the protein network largely consisting of ribosomal proteins and translation elongation factors in leukemia cells. Overall, our work elicits the direct requirement for translation efficiency in tumorigenesis and propose targeting the post-transcriptional circuitry via CNOT3 as a therapeutic vulnerability in AML.

Biodegradable Lipid-Modified Poly(Guanidine Thioctic Acid)s: A Fortifier of Lipid Nanoparticles to Promote the Efficacy and Safety of mRNA Cancer Vaccines.

Lipid nanoparticles (LNPs)-based messenger RNA (mRNA) therapeutics have emerged with promising potentials in the fields of infectious diseases, cancer vaccines, and protein replacement therapies; however, their therapeutic efficacy and safety can still be promoted by the optimization of LNPs formulations. Unfortunately, current LNPs suffer from increased production of reactive oxygen species during translation, which leads to a decreased translation efficiency and the onset of inflammation and other side effects. Herein, we synthesize a lipid-modified poly(guanidine thioctic acid) polymer to fabricate novel LNPs for mRNA vaccines. The acquired G-LNPs significantly promote the translation efficiency of loaded mRNA and attenuate inflammation after vaccination through the elimination of reactive oxygen species that are responsible for translational inhibition and inflammatory responses. In vivo studies demonstrate the excellent antitumor efficacy of the G-LNPs@mRNA vaccine, and two-dose vaccination dramatically increases the population and infiltration of cytotoxic T cells due to the intense antitumor immune responses, thus generating superior antitumor outcomes compared with the mRNA vaccine prepared from traditional LNPs. By synergy with immune checkpoint blockade, the tumor inhibition of G-LNPs@mRNA is further boosted, indicating that G-LNPs-based mRNA vaccines will be powerful and versatile platforms to combat cancer.

Application of deep learning in English translation of children’s picture books

This study aims to explore the application of deep learning technology in the translation of children’s picture books. By analyzing the existing translation of children’s picture books, we extract the key factors to be considered in the translation process, and design a deep learning model to deal with these factors to achieve high-quality translation. At the same time, a picture book image recognition system is also implemented, which can understand the image content in the picture book and integrate these contents into the translation. Through continuous training and optimization of the model, an efficient picture book translation tool is obtained. In addition, the performance of the model in practical applications was evaluated, and the practical impact and value of deep learning in children’s picture book translation was explored through user feedback and surveys.

M6A RNA methylation regulates mitochondrial function.

RNA methylation of N6-methyladenosine (m6A) is emerging as a fundamental regulator of every aspect of RNA biology. RNA methylation directly impacts protein production to achieve quick modulation of dynamic biological processes. However, whether RNA methylation regulates mitochondrial function is not known, especially in neuronal cells which require a high energy supply and quick reactive responses. Here we show that m6A RNA methylation regulates mitochondrial function through promoting nuclear-encoded mitochondrial complex subunit RNA translation. Conditional genetic knockout of m6A RNA methyltransferase Mettl14 (Methyltransferase like 14) by Nestin-Cre together with metabolomic analysis reveals that Mettl14 knockout-induced m6A depletion significantly downregulates metabolites related to energy metabolism. Furthermore, transcriptome-wide RNA methylation profiling of wild type and Mettl14 knockout mouse brains by m6A-Seq shows enrichment of methylation on mitochondria-related RNA. Importantly, loss of m6A leads to a significant reduction in mitochondrial respiratory capacity and membrane potential. These functional defects are paralleled by the reduced expression of mitochondrial electron transport chain complexes, as well as decreased mitochondrial super-complex assembly and activity. Mechanistically, m6A depletion decreases the translational efficiency of methylated RNA encoding mitochondrial complex subunits through reducing their association with polysomes, while not affecting RNA stability. Together, these findings reveal a novel role for RNA methylation in regulating mitochondrial function. Given that mitochondrial dysfunction and RNA methylation have been increasingly implicate in neurodegenerative disorders, our findings not only provide insights into fundamental mechanisms regulating mitochondrial function, but also open up new avenues for understanding the pathogenesis of neurological diseases.

Integrative Transcriptome Analysis of mRNA and miRNA in Pepper's Response to Phytophthora capsici Infection.

Phytophthora blight of pepper is a notorious disease caused by the oomycete pathogen Phytophthora capsici, which poses a great threat to global pepper production. MicroRNA (miRNA) is a class of non-coding small RNAs that regulate gene expressions by altering the translation efficiency or stability of targeted mRNAs, which play important roles in the regulation of a plant's response to pathogens. Herein, time-series mRNA-seq libraries and small RNA-seq libraries were constructed using pepper roots from the resistant line CM334 and the susceptible line EC01 inoculated with P. capsici at 0, 6, 24, and 48 h post-inoculation, respectively. For mRNA-seq analysis, a total of 2159 and 2971 differentially expressed genes (DEGs) were identified in CM334 and EC01, respectively. For miRNA-seq analysis, 491 pepper miRNAs were identified, including 330 known miRNAs and 161 novel miRNAs. Among them, 69 and 88 differentially expressed miRNAs (DEMs) were identified in CM334 and EC01, respectively. Examination of DEMs and their targets revealed 22 regulatory networks, predominantly featuring up-regulated miRNAs corresponding to down-regulated target genes. Notably, these DEM-DEG regulatory networks exhibited significant overlap between CM334 and EC01, suggesting that they might contribute to pepper's basal defense against P. capsici. Furthermore, five selected DEMs (miR166, miR1171, miR395, miR530 and miRN2) and their target genes underwent qRT-PCR validation, confirming a consistent negative correlation in the expression patterns of miRNAs and their targets. This comprehensive analysis provides novel insights into the regulatory networks of miRNAs and their targets, offering valuable contributions to our understanding of pepper's defense mechanisms against P. capsici.

Two distinct waves of transcriptome and translatome changes drive Drosophila germline stem cell differentiation

The tight control of fate transitions during stem cell differentiation is essential for proper tissue development and maintenance. However, the challenges in studying sparsely distributed adult stem cells in a systematic manner have hindered efforts to identify how the multilayered regulation of gene expression programs orchestrates stem cell differentiation in vivo. Here, we synchronised Drosophila female germline stem cell (GSC) differentiation in vivo to perform in-depth transcriptome and translatome analyses at high temporal resolution. This characterisation revealed widespread and dynamic changes in mRNA level, promoter usage, exon inclusion, and translation efficiency. Transient expression of the master regulator, Bam, drives a first wave of expression changes, primarily modifying the cell cycle program. Surprisingly, as Bam levels recede, differentiating cells return to a remarkably stem cell-like transcription and translation program, with a few crucial changes feeding into a second phase driving terminal differentiation to form the oocyte. Altogether, these findings reveal that rather than a unidirectional accumulation of changes, the in vivo differentiation of stem cells relies on distinctly regulated and developmentally sequential waves.

Mapping the tRNA modification landscape of Bartonella henselae Houston I and Bartonella quintana Toulouse.

Transfer RNA (tRNA) modifications play a crucial role in maintaining translational fidelity and efficiency, and they may function as regulatory elements in stress response and virulence. Despite their pivotal roles, a comprehensive mapping of tRNA modifications and their associated synthesis genes is still limited, with a predominant focus on free-living bacteria. In this study, we employed a multidisciplinary approach, incorporating comparative genomics, mass spectrometry, and next-generation sequencing, to predict the set of tRNA modification genes responsible for tRNA maturation in two intracellular pathogens-Bartonella henselae Houston I and Bartonella quintana Toulouse, which are causative agents of cat-scratch disease and trench fever, respectively. This analysis presented challenges, particularly because of host RNA contamination, which served as a potential source of error. However, our approach predicted 26 genes responsible for synthesizing 23 distinct tRNA modifications in B. henselae and 22 genes associated with 23 modifications in B. quintana. Notably, akin to other intracellular and symbiotic bacteria, both Bartonella species have undergone substantial reductions in tRNA modification genes, mostly by simplifying the hypermodifications present at positions 34 and 37. Bartonella quintana exhibited the additional loss of four modifications and these were linked to examples of gene decay, providing snapshots of reductive evolution.

Assessment of feasibility of mRNA vaccines for cancer treatment

Cancer is the group of disease that has high morbidity rate, the traditional treatment people keep using have a lot of limitations. Although the concept of mRNA vaccines has just emerged in the 20th century, it has demonstrated its good availability during the COVID-19 pandemic. From this, researchers infer that mRNA also has great application prospects in other areas, and cancer immunotherapy has become one of them. mRNA vaccine used to have low translation efficiency and strong mRNA immunogenicity but recent research about mRNA sequence optimization could overcome most of these problems. But to apply this platform vaccine to target tumour cells specifically, the target chosen is very important and still needs a lot of research about it. This article reviews the current approach to mRNA vaccine and its therapeutic usage for cancer. Based on the current clinical studies, the mRNA vaccine might be a good auxiliary tool for cancer treatment.

Supramolecular Lipid Nanoparticles Based on Host-Guest Recognition: A New Generation Delivery System of mRNA Vaccines For Cancer Immunotherapy.

Dendritic cell (DC) maturation is a crucial process for antigen presentation and the initiation of T cell-mediated immune responses. Toll-like receptors play pivotal roles in stimulating DC maturation and promoting antigen presentation. Here, a novel message RNA (mRNA) cancer vaccine is reported that boosts antitumor efficacy by codelivering an mRNA encoding tumor antigen and a TLR7/8 agonist (R848) to DC using supramolecular lipid nanoparticles (SMLNP) as a delivery platform, in which a new ionizable lipid (N2-3L) remarkably enhances the translation efficiency of mRNA and a β-cyclodextrin (β-CD)-modified ionizable lipid (Lip-CD) encapsulates R848. The incorporation of R848 adjuvant into the mRNA vaccine through noncovalent host-guest complexation significantly promotes DC maturation and antigen presentation after vaccination, thus resulting in superior antitumor efficacy in vivo. Moreover, the antitumor efficacy is further boosted synergized with immune checkpoint blockade by potentiating the anticancer capability of cytotoxic T lymphocytes infiltrated in tumor sites. This work indicates that SMLNP shows brilliant potential as next-generation delivery system in the development of mRNA vaccines with high efficacy.

Synaptopathy: presynaptic convergence in frontotemporal dementia and amyotrophic lateral sclerosis.

Frontotemporal dementia and amyotrophic lateral sclerosis are common forms of neurodegenerative disease that share overlapping genetics and pathologies. Crucially, no significantly disease-modifying treatments are available for either disease. Identifying the earliest changes that initiate neuronal dysfunction is important for designing effective intervention therapeutics. The genes mutated in genetic forms of frontotemporal dementia and amyotrophic lateral sclerosis have diverse cellular functions, and multiple disease mechanisms have been proposed for both. Identification of a convergent disease mechanism in frontotemporal dementia and amyotrophic lateral sclerosis would focus research for a targetable pathway, which could potentially effectively treat all forms of frontotemporal dementia and amyotrophic lateral sclerosis (both familial and sporadic). Synaptopathies are diseases resulting from physiological dysfunction of synapses, and define the earliest stages in multiple neuronal diseases, with synapse loss a key feature in dementia. At the presynapse, the process of synaptic vesicle recruitment, fusion and recycling is necessary for activity-dependent neurotransmitter release. The unique distal location of the presynaptic terminal means the tight spatio-temporal control of presynaptic homeostasis is dependent on efficient local protein translation and degradation. Recently, numerous publications have shown that mutations associated with frontotemporal dementia and amyotrophic lateral sclerosis present with synaptopathy characterized by presynaptic dysfunction. This review will describe the complex local signalling and membrane trafficking events that occur at the presynapse to facilitate neurotransmission and will summarize recent publications linking frontotemporal dementia/amyotrophic lateral sclerosis genetic mutations to presynaptic function. This evidence indicates that presynaptic synaptopathy is an early and convergent event in frontotemporal dementia and amyotrophic lateral sclerosis and illustrates the need for further research in this area, to identify potential therapeutic targets with the ability to impact this convergent pathomechanism.

Cyclic β2,3-amino acids improve the serum stability of macrocyclic peptide inhibitors targeting the SARS-CoV-2 main protease.

Due to their constrained conformations, cyclic β2,3-amino acids (cβAA) are key building blocks that can fold peptides into compact and rigid structures, improving peptidase resistance and binding affinity to target proteins, due to their constrained conformations. Although the translation efficiency of cβAAs is generally low, our engineered tRNA, referred to as tRNAPro1E2, enabled efficient incorporation of cβAAs into peptide libraries using the flexible in vitro translation (FIT) system. Here we report on the design and application of a macrocyclic peptide library incorporating 3 kinds of cβAAs: (1R,2S)-2-aminocyclopentane carboxylic acid (β1), (1S,2S)-2-aminocyclohexane carboxylic acid (β2), and (1R,2R)-2-aminocyclopentane carboxylic acid. This library was applied to an in vitro selection against the SARS-CoV-2 main protease (Mpro). The resultant peptides, BM3 and BM7, bearing one β2 and two β1, exhibited potent inhibitory activities with IC50 values of 40 and 20 nM, respectively. BM3 and BM7 also showed remarkable serum stability with half-lives of 48 and >168 h, respectively. Notably, BM3A and BM7A, wherein the cβAAs were substituted with alanine, lost their inhibitory activities against Mpro and displayed substantially shorter serum half-lives. This observation underscores the significant contribution of cβAA to the activity and stability of peptides. Overall, our results highlight the potential of cβAA in generating potent and highly stable macrocyclic peptides with drug-like properties.

Word translation for Indo-Aryan languages using different retrieval techniques

<p>The study of Natural Language Processing has been revolutionized by word embedding, enabling advanced language models to understand and generate human-like text. In this research article, we delve deep into the world of word embedding, aiming to provide a comprehensive exploration of its underlying principles, methodologies, and applications. One important factor that affects many multilingual language processing activities is the word translation or incorporation of bilingual dictionaries. We used bilingual dictionaries or parallel data for translation from one language to another. For this research work, this problem is addressed, and also generating the best cross-lingual word embedding for the different language pairs. So, we are using an aligned document sentence-aligned corpus, or any bilingual dictionary for this research analysis. For the most frequent word, we are assuming that there is an intra-lingual similarity distribution, and both the source and the target corpora have a comparable distribution graph. Additionally, these embeddings are isometric. These cross-lingual word embeddings are used for cross-lingual transfer learning and unsupervised neural machine translation. This research aims to improve the accuracy and efficiency of word translation between different language pairs by employing different retrieval techniques. The study analyzes the effectiveness of these techniques on different language pairs, including English-Hindi, English-Punjabi, English-Gujarati, English-Bengali, and English-Marathi. The research is expected to contribute significantly to the field of language translation by introducing innovative methods and other applications.</p>

Synthetic biology approach revealed enhancement in haeme oxygenase-1 gene expression by codon pair optimization while reduction by codon deoptimization.

Haem oxygenase-1 (HO-1) is a ubiquitously expressed gene involved in cellular homoeostasis, and its imbalance in expression results in various disorders. To alleviate such disorders, HO-1 gene expression needs to be modulated. Codon usage bias results from evolutionary forces acting on any nucleotide sequence and determines the gene expression. Like codon usage bias, codon pair bias also exists, playing a role in gene expression. In the present study, HO-1 gene was recoded by manipulating codon and codon pair bias, and four such constructs were made through codon/codon pair deoptimization and codon/codon pair optimization to reduce and enhance the HO-1 gene expression. Codon usage analysis was done for these constructs for four tissues brain, heart, pancreas and liver. Based on codon usage in different tissues, gene expression of these tissues was determined in terms of the codon adaptation index. Based on the codon adaptation index, minimum free energy, and translation efficiency, constructs were evaluated for enhanced or decreased HO-1 expression. The analysis revealed that for enhancing gene expression, codon pair optimization, while for reducing gene expression, codon deoptimization is efficacious. The recoded constructs developed in the study could be used in gene therapy regimens to cure HO-1 over or underexpression-associated disorders.

An integrative platform for detection of RNA 2′-O-methylation reveals its broad distribution on mRNA

Ribose 2'-O-methylation is involved in critical biological processes, but its biological functions and significance in mRNAs remain underexplored. We have developed NJU-seq, a sensitive method for unbiased 2'-O-methylation (Nm) profiling, and Nm-VAQ, a site-specific quantification tool. Using these tools in tandem, we identified thousands of Nm sites on mRNAs of human and mouse cell lines, of which 68 of 84 selected sites were further validated to be more than 1% 2'-O-methylated. Unlike rRNA, most mRNA Nm sites were from 1% to 30% methylated. In addition, mRNA Nm was dynamic, changing according to the circumstance. Furthermore, we show that fibrillarin is involved as a methyltransferase. By mimicking the detected Nm sites and the context sequence, the RNA fragments could be 2'-O-methylated and demonstrated higher stability but lower translation efficiency. Last, profiling of Nm sites in lung surgery samples revealed common signatures of lung cancer pathogenesis, providing potential new diagnostic markers.

Abstract B023: The role of ribosomal protein L22 in regulating the immune landscape in mismatch repair deficient endometrial cancers

Abstract The purpose of this study is to identify novel mechanisms of immune evasion in mismatch repair deficient endometrial cancers. Despite having a hypermutated phenotype that is proposed to lead to the accumulation of many neoantigens for immune recognition, our group has found that mismatch repair deficient endometrial cancers characterized by MLH1 protein loss display large variations in the number of tumors infiltrating CD8+ T cells (TILs) across different tumors. To better understand how variations in TILs arise in mismatch repair deficient endometrial cancers, we utilized human endometrial cancer samples from the UNCseq cohort. Immunohistochemistry (IHC) was used to identify expression patterns in proteins of interest across mismatch repair deficient endometrial cancers. To determine how expression patterns of proteins of interest correlate with TILs in our patient samples, Definiens Tissue Studio was utilized to quantify immunofluorescent CD8+ TILs in our mismatch repair deficient endometrial cancer cohort. Although upregulation of programmed death ligand 1 (PD-L1) expression is often cited as an explanation for low TILs, analysis of human data by our group shows that PD-L1 expression does not correlate with TIL numbers in mismatch repair deficient endometrial cancers. Interestingly, The Cancer Genome Atlas (TCGA) data reported that ribosomal protein L22 (RPL22) is mutated in ~50% of mismatch repair deficient endometrial cancers. We analyzed RPL22 by IHC and found that it was lost in 52% of our human mismatch repair deficient endometrial cancer cohort. Loss of various ribosomal proteins can alter translation efficiency of proteins critical for promoting immunosurveillance and the immune response in cancer. In our cohort, mismatch repair deficient endometrial cancers that have lost expression of RPL22 have lower numbers of CD8+ TILs. Preliminary data also show that human endometrial cancer cell lines that do not express RPL22 also do not express beta-2-microglobulin (β2M), a component of the major histocompatibility complex I (MHC-I) molecules that is necessary for neoantigen presentation to CD8+ T cells. Thus, we hypothesize that RPL22 loss in mismatch repair deficient endometrial cancers results in decreased translation of β2M and CD8+ T cell evasion. Moving forward, we speculate that RPL22 could be utilized as a predictive biomarker for immunotherapy response in mismatch repair deficient endometrial cancers. Citation Format: Macy L. Osborne, Hannah Atkins, Andrew B. Gladden, Russell R. Broaddus. The role of ribosomal protein L22 in regulating the immune landscape in mismatch repair deficient endometrial cancers [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B023.

The Integration of Machine Translation Technology in the Realm of Legal Interpretation

This article aims to provide an overview of the application of machine translation technology in the field of legal translation, exploring its potential, challenges, and future directions. Firstly, it reviews the development process of machine translation technology, including rule-based methods, statistical machine translation, and the application of deep learning methods. Secondly, on the basis of in-depth deconstruction of the operating rules of the big language model, it is demonstrated that the highly modeled written legal language is highly consistent with the underlying logic of the big language model because of its standardization, accuracy and de-contextualization, so compared with other styles, machine translation technology will achieve better translation results in the field of legal translation. In addition, multimodal technology can also be applied to court interpretation, which greatly alleviates the shortage of qualified interpreters and maintains judicial justice. Furthermore, it discusses the human-machine collaborative model in legal translation, emphasizing the importance of human proofreading and review in ensuring translation accuracy and reliability. Lastly, it summarizes the prospects and challenges of machine translation technology in the field of legal translation. Through a systematic review and analysis of relevant literature, this article reveals the immense potential of machine translation technology in legal translation. It can significantly enhance the efficiency and quality of legal translation, thereby enhancing the capacity of legal language services.

Biosynthesis and function of 7-deazaguanine derivatives in bacteria and phages.

SUMMARYDeazaguanine modifications play multifaceted roles in the molecular biology of DNA and tRNA, shaping diverse yet essential biological processes, including the nuanced fine-tuning of translation efficiency and the intricate modulation of codon-anticodon interactions. Beyond their roles in translation, deazaguanine modifications contribute to cellular stress resistance, self-nonself discrimination mechanisms, and host evasion defenses, directly modulating the adaptability of living organisms. Deazaguanine moieties extend beyond nucleic acid modifications, manifesting in the structural diversity of biologically active natural products. Their roles in fundamental cellular processes and their presence in biologically active natural products underscore their versatility and pivotal contributions to the intricate web of molecular interactions within living organisms. Here, we discuss the current understanding of the biosynthesis and multifaceted functions of deazaguanines, shedding light on their diverse and dynamic roles in the molecular landscape of life.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes of early pandemic phase.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome. A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2. A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency. Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.