Translational efficiency across healthy and tumor tissues is proliferation-related

Genes and Pathways Comprising the Human and Mouse ORFeomes Display Distinct Codon Bias Signatures that Can Regulate Protein Levels

Arginine, glutamic acid and selenocysteine based codon bias has been shown to regulate the translation of specific mRNAs for proteins that participate in stress responses, cell cycle and transcriptional regulation. Defining codon-bias in gene networks has the potential to identify other pathways under translational control. Here we have used computational methods to analyze the ORFeome of all unique human (19,711) and mouse (22,138) open-reading frames (ORFs) to characterize codon-usage and codon-bias in genes and biological processes. We show that ORFeome-wide clustering of gene-specific codon frequency data can be used to identify ontology-enriched biological processes and gene networks, with developmental and immunological programs well represented for both humans and mice. We developed codon over-use ontology mapping and hierarchical clustering to identify multi-codon bias signatures in human and mouse genes linked to signaling, development, mitochondria and metabolism, among others. The most distinct multi-codon bias signatures were identified in human genes linked to skin development and RNA metabolism, and in mouse genes linked to olfactory transduction and ribosome, highlighting species-specific pathways potentially regulated by translation. Extreme codon bias was identified in genes that included transcription factors and histone variants. We show that re-engineering extreme usage of C- or U-ending codons for aspartic acid, asparagine, histidine and tyrosine in the transcription factors CEBPB and MIER1, respectively, significantly regulates protein levels. Our study highlights that multi-codon bias signatures can be linked to specific biological pathways and that extreme codon bias with regulatory potential exists in transcription factors for immune response and development.

Integrative multi-omics analysis reveals the translational landscape of the plant-parasitic nematode Meloidogyne incognita

Root-knot nematodes (RKNs) of the genus Meloidogyne pose the most significant threats to global food security due to their destructive nature as plant-parasitic nematodes. Although significant attention has been devoted to investigating the gene transcription profiling of RKNs, our understanding of the translational landscape of RKNs remains limited. In this study, we elucidated the translational landscape of Meloidogyne incognita through the integration of translatome, transcriptome and quantitative proteome analyses. Our findings revealed numerous previously unannotated translation events and refined the genome annotation. By investigating the genome-wide translational dynamics of M. incognita during parasitism, we revealed that the genes of M. incognita undergo parasitic stage-specific regulation at the translational level. Interestingly, we identified 470 micropeptides (containing fewer than 100 amino acids) with the potential to function as effectors. Additionally, we observed that the effector-coding genes in M. incognita exhibit higher translation efficiency (TE). Further analysis suggests that M. incognita has the potential to regulate the TE of effector-coding genes without simultaneous alterations in their transcript abundance, facilitating effector synthesis. Collectively, our study provides comprehensive datasets and explores the genome-wide translational landscape of M. incognita, shedding light on the contributions of translational regulation during parasitism.

Decoding Codon Bias: The Role of tRNA Modifications in Tissue-Specific Translation

The tRNA epitranscriptome has been recognized as an important player in mRNA translation regulation. Our knowledge of the role of the tRNA epitranscriptome in fine-tuning translation via codon decoding at tissue or cell levels remains incomplete. We analyzed tRNA expression and modifications as well as codon optimality across seven mouse tissues. Our analysis revealed distinct enrichment patterns of tRNA modifications in different tissues. Queuosine (Q) tRNA modification was most enriched in the brain compared to other tissues, while mitochondrial tRNA modifications and tRNA expression were highest in the heart. Using this observation, we synthesized, and delivered in vivo, codon-mutated EGFP for Q-codons, where the C-ending Q-codons were replaced with U-ending codons. The protein levels of mutant EGFP were downregulated in liver, which is poor in Q, while in brain EGFP, levels did not change. These data show that understanding tRNA modification enrichments across tissues is not only essential for understanding codon decoding and bias but can also be utilized for optimizing gene and mRNA therapeutics to be more tissue-, cell-, or condition-specific.

Transfer RNA Levels Are Tuned to Support Differentiation During Drosophila Neurogenesis

BACKGROUND/OBJECTIVES

Neural differentiation requires a multifaceted program to alter gene expression along the proliferation to the differentiation axis. While critical changes occur at the level of transcription, post-transcriptional mechanisms allow fine-tuning of protein output. We investigated the role of tRNAs in regulating gene expression during neural differentiation in Drosophila larval brains.

METHODS

We quantified tRNA abundance in neural progenitor-biased and neuron-biased brains using the hydrotRNA-seq method. These tRNA data were combined with cell type-specific mRNA decay measurements and transcriptome profiles in order to model how tRNA abundance affects mRNA stability and translation efficiency.

RESULTS

We found that (1) tRNA abundance is largely constant between neural progenitors and neurons but significant variation exists for 10 nuclear tRNA genes and 8 corresponding anticodon groups, (2) tRNA abundance correlates with codon-mediated mRNA decay in neuroblasts and neurons, but does not completely explain the different stabilizing or destabilizing effects of certain codons, and (3) changes in tRNA levels support a shift in translation optimization from a program supporting proliferation to a program supporting differentiation.

CONCLUSIONS

These findings reveal coordination between tRNA expression and codon usage in transcripts that regulate neural development.

SARS-CoV-2 Displays a Suboptimal Codon Usage Bias for Efficient Translation in Human Cells Diverted by Hijacking the tRNA Epitranscriptome

Codon bias analysis of SARS-CoV-2 reveals suboptimal adaptation for translation in human cells it infects. The detailed examination of the codons preferentially used by SARS-CoV-2 shows a strong preference for LysAAA, GlnCAA, GluGAA, and ArgAGA, which are infrequently used in human genes. In the absence of an adapted tRNA pool, efficient decoding of these codons requires a 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2) modification at the U34 wobble position of the corresponding tRNAs (tLysUUU; tGlnUUG; tGluUUC; tArgUCU). The optimal translation of SARS-CoV-2 open reading frames (ORFs) may therefore require several adjustments to the host's translation machinery, enabling the highly biased viral genome to achieve a more favorable "Ready-to-Translate" state in human cells. Experimental approaches based on LC-MS/MS quantification of tRNA modifications and on alteration of enzymatic tRNA modification pathways provide strong evidence to support the hypothesis that SARS-CoV-2 induces U34 tRNA modifications and relies on these modifications for its lifecycle. The conclusions emphasize the need for future studies on the evolution of SARS-CoV-2 codon bias and its ability to alter the host tRNA pool through the manipulation of RNA modifications.

Transfer RNA levels are tuned to support differentiation during Drosophila neurogenesis

Neural differentiation requires a multifaceted program to alter gene expression along the proliferation to differentiation axis. While critical changes occur at the level of transcription, post-transcriptional mechanisms allow fine-tuning of protein output. We investigated the role of tRNAs in regulating gene expression during neural differentiation by quantifying tRNA abundance in neural progenitor-biased and neuron-biased Drosophila larval brains. We found that tRNA profiles are largely consistent between progenitor-biased and neuron-biased brains but significant variation occurs for 10 cytoplasmic isodecoders (individual tRNA genes) and this establishes differential tRNA levels for 8 anticodon groups. We used these tRNA data to investigate relationships between tRNA abundance, codon optimality-mediated mRNA decay, and translation efficiency in progenitors and neurons. Our data reveal that tRNA levels strongly correlate with codon optimality-mediated mRNA decay within each cell type but generally do not explain differences in stabilizing versus destabilizing codons between cell types. Regarding translation efficiency, we found that tRNA expression in neural progenitors preferentially supports translation of mRNAs whose products are in high demand in progenitors, such as those associated with protein synthesis. In neurons, tRNA expression shifts to disfavor translation of proliferation-related transcripts and preferentially support translation of transcripts tied to neuron-specific functions like axon pathfinding and synapse formation. Overall, our analyses reveal that changes in tRNA levels along the neural differentiation axis support optimal gene expression in progenitors and neurons.

Orb2 enables rare-codon-enriched mRNA expression during Drosophila neuron differentiation

Regulation of codon optimality is an increasingly appreciated layer of cell- and tissue-specific protein expression control. Here, we use codon-modified reporters to show that differentiation of Drosophila neural stem cells into neurons enables protein expression from rare-codon-enriched genes. From a candidate screen, we identify the cytoplasmic polyadenylation element binding (CPEB) protein Orb2 as a positive regulator of rare-codon-dependent mRNA stability in neurons. Using RNA sequencing, we reveal that Orb2-upregulated mRNAs in the brain with abundant Orb2 binding sites have a rare-codon bias. From these Orb2-regulated mRNAs, we demonstrate that rare-codon enrichment is important for mRNA stability and social behavior function of the metabotropic glutamate receptor (mGluR). Our findings reveal a molecular mechanism by which neural stem cell differentiation shifts genetic code regulation to enable critical mRNA stability and protein expression.

Cellular energy regulates mRNA degradation in a codon-specific manner

Codon optimality is a major determinant of mRNA translation and degradation rates. However, whether and through which mechanisms its effects are regulated remains poorly understood. Here we show that codon optimality associates with up to 2-fold change in mRNA stability variations between human tissues, and that its effect is attenuated in tissues with high energy metabolism and amplifies with age. Mathematical modeling and perturbation data through oxygen deprivation and ATP synthesis inhibition reveal that cellular energy variations non-uniformly alter the effect of codon usage. This new mode of codon effect regulation, independent of tRNA regulation, provides a fundamental mechanistic link between cellular energy metabolism and eukaryotic gene expression.

Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing

Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.

The Typical tRNA Co-Expresses Multiple 5' tRNA Halves Whose Sequences and Abundances Depend on Isodecoder and Isoacceptor and Change with Tissue Type, Cell Type, and Disease

Transfer RNA-derived fragments (tRFs) are noncoding RNAs that arise from either mature transfer RNAs (tRNAs) or their precursors. One important category of tRFs comprises the tRNA halves, which are generated through cleavage at the anticodon. A given tRNA typically gives rise to several co-expressed 5'-tRNA halves (5'-tRHs) that differ in the location of their 3' ends. These 5'-tRHs, even though distinct, have traditionally been treated as indistinguishable from one another due to their near-identical sequences and lengths. We focused on co-expressed 5'-tRHs that arise from the same tRNA and systematically examined their exact sequences and abundances across 10 different human tissues. To this end, we manually curated and analyzed several hundred human RNA-seq datasets from NCBI's Sequence Run Archive (SRA). We grouped datasets from the same tissue into their own collection and examined each group separately. We found that a given tRNA produces different groups of co-expressed 5'-tRHs in different tissues, different cell lines, and different diseases. Importantly, the co-expressed 5'-tRHs differ in their sequences, absolute abundances, and relative abundances, even among tRNAs with near-identical sequences from the same isodecoder or isoacceptor group. The findings suggest that co-expressed 5'-tRHs that are produced from the same tRNA or closely related tRNAs have distinct, context-dependent roles. Moreover, our analyses show that cell lines modeling the same tissue type and disease may not be interchangeable when it comes to experimenting with tRFs.

Dynamic Landscapes of tRNA Transcriptomes and Translatomes in Diverse Mouse Tissues

Although the function of tRNAs in the translational process is well established, it remains controversial whether tRNA abundance is tightly associated with translational efficiency (TE) in mammals. Moreover, how critically the expression of tRNAs contributes to the establishment of tissue-specific proteomes in mammals has not been well addressed. Here, we measured both tRNA expression using demethylase-tRNA sequencing (DM-tRNA-seq) and TE of mRNAs using ribosome-tagging sequencing (RiboTag-seq) in the brain, heart, and testis of mice. Remarkable variation in the expression of tRNA isodecoders was observed among different tissues. When the statistical effect of isodecoder-grouping on reducing variations is considered through permutating the anticodons, we observed an expected reduction in the variation of anticodon expression across all samples, an unexpected smaller variation of anticodon usage bias, and an unexpected larger variation of tRNA isotype expression at amino acid level. Regardless of whether or not they share the same anticodons, the isodecoders encoding the same amino acids are co-expressed across different tissues. Based on the expression of tRNAs and the TE of mRNAs, we find that the tRNA adaptation index (tAI) and TE are significantly correlated in the same tissues but not between tissues; and tRNA expression and the amino acid composition of translating peptides are positively correlated in the same tissues but not between tissues. We therefore hypothesize that the tissue-specific expression of tRNAs might be due to post-transcriptional mechanisms. This study provides a resource for tRNA and translation studies, as well as novel insights into the dynamics of tRNAs and their roles in translational regulation.

Orb2 enables rare-codon-enriched mRNA expression during Drosophila neuron differentiation

Regulation of codon optimality is an increasingly appreciated layer of cell- and tissue-specific protein expression control. Here, we use codon-modified reporters to show that differentiation of Drosophila neural stem cells into neurons enables protein expression from rare-codon-enriched genes. From a candidate screen, we identify the cytoplasmic polyadenylation element binding (CPEB) protein Orb2 as a positive regulator of rare-codon-dependent expression in neurons. Using RNA sequencing, we reveal that Orb2-upregulated mRNAs in the brain with abundant Orb2 binding sites have a rare-codon bias. From these Orb2-regulated mRNAs, we demonstrate that rare-codon enrichment is important for expression control and social behavior function of the metabotropic glutamate receptor (mGluR). Our findings reveal a molecular mechanism by which neural stem cell differentiation shifts genetic code regulation to enable critical mRNA and protein expression.

Characteristics and molecular mechanism of drug-tolerant cells in cancer: a review

Drug resistance in tumours has seriously hindered the therapeutic effect. Tumour drug resistance is divided into primary resistance and acquired resistance, and the recent study has found that a significant proportion of cancer cells can acquire stable drug resistance from scratch. This group of cells first enters the drug tolerance state (DT state) under drug pressure, and gradually acquires stable drug resistance through adaptive mutations in this state. Although the specific mechanisms underlying the formation of drug tolerant cells (DTCs) remain unclear, various proteins and signalling pathways have been identified as being involved in the formation of DTCs. In the current review, we summarize the characteristics, molecular mechanisms and therapeutic strategies of DTCs in detail.

Recent advances in access to overcome cancer drug resistance by nanocarrier drug delivery system

Cancer is currently one of the most intractable diseases causing human death. Although the prognosis of tumor patients has been improved to a certain extent through various modern treatment methods, multidrug resistance (MDR) of tumor cells is still a major problem leading to clinical treatment failure. Chemotherapy resistance refers to the resistance of tumor cells and/or tissues to a drug, usually inherent or developed during treatment. Therefore, an urgent need to research the ideal drug delivery system to overcome the shortcoming of traditional chemotherapy. The rapid development of nanotechnology has brought us new enlightenments to solve this problem. The novel nanocarrier provides a considerably effective treatment to overcome the limitations of chemotherapy or other drugs resulting from systemic side effects such as resistance, high toxicity, lack of targeting, and off-target. Herein, we introduce several tumor MDR mechanisms and discuss novel nanoparticle technology applied to surmount cancer drug resistance. Nanomaterials contain liposomes, polymer conjugates, micelles, dendrimers, carbon-based, metal nanoparticles, and nucleotides which can be used to deliver chemotherapeutic drugs, photosensitizers, and small interfering RNA (siRNA). This review aims to elucidate the advantages of nanomedicine in overcoming cancer drug resistance and discuss the latest developments.

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

Genes enriched in A/T-ending codons are co-regulated and conserved across mammals

Codon usage influences gene expression distinctly depending on the cell context. Yet, the importance of codon bias in the simultaneous turnover of specific groups of protein-coding genes remains to be investigated. Here, we find that genes enriched in A/T-ending codons are expressed more coordinately in general and across tissues and development than those enriched in G/C-ending codons. tRNA abundance measurements indicate that this coordination is linked to the expression changes of tRNA isoacceptors reading A/T-ending codons. Genes with similar codon composition are more likely to be part of the same protein complex, especially for genes with A/T-ending codons. The codon preferences of genes with A/T-ending codons are conserved among mammals and other vertebrates. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

Using protein-per-mRNA differences among human tissues in codon optimization

BACKGROUND

Codon usage and nucleotide composition of coding sequences have profound effects on protein expression. However, while it is recognized that different tissues have distinct tRNA profiles and codon usages in their transcriptomes, the effect of tissue-specific codon optimality on protein synthesis remains elusive.

RESULTS

We leverage existing state-of-the-art transcriptomics and proteomics datasets from the GTEx project and the Human Protein Atlas to compute the protein-to-mRNA ratios of 36 human tissues. Using this as a proxy of translational efficiency, we build a machine learning model that identifies codons enriched or depleted in specific tissues. We detect two clusters of tissues with an opposite pattern of codon preferences. We then use these identified patterns for the development of CUSTOM, a codon optimizer algorithm which suggests a synonymous codon design in order to optimize protein production in a tissue-specific manner. In human cell-line models, we provide evidence that codon optimization should take into account particularities of the translational machinery of the tissues in which the target proteins are expressed and that our approach can design genes with tissue-optimized expression profiles.

CONCLUSIONS

We provide proof-of-concept evidence that codon preferences exist in tissue-specific protein synthesis and demonstrate its application to synthetic gene design. We show that CUSTOM can be of benefit in biological and biotechnological applications, such as in the design of tissue-targeted therapies and vaccines.

Single-read tRNA-seq analysis reveals coordination of tRNA modification and aminoacylation and fragmentation

Transfer RNA (tRNA) utilizes multiple properties of abundance, modification, and aminoacylation in translational regulation. These properties were typically studied one-by-one; however, recent advance in high throughput tRNA sequencing enables their simultaneous assessment in the same sequencing data. How these properties are coordinated at the transcriptome level is an open question. Here, we develop a single-read tRNA analysis pipeline that takes advantage of the pseudo single-molecule nature of tRNA sequencing in NGS libraries. tRNAs are short enough that a single NGS read can represent one tRNA molecule, and can simultaneously report on the status of multiple modifications, aminoacylation, and fragmentation of each molecule. We find correlations among modification-modification, modification-aminoacylation and modification-fragmentation. We identify interdependencies among one of the most common tRNA modifications, m1A58, as coordinators of tissue-specific gene expression. Our method, SingLe-read Analysis of Crosstalks (SLAC), reveals tRNAome-wide networks of modifications, aminoacylation, and fragmentation. We observe changes of these networks under different stresses, and assign a function for tRNA modification in translational regulation and fragment biogenesis. SLAC leverages the richness of the tRNA-seq data and provides new insights on the coordination of tRNA properties.

Race with virus evolution: The development and application of mRNA vaccines against SARS-CoV-2

Since the COVID-19 pandemic was declared, vaccines against SARS-CoV-2 have been urgently developed around the world. On the basis of the mRNA vaccine technology developed previously, COVID-19 mRNA vaccines were promptly tested in animals, advanced to clinical trials, and then authorized for emergency use in humans. The administration of COVID-19 mRNA vaccines has successfully reduced the hospitalization and mortality caused by the viral infection, although the virus continuously evolves with its transmission. Therefore, the development of mRNA vaccine technology, including RNA modification and delivery systems, is well recognized for its contribution to moderating the harms caused by the COVID-19 pandemic. The scientists who developed these technologies, Katalin Karikó, Drew Weissman, and Pieter Cullis, were awarded the 2022 Tang Prize in Biopharmaceutical Science. In this review, we summarize the principles, safety and efficacy of as well as the immune response to COVID-19 mRNA vaccines. Since mRNA vaccine approaches could be practical for the prevention of infectious diseases, we also briefly describe mRNA vaccines against other human viral pathogens in clinical trials.

Emerging functions of tRNA modifications in mRNA translation and diseases

tRNAs are essential modulators that recognize mRNA codons and bridge amino acids for mRNA translation. The tRNAs are heavily modified, which is essential for forming a complex secondary structure that facilitates codon recognition and mRNA translation. In recent years, studies have identified the regulatory roles of tRNA modifications in mRNA translation networks. Misregulation of tRNA modifications is closely related to the progression of developmental diseases and cancers. In this review, we summarize the tRNA biogenesis process and then discuss the effects and mechanisms of tRNA modifications on tRNA processing and mRNA translation. Finally, we provide a comprehensive overview of tRNA modifications' physiological and pathological functions, focusing on diseases including cancers.

Detecting RNA modification using direct RNA sequencing: A systematic review

Post-transcriptional RNA modifications are involved in a range of important cellular processes, including the regulation of gene expression and fine-tuning of the functions of RNA molecules. To decipher the context-specific functions of these post-transcriptional modifications, it is crucial to accurately determine their transcriptomic locations and modification levels under a given cellular condition. With the newly emerged sequencing technology, especially nanopore direct RNA sequencing, different RNA modifications can be detected simultaneously with a single molecular level resolution. Here we provide a systematic review of 15 published RNA modification prediction tools based on direct RNA sequencing data, including their computational models, input-output formats, supported modification types, and reported performances. Finally, we also discussed the potential challenges and future improvements of nanopore sequencing-based methods for RNA modification detection.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality

•

Developed tissue-specific codon optimality in 29 human tissues.

•

Applied these to analyze synonymous mutations in ∼10,000 tumor and normal samples.

•

Synonymous mutations frequently increase optimal codons in most cancer types.

•

Synonymous mutations frequently increase optimal codons cell cycle-related genes.

•

Frequency of optimal codon gain relates to proliferation, DDR deficiency, and survival.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

tReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data

BACKGROUND

Recent deep sequencing technologies have proven to be valuable resources to gain insights into the expression profiles of diverse tRNAs. However, despite these technologies, the association of tRNAs with diverse diseases has not been explored in depth because analytical tools are lacking.

RESULTS

We developed a user-friendly tool, tRNA Expression Analysis Software Utilizing R for Easy use (tReasure), to analyze differentially expressed tRNAs (DEtRNAs) from deep sequencing data of small RNAs using R packages. tReasure can quantify individual mature tRNAs, isodecoders, and isoacceptors. By adopting stringent mapping strategies, tReasure supports the precise measurement of mature tRNA read counts. The whole analysis workflow for determining DEtRNAs (uploading FASTQ files, removing adapter sequences and poor-quality reads, mapping and quantifying tRNAs, filtering out low count tRNAs, determining DEtRNAs, and visualizing statistical analysis) can be performed with the tReasure package.

CONCLUSIONS

tReasure is an open-source software available for download at https://treasure.pmrc.re.kr and will be indispensable for users who have little experience with command-line software to explore the biological implication of tRNA expression.

Analysis of eukaryotic lincRNA sequences indicates signatures of hindered translation linked to selection pressure

Long intergenic noncoding RNAs (lincRNAs) represent a large fraction of transcribed loci in eukaryotic genomes. Although classified as noncoding, most lincRNAs contain open reading frames (ORFs), and it remains unclear why cytoplasmic lincRNAs are not or very inefficiently translated. Here, we analyzed signatures of hindered translation in lincRNA sequences from five eukaryotes, covering a range of natural selection pressures. In fission yeast and Caenorhabditis elegans, that is, species under strong selection, we detected significantly shorter ORFs, a suboptimal sequence context around start codons for translation initiation, and trinucleotides (“codons”) corresponding to less abundant tRNAs than for neutrally evolving control sequences, likely impeding translation elongation. For human, we detected signatures for cell-type-specific hindrance of lincRNA translation, in particular codons in abundant cytoplasmic lincRNAs corresponding to lower expressed tRNAs than control codons, in three out of five human cell lines. We verified that varying tRNA expression levels between cell lines are reflected in the amount of ribosomes bound to cytoplasmic lincRNAs in each cell line. We further propose that codons at ORF starts are particularly important for reducing ribosome-binding to cytoplasmic lincRNA ORFs. Altogether, our analyses indicate that in species under stronger selection lincRNAs evolved sequence features generally hindering translation and support cell-type-specific hindrance of translation efficiency in human lincRNAs. The sequence signatures we have identified may improve predicting peptide-coding and genuine noncoding lincRNAs in a cell type.

5' Half of specific tRNAs feeds back to promote corresponding tRNA gene transcription in vertebrate embryos

5′tRFls are small transfer RNA (tRNA) fragments derived from 5′ half of mature tRNAs. However, it is unknown whether 5′tRFls could feed back to regulate tRNA biogenesis. Here, we show that 5′tRFl^Gly/GCC and 5′tRFl^Glu/CTC function to promote transcription of corresponding tRNA genes and are essential for vertebrate early embryogenesis. During zebrafish embryogenesis, dynamics of 5′tRFl^Gly/GCC and 5′tRFl^Glu/CTC levels correlates with that of tRNA^Gly/GCC and tRNA^Glu/CTC levels. Morpholino-mediated knockdown of 5′tRFl^Gly/GCC or 5′tRFl^Glu/CTC down-regulates tRNA^Gly/GCC or tRNA^Glu/CTC levels, respectively, and causes embryonic lethality that is efficiently rescued by coinjection of properly refolded corresponding tRNA. In zebrafish embryos, tRNA:DNA and 5′tRFl:DNA hybrids commonly exist on the template strand of tRNA genes. Mechanistically, unstable 5′tRFl:DNA hybrid may prevent the formation of transcriptionally inhibitory stable tRNA:DNA hybrids on the same tRNA loci so as to facilitate tRNA gene transcription. The uncovered mechanism may be implicated in other physiological and pathological processes.

tRNA Metabolism and Lung Cancer: Beyond Translation

Lung cancer, one of the most malignant tumors, has extremely high morbidity and mortality, posing a serious threat to global health. It is an urgent need to fully understand the pathogenesis of lung cancer and provide new ideas for its treatment. Interestingly, accumulating evidence has identified that transfer RNAs (tRNAs) and tRNA metabolism–associated enzymes not only participate in the protein translation but also play an important role in the occurrence and development of lung cancer. In this review, we summarize the different aspects of tRNA metabolism in lung cancer, such as tRNA transcription and mutation, tRNA molecules and derivatives, tRNA-modifying enzymes, and aminoacyl-tRNA synthetases (ARSs), aiming at a better understanding of the pathogenesis of lung cancer and providing new therapeutic strategies for it.

DBtRend: A Web-Server of tRNA Expression Profiles from Small RNA Sequencing Data in Humans

Transfer RNA (tRNA), a key component of the translation machinery, plays critical roles in stress conditions and various diseases. While knowledge regarding the importance of tRNA function is increasing, its biological roles are still not well understood. There is currently no comprehensive database or web server providing the expression landscape of tRNAs across a variety of human tissues and diseases. Here, we constructed a user-friendly and interactive database, DBtRend, which provides a profile of mature tRNA expression across various biological conditions by reanalyzing the small RNA or microRNA sequencing data from the Cancer Genome Atlas (TCGA) and NCBI's Gene Expression Omnibus (GEO) in humans. Users can explore not only the expression values of mature individual tRNAs in the human genome, but also those of isodecoders and isoacceptors based on our specific pipelines. DBtRend provides the expressed patterns of tRNAs, the differentially expressed tRNAs in different biological conditions, and the information of samples or patients, tissue types, and molecular subtype of cancers. The database is expected to help researchers interested in functional discoveries of tRNAs.

Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

BACKGROUND

Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest.

METHODS

We analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues.

RESULTS

We identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research.

CONCLUSIONS

Based on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/ . These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.

Persistent Cancer Cells: The Deadly Survivors

Persistent cancer cells are the discrete and usually undetected cells that survive cancer drug treatment and constitute a major cause of treatment failure. These cells are characterized by their slow proliferation, highly flexible energy consumption, adaptation to their microenvironment, and phenotypic plasticity. Mechanisms that underlie their persistence offer highly coveted and sought-after therapeutic targets, and include diverse epigenetic, transcriptional, and translational regulatory processes, as well as complex cell-cell interactions. Although the successful clinical targeting of persistent cancer cells remains to be realized, immense progress has been made in understanding their persistence, yielding promising preclinical results.

The RNA landscape of the human placenta in health and disease

The placenta is the interface between mother and fetus and inadequate function contributes to short and long-term ill-health. The placenta is absent from most large-scale RNA-Seq datasets. We therefore analyze long and small RNAs (~101 and 20 million reads per sample respectively) from 302 human placentas, including 94 cases of preeclampsia (PE) and 56 cases of fetal growth restriction (FGR). The placental transcriptome has the seventh lowest complexity of 50 human tissues: 271 genes account for 50% of all reads. We identify multiple circular RNAs and validate 6 of these by Sanger sequencing across the back-splice junction. Using large-scale mass spectrometry datasets, we find strong evidence of peptides produced by translation of two circular RNAs. We also identify novel piRNAs which are clustered on Chr1 and Chr14. PE and FGR are associated with multiple and overlapping differences in mRNA, lincRNA and circRNA but fewer consistent differences in small RNAs. Of the three protein coding genes differentially expressed in both PE and FGR, one encodes a secreted protein FSTL3 (follistatin-like 3). Elevated serum levels of FSTL3 in pregnant women are predictive of subsequent PE and FGR. To aid visualization of our placenta transcriptome data, we develop a web application ( https://www.obgyn.cam.ac.uk/placentome/ ).

Translational adaptation of human viruses to the tissues they infect

Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of 502 human-infecting viruses and determine that tropism explains changes in codon usage. Using the tRNA abundances across 23 human tissues from The Cancer Genome Atlas (TCGA), we build an in silico model of translational efficiency that validates the correspondence of the viral codon usage with the translational machinery of their tropism. For instance, we detect that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is specifically adapted to the upper respiratory tract and alveoli. Furthermore, this correspondence is specifically defined in early viral proteins. The observed tissue-specific translational efficiency could be useful for the development of antiviral therapies and vaccines.

Translational remodeling by RNA-binding proteins and noncoding RNAs

Responsible for generating the proteome that controls phenotype, translation is the ultimate convergence point for myriad upstream signals that influence gene expression. System-wide adaptive translational reprogramming has recently emerged as a pillar of cellular adaptation. As classic regulators of mRNA stability and translation efficiency, foundational studies established the concept of collaboration and competition between RNA-binding proteins (RBPs) and noncoding RNAs (ncRNAs) on individual mRNAs. Fresh conceptual innovations now highlight stress-activated, evolutionarily conserved RBP networks and ncRNAs that increase the translation efficiency of populations of transcripts encoding proteins that participate in a common cellular process. The discovery of post-transcriptional functions for long noncoding RNAs (lncRNAs) was particularly intriguing given their cell-type-specificity and historical definition as nuclear-functioning epigenetic regulators. The convergence of RBPs, lncRNAs, and microRNAs on functionally related mRNAs to enable adaptive protein synthesis is a newer biological paradigm that highlights their role as "translatome (protein output) remodelers" and reinvigorates the paradigm of "RNA operons." Together, these concepts modernize our understanding of cellular stress adaptation and strategies for therapeutic development. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Translation > Translation Regulation Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Fighting Drug Resistance through the Targeting of Drug-Tolerant Persister Cells

Designing specific therapies for drug-resistant cancers is arguably the ultimate challenge in cancer therapy. While much emphasis has been put on the study of genetic alterations that give rise to drug resistance, much less is known about the non-genetic adaptation mechanisms that operate during the early stages of drug resistance development. Drug-tolerant persister cells have been suggested to be key players in this process. These cells are thought to have undergone non-genetic adaptations that enable survival in the presence of a drug, from which full-blown resistant cells may emerge. Such initial adaptations often involve engagement of stress response programs to maintain cancer cell viability. In this review, we discuss the nature of drug-tolerant cancer phenotypes, as well as the non-genetic adaptations involved. We also discuss how malignant cells employ homeostatic stress response pathways to mitigate the intrinsic costs of such adaptations. Lastly, we discuss which vulnerabilities are introduced by these adaptations and how these might be exploited therapeutically.

Small non-coding RNAs in human cancer: function, clinical utility, and characterization

Small non-coding RNAs (sncRNAs) play critical roles in multiple regulatory processes, including transcription, post-transcription, and translation. Emerging evidence reveals the critical roles of sncRNAs in cancer development and their potential role as biomarkers and/or therapeutic targets. In this paper, we review recent research on four sncRNA species with functional significance in cancer: small nucleolar RNAs, transfer RNA, small nuclear RNAs, and piwi-interacting RNAs. We introduce their functional roles in tumorigenesis and discuss the potential utility of sncRNAs as prognostic and diagnostic biomarkers and therapeutic targets. We further summarize approaches to characterize sncRNAs in a high-throughput manner, including the specific library construction and computational framework. Our review provides a perspective of the functions, clinical utility, and characterization of sncRNAs in cancer.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

The biological process of lysine-tRNA charging is therapeutically targetable in liver cancer

BACKGROUND & AIMS

Mature transfer RNAs (tRNA) charged with amino acids decode mRNA to synthesize proteins. Dysregulation of translational machineries has a fundamental impact on cancer biology. This study aims to map the tRNAome landscape in liver cancer patients and to explore potential therapeutic targets at the interface of charging amino acid with tRNA.

METHODS

Resected tumour and paired tumour-free (TFL) tissues from hepatocellular carcinoma (HCC) patients (n = 69), and healthy liver tissues from organ transplant donors (n = 21), HCC cell lines, and cholangiocarcinoma (CC) patient-derived tumour organoids were used.

RESULTS

The expression levels of different mature tRNAs were highly correlated and closely clustered within individual tissues, suggesting that different members of the tRNAome function cooperatively in protein translation. Interestingly, high expression of tRNA-Lys-CUU in HCC tumours was associated with more tumour recurrence (HR 1.1; P = .022) and worse patient survival (HR 1.1; P = .0037). The expression of Lysyl-tRNA Synthetase (KARS), the enzyme catalysing the charge of lysine to tRNA-Lys-CUU, was significantly upregulated in HCC tumour tissues compared to tumour-free liver tissues. In HCC cell lines, lysine deprivation, KARS knockdown or treatment with the KARS inhibitor cladosporin effectively inhibited overall cell growth, single cell-based colony formation and cell migration. This was mechanistically mediated by cell cycling arrest and induction of apoptosis. Finally, these inhibitory effects were confirmed in 3D cultured patient-derived CC organoids.

CONCLUSIONS

The biological process of charging tRNA-Lys-CUU with lysine sustains liver cancer cell growth and migration, and is clinically relevant in HCC patients. This process can be therapeutically targeted and represents an unexplored territory for developing novel treatment strategies against liver cancer.

Manipulation of the human tRNA pool reveals distinct tRNA sets that act in cellular proliferation or cell cycle arrest

Different subsets of the tRNA pool in human cells are expressed in different cellular conditions. The 'proliferation-tRNAs' are induced upon normal and cancerous cell division, while the 'differentiation-tRNAs' are active in non-dividing, differentiated cells. Here we examine the essentiality of the various tRNAs upon cellular growth and arrest. We established a CRISPR-based editing procedure with sgRNAs that each target a tRNA family. We measured tRNA essentiality for cellular growth and found that most proliferation-tRNAs are essential compared to differentiation- tRNAs in rapidly growing cell lines. Yet in more slowly dividing lines, the differentiation-tRNAs were more essential. In addition, we measured the essentiality of each tRNA family upon response to cell cycle arresting signals. Here we detected a more complex behavior with both proliferation-tRNAs and differentiation tRNAs showing various levels of essentiality. These results provide the so-far most comprehensive functional characterization of human tRNAs with intricate roles in various cellular states.

What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis

Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.

In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species

The coronavirus disease COVID-19 constitutes the most severe pandemic of the last decades having caused more than 1 million deaths worldwide. The SARS-CoV-2 virus recognizes the angiotensin converting enzyme 2 (ACE2) on the surface of human cells through its spike protein. It has been reported that the coronavirus can mildly infect cats, and ferrets, and perhaps dogs while not pigs, mice, chicken and ducks. Differences in viral infectivity among different species or individuals could be due to amino acid differences at key positions of the host proteins that interact with the virus, the immune response, expression levels of host proteins and translation efficiency of the viral proteins among other factors. Here, first we have addressed the importance that sequence variants of different animal species, human individuals and virus isolates have on the interaction between the RBD domain of the SARS-CoV-2 spike S protein and human angiotensin converting enzyme 2 (ACE2). Second, we have looked at viral translation efficiency by using the tRNA adaptation index. We find that integration of both interaction energy with ACE2 and translational efficiency explains animal infectivity. Humans are the top species in which SARS-CoV-2 is both efficiently translated as well as optimally interacting with ACE2. We have found some viral mutations that increase affinity for hACE and some hACE2 variants affecting ACE2 stability and virus binding. These variants suggest that different sensitivities to coronavirus infection in humans could arise in some cases from allelic variability affecting ACE2 stability and virus binding.

Mutation bias within oncogene families is related to proliferation-specific codon usage

It is well known that in cancer gene families some members are more frequently mutated in tumor samples than their family counterparts. A paradigmatic case of this phenomenon is KRAS from the RAS family. Different explanations have been proposed ranging from differential interaction with other proteins to preferential expression or localization. Interestingly, it has been described that despite the high amino acid identity between RAS family members, KRAS employs an intriguing differential codon usage. Here, we found that this phenomenon is not exclusive to the RAS family. Indeed, in the RAS family and other oncogene families with two or three members, the most prevalently mutated gene in tumor samples employs a differential codon usage that is characteristic of genes involved in proliferation. Prompted by these observations, we chose the RAS family to experimentally demonstrate that the translation efficiency of oncogenes that are preferentially mutated in tumor samples is increased in proliferative cells compared to quiescent cells. These results were further validated by assessing the translation efficiency of KRAS in cell lines that differ in their tRNA expression profile. These differences are related to the cell division rate of the studied cells and thus suggest an important role in context-specific oncogene expression regulation. Altogether, our study demonstrates that dynamic translation programs contribute to shaping the expression profiles of oncogenes. Therefore, we propose this codon bias as a regulatory layer to control cell context-specific expression and explain the differential prevalence of mutations in certain members of oncogene families.

Control of translation elongation in health and disease

Regulation of protein synthesis makes a major contribution to post-transcriptional control pathways. During disease, or under stress, cells initiate processes to reprogramme protein synthesis and thus orchestrate the appropriate cellular response. Recent data show that the elongation stage of protein synthesis is a key regulatory node for translational control in health and disease. There is a complex set of factors that individually affect the overall rate of elongation and, for the most part, these influence either transfer RNA (tRNA)- and eukaryotic elongation factor 1A (eEF1A)-dependent codon decoding, and/or elongation factor 2 (eEF2)-dependent ribosome translocation along the mRNA. Decoding speeds depend on the relative abundance of each tRNA, the cognate:near-cognate tRNA ratios and the degree of tRNA modification, whereas eEF2-dependent ribosome translocation is negatively regulated by phosphorylation on threonine-56 by eEF2 kinase. Additional factors that contribute to the control of the elongation rate include epigenetic modification of the mRNA, coding sequence variation and the expression of eIF5A, which stimulates peptide bond formation between proline residues. Importantly, dysregulation of elongation control is central to disease mechanisms in both tumorigenesis and neurodegeneration, making the individual key steps in this process attractive therapeutic targets. Here, we discuss the relative contribution of individual components of the translational apparatus (e.g. tRNAs, elongation factors and their modifiers) to the overall control of translation elongation and how their dysregulation contributes towards disease processes.

Translational efficiency across healthy and tumor tissues is proliferation-related

Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon-anticodon co-adaptation in humans is not completely understood, nor is its effect on tissue-specific protein levels. Here, we first validated the accuracy of small RNA-seq for tRNA quantification across five human cell lines. We then analyzed the tRNA abundance of more than 8,000 tumor samples from TCGA, together with their paired mRNA-seq and proteomics data, to determine the Supply-to-Demand Adaptation. We thereby elucidate that the dynamic adaptation of the tRNA pool is largely related to the proliferative state across tissues. The distribution of such tRNA pools over the whole cellular translatome affects the subsequent translational efficiency, which functionally determines a condition-specific expression program both in healthy and tumor states. Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ProCCA and GlyGGT, is associated with poor patient survival. The regulation of these tRNA profiles is partly explained by the tRNA gene copy numbers and their promoter DNA methylation.