Ribosome Footprint Profiling of Translation throughout the Genome

Uncovering the small proteome of Methanosarcina mazei using Ribo-seq and peptidomics under different nitrogen conditions

The mesophilic methanogenic archaeal model organism Methanosarcina mazei strain Gö1 is crucial for climate and environmental research due to its ability to produce methane. Here, we establish a Ribo-seq protocol for M. mazei strain Gö1 under two growth conditions (nitrogen sufficiency and limitation). The translation of 93 previously annotated and 314 unannotated small ORFs, coding for proteins ≤ 70 amino acids, is predicted with high confidence based on Ribo-seq data. LC-MS analysis validates the translation for 62 annotated small ORFs and 26 unannotated small ORFs. Epitope tagging followed by immunoblotting analysis confirms the translation of 13 out of 16 selected unannotated small ORFs. A comprehensive differential transcription and translation analysis reveals that 29 of 314 unannotated small ORFs are differentially regulated in response to nitrogen availability at the transcriptional and 49 at the translational level. A high number of reported small RNAs are emerging as dual-function RNAs, including sRNA154, the central regulatory small RNA of nitrogen metabolism. Several unannotated small ORFs are conserved in Methanosarcina species and overproducing several (small ORF encoded) small proteins suggests key physiological functions. Overall, the comprehensive analysis opens an avenue to elucidate the function(s) of multitudinous small proteins and dual-function RNAs in M. mazei.

The eukaryotic translation initiation factor eIF4E regulates flowering and circadian rhythm in Arabidopsis

Translation initiation is a critical, rate-limiting step in protein synthesis. The eukaryotic translation initiation factor 4E (eIF4E) plays an essential role in this process. However, the mechanisms by which eIF4E-dependent translation initiation regulates plant growth and development remain not fully understood. In this study, we found that Arabidopsis eIF4E proteins are distributed in both the nucleus and cytoplasm, with only the cytoplasmic eIF4E being involved in the control of photoperiodic flowering. Genome-wide translation profiling using Ribo-tag sequencing reveals that eIF4E may regulate plant flowering by maintaining the homeostatic translation of components in the photoperiodic flowering pathway. eIF4E not only regulates the translation of flowering genes such as FLOWERING LOCUS T (FT) and FLOWERING LOCUS D (FLD) but also influences the translation of circadian genes like CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and PSEUDO-RESPONSE REGULATOR 9 (PRR9). Consistently, our results show that the eIF4E modulates the rhythmic oscillation of the circadian clock. Together, our study provides mechanistic insights into how the protein translation regulates multiple developmental processes in Arabidopsis, including the circadian clock and photoperiodic flowering.

Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster

Accuracy and efficiency are fundamental to mRNA translation. Codon usage bias is widespread across species. Despite the long-standing association between optimized codon usage and improved translation, our understanding of its evolutionary basis and functional effects remains limited. Drosophila is widely used to study codon usage bias, but genome-scale experimental data are scarce. Using high-resolution mass spectrometry data from Drosophila melanogaster, we show that optimal codons have lower translation errors than nonoptimal codons after accounting for these biases. Genomic-scale analysis of ribosome profiling data shows that optimal codons are translated more rapidly than nonoptimal codons. Although we find no long-term selection favoring synonymous mutations in D. melanogaster after diverging from D. simulans, we identify signatures of positive selection driving codon optimization in the D. melanogaster population. These findings expand our understanding of the functional consequences of codon optimization and serve as a foundation for future investigations.

Microscale marvels: unveiling the macroscopic significance of micropeptides in human health

Non-coding RNA encodes micropeptides from small open reading frames located within the RNA. Interestingly, these micropeptides are involved in a variety of functions within the body. They are emerging as the resolving piece of the puzzle for complex biomolecular signaling pathways within the body. Recent studies highlight the pivotal role of small peptides in regulating important biological processes like DNA repair, gene expression, muscle regeneration, immune responses, etc. On the contrary, altered expression of micropeptides also plays a pivotal role in the progression of various diseases like cardiovascular diseases, neurological disorders and several types of cancer, including colorectal cancer, hepatocellular cancer, lung cancer, etc. This review delves into the dual impact of micropeptides on health and pathology, exploring their pivotal role in preserving normal physiological homeostasis and probing their involvement in the triggering and progression of diseases.

Calorie restriction and rapamycin distinctly restore non-canonical ORF translation in the muscles of aging mice

Loss of protein homeostasis is one of the hallmarks of aging. As such, interventions that restore proteostasis should slow down the aging process and improve healthspan. Two of the most broadly used anti-aging interventions that are effective in organisms from yeast to mammals are calorie restriction (CR) and rapamycin (RM) treatment. To identify the regulatory mechanisms by which these interventions improve the protein homeostasis, we carried out ribosome footprinting in the muscle of mice aged under standard conditions, or under long-term treatment with CR or RM. We found that the treatments distinctly impact the non-canonical translation, RM primarily remodeling the translation of upstream open reading frames (uORFs), while CR restores stop codon readthrough and the translation of downstream ORFs. Proteomics analysis revealed the expression of numerous non-canonical ORFs at the protein level. The corresponding peptides may provide entry points for therapies aiming to maintain muscle function and extend health span.

Optimization of ribosome profiling in plants including structural analysis of rRNA fragments

BACKGROUND

Ribosome profiling (or Ribo-seq) is a technique that provides genome-wide information on the translational landscape (translatome). Across different plant studies, variable methodological setups have been described which raises questions about the general comparability of data that were generated from diverging methodologies. Furthermore, a common problem when performing Ribo-seq are abundant rRNA fragments that are wastefully incorporated into the libraries and dramatically reduce sequencing depth. To remove these rRNA contaminants, it is common to perform preliminary trials to identify these fragments because they are thought to vary depending on nuclease treatment, tissue source, and plant species.

RESULTS

Here, we compile valuable insights gathered over years of generating Ribo-seq datasets from different species and experimental setups. We highlight which technical steps are important for maintaining cross experiment comparability and describe a highly efficient approach for rRNA removal. Furthermore, we provide evidence that many rRNA fragments are structurally preserved over diverse nuclease regimes, as well as across plant species. Using a recently published cryo-electron microscopy (cryo-EM) structure of the tobacco 80S ribosome, we show that the most abundant rRNA fragments are spatially derived from the solvent-exposed surface of the ribosome.

CONCLUSION

The guidelines presented here shall aid newcomers in establishing ribosome profiling in new plant species and provide insights that will help in customizing the methodology for individual research goals.

Experimental approaches to studying translation in plant semi-autonomous organelles

Plant mitochondria and chloroplasts are semi-autonomous organelles originated from free-living bacteria that have retained reduced genomes during evolution. As a consequence, relatively few of the mitochondrial and chloroplast proteins are encoded in the organellar genomes and synthesized by the organellar ribosomes. Since both organellar genomes encode mainly components of the energy transduction systems, oxidative phosphorylation in mitochondria and photosynthetic apparatus in chloroplasts, understanding organellar translation is critical for a thorough comprehension of key aspects of mitochondrial and chloroplast activity affecting plant growth and development. Recent studies have clearly shown that translation is a key regulatory node in the expression of plant organellar genes, underscoring the need for an adequate methodology to study this unique stage of gene expression. The organellar translatome can be analysed by studying newly synthesized proteins or the mRNA pool recruited to the organellar ribosomes. In this review, we present experimental approaches used for studying translation in plant bioenergetic organelles. Their benefits and limitations, as well as the critical steps, are discussed. Additionally, we briefly mention several recently developed strategies to study organellar translation that have not yet been applied to plants.

Translational Regulation of Duplicated Gene Expression Evolution in Allopolyploid Cotton

Polyploidy, a prevalent event in plant evolution, drives phenotypic diversification and speciation. While transcriptional changes and regulation in polyploids have been extensively studied, the translational level impact remains largely unexplored. To address this gap, we conducted a comparative transcriptomic and translatomic analysis of cotton leaves from allopolyploid species G. hirsutum (AD1) and G. barbadense (AD2) relative to their model A-genome and D-genome diploid progenitors. Our data revealed that while allopolyploidization significantly affects the transcriptional landscape, its impact on translation was relatively modest, evidenced by a narrower expression range and fewer expression changes in ribosome-protected fragments than in mRNA levels. Allopolyploid-specific changes commonly identified in both AD1 and AD2 were observed in 7393 genes at either transcriptional or translational levels. Interestingly, the majority of translational changes exhibited concordant down-regulation in both ribosome-protected fragments and mRNA, particularly associated with terpenoid synthesis and metabolism (352 genes). Regarding translational efficiency (TE), at least one-fifth of cotton genes exhibit translational level regulation, with a general trend of more down-regulation (13.9-15.1%) than up-regulation (7.3-11.2%) of TE. The magnitude of translational regulation was slightly reduced in allopolyploids compared with diploids, and allopolyploidy tends to have a more profound impact on genes and functional associations with ultra-low TE. Moreover, we demonstrated a reduced extent of homeolog expression biases during translation compared with transcription. Our study provides insights into the regulatory consequences of allopolyploidy post-transcription, contributing to a comprehensive understanding of regulatory mechanisms of duplicated gene expression evolution.

Legume-rhizobia symbiosis: Translatome analysis

Leguminous plants can establish endosymbiotic relationships with nitrogen-fixing soil rhizobacteria. Bacterial infection and nodule organogenesis are two independent but highly coordinated genetic programs that are active during this interaction. These genetic programs can be regulated along all the stages of gene expression. Most of the studies, for both eukaryotes and prokaryotes, focused on the transcriptional regulation level determining the abundance of mRNAs. However, it has been demonstrated that mRNA levels only sometimes correlate with the abundance or activity of the coded proteins. For this reason, in the past two decades, interest in the role of translational control of gene expression has increased, since the subset of mRNA being actively translated outperforms the information gained only by the transcriptome. In the case of legume-rhizobia interactions, the study of the translatome still needs to be explored further. Therefore, this review aims to discuss the methodologies for analyzing polysome-associated mRNAs at the genome-scale and their contribution to studying translational control to understand the complexity of this symbiotic interaction. Moreover, the Dual RNA-seq approach is discussed for its relevance in the context of a symbiotic nodule, where intricate multi-species gene expression networks occur.

Beyond traditional translation: ncRNA derived peptides as modulators of tumor behaviors

Within the intricate tapestry of molecular research, noncoding RNAs (ncRNAs) were historically overshadowed by a pervasive presumption of their inability to encode proteins or peptides. However, groundbreaking revelations have challenged this notion, unveiling select ncRNAs that surprisingly encode peptides specifically those nearing a succinct 100 amino acids. At the forefront of this epiphany stand lncRNAs and circRNAs, distinctively characterized by their embedded small open reading frames (sORFs). Increasing evidence has revealed different functions and mechanisms of peptides/proteins encoded by ncRNAs in cancer, including promotion or inhibition of cancer cell proliferation, cellular metabolism (glucose metabolism and lipid metabolism), and promotion or concerted metastasis of cancer cells. The discoveries not only accentuate the depth of ncRNA functionality but also open novel avenues for oncological research and therapeutic innovations. The main difficulties in the study of these ncRNA-derived peptides hinge crucially on precise peptide detection and sORFs identification. Here, we illuminate cutting-edge methodologies, essential instrumentation, and dedicated databases tailored for unearthing sORFs and peptides. In addition, we also conclude the potential of clinical applications in cancer therapy.

Nuclear release of eIF1 globally increases stringency of start-codon selection to preserve mitotic arrest physiology

Regulated start-codon selection has the potential to reshape the proteome through the differential production of uORFs, canonical proteins, and alternative translational isoforms. However, conditions under which start-codon selection is altered remain poorly defined. Here, using transcriptome-wide translation initiation site profiling, we reveal a global increase in the stringency of start-codon selection during mammalian mitosis. Low-efficiency initiation sites are preferentially repressed in mitosis, resulting in pervasive changes in the translation of thousands of start sites and their corresponding protein products. This increased stringency of start-codon selection during mitosis results from increased interactions between the key regulator of start-codon selection, eIF1, and the 40S ribosome. We find that increased eIF1-40S ribosome interactions during mitosis are mediated by the release of a nuclear pool of eIF1 upon nuclear envelope breakdown. Selectively depleting the nuclear pool of eIF1 eliminates the changes to translational stringency during mitosis, resulting in altered mitotic proteome composition. In addition, preventing mitotic translational rewiring results in substantially increased cell death and decreased mitotic slippage following treatment with anti-mitotic chemotherapeutics. Thus, cells globally control translation initiation stringency with critical roles during the mammalian cell cycle to preserve mitotic cell physiology.

Rules and impacts of nonsense-mediated mRNA decay in the degradation of long noncoding RNAs

Nonsense-mediated mRNA decay (NMD) is a quality-control process that selectively degrades mRNAs having premature termination codon, upstream open reading frame, or unusually long 3'UTR. NMD detects such mRNAs and rapidly degrades them during initial rounds of translation in the eukaryotic cells. Since NMD is a translation-dependent cytoplasmic mRNA surveillance process, the noncoding RNAs were initially believed to be NMD-resistant. The sequence feature-based analysis has revealed that many putative long noncoding RNAs (lncRNAs) have short open reading frames, most of which have translation potential. Subsequent transcriptome-based molecular studies showed an association of a large set of such putative lncRNAs with translating ribosomes, and some of them produce stable and functionally active micropeptides. The translationally active lncRNAs typically have relatively longer and unprotected 3'UTR, which can induce their NMD-dependent degradation. This review defines the mechanism and regulation of NMD-dependent degradation of lncRNAs and its impact on biological processes related to the functions of lncRNAs or their encoded micropeptides. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease.

Micropeptides: potential treatment strategies for cancer

Some noncoding RNAs (ncRNAs) carry open reading frames (ORFs) that can be translated into micropeptides, although noncoding RNAs (ncRNAs) have been previously assumed to constitute a class of RNA transcripts without coding capacity. Furthermore, recent studies have revealed that ncRNA-derived micropeptides exhibit regulatory functions in the development of many tumours. Although some of these micropeptides inhibit tumour growth, others promote it. Understanding the role of ncRNA-encoded micropeptides in cancer poses new challenges for cancer research, but also offers promising prospects for cancer therapy. In this review, we summarize the types of ncRNAs that can encode micropeptides, highlighting recent technical developments that have made it easier to research micropeptides, such as ribosome analysis, mass spectrometry, bioinformatics methods, and CRISPR/Cas9. Furthermore, based on the distribution of micropeptides in different subcellular locations, we explain the biological functions of micropeptides in different human cancers and discuss their underestimated potential as diagnostic biomarkers and anticancer therapeutic targets in clinical applications, information that may contribute to the discovery and development of new micropeptide-based tools for early diagnosis and anticancer drug development.

The role of molecular chaperone CCT/TRiC in translation elongation: A literature review

Protein synthesis from mRNA is an energy-intensive and strictly controlled biological process. Translation elongation is a well-coordinated and multifactorial step in translation that ensures the accurate and efficient addition of amino acids to a growing nascent-peptide chain encoded in the sequence of messenger RNA (mRNA). Which undergoes dynamic regulation due to cellular state and environmental determinants. An expanding body of research points to translational elongation as a crucial process that controls the translation of an mRNA through multiple feedback mechanisms. Molecular chaperones are key players in protein homeostasis to keep the balance between protein synthesis, folding, assembly, and degradation. Chaperonin-containing tailless complex polypeptide 1 (CCT) or tailless complex polypeptide 1 ring complex (TRiC) is an essential eukaryotic molecular chaperone that plays an essential role in assisting cellular protein folding and suppressing protein aggregation. In this review, we give an overview of the factors that influence translation elongation, focusing on different functions of molecular chaperones in translation elongation, including how they affect translation rates and post-translational modifications. We also provide an understanding of the mechanisms by which the molecular chaperone CCT plays multiple roles in the elongation phase of eukaryotic protein synthesis.

Translation velocity determines the efficacy of engineered suppressor tRNAs on pathogenic nonsense mutations

Nonsense mutations - the underlying cause of approximately 11% of all genetic diseases - prematurely terminate protein synthesis by mutating a sense codon to a premature stop or termination codon (PTC). An emerging therapeutic strategy to suppress nonsense defects is to engineer sense-codon decoding tRNAs to readthrough and restore translation at PTCs. However, the readthrough efficiency of the engineered suppressor tRNAs (sup-tRNAs) largely varies in a tissue- and sequence context-dependent manner and has not yet yielded optimal clinical efficacy for many nonsense mutations. Here, we systematically analyze the suppression efficacy at various pathogenic nonsense mutations. We discover that the translation velocity of the sequence upstream of PTCs modulates the sup-tRNA readthrough efficacy. The PTCs most refractory to suppression are embedded in a sequence context translated with an abrupt reversal of the translation speed leading to ribosomal collisions. Moreover, modeling translation velocity using Ribo-seq data can accurately predict the suppression efficacy at PTCs. These results reveal previously unknown molecular signatures contributing to genotype-phenotype relationships and treatment-response heterogeneity, and provide the framework for the development of personalized tRNA-based gene therapies.

N-Acetyltransferase 10 represses Uqcr11 and Uqcrb independently of ac4C modification to promote heart regeneration

Translational control is crucial for protein production in various biological contexts. Here, we use Ribo-seq and RNA-seq to show that genes related to oxidative phosphorylation are translationally downregulated during heart regeneration. We find that Nat10 regulates the expression of Uqcr11 and Uqcrb mRNAs in mouse and human cardiomyocytes. In mice, overexpression of Nat10 in cardiomyocytes promotes cardiac regeneration and improves cardiac function after injury. Conversely, treating neonatal mice with Remodelin-a Nat10 pharmacological inhibitor-or genetically removing Nat10 from their cardiomyocytes both inhibit heart regeneration. Mechanistically, Nat10 suppresses the expression of Uqcr11 and Uqcrb independently of its ac4C enzyme activity. This suppression weakens mitochondrial respiration and enhances the glycolytic capacity of the cardiomyocytes, leading to metabolic reprogramming. We also observe that the expression of Nat10 is downregulated in the cardiomyocytes of P7 male pig hearts compared to P1 controls. The levels of Nat10 are also lower in female human failing hearts than non-failing hearts. We further identify the specific binding regions of Nat10, and validate the pro-proliferative effects of Nat10 in cardiomyocytes derived from human embryonic stem cells. Our findings indicate that Nat10 is an epigenetic regulator during heart regeneration and could potentially become a clinical target.

Modeling neurodevelopmental disorder-associated human AGO1 mutations in Caenorhabditis elegans Argonaute alg-1

MicroRNAs (miRNA) associate with Argonaute (AGO) proteins and repress gene expression by base pairing to sequences in the 3' untranslated regions of target genes. De novo coding variants in the human AGO genes AGO1 and AGO2 cause neurodevelopmental disorders (NDD) with intellectual disability, referred to as Argonaute syndromes. Most of the altered amino acids are conserved between the miRNA-associated AGO in Homo sapiens and Caenorhabditis elegans, suggesting that the human mutations could disrupt conserved functions in miRNA biogenesis or activity. We genetically modeled four human AGO1 mutations in C. elegans by introducing identical mutations into the C. elegans AGO1 homologous gene, alg-1. These alg-1 NDD mutations cause phenotypes in C. elegans indicative of disrupted miRNA processing, miRISC (miRNA silencing complex) formation, and/or target repression. We show that the alg-1 NDD mutations are antimorphic, causing developmental and molecular phenotypes stronger than those of alg-1 null mutants, likely by sequestrating functional miRISC components into non-functional complexes. The alg-1 NDD mutations cause allele-specific disruptions in mature miRNA profiles, accompanied by perturbation of downstream gene expression, including altered translational efficiency and/or messenger RNA abundance. The perturbed genes include those with human orthologs whose dysfunction is associated with NDD. These cross-clade genetic studies illuminate fundamental AGO functions and provide insights into the conservation of miRNA-mediated post-transcriptional regulatory mechanisms.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas

Ribosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq yields genome-wide insight into translational dynamics and post-transcriptional control of gene expression. Here, we provide details on the Ribo-seq method and the subsequent analysis with the unicellular model alga Chlamydomonas reinhardtii (Chlamydomonas) for generating high-resolution data covering more than 10 000 different transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5' and 3' sections of transcripts and characteristics of eukaryotic translation termination, which are fundamentally distinct for chloroplast translation. In chloroplasts, a heterogeneous RPF size distribution along the coding sequence indicates specific regulatory phases during protein synthesis. For example, local accumulation of small RPFs correlates with local slowdown of psbA translation, possibly uncovering an uncharacterized regulatory step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light-harvesting complex proteins, LHCs. By providing high-quality datasets for all subcellular genomes and attaching our data to the Chlamydomonas reference genome, we aim to make ribosome profiles easily accessible for the broad research community. The data can be browsed without advanced bioinformatic background knowledge for translation output levels of specific genes and their splice variants and for monitoring genome annotation.

A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X

The road from transcription to protein synthesis is paved with many obstacles, allowing for several modes of post-transcriptional regulation of gene expression. A fundamental player in mRNA biology is DDX3X, an RNA binding protein that canonically regulates mRNA translation. By monitoring dynamics of mRNA abundance and translation following DDX3X depletion, we observe stabilization of translationally suppressed mRNAs. We use interpretable statistical learning models to uncover GC content in the coding sequence as the major feature underlying RNA stabilization. This result corroborates GC content-related mRNA regulation detectable in other studies, including hundreds of ENCODE datasets and recent work focusing on mRNA dynamics in the cell cycle. We provide further evidence for mRNA stabilization by detailed analysis of RNA-seq profiles in hundreds of samples, including a Ddx3x conditional knockout mouse model exhibiting cell cycle and neurogenesis defects. Our study identifies a ubiquitous feature underlying mRNA regulation and highlights the importance of quantifying multiple steps of the gene expression cascade, where RNA abundance and protein production are often uncoupled.

Innovative computational tools provide new insights into the polyploid wheat genome

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Translatome and Transcriptome Analyses Reveal the Mechanism that Underlies the Enhancement of Salt Stress by the Small Peptide Ospep5 in Plants

Salt stress significantly impedes plant growth and the crop yield. This study utilized de novo transcriptome assembly and ribosome profiling to explore mRNA translation's role in rice salt tolerance. We identified unrecognized translated open reading frames (ORFs), including 42 upstream transcripts and 86 unannotated transcripts. A noteworthy discovery was the role of a small ORF, Ospep5, in conferring salt tolerance. Overexpression of Ospep5 in plants increased salt tolerance, while its absence led to heightened sensitivity. This hypothesis was corroborated by the findings that exogenous application of the synthetic small peptide Ospep5 bolstered salt tolerance in both rice and Arabidopsis. We found that the mechanism underpinning the Ospep5-mediated salt tolerance involves the maintenance of intracellular Na+/K+ homeostasis, facilitated by upregulation of high-affinity potassium transporters (HKT) and Na+/H+ exchangers (SOS1). Furthermore, a comprehensive multiomics approach, particularly ribosome profiling, is instrumental in uncovering unannotated ORFs and elucidating their functions in plant stress responses.

No country for old methods: New tools for studying microproteins

Microproteins encoded by small open reading frames (sORFs) have emerged as a fascinating frontier in genomics. Traditionally overlooked due to their small size, recent technological advancements such as ribosome profiling, mass spectrometry-based strategies and advanced computational approaches have led to the annotation of more than 7000 sORFs in the human genome. Despite the vast progress, only a tiny portion of these microproteins have been characterized and an important challenge in the field lies in identifying functionally relevant microproteins and understanding their role in different cellular contexts. In this review, we explore the recent advancements in sORF research, focusing on the new methodologies and computational approaches that have facilitated their identification and functional characterization. Leveraging these new tools hold great promise for dissecting the diverse cellular roles of microproteins and will ultimately pave the way for understanding their role in the pathogenesis of diseases and identifying new therapeutic targets.

Deficiency of the ribosomal protein uS10 (RPS20) reorganizes human cells translatome according to the abundance, CDS length and GC content of mRNAs

Ribosomal protein uS10, a product of the RPS20 gene, is an essential constituent of the small (40S) subunit of the human ribosome. Disruptive mutations in its gene are associated with a predisposition to hereditary colorectal carcinoma. Here, using HEK293T cells, we show that a deficiency of this protein leads to a decrease in the level of ribosomes (ribosomal shortage). RNA sequencing of the total and polysome-associated mRNA samples reveals hundreds of genes differentially expressed in the transcriptome (t)DEGs and translatome (p)DEGs under conditions of uS10 deficiency. We demonstrate that the (t)DEG and (p)DEG sets partially overlap, determine genes with altered translational efficiency (TE) and identify cellular processes affected by uS10 deficiency-induced ribosomal shortage. We reveal that translated mRNAs of upregulated (p)DEGs and genes with altered TE in uS10-deficient cells are generally more abundant and that their GC contents are significantly lower than those of the respective downregulated sets. We also observed that upregulated (p)DEGs have longer coding sequences. Based on our findings, we propose a combinatorial model describing the process of reorganization of mRNA translation under conditions of ribosomal shortage. Our results reveal rules according to which ribosomal shortage reorganizes the transcriptome and translatome repertoires of actively proliferating cells.

Molecular bases for strong phenotypic effects of single synonymous codon substitutions in the E. coli ccdB toxin gene

BACKGROUND

Single synonymous codon mutations typically have only minor or no effects on gene function. Here, we estimate the effects on cell growth of ~ 200 single synonymous codon mutations in an operonic context by mutating almost all positions of ccdB, the 101-residue long cytotoxin of the ccdAB Toxin-Antitoxin (TA) operon to most degenerate codons. Phenotypes were assayed by transforming the mutant library into CcdB sensitive and resistant E. coli strains, isolating plasmid pools, and subjecting them to deep sequencing. Since autoregulation is a hallmark of TA operons, phenotypes obtained for ccdB synonymous mutants after transformation in a RelE toxin reporter strain followed by deep sequencing provided information on the amount of CcdAB complex formed.

RESULTS

Synonymous mutations in the N-terminal region involved in translation initiation showed the strongest non-neutral phenotypic effects. We observe an interplay of numerous factors, namely, location of the codon, codon usage, t-RNA abundance, formation of anti-Shine Dalgarno sequences, predicted transcript secondary structure, and evolutionary conservation in determining phenotypic effects of ccdB synonymous mutations. Incorporation of an N-terminal, hyperactive synonymous mutation, in the background of the single synonymous codon mutant library sufficiently increased translation initiation, such that mutational effects on either folding or termination of translation became more apparent. Introduction of putative pause sites not only affects the translational rate, but might also alter the folding kinetics of the protein in vivo.

CONCLUSION

In summary, the study provides novel insights into diverse mechanisms by which synonymous mutations modulate gene function. This information is useful in optimizing heterologous gene expression in E. coli and understanding the molecular bases for alteration in gene expression that arise due to synonymous mutations.

SARS-CoV-2 infection engenders heterogeneous ribonucleoprotein interactions to impede translation elongation in the lungs

Translational regulation in tissue environments during in vivo viral pathogenesis has rarely been studied due to the lack of translatomes from virus-infected tissues, although a series of translatome studies using in vitro cultured cells with viral infection have been reported. In this study, we exploited tissue-optimized ribosome profiling (Ribo-seq) and severe-COVID-19 model mice to establish the first temporal translation profiles of virus and host genes in the lungs during SARS-CoV-2 pathogenesis. Our datasets revealed not only previously unknown targets of translation regulation in infected tissues but also hitherto unreported molecular signatures that contribute to tissue pathology after SARS-CoV-2 infection. Specifically, we observed gradual increases in pseudoribosomal ribonucleoprotein (RNP) interactions that partially overlapped the trails of ribosomes, being likely involved in impeding translation elongation. Contemporaneously developed ribosome heterogeneity with predominantly dysregulated 5 S rRNP association supported the malfunction of elongating ribosomes. Analyses of canonical Ribo-seq reads (ribosome footprints) highlighted two obstructive characteristics to host gene expression: ribosome stalling on codons within transmembrane domain-coding regions and compromised translation of immunity- and metabolism-related genes with upregulated transcription. Our findings collectively demonstrate that the abrogation of translation integrity may be one of the most critical factors contributing to pathogenesis after SARS-CoV-2 infection of tissues.

A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X

The road from transcription to protein synthesis is paved with many obstacles, allowing for several modes of post-transcriptional regulation of gene expression. A fundamental player in mRNA biology is DDX3X, an RNA binding protein that canonically regulates mRNA translation. By monitoring dynamics of mRNA abundance and translation following DDX3X depletion, we observe stabilization of translationally suppressed mRNAs. We use interpretable statistical learning models to uncover GC content in the coding sequence as the major feature underlying RNA stabilization. This result corroborates GC content-related mRNA regulation detectable in other studies, including hundreds of ENCODE datasets and recent work focusing on mRNA dynamics in the cell cycle. We provide further evidence for mRNA stabilization by detailed analysis of RNA-seq profiles in hundreds of samples, including a Ddx3x conditional knockout mouse model exhibiting cell cycle and neurogenesis defects. Our study identifies a ubiquitous feature underlying mRNA regulation and highlights the importance of quantifying multiple steps of the gene expression cascade, where RNA abundance and protein production are often uncoupled.

Transcriptome-wide profiling of acute stress induced changes in ribosome occupancy level using external standards

Acute cellular stress is known to induce a global reduction in mRNA translation through suppression of cap dependent translation. Selective translation in response to acute stress has been shown to play important roles in regulating the stress response. However, accurately profiling translational changes transcriptome-wide in response to acute cellular stress has been challenging. Commonly used data normalization methods operate on the assumption that any systematic shifts are experimental artifacts. Consequently, if applied to profiling acute cellular stress-induced mRNA translation changes, these methods are expected to produce biased estimates. To address this issue, we designed, produced, and evaluated a panel of 16 oligomers to serve as external standards for ribosome profiling studies. Using Sodium Arsenite treatment-induced oxidative stress in lymphoblastoid cell lines as a model system, we applied spike-in oligomers as external standards. We found our spike-in oligomers to display a strong linear correlation between the observed and the expected quantification, with small ratio compression at the lower concentration range. Using the expected fold changes constructed from spike-in controls, we found in our dataset that TMM normalization, a popular global scaling normalization approach, produced 87.5% false positives at a significant cutoff that is expected to produce only 10% false positive discoveries. In addition, TMM normalization produced a systematic shift of fold change by 3.25 fold. These results highlight the consequences of applying global scaling approaches to conditions that clearly violate their key assumptions. In contrast, we found RUVg normalization using spike-in oligomers as control genes recapitulated the expected stress induced global reduction of translation and resulted in little, if any, systematic shifts in the expected fold change. Our results clearly demonstrated the utility of our spike-in oligomers, both for constructing expected results as controls and for data normalization.

Workability of mRNA Sequencing for Predicting Protein Abundance

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

VeloPro: A pipeline integrating Ribo-seq and AlphaFold deciphers association patterns between translation velocity and protein structure features

VeloPro integrates Ribo-seq data and AlphaFold2-predicted 3D protein structure information for characterization of the association patterns between translation velocity and many protein structure features in prokaryotic and eukaryotic organisms across different taxonomical clades such as bacteria, fungi, protozoa, nematode, plants, insect, and mammals. We illustrated that association patterns between translation velocity and protein structure features differ across organisms, partially reflecting their taxonomical relationship.

mRNA vaccine quality analysis using RNA sequencing

The success of mRNA vaccines has been realised, in part, by advances in manufacturing that enabled billions of doses to be produced at sufficient quality and safety. However, mRNA vaccines must be rigorously analysed to measure their integrity and detect contaminants that reduce their effectiveness and induce side-effects. Currently, mRNA vaccines and therapies are analysed using a range of time-consuming and costly methods. Here we describe a streamlined method to analyse mRNA vaccines and therapies using long-read nanopore sequencing. Compared to other industry-standard techniques, VAX-seq can comprehensively measure key mRNA vaccine quality attributes, including sequence, length, integrity, and purity. We also show how direct RNA sequencing can analyse mRNA chemistry, including the detection of nucleoside modifications. To support this approach, we provide supporting software to automatically report on mRNA and plasmid template quality and integrity. Given these advantages, we anticipate that RNA sequencing methods, such as VAX-seq, will become central to the development and manufacture of mRNA drugs.

Ribosome profiling in the Symbiodiniacean dinoflagellate Fugacium kawagutii shows coordinated protein synthesis of enzymes in different pathways at different times of day

Dinoflagellates respond to daily changes in light and dark by changes in cellular metabolism, yet the mechanisms used are still unclear. For example, Fugacium (previously Symbiodinium) kawagutii shows little difference in the transcriptome between day and night suggesting little transcriptional control over gene expression. Here, we have performed ribosome profiling at 2 h intervals over a daily light-dark cycle to assess the degree to which protein synthesis rates might change over the daily cycle. The number of F. kawagutii coding sequences with significant differences in the number of ribosome-protected fragments (RPF) over the 24-h cycle was 2923 using JTK_Cycle and 3655 using ECHO. The majority of the regulated transcripts showed peak translation at the onset of the dark period. The regulated sequences were assigned to different KEGG pathways and transcripts that were translated at roughly the same time were termed concurrently regulated. Both analyses revealed concurrent regulation of many transcripts whose gene products were involved in spliceosome or lysosome biogenesis with peak translation rates around the onset of the dark period, while others, involved in nitrate metabolism and ribosomal proteins, were preferentially translated around the onset of the day phase or the end of the night phase, respectively. In addition, some sequences involved in DNA synthesis were preferentially translated at the end of the day. We conclude that light-dark cycles seem able to synchronize translation of some transcripts encoding proteins involved in a range of different cellular processes, and propose that these changes may help the cells adapt and alter their metabolism as a function of the time of day.

Detection of Known and Novel Small Proteins in Pseudomonas stutzeri Using a Combination of Bottom-Up and Digest-Free Proteomics and Proteogenomics

Small proteins of around 50 aa in length have been largely overlooked in genetic and biochemical assays due to the inherent challenges with detecting and characterizing them. Recent discoveries of their critical roles in many biological processes have led to an increased recognition of the importance of small proteins for basic research and as potential new drug targets. One example is CcoM, a 36 aa subunit of the cbb3-type oxidase that plays an essential role in adaptation to oxygen-limited conditions in Pseudomonas stutzeri (P. stutzeri), a model for the clinically relevant, opportunistic pathogen Pseudomonas aeruginosa. However, as no comprehensive data were available in P. stutzeri, we devised an integrated, generic approach to study small proteins more systematically. Using the first complete genome as basis, we conducted bottom-up proteomics analyses and established a digest-free, direct-sequencing proteomics approach to study cells grown under aerobic and oxygen-limiting conditions. Finally, we also applied a proteogenomics pipeline to identify missed protein-coding genes. Overall, we identified 2921 known and 29 novel proteins, many of which were differentially regulated. Among 176 small proteins 16 were novel. Direct sequencing, featuring a specialized precursor acquisition scheme, exhibited advantages in the detection of small proteins with higher (up to 100%) sequence coverage and more spectral counts, including sequences with high proline content. Three novel small proteins, uniquely identified by direct sequencing and not conserved beyond P. stutzeri, were predicted to form an operon with a conserved protein and may represent de novo genes. These data demonstrate the power of this combined approach to study small proteins in P. stutzeri and show its potential for other prokaryotes.

Simultaneous measurement of nascent transcriptome and translatome using 4-thiouridine metabolic RNA labeling and translating ribosome affinity purification

Regulation of gene expression in response to various biological processes, including extracellular stimulation and environmental adaptation requires nascent RNA synthesis and translation. Analysis of the coordinated regulation of dynamic RNA synthesis and translation is required to determine functional protein production. However, reliable methods for the simultaneous measurement of nascent RNA synthesis and translation at the gene level are limited. Here, we developed a novel method for the simultaneous assessment of nascent RNA synthesis and translation by combining 4-thiouridine (4sU) metabolic RNA labeling and translating ribosome affinity purification (TRAP) using a monoclonal antibody against evolutionarily conserved ribosomal P-stalk proteins. The P-stalk-mediated TRAP (P-TRAP) technique recovered endogenous translating ribosomes, allowing easy translatome analysis of various eukaryotes. We validated this method in mammalian cells by demonstrating that acute unfolded protein response (UPR) in the endoplasmic reticulum (ER) induces dynamic reprogramming of nascent RNA synthesis and translation. Our nascent P-TRAP (nP-TRAP) method may serve as a simple and powerful tool for analyzing the coordinated regulation of transcription and translation of individual genes in various eukaryotes.

Unlocking the potential of non-coding RNAs in cancer research and therapy

Non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression, with growing evidence implicating their involvement in cancer development and progression. The potential of ncRNAs as diagnostic and prognostic biomarkers for cancer is promising, with emphasis on their use in liquid biopsy and tissue-based diagnostics. In a nutshell, the review comprehensively summarizes the diverse classes of ncRNAs implicated in cancer, including microRNAs, long non-coding RNAs, and circular RNAs, and their functions and mechanisms of action. Furthermore, we describe the potential therapeutic applications of ncRNAs, including anti-miRNA oligonucleotides, siRNAs, and other RNA-based therapeutics in cancer treatment. However, significant challenges remain in developing effective ncRNA-based diagnostics and therapeutics, including the lack of specificity, limited understanding of mechanisms, and delivery challenges. This review also covers the current state-of-the-art non-coding RNA research technologies and bioinformatic analysis tools. Lastly, we outline future research directions in non-coding RNA research in cancer, including developing novel biomarkers, therapeutic targets, and modalities. In summary, this review provides a comprehensive understanding of non-coding RNAs in cancer and their potential clinical applications, highlighting both the opportunities and challenges in this rapidly evolving field.

Spatially resolved single-cell translatomics at molecular resolution

The precise control of messenger RNA (mRNA) translation is a crucial step in posttranscriptional gene regulation of cellular physiology. However, it remains a challenge to systematically study mRNA translation at the transcriptomic scale with spatial and single-cell resolution. Here, we report the development of ribosome-bound mRNA mapping (RIBOmap), a highly multiplexed three-dimensional in situ profiling method to detect cellular translatome. RIBOmap profiling of 981 genes in HeLa cells revealed cell cycle-dependent translational control and colocalized translation of functional gene modules. We mapped 5413 genes in mouse brain tissues, yielding spatially resolved single-cell translatomic profiles for 119,173 cells and revealing cell type-specific and brain region-specific translational regulation, including translation remodeling during oligodendrocyte maturation. Our method detected widespread patterns of localized translation in neuronal and glial cells in intact brain tissue networks.

Extracellular Vesicle MicroRNA in the Kidney

Most cells in our body release membrane-bound, nano-sized particles into the extracellular milieu through cellular metabolic processes. Various types of macromolecules, reflecting the physiological and pathological status of the producing cells, are packaged into such so-called extracellular vesicles (EVs), which can travel over a distance to target cells, thereby transmitting donor cell information. The short, noncoding ribonucleic acid (RNA) called microRNA (miRNA) takes a crucial part in EV-resident macromolecules. Notably, EVs transferring miRNAs can induce alterations in the gene expression profiles of the recipient cells, through genetically instructed, base-pairing interaction between the miRNAs and their target cell messenger RNAs (mRNAs), resulting in either nucleolytic decay or translational halt of the engaged mRNAs. As in other body fluids, EVs released in urine, termed urinary EVs (uEVs), carry specific sets of miRNA molecules, which indicate either normal or diseased states of the kidney, the principal source of uEVs. Studies have therefore been directed to elucidate the contents and biological roles of miRNAs in uEVs and moreover to utilize the gene regulatory properties of miRNA cargos in ameliorating kidney diseases through their delivery via engineered EVs. We here review the fundamental principles of the biology of EVs and miRNA as well as our current understanding of the biological roles and applications of EV-loaded miRNAs in the kidney. We further discuss the limitations of contemporary research approaches, suggesting future directions to overcome the difficulties to advance both the basic biological understanding of miRNAs in EVs and their clinical applications in treating kidney diseases. © 2023 American Physiological Society. Compr Physiol 13:4833-4850, 2023.

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

The translational landscape of bread wheat during grain development

The dynamics of gene expression in crop grains has typically been investigated at the transcriptional level. However, this approach neglects translational regulation, a widespread mechanism that rapidly modulates gene expression to increase the plasticity of organisms. Here, we performed ribosome profiling and polysome profiling to obtain a comprehensive translatome data set of developing bread wheat (Triticum aestivum) grains. We further investigated the genome-wide translational dynamics during grain development, revealing that the translation of many functional genes is modulated in a stage-specific manner. The unbalanced translation between subgenomes is pervasive, which increases the expression flexibility of allohexaploid wheat. In addition, we uncovered widespread previously unannotated translation events, including upstream open reading frames (uORFs), downstream open reading frames (dORFs), and open reading frames (ORFs) in long noncoding RNAs, and characterized the temporal expression dynamics of small ORFs. We demonstrated that uORFs act as cis-regulatory elements that can repress or even enhance the translation of mRNAs. Gene translation may be combinatorially modulated by uORFs, dORFs, and microRNAs. In summary, our study presents a translatomic resource that provides a comprehensive and detailed overview of the translational regulation in developing bread wheat grains. This resource will facilitate future crop improvements for optimal yield and quality.

TP53BP1, a dual-coding gene, uses promoter switching and translational reinitiation to express a smORF protein

The complexity of the metazoan proteome is significantly increased by the expression of small proteins (<100 aa) derived from smORFs within lncRNAs, uORFs, 3' UTRs and, reading frames overlapping the CDS. These smORF encoded proteins (SEPs) have diverse roles, ranging from the regulation of cellular physiological to essential developmental functions. We report the characterization of a new member of this protein family, SEP53BP1, derived from a small internal ORF that overlaps the CDS encoding 53BP1. Its expression is coupled to the utilization of an alternative, cell-type specific promoter coupled to translational reinitiation events mediated by a uORF in the alternative 5' TL of the mRNA. This uORF-mediated reinitiation at an internal ORF is also observed in zebrafish. Interactome studies indicate that the human SEP53BP1 associates with components of the protein turnover pathway including the proteasome, and the TRiC/CCT chaperonin complex, suggesting that it may play a role in cellular proteostasis.

Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurement of translation at genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts and identify sequence determinant of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. It corrects experimental artifacts in previously unseen datasets, reveals subtle differences in synonymous codon translation and uncovers a bottleneck in protein synthesis. Further, we show that Riboformer can be combined with in silico mutagenesis analysis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

Modeling neurodevelopmental disorder-associated hAGO1 mutations in C. elegans Argonaute ALG-1

MicroRNAs (miRNA) are endogenous non-coding RNAs important for post-transcriptional regulation of gene expression. miRNAs associate with Argonaute proteins to bind to the 3' UTR of target genes and confer target repression. Recently, multiple de novo coding variants in the human Argonaute gene AGO1 ( hAGO1 ) have been reported to cause a neurodevelopmental disorder (NDD) with intellectual disability (ID). Most of the altered amino acids are conserved between the miRNA-associated Argonautes in H. sapiens and C. elegans , suggesting the hAGO1 mutations could disrupt evolutionarily conserved functions in the miRNA pathway. To investigate how the hAGO1 mutations may affect miRNA biogenesis and/or functions, we genetically modeled four of the hAGO1 de novo variants (referred to as NDD mutations) by introducing the identical mutations to the C. elegans hAGO1 homolog, alg-1 . This array of mutations caused distinct effects on C. elegans miRNA functions, miRNA populations, and downstream gene expression, indicative of profound alterations in aspects of miRNA processing and miRISC formation and/or activity. Specifically, we found that the alg-1 NDD mutations cause allele-specific disruptions in mature miRNA profiles both in terms of overall abundances and association with mutant ALG-1. We also observed allele-specific profiles of gene expression with altered translational efficiency and/or mRNA abundance. The sets of perturbed genes include human homologs whose dysfunction is known to cause NDD. We anticipate that these cross-clade genetic studies may advance the understanding of fundamental Argonaute functions and provide insights into the conservation of miRNA-mediated post-transcriptional regulatory mechanisms.

The physiology of alternative splicing

Alternative splicing is a substantial contributor to the high complexity of transcriptomes of multicellular eukaryotes. In this Review, we discuss the accumulated evidence that most of this complexity is reflected at the protein level and fundamentally shapes the physiology and pathology of organisms. This notion is supported not only by genome-wide analyses but, mainly, by detailed studies showing that global and gene-specific modulations of alternative splicing regulate highly diverse processes such as tissue-specific and species-specific cell differentiation, thermal regulation, neuron self-avoidance, infrared sensing, the Warburg effect, maintenance of telomere length, cancer and autism spectrum disorders (ASD). We also discuss how mastering the control of alternative splicing paved the way to clinically approved therapies for hereditary diseases.

Deep genomic characterization highlights complexities and prognostic markers of pediatric acute myeloid leukemia

Pediatric acute myeloid leukemia (AML) is an uncommon but aggressive hematological malignancy. The poor outcome is attributed to inadequate prognostic classification and limited treatment options. A thorough understanding on the genetic basis of pediatric AML is important for the development of effective approaches to improve outcomes. Here, by comprehensively profiling fusion genes as well as mutations and copy number changes of 141 myeloid-related genes in 147 pediatric AML patients with subsequent variant functional characterization, we unveil complex mutational patterns of biological relevance and disease mechanisms including MYC deregulation. Also, our findings highlight TP53 alterations as strong adverse prognostic markers in pediatric AML and suggest the core spindle checkpoint kinase BUB1B as a selective dependency in this aggressive subgroup. Collectively, our present study provides detailed genomic characterization revealing not only complexities and mechanistic insights into pediatric AML but also significant risk stratification and therapeutic strategies to tackle the disease.

A single-copy knockin translating ribosome immunoprecipitation toolkit for tissue-specific profiling of actively translated mRNAs in C. elegans

Here, we introduce a single-copy knockin translating ribosome immunoprecipitation (SKI TRIP) toolkit, a collection of Caenorhabditis elegans strains engineered by CRISPR in which tissue-specific expression of FLAG-tagged ribosomal subunit protein RPL-22 is driven by cassettes present in single copy from defined sites in the genome. Through in-depth characterization of the effects of the FLAG tag in animals in which endogenous RPL-22 has been tagged, we show that it incorporates into actively translating ribosomes and efficiently and cleanly pulls down cell-type-specific transcripts. Importantly, the presence of the tag does not impact overall mRNA translation, create bias in transcript use, or cause changes to fitness of the animal. We propose SKI TRIP use for the study of tissue-specific differences in translation and for investigating processes that are acutely sensitive to changes in translation like development or aging.

Unraveling the small proteome of the plant symbiont Sinorhizobium meliloti by ribosome profiling and proteogenomics

The soil-dwelling plant symbiont Sinorhizobium meliloti is a major model organism of Alphaproteobacteria. Despite numerous detailed OMICS studies, information about small open reading frame (sORF)-encoded proteins (SEPs) is largely missing, because sORFs are poorly annotated and SEPs are hard to detect experimentally. However, given that SEPs can fulfill important functions, identification of translated sORFs is critical for analyzing their roles in bacterial physiology. Ribosome profiling (Ribo-seq) can detect translated sORFs with high sensitivity, but is not yet routinely applied to bacteria because it must be adapted for each species. Here, we established a Ribo-seq procedure for S. meliloti 2011 based on RNase I digestion and detected translation for 60% of the annotated coding sequences during growth in minimal medium. Using ORF prediction tools based on Ribo-seq data, subsequent filtering, and manual curation, the translation of 37 non-annotated sORFs with ≤ 70 amino acids was predicted with confidence. The Ribo-seq data were supplemented by mass spectrometry (MS) analyses from three sample preparation approaches and two integrated proteogenomic search database (iPtgxDB) types. Searches against standard and 20-fold smaller Ribo-seq data-informed custom iPtgxDBs confirmed 47 annotated SEPs and identified 11 additional novel SEPs. Epitope tagging and Western blot analysis confirmed the translation of 15 out of 20 SEPs selected from the translatome map. Overall, by combining MS and Ribo-seq approaches, the small proteome of S. meliloti was substantially expanded by 48 novel SEPs. Several of them are part of predicted operons and/or are conserved from Rhizobiaceae to Bacteria, suggesting important physiological functions.

Translational Control of Metabolism and Cell Cycle Progression in Hepatocellular Carcinoma

The liver is a metabolic hub characterized by high levels of protein synthesis. Eukaryotic initiation factors, eIFs, control the first phase of translation, initiation. Initiation factors are essential for tumor progression and, since they regulate the translation of specific mRNAs downstream of oncogenic signaling cascades, may be druggable. In this review, we address the issue of whether the massive translational machinery of liver cells contributes to liver pathology and to the progression of hepatocellular carcinoma (HCC); it represents a valuable biomarker and druggable target. First, we observe that the common markers of HCC cells, such as phosphorylated ribosomal protein S6, belong to the ribosomal and translational apparatus. This fact is in agreement with observations that demonstrate a huge amplification of the ribosomal machinery during the progression to HCC. Some translation factors, such as eIF4E and eIF6, are then harnessed by oncogenic signaling. In particular, the action of eIF4E and eIF6 is particularly important in HCC when driven by fatty liver pathologies. Indeed, both eIF4E and eIF6 amplify at the translational level the production and accumulation of fatty acids. As it is evident that abnormal levels of these factors drive cancer, we discuss their therapeutic value.

De-centralizing the Central Dogma: mRNA translation in space and time

As our understanding of the cell interior has grown, we have come to appreciate that most cellular operations are localized, that is, they occur at discrete and identifiable locations or domains. These cellular domains contain enzymes, machines, and other components necessary to carry out and regulate these localized operations. Here, we review these features of one such operation: the localization and translation of mRNAs within subcellular compartments observed across cell types and organisms. We describe the conceptual advantages and the "ingredients" and mechanisms of local translation. We focus on the nature and features of localized mRNAs, how they travel and get localized, and how this process is regulated. We also evaluate our current understanding of protein synthesis machines (ribosomes) and their cadre of regulatory elements, that is, the translation factors.

Cytosolic and mitochondrial ribosomal proteins mediate the locust phase transition via divergence of translational profiles

The phase transition from solitary to gregarious locusts is crucial in outbreaks of locust plague, which threaten agricultural yield and food security. Research on the regulatory mechanisms of phase transition in locusts has focused primarily on the transcriptional or posttranslational level. However, the translational regulation of phase transition is unexplored. Here, we show a phase-dependent pattern at the translation level, which exhibits different polysome profiles between gregarious and solitary locusts. The gregarious locusts exhibit significant increases in 60S and polyribosomes, while solitary locusts possess higher peaks of the monoribosome and a specific "halfmer." The polysome profiles, a molecular phenotype, respond to changes in population density. In gregarious locusts, ten genes involved in the cytosolic ribosome pathway exhibited increased translational efficiency (TE). In solitary locusts, five genes from the mitochondrial ribosome pathway displayed increased TE. The high expression of large ribosomal protein 7 at the translational level promotes accumulation of the free 60S ribosomal subunit in gregarious locusts, while solitary locusts employ mitochondrial small ribosomal protein 18c to induce the assembly of mitochondrial ribosomes, causing divergence of the translational profiles and behavioral transition. This study reveals the translational regulatory mechanism of locust phase transition, in which the locusts employ divergent ribosome pathways to cope with changes in population density.

Using Mechanistic Models and Machine Learning to Design Single-Color Multiplexed Nascent Chain Tracking Experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Through simulation, we show that with careful application, this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. The proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell signalling applications requiring simultaneous study of multiple mRNAs.