Ribonuclease selection for ribosome profiling

RiboGraph: an interactive visualization system for ribosome profiling data at read length resolution

MOTIVATION

Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses.

RESULTS

In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.

AVAILABILITY AND IMPLEMENTATION

Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.

Translation machinery: the basis of translational control

Messenger RNA (mRNA) translation consists of initiation, elongation, termination, and ribosome recycling, carried out by the translation machinery, primarily including tRNAs, ribosomes, and translation factors (TrFs). Translational regulators transduce signals of growth and development, as well as biotic and abiotic stresses, to the translation machinery, where global or selective translational control occurs to modulate mRNA translation efficiency (TrE). As the basis of translational control, the translation machinery directly determines the quality and quantity of newly synthesized peptides and, ultimately, the cellular adaption. Thus, regulating the availability of diverse machinery components is reviewed as the central strategy of translational control. We provide classical signaling pathways (e.g., integrated stress responses) and cellular behaviors (e.g., liquid-liquid phase separation) to exemplify this strategy within different physiological contexts, particularly during host-microbe interactions. With new technologies developed, further understanding this strategy will speed up translational medicine and translational agriculture.

Impact of eIF2α phosphorylation on the translational landscape of mouse embryonic stem cells

The integrated stress response (ISR) is critical for cell survival under stress. In response to diverse environmental cues, eIF2α becomes phosphorylated, engendering a dramatic change in mRNA translation. The activation of ISR plays a pivotal role in the early embryogenesis, but the eIF2-dependent translational landscape in pluripotent embryonic stem cells (ESCs) is largely unexplored. We employ a multi-omics approach consisting of ribosome profiling, proteomics, and metabolomics in wild-type (eIF2α+/+) and phosphorylation-deficient mutant eIF2α (eIF2αA/A) mouse ESCs (mESCs) to investigate phosphorylated (p)-eIF2α-dependent translational control of naive pluripotency. We show a transient increase in p-eIF2α in the naive epiblast layer of E4.5 embryos. Absence of eIF2α phosphorylation engenders an exit from naive pluripotency following 2i (two chemical inhibitors of MEK1/2 and GSK3α/β) withdrawal. p-eIF2α controls translation of mRNAs encoding proteins that govern pluripotency, chromatin organization, and glutathione synthesis. Thus, p-eIF2α acts as a key regulator of the naive pluripotency gene regulatory network.

RiboGraph: An interactive visualization system for ribosome profiling data at read length resolution

Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses. In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type and eliminates the need for data preprocessing. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.

Availability and Implementation

Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.

Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells

Ribosome profiling has unveiled diverse regulation and perturbations of translation through a transcriptome-wide survey of ribosome occupancy, read out by sequencing of ribosome-protected messenger RNA fragments. Generation of ribosome footprints and their conversion into sequencing libraries is technically demanding and sensitive to biases that distort the representation of physiological ribosome occupancy. We address these challenges by producing ribosome footprints with P1 nuclease rather than RNase I and replacing RNA ligation with ordered two-template relay, a single-tube protocol for sequencing library preparation that incorporates adaptors by reverse transcription. Our streamlined approach reduced sequence bias and enhanced enrichment of ribosome footprints relative to ribosomal RNA. Furthermore, P1 nuclease preserved distinct juxtaposed ribosome complexes informative about yeast and human ribosome fates during translation initiation, stalling and termination. Our optimized methods for mRNA footprint generation and capture provide a richer translatome profile with low input and fewer technical challenges.

Optimized infrared photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (IR-PAR-CLIP) protocol identifies novel IGF2BP3-interacting RNAs in colon cancer cells

The conserved family of RNA-binding proteins (RBPs), IGF2BPs, plays an essential role in posttranscriptional regulation controlling mRNA stability, localization, and translation. Mammalian cells express three isoforms of IGF2BPs: IGF2BP1-3. IGF2BP3 is highly overexpressed in cancer cells, and its expression correlates with a poor prognosis in various tumors. Therefore, revealing its target RNAs with high specificity in healthy tissues and in cancer cells is of crucial importance. Photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) identifies the binding sites of RBPs on their target RNAs at nucleotide resolution in a transcriptome-wide manner. Here, we optimized the PAR-CLIP protocol to study RNA targets of endogenous IGF2BP3 in a human colorectal carcinoma cell line. To this end, we first established an immunoprecipitation protocol to obtain highly pure endogenous IGF2BP3-RNA complexes. Second, we modified the protocol to use highly sensitive infrared (IR) fluorescent dyes instead of radioactive probes to visualize IGF2BP3-crosslinked RNAs. We named the modified method "IR-PAR-CLIP." Third, we compared RNase cleavage conditions and found that sequence preferences of the RNases impact the number of the identified IGF2BP3 targets and introduce a systematic bias in the identified RNA motifs. Fourth, we adapted the single adapter circular ligation approach to increase the efficiency in library preparation. The optimized IR-PAR-CLIP protocol revealed novel RNA targets of IGF2BP3 in a human colorectal carcinoma cell line. We anticipate that our IR-PAR-CLIP approach provides a framework for studies of other RBPs.

18S rRNA methyltransferases DIMT1 and BUD23 drive intergenerational hormesis

Heritable non-genetic information can regulate a variety of complex phenotypes. However, what specific non-genetic cues are transmitted from parents to their descendants are poorly understood. Here, we perform metabolic methyl-labeling experiments to track the heritable transmission of methylation from ancestors to their descendants in the nematode Caenorhabditis elegans (C. elegans). We find heritable methylation in DNA, RNA, proteins, and lipids. We find that parental starvation elicits reduced fertility, increased heat stress resistance, and extended longevity in fed, naïve progeny. This intergenerational hormesis is accompanied by a heritable increase in N6'-dimethyl adenosine (m6,2A) on the 18S ribosomal RNA at adenosines 1735 and 1736. We identified DIMT-1/DIMT1 as the m6,2A and BUD-23/BUD23 as the m7G methyltransferases in C. elegans that are both required for intergenerational hormesis, while other rRNA methyltransferases are dispensable. This study labels and tracks heritable non-genetic material across generations and demonstrates the importance of rRNA methylation for regulating epigenetic inheritance.

Customization of the translational complex regulates mRNA-specific translation to control CNS regeneration

In the adult mammalian central nervous system (CNS), axons fail to regenerate spontaneously after injury because of a combination of extrinsic and intrinsic factors. Despite recent advances targeting the intrinsic regenerative properties of adult neurons, the molecular mechanisms underlying axon regeneration are not fully understood. Here, we uncover a regulatory mechanism that controls the expression of key proteins involved in regeneration at the translational level. Our results show that mRNA-specific translation is critical for promoting axon regeneration. Indeed, we demonstrate that specific ribosome-interacting proteins, such as the protein Huntingtin (HTT), selectively control the translation of a specific subset of mRNAs. Moreover, modulating the expression of these translationally regulated mRNAs is crucial for promoting axon regeneration. Altogether, our findings highlight that selective translation through the customization of the translational complex is a key mechanism of axon regeneration with major implications in the development of therapeutic strategies for CNS repair.

Optimisation of Sample Preparation from Primary Mouse Tissue to Maintain RNA Integrity for Methods Examining Translational Control

The protein output of different mRNAs can vary by two orders of magnitude; therefore, it is critical to understand the processes that control gene expression operating at the level of translation. Translatome-wide techniques, such as polysome profiling and ribosome profiling, are key methods for determining the translation rates occurring on specific mRNAs. These techniques are now widely used in cell lines; however, they are underutilised in tissues and cancer models. Ribonuclease (RNase) expression is often found to be higher in complex primary tissues in comparison to cell lines. Methods used to preserve RNA during lysis often use denaturing conditions, which need to be avoided when maintaining the interaction and position of the ribosome with the mRNA is required. Here, we detail the cell lysis conditions that produce high-quality RNA from several different tissues covering a range of endogenous RNase expression levels. We highlight the importance of RNA integrity for accurate determination of the global translation status of the cell as determined by polysome gradients and discuss key aspects to optimise for accurate assessment of the translatome from primary mouse tissue.

A rapid protocol for ribosome profiling of low input samples

Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments that are protected by ribosomes from nucleolytic digestion. While the overall principle is simple, the workflow of ribosome profiling experiments is complex and challenging, and typically requires large amounts of sample, limiting its broad applicability. Here, we present a new protocol for ultra-rapid ribosome profiling from low-input samples. It features a robust strategy for sequencing library preparation within one day that employs solid phase purification of reaction intermediates, allowing to reduce the input to as little as 0.1 pmol of ∼30 nt RNA fragments. Hence, it is particularly suited for the analyses of small samples or targeted ribosome profiling. Its high sensitivity and its ease of implementation will foster the generation of higher quality data from small samples, which opens new opportunities in applying ribosome profiling.

Rfoot-seq: Transcriptomic RNase Footprinting for Mapping Stable RNA-Protein Complexes and Rapid Ribosome Profiling

Ribosome profiling isolates ribosome-protected fragments for sequencing and is a valuable method for studying different aspects of RNA translation. However, conventional protocols require millions of input cells and time-consuming steps to isolate translating ribosome complexes using ultracentrifugation or immunoprecipitation. These limitations have prevented their application to rare physiological samples. To address these technical barriers, we developed an RNase footprinting approach named Rfoot-seq to map stable transcriptomic RNA-protein complexes that allows rapid ribosome profiling using low-input samples (Li, Yang, Stroup, Wang, & Ji, 2022). In this assay, we treat a cell lysate with concentrated RNase without complex crosslinking and retained only RNA footprints associated with stable complexes for sequencing. The footprints in coding regions represent ribosome-protected fragments and can be used to study cytosolic and mitochondrial translation simultaneously. Rfoot-seq achieves comparable results to conventional ribosome profiling to quantify ribosome occupancy and works robustly for various cultured cells and primary tissue samples. Moreover, Rfoot-seq maps RNA fragments associated with stable non-ribosomal RNA-protein complexes in noncoding domains of small noncoding RNAs and some long noncoding RNAs. Taken together, Rfoot-seq opens an avenue to quantify transcriptomic translation and characterize functional noncoding RNA domains using low-input samples. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Harvesting and lysing adherent cells Alternate Protocol 1: Harvesting and lysing suspension cells Alternate Protocol 2: Harvesting and lysing primary tissue samples Basic Protocol 2: RNase treatment and footprint purification for low-input samples Alternate Protocol 3: RNase treatment and footprint purification for ultra-low-input samples Basic Protocol 3: Library preparation for high-throughput sequencing Support Protocol: Preparation of dsDNA markers for library size selection Basic Protocol 4: Data analysis and quality control after sequencing.

Selective ribosome profiling as a tool to study interactions of translating ribosomes in mammalian cells

The processing, membrane targeting and folding of newly synthesized polypeptides is closely linked to their synthesis at the ribosome. A network of enzymes, chaperones and targeting factors engages ribosome-nascent chain complexes (RNCs) to support these maturation processes. Exploring the modes of action of this machinery is critical for our understanding of functional protein biogenesis. Selective ribosome profiling (SeRP) is a powerful method for interrogating co-translational interactions of maturation factors with RNCs. It provides proteome-wide information on the factor's nascent chain interactome, the timing of factor binding and release during the progress of translation of individual nascent chain species, and the mechanisms and features controlling factor engagement. SeRP is based on the combination of two ribosome profiling (RP) experiments performed on the same cell population. In one experiment the ribosome-protected mRNA footprints of all translating ribosomes of the cell are sequenced (total translatome), while the other experiment detects only the ribosome footprints of the subpopulation of ribosomes engaged by the factor of interest (selected translatome). The codon-specific ratio of ribosome footprint densities from selected over total translatome reports on the factor enrichment at specific nascent chains. In this chapter, we provide a detailed SeRP protocol for mammalian cells. The protocol includes instructions on cell growth and cell harvest, stabilization of factor-RNC interactions, nuclease digest and purification of (factor-engaged) monosomes, as well as preparation of cDNA libraries from ribosome footprint fragments and deep sequencing data analysis. Purification protocols of factor-engaged monosomes and experimental results are exemplified for the human ribosomal tunnel exit-binding factor Ebp1 and chaperone Hsp90, but the protocols are readily adaptable to other co-translationally acting mammalian factors.

Plant HEM1 specifies a condensation domain to control immune gene translation

Translational reprogramming is a fundamental layer of immune regulation, but how such a global regulatory mechanism operates remains largely unknown. Here we perform a genetic screen and identify Arabidopsis HEM1 as a global translational regulator of plant immunity. The loss of HEM1 causes exaggerated cell death to restrict bacterial growth during effector-triggered immunity (ETI). By improving ribosome footprinting, we reveal that the hem1 mutant increases the translation efficiency of pro-death immune genes. We show that HEM1 contains a plant-specific low-complexity domain (LCD) absent from animal homologues. This LCD endows HEM1 with the capability of phase separation in vitro and in vivo. During ETI, HEM1 interacts and condensates with the translation machinery; this activity is promoted by the LCD. CRISPR removal of this LCD causes more ETI cell death. Our results suggest that HEM1 condensation constitutes a brake mechanism of immune activation by controlling the tissue health and disease resistance trade-off during ETI.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

Evaluating data integrity in ribosome footprinting datasets through modelled polysome profiles

The assessment of transcriptome-wide ribosome binding to mRNAs is useful for studying the dynamic regulation of protein synthesis. Two methods frequently applied in eukaryotic cells that operate at different levels of resolution are polysome profiling, which reveals the distribution of ribosome loads across the transcriptome, and ribosome footprinting (also termed ribosome profiling or Ribo-Seq), which when combined with appropriate data on mRNA expression can reveal ribosome densities on individual transcripts. In this study we develop methods for relating the information content of these two methods to one another, by reconstructing theoretical polysome profiles from ribosome footprinting data. Our results validate both approaches as experimental tools. Although we show that both methods can yield highly consistent data, some published ribosome footprinting datasets give rise to reconstructed polysome profiles with non-physiological features. We trace these aberrant features to inconsistencies in RNA and Ribo-Seq data when compared to datasets yielding physiological polysome profiles, thereby demonstrating that modelled polysomes are useful for assessing global dataset properties such as its quality in a simple, visual approach. Aside from using polysome profile reconstructions on published datasets, we propose that this also provides a useful tool for validating new ribosome footprinting datasets in early stages of analyses.

Flow-Seq Method: Features and Application in Bacterial Translation Studies

The Flow-seq method is based on using reporter construct libraries, where a certain element regulating the gene expression of fluorescent reporter proteins is represented in many thousands of variants. Reporter construct libraries are introduced into cells, sorted according to their fluorescence level, and then subjected to next-generation sequencing. Therefore, it turns out to be possible to identify patterns that determine the expression efficiency, based on tens and hundreds of thousands of reporter constructs in one experiment. This method has become common in evaluating the efficiency of protein synthesis simultaneously by multiple mRNA variants. However, its potential is not confined to this area. In the presented review, a comparative analysis of the Flow-seq method and other alternative approaches used for translation efficiency evaluation of mRNA was carried out; the features of its application and the results obtained by Flow-seq were also considered.

Sequence features around cleavage sites are highly conserved among different species and a critical determinant for RNA cleavage position across eukaryotes

RNA degradation is one of the critical steps for control of gene expression, and endonucleolytic cleavage-dependent RNA degradation is conserved among eukaryotes. Some cleavage sites are secondarily capped in the cytoplasm and identified using the Cap analysis of gene expression (CAGE) method. Although uncapped cleavage sites are widespread in eukaryotes, comparatively little information has been obtained about these sites using CAGE-based degradome analysis. Previously, we developed the truncated RNA-end sequencing (TREseq) method in plant species and used it to acquire comprehensive information about uncapped cleavage sites; we observed G-rich sequences near cleavage sites. However, it remains unclear whether this finding is general to other eukaryotes. In this study, we conducted TREseq analyses in fruit flies (Drosophila melanogaster) and budding yeast (Saccharomyces cerevisiae). The results revealed specific sequence features related to RNA cleavage in D. melanogaster and S. cerevisiae that were similar to sequence patterns in Arabidopsis thaliana. Although previous studies suggest that ribosome movements are important for determining cleavage position, feature selection using a random forest classifier showed that sequences around cleavage sites were major determinant for cleaved or uncleaved sites. Together, our results suggest that sequence features around cleavage sites are critical for determining cleavage position, and that sequence-specific endonucleolytic cleavage-dependent RNA degradation is highly conserved across eukaryotes.

Oligodendrocyte differentiation alters tRNA modifications and codon optimality-mediated mRNA decay

Oligodendrocytes are specialized cells that confer neuronal myelination in the central nervous system. Leukodystrophies associated with oligodendrocyte deficits and hypomyelination are known to result when a number of tRNA metabolism genes are mutated. Thus, for unknown reasons, oligodendrocytes may be hypersensitive to perturbations in tRNA biology. In this study, we survey the tRNA transcriptome in the murine oligodendrocyte cell lineage and find that specific tRNAs are hypomodified in oligodendrocytes within or near the anticodon compared to oligodendrocyte progenitor cells (OPCs). This hypomodified state may be the result of differential expression of key modification enzymes during oligodendrocyte differentiation. Moreover, we observe a concomitant relationship between tRNA hypomodification and tRNA decoding potential; observing oligodendrocyte specific alterations in codon optimality-mediated mRNA decay and ribosome transit. Our results reveal that oligodendrocytes naturally maintain a delicate, hypersensitized tRNA/mRNA axis. We suggest this axis is a potential mediator of pathology in leukodystrophies and white matter disease when further insult to tRNA metabolism is introduced.

Limited evidence for protein products of non-coding transcripts in the HEK293T cellular cytosol

Ribosome profiling has revealed translation outside of canonical coding sequences (CDSs) including translation of short upstream ORFs, long non-coding RNAs, overlapping ORFs, ORFs in UTRs or ORFs in alternative reading frames. Studies combining mass spectrometry, ribosome profiling and CRISPR-based screens showed that hundreds of ORFs derived from non-coding transcripts produce (micro)proteins, while other studies failed to find evidence for such types of non-canonical translation products. Here, we attempted to discover translation products from non-coding regions by strongly reducing the complexity of the sample prior to mass spectrometric analysis. We used an extended database as the search space and applied stringent filtering of the identified peptides to find evidence for novel translation events. We show that, theoretically our strategy facilitates the detection of translation events of transcripts from non-coding regions, but experimentally only find 19 peptides that might originate from such translation events. Finally, Virotrap based interactome analysis of two N-terminal proteoforms originating from non-coding regions finally showed the functional potential of these novel proteins.

A dual-activity topoisomerase complex regulates mRNA translation and turnover

Topoisomerase 3β (TOP3B) and TDRD3 form a dual-activity topoisomerase complex that interacts with FMRP and can change the topology of both DNA and RNA. Here, we investigated the post-transcriptional influence of TOP3B and associated proteins on mRNA translation and turnover. First, we discovered that in human HCT116 colon cancer cells, knock-out (KO) of TOP3B had similar effects on mRNA turnover and translation as did TDRD3-KO, while FMRP-KO resulted in rather distinct effects, indicating that TOP3B had stronger coordination with TDRD3 than FMRP in mRNA regulation. Second, we identified TOP3B-bound mRNAs in HCT116 cells; we found that while TOP3B did not directly influence the stability or translation of most TOP3B target mRNAs, it stabilized a subset of target mRNAs but had a more complex effect on translation-enhancing for some mRNAs whereas reducing for others. Interestingly, a point mutation that specifically disrupted TOP3B catalytic activity only partially recapitulated the effects of TOP3B-KO on mRNA stability and translation, suggesting that the impact of TOP3B on target mRNAs is partly linked to its ability to change topology of mRNAs. Collectively, our data suggest that TOP3B-TDRD3 can regulate mRNA translation and turnover by mechanisms that are dependent and independent of topoisomerase activity.

miR-223 Exerts Translational Control of Proatherogenic Genes in Macrophages

A significant burden of atherosclerotic disease is driven by inflammation. Recently, microRNAs (miRNAs) have emerged as important factors driving and protecting from atherosclerosis. miR-223 regulates cholesterol metabolism and inflammation via targeting both cholesterol biosynthesis pathway and NF_kB signaling pathways; however, its role in atherosclerosis has not been investigated. We hypothesize that miR-223 globally regulates core inflammatory pathways in macrophages in response to inflammatory and atherogenic stimuli thus limiting the progression of atherosclerosis.

SSRTool: a web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability

RNA secondary structures can carry out essential cellular functions alone or interact with one another to form the hierarchical tertiary structures. Experimental structure identification approa ches can show the in vitro structures of RNA molecules. However, they usually have limits in the resolution and are costly. In silico structure prediction tools are thus primarily relied on for pre-experiment analysis. Various structure prediction models have been developed over the decades. Since these tools are usually used before knowing the actual RNA structures, evaluating and ranking the pile of secondary structure predictions of a given sequence is essential in computational analysis. In this research, we implemented a web service called SSRTool (RNA Secondary Structure prediction Ranking Tool) to assist in the ranking and evaluation of the generated predicted structures of a given sequence. Based on the computed species-specific interpretability significance in four common RNA structure–function aspects, SSRTool provides three functions along with visualization interfaces: (1) Rank user-generated predictions. (2) Provide an automated streamline of structure prediction and ranking for a given sequence. (3) Infer the functional aspects of a given structure. We demonstrated the applicability of SSRTool via real case studies and reported the similar trends between computed species-specific rankings and the corresponding prediction F1 values. The SSRTool web service is available online at https://cobisHSS0.im.nuk.edu.tw/SSRTool/, http://cosbi3.ee.ncku.edu.tw/SSRTool/, or the redirecting site https://github.com/cobisLab/SSRTool/.

A Ribo-Seq Method to Study Genome-Wide Translational Regulation in Plants

Protein production from mRNA is one of the fundamental molecular processes in a cell. Accurate genome-wide information on the levels of translation and ribosome distribution on mRNA can be gathered by carrying out ribosome footprinting, aka Ribo-seq. Herein, we present a detailed protocol describing the construction of parallel Ribo-seq and RNA-seq libraries from Arabidopsis seedlings treated with the plant hormone auxin. The improved protocol for ribosome footprint library generation can be easily adapted to analyzing the effects on translation of genetic perturbations and various abiotic and biotic factors to shed the much-needed light on translational regulation in plants.

Comparison of rRNA depletion methods for efficient bacterial mRNA sequencing

Current methods of high-throughput RNA sequencing of prokaryotes, including transcriptome analysis or ribosomal profiling, need deep sequencing to achieve sufficient numbers of effective reads (e.g., mapping to mRNA) in order to also find weakly expressed genetic elements. The fraction of high-quality reads mapping to coding RNAs (i.e., mRNA) is mainly influenced by the large content of rRNA and, to a lesser extent, tRNA in total RNA. Thus, depletion of rRNA increases coverage and thus sequencing costs. RiboZero, a depletion kit based on probe hybridisation and rRNA-removal was found to be most efficient in the past, but it was discontinued in 2018. To facilitate comparability with previous experiments and to help choose adequate replacements, we compare three commercially available rRNA depletion kits also based on hybridization and magnetic beads, i.e., riboPOOLs, RiboMinus and MICROBExpress, with the former RiboZero. Additionally, we constructed biotinylated probes for magnetic bead capture and rRNA depletion in this study. Based on E. coli, we found similar efficiencies in rRNA depletion for riboPOOLs and the self-made depletion method; both comparable to the former RiboZero, followed by RiboMinus, succeeded by MICROBExpress. Further, our in-house protocol allows customized species-specific rRNA or even tRNA depletion or depletion of other RNA targets. Both, the self-made biotinylated probes and riboPOOLs, were most successful in reducing the rRNA content and thereby increasing sequencing depth concerning mRNA reads. Additionally, the number of reads matching to weakly expressed genes are increased. In conclusion, the self-made specific biotinylated probes and riboPOOLs are an adequate replacement for the former RiboZero. Both are very efficient in depleting rRNAs, increasing mRNA reads and thus sequencing efficiency.

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

Micropeptides translated from putative long non-coding RNAs

Long non-coding RNAs (lncRNAs) transcribed in mammals and eukaryotes were thought to have no protein coding capability. However, recent studies have suggested that plenty of lncRNAs are mis-annotated and virtually contain coding sequences which are translated into functional peptides by ribosomal machinery, and these functional peptides are called micropeptides or small peptides. Here we review the rapidly advancing field of micropeptides translated from putative lncRNAs, describe the strategies for their identification, and elucidate their critical roles in many fundamental biological processes. We also discuss the prospects of research in micropeptides and the potential applications of micropeptides.

Optimization of Ribosome Footprinting Conditions for Ribo-Seq in Human and Drosophila melanogaster Tissue Culture Cells

Our understanding of mRNA translation and its regulation has been transformed by the development of ribosome profiling. This approach relies upon RNase footprinting of translating ribosomes in a precise manner to generate an accurate snapshot of ribosome positions with nucleotide resolution. Here we tested a variety of conditions, which contribute to the preciseness of ribosome footprinting and therefore the success of ribosome profiling. We found that NaCl concentration, RNaseI source, RNaseI amount, and temperature of footprinting all contributed to the quality of ribosome footprinting in human neuroblastoma SH-SY5Y cells. These ideal conditions for footprinting also improved footprint quality when used with Drosophila melanogaster S2 cells. Footprinting under the same conditions generated different footprints sizes and framing patterns in human and D. melanogaster cells. We also found that treatment of S2 cells with cycloheximide prior to footprinting impacted the distribution of footprints across ORFs, without affecting overall read length distribution and framing pattern, as previously found in other organisms. Together our results indicate that a variety of factors affect ribosome footprint quality and the nature of precise footprinting varies across species.

Identifying Small Open Reading Frames in Prokaryotes with Ribosome Profiling

Small proteins encoded by open reading frames (ORFs) shorter than 50 codons (small ORFs [sORFs]) are often overlooked by annotation engines and are difficult to characterize using traditional biochemical techniques. Ribosome profiling has tremendous potential to empirically improve the annotations of prokaryotic genomes. Recent improvements in ribosome profiling methods for bacterial model organisms have revealed many new sORFs in well-characterized genomes. Antibiotics that trap ribosomes just after initiation have played a key role in these developments by allowing the unambiguous identification of the start codons (and, hence, the reading frame) for novel ORFs. Here, we describe these new methods and highlight critical controls and considerations for adapting ribosome profiling to different prokaryotic species.

An Aggregation Method to Identify the RNA Meta-Stable Secondary Structure and its Functionally Interpretable Structure Ensemble

RNA can provide vital cellular functions through its secondary or tertiary structure. Due to the low-throughput nature of experimental approaches, studies on RNA structures mainly resort to computational methods. However, current existing tools fail to consider RNA structure ensembles and do not provide ways to decipher functional hypotheses for the new predictions. In this research, a novel method was proposed to identify the functionally interpretable structure ensemble of a given RNA sequence and provide the meta-stable structure, or the most frequently observed functional RNA cellular conformation, based on the ensemble. In the prediction of meta-stable structures, the proposed method outperformed existing tools on a yeast test set. The inferred functional aspects were then manually checked and demonstrated a micro-averaging F1 value of 0.92. Further, a biological example of the yeast ASH1-E1 element was discussed to articulate that these functional aspects can also suggest testable hypotheses. Then the proposed method was verified to be well applicable to other species through a human test set. Finally, the proposed method was demonstrated to show resistance to sequence length-dependent performance deterioration.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Single-cell Ribo-seq reveals cell cycle-dependent translational pausing

Single-cell sequencing methods have enabled in-depth analysis of the diversity of cell types and cell states in a wide range of organisms. These tools focus predominantly on sequencing the genomes¹, epigenomes² and transcriptomes³ of single cells. However, despite recent progress in detecting proteins by mass spectrometry with single-cell resolution⁴, it remains a major challenge to measure translation in individual cells. Here, building on existing protocols^5-7, we have substantially increased the sensitivity of these assays to enable ribosome profiling in single cells. Integrated with a machine learning approach, this technology achieves single-codon resolution. We validate this method by demonstrating that limitation for a particular amino acid causes ribosome pausing at a subset of the codons encoding the amino acid. Of note, this pausing is only observed in a sub-population of cells correlating to its cell cycle state. We further expand on this phenomenon in non-limiting conditions and detect pronounced GAA pausing during mitosis. Finally, we demonstrate the applicability of this technique to rare primary enteroendocrine cells. This technology provides a first step towards determining the contribution of the translational process to the remarkable diversity between seemingly identical cells.

Humans and other commonly used model organisms are resistant to cycloheximide-mediated biases in ribosome profiling experiments

Ribosome profiling measures genome-wide translation dynamics at sub-codon resolution. Cycloheximide (CHX), a widely used translation inhibitor to arrest ribosomes in these experiments, has been shown to induce biases in yeast, questioning its use. However, whether such biases are present in datasets of other organisms including humans is unknown. Here we compare different CHX-treatment conditions in human cells and yeast in parallel experiments using an optimized protocol. We find that human ribosomes are not susceptible to conformational restrictions by CHX, nor does it distort gene-level measurements of ribosome occupancy, measured decoding speed or the translational ramp. Furthermore, CHX-induced codon-specific biases on ribosome occupancy are not detectable in human cells or other model organisms. This shows that reported biases of CHX are species-specific and that CHX does not affect the outcome of ribosome profiling experiments in most settings. Our findings provide a solid framework to conduct and analyze ribosome profiling experiments.

Ribosome profiling has become the gold standard to analyze mRNA translation dynamics, and the translation inhibitor cycloheximide (CHX) is often used in its application. Here the authors systematically demonstrate that CHX does not bias the outcome of ribosome profiling experiments in most organisms.

Estimation of peptide elongation times from ribosome profiling spectra

Ribosome profiling spectra bear rich information on translation control and dynamics. Yet, due to technical biases in library generation, extracting quantitative measures of discrete translation events has remained elusive. Using maximum likelihood statistics and data set from Escherichia coli we develop a robust method for neutralizing technical biases (e.g. base specific RNase preferences in ribosome-protected mRNA fragments (RPF) generation), which allows for correct estimation of translation times at single codon resolution. Furthermore, we validated the method with available datasets from E. coli treated with antibiotic to inhibit isoleucyl-tRNA synthetase, and two datasets from Saccharomyces cerevisiae treated with two RNases with distinct cleavage signatures. We demonstrate that our approach accounts for RNase cleavage preferences and provides bias-corrected translation times estimates. Our approach provides a solution to the long-standing problem of extracting reliable information about peptide elongation times from highly noisy and technically biased ribosome profiling spectra.

Persistence of Ambigrammatic Narnaviruses Requires Translation of the Reverse Open Reading Frame

Narnaviruses are RNA viruses detected in diverse fungi, plants, protists, arthropods, and nematodes. Though initially described as simple single-gene nonsegmented viruses encoding RNA-dependent RNA polymerase (RdRp), a subset of narnaviruses referred to as "ambigrammatic" harbor a unique genomic configuration consisting of overlapping open reading frames (ORFs) encoded on opposite strands. Phylogenetic analysis supports selection to maintain this unusual genome organization, but functional investigations are lacking. Here, we establish the mosquito-infecting Culex narnavirus 1 (CxNV1) as a model to investigate the functional role of overlapping ORFs in narnavirus replication. In CxNV1, a reverse ORF without homology to known proteins covers nearly the entire 3.2-kb segment encoding the RdRp. Additionally, two opposing and nearly completely overlapping novel ORFs are found on the second putative CxNV1 segment, the 0.8-kb "Robin" RNA. We developed a system to launch CxNV1 in a naive mosquito cell line and then showed that functional RdRp is required for persistence of both segments, and an intact reverse ORF is required on the RdRp segment for persistence. Mass spectrometry of persistently CxNV1-infected cells provided evidence for translation of this reverse ORF. Finally, ribosome profiling yielded a striking pattern of footprints for all four CxNV1 RNA strands that was distinct from actively translating ribosomes on host mRNA or coinfecting RNA viruses. Taken together, these data raise the possibility that the process of translation itself is important for persistence of ambigrammatic narnaviruses, potentially by protecting viral RNA with ribosomes, thus suggesting a heretofore undescribed viral tactic for replication and transmission. IMPORTANCE Fundamental to our understanding of RNA viruses is a description of which strand(s) of RNA are transmitted as the viral genome relative to which encode the viral proteins. Ambigrammatic narnaviruses break the mold. These viruses, found broadly in fungi, plants, and insects, have the unique feature of two overlapping genes encoded on opposite strands, comprising nearly the full length of the viral genome. Such extensive overlap is not seen in other RNA viruses and comes at the cost of reduced evolutionary flexibility in the sequence. The present study is motivated by investigating the benefits which balance that cost. We show for the first time a functional requirement for the ambigrammatic genome configuration in Culex narnavirus 1, which suggests a model for how translation of both strands might benefit this virus. Our work highlights a new blueprint for viral persistence, distinct from strategies defined by canonical definitions of the coding strand.

Genome-wide Survey of Ribosome Collision

Ribosome movement is not always smooth and is rather often impeded. For ribosome pauses, fundamental issues remain to be addressed, including where ribosomes pause on mRNAs, what kind of RNA/amino acid sequence causes this pause, and the physiological significance of this attenuation of protein synthesis. Here, we survey the positions of ribosome collisions caused by ribosome pauses in humans and zebrafish using modified ribosome profiling. Collided ribosomes, i.e., disomes, emerge at various sites: Pro-Pro/Gly/Asp motifs; Arg-X-Lys motifs; stop codons; and 3' untranslated regions. The electrostatic interaction between the charged nascent chain and the ribosome exit tunnel determines the eIF5A-mediated disome rescue at the Pro-Pro sites. In particular, XBP1u, a precursor of endoplasmic reticulum (ER)-stress-responsive transcription factor, shows striking queues of collided ribosomes and thus acts as a degradation substrate by ribosome-associated quality control. Our results provide insight into the causes and consequences of ribosome pause by dissecting collided ribosomes.

Comparative analysis of the relationship between translation efficiency and sequence features of endogenous proteins in multiple organisms

The translation efficiency of protein genes is known to be affected by sequence features. Previous studies have found that various sequence features based on codon usage and mRNA secondary structure contribute to translation efficiency. However, most studies have focused on a specific organism, usually a model organism such as Escherichia coli or Saccharomyces cerevisiae. Here, we investigate whether the relationship between translation efficiency and sequence features is conserved among multiple organisms using publicly available ribosome profiling data and RNA-Seq data. We analyze nine organisms from various taxa: Staphylococcus aureus, five species of Streptomyces, two strains of E. coli, and S. cerevisiae. We reveal that the relationship between translation efficiency and sequence features differs across organisms, partly reflecting their taxonomy. The codon adaptation index shows high correlation in all analyzed organisms. Our study provides an insight into the diversity and commonality of sequence determinants of protein expression in these organisms.

Codon-based indices for modeling gene expression and transcript evolution

Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.

Active Ribosome Profiling with RiboLace: From Bench to Data Analysis

Ribosome profiling is based on the deep sequencing of RNA fragments protected by ribosomes from nuclease digestion. This technique has been extensively used to study translation, with the unique ability to provide information about ribosomes positioning along transcripts at single-nucleotide resolution. Classical ribosome profiling approaches do not distinguish between fragments protected by either actively translating or inactive ribosomes. Here we describe an original method, called active ribosome profiling or RiboLace, which is based on a unique puromycin-containing molecule capable of isolating active ribosomes by means of an antibody-free and tag-free pull-down approach. This method allows reliable estimates of the translational state of any biological system, in high concordance with protein levels. RiboLace can be applied both in vitro and in vivo and generates snapshots of active ribosome footprints at single-nucleotide resolution and genome-wide level. RiboLace data are suitable for the analysis of translated genes, codon-specific translation rates, and local changes in ribosome occupancy profiles.

Choice of Ribonucleases for Ribosome Profiling Experiments

In the past 10 years, standard transcriptome sequencing protocols were optimized so well that no prior experience is required to prepare the sequencing library. Often, all enzymatic steps are designed to work in the same reaction tube minimizing handling time and reducing human errors. Ribosome profiling stands out from these methods. It is a very demanding technique that requires isolation of intact ribosomes, and thus there are multiple additional considerations that must be accounted for (McGlincy and Ingolia, Methods 126:112-129, 2017). In this chapter, we discuss how to select a ribonuclease to produce ribosomal footprints that will be later converted to the sequencing library. Several ribonucleases with different cutting patterns are commercially available. Selecting the right one for the experimental application can save a lot of time and frustration.

Ribo-ODDR: Oligo design pipeline for experiment-specific rRNA depletion in ribo-seq

Motivation

Ribosome Profiling (Ribo-seq) has revolutionized the study of RNA translation by providing information on ribosome positions across all translated RNAs with nucleotide-resolution. Yet several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of rRNA fragments. Various strategies can be employed to tackle this issue, including the use of commercial rRNA depletion kits. However, as they are designed for more standardized RNAseq experiments, they may perform suboptimally in Ribo-seq. In order to overcome this, it is possible to use custom biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos.

Results

Here, we first show that a major confounding issue is that the rRNA fragments generated via Ribo-seq vary significantly with differing experimental conditions, suggesting that a ‘one-size-fits-all’ approach may be inefficient. Therefore we developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We experimentally show that Ribo-ODDR designed oligos outperform commercially available kits and lead to a significant increase in rRNA depletion in Ribo-seq.

Availability and implementation

Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Variability in mRNA translation: a random matrix theory approach

The rate of mRNA translation depends on the initiation, elongation, and termination rates of ribosomes along the mRNA. These rates depend on many "local" factors like the abundance of free ribosomes and tRNA molecules in the vicinity of the mRNA molecule. All these factors are stochastic and their experimental measurements are also noisy. An important question is how protein production in the cell is affected by this considerable variability. We develop a new theoretical framework for addressing this question by modeling the rates as identically and independently distributed random variables and using tools from random matrix theory to analyze the steady-state production rate. The analysis reveals a principle of universality: the average protein production rate depends only on the of the set of possible values that the random variable may attain. This explains how total protein production can be stabilized despite the overwhelming stochasticticity underlying cellular processes.

The effects of codon bias and optimality on mRNA and protein regulation

The central dogma of molecular biology entails that genetic information is transferred from nucleic acid to proteins. Notwithstanding retro-transcribing genetic elements, DNA is transcribed to RNA which in turn is translated into proteins. Recent advancements have shown that each stage is regulated to control protein abundances for a variety of essential physiological processes. In this regard, mRNA regulation is essential in fine-tuning or calibrating protein abundances. In this review, we would like to discuss one of several mRNA-intrinsic features of mRNA regulation that has been gaining traction of recent-codon bias and optimality. Specifically, we address the effects of codon bias with regard to codon optimality in several biological processes centred on translation, such as mRNA stability and protein folding among others. Finally, we examine how different organisms or cell types, through this system, are able to coordinate physiological pathways to respond to a variety of stress or growth conditions.

Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling

Translation of mRNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. Through a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae, we systematically identify short 3-codon sequences that are differentially translated (DT) across mRNAs, that is, identical sequences that are translated sometimes fast and sometimes slowly beyond what can be attributed to variability between experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.

A Mini-review of Computational Approaches to Predict Functions and Findings of Novel Micro Peptides

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New techniques in bioinformatics and the study of the transcriptome at a wide-scale have uncovered the fact that a large part of the genome is being translated than recently perceived thoughts and research, bringing about the creation of a various quantity of RNA with proteincoding and noncoding potential. A lot of RNA particles have been considered as noncoding due to many reasons, according to developing proofs. Like many sORFs that encode many functional micro peptides have neglected due to their tiny sizes.

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Advanced studies reveal many major biological functions of these sORFs and their encoded micro peptides in a different and wide range of species. All the achievement in the identification of these sORFs and micro peptides is due to the progressive bioinformatics and high-throughput sequencing methods. This field has pulled in more consideration due to the detection of a large number of more sORFs and micro peptides. Nowadays, COVID-19 grabs all the attention of science as it is a sudden outbreak. sORFs of COVID-19 should be revealed for new ways to understand this virus. This review discusses ongoing progress in the systems for the identification and distinguishing proof of sORFs and micro peptides.

Translation elongation rate varies among organs and decreases with age

There has been a surge of interest towards targeting protein synthesis to treat diseases and extend lifespan. Despite the progress, few options are available to assess translation in live animals, as their complexity limits the repertoire of experimental tools to monitor and manipulate processes within organs and individual cells. It this study, we developed a labeling-free method for measuring organ- and cell-type-specific translation elongation rates in vivo. It is based on time-resolved delivery of translation initiation and elongation inhibitors in live animals followed by ribosome profiling. It also reports translation initiation sites in an organ-specific manner. Using this method, we found that the elongation rates differ more than 50% among mouse organs and determined them to be 6.8, 5.0 and 4.3 amino acids per second for liver, kidney, and skeletal muscle, respectively. We further found that the elongation rate is reduced by 20% between young adulthood and mid-life. Thus, translation, a major metabolic process in cells, is tightly regulated at the level of elongation of nascent polypeptide chains.

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling

Translation elongation is a crucial phase during protein biosynthesis. In this study, we develop a novel deep reinforcement learning-based framework, named Riboexp, to model the determinants of the uneven distribution of ribosomes on mRNA transcripts during translation elongation. In particular, our model employs a policy network to perform a context-dependent feature selection in the setting of ribosome density prediction. Our extensive tests demonstrated that Riboexp can significantly outperform the state-of-the-art methods in predicting ribosome density by up to 5.9% in terms of per-gene Pearson correlation coefficient on the datasets from three species. In addition, Riboexp can indicate more informative sequence features for the prediction task than other commonly used attribution methods in deep learning. In-depth analyses also revealed the meaningful biological insights generated by the Riboexp framework. Moreover, the application of Riboexp in codon optimization resulted in an increase of protein production by around 31% over the previous state-of-the-art method that models ribosome density. These results have established Riboexp as a powerful and useful computational tool in the studies of translation dynamics and protein synthesis. Availability: The data and code of this study are available on GitHub: https://github.com/Liuxg16/Riboexp. Contact:  zengjy321@tsinghua.edu.cn; songsen@tsinghua.edu.cn.

Insights Into Translatomics in the Nervous System

Most neurological disorders are caused by abnormal gene translation. Generally, dysregulation of elements involved in the translational process disrupts homeostasis in neurons and neuroglia. Better understanding of how the gene translation process occurs requires detailed analysis of transcriptomic and proteomic profile data. However, a lack of strictly direct correlations between mRNA and protein levels limits translational investigation by combining transcriptomic and proteomic profiling. The much better correlation between proteins and translated mRNAs than total mRNAs in abundance and insufficiently sensitive proteomics approach promote the requirement of advances in translatomics technology. Translatomics which capture and sequence the mRNAs associated with ribosomes has been effective in identifying translational changes by genetics or projections, ribosome stalling, local translation, and transcript isoforms in the nervous system. Here, we place emphasis on the main three translatomics methods currently used to profile mRNAs attached to ribosome-nascent chain complex (RNC-mRNA). Their prominent applications in neurological diseases including glioma, neuropathic pain, depression, fragile X syndrome (FXS), neurodegenerative disorders are outlined. The content reviewed here expands our understanding on the contributions of aberrant translation to neurological disease development.

Monitoring Bacterial Translation Rates Genome-Wide

Modern DNA sequencing technologies have allowed for the sequencing of tens of thousands of bacterial genomes. While this explosion of information has brought about new insights into the diversity of the prokaryotic world, much less is known of the identity of proteins encoded within these genomes, as well as their rates of production. The advent of ribosome profiling, or the deep sequencing of ribosome-protected footprints, has recently enabled the systematic evaluation of every protein-coding region in a given experimental condition, the rates of protein production for each gene, and the variability in translation rates across each message. Here, I provide an update to the bacterial ribosome profiling approach, with a particular emphasis on a simplified strategy to reduce cloning time.

Codon Resolution Analysis of Ribosome Profiling Data

Translation is a central biological process in living cells. Ribosome profiling approach enables assessing translation on a global, cell-wide level. Extracting versatile information from the ribosome profiling data usually requires specialized expertise for handling the sequencing data that is not available to the broad community of experimentalists. Here, we provide an easy-to-use and modifiable workflow that uses a small set of commands and enables full data analysis in a standardized way, including precise positioning of the ribosome-protected fragments, for determining codon-specific translation features. The workflow is complemented with simple step-by-step explanations and is accessible to scientists with no computational background.

Protein Synthesis in the Developing Neocortex at Near-Atomic Resolution Reveals Ebp1-Mediated Neuronal Proteostasis at the 60S Tunnel Exit

Protein synthesis must be finely tuned in the developing nervous system as the final essential step of gene expression. This study investigates the architecture of ribosomes from the neocortex during neurogenesis, revealing Ebp1 as a high-occupancy 60S peptide tunnel exit (TE) factor during protein synthesis at near-atomic resolution by cryoelectron microscopy (cryo-EM). Ribosome profiling demonstrated Ebp1-60S binding is highest during start codon initiation and N-terminal peptide elongation, regulating ribosome occupancy of these codons. Membrane-targeting domains emerging from the 60S tunnel, which recruit SRP/Sec61 to the shared binding site, displace Ebp1. Ebp1 is particularly abundant in the early-born neural stem cell (NSC) lineage and regulates neuronal morphology. Ebp1 especially impacts the synthesis of membrane-targeted cell adhesion molecules (CAMs), measured by pulsed stable isotope labeling by amino acids in cell culture (pSILAC)/bioorthogonal noncanonical amino acid tagging (BONCAT) mass spectrometry (MS). Therefore, Ebp1 is a central component of protein synthesis, and the ribosome TE is a focal point of gene expression control in the molecular specification of neuronal morphology during development.