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

Detecting ribosome collisions with differential rRNA fragment analysis in ribosome profiling data

It has become clear in recent years that ribosomes regularly stall during translation. Such translation impairment has many causes, including exposure to ribotoxic stress agents, the presence of specific RNA structures or sequences, or a shortage of amino acids or translation factors. If they are not resolved, stalled ribosomes can lead to ribosome collisions that are continuously surveilled by various sensor proteins. This in turn initiates a cascade of signalling events that can change the physiology and behaviour of cells. However, measuring changes in collision abundance has proved challenging, and as a result, the importance of collision-mediated biological responses is still unclear. Here, we show that computational analyses of standard ribosome profiling (Ribo-seq) data enable the prediction of changes in ribosome collisions between conditions. This is achieved by using the known 3D structure of collided ribosomes to define the ribosomal RNA (rRNA) positions that are differentially digested by RNases during the Ribo-seq protocol. Comparison of the relative rRNA reads at these positions allows the relative quantification of collisions between samples, an approach we call differential ribosome collisions by Analysis of rRNA Fragments (dricARF). When applied to public datasets across multiple organisms, our approach detects changes in collision events with unprecedented accuracy and sensitivity. In addition to providing supplementary evidence for ribosome collisions, our tool has the potential to uncover novel biological processes that are mediated by them. dricARF is available as part of the ARF R package and can be accessed through https://github.com/fallerlab/ARF.

Advances in ribosome profiling technologies

Ribosome profiling (or Ribo-seq) has emerged as a powerful approach for revealing the regulatory mechanisms of protein synthesis, on the basis of deep sequencing of ribosome footprints. Recent innovations in Ribo-seq technologies have significantly enhanced their sensitivity, specificity, and resolution. In this review, we outline emerging Ribo-seq derivatives that overcome barriers in low inputs, rRNA contamination, data calibration, and single-cell applications. These advances enable detailed insights into translational control across diverse biological contexts.

RiboParser/RiboShiny: an integrated platform for comprehensive analysis and visualization of Ribo-seq data

Translation is a crucial step in gene expression. Over the past decade, the development and application of Ribosome profiling (Ribo-seq) have significantly advanced our understanding of translational regulation in vivo. However, the analysis and visualization of Ribo-seq data remain challenging. Despite the availability of various analytical pipelines, improvements in comprehensiveness, accuracy, and user-friendliness are still necessary. In this study, we develop RiboParser/RiboShiny, a robust framework for analyzing and visualizing Ribo-seq data. Building on published methods, we optimize ribosome structure-based and start/stop-based models to improve the accuracy and stability of P-site detection, even in species with a high proportion of leaderless transcripts. Leveraging these improvements, RiboParser offers comprehensive analyses, including quality control, gene-level analysis, codon-level analysis, and the analysis of Ribo-seq variants. Meanwhile, RiboShiny provides a user-friendly and adaptable platform for data visualization, facilitating deeper insights into the translational landscape. Furthermore, the integration of standardized genome annotation renders our platform universally applicable to various organisms with sequenced genomes. This framework has the potential to significantly improve the precision and efficiency of Ribo-seq data interpretation, thereby deepening our understanding of translational regulation.

NAC regulates metabolism and cell fate in intestinal stem cells

Intestinal stem cells (ISCs) face the challenge of integrating metabolic demands with unique regenerative functions. Studies have shown an intricate interplay between metabolism and stem cell capacity; however, it is still not understood how this process is regulated. Combining ribosome profiling and CRISPR screening in intestinal organoids, we identify the nascent polypeptide-associated complex (NAC) as a key mediator of this process. Our findings suggest that NAC is responsible for relocalizing ribosomes to the mitochondria and regulating ISC metabolism. Upon NAC inhibition, intestinal cells show decreased import of mitochondrial proteins, which are needed for oxidative phosphorylation, and, consequently, enable the cell to maintain a stem cell identity. Furthermore, we show that overexpression of NACα is sufficient to drive mitochondrial respiration and promote ISC identity. Ultimately, our results reveal the pivotal role of NAC in regulating ribosome localization, mitochondrial metabolism, and ISC function, providing insights into the potential mechanism behind it.

Ribo-seq and RNA-seq analyses enrich the regulatory network of tomato fruit cracking

Tomato (Solanum lycopersicum L.), one of the most widely grown vegetable crops in the world, faces cracking problems before and after harvest. Fruit cracking reduces the commercial value and seriously affects the economic performance of the fruits by affecting the appearance and quality of the fruit. Clarifying the molecular mechanism underlying tomato fruit cracking is of great importance for selecting and breeding cracking-resistant varieties. At present, research on the molecular mechanism of tomato fruit cracking has made progress, but few studies have been conducted to explore the genes related to fruit cracking regulation using combined multi-omics analysis. We applied Ribo-seq (ribosome analysis sequencing) and RNA-seq (RNA-sequencing) techniques to uncover potential fruit cracking regulatory genes and improve the regulatory network of fruit cracking using extremely cracking-resistant (CR) and cracking-susceptible (CS) tomato genotypes. Combining these two sets of histological data and translation efficiency, 41 genes were identified to be associated with fruit cracking. The genes played functions on hormone synthesis (e.g. Solyc09g089580.4, Solyc07g049530.3), reactive oxygen species regulation (e.g. Solyc08g080940.3), cell wall metabolism (e.g. Solyc04g071070.2, Solyc03g123630.4), aquaporins activity (e.g. Solyc03g096290.3, Solyc10g083880.2), cuticle and wax composition, as well as mineral elements transport (e.g. Solyc10g006660.3, Solyc01g057770.3), while 10 of them were transcription factors (TF) (e.g. Solyc05g015850.4, Solyc08g078190.2). Based on the investigation of the interaction relationship between these genes, the synergistic regulation of multi-gene tomato fruit cracking was predicted. This study suggests that the synergistic action of transcription and translation is an important molecular mechanism in regulating tomato fruit cracking.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Ribosome profiling, which is based on deep sequencing of ribosome footprints, has served as a powerful tool for elucidating the regulatory mechanism of protein synthesis. However, the current method has substantial issues: contamination by rRNAs and the lack of appropriate methods to measure ribosome numbers in transcripts. Here, we overcome these hurdles through the development of "Ribo-FilterOut", which is based on the separation of footprints from ribosome subunits by ultrafiltration, and "Ribo-Calibration", which relies on external spike-ins of stoichiometrically defined mRNA-ribosome complexes. A combination of these approaches estimates the number of ribosomes on a transcript, the translation initiation rate, and the overall number of translation events before its decay, all in a genome-wide manner. Moreover, our method reveals the allocation of ribosomes under heat shock stress, during aging, and across cell types. Our strategy of modified ribosome profiling measures kinetic and stoichiometric parameters of cellular translation across the transcriptome.

Ribosome impairment regulates intestinal stem cell identity via ZAKɑ activation

The small intestine is a rapidly proliferating organ that is maintained by a small population of Lgr5-expressing intestinal stem cells (ISCs). However, several Lgr5-negative ISC populations have been identified, and this remarkable plasticity allows the intestine to rapidly respond to both the local environment and to damage. However, the mediators of such plasticity are still largely unknown. Using intestinal organoids and mouse models, we show that upon ribosome impairment (driven by Rptor deletion, amino acid starvation, or low dose cyclohexamide treatment) ISCs gain an Lgr5-negative, fetal-like identity. This is accompanied by a rewiring of metabolism. Our findings suggest that the ribosome can act as a sensor of nutrient availability, allowing ISCs to respond to the local nutrient environment. Mechanistically, we show that this phenotype requires the activation of ZAKɑ, which in turn activates YAP, via SRC. Together, our data reveals a central role for ribosome dynamics in intestinal stem cells, and identify the activation of ZAKɑ as a critical mediator of stem cell identity.

Intestinal stem cells are responsible for replenishing cells within the high-turnover intestinal epithelium. Here they show that ribosome dynamics affect intestinal stem cell identity through a mechanism that is triggered by changes in nutrient availability.

Identifying ribosome heterogeneity using ribosome profiling

Recent studies have revealed multiple mechanisms that can lead to heterogeneity in ribosomal composition. This heterogeneity can lead to preferential translation of specific panels of mRNAs, and is defined in large part by the ribosomal protein (RP) content, amongst other things. However, it is currently unknown to what extent ribosomal composition is heterogeneous across tissues, which is compounded by a lack of tools available to study it. Here we present dripARF, a method for detecting differential RP incorporation into the ribosome using Ribosome Profiling (Ribo-seq) data. We combine the 'waste' rRNA fragment data generated in Ribo-seq with the known 3D structure of the human ribosome to predict differences in the composition of ribosomes in the material being studied. We have validated this approach using publicly available data, and have revealed a potential role for eS25/RPS25 in development. Our results indicate that ribosome heterogeneity can be detected in Ribo-seq data, providing a new method to study this phenomenon. Furthermore, with dripARF, previously published Ribo-seq data provides a wealth of new information, allowing the identification of RPs of interest in many disease and normal contexts. dripARF is available as part of the ARF R package and can be accessed through https://github.com/fallerlab/ARF.