Understanding the Organization and functional Control of Polysomes by integrative Approaches

Background and rationale Translation is a fundamental biological process occurring in cells, carried out by ribosomes simultaneously bound to an mRNA molecule (polyribosomes). It has been exhaustively demonstrated that dysregulation of translation is implicated in a wide collection of pathologies including tumours and neurological disorders. Latest findings reveal the existence of translational regulatory mechanisms acting in cis or trans with respect to the mRNAs and governing the movement and the position of ribosomes along transcripts or directly impacting on the ribosome catalogue of its constituent proteins. For this reason, translational controls also account for widespread uncoupling between transcript and protein abundances in cells. To explain the poor correlation between transcripts and protein levels, many computational models of translation have been developed. Usually, these approaches aim at predicting protein abundances in cells starting from the mRNA abundance. Despite the efforts of these modelling studies, a consensus model remains elusive, drawing to contradictory conclusions concerning the role of mRNA regulatory elements such as the usage of codons (codon usage bias) and slowdown mechanism at the beginning of the coding sequence (ramp). More recently, following the rapid and widespread diffusion of ribosome footprinting assays (RiboSeq), which enables the dissection of translation at single nucleotide resolution, a number of computational pipelines dedicated to the analysis of RiboSeq data have been proposed. These tools are typically designed for extracting gene expression alterations at the translational level, while the positional information describing fluxes and positions of ribosomes along the transcript is still underutilized. Therefore, the polysome organization, in term of number and position of ribosomes along the transcript and the translational controls directed in shaping cellular phenotypes is still open to breakthrough discoveries. Broad objectives The aim of my thesis is the development of mathematical and computational tools integrated with experimental data for a comprehensive understanding of translation regulation and polysome organization rules governing the number of ribosomes per polysome and the ribosome position along transcripts. Project design and methods With this purpose, I developed riboWaves, an integrated bioinformatics suite divided in two branches. riboWaves includes in the first branch two modeling modules: riboAbacus, predicting the number of ribosomes per transcript, and riboSim, predicting ribosome localization along mRNAs. In the second branch, riboWaves provides two pipelines, riboWaltz and riboScan, for detailed analyses of ribosome profiling data aimed at providing meaningful and yet unexplored ribosome positional information. The models and the pipelines are implemented in C and R, respectively. riboAbacus and riboWaltz are available on GitHub. Results To predict the number of ribosomes per transcript and the position of ribosomes on mRNAs, I applied riboAbacus and riboSim, respectively, to transcriptomes of different organisms (yeast, mouse, human) for understanding the role of translational regulatory elements in tuning polysome in different organisms. First, I trained and validated performances of riboAbacus taking advantage of Atomic Force Microscopy images of polysomes, while performances of riboSim were assessed employing ribosome profiling data. Predictions provided by riboAbacus and riboSim were evaluated in parallel. I showed that the average number of ribosomes translating a molecule of mRNA can be well explained by the deterministic model, riboAbacus, that includes as features the mRNA levels, the mRNA sequences, the codon usage bias and a slowdown mechanism at the beginning of the CDS (ramp hypothesis). The predictions of ribosome localization by riboSim that used as features the mRNA sequence, the codon usage and the ramp, were run for yeast, mouse and human. I observed a good similarity between the predicted and experimental positions of ribosomes along transcripts in yeast, while poor similarity was obtained between predicted and experimental ribosome positions in the two mammals, suggesting the presence of more elaborate controls that tune ribosomes movement in higher eukaryotes than in simple species. After having developed two tools for the analyses of RiboSeq data and extraction of positional information on ribosome localization along transcripts, I applied both riboWaltz and riboScan in a case study. The aim was to dissect possible defects in ribosome localization in tissues of a mouse model of Spinal Muscular Atrophy (SMA). SMA is a neurodegenerative disorder caused by low levels of the Survival of Motor Neuron protein (SMN) in which translational impairments are recently emerging as possible cause of the disease. I analysed ribosome profiling data obtained from three different types of RiboSeq variants in healthy and SMA-affected mouse brains at the early-symptomatic stage of the disease. I observed i) a significant drop-off of translating ribosomes along the coding sequence in the SMA condition (using riboWaltz); ii) in SMA-affected mice, the possible accumulation of ribosomes along the 3' UTR in neuro-related mRNAs (using riboScan); iii) the involvement of SMN-specialized ribosomes in playing a very intimate role with the elongation stage of translation of the first codons of transcripts (riboWaltz), iv) the loss of ribosomes at the 3rd codon in SMA in transcripts bound by SMN-specialized ribosomes and v) a remarkable connection between SMN and the down-regulation of genes in SMA-affected mice. Overall, these findings confirmed previous observation about possible SMN-related dysregulations of local protein synthesis in neurons. More importantly, they unravel a completely new role of SMN in tuning translation at multiple levels (initiation, elongation and the recycling of terminating ribosomes), opening new hypotheses and scenarios for explaining the most devastating genetic disease, leading cause worldwide of infant mortality. Conclusions The present work provides a new comprehensive and integrated scenario for better understanding translation and demonstrates that this approach is a very powerful strategy to pave the way for new understanding of fine alteration in polysome organization and functional control in both physiological and pathological conditions

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates

An analysis of translation heterogeneity in ribosome profiling data

Les protéines sont responsables de pratiquement toutes les fonctions performées au sein du corps cellulaire et de ses alentours. Le contrôle de l’expression génique détermine l’abondance, la localisation et le moment de la production de protéines dans la cellule. Il s’agit de l’un des processus centraux à la régulation de la physiologie et du fonctionnement cellulaire. La moindre perte de balance dans ce complexe système engendre des conséquences majeures sur l’intégrité cellulaire, menant au développement de plusieurs maladies parfois incurables. La traduction de l’ARN messager en produit protéique constitue la dernière étape de l’expression génique. Elle est régulée de plusieurs façons, intrinsèques et extrinsèques à la séquence. Il s’agit également du processus cellulaire le plus coûteux en termes d’énergie. Le profilage des ribosomes (Ribo-Seq) figure parmi les récentes et prometteuses technologies ayant permis une meilleure étude des mécanismes de régulation de la traduction. Ces résultats contiennent toutefois la présence de variabilité et de bruits de nature infondée. Ce travail présente la mise en place d’une stratégie permettant la dissociation de signaux d’origine biologique de ceux ayant une origine technique. Ceci est effectué au travers de la mise en place de profiles consensus de densité ribosomale extrait d’une analyse comparative de plusieurs expériences de Ribo-Seq chez la levure (Saccharomyces cerevisiae). Les signaux biologiques dérivés par les profils consensus correspondent avec les signatures de pauses ribosomales connues, telles que les scores de repliements de l’ARNm et la charge des acides aminés. Épatamment, notre stratégie a également permis l’identification de séquences différentiellement transcrites (DT). Ces dernières jouent un rôle sur la cinétique de la phase d’élongation de la traduction, elles comportent notamment une surreprésentation de codons associés aux modifications des ARNs de transfert (tRNAs). Elles se retrouvent d’ailleurs impliquées dans le maintien de l’homéostase cellulaire, ayant une présence marquée chez des gènes prenants part aux mécanismes de biosynthèse de la macromolécule ribosomale ainsi que chez les ARNms aux sublocalisations cellulaires précises, notamment chez les mitochondries et le réticulum endoplasmique (ER). En plus de démontrer les possibilités de découvertes offertes par la technique du Ribo-Seq, cette étude présente une évidence de la nature dynamique et hétérogène du processus de traduction chez la cellule eucaryote. Elle démontre également le rôle de l’information directement encodée dans la séquence dans l’optimisation générale de l’homéostasie cellulaire.Proteins are responsible for virtually all functions performed within and in the surroundings of a cell. The control of gene expression, which determines the amount, localisation and timing of protein production in the cell, is the central processes in the regulation of cellular physiology and function. Any disturbance in this complex system can generate important consequences on cellular integrity, sometimes leading to incurable diseases. The translation of messenger RNA into a protein product is the last step of the gene expression mechanism. It can be regulated in manifold ways, both intrinsically and extrinsically to the transcript sequence. It is also the costliest cellular process in terms of energy. Ribosome profiling (Ribo-Seq) is one of the recent and promising technologies making it possible to better study the mechanisms of translation regulation. Its results have however been shown to display variability in reproducibility and to contain noise of uncharted sources. This work presents the implementation of a strategy for dissociating signals of biological origin from those of technical origin. This is performed by the computation of a consensus profile of ribosomal density derived from a comparative analysis of several Ribo-Seq experiments in yeast (Saccharomyces cerevisiae). The biological signals derived by the consensus profiles correspond with signatures of known ribosomal pauses, such as mRNA folding strength and amino acid charges. Amazingly, our strategy also enabled the identification of differentially transcribed (DT) sequences. The latter have shown an over-representation of codons associated with modifications of transfer RNAs (tRNAs). They are also involved in the control of cellular homeostasis, exhibiting a marked presence in genes involved in ribosome biosynthesis as well as in mRNAs with precise translation sub-localization, particularly in mitochondria and the endoplasmic reticulum (ER). In addition to demonstrating the possibilities of discovery offered by the Ribo-Seq technique, this study also presents evidence of the dynamic and heterogeneous nature of the translation process in the eukaryotic cell. It also showcases its diverse regulatory mechanisms and the role of information directly encoded in the sequence in the general optimization of cellular homeostasis

Synonymous codons affect polysome spacing, protein production and protein folding stress: studies of bacterial translation using ribosome profiling

The acquisition of protein secondary and tertiary structure depends on the primary sequence of amino acids. However, predicting a protein's folded structure is difficult even with the knowledge of its sequence. It has been suggested that, in addition to encoding the amino acid sequence, genes also encode kinetic information which regulates the ribosome's translation rate. This information might guide nascent protein folding during translation. With the advent of ribosome profiling, a high-throughput sequencing technique which quantifies ribosome density on mRNA, it is now possible to investigate this hypothesis in greater detail. Here, a new way to analyze ribosome profiling data is presented, confirming that ribosome profiling detects ribosome pauses at slow codons. This method is able to precisely determine the locations of the ribosome aminoacyl and peptidyl transfer sites within the ribosome footprint. Next, a simulation tool which models the progression of ribosomes along an mRNA is used to explore the effects of translation initiation and elongation rates on protein expression. This tool can be used to generate testable predictions for how changing the translation rate should affect various experimental observables, including ribosome density. New experimental data, collected from the bacterium Escherichia coli, demonstrate that the sequence of the Firefly (Photinus pyralis) Luciferase mRNA affects its ribosome occupancy. Importantly, ribosome occupancy is differentially influenced by synonymous codons. These data also show that Luc expression is controlled by the 15 codons immediately downstream of the start codon and that greater Luciferase expression levels progressively activate the heat shock response. However, this response appears to saturate, suggesting that the overexpression of foreign proteins in E. coli readily overwhelms the endogenous chaperone system. This result demonstrates that expression level, rather than translation kinetics, determines the yield of folded Luciferase protein in E. coli