Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices

Experimental evidence shows that synonymous mutations can have important consequences on genetic fitness. Many organisms display codon usage bias (CUB), where synonymous codons that are translated into the same amino acid appear with distinct frequency. CUB is thought to arise from selection for translational efficiency and accuracy, termed the translational efficiency hypothesis (TEH). Indeed, CUB indices correlate with protein expression levels, which is widely interpreted as evidence for translational selection. However, these tests neglect -1 programmed ribosomal frameshifting (-1 PRF), an important translational disruption effect found across all organisms of the tree of life. Genes that contain -1 PRF signals should cost more to express than genes without. Thus, CUB indices that do not consider -1 PRF may overestimate genes' true adaptation to translational efficiency and accuracy constraints. Here, we first investigate whether -1 PRF signals do indeed carry such translational cost. We then propose two corrections for CUB indices for genes containing -1 PRF signals. We retest the TEH under these corrections. We find that the correlation between corrected CUB index and protein expression remains intact for most levels of uniform -1 PRF efficiencies, and tends to increase when these efficiencies decline with protein expression. We conclude that the TEH is strengthened and that -1 PRF events constitute a promising and useful tool to examine the relationships between CUB and selection for translation efficiency and accuracy

Ribosome selectivity and nascent chain context in modulating the incorporation of fluorescent non-canonical amino acid into proteins

Fluorescence reporter groups are important tools to study the structure and dynamics of proteins. Genetic code reprogramming allows for cotranslational incorporation of non‑canonical amino acids at any desired position. However, cotranslational incorporation of bulky fluorescence reporter groups is technically challenging and usually inefficient. Here we analyze the bottlenecks for the cotranslational incorporation of NBD‑, BodipyFL‑ and Atto520‑labeled Cys‑tRNACys into a model protein using a reconstituted in‑vitro translation system. We show that the modified Cys‑tRNACys can be rejected during decoding due to the reduced ribosome selectivity for the modified aa‑tRNA and the competition with native near‑cognate aminoacyl‑tRNAs. Accommodation of the modified Cys‑tRNACys in the A site of the ribosome is also impaired, but can be rescued by one or several Gly residues at the positions −1 to −4 upstream of the incorporation site. The incorporation yield depends on the steric properties of the downstream residue and decreases with the distance from the protein N‑terminus to the incorporation site. In addition to the full‑length translation product, we find protein fragments corresponding to the truncated N‑terminal peptide and the C‑terminal fragment starting with a fluorescence‑labeled Cys arising from a StopGo‑like event due to a defect in peptide bond formation. The results are important for understanding the reasons for inefficient cotranslational protein labeling with bulky reporter groups and for designing new approaches to improve the yield of fluorescence‑ labeled protein

Transfer RNA modification and infection – implications for pathogenicity and host responses

Open Access funded by the author(s).Transfer RNA (tRNA) molecules are sumptuously decorated with evolutionary conserved post-transcriptional nucleoside modifications that are essential for structural stability and ensure efficient protein translation. The tRNA modification levels change significantly in response to physiological stresses, altering translation in a number of ways. For instance, tRNA hypomodification leads to translational slowdown, disrupting protein homeostasis and reducing cellular fitness. This highlights the importance of proper tRNA modification as a determinant for maintaining cellular function and viability during stress. Furthermore, the expression of several microbial virulence factors is induced by changes in environmental conditions; a process where tRNA 2-thiolation is unequivocal for pathogenicity. In this review, we discuss the multifaceted implications of tRNA modification for infection by examining the roles of nucleoside modification in tRNA biology. Future development of novel methods and combinatory utilization of existing technologies will bring tRNA modification-mediated regulation of cellular immunity and pathogenicity to the limelight.Peer reviewe

Expanding and evaluating sense codon reassignment for genetic code expansion

2017 Summer.Includes bibliographical references.Genetic code expansion is a field of synthetic biology that aims to incorporate non-canonical amino acids (ncAAs) into proteins as though they were one of the 20 "natural" amino acids. The amino acids which naturally make up proteins are chemical limited, and ncAAs can carry new chemical functionality into proteins. Proteins are of interest because they are simple to produce with good consistency and have immense potential due to the diversity of structure and function. Incorporating ncAA into proteins expands the scope of function of proteins even further. Two methods have been widely used for genetic code expansion, global amino acid replacement and amber stop codon suppression. Global amino acid replacement exchanges one of the natural amino acids for a ncAA, producing an altered 20 amino acid genetic code. Amber stop codon suppression incorporates ncAA in response to the UAG stop codon making a 21 amino acid genetic code, but is limited in incorporation efficiency and producing proteins with multiple instances of a ncAA is challenging. We wanted to use a third genetic code expansion system called sense codon reassignment which has not been widely employed at all but should enable multisite incorporation of ncAAs. When the work presented in this dissertation was started, a single report of sense codon reassignment existed in the literature. We set out to improve and expand sense codon reassignment for the incorporation of multiple copies of ncAAs into proteins. We quickly discovered disparities in what was known regarding the variables that could be used to manipulate genetic code expansion, and the focus of our work shifted to systems for improving sense codon reassignment using quantitative measurements. The first chapter of this dissertation is an introduction to genetic code expansion and the processes of translation and gene expression that are likely involved or could be involved in genetic code expansion. The three following chapters will build upon the fundamentals described in Chapter 1. The second chapter is a complete story about how a screen to quantify sense codon reassignment was developed. The fluorescence based screen was used in a high throughput fashion to screen a directed evolution library of variants for increased sense codon reassignment efficiency at the Lys AAG sense codon. While evaluating various sense codons for potential reassignment efficiency, the AUG anticodon was found to be incapable of discriminating between the CAU and CAC codons. This was anomalous relative to the other anticodons we tested. Chapter 3 describes how unintended modifications to an engineered tRNA were identified and then how the fluorescence based screen was used to engineer the tRNA further for increased sense codon reassignment efficiency and to avoid the unintentional modification. Most applications of genetic code expansion rely on modifications to tRNAs but few reports actually consider them, The final chapter of this dissertation is a manuscript in preparation describing the reassignment of a rare sense codon to incorporate ncAAs. The chapter focuses on how improvements made in a system specific for an amino acid can be transferred to systems specific for other ncAAs. Over 150 different ncAAs have been incorporated into proteins using genetic code expansion technologies, but the extent to which the various systems are combinable has barely been evaluated. This dissertation is a story about developing sense codon reassignment to functional levels and quantifying the effects of different variables along the way

Biochemical analysis of translational recording driven by 2A peptide

PhD2A/2A-like peptides are short sequences (20-30 amino acids) encoded predominantly within open reading frames (ORFs) of RNA viruses. They drive a non-canonical translation, in which the nascent chain is released from the ribosome at a sense (proline) codon, followed by continued translation to generate a separate downstream protein, initiated from the same proline codon. The aim of this study is to investigate the role of ribosomal factors in the 2A reaction in Saccharomyces cerevisiae cells. Results obtained showed that reduced activity of eRF1/3 inhibits the 2A reaction. This inhibition did not strongly correlate with the effect that mutations have on termination at stop codons. In particular, several mutations within the NIKS motif, which is essential for stop codon recognition, had minimal effect on the 2A reaction. To confirm these results, we developed a new reporter to investigate the 2A activity, where the green fluorescent protein (GFP) sequence was separated with a 2A sequence, between residues 157 and 158. This reporter was utilised to confirm the effects of eRF1 mutations, previously assessed by immunoprecipitation, and results, observed by flow cytometry, revealed consistency in terms of the role of eRFs in the 2A reaction. In summary, these observations provide evidences supporting recruitment of eRFs to the ribosome to drive the non-canonical termination event that releases the first part of the 2A reaction.The Ministry of Higher Education and the University of Mosul/IRA

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

Computational Analysis of Microbial Sequence Data Using Statistics and Machine Learning

Since the discovery of the double helix of DNA in 1953, modern molecular biology has opened the door to a better understanding of how genes control chemical processes within cells, including protein synthesis. Although we are still far from claiming a complete understanding, recent advances in sequencing technologies, increased computational capacity, and more sophisticated computational methods have allowed the development of various new applications that provide further insight into DNA sequence data and how the information they encode impacts living organisms and their environment. Sequencing data can now be used to start identifying the relationships between microorganisms, where they live, and in some cases how they affect their host organisms. We introduce and compare methods used for this bioinformatics application, and develop a machine learning model that can be used to effectively predict environmental factors associated with these microorganisms. Codon Usage Bias (CUB), which refers to the highly non-uniform usage of codons that code for the same amino acid has been known to reflect the expression level of a protein-coding gene under the evolutionary theory that selection favors certain synonymous codons. Traditional methods used to estimate CUB and its relation with protein translation have been proven effective on single-celled organisms such as yeast and E. coli, but their applications are limited when it comes to more complex multi-cellular organisms such as plants and animals. To extend our abilities to further understand the relations between codon usage patterns and the protein translation processes in these organisms, we develop a novel deep learning model that can discover patterns in codon usage bias between different species using only their DNA sequences