Quantitative assessment of ribosome drop-off in E. coli

A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length

Ribosomes are the molecular machinery that catalyse all the fundamental steps involved in the translation of mRNAs into proteins. Given the complexity of this process, the efficiency of protein synthesis depends on a large number of factors among which ribosome drop-off (i.e. the premature detachment of the ribosome from the mRNA template) plays an important role. However, an in vitro quantification of the extent to which ribosome drop-off occurs is not trivial due to difficulties in obtaining the needed experimental evidence. In this work we focus on the study of ribosome drop-off in Saccharomyces cerevisiae by using 'Ribofilio', a novel software tool that relies on a high sensitive strategy to estimate the ribosome drop-off rate from ribosome profiling data. Our results show that ribosome drop-off events occur at a significant rate also when S. cerevisiae is cultured in standard conditions. In this context, we also identified a correlation between the ribosome drop-off rate and the genes length: the longer the gene, the lower the drop-off rate.

Optimizing in vitro expression balance of central dogma-related genes using parallel reaction monitoring

The creation of a self-replicating synthetic cell is an essential to understand life self-replication. One method to create self-replicating artificial cells is to reconstitute the self-replication system of living organisms in vitro. In a living cell, self-replication is achieved via a system called the autonomous central dogma, a system in which central dogma-related factors are autonomously synthesized and genome replication, transcription, and translation are driven by nascent factors. Various studies to reconstitute some processes of the autonomous central dogma in vitro have been conducted. However, in vitro reconstitution of the entire autonomous central dogma system is difficult as it requires balanced expression of several related genes. Therefore, we developed a method to simultaneously quantify and optimize the in vitro expression balance of multiple genes. First, we developed a quantitative mass spectrometry method targeting genome replication-related proteins as a model of central dogma-related factors and acquired in vitro expression profiles of these genes. Additionally, we demonstrated that the in vitro expression balance of these genes can be easily optimized by adjusting the input gene ratio based on the data obtained by the developed method. This study facilitated the easy optimization of the in vitro expression balance of multiple genes. Therefore, extending the scope of this method to other central dogma-related factors will accelerate attempts of self-replicating synthetic cells creation.

A library of reporters of the global regulators of gene expression in Escherichia coli

The topology of the transcription factor network (TFN) of Escherichia coli is far from uniform, with 22 global regulator (GR) proteins controlling one-third of all genes. So far, their production rates cannot be tracked by comparable fluorescent proteins. We developed a library of fluorescent reporters for 16 GRs for this purpose. Each consists of a single-copy plasmid coding for green fluorescent protein (GFP) fused to the full-length copy of the native promoter. We tracked their activity in exponential and stationary growth, as well as under weak and strong stresses. We show that the reporters have high sensitivity and specificity to all stresses tested and detect single-cell variability in transcription rates. Given the influence of GRs on the TFN, we expect that the new library will contribute to dissecting global transcriptional stress-response programs of E. coli. Moreover, the library can be invaluable in bioindustrial applications that tune those programs to, instead of cell growth, favor productivity while reducing energy consumption.IMPORTANCECells contain thousands of genes. Many genes are involved in the control of cellular activities. Some activities require a few hundred genes to run largely synchronous transcriptional programs. To achieve this, cells have evolved global regulator (GR) proteins that can influence hundreds of genes simultaneously. We have engineered a library of Escherichia coli strains to track the levels over time of these, phenotypically critical, GRs. Each strain has a single-copy plasmid coding for a fast-maturing green fluorescent protein whose transcription is controlled by a copy of the natural GR promoter. By allowing the tracking of GR levels, with sensitivity and specificity, this library should become of wide use in scientific research on bacterial gene expression (from molecular to synthetic biology) and, later, be used in applications in therapeutics and bioindustries.

tRNA epitranscriptome determines pathogenicity of the opportunistic pathogen Pseudomonas aeruginosa

The success of bacterial pathogens depends on the coordinated expression of virulence determinants. Regulatory circuits that drive pathogenesis are complex, multilayered, and incompletely understood. Here, we reveal that alterations in tRNA modifications define pathogenic phenotypes in the opportunistic pathogen Pseudomonas aeruginosa. We demonstrate that the enzymatic activity of GidA leads to the introduction of a carboxymethylaminomethyl modification in selected tRNAs. Modifications at the wobble uridine base (cmnm5U34) of the anticodon drives translation of transcripts containing rare codons. Specifically, in P. aeruginosa the presence of GidA-dependent tRNA modifications modulates expression of genes encoding virulence regulators, leading to a cellular proteomic shift toward pathogenic and well-adapted physiological states. Our approach of profiling the consequences of chemical tRNA modifications is general in concept. It provides a paradigm of how environmentally driven tRNA modifications govern gene expression programs and regulate phenotypic outcomes responsible for bacterial adaption to challenging habitats prevailing in the host niche.

Decomposing bulk signals to reveal hidden information in processive enzyme reactions: A case study in mRNA translation

Processive enzymes like polymerases or ribosomes are often studied in bulk experiments by monitoring time-dependent signals, such as fluorescence time traces. However, due to biomolecular process stochasticity, ensemble signals may lack the distinct features of single-molecule signals. Here, we demonstrate that, under certain conditions, bulk signals from processive reactions can be decomposed to unveil hidden information about individual reaction steps. Using mRNA translation as a case study, we show that decomposing a noisy ensemble signal generated by the translation of mRNAs with more than a few codons is an ill-posed problem, addressable through Tikhonov regularization. We apply our method to the fluorescence signatures of in-vitro translated LepB mRNA and determine codon-position dependent translation rates and corresponding state-specific fluorescence intensities. We find a significant change in fluorescence intensity after the fourth and the fifth peptide bond formation, and show that both codon position and encoded amino acid have an effect on the elongation rate. This demonstrates that our approach enhances the information content extracted from bulk experiments, thereby expanding the range of these time- and cost-efficient methods.

Ribosome profiling reveals the fine-tuned response of Escherichia coli to mild and severe acid stress

IMPORTANCE

Bacteria react very differently to survive in acidic environments, such as the human gastrointestinal tract. Escherichia coli is one of the extremely acid-resistant bacteria and has a variety of acid-defense mechanisms. Here, we provide the first genome-wide overview of the adaptations of E. coli K-12 to mild and severe acid stress at both the transcriptional and translational levels. Using ribosome profiling and RNA sequencing, we uncover novel adaptations to different degrees of acidity, including previously hidden stress-induced small proteins and novel key transcription factors for acid defense, and report mRNAs with pH-dependent differential translation efficiency. In addition, we distinguish between acid-specific adaptations and general stress response mechanisms using denoising autoencoders. This workflow represents a powerful approach that takes advantage of next-generation sequencing techniques and machine learning to systematically analyze bacterial stress responses.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

Physical modeling of ribosomes along messenger RNA: Estimating kinetic parameters from ribosome profiling experiments using a ballistic model

Gene expression is the synthesis of proteins from the information encoded on DNA. One of the two main steps of gene expression is the translation of messenger RNA (mRNA) into polypeptide sequences of amino acids. Here, by taking into account mRNA degradation, we model the motion of ribosomes along mRNA with a ballistic model where particles advance along a filament without excluded volume interactions. Unidirectional models of transport have previously been used to fit the average density of ribosomes obtained by the experimental ribo-sequencing (Ribo-seq) technique in order to obtain the kinetic rates. The degradation rate is not, however, accounted for and experimental data from different experiments are needed to have enough parameters for the fit. Here, we propose an entirely novel experimental setup and theoretical framework consisting in splitting the mRNAs into categories depending on the number of ribosomes from one to four. We solve analytically the ballistic model for a fixed number of ribosomes per mRNA, study the different regimes of degradation, and propose a criterion for the quality of the inverse fit. The proposed method provides a high sensitivity to the mRNA degradation rate. The additional equations coming from using the monosome (single ribosome) and polysome (arbitrary number) ribo-seq profiles enable us to determine all the kinetic rates in terms of the experimentally accessible mRNA degradation rate.

Modeling mRNA Translation With Ribosome Abortions

We derive a deterministic mathematical model for the flow of ribosomes along a mRNA called the ribosome flow model with extended objects and abortions (RFMEOA). This model incorporates important cellular features such as every ribosome covers several codons and they may detach from various regions along the track due to more realistic biological situations including phenomena of ribosome-ribosome collisions. We prove that the ribosome density profile along the mRNA in the RFMEOA and in particular, the protein production rate converge to a unique steady-state. Simulations of the RFMEOA demonstrate a surprising result that an increase in the initiation rate may sometimes lead to a decrease in the production rate. We believe that this model could be helpful to provide insight into the effects of premature termination on the protein expression and be useful for understanding and re-engineering the translation process.

A well-characterized polycistronic-like gene expression system in yeast

Efficient expression of multiple genes is critical to yeast metabolic engineering for the bioproduction of bulk and fine chemicals. A yeast polycistronic expression system is of particular interest because one promoter can drive the expression of multiple genes. 2A viral peptides enable the cotranslation of multiple proteins from a single mRNA by ribosomal skipping. However, the wide adaptation of 2A viral peptides for polycistronic-like gene expression in yeast awaits in-depth characterizations. Additionally, a one-step assembly of such a polycistronic-like system is highly desirable. To this end, we have developed a modular cloning (MoClo) compatible 2A peptide-based polycistronic-like system capable of expressing multiple genes from a single promoter in yeast. Characterizing the bi-, tri-, and quad-cistronic expression of fluorescent proteins showed high cleavage efficiencies of three 2A peptides: E2A from equine rhinitis B virus, P2A from porcine teschovirus-1, and O2A from Operophtera brumata cypovirus-18. Applying the polycistronic-like system to produce geraniol, a valuable industrial compound, resulted in comparable or higher titers than using conventional monocistronic constructs. In summary, this highly-characterized polycistronic-like gene expression system is another tool to facilitate multigene expression for metabolic engineering in yeast.

A Neural Networks Approach for the Analysis of Reproducible Ribo–Seq Profiles

In recent years, the Ribosome profiling technique (Ribo–seq) has emerged as a powerful method for globally monitoring the translation process in vivo at single nucleotide resolution. Based on deep sequencing of mRNA fragments, Ribo–seq allows to obtain profiles that reflect the time spent by ribosomes in translating each part of an open reading frame. Unfortunately, the profiles produced by this method can vary significantly in different experimental setups, being characterized by a poor reproducibility. To address this problem, we have employed a statistical method for the identification of highly reproducible Ribo–seq profiles, which was tested on a set of E. coli genes. State-of-the-art artificial neural network models have been used to validate the quality of the produced sequences. Moreover, new insights into the dynamics of ribosome translation have been provided through a statistical analysis on the obtained sequences.

Dynamics and growth rate implications of ribosomes and mRNAs interaction in E. coli

Understanding how cells grow and adapt under various nutrient conditions is pivotal in the study of biological stoichiometry. Recent studies provide empirical evidence that cells use multiple strategies to maintain an optimal protein production rate under different nutrient conditions. Mathematical models can provide a solid theoretical foundation that can explain experimental observations and generate testable hypotheses to further our understanding of the growth process. In this study, we generalize a modeling framework that centers on the translation process and study its asymptotic behaviors to validate algebraic manipulations involving the steady states. Using experimental results on the growth of E. coli under C-, N-, and P-limited environments, we simulate the expected quantitative measurements to show the feasibility of using the model to explain empirical evidence. Our results support the findings that cells employ multiple strategies to maintain a similar protein production rate across different nutrient limitations. Moreover, we find that the previous study underestimates the significance of certain biological rates, such as the binding rate of ribosomes to mRNA and the transition rate between different ribosomal stages. Furthermore, our simulation shows that the strategies used by cells under C- and P-limitations result in a faster overall growth dynamics than under N-limitation. In conclusion, the general modeling framework provides a valuable platform to study cell growth under different nutrient supply conditions, which also allows straightforward extensions to the coupling of transcription, translation, and energetics to deepen our understanding of the growth process.

Modeling transport of extended interacting objects with drop-off phenomenon

We study a deterministic framework for important cellular transport phenomena involving a large number of interacting molecules called the excluded flow of extended interacting objects with drop-off effect (EFEIOD). This model incorporates many realistic features of biological transport process including the length of biological “particles” and the fact that they can detach along the biological ‘tracks’. The flow between the consecutive sites is unidirectional and is described by a “soft” simple exclusion principle and by repelling or attracting forces between neighboring particles. We show that the model admits a unique steady-state. Furthermore, if the parameters are periodic with common period T, then the steady-state profile converge to a unique periodic solution of period T. Simulations of the EFEIOD demonstrate several non-trivial effects of the interactions on the system steady-state profile. For example, detachment rates may help in increasing the steady-state flow by alleviating traffic jams that can exist due to several reasons like bottleneck rate or interactive forces between the particles. We also analyze the special case of our model, when there are no forces exerted by neighboring particles, and called it as the ribosome flow model of extended objects with drop-off effect (RFMEOD), and study the sensitivity of its steady-state to variations in the parameters.

Large-scale mRNA translation and the intricate effects of competition for the finite pool of ribosomes

We present a new theoretical framework for large-scale mRNA translation using a network of models called the ribosome flow model with Langmuir kinetics (RFMLK), interconnected via a pool of free ribosomes. The input to each RFMLK depends on the pool density, and it affects the initiation rate and potentially also the internal ribosome entry rates along each RFMLK. Ribosomes that detach from an RFMLK owing to termination or premature drop-off are fed back into the pool. We prove that the network always converges to a steady state, and study its sensitivity to variations in the parameters. For example, we show that if the drop-off rate at some site in some RFMLK is increased then the pool density increases and consequently the steady-state production rate in all the other RFMLKs increases. Surprisingly, we also show that modifying a parameter of a certain RFMLK can lead to arbitrary effects on the densities along the modified RFMLK, depending on the parameters in the entire network. We conclude that the competition for shared resources generates an indirect and intricate web of mutual effects between the mRNA molecules that must be accounted for in any analysis of translation.

Modeling the ribosomal small subunit dynamic in Saccharomyces cerevisiae based on TCP-seq data

Translation Complex Profile Sequencing (TCP-seq), a protocol that was developed and implemented on Saccharomyces cerevisiae, provides the footprints of the small subunit (SSU) of the ribosome (with additional factors) across the entire transcriptome of the analyzed organism. In this study, based on the TCP-seq data, we developed for the first-time a predictive model of the SSU density and analyzed the effect of transcript features on the dynamics of the SSU scan in the 5′UTR. Among others, our model is based on novel tools for detecting complex statistical relations tailored to TCP-seq. We quantitatively estimated the effect of several important features, including the context of the upstream AUG, the upstream ORF length and the mRNA folding strength. Specifically, we suggest that around 50% of the variance related to the read counts (RC) distribution near a start codon can be attributed to the AUG context score. We provide the first large scale direct quantitative evidence that shows that indeed AUG context affects the small sub-unit movement. In addition, we suggest that strong folding may cause the detachment of the SSU from the mRNA. We also identified a number of novel sequence motifs that can affect the SSU scan; some of these motifs affect transcription factors and RNA binding proteins. The results presented in this study provide a better understanding of the biophysical aspects related to the SSU scan along the 5′UTR and of translation initiation in S. cerevisiae, a fundamental step toward a comprehensive modeling of initiation.

Phosphorylation of ribosomal protein S6 differentially affects mRNA translation based on ORF length

Phosphorylation of Ribosomal Protein S6 (RPS6) was the first post-translational modification of the ribosome to be identified and is a commonly-used readout for mTORC1 activity. Although the cellular and organismal functions of RPS6 phosphorylation are known, the molecular consequences of RPS6 phosphorylation on translation are less well understood. Here we use selective ribosome footprinting to analyze the location of ribosomes containing phosphorylated RPS6 on endogenous mRNAs in cells. We find that RPS6 becomes progressively dephosphorylated on ribosomes as they translate an mRNA. As a consequence, average RPS6 phosphorylation is higher on mRNAs with short coding sequences (CDSs) compared to mRNAs with long CDSs. We test whether RPS6 phosphorylation differentially affects mRNA translation based on CDS length by genetic removal of RPS6 phosphorylation. We find that RPS6 phosphorylation promotes translation of mRNAs with short CDSs more strongly than mRNAs with long CDSs. Interestingly, RPS6 phosphorylation does not promote translation of mRNAs with 5′ TOP motifs despite their short CDS lengths, suggesting they are translated via a different mode. In sum this provides a dynamic view of RPS6 phosphorylation on ribosomes as they translate mRNAs and the functional consequence on translation.

Comparative ribosome profiling reveals distinct translational landscapes of salt-sensitive and -tolerant rice

BACKGROUND

Soil salinization represents a serious threat to global rice production. Although significant research has been conducted to understand salt stress at the genomic, transcriptomic and proteomic levels, few studies have focused on the translatomic responses to this stress. Recent studies have suggested that transcriptional and translational responses to salt stress can often operate independently.

RESULTS

We sequenced RNA and ribosome-protected fragments (RPFs) from the salt-sensitive rice (O. sativa L.) cultivar 'Nipponbare' (NB) and the salt-tolerant cultivar 'Sea Rice 86' (SR86) under normal and salt stress conditions. A large discordance between salt-induced transcriptomic and translatomic alterations was found in both cultivars, with more translationally regulated genes being observed in SR86 in comparison to NB. A biased ribosome occupancy, wherein RPF depth gradually increased from the 5' ends to the 3' ends of coding regions, was revealed in NB and SR86. This pattern was strengthened by salt stress, particularly in SR86. On the contrary, the strength of ribosome stalling was accelerated in salt-stressed NB but decreased in SR86.

CONCLUSIONS

This study revealed that translational reprogramming represents an important layer of salt stress responses in rice, and the salt-tolerant cultivar SR86 adopts a more flexible translationally adaptive strategy to cope with salt stress compared to the salt susceptible cultivar NB. The differences in translational dynamics between NB and SR86 may derive from their differing levels of ribosome stalling under salt stress.

Selection for Cheaper Amino Acids Drives Nucleotide Usage at the Start of Translation in Eukaryotic Genes

Coding regions have complex interactions among multiple selective forces, which are manifested as biases in nucleotide composition. Previous studies have revealed a decreasing GC gradient from the 5′-end to 3′-end of coding regions in various organisms. We confirmed that this gradient is universal in eukaryotic genes, but the decrease only starts from the ∼ 25th codon. This trend is mostly found in nonsynonymous (ns) sites at which the GC gradient is universal across the eukaryotic genome. Increased GC contents at ns sites result in cheaper amino acids, indicating a universal selection for energy efficiency toward the N-termini of encoded proteins. Within a genome, the decreasing GC gradient is intensified from lowly to highly expressed genes (more and more protein products), further supporting this hypothesis. This reveals a conserved selective constraint for cheaper amino acids at the translation start that drives the increased GC contents at ns sites. Elevated GC contents can facilitate transcription but result in a more stable local secondary structure around the start codon and subsequently impede translation initiation. Conversely, the GC gradients at four-fold and two-fold synonymous sites vary across species. They could decrease or increase, suggesting different constraints acting at the GC contents of different codon sites in different species. This study reveals that the overall GC contents at the translation start are consequences of complex interactions among several major biological processes that shape the nucleotide sequences, especially efficient energy usage.

Protein Export via the Type III Secretion System of the Bacterial Flagellum

The bacterial flagellum and the related virulence-associated injectisome system of pathogenic bacteria utilize a type III secretion system (T3SS) to export substrate proteins across the inner membrane in a proton motive force-dependent manner. The T3SS is composed of an export gate (FliPQR/FlhA/FlhB) located in the flagellar basal body and an associated soluble ATPase complex in the cytoplasm (FliHIJ). Here, we summarise recent insights into the structure, assembly and protein secretion mechanisms of the T3SS with a focus on energy transduction and protein transport across the cytoplasmic membrane.

In vitro synthesis of 32 translation-factor proteins from a single template reveals impaired ribosomal processivity

The Protein synthesis Using Recombinant Elements (PURE) system enables transcription and translation of a DNA template from purified components. Therefore, the PURE system-catalyzed generation of RNAs and proteins constituting the PURE system itself represents a major challenge toward a self-replicating minimal cell. In this work, we show that all translation factors (except elongation factor Tu) and 20 aminoacyl-tRNA synthetases can be expressed in the PURE system from a single plasmid encoding 32 proteins in 30 cistrons. Cell-free synthesis of all 32 proteins is confirmed by quantitative mass spectrometry-based proteomic analysis using isotopically labeled amino acids. We find that a significant fraction of the gene products consists of proteins missing their C-terminal ends. The per-codon processivity loss that we measure lies between 1.3 × 10^-3 and 13.2 × 10^-3, depending on the expression conditions, the version of the PURE system, and the coding sequence. These values are 5 to 50 times higher than those measured in vivo in E. coli. With such an impaired processivity, a considerable fraction of the biosynthesis capacity of the PURE system is wasted, posing an unforeseen challenge toward the development of a self-regenerating PURE system.

Algorithms for ribosome traffic engineering and their potential in improving host cells' titer and growth rate

mRNA translation is a fundamental cellular process consuming most of the intracellular energy; thus, it is under extensive evolutionary selection for optimization, and its efficiency can affect the host's growth rate. We describe a generic approach for improving the growth rate (fitness) of any organism by introducing synonymous mutations based on comprehensive computational models. The algorithms introduce silent mutations that may improve the allocation of ribosomes in the cells via the decreasing of their traffic jams during translation respectively. As a result, resources availability in the cell changes leading to improved growth-rate. We demonstrate experimentally the implementation of the method on Saccharomyces cerevisiae: we show that by introducing a few mutations in two computationally selected genes the mutant's titer increased. Our approach can be employed for improving the growth rate of any organism providing the existence of data for inferring models, and with the relevant genomic engineering tools; thus, it is expected to be extremely useful in biotechnology, medicine, and agriculture.

Inferring efficiency of translation initiation and elongation from ribosome profiling

One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.

RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution

Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26–34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.

Computational discovery and modeling of novel gene expression rules encoded in the mRNA

The transcript is populated with numerous overlapping codes that regulate all steps of gene expression. Deciphering these codes is very challenging due to the large number of variables involved, the non-modular nature of the codes, biases and limitations in current experimental approaches, our limited knowledge in gene expression regulation across the tree of life, and other factors. In recent years, it has been shown that computational modeling and algorithms can significantly accelerate the discovery of novel gene expression codes. Here, we briefly summarize the latest developments and different approaches in the field.

Dynamics of ribosomes in mRNA translation under steady- and nonsteady-state conditions

Recent advances in DNA sequencing and fluorescence imaging have made it possible to monitor the dynamics of ribosomes actively engaged in messenger RNA (mRNA) translation. Here, we model these experiments within the inhomogeneous totally asymmetric simple exclusion process (TASEP) using realistic kinetic parameters. In particular, we present analytic expressions to describe the following three cases: (a) translation of a newly transcribed mRNA, (b) translation in the steady state and, specifically, the dynamics of individual (tagged) ribosomes, and (c) runoff translation after inhibition of translation initiation. In cases (b) and (c) we develop an effective medium approximation to describe many-ribosome dynamics in terms of a single tagged ribosome in an effective medium. The predictions are in good agreement with stochastic simulations.

RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data

Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers the user an HTML page to scan own data regarding the following aspects: periodicity, ligation and digestion of footprints; reproducibility and batch effects of replicates; drug-related artifacts; unbiased codon enrichment including variability between mRNAs, for A, P and E sites; mining of some causal or confounding factors. We expect our pipeline to allow an optimal use of the wealth of information provided by ribosome profiling experiments.

A dual role of the ribosome-bound chaperones RAC/Ssb in maintaining the fidelity of translation termination

The yeast ribosome-associated complex RAC and the Hsp70 homolog Ssb are anchored to the ribosome and together act as chaperones for the folding and co-translational assembly of nascent polypeptides. In addition, the RAC/Ssb system plays a crucial role in maintaining the fidelity of translation termination; however, the latter function is poorly understood. Here we show that the RAC/Ssb system promotes the fidelity of translation termination via two distinct mechanisms. First, via direct contacts with the ribosome and the nascent chain, RAC/Ssb facilitates the translation of stalling-prone poly-AAG/A sequences encoding for polylysine segments. Impairment of this function leads to enhanced ribosome stalling and to premature nascent polypeptide release at AAG/A codons. Second, RAC/Ssb is required for the assembly of fully functional ribosomes. When RAC/Ssb is absent, ribosome biogenesis is hampered such that core ribosomal particles are structurally altered at the decoding and peptidyl transferase centers. As a result, ribosomes assembled in the absence of RAC/Ssb bind to the aminoglycoside paromomycin with high affinity (K_D = 76.6 nM) and display impaired discrimination between stop codons and sense codons. The combined data shed light on the multiple mechanisms by which the RAC/Ssb system promotes unimpeded biogenesis of newly synthesized polypeptides.

Power series method for solving TASEP-based models of mRNA translation

We develop a method for solving mathematical models of messenger RNA (mRNA) translation based on the totally asymmetric simple exclusion process (TASEP). Our main goal is to demonstrate that the method is versatile and applicable to realistic models of translation. To this end we consider the TASEP with codon-dependent elongation rates, premature termination due to ribosome drop-off and translation reinitiation due to circularisation of the mRNA. We apply the method to the model organism Saccharomyces cerevisiae under physiological conditions and find an excellent agreement with the results of stochastic simulations. Our findings suggest that the common view on translation as being rate-limited by initiation is oversimplistic. Instead we find theoretical evidence for ribosome interference and also theoretical support for the ramp hypothesis which argues that codons at the beginning of genes have slower elongation rates in order to reduce ribosome density and jamming.

Optimizing the dynamics of protein expression

Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences.

Dissecting the Contribution of Release Factor Interactions to Amber Stop Codon Reassignment Efficiencies of the Methanocaldococcus jannaschii Orthogonal Pair

Non-canonical amino acids (ncAAs) are finding increasing use in basic biochemical studies and biomedical applications. The efficiency of ncAA incorporation is highly variable, as a result of competing system composition and codon context effects. The relative quantitative contribution of the multiple factors affecting incorporation efficiency are largely unknown. This manuscript describes the use of green fluorescent protein (GFP) reporters to quantify the efficiency of amber codon reassignment using the Methanocaldococcus jannaschii orthogonal pair system, commonly employed for ncAA incorporation, and quantify the contribution of release factor 1 (RF1) to the overall efficiency of amino acid incorporation. The efficiencies of amber codon reassignments were quantified at eight positions in GFP and evaluated in multiple combinations. The quantitative contribution of RF1 competition to reassignment efficiency was evaluated through comparisons of amber codon suppression efficiencies in normal and genomically recoded Escherichia coli strains. Measured amber stop codon reassignment efficiencies for eight single stop codon GFP variants ranged from 51 to 117% in E. coli DH10B and 76 to 104% in the RF1 deleted E. coli C321.ΔA.exp. Evaluation of efficiency changes in specific sequence contexts in the presence and absence of RF1 suggested that RF1 specifically interacts with +4 Cs and that the RF1 interactions contributed approximately half of the observed sequence context-dependent variation in measured reassignment efficiency. Evaluation of multisite suppression efficiencies suggests that increasing demand for translation system components limits multisite incorporation in cells with competing RF1.

Polyprotein strategy for stoichiometric assembly of nitrogen fixation components for synthetic biology

The requirement of maintaining balanced expression of a large number of gene products represents a major challenge to the engineering of nitrogen fixation in cereal crops, necessitating reiterative combinatorial assembly cycles to optimize monocistronic gene expression. In this study, we have explored a “fuse-and-cleave” virus-derived polyprotein strategy to reduce gene numbers and achieve balanced expression of protein components required for nitrogenase biosynthesis and activity. After testing and regrouping assemblies on the basis of expression profiles, cleavage patterns, and activity, 14 essential genes were selectively assembled into 5 giant genes that enable growth on dinitrogen. This strategy has potential advantages, not only for transferring nitrogen fixation to plants, but also for the engineering of other complex systems of profound agronomic and ecological importance.

Re-engineering of complex biological systems (CBS) is an important goal for applications in synthetic biology. Efforts have been made to simplify CBS by refactoring a large number of genes with rearranged polycistrons and synthetic regulatory circuits. Here, a posttranslational protein-splicing strategy derived from RNA viruses was exploited to minimize gene numbers of the classic nitrogenase system, where the expression stoichiometry is particularly important. Operon-based nif genes from Klebsiella oxytoca were regrouped into giant genes either by fusing genes together or by expressing polyproteins that are subsequently cleaved with Tobacco Etch Virus protease. After several rounds of selection based on protein expression levels and tolerance toward a remnant C-terminal ENLYFQ-tail, a system with only five giant genes showed optimal nitrogenase activity and supported diazotrophic growth of Escherichia coli. This study provides an approach for efficient translation from an operon-based system into a polyprotein-based assembly that has the potential for portable and stoichiometric expression of the complex nitrogenase system in eukaryotic organisms.

TASEP modelling provides a parsimonious explanation for the ability of a single uORF to derepress translation during the integrated stress response

Translation initiation is the rate-limiting step of protein synthesis that is downregulated during the Integrated Stress Response (ISR). Previously, we demonstrated that most human mRNAs that are resistant to this inhibition possess translated upstream open reading frames (uORFs), and that in some cases a single uORF is sufficient for the resistance. Here we developed a computational model of Initiation Complexes Interference with Elongating Ribosomes (ICIER) to gain insight into the mechanism. We explored the relationship between the flux of scanning ribosomes upstream and downstream of a single uORF depending on uORF features. Paradoxically, our analysis predicts that reducing ribosome flux upstream of certain uORFs increases initiation downstream. The model supports the derepression of downstream translation as a general mechanism of uORF-mediated stress resistance. It predicts that stress resistance can be achieved with long slowly decoded uORFs that do not favor translation reinitiation and that start with initiators of low leakiness.

The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation

Previous studies have shown that translation elongation is regulated by multiple factors, but the observed heterogeneity remains only partially explained. To dissect quantitatively the different determinants of elongation speed, we use probabilistic modeling to estimate initiation and local elongation rates from ribosome profiling data. This model-based approach allows us to quantify the extent of interference between ribosomes on the same transcript. We show that neither interference nor the distribution of slow codons is sufficient to explain the observed heterogeneity. Instead, we find that electrostatic interactions between the ribosomal exit tunnel and specific parts of the nascent polypeptide govern the elongation rate variation as the polypeptide makes its initial pass through the tunnel. Once the N-terminus has escaped the tunnel, the hydropathy of the nascent polypeptide within the ribosome plays a major role in modulating the speed. We show that our results are consistent with the biophysical properties of the tunnel.

Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights

Protein synthesis rates are determined, at the translational level, by properties of the transcript’s sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. According to our results, the proximity of the 3′ end to the ribosomal recruitment site of the mRNA could induce a feedback in the translation process that would favour the recycling of ribosomes. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

A deterministic mathematical model for bidirectional excluded flow with Langmuir kinetics

In many important cellular processes, including mRNA translation, gene transcription, phosphotransfer, and intracellular transport, biological "particles" move along some kind of "tracks". The motion of these particles can be modeled as a one-dimensional movement along an ordered sequence of sites. The biological particles (e.g., ribosomes or RNAPs) have volume and cannot surpass one another. In some cases, there is a preferred direction of movement along the track, but in general the movement may be bidirectional, and furthermore the particles may attach or detach from various regions along the tracks. We derive a new deterministic mathematical model for such transport phenomena that may be interpreted as a dynamic mean-field approximation of an important model from mechanical statistics called the asymmetric simple exclusion process (ASEP) with Langmuir kinetics. Using tools from the theory of monotone dynamical systems and contraction theory we show that the model admits a unique steady-state, and that every solution converges to this steady-state. Furthermore, we show that the model entrains (or phase locks) to periodic excitations in any of its forward, backward, attachment, or detachment rates. We demonstrate an application of this phenomenological transport model for analyzing ribosome drop off in mRNA translation.

Systematic comparison of 2A peptides for cloning multi-genes in a polycistronic vector

Cloning of multiple genes in a single vector has greatly facilitated both basic and translational studies that require co-expression of multiple factors or multi-units of complex protein. Many strategies have been adopted, among which 2A “self-cleaving” peptides have garnered increased interest for their polycistronic nature, small size and high “cleavage” efficiency. However, broad application of 2 A peptides is limited by the lack of systematic comparison of different 2As alone or in combination. Here we characterized the effect of varying gene position and 2As on the expression of proteins encoded in bi-, tri-, or quad-cistronic constructs. Using direct cardiac reprogramming as an example, we further determined the effect of varied 2As on the efficiency of fluorescent cell labeling and cell fate conversion. We found that the expression of fluorophores decreased as it was moved towards the end of the construct while reprogramming was most efficient with the fluorophore at the second position. Moreover, quad-cistronic TPE2A constructs resulted in more efficient reprogramming than 3P2A or PTE2A constructs. We expect that the bi-, tri-, and quad-cistronic vectors constructed here and our results on protein expression ratios from different 2A constructs could serve to guide future utilization of 2A peptides in basic research and clinical applications.

Kinetic modeling predicts a stimulatory role for ribosome collisions at elongation stall sites in bacteria

Ribosome stalling on mRNAs can decrease protein expression. To decipher ribosome kinetics at stall sites, we induced ribosome stalling at specific codons by starving the bacterium Escherichia coli for the cognate amino acid. We measured protein synthesis rates from a reporter library of over 100 variants that encoded systematic perturbations of translation initiation rate, the number of stall sites, and the distance between stall sites. Our measurements are quantitatively inconsistent with two widely-used kinetic models for stalled ribosomes: ribosome traffic jams that block initiation, and abortive (premature) termination of stalled ribosomes. Rather, our measurements support a model in which collision with a trailing ribosome causes abortive termination of the stalled ribosome. In our computational analysis, ribosome collisions selectively stimulate abortive termination without fine-tuning of kinetic rate parameters at ribosome stall sites. We propose that ribosome collisions serve as a robust timer for translational quality control pathways to recognize stalled ribosomes.

Novel mRNA-specific effects of ribosome drop-off on translation rate and polysome profile

The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5' to the 3' end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.

Bacterial flagella grow through an injection-diffusion mechanism

The bacterial flagellum is a self-assembling nanomachine. The external flagellar filament, several times longer than a bacterial cell body, is made of a few tens of thousands subunits of a single protein: flagellin. A fundamental problem concerns the molecular mechanism of how the flagellum grows outside the cell, where no discernible energy source is available. Here, we monitored the dynamic assembly of individual flagella using in situ labelling and real-time immunostaining of elongating flagellar filaments. We report that the rate of flagellum growth, initially ∼1,700 amino acids per second, decreases with length and that the previously proposed chain mechanism does not contribute to the filament elongation dynamics. Inhibition of the proton motive force-dependent export apparatus revealed a major contribution of substrate injection in driving filament elongation. The combination of experimental and mathematical evidence demonstrates that a simple, injection-diffusion mechanism controls bacterial flagella growth outside the cell.

DOI:http://dx.doi.org/10.7554/eLife.23136.001

Most bacteria are able to move in a directed manner towards nutrients or other locations of interest. Many move by rotating long tail-like filaments called flagella that stick out from the cell. The flagellum is a remarkably complex nanomachine. It is several times longer than the main body of the bacterial cell body and its external filament is made of thousands of building blocks of a single protein called flagellin. This protein is made inside the cell and a structure at the base of the flagellum known as a type III secretion system uses chemical energy to pump it out of the cell so that it can be incorporated into the growing flagellum. The exported building blocks travel through a narrow channel within the flagellum and self-assemble at the tip.

It has been a mystery for several decades how bacteria manage to assemble the building blocks of flagella outside of the cell, where no discernible energy source is available. Renault et al. used mathematical modeling, biochemical and microscopy techniques to observe how the flagella of a bacterium called Salmonella enterica assemble in real time. The experiments demonstrate that simple biophysical principles regulate the assembly of the flagellum. The building blocks are pumped into the channel of the flagellum by the type III secretion system and then diffuse to the tip of the filament. Accordingly, the longer the flagellum gets, the slower it grows. This molecular mechanism also explains why the growth of bacterial flagella will eventually stop even without any other control mechanisms in place.

Further work will be needed to understand how the type III secretion system harnesses chemical energy to drive the movement of flagellin out of the cell into the growing flagellum. A molecular understanding of these processes will aid the design of new antibiotics targeted against type III secretion systems.

DOI:http://dx.doi.org/10.7554/eLife.23136.002

Reduction of translating ribosomes enables Escherichia coli to maintain elongation rates during slow growth

Bacteria growing under different conditions experience a broad range of demand on the rate of protein synthesis, which profoundly affects cellular resource allocation. During fast growth, protein synthesis has long been known to be modulated by adjusting the ribosome content, with the vast majority of ribosomes engaged at a near-maximal rate of elongation. Here, we systematically characterize protein synthesis by Escherichia coli, focusing on slow-growth conditions. We establish that the translational elongation rate decreases as growth slows, exhibiting a Michaelis-Menten dependence on the abundance of the cellular translational apparatus. However, an appreciable elongation rate is maintained even towards zero growth, including the stationary phase. This maintenance, critical for timely protein synthesis in harsh environments, is accompanied by a drastic reduction in the fraction of active ribosomes. Interestingly, well-known antibiotics such as chloramphenicol also cause a substantial reduction in the pool of active ribosomes, instead of slowing down translational elongation as commonly thought.

The AAA+ FtsH Protease Degrades an ssrA-Tagged Model Protein in the Inner Membrane of Escherichia coli

In eubacteria, the tmRNA system frees ribosomes that stall during protein synthesis and adds an ssrA tag to the incompletely translated polypeptide to target it for degradation. The AAA+ ClpXP protease degrades most ssrA-tagged proteins in the Escherichia coli cytoplasm and was recently shown to degrade an ssrA-tagged protein in the inner membrane. However, we find that tmRNA-mediated tagging of E. coli ProW_1-182, a different inner-membrane protein, results in degradation by the membrane-tethered AAA+ FtsH protease. ClpXP played no role in the degradation of ProW_1-182 in vivo. These studies suggest that a complex distribution of proteolytic labor maintains protein quality control in the inner membrane.

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.