The Characterization of Separated α and β Chain Polyribosomes in Rabbit Reticulocytes

Analysis of Translation Elongation Dynamics in the Context of an Escherichia coli Cell

Understanding the mechanisms behind translation and its rate-limiting steps is crucial for both the development of drug targets and improvement of heterologous protein production with many biotechnological applications, such as in pharmaceutical and biofuel industries. Despite many advances in the knowledge of the ribosome structure and function, there is still much discussion around the determinants of translation elongation with experiments and computational studies pointing in different directions. Here, we use a stochastic framework to simulate the process of translation in the context of an Escherichia coli cell by gathering the available biochemical data into a ribosome kinetics description. Our results from the study of translation in E. coli at different growth rates contradict the increase of mean elongation rate with growth rate established in the literature. We show that both the level of tRNA competition and the type of cognate binding interaction contribute to the modulation of elongation rate, and that optimization of a heterologous transcript for faster elongation rate is achieved by combining the two. We derive an equation that can accurately predict codon elongation rates based on the abundances of free tRNA in the cell, and can be used to assist transcript design. Finally, we show that non-cognate tRNA-ribosome binding has an important weight in translation, and plays an active role in the modulation of mean elongation rate as shown by our amino-acid starvation/surplus studies.

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

How molecular competition influences fluxes in gene expression networks

Often, in living cells different molecular species compete for binding to the same molecular target. Typical examples are the competition of genes for the transcription machinery or the competition of mRNAs for the translation machinery. Here we show that such systems have specific regulatory features and how they can be analysed. We derive a theory for molecular competition in parallel reaction networks. Analytical expressions for the response of network fluxes to changes in the total competitor and common target pools indicate the precise conditions for ultrasensitivity and intuitive rules for competitor strength. The calculations are based on measurable concentrations of the competitor-target complexes. We show that kinetic parameters, which are usually tedious to determine, are not required in the calculations. Given their simplicity, the obtained equations are easily applied to networks of any dimension. The new theory is illustrated for competing sigma factors in bacterial transcription and for a genome-wide network of yeast mRNAs competing for ribosomes. We conclude that molecular competition can drastically influence the network fluxes and lead to negative response coefficients and ultrasensitivity. Competitors that bind a large fraction of the target, like bacterial σ⁷⁰, tend to influence competing pathways strongly. The less a competitor is saturated by the target, the more sensitive it is to changes in the concentration of the target, as well as to other competitors. As a consequence, most of the mRNAs in yeast turn out to respond ultrasensitively to changes in ribosome concentration. Finally, applying the theory to a genome-wide dataset we observe that high and low response mRNAs exhibit distinct Gene Ontology profiles.

Effects of codon distributions and tRNA competition on protein translation

Translation is a central cellular process and the complexity of its mechanism necessitates mathematical frameworks to better understand system properties and make quantitative predictions. We have developed a gene sequence-specific mechanistic model for translation which accounts for all the elementary steps of translation elongation. Included in our model is the nonspecific binding of tRNAs to the ribosomal A site, and we find that the competitive, nonspecific binding of the tRNAs is the rate-limiting step in the elongation cycle for every codon. By introducing our model in terms of the Michaelis-Menten kinetic framework, we determine that these results are due to the tRNAs that do not recognize the ribosomal A site codon acting as competitive inhibitors to the tRNAs that do recognize the ribosomal A site codon. We present the results of a sensitivity analysis to determine the contribution of elongation cycle kinetic parameters of each codon on the overall translation rate, and observe that the translation rates of mRNAs are controlled by segments of rate-limiting codons that are sequence-specific. Along these lines, we find that the relative position of codons along the mRNA determines the optimal protein synthesis rate.

A model for protein translation: polysome self-organization leads to maximum protein synthesis rates

The genetic information in DNA is transcribed to mRNA and then translated to proteins, which form the building blocks of life. Translation, or protein synthesis, is hence a central cellular process. We have developed a gene-sequence-specific mechanistic model for the translation machinery, which accounts for all the elementary steps of the translation mechanism. We performed a sensitivity analysis to determine the effects of kinetic parameters and concentrations of the translational components on protein synthesis rate. Utilizing our mathematical framework and sensitivity analysis, we investigated the translational kinetic properties of a single mRNA species in Escherichia coli. We propose that translation rate at a given polysome size depends on the complex interplay between ribosomal occupancy of elongation phase intermediate states and ribosome distributions with respect to codon position along the length of the mRNA, and this interplay leads to polysome self-organization that drives translation rate to maximum levels.

Translational step inhibited in vivo by aflatoxin B1 in rat-liver polysomes

Aflatoxin B1 strongly inhibits protein synthesis in rat liver cells. We previously demonstrated that this inhibition could be divided into two steps: up to 5 h aflatoxin blocks protein synthesis directly and specifically at the polysome level; beyond 7 h protein synthesis inhibition appears chiefly as a consequence of transcription impairment due to drug action. This paper confirms the foregoing results and represents an attempt to localize the translational step inhibited in vivo by aflatoxin B1. We used the simulation study developed by Li, Kisilevsky, Wasan and Hammond, 1972 (Biochim. Biophys. Acta, 272, 451-462) to determine precisely the site inhibited in vivo after drug intoxication. This analysis is based on two parameters: the kinetics of polysome labeling to follow the nascent peptide synthesis, and the kinetics of supernatant labeling to follow the completed protein synthesis. Up to 5 h after dosing, aflatoxin specifically inhibits the elongation and/or termination steps during protein synthesis; after longer periods of time inhibition occurs essentially at the initiation step. When the intracellular concentration of aflatoxin is too high, particularly 2 h after dosing, each step of protein synthesis is blocked. Polypeptide synthesis by the postmitochondrial supernatants isolated from aflatoxin-treated animals is impaired in the same proportion as protein synthesis in vivo. The damage caused by aflatoxin is mostly observed on microsomes. However, purified polysomes isolated from aflatoxin-treated rats synthesize proteins in vitro to the same extent as those from controls. These results suggest that aflatoxin metabolite(s) are bound to polysomes with noncovalent bonds. These active metabolites are probably lost during polysome isolation procedures. Finally, relationships between protein metabolism and aflatoxin carcinogenesis are discussed.

Adult hemoglobin synthesis by reticulocytes from the human fetus at midtrimester

The synthesis of adult-type hemoglobin was measured in small samples of peripheral blood cells from 9- to 18-week human fetuses. Hemoglobin indistinguishable from hemoglobin A was identified by ion-exchange chromatography, electrophoresis at pH 8.6, tryptic peptide analysis, and the insensitivity of its synthesis to the action of O-methylthreonine. Synthesis of hemoglobin A accounted for 8 to 14 percent of total hemoglobin synthesis and was demonstrated in as little as 10 microliters of fetal blood. These studies provide sensitive methods for the detection of beta chain types in hemoglobin synthesized by the human fetus at midtrimester. If methods to obtain small quantities of fetal blood at midtrimester become available, these techniques should be applicable to the antenatal detection of sickle cell anemia and related hemoglobinopathies.

The control of haemoglobin synthesis: factors controlling the output of alpha and beta chains

Analysis of the effects of amino acid starvation in reticulocytes is comparatively simple compared with similar analysis in other tissues of whole organisms. This is mainly because of the absence of RNA synthesis in reticulocytes, but also because the bulk of the protein being synthesized is haemoglobin, a protein whose structure is completely known. The absence of RNA synthesis eliminates complications that would otherwise arise through RNA-mediated control mechanisms which in turn might mask the effects of amino acid starvation on the protein synthetic machinery in the cells (Munro, 1969). Consequently reticulocytes have been used to study the effect of amino acid starvation on the actual process of protein synthesis and assembly.

The control of haemoglobin synthesis: factors controlling the output of α and β chains

Analysis of the effects of amino acid starvation in reticulocytes is comparatively simple compared with similar analysis in other tissues of whole organisms. This is mainly because of the absence of RNA synthesis in reticulocytes, but also because the bulk of the protein being synthesized is haemoglobin, a protein whose structure is completely known. The absence of RNA synthesis eliminates complications that would otherwise arise through RNA-mediated control mechanisms which in turn might mask the effects of amino acid starvation on the protein synthetic machinery in the cells (Munro, 1969). Consequently reticulocytes have been used to study the effect of amino acid starvation on the actual process of protein synthesis and assembly.