Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

Abstract

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host.

Ribosome flow model with positive feedback

“…The simulations in the study of Reuveni et al [15] show that, for suitable parameter values, TASEP and the RFM lead to similar predictions. For example, the correlation between their predictions over the set of endogenous genes of Saccharomyces cerevisiae is 0.96.…”

“…Reuveni et al [15] recently introduced a deterministic model for translation called the ribosome flow model (RFM; figure 1). In the RFM, mRNA molecules are coarse-grained into a unidirectional chain of n sites of codons.…”

“…0, but are only able to bind if this site is not already occupied by another ribosome. In practice, the initiation rate is a function of physical features such as the number of available free ribosomes, the folding energy of the 5 0 untranslated regions (UTRs), the folding energy at the beginning of the coding sequence, the base pairing potential between the 5 0 UTR and the ribosomal rRNA, and the context of the START ATG [15][16][17][18][19]. A ribosome that occupies site i moves, with transition rate l i .…”

“…Thus, the RFM captures both the simple exclusion and totally asymmetric properties of the TASEP. The transition rates l i depend on various features of the transcript [18] (see also the Methods section in [15]). …”

Accurate Prediction of Cellular Co-Translational Folding Indicates Proteins can Switch from Post- to Co-Translational Folding

“…This assumption allows for the derivation of an analytical model 11,12 , but there is experimental evidence that ribosome dwell times are best described by the difference of two exponential terms 13 . We show below, however, that the predictions using either dwelltime distribution are highly similar.…”