Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites

Abstract

The ribosome’s interactions with mRNA govern its translation rate and the effects of post-transcriptional regulation. Long, structured 5′ untranslated regions (5′ UTRs) are commonly found in bacterial mRNAs, though the physical mechanisms that determine how the ribosome binds these upstream regions remain poorly defined. Here, we systematically investigate the ribosome’s interactions with structured standby sites, upstream of Shine–Dalgarno sequences, and show that these interactions can modulate translation initiation rates by over 100-fold. We find that an mRNA’s translation initiation rate is controlled by the amount of single-stranded surface area, the partial unfolding of RNA structures to minimize the ribosome’s binding free energy penalty, the absence of cooperative binding and the potential for ribosomal sliding. We develop a biophysical model employing thermodynamic first principles and a four-parameter free energy model to accurately predict the ribosome’s translation initiation rates for 136 synthetic 5′ UTRs with large structures, diverse shapes and multiple standby site modules. The model predicts and experiments confirm that the ribosome can readily bind distant standby site modules that support high translation rates, providing a physical mechanism for observed context effects and long-range post-transcriptional regulation.

Design criteria for synthetic riboswitches acting on transcription

“…As secondary structure elements in the region upstream of the ribosomal binding site can interfere with the efficiency of translation (see refs. [29][30] ), it is very likely that a similar effect due to the highly stable structure of the T8 terminator is the reason for the observed reduced reporter gene expression in this construct. The last non-functional riboswitch RS8D4bp is also not fulfilling both criteria.…”

Efficient Search, Mapping, and Optimization of Multi-protein Genetic Systems in Diverse Bacteria

“…In that regard, our computational design approach is seamlessly augmented by an improved understanding of translation initiation (Borujeni et al, 2013) and the development of new mechanistic models that use sequence information to predict changes in DNA bending and looping, transcription factor and nucleosome binding, transcription initiation and elongation rate, transcriptional termination efficiency, RNA folding and stability, polarity, translation elongation and coupling, regulation by cis-and trans-RNAs, and other interactions that affect protein expression levels (Geggier & Vologodskii, 2010;Rhodius & Mutalik, 2010;Brewster et al, 2012;Johnson et al, 2012;Chen et al, 2013;Kilpinen et al, 2013;Rodrigo et al, 2013). The integration of models, to relate sequence to expression and expression to activity, should be a central goal of synthetic biology as it will expand our ability to navigate a genetic system's behavior space, and to optimize entire synthetic genomes to achieve a desired sensing, signaling, and metabolic performance.…”

“…However, the presence of long, highly structured 5 0 UTRs can further alter the translation initiation rate of a protein-coding sequence by manipulating its DG standby . The ribosome's rules for binding to long, highly structured 5 0 UTRs has been characterized (Espah Borujeni et al, 2014) and will be incorporated into a future version of the RBS Calculator (v2.0).…”

“…These relationships, called sequence-expression-activity maps (SEAMAPs), can be formulated by combining sequencedependent models predicting changes in protein expression levels (Rhodius & Mutalik, 2010;Salis, 2011;Brewster et al, 2012;Johnson et al, 2012;Borujeni et al, 2013;Kilpinen et al, 2013) with systemlevel models describing genetic system function (Fendt et al, 2010;Sneppen et al, 2010;Hyeon & Thirumalai, 2011;Wessely et al, 2011;Smallbone et al, 2013). Several types of models can be combined, utilizing thermodynamics, kinetics, mass transfer, and dynamical systems theory, to describe the multi-scale physical interactions affecting system function (Hyeon & Thirumalai, 2011).…”

Improvement of DNA minicircle production by optimization of the secondary structure of the 5′-UTR of ParA resolvase

“…c Predicted structures of the original and optimized parA transcripts encompassing the 5′-UTR (27 nt) and the first 50 nt. Rectangular boxes correspond to the AUG or UUG start codons (dashed) and to the Shine-Dalgarno sequence (solid line) the change in Gibbs free energy upon assembly, ΔG total , using an equation that accounts for five molecular interactions (Salis et al 2009;Borujeni et al 2013):…”