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

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Michael A Ferrin ◽  
Arvind R Subramaniam

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.

2016 ◽  
Author(s):  
Michael Ferrin ◽  
Arvind R. Subramaniam

AbstractRibosomes can stall during translation elongation in bacteria and eukaryotes. To identify mechanisms by which ribosome stalling affects expression of the encoded protein, we develop an inverse approach that combines computational modeling with systematic perturbations of translation initiation rate, the number of stall sites, and the distance between stall sites on a reporter mRNA. By applying this approach to ribosome stalls caused by amino acid starvation in the bacteriumEscherichia coli, we find that 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. To account for this discrepancy, we consider a model in which collision from a trailing ribosome causes abortive termination of the stalled ribosome. This collision-stimulated abortive termination model provides a better fit to measured protein synthesis rates from our reporter library, and is consistent with observed ribosome densities near stall sites. Analysis of this model further predicts that ribosome collisions can selectively stimulate abortive termination of stalled ribosomes without fine-tuning of kinetic rate parameters. Thus ribosome collisions may serve as a robust timer for translational quality control pathways to recognize stalled ribosomes.


2014 ◽  
Vol 289 (41) ◽  
pp. 28160-28171 ◽  
Author(s):  
Steven J. Hersch ◽  
Sara Elgamal ◽  
Assaf Katz ◽  
Michael Ibba ◽  
William Wiley Navarre

1997 ◽  
Vol 17 (12) ◽  
pp. 1291-1302 ◽  
Author(s):  
Donald J. DeGracia ◽  
Jonathon M. Sullivan ◽  
Robert W. Neumar ◽  
Sarah S. Alousi ◽  
Katie R. Hikade ◽  
...  

Postischemic brain reperfusion is associated with a substantial and long-lasting reduction of protein synthesis in selectively vulnerable neurons. Because the overall translation initiation rate is typically regulated by altering the phosphorylation of serine 51 on the α-subunit of eukaryotic initiation factor 2 (eIF-2α), we used an antibody specific to phosphorylated eIF-2α [eIF-2(αP)] to study the regional and cellular distribution of eIF-2(αP) in normal, ischemic, and reperfused rat brains. Western blots of brain postmitochondrial supernatants revealed that ~1% of all eIF-2α is phosphorylated in controls, eIF-2(αP) is not reduced by up to 30 minutes of ischemia, and eIF-2(αP) is increased ~20-fold after 10 and 90 minutes of reperfusion. Immunohistochemistry shows localization of eIF-2(αP) to astrocytes in normal brains, a massive increase in eIF-2(αP) in the cytoplasm of neurons within the first 10 minutes of reperfusion, accumulation of eIF-2(αP) in the nuclei of selectively vulnerable neurons after 1 hour of reperfusion, and morphology suggesting pyknosis or apoptosis in neuronal nuclei that continue to display eIF-2(αP) after 4 hours of reperfusion. These observations, together with the fact that eIF-2(αP) inhibits translation initiation, make a compelling case that eIF-2(αP) is responsible for reperfusion-induced inhibition of protein synthesis in vulnerable neurons.


2019 ◽  
Vol 47 (20) ◽  
pp. 10477-10488 ◽  
Author(s):  
William D Baez ◽  
Bappaditya Roy ◽  
Zakkary A McNutt ◽  
Elan A Shatoff ◽  
Shicheng Chen ◽  
...  

Abstract In all cells, initiation of translation is tuned by intrinsic features of the mRNA. Here, we analyze translation in Flavobacterium johnsoniae, a representative of the Bacteroidetes. Members of this phylum naturally lack Shine–Dalgarno (SD) sequences in their mRNA, and yet their ribosomes retain the conserved anti-SD sequence. Translation initiation is tuned by mRNA secondary structure and by the identities of several key nucleotides upstream of the start codon. Positive determinants include adenine at position –3, reminiscent of the Kozak sequence of Eukarya. Comparative analysis of Escherichia coli reveals use of the same Kozak-like sequence to enhance initiation, suggesting an ancient and widespread mechanism. Elimination of contacts between A-3 and the conserved β-hairpin of ribosomal protein uS7 fails to diminish the contribution of A-3 to initiation, suggesting an indirect mode of recognition. Also, we find that, in the Bacteroidetes, the trinucleotide AUG is underrepresented in the vicinity of the start codon, which presumably helps compensate for the absence of SD sequences in these organisms.


2017 ◽  
Vol 199 (11) ◽  
Author(s):  
Shreya Ahana Ayyub ◽  
Divya Dobriyal ◽  
Umesh Varshney

ABSTRACT Initiation factor 3 (IF3) is one of the three conserved prokaryotic translation initiation factors essential for protein synthesis and cellular survival. Bacterial IF3 is composed of a conserved architecture of globular N- and C-terminal domains (NTD and CTD) joined by a linker region. IF3 is a ribosome antiassociation factor which also modulates selection of start codon and initiator tRNA. All the functions of IF3 have been attributed to its CTD by in vitro studies. However, the in vivo relevance of these findings has not been investigated. By generating complete and partial IF3 (infC) knockouts in Escherichia coli and by complementation analyses using various deletion constructs, we show that while the CTD is essential for E. coli survival, the NTD is not. Polysome profiles reaffirm that CTD alone can bind to the 30S ribosomal subunit and carry out the ribosome antiassociation function. Importantly, in the absence of the NTD, bacterial growth is compromised, indicating a role for the NTD in the fitness of cellular growth. Using reporter assays for in vivo initiation, we show that the NTD plays a crucial role in the fidelity function of IF3 by avoiding (i) initiation from non-AUG codons and (ii) initiation by initiator tRNAs lacking the three highly conserved consecutive GC pairs (in the anticodon stem) known to function in concert with IF3. IMPORTANCE Initiation factor 3 regulates the fidelity of eubacterial translation initiation by ensuring the formation of an initiation complex with an mRNA bearing a canonical start codon and with an initiator tRNA at the ribosomal P site. Additionally, IF3 prevents premature association of the 50S ribosomal subunit with the 30S preinitiation complex. The significance of our work in Escherichia coli is in demonstrating that while the C-terminal domain alone sustains E. coli for its growth, the N-terminal domain adds to the fidelity of initiation of protein synthesis and to the fitness of the bacterial growth.


2016 ◽  
Author(s):  
Ariel Hecht ◽  
Jeff Glasgow ◽  
Paul R. Jaschke ◽  
Lukmaan Bawazer ◽  
Matthew S. Munson ◽  
...  

ABSTRACTOur understanding of translation is one cornerstone of molecular biology that underpins our capacity to engineer living matter. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are typically considered as the “start codons” for translation initiation inEscherichia coli(E. coli). Translation is typically not thought to initiate from the 61 remaining codons. Here, we systematically quantified translation initiation inE. colifrom all 64 triplet codons. We detected protein synthesis above background initiating from at least 46 codons. Translation initiated from these non-canonical start codons at levels ranging from 0.01% to 2% relative to AUG. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems


2020 ◽  
Author(s):  
Nana Ding ◽  
Shenghu Zhou ◽  
Zhenqi Yuan ◽  
Xiaojuan Zhang ◽  
Jing Chen ◽  
...  

ABSTRACTCurrently, predictive translation tuning of regulatory elements to the desired output of transcription factor based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e., fold change in gene expression between the presence and absence of inducer) by adjusting the translation initiation rate of the transcription factor and reporter. However, existing genetically encoded biosensors generally suffer from unpredictable translation tuning of regulatory elements to dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation initiation rate, protein folding and dynamic range, and presented a rational design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). A library containing 24,000 semi-rationally designed cRBSs was constructed using DNA microarray, and was divided into five sub-libraries through fluorescence-activated cell sorting. To explore the relationship between cRBSs and dynamic range, we established a classification model with the cRBSs and average dynamic range of five sub-libraries to accurately predict the dynamic range of biosensors based on convolutional neural network in deep learning. Thus, this work provides a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.


FEBS Letters ◽  
2000 ◽  
Vol 468 (1) ◽  
pp. 73-78 ◽  
Author(s):  
Alessandra Andrè ◽  
Antimina Puca ◽  
Federica Sansone ◽  
Anna Brandi ◽  
Giovanni Antico ◽  
...  

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