Ribosome kinetics and aa-tRNA competition determine rate and fidelity of peptide synthesis

Fluitt, Aaron M.; Pienaar, Elsje; Viljoen, Hendrik J.

doi:10.1016/j.compbiolchem.2007.07.003

Cited by 134 publications

(239 citation statements)

References 21 publications

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“…To calculate τ A,i , the mean time of translation of the ith codon in the mRNA sequence, we used the method of Viljoen and colleagues (12), which estimates τ A,i as a function of the codon identity, and the in vivo concentration of cognate, near-cognate, and noncognate tRNA molecules (SI Methods). This method accounts for competitive binding of cognate and noncognate tRNA molecules for a codon and accurately predicts the average translation rate of various proteins measured in vivo.…”

Section: Methodsmentioning

confidence: 99%

“…Synonymous codon mutations alter the mRNA sequence but leave the translated protein sequence unaltered. Synonymous codons can also change the translation rate, which can itself directly affect the extent of cotranslational folding (7,8,12). Thus, altering the mRNA sequence such that the slowest translating synonymous mutation is present at each codon has the potential to minimize kinetic effects by decreasing the τF;i τ A;iþ1 ratio.…”

Section: Synonymous Codon Mutations Can Significantly Decrease Kinetimentioning

confidence: 99%

“…We focus on this organism because it is unicellular, which avoids issues of proteome variation among different cell types. E. coli has also been extensively characterized in terms of its genome and proteome, and the concentrations of ribosome and tRNA molecules present at different growth rates have been measured (11), allowing predictive models for τ A,i to be developed (12). We focus on the E. coli proteins that are synthesized and remain in the cytosol because this strategy avoids the need to consider additional processes, such as cotranslational protein translocation through translocons (13), that would complicate our approach to modeling and analysis.…”

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confidence: 99%

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In vivo translation rates can substantially delay the cotranslational folding of the Escherichia coli cytosolic proteome

Ciryam

Morimoto

Vendruscolo

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

125

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A question of fundamental importance concerning protein folding in vivo is whether the kinetics of translation or the thermodynamics of the ribosome nascent chain (RNC) complex is the major determinant of cotranslational folding behavior. This is because translation rates can reduce the probability of cotranslational folding below that associated with arrested ribosomes, whose behavior is determined by the equilibrium thermodynamics of the RNC complex. Here, we combine a chemical kinetic equation with genomic and proteomic data to predict domain folding probabilities as a function of nascent chain length for Escherichia coli cytosolic proteins synthesized on both arrested and continuously translating ribosomes. Our results indicate that, at in vivo translation rates, about one-third of the Escherichia coli cytosolic proteins exhibit cotranslational folding, with at least one domain in each of these proteins folding into its stable native structure before the fulllength protein is released from the ribosome. The majority of these cotranslational folding domains are influenced by translation kinetics which reduces their probability of cotranslational folding and consequently increases the nascent chain length at which they fold into their native structures. For about 20% of all cytosolic proteins this delay in folding can exceed the length of the completely synthesized protein, causing one or more of their domains to switch from co-to posttranslational folding solely as a result of the in vivo translation rates. These kinetic effects arise from the difference in time scales of folding and amino-acid addition, and they represent a source of metastability in Escherichia coli's proteome.

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Section: Methodsmentioning

confidence: 99%

Section: Synonymous Codon Mutations Can Significantly Decrease Kinetimentioning

confidence: 99%

mentioning

confidence: 99%

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In vivo translation rates can substantially delay the cotranslational folding of the Escherichia coli cytosolic proteome

Ciryam

Morimoto

Vendruscolo

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

125

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“…The model is agent-based representing explicitly every single mRNA and ribosome. The latter bind to individual transcripts following first order kinetics and then perform a directed random walk with transition rates calculated following the Gromadski-Rodnina model (Gromadski and Rodnina, 2004;Fluitt et al, 2007). Upon termination ribosomes may re-initiate at the same transcript or unbind into the cell volume to rebind to a randomly chosen transcript at a later time again.…”

Section: Simulation Modelmentioning

confidence: 99%

“…The central element of the model is that cognate aa-tRNA species compete with near matches (the so-called near-cognate aa-tRNA) for access to the ribosome. The latter are thought to occupy the ribosomal Asite for significant amounts of time before eventually unbinding; while bound they prevent access for the cognate aa-tRNA (Fluitt et al, 2007) thus causing a delay.…”

Section: Introductionmentioning

confidence: 99%

Charting the dynamics of translation

2014

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a b s t r a c tCodon usage bias (CUB) is the well-known phenomenon that the frequency of synonymous codons is unequal. This is presumably the result of adaptive pressures favouring some codons over others. The underlying reason for this pressure is unknown, although a large number of possible driver mechanisms have been proposed. According to one hypothesis, the decoding time could be such a driver. A tacit assumption of this hypothesis is that faster codons lead to a higher translation rate which in turn is more resource efficient. While it is generally assumed that there is such a link, there are no rigorous studies to establish under which conditions the link between translation speed and rate actually exists. Using a computational simulation model and explicitly calculated codon decoding times, this contribution maps the entire range of dynamical regimes of translation. These simulations make it possible to understand precisely under which conditions translation speed and rate are linked.

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