Global and local depletion of ternary complex limits translational elongation

Zhang, Gong; Fedyunin, Ivan; Miekley, Oskar; Valleriani, Angelo; Moura, Arnaldo Vieira; Ignatova, Zoya

doi:10.1093/nar/gkq196

Cited by 77 publications

(95 citation statements)

References 53 publications

(89 reference statements)

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“…Due to this phenomenon the BTD, which we obtain analytically from the model, deviates from a pure exponential, consistently with the findings in Ref. [24]. Besides, this model asymptotically reaches a nonequilibrium steady state (NESS).…”

Section: Introductionsupporting

confidence: 89%

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Nonequilibrium stochastic model for tRNA binding time statistics

Caniparoli

Lombardo

2014

Phys. Rev. E

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Protein translation is one of the most important processes in cell life, but despite being well-understood biochemically, the implications of its intrinsic stochastic nature have not been fully elucidated. In this paper we develop a microscopic and stochastic model which describes a crucial step in protein translation, namely the binding of the tRNA to the ribosome. Our model explicitly takes into consideration tRNA recharging dynamics, spatial inhomogeneity, and stochastic fluctuations in the number of charged tRNAs around the ribosome. By analyzing this nonequilibrium system we are able to derive the statistical distribution of the times needed by the tRNAs to bind to the ribosome, and to show that it deviates from an exponential due to the coupling between the fluctuations of charged and uncharged populations of tRNA.

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Section: Introductionsupporting

confidence: 89%

“…This fundamental step heavily depends on the conditions in the cell, and, in particular, on the concentration of charged tRNAs around the ribosome [7,22,24]. We consider the recharge dynamics and the diffusion of the tRNA molecules by assuming that each tRNA can be either charged with the relative amino acid, or uncharged.…”

Section: Discussionmentioning

confidence: 99%

Nonequilibrium stochastic model for tRNA binding time statistics

Caniparoli

Lombardo

2014

Phys. Rev. E

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“…Our earlier work shows that pathological expansion of the CAG repeats (Ͼ35 consecutive CAG codons) in huntingtin (Htt) exon 1, implicated in Huntington disease, involves stochastic Ϫ1 frameshifting within the CAG stretch that is triggered by limitation of the charged cognate glutaminyl-tRNA Gln CUG, although uncharged tRNA Gln CUG is plentiful (5). This is conceptually similar to the frameshifting characterized earlier at tandem rare codons in Escherichia coli that is caused by cognate tRNA depletion (11,12). In partial contrast, for the stochastic Ϫ1 frameshifting in decoding the expanded CAG run in the SCA3 gene associated with spinocerebellar ataxia type 3, an mRNA structure formed by the CAG repeats has been proposed as a major stimulatory component of the Ϫ1 frameshifting.…”

mentioning

confidence: 74%

An Expanded CAG Repeat in Huntingtin Causes +1 Frameshifting

Saffert

Adamla

Schieweck

et al. 2016

Journal of Biological Chemistry

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Maintenance of triplet decoding is crucial for the expression of functional protein because deviations either into the ؊1 or ؉1 reading frames are often non-functional. We report here that expression of huntingtin (Htt) exon 1 with expanded CAG repeats, implicated in Huntington pathology, undergoes a sporadic ؉1 frameshift to generate from the CAG repeat a transframe AGC repeat-encoded product. This ؉1 recoding is exclusively detected in pathological Htt variants, i.e. those with expanded repeats with more than 35 consecutive CAG codons. An atypical ؉1 shift site, UUC C at the 5 end of CAG repeats, which has some resemblance to the influenza A virus shift site, triggers the ؉1 frameshifting and is enhanced by the increased propensity of the expanded CAG repeats to form a stem-loop structure. The ؉1 trans-frame-encoded product can directly influence the aggregation of the parental Htt exon 1.

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“…Each of the three main stages of gene translation, namely initiation, elongation, and termination, can be broken down to the multifarious steps comprising them, see, for example, Zhang et al . (51). …”

Section: Introductionmentioning

confidence: 99%

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

2016

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mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.

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Global and local depletion of ternary complex limits translational elongation

Cited by 77 publications

References 53 publications

Nonequilibrium stochastic model for tRNA binding time statistics

Nonequilibrium stochastic model for tRNA binding time statistics

An Expanded CAG Repeat in Huntingtin Causes +1 Frameshifting

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

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