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Deducing the kinetics of protein synthesis in vivo from the transition rates measured in vitro.

Rudorf S, Thommen M, Rodnina MV, Lipowsky R - PLoS Comput. Biol. (2014)

Bottom Line: In all cases, we find good agreement between theory and experiment without adjusting any fit parameter.The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA.The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

View Article: PubMed Central - PubMed

Affiliation: Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.

ABSTRACT
The molecular machinery of life relies on complex multistep processes that involve numerous individual transitions, such as molecular association and dissociation steps, chemical reactions, and mechanical movements. The corresponding transition rates can be typically measured in vitro but not in vivo. Here, we develop a general method to deduce the in-vivo rates from their in-vitro values. The method has two basic components. First, we introduce the kinetic distance, a new concept by which we can quantitatively compare the kinetics of a multistep process in different environments. The kinetic distance depends logarithmically on the transition rates and can be interpreted in terms of the underlying free energy barriers. Second, we minimize the kinetic distance between the in-vitro and the in-vivo process, imposing the constraint that the deduced rates reproduce a known global property such as the overall in-vivo speed. In order to demonstrate the predictive power of our method, we apply it to protein synthesis by ribosomes, a key process of gene expression. We describe the latter process by a codon-specific Markov model with three reaction pathways, corresponding to the initial binding of cognate, near-cognate, and non-cognate tRNA, for which we determine all individual transition rates in vitro. We then predict the in-vivo rates by the constrained minimization procedure and validate these rates by three independent sets of in-vivo data, obtained for codon-dependent translation speeds, codon-specific translation dynamics, and missense error frequencies. In all cases, we find good agreement between theory and experiment without adjusting any fit parameter. The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA. The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

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Quantitative comparison between the in-vitro kinetics of translation elongation at 37°C and the in-vivo kinetics as deduced for the growth condition of 2.5 dbl/h.(A) Single barrier shifts  for the individual transition rates, see Eq. 2 and Fig. 2; and (B) Scale factors  for all individual transitions of the ribosomes. A barrier shift  implies that the in-vivo rate  is increased compared to the in-vitro rate .
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pcbi-1003909-g005: Quantitative comparison between the in-vitro kinetics of translation elongation at 37°C and the in-vivo kinetics as deduced for the growth condition of 2.5 dbl/h.(A) Single barrier shifts for the individual transition rates, see Eq. 2 and Fig. 2; and (B) Scale factors for all individual transitions of the ribosomes. A barrier shift implies that the in-vivo rate is increased compared to the in-vitro rate .

Mentions: Because the in-vivo experiments are typically performed at 37°C, we use the in-vitro values for the same temperature, see Table 1. Furthermore, we take into account the known in-vivo values of the overall elongation rate at different growth conditions [26], [27]. For each growth condition, the constraint in Eq. 8 now has the explicit form as given by Eq. 23 in the Methods section. As a result of the constrained minimization procedure, we find the in-vivo rates as given in Table 2 and the single barrier shifts displayed in Fig. 5A, where we have again omitted the subscript ‘min’ for notational simplicity.


Deducing the kinetics of protein synthesis in vivo from the transition rates measured in vitro.

Rudorf S, Thommen M, Rodnina MV, Lipowsky R - PLoS Comput. Biol. (2014)

Quantitative comparison between the in-vitro kinetics of translation elongation at 37°C and the in-vivo kinetics as deduced for the growth condition of 2.5 dbl/h.(A) Single barrier shifts  for the individual transition rates, see Eq. 2 and Fig. 2; and (B) Scale factors  for all individual transitions of the ribosomes. A barrier shift  implies that the in-vivo rate  is increased compared to the in-vitro rate .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4214572&req=5

pcbi-1003909-g005: Quantitative comparison between the in-vitro kinetics of translation elongation at 37°C and the in-vivo kinetics as deduced for the growth condition of 2.5 dbl/h.(A) Single barrier shifts for the individual transition rates, see Eq. 2 and Fig. 2; and (B) Scale factors for all individual transitions of the ribosomes. A barrier shift implies that the in-vivo rate is increased compared to the in-vitro rate .
Mentions: Because the in-vivo experiments are typically performed at 37°C, we use the in-vitro values for the same temperature, see Table 1. Furthermore, we take into account the known in-vivo values of the overall elongation rate at different growth conditions [26], [27]. For each growth condition, the constraint in Eq. 8 now has the explicit form as given by Eq. 23 in the Methods section. As a result of the constrained minimization procedure, we find the in-vivo rates as given in Table 2 and the single barrier shifts displayed in Fig. 5A, where we have again omitted the subscript ‘min’ for notational simplicity.

Bottom Line: In all cases, we find good agreement between theory and experiment without adjusting any fit parameter.The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA.The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

View Article: PubMed Central - PubMed

Affiliation: Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.

ABSTRACT
The molecular machinery of life relies on complex multistep processes that involve numerous individual transitions, such as molecular association and dissociation steps, chemical reactions, and mechanical movements. The corresponding transition rates can be typically measured in vitro but not in vivo. Here, we develop a general method to deduce the in-vivo rates from their in-vitro values. The method has two basic components. First, we introduce the kinetic distance, a new concept by which we can quantitatively compare the kinetics of a multistep process in different environments. The kinetic distance depends logarithmically on the transition rates and can be interpreted in terms of the underlying free energy barriers. Second, we minimize the kinetic distance between the in-vitro and the in-vivo process, imposing the constraint that the deduced rates reproduce a known global property such as the overall in-vivo speed. In order to demonstrate the predictive power of our method, we apply it to protein synthesis by ribosomes, a key process of gene expression. We describe the latter process by a codon-specific Markov model with three reaction pathways, corresponding to the initial binding of cognate, near-cognate, and non-cognate tRNA, for which we determine all individual transition rates in vitro. We then predict the in-vivo rates by the constrained minimization procedure and validate these rates by three independent sets of in-vivo data, obtained for codon-dependent translation speeds, codon-specific translation dynamics, and missense error frequencies. In all cases, we find good agreement between theory and experiment without adjusting any fit parameter. The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA. The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

Show MeSH
Related in: MedlinePlus