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Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.

Deneke C, Lipowsky R, Valleriani A - PLoS ONE (2013)

Bottom Line: Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified.Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation.We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs.

View Article: PubMed Central - PubMed

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

ABSTRACT
Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.

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Average residual lifetime and residual protein synthesis capacity.(A) Average residual lifetime  as function of time , as defined in Eq. (20), after the interruption of transcription for MGS1 (red) and RPS16B mRNA (blue). Under steady state conditions, i.e., both have similar residual lifetimes. However, if transcription is stopped, the remaining mRNA population ages. The average residual lifetime of MGS1 mRNA still present in the cell at time  increases with  because only old mRNAs with a low degradation rate are still in the sample (see Fig. 4). In contrast, for RPS16B mRNA the average residual lifetime decreases. Only for exponentially distributed lifetimes (dashed lines) the average residual lifetime stays constant, which reflects the memoryless property of the exponential distribution; (B) Residual protein synthesis capacity  versus  as defined in Eq. (7). The capacity  is proportional to the amount of proteins that will be produced by an average mRNA from the sample. The residual protein synthesis capacity decays exponentially if the mRNA has an exponential lifetime distribution (dashed lines) but follows a different pattern if the process of degradation is more complex. The small differences between the exponential and the true decay patterns indicate that the non-exponential character of the lifetime distributions may be difficult to deduce from measurements of the residual protein synthesis capacity .
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pone-0055442-g006: Average residual lifetime and residual protein synthesis capacity.(A) Average residual lifetime as function of time , as defined in Eq. (20), after the interruption of transcription for MGS1 (red) and RPS16B mRNA (blue). Under steady state conditions, i.e., both have similar residual lifetimes. However, if transcription is stopped, the remaining mRNA population ages. The average residual lifetime of MGS1 mRNA still present in the cell at time increases with because only old mRNAs with a low degradation rate are still in the sample (see Fig. 4). In contrast, for RPS16B mRNA the average residual lifetime decreases. Only for exponentially distributed lifetimes (dashed lines) the average residual lifetime stays constant, which reflects the memoryless property of the exponential distribution; (B) Residual protein synthesis capacity versus as defined in Eq. (7). The capacity is proportional to the amount of proteins that will be produced by an average mRNA from the sample. The residual protein synthesis capacity decays exponentially if the mRNA has an exponential lifetime distribution (dashed lines) but follows a different pattern if the process of degradation is more complex. The small differences between the exponential and the true decay patterns indicate that the non-exponential character of the lifetime distributions may be difficult to deduce from measurements of the residual protein synthesis capacity .

Mentions: It was shown that the aging of mRNA affects both the polysomal size distributions [33], [34] and the rate of protein synthesis [35]. From the point of view of mRNA degradation, aging becomes manifest in the residual lifetime R of the molecule. The residual lifetime of a randomly chosen mRNA is the remaining time until it is degraded. The average residual lifetime in a sample of mRNA molecules can be easily computed both at the beginning of the experiment, corresponding to the steady state, and during the decay assays (see Models and methods). Fig. 6A shows the behavior of the average residual lifetime as a function of time after the interruption of transcription for the two mRNAs discussed in Fig. 3. One can clearly see that the average residual lifetime changes with time reflecting the aging of the mRNA population after the stop of transcription, which is a consequence of the non-constant degradation rate in Fig. 4. Because the remaining mRNAs are older, their average degradation rate has changed and, thus, the average residual lifetime can increase (MGS1) or decrease (RPS16B). Only the exponential fit shows no aging and a constant residual lifetime (dashed lines).


Complex degradation processes lead to non-exponential decay patterns and age-dependent decay rates of messenger RNA.

Deneke C, Lipowsky R, Valleriani A - PLoS ONE (2013)

Average residual lifetime and residual protein synthesis capacity.(A) Average residual lifetime  as function of time , as defined in Eq. (20), after the interruption of transcription for MGS1 (red) and RPS16B mRNA (blue). Under steady state conditions, i.e., both have similar residual lifetimes. However, if transcription is stopped, the remaining mRNA population ages. The average residual lifetime of MGS1 mRNA still present in the cell at time  increases with  because only old mRNAs with a low degradation rate are still in the sample (see Fig. 4). In contrast, for RPS16B mRNA the average residual lifetime decreases. Only for exponentially distributed lifetimes (dashed lines) the average residual lifetime stays constant, which reflects the memoryless property of the exponential distribution; (B) Residual protein synthesis capacity  versus  as defined in Eq. (7). The capacity  is proportional to the amount of proteins that will be produced by an average mRNA from the sample. The residual protein synthesis capacity decays exponentially if the mRNA has an exponential lifetime distribution (dashed lines) but follows a different pattern if the process of degradation is more complex. The small differences between the exponential and the true decay patterns indicate that the non-exponential character of the lifetime distributions may be difficult to deduce from measurements of the residual protein synthesis capacity .
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3569439&req=5

pone-0055442-g006: Average residual lifetime and residual protein synthesis capacity.(A) Average residual lifetime as function of time , as defined in Eq. (20), after the interruption of transcription for MGS1 (red) and RPS16B mRNA (blue). Under steady state conditions, i.e., both have similar residual lifetimes. However, if transcription is stopped, the remaining mRNA population ages. The average residual lifetime of MGS1 mRNA still present in the cell at time increases with because only old mRNAs with a low degradation rate are still in the sample (see Fig. 4). In contrast, for RPS16B mRNA the average residual lifetime decreases. Only for exponentially distributed lifetimes (dashed lines) the average residual lifetime stays constant, which reflects the memoryless property of the exponential distribution; (B) Residual protein synthesis capacity versus as defined in Eq. (7). The capacity is proportional to the amount of proteins that will be produced by an average mRNA from the sample. The residual protein synthesis capacity decays exponentially if the mRNA has an exponential lifetime distribution (dashed lines) but follows a different pattern if the process of degradation is more complex. The small differences between the exponential and the true decay patterns indicate that the non-exponential character of the lifetime distributions may be difficult to deduce from measurements of the residual protein synthesis capacity .
Mentions: It was shown that the aging of mRNA affects both the polysomal size distributions [33], [34] and the rate of protein synthesis [35]. From the point of view of mRNA degradation, aging becomes manifest in the residual lifetime R of the molecule. The residual lifetime of a randomly chosen mRNA is the remaining time until it is degraded. The average residual lifetime in a sample of mRNA molecules can be easily computed both at the beginning of the experiment, corresponding to the steady state, and during the decay assays (see Models and methods). Fig. 6A shows the behavior of the average residual lifetime as a function of time after the interruption of transcription for the two mRNAs discussed in Fig. 3. One can clearly see that the average residual lifetime changes with time reflecting the aging of the mRNA population after the stop of transcription, which is a consequence of the non-constant degradation rate in Fig. 4. Because the remaining mRNAs are older, their average degradation rate has changed and, thus, the average residual lifetime can increase (MGS1) or decrease (RPS16B). Only the exponential fit shows no aging and a constant residual lifetime (dashed lines).

Bottom Line: Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified.Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation.We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs.

View Article: PubMed Central - PubMed

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

ABSTRACT
Experimental studies on mRNA stability have established several, qualitatively distinct decay patterns for the amount of mRNA within the living cell. Furthermore, a variety of different and complex biochemical pathways for mRNA degradation have been identified. The central aim of this paper is to bring together both the experimental evidence about the decay patterns and the biochemical knowledge about the multi-step nature of mRNA degradation in a coherent mathematical theory. We first introduce a mathematical relationship between the mRNA decay pattern and the lifetime distribution of individual mRNA molecules. This relationship reveals that the mRNA decay patterns at steady state expression level must obey a general convexity condition, which applies to any degradation mechanism. Next, we develop a theory, formulated as a Markov chain model, that recapitulates some aspects of the multi-step nature of mRNA degradation. We apply our theory to experimental data for yeast and explicitly derive the lifetime distribution of the corresponding mRNAs. Thereby, we show how to extract single-molecule properties of an mRNA, such as the age-dependent decay rate and the residual lifetime. Finally, we analyze the decay patterns of the whole translatome of yeast cells and show that yeast mRNAs can be grouped into three broad classes that exhibit three distinct decay patterns. This paper provides both a method to accurately analyze non-exponential mRNA decay patterns and a tool to validate different models of degradation using decay data.

Show MeSH
Related in: MedlinePlus