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Stochastic sequence-level model of coupled transcription and translation in prokaryotes.

Mäkelä J, Lloyd-Price J, Yli-Harja O, Ribeiro AS - BMC Bioinformatics (2011)

Bottom Line: Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels.For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels.Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.

ABSTRACT

Background: In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation and alternative pathways to elongation, namely pausing, arrests, editing, pyrophosphorolysis, RNA polymerase traffic, and premature termination. Stepwise translation can start after the ribosome binding site is formed and accounts for variable codon translation rates, ribosome traffic, back-translocation, drop-off, and trans-translation.

Results: First, we show that the model accurately matches measurements of sequence-dependent translation elongation dynamics. Next, we characterize the degree of coupling between fluctuations in RNA and protein levels, and its dependence on the rates of transcription and translation initiation. Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels.

Conclusions: For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels. Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.

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Noise in mRNA as a function of the transcription initiation rate. Noise (CV2) in mRNA levels for varying effective transcription initiation rates. The mRNA degradation rate is set so that the mean mRNA levels at steady state are identical in all cases.
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Figure 4: Noise in mRNA as a function of the transcription initiation rate. Noise (CV2) in mRNA levels for varying effective transcription initiation rates. The mRNA degradation rate is set so that the mean mRNA levels at steady state are identical in all cases.

Mentions: In Figure 4, we first show the CV2 of mRNA time series for varying keff. Noise decreases as keff increases due to the promoter open complex formation step [6]. Without this event, the distribution of time intervals between transcription initiation events would be exponential, and the CV2 would not vary. However, with this step, if the expected time for an RNAp to bind to the free promoter is faster than the duration of the promoter open complex formation, then the distribution of time intervals becomes Gaussian-like [6].


Stochastic sequence-level model of coupled transcription and translation in prokaryotes.

Mäkelä J, Lloyd-Price J, Yli-Harja O, Ribeiro AS - BMC Bioinformatics (2011)

Noise in mRNA as a function of the transcription initiation rate. Noise (CV2) in mRNA levels for varying effective transcription initiation rates. The mRNA degradation rate is set so that the mean mRNA levels at steady state are identical in all cases.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3113936&req=5

Figure 4: Noise in mRNA as a function of the transcription initiation rate. Noise (CV2) in mRNA levels for varying effective transcription initiation rates. The mRNA degradation rate is set so that the mean mRNA levels at steady state are identical in all cases.
Mentions: In Figure 4, we first show the CV2 of mRNA time series for varying keff. Noise decreases as keff increases due to the promoter open complex formation step [6]. Without this event, the distribution of time intervals between transcription initiation events would be exponential, and the CV2 would not vary. However, with this step, if the expected time for an RNAp to bind to the free promoter is faster than the duration of the promoter open complex formation, then the distribution of time intervals becomes Gaussian-like [6].

Bottom Line: Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels.For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels.Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.

ABSTRACT

Background: In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation and alternative pathways to elongation, namely pausing, arrests, editing, pyrophosphorolysis, RNA polymerase traffic, and premature termination. Stepwise translation can start after the ribosome binding site is formed and accounts for variable codon translation rates, ribosome traffic, back-translocation, drop-off, and trans-translation.

Results: First, we show that the model accurately matches measurements of sequence-dependent translation elongation dynamics. Next, we characterize the degree of coupling between fluctuations in RNA and protein levels, and its dependence on the rates of transcription and translation initiation. Finally, modeling sequence-specific transcriptional pauses, we find that these affect protein noise levels.

Conclusions: For parameter values within realistic intervals, transcription and translation are found to be tightly coupled in Escherichia coli, as the noise in protein levels is mostly determined by the underlying noise in RNA levels. Sequence-dependent events in transcription elongation, e.g. pauses, are found to cause tangible effects in the degree of fluctuations in protein levels.

Show MeSH
Related in: MedlinePlus