Abstract
Recent studies have demonstrated how the competition for the finite pool of available gene expression factors has important effect on fundamental gene expression aspects. In this study, based on a whole-cell model simulation of translation in S. cerevisiae, we evaluate for the first time the expected effect of mRNA levels fluctuations on translation due to the finite pool of ribosomes. We show that fluctuations of a single gene or a group of genes mRNA levels induce periodic behavior in all S. cerevisiae translation factors and aspects: the ribosomal densities and the translation rates of all S. cerevisiae mRNAs oscillate. We numerically measure the oscillation amplitudes demonstrating that fluctuations of endogenous and heterologous genes can cause a significant fluctuation of up to 50% in the steady-state translation rates of the rest of the genes. Furthermore, we demonstrate by synonymous mutations that oscillating the levels of mRNAs that experience high ribosomal occupancy (e.g. ribosomal “traffic jam”) induces the largest impact on the translation of the S. cerevisiae genome.The results reported here should provide novel insights and principles related to the design of synthetic gene expression circuits and related to the evolutionary constraints shaping gene expression of endogenous genes.
Highlights
During the gene expression process various macromolecules (e.g. ribosomes, RNA polymerase (RNAP), transcription factors, elongation factors, spliceosome, transfer RNA molecules, etc.) process the genetic material (DNA, mRNA, pre-mRNA) in order to generate proteins [1]
Oscillatory behavior at the translation level induced by mRNA levels oscillations
Oscillatory behavior at the translation level induced by mRNA levels oscillations example, increased mRNA levels in one gene affects the translation levels of all other genes
Summary
During the gene expression process various macromolecules (e.g. ribosomes, RNA polymerase (RNAP), transcription factors, elongation factors, spliceosome, transfer RNA (tRNA) molecules, etc.) process the genetic material (DNA, mRNA, pre-mRNA) in order to generate proteins [1]. The number of gene expression macromolecules and factors in the cell is finite; for example, there are about 200,000 ribosomes and 30,000 RNAP-II molecules in the S. cerevisiae cell [2, 3]. This limited resource budget induces competition between the different molecules/regions encoding the genetic material, resulting in non-trivial correlations and couplings between the different gene expression stages, and between the processed genetic material molecules. [9] considered a stochastic model to analyze the competition of two types of mRNAs (two genes) for the limited ribosomal resource, where the total number of mRNAs and ribosomes fluctuate randomly. It was shown that the strength of the couplings (or cross-talk) between the translation of the two protein types strongly depends on whether the ribosomes are underloaded (i.e., there are more ribosomes than mRNAs) or overloaded (i.e., there are more mRNAs than ribosomes)
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