In eukaryotic cells, many genes are transcribed into non-coding RNAs. Small RNAs or, more specifically, microRNAs (miRNAs) form an abundant sub-class of such RNAs. miRNAs are transcribed as long noncoding RNA and then generated via a processing pathway down to the 20–24-nucleotide length. The key ability of miRNAs is to associate with target mRNAs and to suppress their translation and/or facilitate degradation. Using the mean-field kinetic equations and Monte Carlo simulations, we analyze two aspects of this interplay. First, we describe the situation when the formation of mRNA or miRNA is periodically modulated by a transcription factor which itself is not perturbed by these species. Depending on the ratio between the mRNA and miRNA formation rates, the corresponding induced periodic kinetics are shown to be either nearly harmonic or shaped as anti-phase pulses. The second part of the work is related to recent experimental studies indicating that differentiation of stem cells often involves changes in gene transcription into miRNAs and/or the interference between miRNAs, mRNAs and proteins. In particular, the regulatory protein obtained via mRNA translation may suppress the miRNA formation, and the latter may suppress in turn the miRNA-mRNA association and degradation. The corresponding bistable kinetics are described in detail.
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Recent direct observations of localization of mRNAs and proteins both in prokaryotic and eukaryotic cells can be related to slowdown of diffusion of these species due to macromolecular crowding and their ability to aggregate and form immobile or slowly mobile complexes. Here, a generic kinetic model describing both these factors is presented and comprehensively analyzed. Although the model is non-linear, an accurate self-consistent analytical solution of the corresponding reaction-diffusion equation has been constructed, the types of localized protein distributions have been explicitly shown, and the predicted kinetic regimes of gene expression have been classified.
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Recent experiments show that mRNAs and proteins can be localized both in prokaryotic and eukaryotic cells. To describe such situations, I present a 3D mean-field kinetic model aimed primarily at gene expression in prokaryotic cells, including the formation of mRNA, its translation into protein, and slow diffusion of these species. Under steady-state conditions, the mRNA and protein spatial distribution is described by simple exponential functions. The protein concentration near the gene transcribed into mRNA is shown to depend on the protein and mRNA diffusion coefficients and degradation rate constants.
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Recent experiments indicate that several viruses may encode microRNAs (miRNAs) in cells. Such RNAs may interfere with the host mRNAs and proteins. We present a kinetic analysis of this interplay. In our treatment, the viral miRNA is considered to be able to associate with the host mRNA with subsequent degradation. This process may result in a decline of the mRNA population and also in a decline of the population of the protein encoded by this mRNA. With these ingredients, we first show the types of the corresponding steady-state kinetics in the cases of positive and negative regulation of the miRNA synthesis by the protein. In addition, we scrutinize the situation when the protein regulates the virion replication or, in other words, provides a feedback for the replication. For the negative feedback, the replication rate is found to increase with increasing the intracellular virion population. For the positive feedback, the replication rate first increases and then drops. These features may determine the stability of steady states.
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In eukaryotic cells, protein-coding sequences constitute a relatively small part of the genome. The rest of the genome is transcribed to non-coding RNAs (ncRNAs). Such RNAs form the cornerstone of a regulatory network that operates in parallel with the protein network. Their biological functions are based primarily on the ability to pair with and deactivate target messenger RNAs (mRNAs). To clarify the likely role of ncRNAs in complex genetic networks, we present and comprehensively analyze a kinetic model of one of the key counterparts of the network architectures. Specifically, the genes transcribed to ncRNAs are considered to interplay with a hierarchical two-layer set of genes transcribed to mRNAs. The genes forming the bottom layer are regulated from the top and negatively self-regulated. If the former regulation is positive, the dependence of the RNA populations on the governing parameters is found to be often non-monotonous. Specifically, the model predicts bistability. If the regulation is negative, the dependence of the RNA populations on the governing parameters is monotonous. In particular, the population of the mRNAs, corresponding to the genes forming the bottom layer, is nearly constant.
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