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A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes

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  • Andrea Riba
  • Carla Bosia
  • Mariama El Baroudi
  • Laura Ollino
  • Michele Caselle

Abstract

It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called “sponge effect”). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells.Author Summary: Gene expression is controlled by a complex network of regulatory interactions which may be organized in two complementary subnetworks: the transcriptional one, mediated by Transcription Factors (TF), and the post-transcriptional one, in which a central role is played by microRNAs. In this paper we add a further step in the study of synergistic role of these layers of regulation: a stable fine tuning of the relative expression of target genes is obtained by a combination of transcriptional and post-transcriptional interactions, and such a combination ensures robustness against stochastic fluctuations. We show that optimal fine tuning is reached when the microRNA plays the role of master regulator and one of its targets is a TF which regulates the other microRNA targets. This combination defines a new class of feed-forward loops. We show that such circuitries are strongly enriched when the TF and its targets have to be precisely kept at the same concentration notwithstanding the environmental noise. We complete our analysis with a detailed description, using both deterministic and stochastic equations, of the steady state concentrations of the genes involved in the motifs as a function of the miRNA concentration and of the miRNA-target interaction strength.

Suggested Citation

  • Andrea Riba & Carla Bosia & Mariama El Baroudi & Laura Ollino & Michele Caselle, 2014. "A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-12, February.
    • Handle: RePEc:plo:pcbi00:1003490
    DOI: 10.1371/journal.pcbi.1003490
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    1. Carla Bosia & Andrea Pagnani & Riccardo Zecchina, 2013. "Modelling Competing Endogenous RNA Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-13, June.
    2. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
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    1. Jae Kyoung Kim & Eduardo D Sontag, 2017. "Reduction of multiscale stochastic biochemical reaction networks using exact moment derivation," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-24, June.

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