Li2021-MicroRNAs noncanonical feedback model

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Model Identifier
MODEL2301180001
Short description
(I am not the first author of the paper who contributed to the experimental data, I did the modeling) Bistable switches and oscillators have long been considered key mechanisms underlying cell fate decisions and pattern formation in biology. Previous studies of these dynamical behaviors focused on regulatory networks with intuitive feedback loops. It was therefore unclear whether other common biochemical reactions can act as bistable switches or oscillators crucial for cellular and physiological dynamics. In this work, we used mass-action-based models to show that elementary production, degradation and binding reactions involving as few as two RNA species (e.g.an mRNA and a microRNA) can generate bistability and oscillation. We showed that both bistability and oscillation depend on cooperativity of two microRNA binding sites on the mRNA. We therefore termed our model the two-site mRNA-microRNA (MMI2) model. Remarkably, the network structure of the MMI2 model does not have any explicit feedback loop. We estimated that this simple reaction network is applicable to nearly half of human protein-coding genes. Using in vitro and in vivo experiments, we showed the function of a newly proposed MMI2-based switch in governing motor neuron lineage segregation in the spinal cord of mammalian embryos. Our findings reveal a previously underappreciated post-transcriptional mechanism that may have widespread functions in cell fate decisions, oscillatory cell dynamics and tissue patterning. Furthermore, our results challenge the long-standing idea of using intuitive feedback loops to explain bistability and oscillation. In addition to its significance in biology, the MMI2 model enables nontrivial mathematical analysis due to its simplicity. Using algebraic geometry and chemical reaction network theory, we obtained key conditions for bistability of the MMI2 model. These conditions include an inequality that reveals to a hidden feedback loop arising from regulated degradation. For these reasons, we expect that our model will not only provide useful insights into a wide range of problems in cell and developmental biology, but also enable new analytical approaches in systems biology and mathematical biology.
Format
SBML (L3V1)
Related Publication
  • MicroRNA governs bistable cell differentiation and lineage segregation via a noncanonical feedback.
  • Li CJ, Liau ES, Lee YH, Huang YZ, Liu Z, Willems A, Garside V, McGlinn E, Chen JA, Hong T
  • Molecular systems biology , 4/ 2021 , Volume 17 , Issue 4 , pages: e9945 , PubMed ID: 33890404
  • Molecular and Cell Biology, Taiwan International Graduate Program, Academia Sinica and Graduate Institute of Life Science, National Defense Medical Center, Taipei, Taiwan.
  • Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription-driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA-mRNA reaction circuits that differ from known feedback loop-like structures. Strikingly, we show that a wide range of biologically plausible post-transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA-mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning.
Contributors
Submitter of the first revision: Ziyi Liu
Submitter of this revision: Ziyi Liu
Modellers: Ziyi Liu

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Non-curated


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Model files

MMI2_bistability_ocillation_4v.xml SBML representation of Elementary RNA-based model 27.29 KB Preview | Download

Additional files

RNA based model abstract.docx abstract of the model 13.45 KB Preview | Download
mmi2_bistability_oscillation_4v.jl Julia representation of Elementary RNA-based model 2.45 KB Preview | Download
mmi2_bistability_oscillation_v4.py Py representation of Elementary RNA-based model 1.43 KB Preview | Download

  • Model originally submitted by : Ziyi Liu
  • Submitted: Jan 18, 2023 4:53:37 AM
  • Last Modified: Jan 18, 2023 4:53:37 AM
Revisions
  • Version: 1 public model Download this version
    • Submitted on: Jan 18, 2023 4:53:37 AM
    • Submitted by: Ziyi Liu
    • With comment: Import of Li2021-MicroRNAs noncanonical feedback model