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A plausible identifiable model of the canonical NF-κB signaling pathway

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  • Joanna Jaruszewicz-Błońska
  • Ilona Kosiuk
  • Wiktor Prus
  • Tomasz Lipniacki

Abstract

An overwhelming majority of mathematical models of regulatory pathways, including the intensively studied NF-κB pathway, remains non-identifiable, meaning that their parameters may not be determined by existing data. The existing NF-κB models that are capable of reproducing experimental data contain non-identifiable parameters, whereas simplified models with a smaller number of parameters exhibit dynamics that differs from that observed in experiments. Here, we reduced an existing model of the canonical NF-κB pathway by decreasing the number of equations from 15 to 6. The reduced model retains two negative feedback loops mediated by IκBα and A20, and in response to both tonic and pulsatile TNF stimulation exhibits dynamics that closely follow that of the original model. We carried out the sensitivity-based linear analysis and Monte Carlo-based analysis to demonstrate that the resulting model is both structurally and practically identifiable given measurements of 5 model variables from a simple TNF stimulation protocol. The reduced model is capable of reproducing different types of responses that are characteristic to regulatory motifs controlled by negative feedback loops: nearly-perfect adaptation as well as damped and sustained oscillations. It can serve as a building block of more comprehensive models of the immune response and cancer, where NF-κB plays a decisive role. Our approach, although may not be automatically generalized, suggests that models of other regulatory pathways can be transformed to identifiable, while retaining their dynamical features.

Suggested Citation

  • Joanna Jaruszewicz-Błońska & Ilona Kosiuk & Wiktor Prus & Tomasz Lipniacki, 2023. "A plausible identifiable model of the canonical NF-κB signaling pathway," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-26, June.
  • Handle: RePEc:plo:pone00:0286416
    DOI: 10.1371/journal.pone.0286416
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    References listed on IDEAS

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    1. repec:plo:pone00:0027755 is not listed on IDEAS
    2. D Joubert & J D Stigter & J Molenaar, 2018. "Determining minimal output sets that ensure structural identifiability," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-19, November.
    3. Sanjana Gupta & Robin E C Lee & James R Faeder, 2020. "Parallel Tempering with Lasso for model reduction in systems biology," PLOS Computational Biology, Public Library of Science, vol. 16(3), pages 1-22, March.
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