Cacace2020 - Logical model of the regulatory network controlling T cell commitment

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Model Identifier
MODEL2002170001
Short description
Boolean approaches and extensions thereof are becoming increasingly popular to model signaling and regulatory networks, including those controlling cell differentiation, pattern formation and embryonic development. Here, we describe a logical modeling framework relying on three steps: the delineation of a regulatory graph, the specification of multilevel components, and the encoding of Boolean rules specifying the behavior of model components depending on the levels or activities of their regulators. Referring to a non-deterministic, asynchronous updating scheme, we present several complementary methods and tools enabling the computation of stable activity patterns, the verification of the reachability of such patterns, as well as the generation of mean temporal evolution curves and the computation of the probabilities to reach distinct activity patterns. We apply this logical framework to the regulatory network controlling T lymphocyte specification. This process involves cross-regulations between specific T cell regulatory factors and factors driving alternative differentiation pathways, which remain accessible during the early steps of thymocyte development. Many transcription factors needed for T cell specification are required in other hematopoietic differentiation pathways and are combined in a fine-tuned, time-dependent fashion to achieve T cell commitment. Using the software GINsim, we integrated current knowledge into a dynamical model, which recapitulates the main developmental steps from early progenitors entering the thymus up to T cell commitment, as well as the impact of various documented environmental and genetic perturbations. Our model analysis further enabled the identification of several knowledge gaps. The model, software and whole analysis workflow are provided in computer-readable and executable form to ensure reproducibility and ease extensions.
Format
SBML (L3V1)
Related Publication
  • Logical modeling of cell fate specification-Application to T cell commitment.
  • Cacace E, Collombet S, Thieffry D
  • Current topics in developmental biology , 1/ 2020 , Volume 139 , pages: 205-238 , PubMed ID: 32450961
  • European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
  • Boolean approaches and extensions thereof are becoming increasingly popular to model signaling and regulatory networks, including those controlling cell differentiation, pattern formation and embryonic development. Here, we describe a logical modeling framework relying on three steps: the delineation of a regulatory graph, the specification of multilevel components, and the encoding of Boolean rules specifying the behavior of model components depending on the levels or activities of their regulators. Referring to a non-deterministic, asynchronous updating scheme, we present several complementary methods and tools enabling the computation of stable activity patterns, the verification of the reachability of such patterns, as well as the generation of mean temporal evolution curves and the computation of the probabilities to reach distinct activity patterns. We apply this logical framework to the regulatory network controlling T lymphocyte specification. This process involves cross-regulations between specific T cell regulatory factors and factors driving alternative differentiation pathways, which remain accessible during the early steps of thymocyte development. Many transcription factors needed for T cell specification are required in other hematopoietic differentiation pathways and are combined in a fine-tuned, time-dependent fashion to achieve T cell commitment. Using the software GINsim, we integrated current knowledge into a dynamical model, which recapitulates the main developmental steps from early progenitors entering the thymus up to T cell commitment, as well as the impact of various documented environmental and genetic perturbations. Our model analysis further enabled the identification of several knowledge gaps. The model, software and whole analysis workflow are provided in computer-readable and executable form to ensure reproducibility and ease extensions.
Contributors
Denis Thieffry, Kausthubh Ramachandran

Metadata information

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hasProperty
Mathematical Modelling Ontology Logical model

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Non-curated

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Model files

Cacace_TdevModel_2nov2020.sbml Logical model of the regulatory network controlling T cell commitment (SBML L3VI qual). 240.89 KB Preview | Download

  • Model originally submitted by : Denis Thieffry
  • Submitted: 06-Apr-2021 14:56:12
  • Last Modified: 06-Apr-2021 14:56:12
Revisions
  • Version: 4 public model Download this version
    • Submitted on: 06-Apr-2021 14:56:12
    • Submitted by: Kausthubh Ramachandran
    • With comment: Updated submission name and short description as per the BioModels submission guidelines
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