This model is described in the article:
Abstract:
CD4+ T cells orchestrate the adaptive immune response in vertebrates. While both experimental and modeling work has been conducted to understand the molecular genetic mechanisms involved in CD4+ T cell responses and fate attainment, the dynamic role of intrinsic (produced by CD4+ T lymphocytes) versus extrinsic (produced by other cells) components remains unclear, and the mechanistic and dynamic understanding of the plastic responses of these cells remains incomplete. In this work, we studied a regulatory network for the core transcription factors involved in CD4+ T cell-fate attainment. We first show that this core is not sufficient to recover common CD4+ T phenotypes. We thus postulate a minimal Boolean regulatory network model derived from a larger and more comprehensive network that is based on experimental data. The minimal network integrates transcriptional regulation, signaling pathways and the micro-environment. This network model recovers reported configurations of most of the characterized cell types (Th0, Th1, Th2, Th17, Tfh, Th9, iTreg, and Foxp3-independent T regulatory cells). This transcriptional-signaling regulatory network is robust and recovers mutant configurations that have been reported experimentally. Additionally, this model recovers many of the plasticity patterns documented for different T CD4+ cell types, as summarized in a cell-fate map. We tested the effects of various micro-environments and transient perturbations on such transitions among CD4+ T cell types. Interestingly, most cell-fate transitions were induced by transient activations, with the opposite behavior associated with transient inhibitions. Finally, we used a novel methodology was used to establish that T-bet, TGF-? and suppressors of cytokine signaling proteins are keys to recovering observed CD4+ T cell plastic responses. In conclusion, the observed CD4+ T cell-types and transition patterns emerge from the feedback between the intrinsic or intracellular regulatory core and the micro-environment. We discuss the broader use of this approach for other plastic systems and possible therapeutic interventions.
This model is hosted on BioModels Database and identified by: BIOMD0000000593.
To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.
-
A Minimal Regulatory Network of Extrinsic and Intrinsic Factors Recovers Observed Patterns of CD4+ T Cell Differentiation and Plasticity.
- Mariana Esther Martinez-Sanchez, Luis Mendoza, Carlos Villarreal, Elena R Alvarez-Buylla
- PLoS computational biology , 6/ 2015 , Volume 11 , Issue 6 , pages: e1004324 , PubMed ID: 26090929
- Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, México Distrito Federal, México; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, México Distrito Federal, México.
- CD4+ T cells orchestrate the adaptive immune response in vertebrates. While both experimental and modeling work has been conducted to understand the molecular genetic mechanisms involved in CD4+ T cell responses and fate attainment, the dynamic role of intrinsic (produced by CD4+ T lymphocytes) versus extrinsic (produced by other cells) components remains unclear, and the mechanistic and dynamic understanding of the plastic responses of these cells remains incomplete. In this work, we studied a regulatory network for the core transcription factors involved in CD4+ T cell-fate attainment. We first show that this core is not sufficient to recover common CD4+ T phenotypes. We thus postulate a minimal Boolean regulatory network model derived from a larger and more comprehensive network that is based on experimental data. The minimal network integrates transcriptional regulation, signaling pathways and the micro-environment. This network model recovers reported configurations of most of the characterized cell types (Th0, Th1, Th2, Th17, Tfh, Th9, iTreg, and Foxp3-independent T regulatory cells). This transcriptional-signaling regulatory network is robust and recovers mutant configurations that have been reported experimentally. Additionally, this model recovers many of the plasticity patterns documented for different T CD4+ cell types, as summarized in a cell-fate map. We tested the effects of various micro-environments and transient perturbations on such transitions among CD4+ T cell types. Interestingly, most cell-fate transitions were induced by transient activations, with the opposite behavior associated with transient inhibitions. Finally, we used a novel methodology was used to establish that T-bet, TGF-β and suppressors of cytokine signaling proteins are keys to recovering observed CD4+ T cell plastic responses. In conclusion, the observed CD4+ T cell-types and transition patterns emerge from the feedback between the intrinsic or intracellular regulatory core and the micro-environment. We discuss the broader use of this approach for other plastic systems and possible therapeutic interventions.
Submitter of this revision: administrator
Curator: Lucian Smith
Modellers: administrator, Mariana Martinez-Sanchez
Metadata information
is1,
isDescribedBy (1 statement)
isDescribedBy1,
hasTaxon (1 statement)
hasTaxon1,
isVersionOf (1 statement)
isVersionOf1,
hasProperty (1 statement)
hasProperty1,
is,isDescribedBy,hasTaxon,isVersionOf,hasProperty
Connected external resources
OmicsDI Impact Metrics
Name | Description | Size | Actions |
---|---|---|---|
Model files (1) |
|||
BIOMD0000000593_url.xml | SBML L3V1 representation of Martinez-Sanchez2015 - T CD4+ lymphocyte transcriptional-signaling regulatory network | 49.40 KB | Preview | Download |
Additional files (10) |
|||
BIOMD0000000593-biopax2.owl | Auto-generated BioPAX (Level 2) | 3.25 KB | Preview | Download |
BIOMD0000000593-biopax3.owl | Auto-generated BioPAX (Level 3) | 3.34 KB | Preview | Download |
BIOMD0000000593.m | Auto-generated Octave file | 2.14 KB | Preview | Download |
BIOMD0000000593.pdf | Auto-generated PDF file | 104.37 KB | Preview | Download |
BIOMD0000000593.png | Auto-generated Reaction graph (PNG) | 5.04 KB | Preview | Download |
BIOMD0000000593.sci | Auto-generated Scilab file | 380.00 Bytes | Preview | Download |
BIOMD0000000593.svg | Auto-generated Reaction graph (SVG) | 851.00 Bytes | Preview | Download |
BIOMD0000000593.vcml | Auto-generated VCML file | 950.00 Bytes | Preview | Download |
BIOMD0000000593.xpp | Auto-generated XPP file | 674.00 Bytes | Preview | Download |
BIOMD0000000593_urn.xml | Auto-generated SBML file with URNs | 49.34 KB | Preview | Download |
- Model originally submitted by : Mariana Martinez-Sanchez
- Submitted: Nov 17, 2014 5:57:31 PM
- Last Modified: Aug 21, 2024 11:27:47 PM
Revisions
-
Version: 4
- Submitted on: Aug 21, 2024 11:27:47 PM
- Submitted by: Lucian Smith
- With comment: CRBM-sponsored manual and automated updates.
-
Version: 3
- Submitted on: Oct 4, 2017 3:14:33 PM
- Submitted by: administrator
- With comment: When reproducing the data in the paper has discussion with author.
Ally Hume:
This model should correspond to figure 2A of the paper. The model has 10 nodes but only 5 are shown in the paper. I assume you wanted to keep the diagram simple in the paper. Are you happy with this difference?
When I ran the model (in GinSIM) to find the attractors and it shows 9 steady states but the paper (fig 2B) only show 5. Is this OK? I assume you only showed the relevant attractors in the paper? The steady states in the paper are all in the above result.
Author reply:
Yes, we only included part of the network and the attractors for simplicity. The result you obtain is correct.
-
Version: 2
- Submitted on: Apr 19, 2016 10:28:58 PM
- Submitted by: Mariana Martinez-Sanchez
- With comment: Current version of Martinez-Sanchez2015 - T CD4+ lymphocyte transcriptional-signaling regulatory network
-
Version: 1
- Submitted on: Nov 17, 2014 5:57:31 PM
- Submitted by: Mariana Martinez-Sanchez
- With comment: Original import of BIOMD0000000593.xml.origin
(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions of this model will only be shown to the submitter and their collaborators.
(added: 08 Mar 2016, 15:35:22, updated: 08 Mar 2016, 15:35:22)