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Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation

Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation
Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation
Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-g production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.
Langerhans Cells, Interferon Regulatory Factors, Petri nets, gene regulatory network
1-13
Polak, Marta
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Ung, Chuin Ying
d6acb9f2-661b-47a1-9c4c-6101e2be18a5
Masapust, Joanna
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Freeman, Tom C.
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Ardern-Jones, Michael
7ac43c24-94ab-4d19-ba69-afaa546bec90
Polak, Marta
e0ac5e1a-7074-4776-ba23-490bd4da612d
Ung, Chuin Ying
d6acb9f2-661b-47a1-9c4c-6101e2be18a5
Masapust, Joanna
840504fe-2f47-4f17-9e2b-b1d81c1a875b
Freeman, Tom C.
cc87674c-872c-4282-94d8-1a27bab90a2e
Ardern-Jones, Michael
7ac43c24-94ab-4d19-ba69-afaa546bec90

Polak, Marta, Ung, Chuin Ying, Masapust, Joanna, Freeman, Tom C. and Ardern-Jones, Michael (2017) Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation. Scientific Reports, 7, 1-13. (doi:10.1038/s41598-017-00651-5).

Record type: Article

Abstract

Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-g production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.

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Polak ME_Sci_Reps_2017 - Accepted Manuscript
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s41598-017-00651-5 - Version of Record
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More information

Accepted/In Press date: 8 March 2017
e-pub ahead of print date: 6 April 2017
Published date: 2017
Keywords: Langerhans Cells, Interferon Regulatory Factors, Petri nets, gene regulatory network
Organisations: Clinical & Experimental Sciences

Identifiers

Local EPrints ID: 410745
URI: https://eprints.soton.ac.uk/id/eprint/410745
PURE UUID: 22b2eb16-6db6-4c5d-b3c8-51b8aa167101

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Date deposited: 09 Jun 2017 09:33
Last modified: 10 Dec 2019 06:05

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Contributors

Author: Marta Polak
Author: Chuin Ying Ung
Author: Joanna Masapust
Author: Tom C. Freeman

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