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Related Experiment Video

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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
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Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA

Jukka Intosalmi1, Helena Ahlfors2,3, Sini Rautio4

  • 1Department of Computer Science, Aalto University, Aalto, FI-00076, Finland. jukka.intosalmi@aalto.fi.

BMC Systems Biology
|November 19, 2015
PubMed
Summary

This study models T helper 17 (Th17) cell differentiation, revealing inhibitory transcription factor interactions and a novel link between TGF-β dosage and regulatory T cell master regulator expression.

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Area of Science:

  • Immunology
  • Systems Biology
  • Computational Biology

Background:

  • T helper 17 (Th17) cell differentiation is regulated by extracellular cytokines and transcription factors.
  • Mechanistic details of core Th17 regulatory networks remain incompletely understood.

Purpose of the Study:

  • To develop an integrative modeling framework for constructing a data-driven mechanistic model of the core Th17 regulatory network.

Main Methods:

  • Integrated modeling framework combining RNA sequencing data with mathematical modeling.
  • Data-driven construction of a mechanistic model for the Th17 regulatory network.

Main Results:

  • Identified inhibitory mechanisms between key transcription factors.
  • Discovered a novel dependency between transforming growth factor-beta (TGF-β) dosage and the expression of the master regulator for induced regulatory T cells.

Conclusions:

  • The developed framework provides mechanistic insights into Th17 cell differentiation.
  • Experimental validation confirmed the TGF-β dosage dependency in Th17 polarizing conditions.