Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Intosalmi, Jukka; Ahlfors, Helena; Rautio, Sini; Mannerstöm, Henrik; Chen, Zhi; Lahesmaa, Riitta; Stockinger, Brigitta; Lähdesmäki, Harri
• Is Part Of: BMC systems biology. Volume 9:Issue 1(2015)
• Page Start: 1
• Page End: 12
• Publication Date: 2015-12
• Subjects: T cell differentiation -- T helper 17 cell -- Sequencing data -- Mathematical modeling -- Statistical modeling -- Computational statistics; Biological systems -- Periodicals; Biology -- Research -- Periodicals; Cell physiology -- Periodicals; Genes -- Analysis -- Periodicals; 571
• DOI: 10.1186/s12918-015-0223-6
• Languages: English
• ISSNs: 1752-0509

Abstract

Abstract Background The differentiation of naive CD 4+ helper T (Th) cells into effector Th17 cells is steered by extracellular cytokines that activate and control the lineage specific transcriptional program. While the inducing cytokine signals and core transcription factors driving the differentiation towards Th17 lineage are well known, detailed mechanistic interactions between the key components are poorly understood. Results We develop an integrative modeling framework which combines RNA sequencing data with mathematical modeling and enables us to construct a mechanistic model for the core Th17 regulatory network in a data-driven manner. Conclusions Our results show significant evidence, for instance, for inhibitory mechanisms between the transcription factors and reveal a previously unknown dependency between the dosage of the inducing cytokine TGFβ and the expression of the master regulator of competing (induced) regulatory T cell lineage. Further, our experimental validation approves this dependency in Th17 polarizing conditions.