Model checking to assess T-helper cell plasticity.

Wassim Abou-Jaoudé,Aurélien Naldi,Denis Thieffry,Claudine Chaouiya,Maximilien Grandclaudon,Pedro T Monteiro,Vassili Soumelis

doi:10.3389/fbioe.2014.00086

Abstract

Computational modeling constitutes a crucial step toward the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g., stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity. In this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models. We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions. As a case study, we consider the cellular network regulating the differentiation of T-helper (Th) cells, which orchestrate many physiological and pathological immune responses. To account for novel cellular subtypes, we present an extended version of a published model of Th cell differentiation. We then use symbolic model checking to analyze reachability properties between Th subtypes upon changes of environmental cues. This allows for the construction of a synthetic view of Th cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions. Finally, we explore novel strategies enabling specific Th cell polarizing or reprograming events.

Highlights

Cellular signaling pathways and regulatory circuits are progressively deciphered, with a recent acceleration allowed by the development of powerful high-throughput experimental approaches
Considering logical models of large cellular regulatory networks, we have focused on model checking to explore induced dynamical properties
Asynchronous dynamics of logical models integrating signaling pathways with transcriptional networks can be readily translated into explicit or implicit Kripke structures, and thereby become amenable to standard or action-restricted model checking. We have applied this approach to the analysis of a logical model for a comprehensive signaling/regulatory network controlling Th cell differentiation, which encompasses 101 components and 221 regulatory interactions

Summary

INTRODUCTION

Cellular signaling pathways and regulatory circuits are progressively deciphered, with a recent acceleration allowed by the development of powerful high-throughput experimental approaches. The capacity of cells to change their asymptotic behaviors depending on environmental cues is referred to as cell plasticity [see e.g., O’Shea and Paul (2010)] In this manuscript, we present a methodology to assess cell plasticity, relying on the logical formalism assets and recent computational methods, including model checking techniques. We compute all reprograming events between Th subtypes under specific documented polarizing cytokine environments, providing a global and synthetic representation of Th plasticity in response to these environmental cues This analysis leads to the prediction of Th-subtypes conversions, which will need to be assessed experimentally.

MATERIALS AND METHODS

APPLICATION

CONCLUSION AND PROSPECTS