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Review
. 2014 Jul 29:2:31.
doi: 10.3389/fcell.2014.00031. eCollection 2014.

Computational modeling of heterogeneity and function of CD4+ T cells

Adria Carbo  1 , Raquel Hontecillas  1 , Tricity Andrew  1 , Kristin Eden  1 , Yongguo Mei  1 , Stefan Hoops  2 , Josep Bassaganya-Riera  3
Affiliations
Review

Computational modeling of heterogeneity and function of CD4+ T cells

Adria Carbo et al. Front Cell Dev Biol. .

Abstract

The immune system is composed of many different cell types and hundreds of intersecting molecular pathways and signals. This large biological complexity requires coordination between distinct pro-inflammatory and regulatory cell subsets to respond to infection while maintaining tissue homeostasis. CD4+ T cells play a central role in orchestrating immune responses and in maintaining a balance between pro- and anti- inflammatory responses. This tight balance between regulatory and effector reactions depends on the ability of CD4+ T cells to modulate distinct pathways within large molecular networks, since dysregulated CD4+ T cell responses may result in chronic inflammatory and autoimmune diseases. The CD4+ T cell differentiation process comprises an intricate interplay between cytokines, their receptors, adaptor molecules, signaling cascades and transcription factors that help delineate cell fate and function. Computational modeling can help to describe, simulate, analyze, and predict some of the behaviors in this complicated differentiation network. This review provides a comprehensive overview of existing computational immunology methods as well as novel strategies used to model immune responses with a particular focus on CD4+ T cell differentiation.

Keywords: CD4+ T cell differentiation; CD4+ T cell dogma; computational immunology; computational modeling; immunoinformatics.

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Figures

Figure 1
Figure 1
Main intracellular differentiation pathways of a single CD4+ T cell. Systems Biology Markup Language (SBML)-compliant network model of CD4+ T cell differentiation, including cytokines, receptors, and intracellular signaling pathways controlling CD4+ T cell fate and function.
Figure 2
Figure 2
Heterogeneity of CD4+ T cell subsets. T helper type 1 (Th1), type 2 (Th2), type 17 (Th17), type 9 (Th9) and type 22 (Th22), Follicular T helper cells (Tfh), and induced regulatory T cells (iTreg) as well as type 1 regulatory T cells (Tr1) are induced based on multiple cytokines being produced by dendritic cells and macrophages among other immune subsets.
Figure 3
Figure 3
Multiscale modeling of CD4+ T cell differentiation. The CD4+ T cell differentiation process comprises (A) different spatiotemporal parameters (milliseconds to hours and nanometers to centimeters) as well as (B) different scales (intracellular, difussion gradient, cellular, and tissue-level scale).
See this image and copyright information in PMC

References

    1. Abraham C., Cho J. H. (2009). Inflammatory bowel disease. N. Engl. J. Med. 361, 2066–2078. 10.1056/NEJMra0804647 - DOI - PMC - PubMed
    1. Ahern P. P., Schiering C., Buonocore S., McGeachy M. J., Cua D. J., Maloy K. J., et al. . (2010). Interleukin-23 drives intestinal inflammation through direct activity on T cells. Immunity 33, 279–288. 10.1016/j.immuni.2010.08.010 - DOI - PMC - PubMed
    1. Ansel K. M., McHeyzer-Williams L. J., Ngo V. N., McHeyzer-Williams M. G., Cyster J. G. (1999). In vivo-activated CD4 T cells upregulate CXC chemokine receptor 5 and reprogram their response to lymphoid chemokines. J. Exp. Med. 190, 1123–1134. 10.1084/jem.190.8.1123 - DOI - PMC - PubMed
    1. Arababadi M. K., Nosratabadi R., Hassanshahi G., Yaghini N., Pooladvand V., Shamsizadeh A., et al. . (2010). Nephropathic complication of type-2 diabetes is following pattern of autoimmune diseases? Diabetes Res. Clin. Pract. 87, 33–37. 10.1016/j.diabres.2009.09.027 - DOI - PubMed
    1. Basu R., Hatton R. D., Weaver C. T. (2013). The Th17 family: flexibility follows function. Immunol. Rev. 252, 89–103. 10.1111/imr.12035 - DOI - PMC - PubMed